Medix-AI/coqui-tts
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coqui-tts
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coqui-tts/notebooks/TacotronPlayGround.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2\n",
"import os\n",
"import sys\n",
"import io\n",
"import torch \n",
"import time\n",
"import numpy as np\n",
"from collections import OrderedDict\n",
"\n",
"%pylab inline\n",
"rcParams[\"figure.figsize\"] = (16,5)\n",
"sys.path.append('/home/erogol/projects/')\n",
"\n",
"import librosa\n",
"import librosa.display\n",
"\n",
"from TTS.models.tacotron import Tacotron \n",
"from TTS.layers import *\n",
"from TTS.utils.data import *\n",
"from TTS.utils.audio import AudioProcessor\n",
"from TTS.utils.generic_utils import load_config\n",
"from TTS.utils.text import text_to_sequence\n",
"\n",
"import IPython\n",
"from IPython.display import Audio\n",
"from utils import *"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def tts(model, text, CONFIG, use_cuda, ap, figures=True):\n",
" t_1 = time.time()\n",
" waveform, alignment, spectrogram = create_speech(model, text, CONFIG, use_cuda, ap) \n",
" print(\" > Run-time: {}\".format(time.time() - t_1))\n",
" if figures: \n",
" visualize(alignment, spectrogram, CONFIG) \n",
" IPython.display.display(Audio(waveform, rate=CONFIG.sample_rate)) \n",
" return alignment, spectrogram"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Set constants\n",
"ROOT_PATH = '../result/February-13-2018_01:04AM/'\n",
"MODEL_PATH = ROOT_PATH + '/best_model.pth.tar'\n",
"CONFIG_PATH = ROOT_PATH + '/config.json'\n",
"OUT_FOLDER = ROOT_PATH + '/test/'\n",
"CONFIG = load_config(CONFIG_PATH)\n",
"use_cuda = False"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" | > Embedding dim : 149\n"
]
},
{
"ename": "KeyError",
"evalue": "'unexpected key \"module.embedding.weight\" in state_dict'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-5-994bc6f7ae61>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0;31m# load the model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload_state_dict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcp\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'model'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 26\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0muse_cuda\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/miniconda3/envs/pytorch/lib/python3.6/site-packages/torch/nn/modules/module.py\u001b[0m in \u001b[0;36mload_state_dict\u001b[0;34m(self, state_dict, strict)\u001b[0m\n\u001b[1;32m 488\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mstrict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 489\u001b[0m raise KeyError('unexpected key \"{}\" in state_dict'\n\u001b[0;32m--> 490\u001b[0;31m .format(name))\n\u001b[0m\u001b[1;32m 491\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mstrict\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 492\u001b[0m \u001b[0mmissing\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mown_state\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate_dict\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'unexpected key \"module.embedding.weight\" in state_dict'"
]
}
],
"source": [
"# load the model\n",
"model = Tacotron(CONFIG.embedding_size, CONFIG.hidden_size,\n",
" CONFIG.num_mels, CONFIG.num_freq, CONFIG.r)\n",
"\n",
"# load the audio processor\n",
"ap = AudioProcessor(CONFIG.sample_rate, CONFIG.num_mels, CONFIG.min_level_db,\n",
" CONFIG.frame_shift_ms, CONFIG.frame_length_ms, CONFIG.preemphasis,\n",
" CONFIG.ref_level_db, CONFIG.num_freq, CONFIG.power, griffin_lim_iters=80) \n",
"\n",
"\n",
"# load model state\n",
"if use_cuda:\n",
" cp = torch.load(MODEL_PATH)\n",
"else:\n",
" cp = torch.load(MODEL_PATH, map_location=lambda storage, loc: storage)\n",
"\n",
"# # small trick to remove DataParallel wrapper\n",
"new_state_dict = OrderedDict()\n",
"for k, v in cp['model'].items():\n",
" name = k[7:] # remove `module.`\n",
" new_state_dict[name] = v\n",
"cp['model'] = new_state_dict\n",
"\n",
"# load the model\n",
"model.load_state_dict(cp['model'])\n",
"if use_cuda:\n",
" model.cuda()\n",
"model.eval()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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" ('module.encoder.cbhg.conv1d_banks.0.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -6.6251e-02\n",
" -6.8183e-01\n",
" -8.8998e-01\n",
" ⋮ \n",
" -7.3685e-02\n",
" -1.7196e-01\n",
" -6.8184e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" -3.6669e-02\n",
" 1.0216e-01\n",
" 2.9180e-01\n",
" ⋮ \n",
" -4.3819e-01\n",
" 1.1236e-02\n",
" -8.6161e-02\n",
" \n",
" ( 2 ,.,.) = \n",
" 3.1580e-02\n",
" -4.6436e-02\n",
" -3.1578e-02\n",
" ⋮ \n",
" -2.9636e-01\n",
" -3.1398e-01\n",
" -9.8746e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -4.8537e-02\n",
" -9.7628e-01\n",
" -4.7115e-02\n",
" ⋮ \n",
" 3.7837e-02\n",
" -2.5917e-01\n",
" -4.0414e-01\n",
" \n",
" (126,.,.) = \n",
" -1.0193e-01\n",
" 4.4068e-01\n",
" -5.4034e-01\n",
" ⋮ \n",
" -1.7104e-01\n",
" -2.3850e-01\n",
" -1.6505e-01\n",
" \n",
" (127,.,.) = \n",
" 2.5536e-02\n",
" -9.0031e-01\n",
" -7.3607e-01\n",
" ⋮ \n",
" -3.3190e-01\n",
" -7.5025e-03\n",
" -1.0425e-01\n",
" [torch.FloatTensor of size 128x128x1]),\n",
" ('module.encoder.cbhg.conv1d_banks.0.bn.weight', \n",
" 0.6591\n",
" -1.2572\n",
" 0.8739\n",
" 0.0423\n",
" -0.8999\n",
" 0.4206\n",
" 1.2460\n",
" -1.7693\n",
" 1.1016\n",
" 0.3619\n",
" -1.5488\n",
" -0.4151\n",
" 0.0202\n",
" -1.1553\n",
" 0.6241\n",
" -0.7603\n",
" 0.1831\n",
" -1.3233\n",
" -1.1399\n",
" 0.2576\n",
" 0.3289\n",
" 0.1837\n",
" -0.3407\n",
" 0.3372\n",
" -0.7382\n",
" 0.3482\n",
" 0.3916\n",
" 0.6138\n",
" -0.0488\n",
" -1.7011\n",
" 0.5796\n",
" 0.2722\n",
" -0.4631\n",
" 0.0869\n",
" -1.8734\n",
" 0.7504\n",
" -0.4008\n",
" -0.0150\n",
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" 0.1789\n",
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" 0.4261\n",
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" 1.7856\n",
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" 1.7832\n",
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" -1.5547\n",
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" 0.2358\n",
" -0.7742\n",
" 0.1305\n",
" -0.0683\n",
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" -0.8753\n",
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" -0.0851\n",
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" 1.2336\n",
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" 1.9755\n",
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" -0.1720\n",
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" -0.9210\n",
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" 0.8603\n",
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" 0.5001\n",
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" -0.9646\n",
" 0.0032\n",
" 0.0372\n",
" 1.2075\n",
" 0.9911\n",
" 0.2357\n",
" 0.8908\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.0.bn.bias', \n",
" 0.0496\n",
" -0.3761\n",
" 0.1720\n",
" 0.0088\n",
" -0.1417\n",
" 0.0287\n",
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" -0.3297\n",
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" 0.1521\n",
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" -0.2840\n",
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" 0.0796\n",
" 0.1045\n",
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" 0.0719\n",
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" 0.0499\n",
" 0.0884\n",
" 0.2548\n",
" -0.0211\n",
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" 0.1719\n",
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" -0.3729\n",
" 0.2631\n",
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" 0.2012\n",
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" -0.3361\n",
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" 0.0690\n",
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" 0.0471\n",
" -0.2774\n",
" 0.0282\n",
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" 0.1838\n",
" -0.3682\n",
" -0.2745\n",
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" 0.0966\n",
" 0.0550\n",
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" 0.2190\n",
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" 0.0363\n",
" -0.3328\n",
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" -0.4342\n",
" -0.0747\n",
" 0.1348\n",
" 0.2771\n",
" 0.0020\n",
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" 0.2828\n",
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" -0.0237\n",
" 0.1105\n",
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" -0.0307\n",
" -0.1974\n",
" -0.0047\n",
" 0.0069\n",
" 0.1067\n",
" 0.2567\n",
" -0.0471\n",
" 0.2444\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.0.bn.running_mean', \n",
" 0.0870\n",
" 0.8101\n",
" 0.5247\n",
" 2.2122\n",
" 0.4873\n",
" 0.0197\n",
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" 1.0392\n",
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" 4.5341\n",
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" 0.0551\n",
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" 1.6102\n",
" 0.1971\n",
" 2.0502\n",
" 0.1030\n",
" 0.0089\n",
" 0.0028\n",
" 2.7830\n",
" 0.3154\n",
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" 3.0063\n",
" 2.0216\n",
" 0.5201\n",
" 0.1247\n",
" 0.2195\n",
" 0.3367\n",
" 0.2375\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.0.bn.running_var', \n",
" 0.3437\n",
" 3.1590\n",
" 3.5308\n",
" 16.8469\n",
" 3.0804\n",
" 0.0273\n",
" 0.2468\n",
" 31.7647\n",
" 1.4386\n",
" 0.9426\n",
" 6.6400\n",
" 3.8405\n",
" 9.8438\n",
" 50.8472\n",
" 4.1808\n",
" 21.3124\n",
" 0.5102\n",
" 9.6467\n",
" 1.7094\n",
" 2.8162\n",
" 0.1607\n",
" 2.5650\n",
" 5.6620\n",
" 1.3423\n",
" 10.7854\n",
" 0.3705\n",
" 0.0262\n",
" 0.0040\n",
" 16.0253\n",
" 1.5826\n",
" 2.8785\n",
" 0.0123\n",
" 7.1599\n",
" 0.4248\n",
" 1.3036\n",
" 3.5653\n",
" 5.6428\n",
" 11.3821\n",
" 1.8151\n",
" 6.7774\n",
" 0.0608\n",
" 3.9251\n",
" 0.9103\n",
" 0.3961\n",
" 0.1327\n",
" 2.1445\n",
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" 5.4538\n",
" 25.3652\n",
" 0.0586\n",
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" 2.1219\n",
" 0.9367\n",
" 6.9949\n",
" 3.4362\n",
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" 3.5132\n",
" 0.9837\n",
" 0.8066\n",
" 0.2909\n",
" 3.5503\n",
" 22.5505\n",
" 0.1241\n",
" 0.4674\n",
" 1.4275\n",
" 8.2066\n",
" 2.8071\n",
" 0.3559\n",
" 0.2892\n",
" 18.5240\n",
" 3.1646\n",
" 1.0415\n",
" 0.0045\n",
" 0.3100\n",
" 2.6372\n",
" 3.3976\n",
" 0.2980\n",
" 8.8771\n",
" 0.4361\n",
" 3.1446\n",
" 12.0329\n",
" 5.2685\n",
" 8.6919\n",
" 0.3742\n",
" 15.9113\n",
" 3.2323\n",
" 3.6449\n",
" 2.1727\n",
" 2.5035\n",
" 5.6634\n",
" 5.1186\n",
" 0.7378\n",
" 10.0247\n",
" 1.0395\n",
" 33.3002\n",
" 3.8079\n",
" 0.0013\n",
" 14.0447\n",
" 3.7312\n",
" 10.0017\n",
" 6.9413\n",
" 6.1180\n",
" 0.1488\n",
" 3.0287\n",
" 11.6265\n",
" 6.9702\n",
" 3.3300\n",
" 0.1468\n",
" 7.1564\n",
" 0.0031\n",
" 14.6520\n",
" 18.4089\n",
" 12.1343\n",
" 0.4487\n",
" 2.2629\n",
" 9.2180\n",
" 5.7901\n",
" 7.2934\n",
" 18.6814\n",
" 0.0180\n",
" 14.8378\n",
" 14.6351\n",
" 8.0705\n",
" 2.4461\n",
" 0.8510\n",
" 1.0535\n",
" 1.1406\n",
" 0.7860\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.1.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -1.7469e-03 -5.8269e-02\n",
" 6.7772e-02 -8.3827e-01\n",
" -1.9679e+00 3.3696e-01\n",
" ⋮ \n",
" -6.3320e-01 -4.1194e-01\n",
" -6.1837e-01 -4.3298e-01\n",
" 1.2093e-01 -2.6532e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -7.0265e-02 -4.4727e-02\n",
" -1.3089e-02 1.0594e-01\n",
" -1.4405e-01 3.7635e-01\n",
" ⋮ \n",
" 3.0504e-01 5.5851e-02\n",
" 3.3968e-01 -7.2954e-03\n",
" 5.3568e-02 1.9476e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 1.2149e-02 -6.5031e-02\n",
" -1.1192e-02 2.0588e-02\n",
" -9.9884e-02 2.7532e-01\n",
" ⋮ \n",
" 2.2661e-01 -1.4156e-01\n",
" 1.0049e-01 3.1395e-03\n",
" 7.0527e-02 -2.9458e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -4.5840e-02 -3.6793e-02\n",
" 1.6884e-01 -4.0931e-01\n",
" 2.5989e-01 2.7923e-01\n",
" ⋮ \n",
" -2.6109e-01 -3.3987e-01\n",
" 1.5648e-01 -6.1283e-02\n",
" -5.4954e-01 -1.1350e-01\n",
" \n",
" (126,.,.) = \n",
" -6.2937e-02 4.4589e-02\n",
" -6.2535e-02 -5.3324e-01\n",
" 2.1476e-01 -3.5696e-01\n",
" ⋮ \n",
" 2.1135e-01 -5.8720e-01\n",
" -1.0717e-01 -4.9246e-02\n",
" 2.3508e-01 -8.5545e-03\n",
" \n",
" (127,.,.) = \n",
" 1.0879e-01 -3.1740e-02\n",
" 4.4000e-03 -1.4642e+00\n",
" 3.1502e-01 2.8231e-01\n",
" ⋮ \n",
" -7.7851e-01 5.1266e-02\n",
" -1.2681e-03 -2.2417e-01\n",
" -2.1902e-01 -3.5927e-01\n",
" [torch.FloatTensor of size 128x128x2]),\n",
" ('module.encoder.cbhg.conv1d_banks.1.bn.weight', \n",
" 0.4733\n",
" 0.0235\n",
" -0.0062\n",
" 0.4201\n",
" 1.3014\n",
" 0.1988\n",
" -0.0900\n",
" 1.3110\n",
" 0.3646\n",
" 0.4270\n",
" -1.1778\n",
" 0.7919\n",
" 0.1093\n",
" -0.0262\n",
" 0.7808\n",
" 0.4058\n",
" 1.0810\n",
" -0.0285\n",
" 0.4852\n",
" 0.3591\n",
" 0.5424\n",
" 0.8443\n",
" 0.5654\n",
" -0.3290\n",
" 1.2563\n",
" 0.2957\n",
" 0.6080\n",
" -1.0073\n",
" -0.6875\n",
" 0.6321\n",
" 0.6867\n",
" -1.3513\n",
" -0.3735\n",
" 1.0324\n",
" 0.4403\n",
" -1.3225\n",
" 1.0055\n",
" -1.0831\n",
" 0.3380\n",
" -0.7721\n",
" -0.0921\n",
" 0.6735\n",
" 0.7410\n",
" 0.0396\n",
" 1.0561\n",
" 0.0040\n",
" 1.0135\n",
" 0.8185\n",
" 0.7132\n",
" 1.1297\n",
" -0.0641\n",
" 0.5488\n",
" 0.6189\n",
" 0.6287\n",
" 1.6989\n",
" 0.2293\n",
" 0.5385\n",
" 0.7866\n",
" -0.0101\n",
" 0.7307\n",
" -0.8609\n",
" 0.1057\n",
" 1.3026\n",
" 0.3684\n",
" 1.4587\n",
" -0.1244\n",
" 0.6186\n",
" -1.1850\n",
" 1.2956\n",
" -1.2645\n",
" 0.4718\n",
" 0.0087\n",
" 0.2734\n",
" -0.3027\n",
" -0.9086\n",
" -0.7481\n",
" -0.0305\n",
" 0.1738\n",
" 0.6157\n",
" 0.2185\n",
" -0.5635\n",
" 0.4902\n",
" 0.4909\n",
" -0.7121\n",
" -1.4196\n",
" 0.0211\n",
" 0.2764\n",
" 0.8459\n",
" -1.0611\n",
" -1.9599\n",
" 0.6789\n",
" -0.0087\n",
" 0.8961\n",
" 0.4669\n",
" 0.3157\n",
" 0.9896\n",
" 0.5475\n",
" 0.4048\n",
" -0.7899\n",
" 0.9126\n",
" -0.2827\n",
" 0.0139\n",
" -1.1461\n",
" 1.1425\n",
" 0.2756\n",
" 1.0780\n",
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" 0.5876\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.1.bn.bias', \n",
" 0.1701\n",
" -0.0081\n",
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" -0.1487\n",
" -0.2297\n",
" -0.2560\n",
" -0.1302\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.1.bn.running_mean', \n",
" 0.2278\n",
" 1.3284\n",
" 5.4859\n",
" 2.7325\n",
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" 1.5379\n",
" 1.2445\n",
" 0.3488\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.1.bn.running_var', \n",
" 1.3367\n",
" 7.6086\n",
" 29.6188\n",
" 19.9479\n",
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" 10.5301\n",
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" 46.5058\n",
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" 4.7017\n",
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" 0.2543\n",
" 1.0787\n",
" 0.7361\n",
" 15.2158\n",
" 9.3967\n",
" 14.4744\n",
" 47.6725\n",
" 0.0015\n",
" 1.4966\n",
" 8.1529\n",
" 2.0170\n",
" 24.5650\n",
" 0.4699\n",
" 24.9536\n",
" 0.6458\n",
" 1.1774\n",
" 8.2636\n",
" 5.0634\n",
" 0.8180\n",
" 10.3734\n",
" 7.5653\n",
" 9.4897\n",
" 11.5371\n",
" 4.4367\n",
" 0.2274\n",
" 46.4561\n",
" 6.3732\n",
" 8.3160\n",
" 14.7590\n",
" 2.9065\n",
" 15.0195\n",
" 8.1915\n",
" 1.9411\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.2.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -5.4286e-02 -9.4237e-02 4.7910e-02\n",
" -2.0761e-01 1.6850e-01 -1.9503e+00\n",
" -4.2229e-01 -1.3163e+00 -2.3051e-01\n",
" ⋮ \n",
" 6.4546e-02 -1.0657e+00 -1.1922e+00\n",
" 5.5012e-02 -5.6582e-01 -2.0700e-01\n",
" 2.8215e-02 -1.4465e-01 -1.5023e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -2.9313e-02 -4.5640e-03 -2.5330e-02\n",
" -1.8320e+00 9.9294e-02 2.6152e-01\n",
" 1.1664e-01 9.9127e-02 -2.0662e+00\n",
" ⋮ \n",
" -8.1441e-01 -8.7617e-01 1.7442e-02\n",
" -1.5637e-01 1.0771e-01 -6.5480e-01\n",
" 1.2788e-01 1.0396e-01 -5.3307e-02\n",
" \n",
" ( 2 ,.,.) = \n",
" 1.3774e-02 -2.2764e-02 1.7160e-02\n",
" -5.4339e-01 8.6952e-02 8.0073e-03\n",
" -2.6484e-01 -1.3497e+00 8.9788e-02\n",
" ⋮ \n",
" 1.1648e-01 -7.7175e-01 1.5116e-01\n",
" -2.1602e-01 2.5640e-01 1.0208e-01\n",
" 1.2165e-01 -2.6676e-02 -4.5937e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -4.6806e-02 -3.6873e-02 3.9662e-02\n",
" -7.0332e-02 -8.7892e-01 -1.4400e+00\n",
" 1.8573e-01 9.4182e-02 1.1713e-01\n",
" ⋮ \n",
" 1.5029e-01 -3.6476e-02 6.7077e-02\n",
" 2.8011e-01 -4.7094e-02 2.2105e-01\n",
" -2.4804e-01 -1.3658e-02 -3.4306e-03\n",
" \n",
" (126,.,.) = \n",
" -1.9260e-02 -1.2697e-02 -1.4019e-02\n",
" -1.3391e-01 -3.4813e-01 -4.7117e-01\n",
" 1.4140e-01 1.4029e-01 -1.3311e-01\n",
" ⋮ \n",
" 1.8775e-01 5.7309e-02 2.6160e-01\n",
" 2.2137e-01 -2.6558e-02 -3.1574e-02\n",
" 1.0015e-02 -1.2476e-01 -3.1886e-02\n",
" \n",
" (127,.,.) = \n",
" 2.4374e-02 1.2599e-02 1.4980e-02\n",
" -1.8930e-01 -3.1155e-02 -2.2507e-01\n",
" 3.4954e-01 -6.2865e-02 4.2429e-01\n",
" ⋮ \n",
" 2.4214e-01 -4.6694e-02 -1.8781e-01\n",
" -2.5548e-01 2.9772e-01 4.9350e-01\n",
" 1.5860e-01 -2.1079e-01 1.1477e-01\n",
" [torch.FloatTensor of size 128x128x3]),\n",
" ('module.encoder.cbhg.conv1d_banks.2.bn.weight', \n",
" 0.7882\n",
" 1.1679\n",
" 0.6868\n",
" -0.5602\n",
" 0.6926\n",
" 0.3480\n",
" 1.3040\n",
" -0.5898\n",
" 0.8252\n",
" -0.1509\n",
" 0.6994\n",
" 0.5404\n",
" 0.7474\n",
" 0.9570\n",
" 0.1598\n",
" 0.5288\n",
" 0.8474\n",
" -0.4721\n",
" 0.7928\n",
" 0.6296\n",
" 0.9907\n",
" -0.6676\n",
" -0.1030\n",
" -1.0869\n",
" 0.4828\n",
" 1.1944\n",
" -0.3796\n",
" 0.7430\n",
" 0.5693\n",
" 0.4382\n",
" 0.3220\n",
" 0.3703\n",
" 0.8995\n",
" 0.7451\n",
" -1.3021\n",
" -0.8754\n",
" -0.8579\n",
" 0.5799\n",
" 0.4983\n",
" 0.5480\n",
" -2.1142\n",
" 0.9737\n",
" 1.2022\n",
" 0.3887\n",
" 0.5268\n",
" 1.2057\n",
" 0.8936\n",
" 0.3334\n",
" 0.7513\n",
" 0.6445\n",
" -0.7795\n",
" 1.0365\n",
" 0.4544\n",
" 0.5647\n",
" 0.7380\n",
" 1.1126\n",
" 0.6847\n",
" 0.2264\n",
" 0.3797\n",
" -1.0073\n",
" 0.9932\n",
" 0.5080\n",
" -1.0126\n",
" 0.8422\n",
" -0.9466\n",
" 0.4633\n",
" 1.2529\n",
" 0.7878\n",
" 0.3980\n",
" 0.9587\n",
" 0.5316\n",
" -0.5880\n",
" 0.6710\n",
" 0.7551\n",
" 0.5722\n",
" 0.5651\n",
" -0.8144\n",
" 0.8886\n",
" 0.4788\n",
" 0.6518\n",
" 0.9727\n",
" -0.7357\n",
" 1.2086\n",
" 0.5821\n",
" 0.2523\n",
" 1.3351\n",
" 1.0008\n",
" 1.0258\n",
" -0.8218\n",
" 0.2004\n",
" 0.4271\n",
" 0.9437\n",
" -0.3267\n",
" 1.2607\n",
" 0.6416\n",
" 0.6931\n",
" -0.6647\n",
" -1.7838\n",
" 0.9953\n",
" -0.5783\n",
" -0.8165\n",
" 0.8011\n",
" 0.8279\n",
" 1.0071\n",
" -0.9063\n",
" 0.7007\n",
" -1.4719\n",
" -1.4968\n",
" -1.0625\n",
" 0.8999\n",
" 0.7239\n",
" 0.0646\n",
" -0.9613\n",
" 0.6627\n",
" 0.7891\n",
" 1.0621\n",
" 0.6897\n",
" 0.7706\n",
" 0.5824\n",
" 0.7817\n",
" -1.3201\n",
" -0.9172\n",
" 0.3756\n",
" -1.4005\n",
" 0.8096\n",
" 0.6342\n",
" -0.7933\n",
" 0.1299\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.2.bn.bias', \n",
" 0.0638\n",
" 0.0563\n",
" 0.2731\n",
" -0.1831\n",
" 0.0058\n",
" -0.1194\n",
" 0.1583\n",
" -0.1720\n",
" 0.0106\n",
" -0.0349\n",
" 0.0823\n",
" 0.0839\n",
" 0.2265\n",
" 0.3051\n",
" 0.0007\n",
" -0.1692\n",
" 0.1714\n",
" -0.0963\n",
" 0.0330\n",
" 0.0207\n",
" -0.1119\n",
" -0.1277\n",
" -0.0389\n",
" -0.3312\n",
" -0.0054\n",
" 0.0919\n",
" -0.0990\n",
" 0.2415\n",
" 0.1045\n",
" 0.0839\n",
" -0.0179\n",
" 0.1326\n",
" 0.1313\n",
" 0.3185\n",
" -0.1222\n",
" -0.2094\n",
" -0.2618\n",
" -0.1596\n",
" 0.2535\n",
" -0.0093\n",
" -0.0895\n",
" 0.1695\n",
" 0.1285\n",
" 0.1045\n",
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" 0.0559\n",
" 0.2153\n",
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" 0.1243\n",
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" -0.0646\n",
" 0.3177\n",
" 0.0043\n",
" 0.0961\n",
" 0.0593\n",
" 0.0338\n",
" 0.0701\n",
" 0.0092\n",
" -0.0261\n",
" -0.3211\n",
" 0.1917\n",
" 0.0501\n",
" -0.1208\n",
" 0.2013\n",
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" 0.0901\n",
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" -0.2259\n",
" 0.2413\n",
" -0.1080\n",
" 0.0616\n",
" 0.3122\n",
" -0.2073\n",
" 0.0341\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.2.bn.running_mean', \n",
" 1.1630\n",
" 0.2190\n",
" 0.6604\n",
" 6.8502\n",
" 0.5800\n",
" 0.7456\n",
" 0.8671\n",
" 4.6402\n",
" 0.1669\n",
" 3.2986\n",
" 0.3361\n",
" 1.2620\n",
" 0.4217\n",
" 0.3617\n",
" 1.4444\n",
" 0.6314\n",
" 0.9157\n",
" 1.0370\n",
" 1.7103\n",
" 0.1520\n",
" 0.2035\n",
" 3.8058\n",
" 1.4098\n",
" 3.0435\n",
" 1.8632\n",
" 0.2145\n",
" 1.3484\n",
" 0.0739\n",
" 3.0820\n",
" 4.6308\n",
" 0.8663\n",
" 5.6400\n",
" 1.1108\n",
" 1.6447\n",
" 0.2646\n",
" 2.1980\n",
" 3.5989\n",
" 0.5466\n",
" 0.4014\n",
" 0.5370\n",
" 0.1492\n",
" 0.4578\n",
" 0.0107\n",
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" 1.5005\n",
" 2.0964\n",
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" 0.6175\n",
" 0.9700\n",
" 0.0986\n",
" 2.0744\n",
" 1.9988\n",
" 1.1954\n",
" 2.7618\n",
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" 1.4422\n",
" 0.9258\n",
" 1.6989\n",
" 12.8986\n",
" 0.7410\n",
" 0.3696\n",
" 0.9520\n",
" 0.4256\n",
" 0.8205\n",
" 4.3940\n",
" 1.5047\n",
" 0.6868\n",
" 3.1306\n",
" 2.5420\n",
" 1.0325\n",
" 0.3960\n",
" 0.7334\n",
" 1.4882\n",
" 0.5329\n",
" 2.3058\n",
" 0.0159\n",
" 0.7815\n",
" 10.4380\n",
" 0.1061\n",
" 0.1331\n",
" 0.6696\n",
" 2.0808\n",
" 3.2479\n",
" 4.0375\n",
" 0.5901\n",
" 1.7219\n",
" 0.2626\n",
" 1.2888\n",
" 2.9755\n",
" 2.2197\n",
" 0.2895\n",
" 0.9920\n",
" 1.0100\n",
" 1.7728\n",
" 0.3082\n",
" 0.1416\n",
" 0.2235\n",
" 2.5931\n",
" 0.0869\n",
" 0.4106\n",
" 0.7252\n",
" 1.9628\n",
" 0.0089\n",
" 1.1316\n",
" 4.9027\n",
" 1.3078\n",
" 0.1001\n",
" 0.2413\n",
" 0.2598\n",
" 0.3739\n",
" 0.1684\n",
" 1.3397\n",
" 0.2249\n",
" 1.6900\n",
" 1.6697\n",
" 1.3694\n",
" 0.4396\n",
" 0.8980\n",
" 0.2888\n",
" 1.2549\n",
" 4.6069\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.2.bn.running_var', \n",
" 9.7994\n",
" 1.2514\n",
" 4.1081\n",
" 46.8629\n",
" 3.6430\n",
" 4.7418\n",
" 6.4415\n",
" 33.7882\n",
" 0.9173\n",
" 15.8640\n",
" 3.5358\n",
" 11.0178\n",
" 3.2181\n",
" 2.7233\n",
" 6.4556\n",
" 5.5252\n",
" 7.7024\n",
" 5.3057\n",
" 14.0739\n",
" 1.0280\n",
" 1.1828\n",
" 28.1004\n",
" 7.1049\n",
" 23.1384\n",
" 13.8020\n",
" 1.1702\n",
" 8.0575\n",
" 0.3680\n",
" 29.6075\n",
" 42.2086\n",
" 5.7056\n",
" 61.3984\n",
" 8.8590\n",
" 14.3460\n",
" 1.8237\n",
" 17.0321\n",
" 38.5890\n",
" 4.8810\n",
" 3.5166\n",
" 3.8442\n",
" 1.1839\n",
" 2.8182\n",
" 0.0253\n",
" 13.5511\n",
" 8.0220\n",
" 3.5922\n",
" 3.4204\n",
" 13.1982\n",
" 14.3898\n",
" 15.3038\n",
" 0.0906\n",
" 13.9396\n",
" 7.8078\n",
" 5.1677\n",
" 7.0526\n",
" 0.5769\n",
" 16.6135\n",
" 13.2465\n",
" 9.8636\n",
" 23.3770\n",
" 0.9680\n",
" 0.6132\n",
" 11.0925\n",
" 7.6960\n",
" 15.5853\n",
" 49.7492\n",
" 5.7911\n",
" 1.9542\n",
" 6.6985\n",
" 2.6736\n",
" 6.1363\n",
" 38.2642\n",
" 14.4988\n",
" 4.6359\n",
" 34.5189\n",
" 19.9102\n",
" 7.4275\n",
" 2.7323\n",
" 7.2089\n",
" 12.1778\n",
" 2.7965\n",
" 21.4060\n",
" 0.0439\n",
" 5.3728\n",
" 58.0339\n",
" 0.5599\n",
" 0.6702\n",
" 4.5155\n",
" 19.7068\n",
" 24.7468\n",
" 32.4359\n",
" 3.7611\n",
" 8.8014\n",
" 1.4880\n",
" 9.7919\n",
" 22.7541\n",
" 17.9358\n",
" 1.9441\n",
" 7.9773\n",
" 5.0693\n",
" 15.6299\n",
" 2.0215\n",
" 0.7720\n",
" 1.1532\n",
" 23.9688\n",
" 0.3376\n",
" 2.5808\n",
" 6.6397\n",
" 15.5070\n",
" 0.0205\n",
" 9.0777\n",
" 22.0513\n",
" 11.2502\n",
" 0.5872\n",
" 1.3869\n",
" 1.4350\n",
" 2.5002\n",
" 0.9065\n",
" 11.0231\n",
" 1.2137\n",
" 12.7303\n",
" 15.6336\n",
" 9.6978\n",
" 3.0546\n",
" 6.9087\n",
" 2.1190\n",
" 8.6749\n",
" 36.0892\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.3.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -3.0199e-02 -4.5101e-02 4.1657e-02 -1.3989e-01\n",
" 5.9655e-02 1.3077e-01 -1.0970e+00 9.7011e-03\n",
" -1.3781e+00 2.7077e-01 -1.9742e-02 2.1801e-02\n",
" ⋮ \n",
" -9.1431e-02 1.5480e-01 2.4212e-02 7.3165e-02\n",
" 1.4958e-01 -4.2327e-01 1.9488e-01 -6.6253e-01\n",
" -1.3541e-01 -2.3292e-01 -3.2272e-01 -1.7024e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" 3.2595e-02 -3.2977e-03 4.1706e-02 -1.3661e-03\n",
" -1.0077e+00 -2.9712e-01 -4.7499e-02 -5.7860e-01\n",
" 2.7742e-01 5.4497e-02 2.4373e-01 -1.1944e+00\n",
" ⋮ \n",
" -7.5219e-01 5.6820e-02 -4.2962e-01 -2.7082e-01\n",
" 6.5423e-02 2.2855e-01 -7.5106e-02 2.1938e-01\n",
" -1.2268e-01 -2.7853e-02 8.2643e-02 -2.9314e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" -3.8005e-02 -1.8723e-02 9.9610e-03 -1.8004e-02\n",
" 2.8541e-01 -4.0136e-01 -6.4734e-01 -9.4345e-01\n",
" -4.9899e-03 1.0887e-01 -5.8836e-02 -5.9108e-01\n",
" ⋮ \n",
" -5.1846e-01 4.7479e-03 -4.8246e-01 -1.0629e-01\n",
" 8.4392e-02 9.2139e-02 -5.7263e-02 -2.2137e-01\n",
" -2.2947e-01 -8.1368e-02 -1.8130e-01 1.4157e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -1.9266e-02 -5.8194e-03 -5.9193e-02 1.2790e-02\n",
" 7.3518e-02 1.8488e-01 1.2557e-01 1.2247e-01\n",
" -1.3630e-01 5.6454e-02 1.3659e-01 -6.8306e-02\n",
" ⋮ \n",
" 4.1640e-01 -1.0616e-01 -2.5067e-01 1.5842e-01\n",
" -7.1185e-02 1.9634e-01 -1.7411e-01 2.7764e-01\n",
" 3.3945e-03 -3.4820e-03 8.2969e-02 -1.0172e-01\n",
" \n",
" (126,.,.) = \n",
" -1.9898e-02 1.1437e-02 -6.1109e-02 -2.0294e-02\n",
" -1.9157e-01 1.5399e-01 -2.3774e+00 -1.2851e+00\n",
" 4.7223e-02 -8.3199e-01 1.5482e-01 -1.4128e+00\n",
" ⋮ \n",
" 9.8303e-02 8.7049e-02 -4.9641e-01 1.8631e-02\n",
" -1.5819e-01 -7.8419e-01 -4.9958e-01 -4.4801e-01\n",
" -2.3128e-01 -8.0637e-02 -1.0088e-01 3.4297e-02\n",
" \n",
" (127,.,.) = \n",
" -4.6688e-02 2.6377e-02 -1.1830e-01 4.1776e-02\n",
" 1.7381e-01 7.2495e-02 -4.0078e-02 1.2306e-01\n",
" -1.6091e-01 -1.0786e-01 -1.6649e-01 3.2966e-02\n",
" ⋮ \n",
" 2.8699e-01 2.1908e-01 -4.5487e-01 -2.5770e-02\n",
" 2.0351e-01 -4.6262e-01 1.0559e-01 -3.1717e-01\n",
" -4.0802e-02 6.2488e-02 1.3862e-01 -1.4880e-02\n",
" [torch.FloatTensor of size 128x128x4]),\n",
" ('module.encoder.cbhg.conv1d_banks.3.bn.weight', \n",
" 0.6762\n",
" 1.2839\n",
" 0.5925\n",
" 0.4043\n",
" 0.5573\n",
" 0.4524\n",
" 0.4971\n",
" -0.5960\n",
" 0.5021\n",
" -0.9494\n",
" 0.5080\n",
" -0.8624\n",
" 0.6140\n",
" 0.5730\n",
" -1.2350\n",
" 0.7618\n",
" 0.4530\n",
" 1.6662\n",
" -0.3794\n",
" 0.5542\n",
" 0.4506\n",
" 0.5946\n",
" 0.5797\n",
" 0.4881\n",
" 0.4952\n",
" -0.5356\n",
" 0.6488\n",
" -0.8908\n",
" 0.4057\n",
" 0.6898\n",
" 0.6750\n",
" -0.1251\n",
" 0.6325\n",
" 0.4851\n",
" 0.4389\n",
" 0.4041\n",
" 0.4299\n",
" 0.7708\n",
" 0.7325\n",
" -0.0463\n",
" 0.6394\n",
" 0.5451\n",
" 0.3378\n",
" 0.7166\n",
" 0.6030\n",
" 1.1028\n",
" 0.3994\n",
" -0.9556\n",
" 0.3748\n",
" 0.5475\n",
" 0.4361\n",
" 0.3910\n",
" 0.7346\n",
" 0.6367\n",
" 0.5006\n",
" 0.6014\n",
" 0.6725\n",
" 0.4923\n",
" 0.6960\n",
" 0.3339\n",
" 0.3371\n",
" 0.3961\n",
" 0.4107\n",
" 0.5951\n",
" 0.4860\n",
" 0.5769\n",
" -0.7742\n",
" 0.4339\n",
" 0.7209\n",
" 0.4315\n",
" 0.5832\n",
" 0.5863\n",
" 0.5736\n",
" 0.4677\n",
" -1.0682\n",
" 0.9264\n",
" 0.7246\n",
" 0.7324\n",
" 0.4137\n",
" -0.5774\n",
" 0.4973\n",
" 0.7447\n",
" 0.3545\n",
" 0.7746\n",
" 0.6656\n",
" 0.5835\n",
" 0.5291\n",
" 1.1132\n",
" 0.4102\n",
" 0.5999\n",
" 0.3807\n",
" 0.3736\n",
" 0.6172\n",
" 1.1931\n",
" -0.0256\n",
" 0.4723\n",
" 0.6797\n",
" 0.8751\n",
" 0.4438\n",
" 0.4281\n",
" 0.3294\n",
" 0.9565\n",
" 0.7108\n",
" 0.8660\n",
" 0.7950\n",
" 1.0954\n",
" -0.0163\n",
" 0.0693\n",
" 0.4338\n",
" -0.0255\n",
" 0.0793\n",
" -0.7395\n",
" 0.0218\n",
" 0.3456\n",
" 0.6162\n",
" -0.6018\n",
" 1.5660\n",
" 0.7036\n",
" 0.8461\n",
" 0.6650\n",
" 0.3238\n",
" -0.1641\n",
" 0.3654\n",
" 0.6098\n",
" 0.6175\n",
" -0.5964\n",
" 0.6494\n",
" 0.3895\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.3.bn.bias', \n",
" 0.1157\n",
" 0.4014\n",
" 0.1449\n",
" 0.0870\n",
" 0.0422\n",
" -0.1932\n",
" 0.2791\n",
" -0.1141\n",
" 0.0616\n",
" -0.1564\n",
" 0.1885\n",
" -0.1000\n",
" 0.0900\n",
" 0.1455\n",
" -0.3226\n",
" 0.0664\n",
" 0.1438\n",
" 0.0250\n",
" -0.0582\n",
" 0.0415\n",
" 0.0589\n",
" 0.1084\n",
" 0.0381\n",
" -0.0546\n",
" 0.0147\n",
" -0.1381\n",
" -0.0526\n",
" -0.1121\n",
" 0.0751\n",
" 0.0238\n",
" 0.0121\n",
" -0.0361\n",
" 0.1103\n",
" 0.1307\n",
" -0.0235\n",
" -0.0487\n",
" 0.0064\n",
" 0.1435\n",
" -0.2283\n",
" -0.0059\n",
" 0.0107\n",
" -0.0105\n",
" 0.0806\n",
" 0.0485\n",
" 0.0593\n",
" 0.2291\n",
" -0.0547\n",
" -0.2096\n",
" -0.1142\n",
" 0.0520\n",
" 0.0096\n",
" -0.0157\n",
" 0.0705\n",
" -0.1203\n",
" 0.2084\n",
" 0.0232\n",
" 0.1335\n",
" 0.0985\n",
" -0.0865\n",
" 0.0218\n",
" -0.0995\n",
" 0.1750\n",
" 0.0665\n",
" 0.1305\n",
" 0.1409\n",
" -0.0519\n",
" -0.2571\n",
" -0.2469\n",
" 0.1067\n",
" -0.1175\n",
" -0.0143\n",
" 0.0273\n",
" 0.1013\n",
" -0.1832\n",
" -0.0928\n",
" 0.1175\n",
" 0.0343\n",
" 0.1175\n",
" 0.1041\n",
" 0.0484\n",
" 0.2421\n",
" 0.1170\n",
" -0.0565\n",
" 0.1435\n",
" 0.0914\n",
" 0.1470\n",
" -0.1090\n",
" 0.2005\n",
" 0.0871\n",
" 0.0101\n",
" 0.0458\n",
" -0.0110\n",
" 0.1671\n",
" 0.0892\n",
" 0.0073\n",
" 0.0335\n",
" 0.0925\n",
" 0.1804\n",
" -0.0319\n",
" -0.0401\n",
" 0.1655\n",
" 0.1278\n",
" 0.1544\n",
" 0.2714\n",
" -0.1484\n",
" 0.0515\n",
" -0.0145\n",
" 0.0018\n",
" 0.0577\n",
" 0.0064\n",
" -0.0056\n",
" -0.0825\n",
" -0.0013\n",
" 0.0528\n",
" -0.0137\n",
" -0.1068\n",
" 0.0190\n",
" 0.0481\n",
" 0.0621\n",
" 0.1866\n",
" 0.0732\n",
" -0.0291\n",
" -0.0383\n",
" 0.2391\n",
" 0.1083\n",
" -0.1501\n",
" -0.0074\n",
" -0.0611\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.3.bn.running_mean', \n",
" 0.2907\n",
" 0.9724\n",
" 0.0591\n",
" 7.0921\n",
" 0.3564\n",
" 1.5779\n",
" 13.5156\n",
" 1.0280\n",
" 0.5696\n",
" 2.6036\n",
" 0.2261\n",
" 2.1813\n",
" 0.6724\n",
" 0.6929\n",
" 0.7458\n",
" 0.3476\n",
" 1.9931\n",
" 0.1909\n",
" 7.2323\n",
" 0.5527\n",
" 0.3362\n",
" 2.3720\n",
" 1.5167\n",
" 3.6392\n",
" 1.3306\n",
" 2.6000\n",
" 0.5801\n",
" 1.3793\n",
" 1.9162\n",
" 0.3574\n",
" 0.1882\n",
" 1.2014\n",
" 1.2526\n",
" 0.7860\n",
" 0.5745\n",
" 0.3189\n",
" 0.7388\n",
" 0.7234\n",
" 0.0937\n",
" 9.9037\n",
" 1.0526\n",
" 0.1291\n",
" 1.8733\n",
" 0.9669\n",
" 1.0198\n",
" 0.0990\n",
" 10.1295\n",
" 1.1176\n",
" 1.2340\n",
" 1.5836\n",
" 2.7698\n",
" 1.7052\n",
" 1.6756\n",
" 0.2054\n",
" 1.8708\n",
" 0.8747\n",
" 0.3102\n",
" 4.3427\n",
" 0.2556\n",
" 1.4933\n",
" 1.1341\n",
" 10.7140\n",
" 1.2381\n",
" 0.5267\n",
" 0.3254\n",
" 0.1514\n",
" 2.8627\n",
" 0.3161\n",
" 0.6128\n",
" 3.2774\n",
" 1.0922\n",
" 1.4499\n",
" 0.1820\n",
" 0.3361\n",
" 4.7489\n",
" 0.9300\n",
" 0.3193\n",
" 0.1965\n",
" 0.1582\n",
" 4.3853\n",
" 0.7887\n",
" 0.7031\n",
" 2.5427\n",
" 0.1071\n",
" 0.4976\n",
" 0.3115\n",
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" 0.1709\n",
" 5.0987\n",
" 2.5484\n",
" 0.1011\n",
" 0.0435\n",
" 1.7191\n",
" 0.7203\n",
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" 1.1218\n",
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" 5.0673\n",
" 0.8436\n",
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" 8.1118\n",
" 3.5657\n",
" 1.1770\n",
" 3.5329\n",
" 1.3464\n",
" 1.5698\n",
" 5.1944\n",
" 3.2881\n",
" 0.3376\n",
" 4.2355\n",
" 1.4871\n",
" 2.0011\n",
" 0.0229\n",
" 1.0462\n",
" 2.2058\n",
" 3.6935\n",
" 0.6207\n",
" 2.2306\n",
" 0.3112\n",
" 2.4165\n",
" 0.1631\n",
" 2.1980\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.3.bn.running_var', \n",
" 1.8418\n",
" 12.1676\n",
" 0.4626\n",
" 43.6007\n",
" 4.3930\n",
" 15.3208\n",
" 87.6767\n",
" 7.0887\n",
" 5.4963\n",
" 25.9627\n",
" 2.0877\n",
" 20.8844\n",
" 5.1665\n",
" 5.3227\n",
" 6.8652\n",
" 2.6800\n",
" 16.6571\n",
" 4.4653\n",
" 43.1472\n",
" 3.8001\n",
" 2.2434\n",
" 23.9898\n",
" 15.3317\n",
" 31.4329\n",
" 9.5696\n",
" 18.6807\n",
" 6.8543\n",
" 12.6780\n",
" 21.7198\n",
" 2.8985\n",
" 1.4760\n",
" 5.6311\n",
" 10.7562\n",
" 7.2283\n",
" 5.4736\n",
" 3.2340\n",
" 7.0783\n",
" 6.1088\n",
" 0.5139\n",
" 48.0629\n",
" 13.1178\n",
" 0.7780\n",
" 15.6500\n",
" 8.2420\n",
" 9.1927\n",
" 0.6737\n",
" 64.0188\n",
" 7.9275\n",
" 12.5226\n",
" 18.7606\n",
" 29.9964\n",
" 13.7883\n",
" 15.7356\n",
" 1.4478\n",
" 15.4805\n",
" 7.1590\n",
" 2.7078\n",
" 36.3994\n",
" 1.7871\n",
" 9.7304\n",
" 10.0635\n",
" 72.9783\n",
" 9.4999\n",
" 5.3499\n",
" 2.3363\n",
" 0.9517\n",
" 26.1254\n",
" 2.6923\n",
" 4.6281\n",
" 26.8849\n",
" 10.3987\n",
" 13.1628\n",
" 1.4532\n",
" 2.4368\n",
" 52.3030\n",
" 13.3247\n",
" 2.5919\n",
" 1.7007\n",
" 1.1596\n",
" 42.2475\n",
" 6.4425\n",
" 5.6024\n",
" 19.3698\n",
" 0.5629\n",
" 3.6024\n",
" 2.4057\n",
" 2.8786\n",
" 2.9411\n",
" 7.8058\n",
" 4.0184\n",
" 4.0513\n",
" 4.5486\n",
" 10.3213\n",
" 1.0285\n",
" 26.9182\n",
" 23.5436\n",
" 0.7894\n",
" 0.2378\n",
" 17.0778\n",
" 5.9807\n",
" 6.3857\n",
" 8.9704\n",
" 1.8861\n",
" 65.6700\n",
" 7.0327\n",
" 0.2992\n",
" 74.7671\n",
" 15.9068\n",
" 12.2373\n",
" 14.9016\n",
" 6.7227\n",
" 13.5921\n",
" 39.4942\n",
" 22.5308\n",
" 2.6461\n",
" 29.9793\n",
" 11.1880\n",
" 17.1316\n",
" 0.0988\n",
" 9.8629\n",
" 14.2450\n",
" 27.3753\n",
" 5.3518\n",
" 21.6821\n",
" 2.3591\n",
" 19.7895\n",
" 1.0592\n",
" 17.0844\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.4.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 1.8676e-02 4.3095e-02 -1.5726e-02 -4.3661e-02 -9.8139e-03\n",
" -2.0828e-02 3.0502e-01 -2.4855e-01 -1.1689e-01 -1.2934e-02\n",
" -2.4981e-01 6.2893e-02 -1.9024e-01 -5.0738e-02 3.3915e-01\n",
" ⋮ \n",
" 1.6444e-01 -6.0511e-01 -5.3369e-01 -2.9930e-01 3.1245e-01\n",
" -2.8105e-01 2.4210e-01 -5.1733e-01 -5.1014e-01 -3.4072e-01\n",
" -2.4825e-01 -7.7791e-02 -2.0725e-02 -4.8233e-02 -9.1717e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" 6.9531e-02 -4.4087e-02 9.2566e-02 -4.6828e-02 3.0438e-02\n",
" 1.0145e-01 1.8946e-01 -2.9237e+00 -2.4120e+00 1.6530e-01\n",
" -4.3283e-02 -7.5086e-02 -6.1910e-01 -1.1024e+00 3.5328e-01\n",
" ⋮ \n",
" -1.2166e-01 1.3522e-01 2.8608e-04 2.4502e-01 -7.5205e-02\n",
" -4.6553e-02 1.3329e-02 -8.7335e-01 -3.2406e-02 2.4081e-01\n",
" 1.9314e-01 3.8841e-02 -6.1874e-01 4.3118e-02 -2.3558e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 1.9084e-02 -6.8872e-03 -4.7294e-02 -1.1103e-03 5.2093e-02\n",
" 3.9098e-01 -4.9400e-02 -5.5011e-02 -1.4766e-01 3.7494e-01\n",
" -3.2525e-01 1.6407e-01 1.2210e-01 2.1276e-01 3.4819e-02\n",
" ⋮ \n",
" -1.2377e-01 3.4028e-02 2.1447e-01 -4.6228e-01 8.3448e-02\n",
" -4.6388e-01 2.2220e-01 -3.5371e-01 2.5234e-01 3.4024e-01\n",
" 3.3419e-02 1.7029e-01 3.2783e-02 -5.3499e-02 9.5706e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -4.0932e-02 -2.5763e-02 7.7512e-03 3.6522e-02 3.7960e-02\n",
" -3.4469e-02 -1.0437e+00 -7.4566e-01 -1.6032e-02 1.0350e-01\n",
" -8.7426e-01 1.6048e-01 -8.3122e-02 -1.8413e-03 -9.7011e-01\n",
" ⋮ \n",
" -1.6335e-01 7.2348e-02 -1.1172e+00 -4.5718e-01 -1.0383e+00\n",
" 2.5089e-01 1.4073e-01 -5.9574e-01 -9.8118e-01 1.5447e-01\n",
" -1.8739e-01 -4.8575e-01 -1.2125e-01 -3.5486e-01 -4.8543e-01\n",
" \n",
" (126,.,.) = \n",
" 4.5631e-02 1.0822e-02 -2.5906e-02 8.9613e-03 -4.3499e-02\n",
" -6.0878e-01 -9.8588e-01 -5.2404e-01 -8.0881e-01 -3.5317e-01\n",
" -3.4792e-02 -1.0723e+00 -7.0286e-01 -5.1342e-01 8.7097e-03\n",
" ⋮ \n",
" 1.7486e-01 5.7678e-02 -5.5733e-01 -1.9898e-01 -3.2039e-01\n",
" 1.6729e-01 -2.5874e-01 -3.0634e-01 -4.0217e-01 7.8019e-02\n",
" -3.8354e-02 5.5831e-02 -1.5912e-01 -1.3364e-01 -1.0953e-01\n",
" \n",
" (127,.,.) = \n",
" -3.2366e-02 2.3642e-02 3.2589e-02 -1.1044e-02 8.8390e-03\n",
" -7.1364e-01 -3.9804e-01 2.8420e-02 -1.2269e+00 -4.1309e-01\n",
" -1.2522e-01 5.2512e-02 1.4330e-02 9.9259e-02 3.5246e-02\n",
" ⋮ \n",
" -1.6750e-02 -4.6182e-01 -8.4984e-01 -7.7151e-01 6.1423e-02\n",
" 8.0939e-02 -4.9918e-01 -3.9325e-02 -3.2784e-01 -4.4412e-01\n",
" 7.7830e-02 -6.5344e-02 1.7677e-02 -5.8119e-02 2.2737e-02\n",
" [torch.FloatTensor of size 128x128x5]),\n",
" ('module.encoder.cbhg.conv1d_banks.4.bn.weight', \n",
" 0.3426\n",
" 0.6003\n",
" 0.2337\n",
" 0.2767\n",
" -1.5664\n",
" 0.6790\n",
" 0.2967\n",
" 0.6112\n",
" 0.5981\n",
" 1.2043\n",
" 0.8861\n",
" 0.4381\n",
" 0.5049\n",
" 0.4052\n",
" 1.1499\n",
" 0.0001\n",
" 0.5920\n",
" -0.6619\n",
" 0.5119\n",
" 0.8957\n",
" 0.4586\n",
" 0.8248\n",
" 0.5741\n",
" 0.3737\n",
" -0.7913\n",
" 0.3334\n",
" 0.4213\n",
" 0.7619\n",
" 0.9248\n",
" 0.8743\n",
" 0.8350\n",
" 1.1013\n",
" 1.1371\n",
" 0.4845\n",
" 0.5254\n",
" 0.3206\n",
" 0.4344\n",
" 0.5647\n",
" 0.5539\n",
" 0.8183\n",
" 0.6006\n",
" 0.4469\n",
" 1.2965\n",
" -0.6258\n",
" 0.4940\n",
" 0.6888\n",
" 0.5895\n",
" 0.5103\n",
" 0.1940\n",
" -0.0739\n",
" 0.4408\n",
" -1.0388\n",
" 0.4637\n",
" 0.5204\n",
" 0.5693\n",
" 0.7005\n",
" 0.3624\n",
" 0.5829\n",
" 0.5393\n",
" 0.5945\n",
" 0.2330\n",
" 0.2835\n",
" 0.7863\n",
" 0.4587\n",
" 0.5319\n",
" -0.6582\n",
" -1.5175\n",
" 0.5959\n",
" 0.3762\n",
" 0.4533\n",
" 0.8087\n",
" 0.7461\n",
" 0.7765\n",
" 0.4178\n",
" 0.5040\n",
" 0.5407\n",
" 0.7416\n",
" -0.9143\n",
" -1.0565\n",
" 1.1500\n",
" -1.2856\n",
" 0.4806\n",
" 0.5750\n",
" 1.2181\n",
" 0.7721\n",
" 0.6361\n",
" 0.4319\n",
" 0.5130\n",
" 0.0221\n",
" -0.9896\n",
" -1.1924\n",
" 0.4069\n",
" 0.6089\n",
" 0.3713\n",
" -0.1563\n",
" 0.4905\n",
" 0.3348\n",
" 0.5328\n",
" 0.5235\n",
" 0.5093\n",
" 0.4743\n",
" 0.5250\n",
" 0.6474\n",
" 0.3690\n",
" 0.4880\n",
" 0.5428\n",
" 0.5635\n",
" 0.4048\n",
" 0.4607\n",
" -0.8978\n",
" 0.6659\n",
" 0.6544\n",
" -1.4788\n",
" -1.0401\n",
" 0.9904\n",
" 0.5127\n",
" 0.4872\n",
" 0.4587\n",
" 0.7145\n",
" 0.7750\n",
" 0.3730\n",
" -1.0018\n",
" 0.5827\n",
" 0.3664\n",
" 0.6188\n",
" 0.6160\n",
" -1.4819\n",
" 0.7840\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.4.bn.bias', \n",
" 0.1269\n",
" 0.1285\n",
" 0.0361\n",
" -0.0386\n",
" -0.1509\n",
" 0.0291\n",
" -0.0117\n",
" 0.0266\n",
" 0.1041\n",
" 0.1785\n",
" 0.2022\n",
" -0.1472\n",
" 0.0636\n",
" -0.0567\n",
" 0.0901\n",
" -0.0037\n",
" 0.0677\n",
" -0.0685\n",
" 0.0430\n",
" 0.0297\n",
" 0.0887\n",
" -0.1836\n",
" 0.1372\n",
" -0.1900\n",
" -0.0034\n",
" -0.1570\n",
" 0.0834\n",
" 0.1421\n",
" 0.1412\n",
" -0.0480\n",
" 0.0061\n",
" -0.0238\n",
" 0.0758\n",
" -0.0220\n",
" 0.0793\n",
" 0.0252\n",
" -0.0169\n",
" 0.1349\n",
" -0.0997\n",
" -0.0222\n",
" 0.0424\n",
" 0.2772\n",
" 0.2115\n",
" -0.1162\n",
" -0.0630\n",
" -0.1354\n",
" 0.0988\n",
" 0.0382\n",
" -0.0212\n",
" -0.0052\n",
" -0.0553\n",
" -0.2416\n",
" 0.0796\n",
" 0.1696\n",
" 0.0128\n",
" 0.2235\n",
" 0.0418\n",
" 0.0549\n",
" 0.0119\n",
" -0.2704\n",
" -0.0125\n",
" 0.0839\n",
" 0.0265\n",
" 0.0725\n",
" 0.1788\n",
" -0.0850\n",
" -0.0673\n",
" 0.2108\n",
" -0.0181\n",
" -0.0814\n",
" 0.0149\n",
" 0.0042\n",
" 0.1059\n",
" -0.0182\n",
" 0.0980\n",
" 0.1088\n",
" 0.1629\n",
" -0.1967\n",
" -0.1704\n",
" 0.0361\n",
" -0.2944\n",
" -0.0876\n",
" 0.0523\n",
" 0.0819\n",
" 0.1366\n",
" -0.2225\n",
" -0.1965\n",
" 0.0689\n",
" -0.0139\n",
" -0.2385\n",
" -0.2867\n",
" 0.0257\n",
" -0.1125\n",
" 0.0647\n",
" -0.0456\n",
" 0.0824\n",
" 0.1223\n",
" 0.0441\n",
" -0.0074\n",
" 0.1459\n",
" 0.0766\n",
" 0.2161\n",
" 0.0482\n",
" -0.0085\n",
" 0.1937\n",
" 0.1123\n",
" 0.1412\n",
" -0.0042\n",
" 0.0901\n",
" -0.1947\n",
" 0.0449\n",
" -0.0446\n",
" -0.0334\n",
" -0.2068\n",
" 0.1845\n",
" -0.0796\n",
" 0.0236\n",
" 0.0239\n",
" 0.0896\n",
" 0.0036\n",
" 0.0559\n",
" 0.0695\n",
" 0.0764\n",
" -0.0007\n",
" -0.1054\n",
" 0.0849\n",
" -0.1300\n",
" 0.0266\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.4.bn.running_mean', \n",
" 1.1662e+00\n",
" 5.7806e-01\n",
" 8.6421e+00\n",
" 1.5111e+00\n",
" 1.4286e-01\n",
" 4.7887e-01\n",
" 2.5149e+00\n",
" 4.1017e-01\n",
" 1.7029e+00\n",
" 6.8182e-01\n",
" 5.2371e-01\n",
" 4.1583e+00\n",
" 9.4160e-02\n",
" 1.1704e+00\n",
" 2.1705e-02\n",
" 1.2901e+01\n",
" 5.2419e+00\n",
" 4.7075e-01\n",
" 7.1928e-02\n",
" 8.2839e-02\n",
" 3.8725e-01\n",
" 1.5272e-01\n",
" 2.7374e+00\n",
" 1.2776e+00\n",
" 4.3609e-09\n",
" 2.0726e+00\n",
" 1.1753e+00\n",
" 5.5592e-01\n",
" 3.3004e-01\n",
" 1.3981e+00\n",
" 4.9237e-02\n",
" 2.0195e-01\n",
" 3.9373e-01\n",
" 9.7453e-01\n",
" 1.2037e+01\n",
" 1.4995e+00\n",
" 6.6274e-01\n",
" 3.8213e-01\n",
" 6.1267e-01\n",
" 4.6233e-02\n",
" 1.9922e-01\n",
" 4.2108e-01\n",
" 2.4134e+00\n",
" 3.7927e+00\n",
" 8.8383e-01\n",
" 2.1092e+00\n",
" 3.5873e-02\n",
" 1.0479e+00\n",
" 2.5503e+00\n",
" 4.3555e+00\n",
" 9.6033e-01\n",
" 1.9151e+00\n",
" 8.3043e-01\n",
" 9.1108e-01\n",
" 6.2211e-01\n",
" 6.0335e-02\n",
" 1.8175e+00\n",
" 2.3355e-01\n",
" 6.3597e-01\n",
" 3.3824e-01\n",
" 4.1144e+00\n",
" 1.0162e+01\n",
" 2.9306e-01\n",
" 1.6782e-01\n",
" 3.0191e+00\n",
" 1.3903e+00\n",
" 7.1522e-02\n",
" 2.3149e-01\n",
" 7.9709e-01\n",
" 4.1425e-01\n",
" 5.9430e-02\n",
" 6.7193e-02\n",
" 1.7077e-01\n",
" 8.2555e+00\n",
" 1.0324e+00\n",
" 2.9795e-01\n",
" 2.9554e+00\n",
" 3.0318e+00\n",
" 1.3888e+00\n",
" 4.4584e-02\n",
" 7.3407e-01\n",
" 3.9918e+00\n",
" 4.1640e-01\n",
" 4.0112e-01\n",
" 1.1698e-01\n",
" 1.3736e+00\n",
" 8.5450e-01\n",
" 3.1089e+00\n",
" 9.4334e+00\n",
" 2.0476e+00\n",
" 2.7410e+00\n",
" 2.9759e-01\n",
" 3.9749e-01\n",
" 3.2181e-01\n",
" 7.5011e+00\n",
" 4.1735e-01\n",
" 1.6323e+01\n",
" 3.7291e-01\n",
" 5.9362e-01\n",
" 7.4685e-01\n",
" 5.1302e-01\n",
" 4.3762e-01\n",
" 1.5844e+00\n",
" 4.9481e-01\n",
" 1.2357e+00\n",
" 6.6337e-01\n",
" 3.1602e-01\n",
" 7.9581e+00\n",
" 5.7080e+00\n",
" 1.7927e+00\n",
" 1.4669e+00\n",
" 1.4931e+00\n",
" 6.7405e-03\n",
" 1.7772e+00\n",
" 5.2709e-01\n",
" 3.7220e-01\n",
" 8.1531e-01\n",
" 1.0348e+00\n",
" 8.1878e-02\n",
" 3.5830e-01\n",
" 1.9062e+00\n",
" 1.2071e+00\n",
" 2.6719e-01\n",
" 8.8440e-01\n",
" 7.4879e-01\n",
" 4.4662e-01\n",
" 8.5571e-02\n",
" 8.4275e-02\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.4.bn.running_var', \n",
" 1.1161e+01\n",
" 5.8489e+00\n",
" 6.2559e+01\n",
" 1.3760e+01\n",
" 1.1316e+00\n",
" 4.6863e+00\n",
" 2.8584e+01\n",
" 4.4339e+00\n",
" 2.0113e+01\n",
" 7.2040e+00\n",
" 4.8571e+00\n",
" 3.6512e+01\n",
" 6.5280e-01\n",
" 1.0856e+01\n",
" 1.2327e-01\n",
" 9.9910e+01\n",
" 6.3146e+01\n",
" 3.9984e+00\n",
" 5.3184e-01\n",
" 5.8083e-01\n",
" 2.9553e+00\n",
" 1.1699e+00\n",
" 3.3601e+01\n",
" 1.3705e+01\n",
" 3.9209e-09\n",
" 1.9752e+01\n",
" 1.3838e+01\n",
" 4.7755e+00\n",
" 3.3254e+00\n",
" 1.4998e+01\n",
" 2.8412e-01\n",
" 1.9239e+00\n",
" 3.3981e+00\n",
" 9.1401e+00\n",
" 8.0982e+01\n",
" 1.4672e+01\n",
" 7.0427e+00\n",
" 3.5584e+00\n",
" 5.6003e+00\n",
" 3.3115e-01\n",
" 1.5336e+00\n",
" 4.0793e+00\n",
" 2.8563e+01\n",
" 3.5319e+01\n",
" 7.8510e+00\n",
" 2.2402e+01\n",
" 2.3532e-01\n",
" 1.1328e+01\n",
" 1.2928e+01\n",
" 2.3886e+01\n",
" 8.7510e+00\n",
" 1.8744e+01\n",
" 7.6653e+00\n",
" 9.4153e+00\n",
" 5.6654e+00\n",
" 4.7516e-01\n",
" 1.8806e+01\n",
" 2.1668e+00\n",
" 6.3653e+00\n",
" 2.6073e+00\n",
" 3.9408e+01\n",
" 6.9438e+01\n",
" 2.9417e+00\n",
" 1.2135e+00\n",
" 2.8289e+01\n",
" 1.4237e+01\n",
" 4.5265e-01\n",
" 2.0719e+00\n",
" 7.5292e+00\n",
" 3.9462e+00\n",
" 3.8858e-01\n",
" 4.1534e-01\n",
" 1.1462e+00\n",
" 6.7391e+01\n",
" 1.1868e+01\n",
" 2.6739e+00\n",
" 3.1718e+01\n",
" 3.5087e+01\n",
" 1.3465e+01\n",
" 3.2188e-01\n",
" 6.7510e+00\n",
" 4.8879e+01\n",
" 4.4594e+00\n",
" 3.8057e+00\n",
" 8.5733e-01\n",
" 1.1967e+01\n",
" 8.7259e+00\n",
" 3.7869e+01\n",
" 8.3978e+01\n",
" 2.3187e+01\n",
" 3.3431e+01\n",
" 2.8585e+00\n",
" 3.4761e+00\n",
" 3.1597e+00\n",
" 3.5961e+01\n",
" 3.7471e+00\n",
" 9.6401e+01\n",
" 3.2155e+00\n",
" 6.9874e+00\n",
" 7.7710e+00\n",
" 4.5784e+00\n",
" 4.4322e+00\n",
" 1.7687e+01\n",
" 4.4191e+00\n",
" 1.1004e+01\n",
" 6.7891e+00\n",
" 2.8761e+00\n",
" 4.6781e+01\n",
" 4.7436e+01\n",
" 1.9463e+01\n",
" 1.4606e+01\n",
" 1.7952e+01\n",
" 4.9074e-02\n",
" 2.2192e+01\n",
" 5.1112e+00\n",
" 2.9833e+00\n",
" 9.0143e+00\n",
" 1.0664e+01\n",
" 6.4345e-01\n",
" 2.8626e+00\n",
" 2.0771e+01\n",
" 1.2641e+01\n",
" 2.3985e+00\n",
" 7.9465e+00\n",
" 6.2094e+00\n",
" 4.9007e+00\n",
" 6.8326e-01\n",
" 5.1287e-01\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.5.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -1.6707e-02 1.5062e-02 -2.4290e-02 -2.0553e-02 7.6927e-02 2.5556e-02\n",
" -1.5825e-01 1.8375e-01 -1.3715e+00 -1.0272e-01 -1.0912e+00 5.3088e-03\n",
" -2.9068e-01 -4.3543e-01 -4.9879e-02 1.9555e-02 1.5983e-01 7.6618e-02\n",
" ⋮ \n",
" -3.8250e-03 -8.1282e-02 7.3171e-02 1.9127e-02 1.2154e-01 -1.3264e+00\n",
" -5.9122e-02 -4.1025e-01 -3.0630e-01 -8.2133e-02 -5.3492e-01 1.9383e-01\n",
" 1.1465e-01 -8.7856e-02 1.9600e-01 -2.7086e-01 -3.4039e-02 -6.0773e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" -5.3984e-04 9.0873e-04 9.3033e-03 -9.9289e-03 -2.5024e-02 6.0367e-02\n",
" -4.0239e-01 1.9475e-02 -5.3144e-01 -2.0597e+00 -9.3734e-02 1.1011e-01\n",
" 1.1027e-01 -8.8092e-02 -6.0984e-01 2.7714e-01 -2.5632e+00 -1.7113e-02\n",
" ⋮ \n",
" -7.9546e-01 -1.1268e+00 5.8257e-02 1.1209e-01 1.2857e-01 -1.9039e-01\n",
" 1.4975e-01 1.0255e-01 -5.6228e-01 -4.2333e-01 -4.6771e-01 5.2113e-02\n",
" 9.4120e-02 -2.0300e-01 -1.4289e-01 -3.4866e-01 -3.5331e-01 6.1327e-03\n",
" \n",
" ( 2 ,.,.) = \n",
" 8.2903e-02 -2.8668e-02 -4.9796e-03 8.3328e-02 7.2743e-03 -1.2039e-03\n",
" 1.2976e-01 3.7283e-02 5.2159e-02 2.3635e-01 7.3198e-02 -1.5133e+00\n",
" 1.3264e-01 -1.4702e-01 1.6758e-01 1.0320e-01 -8.4526e-02 6.9735e-02\n",
" ⋮ \n",
" -1.4193e-01 -1.2630e-02 1.8733e-01 1.9073e-01 -2.8929e-01 -3.8090e-02\n",
" -3.0786e-01 -6.9524e-01 -2.1240e-01 -8.6229e-01 -2.4218e-02 9.6994e-02\n",
" -1.9311e-01 9.7328e-03 -2.3853e-01 -6.1829e-02 2.2485e-02 2.0454e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -1.9382e-02 -5.8581e-02 2.0791e-02 -3.7576e-02 -2.6406e-02 -1.5199e-02\n",
" 2.0389e-02 -1.8575e-01 -1.1484e-01 1.1992e-01 -1.4563e-02 -6.6121e-02\n",
" 3.8035e-02 -1.8355e-02 -3.8509e-01 1.3890e-01 -3.7742e-01 3.6402e-02\n",
" ⋮ \n",
" 3.2539e-01 1.4324e-01 1.2824e-01 7.3527e-02 -1.1932e-01 -2.4204e-01\n",
" -1.6890e-01 7.2598e-02 -7.4014e-03 -8.6582e-02 -2.3952e-01 9.7968e-02\n",
" 5.8235e-02 -7.7000e-02 5.9546e-02 4.4890e-02 3.4878e-01 -2.8980e-01\n",
" \n",
" (126,.,.) = \n",
" 6.8186e-02 2.5241e-02 8.6074e-03 -5.2280e-02 -2.3363e-02 3.2551e-02\n",
" 1.8539e-01 -5.2975e-02 -4.4095e-01 -1.0673e+00 2.9257e-01 1.3955e-01\n",
" 4.7721e-03 1.0114e-01 -4.3054e-01 -1.8220e-01 -3.3834e-01 -3.7529e-01\n",
" ⋮ \n",
" -1.3286e-01 6.4792e-03 1.3652e-01 -1.6517e+00 -3.3156e-01 2.8734e-01\n",
" -9.4012e-01 3.8226e-01 1.5905e-01 -3.5121e-01 6.5831e-02 -1.9648e-01\n",
" 6.5724e-02 -1.5490e-01 6.5657e-02 -1.0527e-01 -1.5488e-01 -9.4005e-03\n",
" \n",
" (127,.,.) = \n",
" -2.3498e-02 6.9453e-03 4.4837e-02 2.5762e-02 4.6459e-02 2.5738e-02\n",
" 1.3858e-01 -5.1303e-01 -2.2565e-02 9.0544e-02 1.9153e-01 1.7328e-01\n",
" -8.9238e-02 -5.8354e-02 5.8674e-02 1.4331e-02 -1.2725e-01 -9.0258e-02\n",
" ⋮ \n",
" 5.6267e-02 7.4358e-02 -2.7942e-01 -1.4918e+00 -1.2619e+00 -7.9139e-03\n",
" -1.6702e-01 2.0627e-01 -7.0767e-02 6.5989e-03 6.8970e-02 1.4741e-01\n",
" 8.9828e-02 -1.9443e-01 -1.1682e-01 1.7129e-01 5.7646e-02 1.2306e-02\n",
" [torch.FloatTensor of size 128x128x6]),\n",
" ('module.encoder.cbhg.conv1d_banks.5.bn.weight', \n",
" 0.6030\n",
" 0.4659\n",
" 0.6145\n",
" 0.5868\n",
" 0.5053\n",
" 0.4299\n",
" 0.3208\n",
" 0.3690\n",
" 0.5187\n",
" 0.3643\n",
" 0.7580\n",
" 0.5170\n",
" -0.9788\n",
" 0.2888\n",
" 0.6778\n",
" 0.5030\n",
" 0.3522\n",
" 0.5321\n",
" 0.6273\n",
" -1.3146\n",
" 0.4277\n",
" 0.6141\n",
" 0.4835\n",
" 0.4332\n",
" 0.5083\n",
" -0.9616\n",
" -0.8252\n",
" 0.4086\n",
" -0.6273\n",
" 0.5303\n",
" 0.5253\n",
" 0.4767\n",
" 0.4248\n",
" 0.6602\n",
" 0.6277\n",
" 0.6253\n",
" 0.4188\n",
" 0.6715\n",
" 0.6525\n",
" 0.4297\n",
" 0.4657\n",
" 0.3448\n",
" 0.6934\n",
" -0.0343\n",
" 0.6080\n",
" 0.4010\n",
" 0.4177\n",
" 0.4304\n",
" 0.5196\n",
" -0.9563\n",
" 0.5729\n",
" 0.4634\n",
" 0.5252\n",
" 0.4574\n",
" 0.4260\n",
" 0.5545\n",
" 0.7378\n",
" 0.5902\n",
" -0.9966\n",
" 0.6326\n",
" 0.5971\n",
" -0.9012\n",
" -0.6216\n",
" 0.2051\n",
" 0.5022\n",
" 0.4865\n",
" -0.9215\n",
" 0.4763\n",
" 0.3403\n",
" 0.3322\n",
" -0.7515\n",
" 1.1560\n",
" 0.4566\n",
" 0.5261\n",
" 0.3933\n",
" 0.4992\n",
" 0.3358\n",
" 0.4127\n",
" 0.4077\n",
" 0.4432\n",
" 1.0589\n",
" 0.6539\n",
" 0.2347\n",
" -0.8491\n",
" 0.6595\n",
" 0.5311\n",
" 0.4118\n",
" 0.4477\n",
" 0.1726\n",
" 0.5200\n",
" 0.4053\n",
" 0.4654\n",
" 0.9625\n",
" 0.5017\n",
" 0.5881\n",
" 0.5774\n",
" 0.4825\n",
" 0.3396\n",
" -0.7531\n",
" 0.3112\n",
" 0.5963\n",
" 1.0316\n",
" 0.3974\n",
" 0.5853\n",
" 0.7602\n",
" 0.4758\n",
" 0.3991\n",
" 0.4226\n",
" 0.5176\n",
" 0.7534\n",
" 0.6088\n",
" 0.5584\n",
" -0.8560\n",
" 0.7328\n",
" 0.4891\n",
" -0.8217\n",
" 0.4753\n",
" 0.6604\n",
" 0.6666\n",
" 0.4886\n",
" 0.5125\n",
" 0.4264\n",
" 0.5448\n",
" -1.0820\n",
" 0.3960\n",
" 0.2083\n",
" 0.5247\n",
" 0.9695\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.5.bn.bias', \n",
" 0.0947\n",
" 0.0718\n",
" 0.0124\n",
" 0.2336\n",
" 0.0085\n",
" 0.1004\n",
" -0.0893\n",
" -0.0778\n",
" -0.0524\n",
" 0.0065\n",
" 0.1136\n",
" -0.0418\n",
" -0.1065\n",
" -0.0254\n",
" 0.1232\n",
" 0.0879\n",
" 0.0633\n",
" -0.0840\n",
" 0.1193\n",
" -0.2054\n",
" 0.1677\n",
" 0.2151\n",
" 0.0697\n",
" 0.0597\n",
" 0.0166\n",
" -0.1709\n",
" -0.1288\n",
" 0.0489\n",
" -0.1630\n",
" -0.0754\n",
" 0.0570\n",
" 0.0086\n",
" 0.1426\n",
" 0.0505\n",
" 0.0564\n",
" 0.2278\n",
" 0.0128\n",
" -0.0277\n",
" 0.0535\n",
" 0.0196\n",
" 0.0594\n",
" 0.0252\n",
" -0.0084\n",
" 0.0057\n",
" 0.0969\n",
" 0.0142\n",
" -0.1417\n",
" 0.1198\n",
" -0.1133\n",
" -0.2663\n",
" 0.2193\n",
" 0.0708\n",
" 0.0075\n",
" 0.0174\n",
" 0.0811\n",
" -0.0021\n",
" 0.0313\n",
" 0.1300\n",
" -0.1708\n",
" 0.0537\n",
" 0.1554\n",
" -0.1699\n",
" -0.1159\n",
" -0.0202\n",
" -0.0004\n",
" 0.0829\n",
" -0.2699\n",
" -0.0136\n",
" 0.0054\n",
" -0.0462\n",
" -0.1225\n",
" 0.0095\n",
" 0.0144\n",
" 0.1135\n",
" -0.0139\n",
" 0.0421\n",
" -0.0032\n",
" 0.0377\n",
" 0.0843\n",
" 0.0332\n",
" 0.1215\n",
" 0.3692\n",
" -0.0251\n",
" -0.1014\n",
" -0.1097\n",
" 0.0472\n",
" 0.1536\n",
" 0.0918\n",
" -0.0179\n",
" 0.1474\n",
" -0.0726\n",
" 0.0957\n",
" 0.1166\n",
" 0.0688\n",
" 0.2160\n",
" 0.0116\n",
" -0.0253\n",
" 0.1411\n",
" -0.0984\n",
" -0.0216\n",
" 0.1054\n",
" -0.0392\n",
" -0.1219\n",
" 0.1568\n",
" -0.0006\n",
" -0.0553\n",
" -0.0160\n",
" 0.0574\n",
" -0.0736\n",
" 0.0534\n",
" -0.0771\n",
" 0.0323\n",
" -0.1174\n",
" -0.0647\n",
" 0.0409\n",
" -0.0897\n",
" 0.1087\n",
" 0.0810\n",
" -0.0016\n",
" -0.0134\n",
" 0.0187\n",
" 0.0645\n",
" -0.0278\n",
" -0.1699\n",
" 0.0223\n",
" 0.0254\n",
" -0.1488\n",
" 0.0309\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.5.bn.running_mean', \n",
" 0.1942\n",
" 0.2407\n",
" 2.3295\n",
" 13.7009\n",
" 0.5646\n",
" 1.5938\n",
" 1.6236\n",
" 0.1412\n",
" 3.5567\n",
" 0.3877\n",
" 0.1246\n",
" 1.3773\n",
" 2.0049\n",
" 5.1180\n",
" 0.4043\n",
" 0.2196\n",
" 2.6233\n",
" 0.2074\n",
" 0.4685\n",
" 0.4912\n",
" 1.4852\n",
" 0.0517\n",
" 2.0695\n",
" 0.3175\n",
" 0.1819\n",
" 2.0328\n",
" 2.0154\n",
" 0.4518\n",
" 7.0997\n",
" 0.6767\n",
" 0.0989\n",
" 0.8559\n",
" 0.5069\n",
" 0.0173\n",
" 0.0892\n",
" 0.3716\n",
" 2.1047\n",
" 0.4246\n",
" 0.1018\n",
" 4.0117\n",
" 0.4722\n",
" 1.4483\n",
" 0.3713\n",
" 9.8769\n",
" 1.0078\n",
" 2.7833\n",
" 0.2142\n",
" 2.5666\n",
" 2.5710\n",
" 3.1552\n",
" 1.3968\n",
" 0.2538\n",
" 0.8166\n",
" 1.4437\n",
" 0.2308\n",
" 6.6636\n",
" 0.3067\n",
" 0.1399\n",
" 0.7262\n",
" 0.1478\n",
" 0.1166\n",
" 3.7425\n",
" 6.9665\n",
" 1.8447\n",
" 1.2830\n",
" 0.4066\n",
" 3.4474\n",
" 0.5367\n",
" 0.3763\n",
" 0.4006\n",
" 2.5741\n",
" 0.1998\n",
" 0.4160\n",
" 0.3257\n",
" 1.5232\n",
" 1.1630\n",
" 2.7245\n",
" 0.2250\n",
" 0.8890\n",
" 2.0377\n",
" 0.0878\n",
" 2.4357\n",
" 0.8960\n",
" 2.0837\n",
" 0.5346\n",
" 0.0699\n",
" 0.7732\n",
" 0.5608\n",
" 1.8463\n",
" 0.0790\n",
" 1.3423\n",
" 0.4863\n",
" 0.1751\n",
" 2.8209\n",
" 2.3684\n",
" 0.3946\n",
" 0.8917\n",
" 14.5403\n",
" 1.9912\n",
" 6.0808\n",
" 0.5597\n",
" 0.0064\n",
" 1.8138\n",
" 0.5429\n",
" 0.1226\n",
" 0.2695\n",
" 0.4319\n",
" 0.6293\n",
" 0.2789\n",
" 0.0554\n",
" 0.9388\n",
" 0.0294\n",
" 2.7917\n",
" 0.2053\n",
" 0.1704\n",
" 4.8849\n",
" 0.4043\n",
" 0.2905\n",
" 0.2785\n",
" 0.2442\n",
" 3.3915\n",
" 6.8654\n",
" 0.8866\n",
" 0.8732\n",
" 2.7530\n",
" 2.3496\n",
" 2.6061\n",
" 0.6980\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.5.bn.running_var', \n",
" 2.0262\n",
" 1.9987\n",
" 25.1144\n",
" 218.8765\n",
" 6.4417\n",
" 17.2455\n",
" 17.5415\n",
" 1.4495\n",
" 46.8464\n",
" 4.0630\n",
" 1.1017\n",
" 16.3569\n",
" 23.2124\n",
" 31.4073\n",
" 3.9895\n",
" 2.2963\n",
" 22.1562\n",
" 2.0646\n",
" 5.9942\n",
" 4.7428\n",
" 17.5209\n",
" 0.3373\n",
" 26.3400\n",
" 3.9097\n",
" 1.7637\n",
" 25.6737\n",
" 22.4007\n",
" 4.7676\n",
" 54.8449\n",
" 8.0765\n",
" 0.8915\n",
" 8.6571\n",
" 4.9478\n",
" 0.1151\n",
" 0.8361\n",
" 3.9047\n",
" 19.3890\n",
" 5.0134\n",
" 0.8813\n",
" 32.9457\n",
" 4.8735\n",
" 15.3827\n",
" 3.2114\n",
" 72.7250\n",
" 10.3798\n",
" 27.6761\n",
" 2.1794\n",
" 24.0510\n",
" 35.4656\n",
" 40.1592\n",
" 17.1983\n",
" 2.5397\n",
" 8.5297\n",
" 13.3604\n",
" 2.1418\n",
" 61.0993\n",
" 2.9829\n",
" 1.3570\n",
" 7.2358\n",
" 1.4686\n",
" 1.0055\n",
" 53.2624\n",
" 58.9634\n",
" 11.5873\n",
" 13.8819\n",
" 4.3137\n",
" 48.9352\n",
" 5.7693\n",
" 3.6650\n",
" 4.0847\n",
" 30.2679\n",
" 1.4583\n",
" 3.7447\n",
" 3.1868\n",
" 17.5012\n",
" 11.1999\n",
" 36.6523\n",
" 2.1900\n",
" 12.0475\n",
" 17.7696\n",
" 0.7518\n",
" 28.8415\n",
" 7.9658\n",
" 24.2708\n",
" 5.0903\n",
" 0.5693\n",
" 8.9742\n",
" 5.9398\n",
" 12.8828\n",
" 0.5220\n",
" 17.0810\n",
" 5.1503\n",
" 1.5296\n",
" 26.6620\n",
" 25.7122\n",
" 4.1311\n",
" 11.0452\n",
" 105.3546\n",
" 16.2668\n",
" 40.0044\n",
" 5.6596\n",
" 0.0321\n",
" 25.1323\n",
" 5.5465\n",
" 1.2754\n",
" 5.0395\n",
" 4.8464\n",
" 7.7836\n",
" 2.8487\n",
" 0.3995\n",
" 12.0627\n",
" 0.2450\n",
" 34.3101\n",
" 2.2691\n",
" 1.5937\n",
" 65.4531\n",
" 3.9816\n",
" 3.0409\n",
" 2.7536\n",
" 2.6018\n",
" 47.5258\n",
" 63.4379\n",
" 11.8568\n",
" 9.6248\n",
" 23.6316\n",
" 16.6635\n",
" 31.3495\n",
" 8.4266\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.6.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -4.5353e-03 4.5222e-03 -3.9971e-02 ... -3.5038e-02 4.8943e-02 -5.0395e-03\n",
" 8.4028e-02 2.2407e-02 -6.3263e-01 ... -2.4554e-01 -4.2537e-03 -8.9171e-01\n",
" -4.7564e-02 6.2109e-02 -9.9553e-01 ... 1.4646e-01 -9.9596e-01 1.6758e-01\n",
" ... ⋱ ... \n",
" 2.2037e-01 1.9275e-01 1.5566e-01 ... -4.8230e-01 -9.3068e-01 -1.2051e-01\n",
" -2.5592e-02 -6.7962e-01 -2.8601e-01 ... 1.0041e-01 -3.2003e-01 -2.3566e-02\n",
" 9.6592e-02 -1.9106e-01 8.4323e-02 ... -7.2522e-01 -4.6632e-02 1.1757e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" 3.8156e-02 3.8708e-02 9.7287e-03 ... 4.9475e-02 4.8088e-02 3.4232e-02\n",
" -1.2674e-01 1.4788e-01 -2.9398e-01 ... 1.5944e-01 -1.7241e-02 7.4101e-02\n",
" 3.7165e-01 -1.2560e-01 1.2577e-01 ... -1.2738e-01 5.0040e-01 -6.6209e-01\n",
" ... ⋱ ... \n",
" 1.1140e-01 2.7386e-01 -4.2877e-01 ... 2.7582e-01 9.3554e-02 -5.7552e-01\n",
" -5.0430e-01 1.2536e-01 -3.1027e-01 ... -4.4512e-01 -4.1321e-01 7.5062e-02\n",
" -2.2296e-01 9.1203e-02 -1.4282e-01 ... -1.0473e-01 2.4301e-01 -1.2898e-03\n",
" \n",
" ( 2 ,.,.) = \n",
" -3.0079e-02 1.5203e-02 -2.8322e-02 ... -4.0184e-03 -1.2454e-02 8.4558e-04\n",
" 6.6261e-02 -7.0814e-02 -6.4725e-02 ... 7.4598e-02 -5.3767e-01 -4.6577e-02\n",
" -1.0299e-01 -6.4324e-02 -9.7807e-02 ... -6.6077e-01 -6.5349e-02 -4.2513e-02\n",
" ... ⋱ ... \n",
" -2.4065e-01 2.6608e-01 1.7404e-01 ... -6.9059e-02 -4.1446e-01 9.7021e-02\n",
" -9.1595e-02 -2.3584e-01 1.2416e-01 ... -9.2408e-01 4.9623e-02 -5.6548e-01\n",
" -7.9593e-02 -9.2951e-02 -1.1617e-01 ... -4.8386e-02 -9.6230e-02 -1.4643e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 1.0336e-02 -2.2211e-03 3.0974e-02 ... 5.5323e-02 7.0989e-03 1.1988e-02\n",
" -3.3972e-02 -2.6190e-01 3.3510e-02 ... -2.2103e+00 -1.2093e+00 -8.1943e-02\n",
" 1.9794e-02 -1.1747e-01 2.1005e-01 ... -3.2863e-02 6.6548e-02 1.8791e-01\n",
" ... ⋱ ... \n",
" 1.8541e-01 2.1995e-01 -9.6276e-01 ... -1.6338e-01 -8.7571e-01 -1.0884e+00\n",
" 2.3457e-01 2.4633e-01 1.5244e-01 ... -2.2887e-01 -2.0436e-01 9.2099e-02\n",
" 7.3668e-02 -1.5229e-01 -2.5827e-01 ... -1.0859e-01 -4.0845e-01 -2.8507e-02\n",
" \n",
" (126,.,.) = \n",
" -1.6866e-02 2.1091e-02 -1.3386e-02 ... -4.4216e-03 6.1371e-02 -1.1978e-02\n",
" 5.1298e-02 -1.8507e-01 1.7350e-01 ... -6.8860e-01 1.3121e-01 1.1693e-01\n",
" -2.1713e-02 9.1121e-02 -8.1626e-01 ... -8.0668e-02 7.9635e-02 -1.6500e-01\n",
" ... ⋱ ... \n",
" 5.4700e-02 -1.4175e-01 7.1425e-02 ... -9.5701e-01 3.1120e-01 -2.1914e-02\n",
" -3.2772e-01 4.5213e-02 -4.7685e-01 ... -3.1668e-01 -3.9196e-01 2.9794e-02\n",
" 2.3587e-01 6.2199e-02 9.8133e-02 ... -2.6222e-01 -2.2871e-02 8.5439e-02\n",
" \n",
" (127,.,.) = \n",
" 3.3882e-02 -5.7220e-03 -2.2094e-02 ... 9.1597e-03 4.2177e-03 6.7870e-02\n",
" -1.4162e+00 -7.0018e-02 -7.7413e-01 ... -9.2951e-01 -1.7080e+00 -1.0842e-01\n",
" -2.1010e-03 1.1678e-01 -3.1630e-01 ... -3.0953e-01 2.2892e-01 -1.1174e+00\n",
" ... ⋱ ... \n",
" -6.8819e-02 -2.1103e-03 2.1246e-02 ... 1.1823e-01 -8.3776e-01 -1.3537e+00\n",
" -1.6399e-01 2.0398e-01 -8.5368e-01 ... -5.6074e-01 -5.9672e-01 1.0280e-01\n",
" 1.9300e-01 1.8914e-02 -8.1840e-02 ... 1.1959e-01 -3.3886e-01 -3.0645e-01\n",
" [torch.FloatTensor of size 128x128x7]),\n",
" ('module.encoder.cbhg.conv1d_banks.6.bn.weight', \n",
" 0.7607\n",
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" 0.5383\n",
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" 0.6085\n",
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" 0.6034\n",
" 0.4023\n",
" 0.4413\n",
" 0.3966\n",
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" -1.1406\n",
" 0.4644\n",
" 0.4746\n",
" 0.4408\n",
" -0.9712\n",
" 0.4288\n",
" 0.6129\n",
" 0.5061\n",
" 0.5056\n",
" 0.4656\n",
" -0.9311\n",
" 0.4196\n",
" 0.4411\n",
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" 0.6136\n",
" -0.6578\n",
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" 0.5747\n",
" 0.5351\n",
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" 0.4250\n",
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" 0.5735\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.6.bn.bias', \n",
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" -0.1710\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.6.bn.running_mean', \n",
" 0.1225\n",
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" 0.4293\n",
" 0.3980\n",
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" 5.5845\n",
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" 2.7031\n",
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" 1.5261\n",
" 5.5516\n",
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" 2.6043\n",
" 0.8857\n",
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" 0.7491\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.6.bn.running_var', \n",
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" 0.8977\n",
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" 1.2615\n",
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" 6.3970\n",
" 3.1219\n",
" 35.8959\n",
" 1.4659\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.7.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 5.8847e-03 2.1921e-03 -1.8377e-02 ... -1.3964e-02 2.6978e-02 5.5054e-02\n",
" 7.2680e-02 -3.6535e-01 -5.2221e-03 ... -2.3408e-01 1.2410e-01 3.1972e-03\n",
" 1.3844e-02 -1.1377e-01 1.9315e-02 ... 3.8549e-02 -1.6374e+00 4.1895e-01\n",
" ... ⋱ ... \n",
" -4.8199e-01 3.3490e-01 -3.2895e-01 ... 8.4339e-02 6.1372e-02 -1.5737e+00\n",
" -1.0041e+00 -1.5568e-01 5.7800e-02 ... -5.0289e-01 9.4830e-02 1.0988e-02\n",
" -1.4340e-01 -3.7784e-01 1.9994e-01 ... -1.7842e-01 -5.8743e-02 -7.0364e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" -3.3945e-02 -8.2994e-04 1.3010e-02 ... 1.9219e-02 -2.1708e-02 3.9321e-02\n",
" 3.4651e-02 -1.7901e-01 -5.5429e-01 ... -7.5145e-01 -4.6915e-01 6.6311e-02\n",
" 2.7764e-01 -9.3591e-02 1.3791e-01 ... -2.7145e-01 2.8122e-02 1.0651e-01\n",
" ... ⋱ ... \n",
" 8.7166e-02 1.5260e-01 -7.1763e-02 ... -1.3844e+00 -1.0487e+00 -1.2397e+00\n",
" -1.2803e-01 -3.3113e-02 -3.9552e-01 ... -3.1659e-01 1.0684e-01 8.3546e-02\n",
" -8.9448e-02 2.4670e-02 2.8182e-02 ... 1.6902e-01 -5.5595e-02 -2.6387e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 2.4514e-02 2.0854e-02 -3.0092e-02 ... 4.2989e-02 3.4699e-02 3.5149e-02\n",
" -8.7910e-02 -3.7414e-02 -1.6182e-02 ... 1.3356e-01 -3.4510e-01 2.9737e-01\n",
" -5.0063e-02 -2.8385e-01 2.0934e-01 ... 2.8240e-02 8.9445e-02 -7.5023e-01\n",
" ... ⋱ ... \n",
" -1.0467e-01 -2.0252e-01 -9.7439e-02 ... -1.9067e-03 7.2500e-02 -3.6290e-02\n",
" 5.2983e-01 3.4188e-02 -1.1855e-01 ... -2.9443e-02 -2.1767e-01 -1.4374e-01\n",
" 2.0587e-01 -5.5229e-02 1.2016e-01 ... 1.0737e-01 2.8937e-03 9.0145e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 2.3339e-02 -2.2911e-02 -2.5257e-02 ... 3.4837e-02 -3.6842e-03 -2.4066e-02\n",
" 1.7219e-01 2.6568e-01 3.3388e-02 ... -8.4869e-02 1.0888e-01 -1.6184e-01\n",
" 1.4101e-01 1.0440e-01 -1.5647e-01 ... 1.7188e-01 -1.0538e+00 -1.3552e+00\n",
" ... ⋱ ... \n",
" -3.3658e-01 1.9421e-01 7.1169e-04 ... -4.4340e-01 -1.4363e+00 1.1073e-01\n",
" -2.8200e-01 -2.7627e-01 -3.5717e-01 ... -2.6617e-01 1.8424e-01 -5.1155e-02\n",
" -2.2967e-01 -9.3827e-02 1.8522e-01 ... -3.8467e-01 -8.9247e-02 -5.5430e-02\n",
" \n",
" (126,.,.) = \n",
" -1.6671e-02 -4.0164e-02 -3.8903e-02 ... -6.3660e-02 -3.1307e-02 -2.3072e-02\n",
" -2.9091e-01 1.1981e-01 8.3795e-02 ... -1.5997e+00 -1.1918e+00 -9.8389e-02\n",
" 1.3939e-01 1.5886e-01 1.7142e-01 ... 2.3185e-01 -5.8920e-01 2.3799e-01\n",
" ... ⋱ ... \n",
" 3.5581e-02 2.9580e-02 1.4395e-01 ... -6.6605e-01 -1.4438e+00 -7.2258e-01\n",
" 1.3443e-02 -1.0530e-01 -6.6303e-01 ... -5.2410e-01 -1.6476e-01 9.5399e-02\n",
" 2.5848e-02 -8.6919e-02 -1.2343e-01 ... 7.9862e-02 -1.0104e-02 -3.2548e-01\n",
" \n",
" (127,.,.) = \n",
" 1.3345e-02 1.6564e-02 -3.3550e-02 ... 2.5938e-02 2.8583e-02 -4.1905e-02\n",
" 1.3643e-01 -1.3233e-01 1.6668e-01 ... 1.4648e-01 -1.8051e-01 -9.3971e-02\n",
" 7.5661e-02 1.2190e-01 -1.9221e-01 ... 6.9154e-03 -1.6507e-02 -5.3025e-02\n",
" ... ⋱ ... \n",
" 3.2565e-01 1.2659e-01 1.3699e-01 ... -1.9743e-01 2.6545e-01 -3.4281e-02\n",
" -1.7613e-02 -8.1578e-02 4.1549e-01 ... -1.9517e-01 4.2245e-01 2.1490e-02\n",
" 9.5571e-02 1.0512e-01 -6.3192e-02 ... 1.4061e-01 2.6262e-01 1.6268e-01\n",
" [torch.FloatTensor of size 128x128x8]),\n",
" ('module.encoder.cbhg.conv1d_banks.7.bn.weight', \n",
" 0.5201\n",
" 0.6178\n",
" 0.3503\n",
" 0.1448\n",
" 0.5527\n",
" 0.4999\n",
" 0.7059\n",
" 0.4651\n",
" 0.4145\n",
" 0.4550\n",
" 0.5447\n",
" 0.4034\n",
" 0.4155\n",
" 0.3661\n",
" 0.5640\n",
" 0.5221\n",
" 0.3899\n",
" 0.4972\n",
" 0.5214\n",
" 0.4538\n",
" 0.5328\n",
" -1.0370\n",
" 0.6178\n",
" 0.5419\n",
" 0.4244\n",
" 0.3987\n",
" -1.6089\n",
" 0.4248\n",
" 0.3864\n",
" 0.4433\n",
" 0.4740\n",
" 0.5513\n",
" 0.4550\n",
" -1.1776\n",
" 0.5307\n",
" 0.5215\n",
" 0.4541\n",
" 0.5152\n",
" 0.4265\n",
" -0.4415\n",
" 0.4885\n",
" 0.6703\n",
" 0.4037\n",
" 0.5493\n",
" 0.3952\n",
" 0.3893\n",
" 0.4978\n",
" 0.5512\n",
" 0.4581\n",
" 0.0155\n",
" 0.6011\n",
" 0.4262\n",
" 0.4914\n",
" 0.4226\n",
" 0.4978\n",
" 0.5835\n",
" 0.4875\n",
" 0.3945\n",
" 0.3939\n",
" 0.4874\n",
" 0.5940\n",
" 0.5797\n",
" -0.9385\n",
" 0.6759\n",
" 0.5902\n",
" 0.5815\n",
" 0.5256\n",
" 0.4608\n",
" -1.2700\n",
" 0.4835\n",
" 0.5862\n",
" 0.8845\n",
" 0.5304\n",
" 0.3843\n",
" 0.4911\n",
" 0.4653\n",
" -0.8797\n",
" 0.4928\n",
" -1.0461\n",
" 0.4720\n",
" 0.5692\n",
" -0.8213\n",
" 0.4002\n",
" 0.4373\n",
" 0.5114\n",
" 0.4222\n",
" 0.3675\n",
" -1.3332\n",
" 0.4836\n",
" 0.5117\n",
" 0.4860\n",
" 0.4630\n",
" 0.4095\n",
" -0.6982\n",
" -0.8360\n",
" 0.5048\n",
" 0.4621\n",
" 0.4235\n",
" -0.8588\n",
" 0.5175\n",
" 0.3910\n",
" 0.5467\n",
" 0.5042\n",
" 0.5353\n",
" 0.4100\n",
" -1.0143\n",
" 0.4884\n",
" 0.4789\n",
" 0.4557\n",
" 0.6047\n",
" 0.4890\n",
" 1.0135\n",
" 0.6491\n",
" -0.9885\n",
" 0.4902\n",
" 0.4262\n",
" 0.5985\n",
" 0.3811\n",
" 0.4982\n",
" 0.4380\n",
" -1.0503\n",
" 0.5028\n",
" 0.3959\n",
" -0.9950\n",
" 0.5104\n",
" 0.4080\n",
" 0.5989\n",
" -0.7140\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.7.bn.bias', \n",
" 0.0531\n",
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" -0.0226\n",
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" -0.0722\n",
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" 0.1540\n",
" 0.0093\n",
" 0.0824\n",
" -0.1027\n",
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" -0.0583\n",
" -0.2360\n",
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" -0.1012\n",
" -0.0647\n",
" -0.0001\n",
" 0.1090\n",
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" 0.0867\n",
" -0.1156\n",
" -0.0776\n",
" 0.0726\n",
" -0.0987\n",
" 0.2782\n",
" 0.0555\n",
" -0.0561\n",
" -0.0393\n",
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" -0.1254\n",
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" 0.0373\n",
" 0.0833\n",
" 0.1624\n",
" -0.0043\n",
" 0.1495\n",
" 0.0487\n",
" 0.0595\n",
" -0.0549\n",
" 0.1385\n",
" 0.0319\n",
" 0.0761\n",
" 0.1448\n",
" -0.0136\n",
" 0.0397\n",
" 0.2314\n",
" 0.2268\n",
" -0.0985\n",
" 0.1825\n",
" 0.1466\n",
" -0.0436\n",
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" -0.0878\n",
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" -0.0325\n",
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" -0.1996\n",
" -0.0028\n",
" -0.2038\n",
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" -0.1240\n",
" -0.0317\n",
" 0.0253\n",
" 0.0478\n",
" -0.0950\n",
" 0.0721\n",
" -0.2091\n",
" 0.0940\n",
" -0.1020\n",
" 0.0115\n",
" 0.0147\n",
" 0.1373\n",
" -0.1032\n",
" 0.0048\n",
" -0.1266\n",
" -0.1190\n",
" 0.1090\n",
" -0.0406\n",
" 0.1024\n",
" -0.1009\n",
" 0.0821\n",
" 0.0140\n",
" 0.2145\n",
" 0.0478\n",
" -0.2095\n",
" -0.1442\n",
" 0.0544\n",
" 0.0345\n",
" 0.0340\n",
" 0.0834\n",
" 0.2172\n",
" 0.1414\n",
" -0.1626\n",
" -0.0807\n",
" 0.0232\n",
" -0.0692\n",
" -0.0451\n",
" 0.0634\n",
" 0.0790\n",
" -0.1703\n",
" 0.0544\n",
" 0.0259\n",
" -0.2925\n",
" -0.1293\n",
" 0.0527\n",
" 0.0511\n",
" -0.0644\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.7.bn.running_mean', \n",
" 0.2812\n",
" 0.1372\n",
" 3.9745\n",
" 7.4301\n",
" 1.2966\n",
" 2.3002\n",
" 0.3036\n",
" 1.0330\n",
" 0.1696\n",
" 0.1970\n",
" 0.0372\n",
" 0.8095\n",
" 3.5538\n",
" 0.6015\n",
" 1.1094\n",
" 0.5394\n",
" 6.0354\n",
" 0.2902\n",
" 1.2992\n",
" 1.0459\n",
" 1.4696\n",
" 3.5347\n",
" 1.2122\n",
" 0.8080\n",
" 0.5515\n",
" 0.7807\n",
" 0.0896\n",
" 0.6803\n",
" 1.1137\n",
" 0.1049\n",
" 2.4879\n",
" 0.1218\n",
" 0.5865\n",
" 1.5523\n",
" 4.8728\n",
" 0.9130\n",
" 0.9491\n",
" 1.5586\n",
" 2.0178\n",
" 12.4710\n",
" 0.8012\n",
" 0.3510\n",
" 0.3879\n",
" 8.8085\n",
" 1.0802\n",
" 0.4705\n",
" 0.9743\n",
" 0.4803\n",
" 0.5677\n",
" 9.9005\n",
" 1.3111\n",
" 0.3241\n",
" 1.5443\n",
" 0.9569\n",
" 1.3462\n",
" 1.8252\n",
" 0.9787\n",
" 1.1744\n",
" 0.8573\n",
" 0.9252\n",
" 4.9456\n",
" 4.2871\n",
" 0.0392\n",
" 0.4906\n",
" 3.7855\n",
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" 0.8360\n",
" 0.8939\n",
" 0.3714\n",
" 0.2258\n",
" 2.8575\n",
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" 0.1251\n",
" 0.9596\n",
" 0.2072\n",
" 0.5053\n",
" 3.7698\n",
" 9.7333\n",
" 1.5940\n",
" 1.2681\n",
" 0.1128\n",
" 3.9079\n",
" 4.3071\n",
" 0.1252\n",
" 0.5050\n",
" 1.4095\n",
" 1.2890\n",
" 0.6643\n",
" 0.2945\n",
" 0.3837\n",
" 1.9824\n",
" 0.4402\n",
" 0.7092\n",
" 2.5530\n",
" 6.0500\n",
" 0.6629\n",
" 0.4099\n",
" 1.3019\n",
" 5.8735\n",
" 0.8943\n",
" 0.2518\n",
" 0.9939\n",
" 0.1958\n",
" 2.5477\n",
" 0.3094\n",
" 2.3750\n",
" 0.7993\n",
" 1.1749\n",
" 0.4016\n",
" 8.2615\n",
" 0.7854\n",
" 0.1583\n",
" 1.5999\n",
" 5.3653\n",
" 0.5013\n",
" 0.9868\n",
" 0.3480\n",
" 0.2088\n",
" 0.2505\n",
" 0.3646\n",
" 1.0942\n",
" 0.3739\n",
" 0.5132\n",
" 3.1107\n",
" 0.9551\n",
" 0.9754\n",
" 0.0634\n",
" 5.9613\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.7.bn.running_var', \n",
" 3.4528\n",
" 1.4335\n",
" 56.6181\n",
" 43.0498\n",
" 19.2615\n",
" 33.8639\n",
" 3.2992\n",
" 13.0646\n",
" 1.7917\n",
" 2.1548\n",
" 0.5802\n",
" 10.7251\n",
" 53.0717\n",
" 7.4029\n",
" 16.0876\n",
" 7.8325\n",
" 64.2025\n",
" 3.4285\n",
" 17.8234\n",
" 14.2309\n",
" 20.2142\n",
" 46.8463\n",
" 13.8736\n",
" 11.6845\n",
" 6.8415\n",
" 10.1249\n",
" 0.5939\n",
" 7.8891\n",
" 14.9711\n",
" 1.2082\n",
" 26.2391\n",
" 1.4065\n",
" 7.8775\n",
" 21.0462\n",
" 59.2802\n",
" 12.7272\n",
" 15.2322\n",
" 23.1035\n",
" 29.2466\n",
" 100.4376\n",
" 11.8395\n",
" 4.3766\n",
" 4.0224\n",
" 99.0680\n",
" 14.3279\n",
" 4.6216\n",
" 10.4203\n",
" 7.0414\n",
" 7.9117\n",
" 88.7863\n",
" 14.2661\n",
" 3.8882\n",
" 23.2832\n",
" 12.0185\n",
" 20.1529\n",
" 22.3754\n",
" 13.8920\n",
" 15.9952\n",
" 10.1813\n",
" 13.3677\n",
" 67.4268\n",
" 49.7770\n",
" 0.2859\n",
" 7.1800\n",
" 45.6419\n",
" 2.0598\n",
" 11.4943\n",
" 10.0566\n",
" 3.6953\n",
" 2.3665\n",
" 36.3690\n",
" 2.9168\n",
" 1.4601\n",
" 12.4855\n",
" 2.7109\n",
" 6.1154\n",
" 47.0909\n",
" 84.9703\n",
" 28.9722\n",
" 17.3121\n",
" 1.7708\n",
" 46.1098\n",
" 40.3095\n",
" 1.3421\n",
" 6.2969\n",
" 19.3591\n",
" 18.4596\n",
" 8.4604\n",
" 3.7825\n",
" 4.2503\n",
" 28.9321\n",
" 4.7093\n",
" 9.0993\n",
" 26.3167\n",
" 79.0112\n",
" 8.9691\n",
" 4.0326\n",
" 19.4620\n",
" 78.8674\n",
" 12.4432\n",
" 3.5051\n",
" 12.4378\n",
" 2.4673\n",
" 29.6752\n",
" 3.7716\n",
" 32.0126\n",
" 10.5445\n",
" 13.3852\n",
" 5.1200\n",
" 84.1416\n",
" 12.3769\n",
" 1.6237\n",
" 19.6032\n",
" 71.8491\n",
" 5.8113\n",
" 10.7161\n",
" 4.0810\n",
" 2.1904\n",
" 2.5760\n",
" 5.0541\n",
" 12.6978\n",
" 4.9397\n",
" 5.0230\n",
" 37.5503\n",
" 12.6321\n",
" 13.6513\n",
" 0.5706\n",
" 66.9323\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.8.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -2.7547e-02 4.2572e-02 4.9609e-02 ... 3.9734e-02 4.3074e-02 3.7359e-02\n",
" 7.7272e-02 1.5924e-01 1.1967e-01 ... -1.0723e+00 -1.3182e+00 8.4199e-02\n",
" 1.2160e-01 -2.6351e-01 -9.3865e-02 ... 1.9552e-01 3.4170e-01 -3.8920e-01\n",
" ... ⋱ ... \n",
" 8.6547e-02 1.8861e-02 1.8739e-01 ... -1.3392e+00 1.6523e-01 -7.8392e-01\n",
" 6.9175e-02 5.4181e-02 2.3608e-01 ... -6.6663e-01 -8.3389e-02 -2.4729e-01\n",
" -1.6154e-01 -5.3170e-02 7.6704e-02 ... -8.9796e-02 -4.5192e-02 -1.7497e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" 2.0992e-02 -6.3350e-03 5.8229e-03 ... -7.8143e-03 1.5739e-02 9.7577e-04\n",
" -6.3255e-02 1.6842e-01 2.9652e-01 ... -1.1351e+00 2.6696e-02 -2.3831e-01\n",
" -7.5772e-03 4.0876e-01 2.8722e-02 ... -3.6409e-01 1.6402e-02 6.1327e-02\n",
" ... ⋱ ... \n",
" 4.7118e-03 4.9662e-02 -1.0712e-01 ... 2.1898e-01 2.2844e-01 4.2636e-01\n",
" -1.5443e-01 -4.4623e-02 -4.2821e-02 ... 3.0447e-01 -1.1925e+00 -1.1519e-01\n",
" -6.3182e-02 8.5808e-02 -1.1307e-01 ... 5.1514e-02 -1.5927e-01 -2.3402e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" -8.6872e-03 9.8962e-03 -1.3881e-02 ... 6.4804e-03 1.7940e-02 -1.6702e-02\n",
" -5.5718e-02 -3.8603e-02 3.3173e-01 ... -5.4399e-02 -2.6046e-02 -1.8899e-01\n",
" 1.7230e-01 -3.0073e-01 1.2899e-01 ... 1.5112e-01 -2.3045e-01 -2.2903e-01\n",
" ... ⋱ ... \n",
" -6.5743e-02 -4.2672e-03 1.5176e-01 ... 6.4832e-03 1.4361e-01 3.0495e-02\n",
" 1.7581e-01 -1.3613e-01 -1.2332e-01 ... -1.2568e-01 -4.6832e-03 -2.4509e-01\n",
" -4.4992e-02 -1.2710e-01 1.3147e-02 ... -3.4621e-02 2.4574e-02 -4.5390e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -1.7292e-02 -7.6999e-03 1.0731e-02 ... 6.0297e-03 3.7521e-03 2.6006e-02\n",
" -7.9919e-02 -4.9393e-02 -5.8662e-01 ... -3.1168e-01 -1.3692e+00 -9.1817e-01\n",
" -3.7842e-01 5.7602e-02 -7.9871e-02 ... 9.0100e-03 -9.7410e-02 5.3491e-02\n",
" ... ⋱ ... \n",
" -2.0529e-01 6.3498e-02 2.7442e-02 ... -7.3926e-01 1.5999e-01 -1.1082e-01\n",
" -2.1393e-01 1.3996e-01 -7.4514e-02 ... -1.9744e-01 -4.8600e-01 -4.3896e-01\n",
" 1.2696e-02 -1.9454e-01 5.5097e-02 ... -9.6668e-03 -7.0573e-01 -4.2450e-01\n",
" \n",
" (126,.,.) = \n",
" 9.5369e-03 -1.4266e-02 -9.3971e-03 ... 1.1653e-02 -4.1660e-03 1.2811e-02\n",
" 1.8217e-01 2.1676e-02 -3.0760e-01 ... 1.6222e-01 1.0926e-01 -4.7690e-02\n",
" 5.3789e-02 -2.5205e-01 2.3654e-01 ... -5.4497e-03 7.4248e-02 -2.2669e-01\n",
" ... ⋱ ... \n",
" -1.6270e-01 -8.9960e-02 -6.6290e-02 ... 5.3901e-02 2.5797e-04 7.1787e-01\n",
" -1.0061e-01 1.4840e-01 -1.0621e-01 ... -5.7225e-01 3.4818e-02 4.1044e-01\n",
" -3.5203e-02 -7.5935e-03 8.3569e-02 ... 1.1512e-01 1.9343e-02 -8.4515e-02\n",
" \n",
" (127,.,.) = \n",
" 1.7825e-02 5.7461e-03 -5.2420e-02 ... -8.4316e-03 3.7530e-02 7.4160e-03\n",
" -7.5303e-01 2.5693e-01 -5.4925e-01 ... -1.6473e-01 9.0183e-03 -1.2218e-01\n",
" -3.1759e-01 5.5704e-02 -2.5702e-01 ... 1.2007e-01 -5.1170e-01 -5.0482e-01\n",
" ... ⋱ ... \n",
" 7.2999e-02 2.4884e-01 -6.3399e-01 ... -1.0819e-01 -8.2761e-01 -3.9823e-02\n",
" -6.4678e-02 2.1777e-01 1.4814e-01 ... -2.4322e-01 2.4405e-01 -5.4170e-01\n",
" 1.5825e-01 -1.0545e-01 8.2131e-02 ... 3.3050e-01 -3.3931e-01 -6.4139e-02\n",
" [torch.FloatTensor of size 128x128x9]),\n",
" ('module.encoder.cbhg.conv1d_banks.8.bn.weight', \n",
" 0.5771\n",
" 0.4581\n",
" -0.7716\n",
" 0.6157\n",
" -0.0321\n",
" 0.5181\n",
" -0.9333\n",
" 0.9233\n",
" 0.4347\n",
" 0.4704\n",
" -1.3071\n",
" 0.4834\n",
" 0.4864\n",
" 0.3935\n",
" 0.4802\n",
" 0.4552\n",
" 0.4248\n",
" 0.5687\n",
" 0.4133\n",
" 0.5554\n",
" 0.5055\n",
" 0.5408\n",
" 0.4969\n",
" 0.4613\n",
" -0.9117\n",
" 0.6503\n",
" 0.3440\n",
" 0.4934\n",
" 0.4743\n",
" 0.7277\n",
" 0.5781\n",
" -0.9944\n",
" 0.4250\n",
" 0.4817\n",
" 0.4396\n",
" 0.6737\n",
" 0.4569\n",
" 0.4752\n",
" 0.4585\n",
" 0.4791\n",
" 0.7359\n",
" 0.5473\n",
" 0.5542\n",
" 0.8879\n",
" 0.4969\n",
" 0.4156\n",
" 0.4636\n",
" 0.5663\n",
" 0.6065\n",
" 0.4312\n",
" 0.4343\n",
" -1.1273\n",
" -1.2112\n",
" 0.4511\n",
" -1.0567\n",
" 0.4800\n",
" 0.7169\n",
" 0.6837\n",
" 0.4633\n",
" 0.4376\n",
" 0.4631\n",
" 0.3726\n",
" 0.4705\n",
" 0.4251\n",
" -0.7982\n",
" -1.0721\n",
" 0.6287\n",
" 0.3680\n",
" 0.4368\n",
" 0.4333\n",
" -0.9332\n",
" 0.3998\n",
" 0.4077\n",
" 0.4922\n",
" 0.4723\n",
" 0.5908\n",
" 0.5140\n",
" -0.8896\n",
" -0.7219\n",
" 0.4918\n",
" 0.5012\n",
" 0.4491\n",
" 0.3801\n",
" 0.3578\n",
" 0.3361\n",
" -0.8209\n",
" 0.5648\n",
" 0.5712\n",
" 0.4660\n",
" 0.5767\n",
" -0.9550\n",
" 0.5229\n",
" 1.1241\n",
" 0.4727\n",
" 0.4580\n",
" 0.4395\n",
" 0.4749\n",
" 0.4501\n",
" 0.4727\n",
" 0.4406\n",
" -0.0748\n",
" 0.5233\n",
" 0.3423\n",
" 0.5639\n",
" 0.5692\n",
" 0.6152\n",
" 0.4194\n",
" -1.0430\n",
" -0.9918\n",
" 0.5580\n",
" 0.4808\n",
" 0.4698\n",
" 0.5428\n",
" 0.4862\n",
" 0.4849\n",
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" 0.4148\n",
" 0.6059\n",
" 0.3756\n",
" 0.4541\n",
" 0.4012\n",
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" -1.0728\n",
" 0.4493\n",
" 0.5653\n",
" 0.5266\n",
" -0.7840\n",
" 0.5118\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.8.bn.bias', \n",
" 0.0501\n",
" -0.0455\n",
" -0.1282\n",
" 0.0573\n",
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" -0.1950\n",
" -0.0008\n",
" 0.0860\n",
" 0.0740\n",
" -0.0304\n",
" 0.0451\n",
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" -0.0701\n",
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" -0.0170\n",
" -0.0699\n",
" 0.2331\n",
" 0.0394\n",
" 0.0186\n",
" -0.0887\n",
" 0.1286\n",
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" -0.3693\n",
" 0.2549\n",
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" -0.0266\n",
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" 0.1036\n",
" -0.0043\n",
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" 0.1415\n",
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" 0.1490\n",
" 0.1656\n",
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" -0.0647\n",
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" -0.0566\n",
" 0.1294\n",
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" -0.0811\n",
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" -0.1212\n",
" -0.2811\n",
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" -0.0276\n",
" 0.0304\n",
" -0.2490\n",
" -0.0301\n",
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" -0.0490\n",
" -0.0082\n",
" 0.0151\n",
" 0.0540\n",
" -0.0843\n",
" 0.2147\n",
" 0.1075\n",
" 0.0691\n",
" 0.0812\n",
" -0.1074\n",
" 0.0371\n",
" 0.0939\n",
" 0.0553\n",
" 0.0268\n",
" -0.0289\n",
" 0.0969\n",
" 0.0376\n",
" 0.0850\n",
" 0.0560\n",
" -0.0032\n",
" 0.1189\n",
" -0.1336\n",
" 0.1118\n",
" 0.0979\n",
" -0.1019\n",
" 0.0585\n",
" -0.1189\n",
" -0.2122\n",
" 0.0355\n",
" 0.0324\n",
" 0.1024\n",
" -0.0053\n",
" 0.0846\n",
" -0.0164\n",
" 0.0347\n",
" -0.0575\n",
" 0.1198\n",
" 0.0437\n",
" 0.0006\n",
" 0.0076\n",
" 0.0700\n",
" -0.3651\n",
" 0.1086\n",
" -0.0448\n",
" 0.1511\n",
" -0.1061\n",
" 0.0879\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.8.bn.running_mean', \n",
" 0.2172\n",
" 1.0771\n",
" 4.1651\n",
" 0.9412\n",
" 9.1795\n",
" 0.7024\n",
" 4.9453\n",
" 0.0088\n",
" 0.4241\n",
" 0.5401\n",
" 0.4936\n",
" 0.9792\n",
" 0.2949\n",
" 0.4522\n",
" 1.2292\n",
" 0.4527\n",
" 0.2819\n",
" 0.3859\n",
" 0.1360\n",
" 5.6269\n",
" 1.4467\n",
" 0.9929\n",
" 0.6515\n",
" 0.1727\n",
" 1.0151\n",
" 0.8062\n",
" 0.8452\n",
" 0.2774\n",
" 1.3303\n",
" 1.9343\n",
" 0.2595\n",
" 7.0958\n",
" 1.3832\n",
" 0.1969\n",
" 1.2018\n",
" 0.2215\n",
" 0.3508\n",
" 0.1674\n",
" 0.1257\n",
" 0.6598\n",
" 0.2392\n",
" 0.0863\n",
" 1.0187\n",
" 0.2623\n",
" 2.1649\n",
" 0.8956\n",
" 1.5223\n",
" 0.0435\n",
" 0.5574\n",
" 0.6954\n",
" 0.8634\n",
" 2.5703\n",
" 1.4503\n",
" 1.2198\n",
" 2.5609\n",
" 0.5472\n",
" 0.1622\n",
" 0.7101\n",
" 0.7225\n",
" 0.1451\n",
" 0.8528\n",
" 1.9435\n",
" 0.5099\n",
" 0.2758\n",
" 7.3982\n",
" 1.0463\n",
" 1.3533\n",
" 0.1834\n",
" 0.3139\n",
" 1.3081\n",
" 9.1900\n",
" 1.7530\n",
" 0.3186\n",
" 0.0864\n",
" 0.3088\n",
" 3.5589\n",
" 3.8022\n",
" 4.5939\n",
" 0.1067\n",
" 2.4051\n",
" 1.6988\n",
" 3.5461\n",
" 1.2979\n",
" 0.2601\n",
" 0.2093\n",
" 0.6377\n",
" 0.9761\n",
" 0.7301\n",
" 0.8001\n",
" 0.1085\n",
" 2.1115\n",
" 0.2482\n",
" 0.0415\n",
" 0.0286\n",
" 0.4192\n",
" 0.9545\n",
" 0.8663\n",
" 0.3971\n",
" 1.4581\n",
" 0.2442\n",
" 8.4836\n",
" 0.1308\n",
" 1.3314\n",
" 0.4853\n",
" 0.2627\n",
" 20.8991\n",
" 0.4634\n",
" 6.1021\n",
" 3.4489\n",
" 1.1361\n",
" 1.6796\n",
" 0.4814\n",
" 0.1891\n",
" 0.5700\n",
" 0.7645\n",
" 0.5785\n",
" 0.9796\n",
" 0.2983\n",
" 2.0324\n",
" 0.8786\n",
" 0.2386\n",
" 1.3299\n",
" 3.0389\n",
" 0.8985\n",
" 0.3829\n",
" 0.1680\n",
" 6.3584\n",
" 0.9019\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.8.bn.running_var', \n",
" 2.6072\n",
" 15.8986\n",
" 41.4874\n",
" 12.6203\n",
" 120.1542\n",
" 9.2696\n",
" 69.7438\n",
" 0.1051\n",
" 5.7360\n",
" 7.4304\n",
" 5.7254\n",
" 13.7302\n",
" 3.6712\n",
" 5.7503\n",
" 19.8554\n",
" 5.4608\n",
" 3.6343\n",
" 4.9982\n",
" 1.3920\n",
" 56.8145\n",
" 23.1102\n",
" 13.2925\n",
" 8.4560\n",
" 2.5918\n",
" 14.3851\n",
" 12.5008\n",
" 11.4232\n",
" 3.0210\n",
" 22.5177\n",
" 24.3255\n",
" 3.4395\n",
" 105.0245\n",
" 20.6933\n",
" 2.8084\n",
" 18.2451\n",
" 3.1466\n",
" 4.5639\n",
" 2.3411\n",
" 1.3012\n",
" 9.6010\n",
" 3.1274\n",
" 1.0201\n",
" 16.0106\n",
" 4.2138\n",
" 34.5435\n",
" 12.2854\n",
" 23.6870\n",
" 0.5350\n",
" 7.4291\n",
" 8.9021\n",
" 11.7848\n",
" 36.8306\n",
" 20.2813\n",
" 17.7479\n",
" 36.3394\n",
" 7.2768\n",
" 2.1176\n",
" 10.1342\n",
" 11.8166\n",
" 2.0295\n",
" 10.7391\n",
" 28.6486\n",
" 6.8892\n",
" 4.2384\n",
" 101.8086\n",
" 10.5774\n",
" 15.8857\n",
" 2.3810\n",
" 3.1255\n",
" 19.9336\n",
" 109.9822\n",
" 27.0445\n",
" 3.5758\n",
" 1.2688\n",
" 4.0835\n",
" 55.7266\n",
" 59.2590\n",
" 59.2517\n",
" 1.0412\n",
" 31.4357\n",
" 22.5261\n",
" 39.3778\n",
" 23.9771\n",
" 1.8874\n",
" 1.7850\n",
" 6.1222\n",
" 13.9891\n",
" 8.8358\n",
" 11.9521\n",
" 0.9764\n",
" 29.9719\n",
" 3.0948\n",
" 0.4055\n",
" 0.3364\n",
" 4.8352\n",
" 13.7660\n",
" 12.5649\n",
" 5.3636\n",
" 24.2606\n",
" 3.5150\n",
" 38.5196\n",
" 1.5219\n",
" 13.0963\n",
" 6.5039\n",
" 3.6606\n",
" 184.7602\n",
" 7.0112\n",
" 75.9883\n",
" 56.8520\n",
" 17.2093\n",
" 27.7894\n",
" 6.7595\n",
" 2.5488\n",
" 8.0841\n",
" 10.2645\n",
" 7.5262\n",
" 12.5878\n",
" 3.9603\n",
" 28.3046\n",
" 11.7080\n",
" 2.7740\n",
" 20.5979\n",
" 48.2758\n",
" 11.8036\n",
" 5.0028\n",
" 1.9099\n",
" 58.3826\n",
" 12.9609\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.9.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -1.2490e-03 -2.1708e-02 -1.3717e-02 ... -3.0470e-02 2.3697e-02 -2.0284e-02\n",
" 5.8066e-04 -1.5938e-01 1.0033e-01 ... -1.2398e-01 7.3970e-02 -2.7781e-01\n",
" 5.9249e-03 4.6126e-02 1.9371e-02 ... 3.9461e-01 -4.0300e-01 -8.3866e-02\n",
" ... ⋱ ... \n",
" 2.8160e-01 3.5017e-01 4.8683e-03 ... -4.4023e-01 -1.8014e+00 1.0488e-01\n",
" -2.9543e-01 9.8797e-02 -4.6013e-02 ... -1.5038e-01 1.5641e-01 -1.1150e+00\n",
" -1.8047e-01 4.8216e-02 -8.1360e-02 ... -7.3457e-02 -1.7689e-01 1.3239e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.8107e-02 -1.6579e-02 -2.2401e-02 ... -3.5960e-03 2.1527e-02 1.0929e-02\n",
" -1.8054e-01 -2.7563e-01 4.2408e-02 ... 3.0541e-02 -4.6706e-02 -1.8934e-01\n",
" -1.1431e-01 2.2401e-01 -2.3183e-01 ... 2.9956e-02 -2.6556e-02 4.7747e-02\n",
" ... ⋱ ... \n",
" -1.4706e-01 -3.5813e-02 3.4498e-01 ... -5.3065e-02 3.5055e-03 -4.3279e-02\n",
" 6.3806e-02 -1.0685e-01 1.2551e-01 ... 1.1024e-01 1.9199e-01 2.5452e-01\n",
" -2.1525e-02 -5.1525e-02 1.2442e-02 ... 2.5958e-02 -6.9614e-02 1.0687e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 2.2546e-02 3.1870e-02 6.1550e-03 ... 2.5899e-02 2.4231e-03 -2.4090e-02\n",
" 1.6648e-01 -2.2620e-01 1.8013e-03 ... 2.6781e-01 -2.2226e-01 -2.3612e-01\n",
" -2.5657e-01 1.0353e-02 6.2530e-02 ... 9.9296e-02 2.0786e-01 3.0163e-01\n",
" ... ⋱ ... \n",
" -5.6254e-01 -1.4620e-01 -1.5079e-01 ... -1.5648e-02 1.4819e-01 -2.9422e-01\n",
" 7.9525e-02 4.4902e-01 -1.9844e-01 ... 2.4591e-01 -2.6186e-02 9.1251e-02\n",
" -2.2625e-02 -3.3239e-01 5.0177e-02 ... -1.7797e-01 1.0420e-01 -4.0915e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 1.6619e-02 -1.2193e-02 1.8705e-02 ... -3.8572e-02 1.2710e-02 -4.4064e-03\n",
" -9.2771e-03 -2.2271e-01 1.7887e-01 ... 1.1817e-01 -1.3845e-01 1.2891e-01\n",
" -3.6453e-02 -2.4411e-01 3.2742e-01 ... 2.4662e-01 -1.0074e-01 -7.5640e-01\n",
" ... ⋱ ... \n",
" 1.5101e-01 4.6638e-02 -4.4681e-01 ... -2.7759e-01 -2.9360e-01 -4.4486e-03\n",
" 5.1798e-01 -5.7905e-01 -5.9879e-01 ... 1.4691e-01 3.9102e-01 -2.4114e-02\n",
" -4.9070e-02 7.3786e-02 1.1952e-01 ... 6.9462e-02 -4.3941e-02 -1.3187e-01\n",
" \n",
" (126,.,.) = \n",
" -2.0730e-02 -2.2372e-02 -1.4065e-02 ... -6.3372e-02 3.2751e-02 5.6936e-02\n",
" -1.6303e-01 -3.9686e-01 4.6270e-02 ... -8.9372e-02 -1.7251e-01 1.2557e-01\n",
" 3.6537e-02 1.4654e-01 5.6433e-01 ... 3.5981e-01 4.9119e-02 -1.3890e-01\n",
" ... ⋱ ... \n",
" -1.7771e-01 -1.9284e-01 3.4713e-01 ... 1.7397e-01 -3.4972e-02 4.2198e-01\n",
" -3.6182e-01 -2.9011e-01 -8.5047e-01 ... 2.9102e-02 -8.1940e-01 6.1122e-02\n",
" 4.3997e-02 1.5453e-01 -7.1149e-02 ... -5.7751e-02 1.6488e-01 -2.2338e-01\n",
" \n",
" (127,.,.) = \n",
" -2.2192e-02 -2.3334e-02 -1.8660e-02 ... -1.6811e-02 1.4472e-02 -2.1724e-02\n",
" -3.5289e-01 7.6216e-02 1.3014e-01 ... 3.1498e-02 1.8133e-01 -8.8622e-02\n",
" 2.3091e-01 -7.8763e-02 1.1455e-01 ... -4.8957e-02 -2.1180e-02 9.7200e-02\n",
" ... ⋱ ... \n",
" -1.1430e-01 -9.1477e-02 5.9393e-02 ... -7.1157e-02 -3.4201e-02 -7.4520e-02\n",
" 2.3236e-01 -9.3504e-02 8.0771e-02 ... -1.7873e-01 -3.8356e-02 -7.7936e-02\n",
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" [torch.FloatTensor of size 128x128x10]),\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.9.bn.bias', \n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.9.bn.running_mean', \n",
" 6.5877e-01\n",
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" 1.2301e-01\n",
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" 7.7597e-01\n",
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" 5.0649e-01\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.9.bn.running_var', \n",
" 1.1393e+01\n",
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" 7.4962e+00\n",
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" 4.0454e+01\n",
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" 1.9501e+01\n",
" 1.6277e+01\n",
" 7.7052e+00\n",
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" 4.5366e+00\n",
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" 1.0230e+00\n",
" 3.0405e+00\n",
" 1.2984e+01\n",
" 1.7935e+01\n",
" 9.7486e+00\n",
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" 5.4263e+01\n",
" 1.4682e+01\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.10.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 3.1965e-02 -2.1600e-02 -1.0129e-02 ... -3.9500e-02 2.4110e-02 -5.2788e-02\n",
" -3.4690e-01 -2.2403e-01 -1.4392e-01 ... 1.9043e-01 -4.2190e-02 9.6729e-02\n",
" -5.6671e-02 8.6796e-02 4.9753e-02 ... 4.1030e-01 -5.7082e-02 -2.4434e-01\n",
" ... ⋱ ... \n",
" -3.9421e-01 -3.9091e-01 1.9921e-01 ... -5.9211e-04 7.9745e-02 2.5677e-01\n",
" 5.6460e-02 -4.6051e-01 -7.2606e-01 ... 1.4965e-01 2.2783e-02 2.5805e-01\n",
" -6.5163e-02 -6.0904e-02 -1.0758e-01 ... -1.2326e-01 1.9627e-01 5.3745e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.1012e-02 -2.4141e-02 7.4641e-03 ... -3.5029e-02 2.1609e-02 2.7473e-02\n",
" 6.4160e-02 -4.5087e-02 2.4176e-02 ... -2.1199e+00 1.6511e-01 7.0646e-02\n",
" -2.0581e-02 -3.0219e-01 2.2424e-01 ... -1.9432e+00 -2.2556e-02 2.3356e-01\n",
" ... ⋱ ... \n",
" 3.6412e-02 8.1937e-02 -3.6133e-01 ... -1.4206e-01 -1.0086e-01 3.7693e-03\n",
" -1.2741e-01 2.0047e-01 -3.4011e-01 ... -2.2786e-01 9.9893e-02 -9.1123e-02\n",
" 4.0323e-02 -6.2912e-02 -1.3398e-01 ... 1.2671e-01 -3.4339e-01 5.6047e-03\n",
" \n",
" ( 2 ,.,.) = \n",
" 2.4882e-02 6.8116e-03 -2.3403e-03 ... 1.7273e-02 -3.0395e-02 1.5216e-02\n",
" -7.1228e-02 1.7549e-02 1.7411e-01 ... -3.0658e-01 -3.1027e-01 -1.8680e-02\n",
" 2.0702e-02 3.8690e-01 3.5982e-01 ... -1.4068e-02 4.9060e-01 -6.0749e-01\n",
" ... ⋱ ... \n",
" -3.4607e-01 1.7243e-01 -2.9192e-01 ... -1.2063e-01 -6.2334e-01 1.5975e-01\n",
" 4.4745e-02 -6.6337e-01 9.9555e-02 ... 1.0091e-01 -5.8471e-01 -6.7909e-01\n",
" -3.9671e-01 3.0501e-02 -2.3217e-01 ... 5.8709e-02 -1.5712e-01 -1.7326e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 8.0183e-04 4.9156e-02 3.7375e-02 ... 3.8611e-02 -2.6888e-02 2.1561e-02\n",
" 2.7643e-01 -4.8574e-01 3.0004e-01 ... -5.0056e-01 1.2600e-01 6.9725e-02\n",
" -1.2696e-01 -7.3011e-01 -2.5322e-01 ... 1.9872e-01 -4.8887e-01 3.7973e-01\n",
" ... ⋱ ... \n",
" -5.3998e-01 9.9488e-02 5.8411e-02 ... -1.0019e+00 -3.1663e-01 -9.8524e-02\n",
" -2.3971e-01 6.2732e-02 -5.4200e-01 ... 1.1759e-01 -1.0818e+00 -4.4208e-01\n",
" -5.9369e-03 -2.3910e-02 -3.4175e-02 ... -4.2960e-01 1.6119e-01 -1.5830e-01\n",
" \n",
" (126,.,.) = \n",
" 3.0219e-02 -1.9569e-02 2.2828e-02 ... -4.9221e-03 -1.5746e-04 1.6835e-03\n",
" -5.2897e-02 -1.0896e+00 -2.5633e-02 ... -1.3852e+00 8.2560e-02 -3.2648e-01\n",
" 1.7529e-01 3.1022e-01 7.6865e-02 ... -6.4377e-01 -1.1810e+00 -5.8760e-03\n",
" ... ⋱ ... \n",
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" 9.4663e-02 -1.5956e-02 4.3235e-03 ... 6.6401e-02 7.0955e-02 -9.5309e-02\n",
" \n",
" (127,.,.) = \n",
" 7.3776e-03 -1.5134e-02 -2.4655e-02 ... 3.2836e-02 2.8032e-03 8.1508e-03\n",
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" ... ⋱ ... \n",
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" 4.5081e-02 -8.4197e-03 -2.9812e-01 ... 9.3342e-02 -2.5426e-01 6.9766e-02\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.10.bn.running_mean', \n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.10.bn.running_var', \n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.11.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 1.4652e-02 5.3001e-03 1.0720e-03 ... 1.5744e-02 1.2328e-02 1.4525e-02\n",
" 7.5329e-02 -1.8212e-01 -5.1388e-01 ... -1.1485e+00 -8.6555e-02 9.2271e-02\n",
" -1.5347e-01 -1.8767e-01 3.9370e-02 ... -7.1084e-02 6.2531e-02 -1.3709e-01\n",
" ... ⋱ ... \n",
" -7.7978e-02 -2.1314e-02 4.5352e-02 ... -1.2343e-02 -3.4504e-01 -8.0914e-03\n",
" -6.4026e-01 6.0411e-02 -9.7488e-01 ... -2.4730e-01 -3.6128e-01 1.5796e-02\n",
" -1.0371e-01 -1.2962e-01 3.2543e-01 ... 4.1171e-03 -5.8695e-01 -6.4797e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.0019e-02 -2.5829e-02 4.0702e-03 ... -3.8123e-02 8.5839e-04 -1.2530e-02\n",
" 9.8703e-02 2.6438e-01 -2.0426e-02 ... -1.3528e+00 3.5872e-02 6.7084e-02\n",
" -8.0820e-03 -7.2237e-02 -2.2399e-01 ... -5.5380e-02 -2.0954e-01 -3.6943e-01\n",
" ... ⋱ ... \n",
" -3.1969e-02 2.7417e-01 1.2250e-01 ... -1.4495e-01 -8.4950e-01 -2.2803e-01\n",
" 3.2143e-01 1.2398e-01 -4.5293e-01 ... -1.4413e-01 2.1823e-01 -3.8627e-01\n",
" 1.7834e-02 2.2267e-02 -7.0417e-02 ... 4.2893e-02 -2.8627e-01 3.4247e-02\n",
" \n",
" ( 2 ,.,.) = \n",
" 1.9375e-02 2.3812e-02 1.1276e-02 ... 5.1828e-03 -2.3985e-02 2.3789e-02\n",
" -4.3739e-01 2.0894e-01 -3.8575e-02 ... 3.2274e-01 1.7369e-01 1.0408e-01\n",
" 1.8813e-01 2.6524e-01 5.7974e-01 ... -8.7242e-03 -1.0690e-01 -7.8983e-01\n",
" ... ⋱ ... \n",
" 2.3529e-01 -6.2904e-02 -1.4557e-01 ... -4.5544e-02 1.7732e-01 8.4309e-03\n",
" 3.3294e-01 -8.4541e-02 8.7829e-02 ... -1.1917e-01 -4.7819e-02 -7.6159e-01\n",
" 1.3981e-02 -1.6293e-02 -3.2810e-03 ... -2.1877e-01 1.0173e-01 -1.8190e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 3.4189e-03 -2.0456e-02 1.4243e-02 ... -2.3227e-03 9.3239e-04 -1.0247e-03\n",
" -3.3739e-02 -1.0891e-01 4.8999e-02 ... 1.4597e-02 1.6591e-01 5.4610e-01\n",
" 2.9653e-01 -1.0343e-01 1.2764e-01 ... -2.8191e-01 1.4097e-01 -1.2534e-01\n",
" ... ⋱ ... \n",
" -2.1604e-01 4.4984e-02 -2.8327e-03 ... -2.6177e-02 2.6116e-01 -3.5064e-01\n",
" -3.2880e-03 -4.0734e-02 -1.9771e-02 ... -1.2193e-01 -2.4205e-01 3.3782e-02\n",
" -5.5796e-02 3.7811e-02 2.0099e-02 ... 7.9827e-02 1.1639e-01 -3.2006e-01\n",
" \n",
" (126,.,.) = \n",
" -1.4516e-02 1.7064e-02 -9.8402e-03 ... -2.3872e-02 -3.4032e-02 1.4728e-02\n",
" 1.5041e-01 -9.3227e-02 6.9412e-03 ... 1.4876e-01 1.2624e-01 -8.2570e-03\n",
" 1.4423e-01 5.5396e-02 3.7413e-01 ... -3.2377e-02 9.6140e-03 -1.9368e-01\n",
" ... ⋱ ... \n",
" -1.3670e-01 1.9511e-01 1.7143e-02 ... 2.1694e-01 2.6442e-01 1.4836e-01\n",
" 1.3229e-01 -1.1568e-01 -2.9643e-01 ... 2.0208e-02 -8.4069e-01 -3.5946e-01\n",
" -5.8840e-02 3.1408e-02 4.1788e-02 ... 1.1578e-01 8.8983e-02 -9.6329e-02\n",
" \n",
" (127,.,.) = \n",
" 2.7546e-02 -5.6759e-03 1.0084e-02 ... 2.6578e-02 1.1931e-02 -1.4826e-02\n",
" -1.6599e-01 -2.7726e-02 1.0764e-01 ... -2.8034e-02 1.1052e-01 1.5459e-01\n",
" 4.3881e-01 -1.1269e-01 -5.1397e-01 ... 1.1887e-01 -5.0752e-03 1.7655e-02\n",
" ... ⋱ ... \n",
" -1.3443e-01 -3.9785e-01 -6.7975e-01 ... 2.2963e-01 -2.1617e-01 -5.5946e-01\n",
" -1.4329e-01 -7.1816e-02 8.6829e-02 ... -2.5498e-01 1.2733e-01 -5.0500e-01\n",
" -2.2701e-02 -3.5109e-02 8.2566e-02 ... 6.8880e-02 -2.8114e-02 -2.3018e-02\n",
" [torch.FloatTensor of size 128x128x12]),\n",
" ('module.encoder.cbhg.conv1d_banks.11.bn.weight', \n",
" 0.4696\n",
" 0.5719\n",
" -1.1061\n",
" 0.5807\n",
" -0.7647\n",
" 0.4872\n",
" 0.4623\n",
" 0.4274\n",
" -1.3260\n",
" 0.4248\n",
" 0.4323\n",
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" [torch.FloatTensor of size 128]),\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.11.bn.running_mean', \n",
" 0.8973\n",
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" 4.8064\n",
" 2.1079\n",
" 0.1551\n",
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" 0.6739\n",
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" 1.1109\n",
" 0.9439\n",
" 0.5355\n",
" 1.3070\n",
" 0.2914\n",
" 1.5545\n",
" 1.5114\n",
" 6.3411\n",
" 0.3893\n",
" 1.6662\n",
" 3.2795\n",
" 1.6572\n",
" 6.7529\n",
" 1.8553\n",
" 1.4979\n",
" 0.5757\n",
" 4.7291\n",
" 0.9452\n",
" 0.8243\n",
" 0.7778\n",
" 1.3144\n",
" 0.3643\n",
" 0.7754\n",
" 4.2364\n",
" 3.2026\n",
" 18.7853\n",
" 1.7417\n",
" 0.1808\n",
" 2.4082\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.11.bn.running_var', \n",
" 15.9795\n",
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" 14.9030\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.12.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 2.5124e-03 -2.2784e-02 1.0984e-02 ... 4.9846e-04 2.8635e-02 1.0756e-03\n",
" -1.3106e-01 1.4341e-01 7.9323e-02 ... 6.3507e-02 -4.5839e-02 2.1501e-01\n",
" 9.0208e-02 -1.7771e-01 -4.5272e-01 ... -6.9815e-02 -1.9479e-01 -1.8784e-03\n",
" ... ⋱ ... \n",
" -1.3932e-01 -3.7012e-01 -4.7639e-01 ... -1.0966e+00 1.5456e-01 -9.4229e-01\n",
" 5.7549e-02 -3.5620e-02 -2.3836e-01 ... 2.2370e-01 -3.1791e-01 -4.1511e-01\n",
" 7.0249e-02 1.9633e-01 1.1341e-01 ... -3.2817e-01 2.5300e-01 -1.3422e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.7731e-02 4.5285e-02 -1.2814e-02 ... -2.7173e-03 -1.4069e-02 -3.6759e-03\n",
" -7.2258e-02 -4.0775e-01 -1.8876e-01 ... 4.4626e-02 -1.0953e-01 -4.6202e-01\n",
" -1.1532e-02 2.4754e-01 -1.5029e-01 ... 3.5624e-01 -4.6946e-02 -1.4037e-01\n",
" ... ⋱ ... \n",
" -3.6031e-01 1.9696e-01 1.2519e-01 ... -1.9825e-01 -4.8447e-02 -1.3655e+00\n",
" 3.2029e-01 -6.1391e-02 1.5598e-01 ... -1.5652e-01 1.6171e-01 1.2432e-01\n",
" 6.3132e-02 -1.3603e-01 1.7496e-01 ... 5.9061e-02 9.7532e-02 -1.7508e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" -6.3073e-03 -7.1700e-03 -9.2430e-03 ... 1.5414e-02 -1.2460e-02 -1.5091e-03\n",
" -1.9551e-01 1.3026e-01 1.2604e-01 ... 9.2214e-02 -1.9176e-01 2.9766e-01\n",
" 1.9804e-01 -3.1485e-01 2.3391e-01 ... -1.3164e-01 4.3471e-01 -1.9872e-02\n",
" ... ⋱ ... \n",
" 2.8241e-01 1.6263e-01 -1.1973e-01 ... -1.9607e-01 2.0565e-01 -4.4889e-01\n",
" 1.6790e-01 -3.0801e-01 3.3417e-01 ... 4.0863e-02 -6.6297e-02 1.1063e-01\n",
" 7.7762e-02 1.0632e-01 6.3908e-02 ... 1.2705e-01 -4.4205e-02 9.7256e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -2.7683e-02 1.0624e-02 -5.0701e-03 ... -2.5705e-02 -3.8035e-02 -1.6509e-02\n",
" -3.8700e-01 -1.5979e-02 -2.6519e-01 ... 3.7613e-02 -3.7213e-02 1.0377e-01\n",
" -6.5393e-02 -1.7880e-01 -4.2023e-02 ... 1.0308e-02 -6.8235e-02 1.3338e-02\n",
" ... ⋱ ... \n",
" -6.8673e-01 1.2962e-01 -1.2936e-01 ... -1.4112e+00 3.2245e-01 3.7807e-02\n",
" 1.8645e-02 -7.1574e-02 -3.7431e-01 ... 5.2542e-02 -5.8785e-02 3.6606e-02\n",
" -2.0383e-01 8.8988e-02 4.6355e-02 ... -2.3510e-01 -2.2312e-01 -3.7548e-01\n",
" \n",
" (126,.,.) = \n",
" 1.6585e-02 1.8607e-02 -3.3634e-02 ... 6.2257e-03 1.5424e-03 -2.4602e-02\n",
" -3.4146e-01 2.2077e-02 -4.2619e-01 ... 1.9176e-01 -1.5382e-02 1.8814e-01\n",
" 2.1378e-01 -2.0700e-01 1.5258e-01 ... -2.4342e-01 -1.1730e-01 1.1733e-01\n",
" ... ⋱ ... \n",
" 9.8764e-02 3.2841e-01 3.0355e-01 ... 5.4214e-02 -9.0069e-02 -3.2505e-01\n",
" -3.9483e-01 2.0615e-01 2.1718e-01 ... -4.8824e-01 -8.4747e-01 1.1944e-01\n",
" -3.3625e-02 -4.8884e-03 4.1738e-02 ... -1.3514e-01 -2.0050e-01 -1.4370e-01\n",
" \n",
" (127,.,.) = \n",
" 2.5590e-02 1.8387e-02 2.0806e-02 ... 8.1549e-03 -1.6850e-03 7.8334e-03\n",
" -2.8174e-01 -3.6004e-01 -2.3312e-01 ... 4.5390e-02 4.9092e-02 -4.5602e-02\n",
" 6.9535e-01 1.4977e-01 -2.8423e-02 ... -1.3624e-01 1.0768e-01 -2.6318e-01\n",
" ... ⋱ ... \n",
" 5.7602e-02 1.3463e-01 5.8125e-03 ... -2.4428e-02 -5.6623e-01 -2.7310e-01\n",
" 5.5486e-02 2.0697e-01 -2.1729e-01 ... 2.6449e-01 -7.7781e-02 -2.6877e-01\n",
" 8.7469e-02 -4.8216e-02 4.2947e-02 ... 2.2505e-01 -2.1960e-01 -1.7593e-01\n",
" [torch.FloatTensor of size 128x128x13]),\n",
" ('module.encoder.cbhg.conv1d_banks.12.bn.weight', \n",
" 0.5730\n",
" 0.4872\n",
" -0.8539\n",
" 0.4749\n",
" 0.5131\n",
" -1.1585\n",
" -1.4734\n",
" 0.7568\n",
" 0.5510\n",
" 0.5189\n",
" 0.5052\n",
" 0.6131\n",
" 0.5743\n",
" 0.5302\n",
" 0.4877\n",
" 0.5639\n",
" 0.5930\n",
" -1.1419\n",
" 0.4849\n",
" 0.5213\n",
" -1.2542\n",
" 0.5455\n",
" 0.4479\n",
" -0.9798\n",
" 0.4703\n",
" 0.5385\n",
" -0.5705\n",
" -1.1007\n",
" 0.5222\n",
" -1.0825\n",
" 0.6221\n",
" 0.4761\n",
" 0.4963\n",
" 0.5569\n",
" 0.5680\n",
" 0.5440\n",
" -1.0525\n",
" 0.5683\n",
" 0.5189\n",
" 0.6212\n",
" 0.4043\n",
" -0.9544\n",
" -1.3453\n",
" 0.5191\n",
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" 0.5956\n",
" 0.5559\n",
" 0.5394\n",
" 1.3447\n",
" 0.7187\n",
" 0.5206\n",
" 0.5399\n",
" 0.4557\n",
" -1.2270\n",
" 0.5964\n",
" 0.4943\n",
" 0.5270\n",
" 0.7588\n",
" 0.5271\n",
" 0.6135\n",
" 0.5529\n",
" 0.4835\n",
" 0.5829\n",
" 0.0193\n",
" 0.4772\n",
" 0.4560\n",
" 0.5157\n",
" 0.4611\n",
" 0.5422\n",
" 0.5020\n",
" 0.4983\n",
" 0.5436\n",
" 0.5950\n",
" 0.4876\n",
" 0.4689\n",
" -0.3098\n",
" 0.5467\n",
" 0.0583\n",
" 0.4947\n",
" 0.4951\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.12.bn.running_mean', \n",
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" [torch.FloatTensor of size 128]),\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.13.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 1.7745e-02 -4.4126e-03 -4.8155e-03 ... -1.1811e-02 -1.2982e-02 4.8544e-03\n",
" 1.3211e-01 6.4812e-03 3.9755e-02 ... 1.3613e-01 -1.4129e-01 2.5989e-01\n",
" 1.3647e-01 -2.4757e-02 8.7259e-02 ... -3.0748e-01 -1.5349e-01 4.7045e-02\n",
" ... ⋱ ... \n",
" 2.7293e-01 -6.1637e-02 2.6514e-01 ... -9.1236e-02 1.3647e-01 -4.1393e-01\n",
" 1.8076e-01 1.4856e-01 -9.5415e-02 ... 2.6375e-02 9.1741e-02 -6.9988e-02\n",
" 1.8714e-02 2.2266e-01 -8.0913e-03 ... -1.3792e-01 2.0871e-03 6.6364e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" 1.4681e-02 -2.8576e-02 -3.3572e-03 ... -3.5963e-02 -2.6190e-03 -1.6106e-02\n",
" -3.0001e-01 -1.0300e-01 -2.9653e-01 ... -2.3369e-01 1.2638e-01 -8.7112e-02\n",
" -1.7102e-02 5.5029e-02 -2.2974e-01 ... -2.6807e-01 2.8310e-01 -2.0486e-01\n",
" ... ⋱ ... \n",
" -7.0041e-01 -9.4564e-01 1.6966e-02 ... 2.6940e-01 -2.8557e-01 1.2184e-01\n",
" -3.2194e-01 1.2850e-01 1.9510e-01 ... 2.4279e-01 2.1059e-01 -5.5531e-01\n",
" 6.1039e-02 -7.2539e-02 7.3692e-02 ... 1.1038e-01 1.2474e-02 -1.0941e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" -2.4671e-02 3.1477e-02 -1.8527e-02 ... 7.6964e-03 1.1642e-02 -3.8481e-03\n",
" -2.4675e-01 -1.0154e-01 -1.0051e-01 ... 2.4323e-01 1.1612e-01 -3.4125e-01\n",
" 1.4512e-03 3.5649e-01 -2.7982e-01 ... -9.7022e-01 -1.5814e-01 -4.0816e-01\n",
" ... ⋱ ... \n",
" -3.7522e-02 2.2590e-02 1.0087e-01 ... 2.1287e-01 -3.6022e-01 -5.4785e-01\n",
" -5.4449e-01 -5.5681e-02 -2.9264e-01 ... 1.3152e-01 4.3553e-02 5.6911e-02\n",
" 1.3604e-01 2.1225e-01 -1.1628e-01 ... 1.2776e-01 -5.8087e-02 9.8960e-02\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -2.4497e-02 -3.7381e-03 -1.4529e-02 ... -8.6942e-03 -2.6910e-02 3.1877e-02\n",
" -6.6612e-02 1.3753e-01 -9.7248e-02 ... -1.5097e-01 1.2860e-01 -7.2238e-01\n",
" 1.7896e-01 2.9136e-01 1.9650e-01 ... -2.0288e-01 -2.9753e-01 -1.3484e-01\n",
" ... ⋱ ... \n",
" 9.3054e-02 1.7660e-01 1.1617e-01 ... -1.8692e-01 -2.5153e-01 -1.1928e+00\n",
" 2.1528e-01 2.8482e-01 7.7727e-03 ... -3.3763e-02 -7.1726e-01 -2.4033e-01\n",
" -5.5266e-02 2.0036e-01 5.1280e-02 ... 6.3100e-03 -1.4751e-01 -8.7516e-02\n",
" \n",
" (126,.,.) = \n",
" -1.8795e-02 -1.4157e-02 1.8972e-02 ... 5.5805e-02 4.5948e-02 -5.0825e-03\n",
" 1.0776e-01 -7.5393e-01 -4.2556e-02 ... 5.1656e-02 1.6126e-01 -4.3502e-02\n",
" -3.9349e-01 2.7921e-01 -2.4415e-01 ... 7.9829e-02 8.0948e-02 -2.1672e-01\n",
" ... ⋱ ... \n",
" -4.9517e-02 -2.4103e-01 2.3441e-01 ... 6.0706e-02 -2.1137e-01 4.1497e-01\n",
" 1.5899e-01 -2.3921e-01 1.2935e-01 ... 1.4634e-01 1.8446e-01 -1.5869e-01\n",
" 1.4117e-01 9.5894e-03 1.1945e-02 ... -2.3359e-02 1.0747e-01 2.3452e-01\n",
" \n",
" (127,.,.) = \n",
" -2.3473e-02 -9.4031e-03 -1.5690e-02 ... -2.3350e-02 1.3103e-02 2.7526e-03\n",
" -3.6479e-01 -4.8598e-01 9.1681e-02 ... 1.8447e-01 -1.1075e-01 -5.3281e-02\n",
" 1.7906e-02 2.0140e-01 2.0678e-02 ... 7.1253e-02 3.2277e-01 -5.8525e-01\n",
" ... ⋱ ... \n",
" 2.8675e-01 -4.1663e-01 -1.8265e-01 ... 1.1046e-01 2.5976e-01 5.3310e-01\n",
" -1.2504e+00 -7.7143e-01 -8.7459e-01 ... -1.3034e+00 4.1625e-01 -4.3742e-01\n",
" -4.1942e-02 2.4496e-02 -2.3016e-01 ... -2.1655e-01 -2.3814e-01 2.8768e-01\n",
" [torch.FloatTensor of size 128x128x14]),\n",
" ('module.encoder.cbhg.conv1d_banks.13.bn.weight', \n",
" -0.6298\n",
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" -1.1730\n",
" 0.4535\n",
" -1.0682\n",
" 0.5419\n",
" 0.5654\n",
" 0.4253\n",
" 0.4681\n",
" 0.4466\n",
" 0.6438\n",
" -0.9214\n",
" 0.6425\n",
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" 0.5556\n",
" 0.7262\n",
" 0.5962\n",
" 0.5239\n",
" -1.0640\n",
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" 0.4708\n",
" 0.5036\n",
" 0.7284\n",
" -1.0950\n",
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" 0.5276\n",
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" 0.5367\n",
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" -1.8053\n",
" 0.5561\n",
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" 0.6790\n",
" 0.4250\n",
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" 0.5733\n",
" 0.5620\n",
" 0.5780\n",
" -1.2931\n",
" 0.5389\n",
" -1.0939\n",
" 0.5530\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.13.bn.bias', \n",
" -0.0561\n",
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" -0.1471\n",
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" -0.0884\n",
" 0.0868\n",
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" 0.0781\n",
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" 0.0971\n",
" 0.2286\n",
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" -0.0069\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.13.bn.running_mean', \n",
" 17.4920\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.13.bn.running_var', \n",
" 130.6758\n",
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" 35.8358\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.14.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -9.6386e-03 3.0975e-03 -2.5502e-03 ... 1.5233e-02 2.2425e-02 -3.1626e-02\n",
" 9.2219e-03 -9.3129e-02 -1.1708e-03 ... -6.1531e-01 4.4129e-02 -6.2089e-01\n",
" -3.7936e-01 -5.3634e-02 4.1889e-01 ... -2.1778e-01 5.3546e-01 -1.3575e-01\n",
" ... ⋱ ... \n",
" 1.9159e-01 -3.5651e-01 -1.5055e-01 ... -2.5301e-01 -1.4246e-01 -7.7590e-02\n",
" -5.7804e-02 2.4481e-01 -5.1024e-01 ... 3.3023e-01 -1.1456e-01 -4.6667e-01\n",
" 8.0287e-02 -6.9695e-02 -1.5106e-01 ... -2.3315e-01 -3.4729e-02 5.8015e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.7977e-02 -1.1838e-02 -2.9291e-02 ... 1.1945e-02 6.4109e-03 -2.0085e-02\n",
" 2.2693e-01 1.1070e-01 -1.2156e-01 ... 3.9183e-02 1.7745e-01 -9.5893e-02\n",
" -4.8388e-02 -2.2365e-01 1.0250e-01 ... 1.1775e-01 5.5102e-02 -2.7197e-01\n",
" ... ⋱ ... \n",
" 3.2907e-01 -3.3454e-01 1.9553e-01 ... -6.8944e-02 2.0750e-01 -5.4171e-01\n",
" 1.0093e-01 -2.0825e-01 -2.1511e-01 ... -1.2759e-01 -5.0020e-01 -2.9427e-01\n",
" 8.3563e-02 8.9445e-02 -1.6162e-01 ... -1.0580e-01 -3.8315e-02 1.1123e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 7.2138e-04 -3.1993e-02 9.4911e-03 ... -8.7489e-03 1.7652e-02 4.0780e-03\n",
" -1.3638e-02 -1.3663e-01 3.2960e-02 ... 4.7582e-02 -2.4319e-01 2.2738e-01\n",
" -7.7567e-01 -9.2321e-02 -1.1529e-01 ... -6.4581e-01 3.7072e-01 2.2190e-01\n",
" ... ⋱ ... \n",
" 1.3387e-01 -1.0459e-02 -2.2410e-01 ... -7.1280e-01 9.4690e-02 -1.0131e+00\n",
" 2.6751e-02 -2.9849e-01 -7.0005e-01 ... 1.3902e-01 -3.7694e-01 -1.2595e-01\n",
" -2.6215e-01 1.2256e-01 -2.8348e-01 ... 1.1236e-01 -2.6863e-01 -2.8805e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" 1.3993e-02 -7.3525e-03 -2.6726e-02 ... 2.4495e-02 -4.0242e-03 3.1814e-02\n",
" 1.4469e-01 1.2966e-01 2.0149e-01 ... -2.7853e-02 -6.0647e-01 -1.7823e-01\n",
" -1.1353e-01 -8.8484e-02 -5.0216e-01 ... -1.3258e-01 1.6498e-02 -3.3027e-01\n",
" ... ⋱ ... \n",
" -9.3859e-02 -3.1071e-01 -1.3097e-01 ... -9.2499e-03 8.2636e-02 7.8388e-02\n",
" -4.2766e-01 -1.2047e+00 -1.3363e-01 ... -2.5266e-02 1.3353e-01 -1.5399e-03\n",
" -6.4824e-02 -9.3140e-02 -7.5200e-02 ... -4.9299e-02 -2.9521e-01 2.1217e-01\n",
" \n",
" (126,.,.) = \n",
" 1.1726e-02 -9.5735e-03 2.0397e-02 ... 1.7887e-02 1.1456e-02 -1.8427e-02\n",
" -4.9714e-02 1.2782e-02 7.9058e-02 ... 8.2599e-03 -1.2522e-01 -3.1907e-01\n",
" 1.7756e-01 -1.2267e+00 2.0300e-01 ... 1.5960e-01 1.7278e-01 1.4348e-01\n",
" ... ⋱ ... \n",
" 2.3941e-01 -1.3360e-01 -2.8874e-01 ... -1.0559e+00 2.5745e-01 8.1122e-03\n",
" -3.4058e-01 3.1620e-01 -1.1758e+00 ... 2.4224e-02 -5.0012e-02 5.8442e-02\n",
" 3.5690e-02 8.2707e-02 3.0048e-02 ... -1.3737e-01 -4.6989e-02 3.6012e-02\n",
" \n",
" (127,.,.) = \n",
" -1.9347e-02 -1.3504e-02 8.1035e-03 ... 1.6393e-02 -2.4877e-02 -2.7250e-02\n",
" 2.1160e-01 2.5268e-01 4.1301e-01 ... 4.0031e-02 8.8184e-03 -2.1723e-01\n",
" 4.2787e-01 -3.9118e-01 -3.0853e-01 ... 1.4695e-01 -2.9853e-03 1.2570e-01\n",
" ... ⋱ ... \n",
" -7.8121e-01 -1.0999e-01 7.8042e-02 ... 2.2160e-01 1.1807e-01 -7.1094e-01\n",
" -3.6032e-02 8.9521e-02 1.7480e-02 ... -3.0489e-01 -1.5970e-01 -6.4072e-01\n",
" 1.6602e-01 1.1174e-02 -5.0506e-02 ... 2.8903e-01 1.0849e-01 -2.9205e-01\n",
" [torch.FloatTensor of size 128x128x15]),\n",
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" 0.5219\n",
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" 0.5868\n",
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" -1.2131\n",
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" -1.0432\n",
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" [torch.FloatTensor of size 128]),\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.14.bn.running_mean', \n",
" 1.6630\n",
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" [torch.FloatTensor of size 128]),\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.15.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 2.5623e-02 8.7796e-03 1.2732e-02 ... -2.4308e-02 -3.4531e-02 2.3106e-02\n",
" 3.2059e-01 3.7947e-02 -1.5134e-01 ... 4.1423e-02 1.4764e-02 -7.1850e-01\n",
" -3.0223e-01 -2.4837e-02 -3.8476e-01 ... 2.5859e-01 -2.4867e-01 -2.0122e-01\n",
" ... ⋱ ... \n",
" -3.2559e-01 -2.0264e-01 -2.0674e-01 ... -4.4623e-01 6.1603e-02 -1.4264e-01\n",
" 2.1641e-02 3.0297e-01 -1.5960e-02 ... -6.5608e-01 1.6242e-01 1.1450e-01\n",
" 7.3044e-02 1.4630e-01 8.5614e-02 ... -9.3979e-02 -3.5798e-02 -1.3267e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" 1.8823e-02 -3.0998e-02 -8.2396e-03 ... -2.8736e-02 9.6009e-04 2.1219e-02\n",
" -2.3189e+00 -7.2369e-02 2.4549e-01 ... -9.9233e-03 -5.9065e-01 6.0773e-02\n",
" 1.1587e-01 1.7568e-01 1.6188e-01 ... -7.3982e-01 -1.7959e-01 -9.6831e-01\n",
" ... ⋱ ... \n",
" 1.1053e-01 -3.7228e-01 5.2072e-02 ... -6.5126e-01 -2.0501e-01 -6.8167e-02\n",
" -2.3758e-01 -5.0526e-01 -2.4295e-01 ... 3.8033e-02 -5.6007e-03 1.5756e-02\n",
" 1.6876e-01 -1.5944e-01 -3.1784e-02 ... -4.3685e-01 -1.4064e-01 8.8937e-02\n",
" \n",
" ( 2 ,.,.) = \n",
" -3.0412e-02 -9.0673e-03 1.5075e-02 ... -1.4950e-02 3.6065e-03 -1.4769e-03\n",
" -3.9896e-01 1.4230e-01 -6.3218e-02 ... 4.4698e-01 -7.1939e-02 -3.8281e-02\n",
" -5.2769e-01 -3.1808e-01 3.9282e-03 ... -2.3788e-01 9.1319e-02 -6.3756e-01\n",
" ... ⋱ ... \n",
" 2.7757e-01 3.0037e-01 1.9336e-01 ... 8.2704e-02 3.3772e-01 1.7109e-01\n",
" -5.2782e-01 -5.2583e-02 -4.1151e-01 ... 2.9238e-01 -1.5851e-02 1.7705e-01\n",
" -3.1717e-02 -8.4575e-02 7.6925e-02 ... -4.8261e-02 -1.1192e-02 -1.3210e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -2.4106e-02 6.6282e-03 -1.8465e-02 ... -2.3786e-02 2.1597e-03 -1.3986e-02\n",
" -1.4231e-01 3.4451e-02 1.0366e-01 ... -4.9271e-01 -1.2217e-01 -1.0208e-01\n",
" -2.5530e-01 1.1695e-01 3.4305e-02 ... 5.0204e-03 -3.1896e-01 -9.6129e-02\n",
" ... ⋱ ... \n",
" 1.1271e-01 1.5310e-01 1.8242e-01 ... -1.4086e-01 4.2609e-02 -6.2007e-01\n",
" -1.0876e-01 -6.2901e-01 -3.5915e-01 ... 1.3079e-01 -6.1319e-01 5.1483e-02\n",
" -3.8345e-02 -5.3109e-02 -5.6655e-02 ... 1.9094e-02 -7.8271e-03 5.1170e-03\n",
" \n",
" (126,.,.) = \n",
" -5.0714e-03 -1.3371e-02 -5.9716e-03 ... -4.7321e-04 -1.5764e-02 2.2393e-03\n",
" -2.1972e-01 -1.0131e-02 -7.3959e-01 ... -1.0185e-01 -8.5600e-01 2.1385e-02\n",
" 2.9147e-01 1.6190e-01 1.7895e-01 ... -1.2549e+00 1.2088e-01 -3.7305e-01\n",
" ... ⋱ ... \n",
" 3.9247e-01 -5.5293e-01 1.1685e-01 ... 2.6583e-01 -2.7808e-01 1.0660e-02\n",
" 1.9686e-01 -2.6261e-01 -3.2170e-01 ... -2.5084e-01 -3.7867e-01 -8.2786e-01\n",
" 1.1004e-01 -1.3190e-01 -3.9576e-02 ... 9.9157e-03 -1.3757e-01 -4.7838e-02\n",
" \n",
" (127,.,.) = \n",
" -2.9438e-03 -6.5579e-03 1.0269e-02 ... -2.6457e-02 -1.8135e-02 8.6984e-03\n",
" -1.8795e-01 -2.1250e-02 -1.5791e-01 ... 1.1983e-01 1.2248e-01 -1.7003e-01\n",
" -4.6693e-03 -2.2383e-01 2.8204e-02 ... 2.2932e-02 -1.6864e-01 -4.6507e-01\n",
" ... ⋱ ... \n",
" -1.7754e-02 1.6717e-01 -2.0567e-01 ... 1.1366e-01 -1.0704e-01 5.5078e-02\n",
" 3.0380e-01 -1.5191e-01 2.2612e-01 ... 6.7546e-01 6.6147e-02 -1.0390e-01\n",
" 1.0645e-01 7.5489e-02 1.0369e-01 ... 5.6466e-02 1.0624e-01 3.4812e-02\n",
" [torch.FloatTensor of size 128x128x16]),\n",
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" [torch.FloatTensor of size 128]),\n",
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" 9.6724\n",
" 13.2361\n",
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" 1.6991\n",
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" 0.0007\n",
" 3.1607\n",
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" 0.3563\n",
" 11.9602\n",
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" 3.6062\n",
" 0.5507\n",
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" 3.4993\n",
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" 1.0194\n",
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" 0.0001\n",
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" 0.4954\n",
" 8.2006\n",
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" 3.0251\n",
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" 11.2387\n",
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" 5.6987\n",
" 0.9826\n",
" 1.2777\n",
" 6.8550\n",
" 0.3461\n",
" 7.7890\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_banks.15.bn.running_var', \n",
" 19.3441\n",
" 7.2210\n",
" 52.1670\n",
" 10.0785\n",
" 0.8694\n",
" 19.9234\n",
" 3.0400\n",
" 7.1023\n",
" 48.8550\n",
" 6.8233\n",
" 79.8547\n",
" 9.1791\n",
" 2.2923\n",
" 8.2448\n",
" 73.9919\n",
" 141.0537\n",
" 14.1035\n",
" 40.1774\n",
" 91.0158\n",
" 9.2547\n",
" 12.4517\n",
" 5.1783\n",
" 157.9901\n",
" 231.3361\n",
" 13.6326\n",
" 5.5508\n",
" 26.2938\n",
" 6.0275\n",
" 89.2656\n",
" 19.1362\n",
" 46.1800\n",
" 10.6488\n",
" 18.0966\n",
" 33.1807\n",
" 12.2791\n",
" 1.9163\n",
" 23.7852\n",
" 8.4300\n",
" 72.0607\n",
" 14.9116\n",
" 5.9400\n",
" 6.2749\n",
" 21.8647\n",
" 6.2331\n",
" 34.8539\n",
" 116.9517\n",
" 23.9962\n",
" 107.2270\n",
" 19.6034\n",
" 88.5838\n",
" 85.4811\n",
" 23.7413\n",
" 0.0000\n",
" 5.1239\n",
" 124.2238\n",
" 15.7109\n",
" 24.0241\n",
" 124.8482\n",
" 79.0445\n",
" 7.0774\n",
" 30.6366\n",
" 26.3645\n",
" 31.4898\n",
" 44.0007\n",
" 36.0663\n",
" 0.0021\n",
" 48.7602\n",
" 11.8073\n",
" 6.2930\n",
" 23.4775\n",
" 7.3132\n",
" 242.1393\n",
" 39.2080\n",
" 16.3218\n",
" 48.5017\n",
" 9.5221\n",
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" 52.8122\n",
" 74.0767\n",
" 7.5589\n",
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" 1.5151\n",
" 29.8387\n",
" 33.0634\n",
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" 11.5707\n",
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" 25.2861\n",
" 35.6485\n",
" 8.2998\n",
" 25.4361\n",
" 20.3728\n",
" 6.9308\n",
" 45.0786\n",
" 10.2328\n",
" 0.0008\n",
" 8.8821\n",
" 20.8823\n",
" 10.3538\n",
" 142.8971\n",
" 43.0934\n",
" 52.4043\n",
" 10.1972\n",
" 201.6355\n",
" 27.1906\n",
" 23.0948\n",
" 23.9127\n",
" 19.4774\n",
" 23.5042\n",
" 5.9305\n",
" 2.9476\n",
" 22.1587\n",
" 1.1825\n",
" 9.4386\n",
" 23.9990\n",
" 10.7355\n",
" 100.3000\n",
" 9.3527\n",
" 13.9741\n",
" 128.4238\n",
" 18.1951\n",
" 23.8309\n",
" 136.7777\n",
" 6.1809\n",
" 149.2479\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.0.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 3.0814e-01 4.3928e-02 5.9386e-02\n",
" 1.1993e-01 5.8452e-02 4.1407e-01\n",
" -3.3929e-01 -2.6133e-01 -3.4512e-01\n",
" ⋮ \n",
" 2.6667e-01 6.0643e-01 -3.8510e-01\n",
" -3.8135e-01 -1.7756e-01 1.8003e-01\n",
" -3.7152e-02 -2.8518e-03 -5.0003e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" 6.7310e-03 -1.9074e-01 -4.0766e-01\n",
" -3.7384e-01 3.8173e-02 -8.6705e-02\n",
" -1.4769e-01 -4.1923e-02 -1.0642e-01\n",
" ⋮ \n",
" -6.6837e-02 6.2199e-01 2.5974e-02\n",
" -1.1596e-01 -2.3071e-01 7.0891e-02\n",
" -6.6795e-01 2.1777e-01 1.5540e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" -2.3889e-02 1.2623e-02 -1.6646e+00\n",
" 3.5820e-01 -2.0916e-01 1.3814e+00\n",
" -1.3201e-01 -1.2885e-01 2.0583e-01\n",
" ⋮ \n",
" -1.4197e-01 1.5728e-01 -4.6813e-02\n",
" 4.1027e-02 1.1533e-01 -2.0033e-01\n",
" 1.0978e-01 -1.6570e-01 -8.2350e-02\n",
" ... \n",
" \n",
" (125 ,.,.) = \n",
" -9.2253e-03 -4.7290e-01 -6.3990e-01\n",
" 1.8074e-01 5.8933e-01 3.6671e-01\n",
" -2.7379e-01 -1.4911e-01 -1.0068e-02\n",
" ⋮ \n",
" 4.6931e-01 3.3843e-02 -9.3615e-02\n",
" 1.8630e-01 2.2686e-01 -5.0762e-02\n",
" 4.6377e-01 5.5982e-01 2.5739e-01\n",
" \n",
" (126 ,.,.) = \n",
" -3.0432e-01 2.8374e-01 -2.8736e-02\n",
" -6.6618e-02 -3.0130e-01 1.1153e-01\n",
" 1.0508e-01 -2.2993e-02 6.0722e-02\n",
" ⋮ \n",
" -1.5460e-01 3.0680e-01 -2.1939e-01\n",
" 1.0348e-02 1.1076e-01 -2.4765e-01\n",
" -1.2953e-01 2.0722e-01 -2.8834e-01\n",
" \n",
" (127 ,.,.) = \n",
" -3.5357e-01 5.5979e-03 -1.1791e-01\n",
" -1.3253e-01 -1.0162e-01 -4.8239e-01\n",
" -5.9012e-02 1.8944e-01 -2.2635e-01\n",
" ⋮ \n",
" 1.0666e-01 3.3147e-01 -3.4622e-02\n",
" -2.3130e-02 3.4870e-01 2.0421e-01\n",
" -3.4532e-01 4.7640e-01 -1.8542e-01\n",
" [torch.FloatTensor of size 128x2048x3]),\n",
" ('module.encoder.cbhg.conv1d_projections.0.bn.weight', \n",
" 0.6646\n",
" 0.8037\n",
" 0.5687\n",
" -0.3298\n",
" 0.3331\n",
" 0.5846\n",
" 0.7305\n",
" 0.5224\n",
" 0.5024\n",
" 0.3957\n",
" 0.4767\n",
" 0.6206\n",
" 0.7052\n",
" -0.4729\n",
" 0.4754\n",
" 0.4523\n",
" 0.3607\n",
" 0.5262\n",
" 0.5655\n",
" 0.2685\n",
" 0.5239\n",
" 0.4226\n",
" 0.7581\n",
" 0.4334\n",
" 0.9309\n",
" 0.3395\n",
" 0.3421\n",
" 0.4946\n",
" 0.6343\n",
" 0.3663\n",
" 0.5080\n",
" 0.5530\n",
" 0.3504\n",
" 0.3564\n",
" 0.5745\n",
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" 0.4997\n",
" 0.6707\n",
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" 0.4622\n",
" 0.6502\n",
" -0.3914\n",
" 0.6328\n",
" 0.7951\n",
" 0.5793\n",
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" 0.8058\n",
" 0.4266\n",
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" 0.4265\n",
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" 1.0867\n",
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" -0.0049\n",
" 0.6564\n",
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" 0.5283\n",
" 1.3802\n",
" 0.4614\n",
" 0.5294\n",
" 0.5872\n",
" 0.4923\n",
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" 0.6569\n",
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" 0.6301\n",
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" 0.4971\n",
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" 0.5801\n",
" 0.5462\n",
" 0.4063\n",
" 0.5967\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.0.bn.bias', \n",
" 0.4170\n",
" -0.0814\n",
" 0.5861\n",
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" 0.1705\n",
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" 1.0144\n",
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" 0.4903\n",
" 0.0312\n",
" 1.1306\n",
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" 0.6143\n",
" -0.0467\n",
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" -1.1164\n",
" 0.5284\n",
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" -0.6266\n",
" -0.3952\n",
" 0.1032\n",
" 0.4301\n",
" 0.5007\n",
" -0.7266\n",
" 0.0655\n",
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" -0.0068\n",
" 0.4664\n",
" -0.9305\n",
" 0.7540\n",
" 0.0923\n",
" 0.0029\n",
" 0.1134\n",
" -0.3432\n",
" 0.3094\n",
" 0.8301\n",
" 0.0221\n",
" 0.7642\n",
" -0.2436\n",
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" -1.0682\n",
" 1.0367\n",
" 0.3307\n",
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" -0.4417\n",
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" 0.7529\n",
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" 0.2944\n",
" 0.2873\n",
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" -0.8139\n",
" 0.2548\n",
" -1.1177\n",
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" 0.7131\n",
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" 0.5456\n",
" 0.7895\n",
" -0.1775\n",
" 0.7853\n",
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" 0.2082\n",
" -0.0249\n",
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" 0.6822\n",
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" 0.7948\n",
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" 0.1007\n",
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" 0.6086\n",
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" 0.3299\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.0.bn.running_mean', \n",
" 0.2210\n",
" 0.0529\n",
" 1.3052\n",
" 0.0680\n",
" 0.2829\n",
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" 0.2964\n",
" 0.0397\n",
" 0.1658\n",
" 5.2520\n",
" 1.7325\n",
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" 0.4226\n",
" 0.0934\n",
" 4.8479\n",
" 0.8025\n",
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" 20.9054\n",
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" 0.0000\n",
" 4.5476\n",
" 3.2742\n",
" 1.0132\n",
" 0.2117\n",
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" 18.8371\n",
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" 10.7140\n",
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" 0.0763\n",
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" 0.1182\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.0.bn.running_var', \n",
" 10.1925\n",
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" 40.7506\n",
" 2.2552\n",
" 5.7887\n",
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" 1.1643\n",
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" 10.8992\n",
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" 4.9660\n",
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" 262.8981\n",
" 16.3489\n",
" 288.6512\n",
" 158.7979\n",
" 7.0622\n",
" 123.5744\n",
" 5.8243\n",
" 6.8162\n",
" 113.7955\n",
" 358.1396\n",
" 17.4511\n",
" 0.7085\n",
" 12.1286\n",
" 283.4341\n",
" 2.8528\n",
" 38.1696\n",
" 37.2666\n",
" 3.2165\n",
" 239.5753\n",
" 336.7714\n",
" 544.2413\n",
" 116.3443\n",
" 4.9104\n",
" 81.7024\n",
" 37.3843\n",
" 3.3905\n",
" 341.0682\n",
" 0.5235\n",
" 6.1596\n",
" 301.3521\n",
" 2.4722\n",
" 0.0616\n",
" 2.5850\n",
" 0.0000\n",
" 276.1491\n",
" 18.7097\n",
" 161.9815\n",
" 1.8596\n",
" 0.1399\n",
" 57.3707\n",
" 119.9483\n",
" 365.9788\n",
" 149.1642\n",
" 156.6599\n",
" 396.5631\n",
" 4.4044\n",
" 23.1890\n",
" 556.5134\n",
" 3.8096\n",
" 158.6554\n",
" 10.4037\n",
" 0.0000\n",
" 128.4091\n",
" 16.4895\n",
" 1.0318\n",
" 0.0000\n",
" 304.3759\n",
" 0.0005\n",
" 69.4994\n",
" 3.5712\n",
" 144.1262\n",
" 0.0000\n",
" 0.0000\n",
" 5.1930\n",
" 0.7164\n",
" 1.2742\n",
" 3.1561\n",
" 40.9657\n",
" 25.8127\n",
" 0.4160\n",
" 376.6815\n",
" 91.2860\n",
" 8.4013\n",
" 129.7561\n",
" 116.1720\n",
" 3.4888\n",
" 56.6032\n",
" 7.4175\n",
" 6.8700\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.1.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -7.9624e-02 9.5472e-02 -6.5400e-02\n",
" -9.0511e-02 -1.2361e-01 -2.9827e-01\n",
" -1.0070e-01 -4.9918e-01 1.5549e-01\n",
" ⋮ \n",
" -2.0914e-01 8.3182e-01 3.5420e-01\n",
" -9.0347e-02 -1.9814e-01 1.5357e-01\n",
" 2.0842e-01 -1.6191e-01 -1.3249e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -2.6338e-01 2.0028e-01 -5.5048e-01\n",
" -6.3165e-02 2.0704e-01 4.7220e-01\n",
" 1.5427e-01 -2.4553e-01 -2.8350e-01\n",
" ⋮ \n",
" 2.4556e-02 -2.8573e-01 6.1484e-02\n",
" 2.4085e-01 5.7162e-03 3.0859e-01\n",
" 3.4030e-01 1.2176e-01 1.1497e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 1.2434e-02 4.0604e-01 2.5618e-01\n",
" 8.7541e-02 -5.6916e-02 -5.7893e-01\n",
" -1.9563e-01 -7.3344e-02 -6.0057e-02\n",
" ⋮ \n",
" 1.0950e-01 3.1177e-02 -1.4969e-03\n",
" -8.3942e-02 -1.2569e-01 -2.7982e-01\n",
" 1.3968e-01 -2.1056e-01 -3.8614e-01\n",
" ... \n",
" \n",
" (125,.,.) = \n",
" -2.0339e-01 -9.2574e-02 1.9148e-01\n",
" 1.9614e-01 1.8801e-01 5.5208e-01\n",
" -5.3128e-02 4.0566e-01 -3.9731e-01\n",
" ⋮ \n",
" 2.4068e-01 3.5523e-02 -1.7478e-01\n",
" 1.3921e-01 -3.7821e-01 -7.7398e-02\n",
" 3.1290e-01 1.0250e-01 1.6110e-01\n",
" \n",
" (126,.,.) = \n",
" 1.8149e-01 1.4161e-01 -2.1990e-01\n",
" 9.2477e-02 1.8051e-01 3.1933e-01\n",
" 4.1670e-02 6.6928e-02 2.5147e-01\n",
" ⋮ \n",
" -2.6391e-01 -7.2917e-02 -5.0047e-02\n",
" 1.1001e-01 3.4186e-01 2.3474e-01\n",
" 1.2854e-01 1.6606e-01 -1.7315e-02\n",
" \n",
" (127,.,.) = \n",
" -2.3090e-01 1.5042e-01 6.3597e-01\n",
" -3.4157e-02 3.5767e-03 3.4091e-01\n",
" 4.9821e-02 -5.0298e-02 5.0703e-02\n",
" ⋮ \n",
" 2.7414e-02 1.3014e-01 2.9182e-01\n",
" 1.6557e-01 4.1488e-01 1.0505e-01\n",
" 8.3979e-02 -3.8755e-01 -1.7537e-02\n",
" [torch.FloatTensor of size 128x128x3]),\n",
" ('module.encoder.cbhg.conv1d_projections.1.bn.weight', \n",
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" -0.2415\n",
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" 0.7386\n",
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" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.conv1d_projections.1.bn.running_var', \n",
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" 22.7567\n",
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" 9.4996\n",
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" 20.7137\n",
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" 9.6516\n",
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" 13.5345\n",
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" 25.8441\n",
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" 9.1293\n",
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" 13.3793\n",
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" 22.9312\n",
" 23.8098\n",
" 21.8152\n",
" 9.1292\n",
" 21.1067\n",
" 13.2162\n",
" [torch.FloatTensor of size 128]),\n",
" ('module.encoder.cbhg.pre_highway.weight', \n",
" 7.6424e-03 2.5910e-02 5.8759e-02 ... 2.5778e-02 5.1379e-02 -4.2433e-03\n",
" -2.4070e-02 7.6139e-02 4.9189e-02 ... 6.4792e-02 4.8108e-02 -7.3651e-02\n",
" -3.4366e-02 -7.9627e-02 -4.4232e-02 ... 3.5146e-02 -8.0961e-02 -5.9398e-02\n",
" ... ⋱ ... \n",
" 7.6387e-02 1.1982e-02 -7.0450e-04 ... 5.7644e-02 5.5235e-02 -7.8248e-02\n",
" 6.9834e-02 -7.8794e-02 6.8049e-02 ... 4.9438e-02 2.3717e-02 5.5143e-03\n",
" -2.9588e-02 -8.4442e-02 2.6452e-02 ... -4.1797e-02 4.1798e-02 2.6897e-02\n",
" [torch.FloatTensor of size 128x128]),\n",
" ('module.encoder.cbhg.highways.0.H.weight', \n",
" -3.7753e-01 -1.1873e-01 -7.2885e-02 ... -1.3706e-01 -5.0812e-01 -3.1839e-01\n",
" -3.1247e-01 -1.9993e-01 -8.0211e-01 ... -3.2072e-01 2.9533e-01 -2.5461e-02\n",
" 6.9581e-02 -6.6954e-02 -1.6043e-01 ... -1.3403e-01 -3.1564e-01 -3.1844e-01\n",
" ... ⋱ ... \n",
" -3.6133e-01 1.4214e-02 1.2277e-01 ... -3.4546e-01 1.7992e-01 -1.3199e-01\n",
" -9.9197e-02 -3.4521e-02 -1.2004e-01 ... -3.2145e-01 -1.7860e-01 -1.6176e-01\n",
" 1.3408e-01 3.0038e-03 -1.0454e-01 ... -1.3727e-04 3.0389e-02 -8.2818e-02\n",
" [torch.FloatTensor of size 128x128]),\n",
" ('module.encoder.cbhg.highways.0.H.bias', \n",
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" [torch.FloatTensor of size 768]),\n",
" ('module.decoder.attention_rnn.alignment_model.query_layer.weight',\n",
" \n",
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" ... ⋱ ... \n",
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" ('module.decoder.attention_rnn.alignment_model.v.weight', \n",
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" [torch.FloatTensor of size 768]),\n",
" ('module.decoder.proj_to_mel.weight', \n",
" -1.3074e-03 -2.4511e-03 4.0127e-03 ... -1.8974e-04 -3.5570e-03 -1.0731e-02\n",
" 1.6458e-04 -3.4461e-03 -1.7653e-02 ... -1.2636e-03 -2.7327e-04 1.3112e-02\n",
" -4.7382e-03 2.9522e-03 -3.0874e-02 ... 2.8109e-04 -1.5848e-03 -6.4812e-03\n",
" ... ⋱ ... \n",
" -4.6943e-03 4.4080e-03 -1.1201e-02 ... 1.1059e-01 -9.0196e-04 1.6526e-02\n",
" -6.3213e-03 5.4862e-03 -4.3771e-03 ... 1.0128e-01 -4.8409e-03 1.2473e-02\n",
" -2.1717e-03 4.6354e-03 -1.0125e-02 ... 9.4980e-02 -1.4286e-03 2.9772e-02\n",
" [torch.FloatTensor of size 400x256]),\n",
" ('module.decoder.proj_to_mel.bias', \n",
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" 1.2573\n",
" 1.1643\n",
" 1.0473\n",
" 0.6013\n",
" [torch.FloatTensor of size 400]),\n",
" ('module.postnet.conv1d_banks.0.conv1d.weight', \n",
" (0 ,.,.) = \n",
" 5.1769e-01\n",
" -1.9350e-01\n",
" -5.1565e-02\n",
" ⋮ \n",
" -1.4517e-02\n",
" 7.1059e-02\n",
" 6.6071e-02\n",
" \n",
" (1 ,.,.) = \n",
" -1.0924e-02\n",
" -8.0526e-02\n",
" 3.5597e-02\n",
" ⋮ \n",
" -2.0654e-01\n",
" -1.3508e-01\n",
" 3.8456e-01\n",
" \n",
" (2 ,.,.) = \n",
" 2.9784e+00\n",
" -6.2878e-01\n",
" -1.7459e-01\n",
" ⋮ \n",
" 7.2299e-02\n",
" 2.2709e-01\n",
" 6.0340e-01\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" -9.9861e-01\n",
" 9.4519e-02\n",
" 1.9491e-01\n",
" ⋮ \n",
" 1.0430e-01\n",
" -1.9140e-02\n",
" 2.6940e-01\n",
" \n",
" (78,.,.) = \n",
" 2.1744e-01\n",
" -8.0680e-02\n",
" 2.1582e-01\n",
" ⋮ \n",
" -4.2295e-02\n",
" 1.6425e-02\n",
" -2.3594e-03\n",
" \n",
" (79,.,.) = \n",
" 1.7220e+00\n",
" -1.5493e+00\n",
" 2.8362e-01\n",
" ⋮ \n",
" 1.4140e-01\n",
" 1.6998e-02\n",
" 4.2408e-01\n",
" [torch.FloatTensor of size 80x80x1]),\n",
" ('module.postnet.conv1d_banks.0.bn.weight', \n",
" -11.9678\n",
" -12.2330\n",
" 0.5874\n",
" -12.7266\n",
" -14.8812\n",
" -2.5761\n",
" -11.9427\n",
" -4.2313\n",
" 0.6492\n",
" -14.3888\n",
" 0.5280\n",
" 0.5165\n",
" -3.7921\n",
" 0.6091\n",
" -1.2100\n",
" -5.2468\n",
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" -9.6767\n",
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" -11.3032\n",
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" -1.2537\n",
" -4.8199\n",
" 0.4803\n",
" 0.3263\n",
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" -11.5061\n",
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" -12.2295\n",
" -3.9541\n",
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" 0.3231\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.0.bn.bias', \n",
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" -0.5499\n",
" -0.6805\n",
" -0.5549\n",
" -0.2024\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.0.bn.running_mean', \n",
" 2.1287e-05\n",
" 1.3011e-05\n",
" 3.0102e-01\n",
" 7.9208e-06\n",
" 2.9520e-04\n",
" 3.8135e-02\n",
" 1.0149e-05\n",
" 4.4172e-05\n",
" 9.3081e-01\n",
" 1.1545e-04\n",
" 1.1260e+00\n",
" 1.9549e+00\n",
" 1.2658e-04\n",
" 2.7999e-01\n",
" 6.6247e-02\n",
" 3.7660e-05\n",
" 1.8550e-01\n",
" 1.7950e-05\n",
" 2.6923e+00\n",
" 1.3024e-01\n",
" 6.4194e-06\n",
" 1.9988e-05\n",
" 3.6879e-04\n",
" 1.2148e-01\n",
" 3.0188e-02\n",
" 1.2351e-05\n",
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" 1.2651e-06\n",
" 1.6360e-01\n",
" 8.9487e-02\n",
" 4.3512e-05\n",
" 2.1093e-05\n",
" 2.2089e-05\n",
" 1.8914e-05\n",
" 1.8063e-04\n",
" 3.8698e+00\n",
" 1.5270e-01\n",
" 1.3995e-05\n",
" 5.7557e-06\n",
" 2.8174e+00\n",
" 1.2101e-05\n",
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" 2.9588e-06\n",
" 3.3828e-06\n",
" 1.7701e-01\n",
" 6.5255e-05\n",
" 1.2166e-01\n",
" 1.9112e+00\n",
" 1.5575e-05\n",
" 3.8261e+00\n",
" 2.3136e-05\n",
" 2.2370e-05\n",
" 2.5962e-01\n",
" 2.6652e-05\n",
" 4.7766e-05\n",
" 1.0692e-05\n",
" 4.4529e-01\n",
" 1.2559e-01\n",
" 2.7961e-01\n",
" 1.3356e-05\n",
" 1.8169e-04\n",
" 1.9655e-01\n",
" 8.2612e-06\n",
" 2.1740e+00\n",
" 6.1940e-02\n",
" 3.7653e-01\n",
" 1.4797e-04\n",
" 2.1150e-05\n",
" 5.7097e-02\n",
" 4.5371e-05\n",
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" 1.8344e-04\n",
" 5.5461e-05\n",
" 1.8992e-01\n",
" 3.4101e-02\n",
" 4.6944e-05\n",
" 5.0050e-05\n",
" 2.6779e-05\n",
" 5.0445e-02\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.0.bn.running_var', \n",
" 3.4790e-07\n",
" 1.3100e-07\n",
" 9.3850e-02\n",
" 9.8571e-08\n",
" 4.2421e-06\n",
" 7.1133e-04\n",
" 9.6986e-08\n",
" 2.3501e-07\n",
" 1.9607e-01\n",
" 1.1185e-06\n",
" 7.5229e-01\n",
" 8.2943e-01\n",
" 1.5405e-06\n",
" 3.7033e-02\n",
" 3.0053e-03\n",
" 3.7897e-07\n",
" 4.2127e-02\n",
" 1.3493e-07\n",
" 1.8891e+00\n",
" 9.1971e-02\n",
" 5.4875e-08\n",
" 1.6678e-07\n",
" 1.0535e-05\n",
" 5.2598e-02\n",
" 1.0646e-02\n",
" 1.3590e-07\n",
" 4.9546e-04\n",
" 3.7495e-09\n",
" 3.6607e-02\n",
" 3.8562e-02\n",
" 4.6355e-07\n",
" 1.0277e-07\n",
" 3.1599e-07\n",
" 1.6569e-07\n",
" 1.9677e-06\n",
" 3.2907e+00\n",
" 2.8827e-02\n",
" 2.4286e-07\n",
" 7.4433e-08\n",
" 1.6466e+00\n",
" 7.0617e-08\n",
" 1.3520e+00\n",
" 1.6808e-08\n",
" 2.3399e-08\n",
" 4.7179e-02\n",
" 8.3522e-07\n",
" 2.4160e-02\n",
" 1.0465e+00\n",
" 2.0186e-07\n",
" 3.3099e+00\n",
" 3.4907e-07\n",
" 1.5072e-07\n",
" 1.6966e-02\n",
" 4.8098e-07\n",
" 3.1123e-07\n",
" 1.3480e-07\n",
" 1.4162e-01\n",
" 2.3337e-02\n",
" 7.2239e-02\n",
" 1.5036e-07\n",
" 2.4603e-06\n",
" 4.7200e-02\n",
" 7.7703e-08\n",
" 1.1384e+00\n",
" 9.7417e-03\n",
" 1.0520e-01\n",
" 1.4845e-06\n",
" 2.0648e-07\n",
" 1.6840e-02\n",
" 9.0840e-07\n",
" 2.7039e-08\n",
" 3.1538e-02\n",
" 4.6559e-06\n",
" 5.6221e-07\n",
" 2.9305e-02\n",
" 4.8931e-03\n",
" 7.6341e-07\n",
" 5.7731e-07\n",
" 2.6599e-07\n",
" 4.4374e-02\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.1.conv1d.weight', \n",
" (0 ,.,.) = \n",
" 2.2803e-01 3.5122e-02\n",
" 9.0641e-04 5.3618e-02\n",
" -7.8795e-02 1.4725e-02\n",
" ⋮ \n",
" -6.7398e-02 3.0243e-02\n",
" -1.4825e-01 -3.2397e-02\n",
" 4.5505e-02 6.4718e-02\n",
" \n",
" (1 ,.,.) = \n",
" 4.4825e-01 2.4676e-01\n",
" -1.0999e-01 -1.5665e-01\n",
" 2.9031e-02 -4.8570e-03\n",
" ⋮ \n",
" -8.9446e-02 1.8276e-01\n",
" 2.4644e-02 6.5687e-02\n",
" -1.9755e-02 -2.3221e-02\n",
" \n",
" (2 ,.,.) = \n",
" -4.8638e-01 1.2996e+00\n",
" -3.9909e-01 -1.7756e-01\n",
" -5.2663e-02 5.4679e-01\n",
" ⋮ \n",
" 1.1216e-01 8.3459e-02\n",
" -1.1575e-01 -8.2108e-02\n",
" -3.9344e-01 2.8520e-02\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" 1.3718e-01 4.9113e-01\n",
" -3.1217e-03 1.6377e-02\n",
" 1.8865e-01 -6.7507e-02\n",
" ⋮ \n",
" 7.4536e-02 -4.8456e-02\n",
" 4.2454e-03 -1.0714e-01\n",
" 2.5783e-01 6.0486e-02\n",
" \n",
" (78,.,.) = \n",
" 1.4156e-01 8.3407e-02\n",
" -1.1070e-01 2.2991e-01\n",
" 1.2974e-01 8.5432e-02\n",
" ⋮ \n",
" 1.3325e-02 -7.5131e-02\n",
" 1.7926e-01 -8.9462e-03\n",
" -4.1264e-04 2.6007e-02\n",
" \n",
" (79,.,.) = \n",
" 3.1951e-01 -8.2399e-01\n",
" -2.8575e-01 3.6496e-02\n",
" -1.9432e-01 -3.7100e-01\n",
" ⋮ \n",
" 8.6748e-02 -1.2156e-01\n",
" -2.9631e-02 -1.3142e-01\n",
" 1.2614e-02 -1.6323e-01\n",
" [torch.FloatTensor of size 80x80x2]),\n",
" ('module.postnet.conv1d_banks.1.bn.weight', \n",
" -4.6559\n",
" -4.0374\n",
" 0.5697\n",
" 0.2481\n",
" -2.0727\n",
" 0.1974\n",
" -4.4233\n",
" -12.7494\n",
" -11.2140\n",
" -10.3780\n",
" -12.1605\n",
" -13.5825\n",
" 0.2552\n",
" -7.1670\n",
" -4.3186\n",
" -13.1333\n",
" 0.4902\n",
" -14.6622\n",
" -4.2768\n",
" -13.1279\n",
" -4.3025\n",
" 0.5430\n",
" 0.2588\n",
" -2.9486\n",
" -13.0833\n",
" -4.4657\n",
" 0.2853\n",
" -4.3336\n",
" -11.0073\n",
" 0.4570\n",
" -10.7826\n",
" 0.4264\n",
" 0.3180\n",
" 0.7737\n",
" -15.5740\n",
" -0.0243\n",
" -12.4222\n",
" -15.6479\n",
" 0.4490\n",
" 0.2373\n",
" -11.2645\n",
" 0.2832\n",
" -13.6475\n",
" 0.2258\n",
" -13.5477\n",
" -11.1852\n",
" -12.1963\n",
" -24.0367\n",
" -4.1066\n",
" -4.9623\n",
" 0.4799\n",
" 0.7183\n",
" -11.3978\n",
" 0.0855\n",
" -13.4413\n",
" 0.2855\n",
" 0.0430\n",
" 0.3015\n",
" -15.7421\n",
" -14.6467\n",
" 0.3438\n",
" 0.7918\n",
" -13.1479\n",
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" 0.6624\n",
" -4.3095\n",
" -10.4288\n",
" 0.0540\n",
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" -2.1997\n",
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" -0.8526\n",
" -11.0237\n",
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" -13.1054\n",
" -12.2283\n",
" 0.2761\n",
" -11.2452\n",
" -10.0655\n",
" 0.1193\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.1.bn.bias', \n",
" -3.5955\n",
" -2.4005\n",
" -0.4212\n",
" -0.3180\n",
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" 0.1549\n",
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" 0.6684\n",
" -0.4975\n",
" -0.2724\n",
" -0.3186\n",
" -1.2307\n",
" -0.4911\n",
" -0.3951\n",
" 0.0476\n",
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" -0.3600\n",
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" -0.5023\n",
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" -0.4027\n",
" -3.1746\n",
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" -0.2009\n",
" -0.2193\n",
" -0.4634\n",
" -0.5115\n",
" 0.2173\n",
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" -0.1203\n",
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" 0.4986\n",
" 0.2563\n",
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" 0.0162\n",
" -0.5236\n",
" -0.4651\n",
" -0.6325\n",
" -3.2684\n",
" -0.3006\n",
" 0.3432\n",
" -0.5174\n",
" -0.2651\n",
" 0.3860\n",
" 0.5317\n",
" -0.3071\n",
" -0.5193\n",
" -0.5852\n",
" -2.6626\n",
" -0.3978\n",
" -0.6819\n",
" -0.3028\n",
" -0.1223\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.1.bn.running_mean', \n",
" 2.2363e-04\n",
" 2.9094e-04\n",
" 2.3534e-01\n",
" 2.4942e-02\n",
" 1.3132e-04\n",
" 1.7823e-02\n",
" 1.7010e-05\n",
" 2.1813e-05\n",
" 1.3471e-05\n",
" 1.5838e-05\n",
" 4.8694e-06\n",
" 3.0307e-05\n",
" 1.1366e-01\n",
" 4.4294e-05\n",
" 4.5411e-05\n",
" 1.9422e-05\n",
" 2.8304e-01\n",
" 4.2274e-05\n",
" 3.1824e-05\n",
" 4.1937e-05\n",
" 2.1202e-05\n",
" 1.4217e+00\n",
" 5.6688e+00\n",
" 6.3756e-05\n",
" 2.3630e-05\n",
" 2.1025e-06\n",
" 9.9421e-02\n",
" 6.7157e-06\n",
" 1.1267e-05\n",
" 1.7153e-01\n",
" 4.9026e-06\n",
" 1.7071e-01\n",
" 2.8186e-02\n",
" 5.9749e-01\n",
" 2.0170e-05\n",
" 3.7440e+00\n",
" 1.7805e-05\n",
" 3.5869e-06\n",
" 2.8605e-01\n",
" 8.7782e-02\n",
" 1.0984e-05\n",
" 4.1899e+00\n",
" 2.3876e-05\n",
" 1.3776e-01\n",
" 7.9306e-05\n",
" 1.1640e-05\n",
" 3.5394e-05\n",
" 2.7546e-04\n",
" 1.5698e-06\n",
" 1.9729e-06\n",
" 2.5174e-01\n",
" 6.5254e-01\n",
" 6.0419e-06\n",
" 6.2503e+00\n",
" 3.1011e-05\n",
" 5.1328e-02\n",
" 6.1270e+00\n",
" 2.8697e+00\n",
" 1.7399e-05\n",
" 4.1985e-05\n",
" 2.5586e-02\n",
" 3.5167e-01\n",
" 4.7537e-06\n",
" 6.9266e-06\n",
" 3.3323e-01\n",
" 2.5710e-04\n",
" 3.6380e-05\n",
" 6.8674e+00\n",
" 9.0483e-06\n",
" 1.6014e-05\n",
" 1.0817e-05\n",
" 3.3237e-05\n",
" 2.1958e-06\n",
" 1.7984e-05\n",
" 1.2633e-05\n",
" 1.6877e-07\n",
" 1.6081e-01\n",
" 4.6447e-06\n",
" 7.3561e-06\n",
" 5.9757e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.1.bn.running_var', \n",
" 3.6303e-05\n",
" 6.7024e-05\n",
" 5.4235e-02\n",
" 5.1356e-03\n",
" 3.3565e-06\n",
" 4.4920e-03\n",
" 3.1855e-07\n",
" 2.6009e-07\n",
" 6.1145e-07\n",
" 3.7904e-07\n",
" 7.6811e-08\n",
" 8.5661e-07\n",
" 6.2907e-02\n",
" 9.7532e-07\n",
" 6.8136e-07\n",
" 2.7929e-07\n",
" 1.1577e-01\n",
" 3.2672e-06\n",
" 9.4797e-08\n",
" 2.8717e-06\n",
" 2.0015e-07\n",
" 9.1117e-01\n",
" 8.3589e+00\n",
" 1.0567e-06\n",
" 1.7558e-06\n",
" 1.3394e-08\n",
" 2.9529e-02\n",
" 5.6320e-08\n",
" 1.6233e-07\n",
" 7.0599e-02\n",
" 2.8805e-08\n",
" 7.6354e-02\n",
" 4.6784e-03\n",
" 1.2298e-01\n",
" 2.5616e-07\n",
" 2.8811e+00\n",
" 3.1228e-07\n",
" 2.9966e-08\n",
" 5.1873e-02\n",
" 2.1567e-02\n",
" 6.6883e-07\n",
" 3.7025e+00\n",
" 4.6636e-07\n",
" 2.7070e-02\n",
" 6.0551e-06\n",
" 2.2597e-07\n",
" 1.8449e-07\n",
" 5.8589e-05\n",
" 9.0792e-09\n",
" 1.6147e-08\n",
" 2.2007e-01\n",
" 8.9547e-02\n",
" 7.5446e-08\n",
" 7.9119e+00\n",
" 5.5627e-07\n",
" 4.0713e-02\n",
" 7.4552e+00\n",
" 2.0425e+00\n",
" 1.5050e-07\n",
" 2.4783e-06\n",
" 4.8531e-03\n",
" 1.8566e-01\n",
" 3.7803e-08\n",
" 4.1020e-08\n",
" 4.3489e-02\n",
" 4.7513e-05\n",
" 1.8622e-07\n",
" 1.0191e+01\n",
" 1.8340e-07\n",
" 3.2625e-07\n",
" 1.0982e-07\n",
" 5.2538e-07\n",
" 9.5139e-09\n",
" 1.8233e-06\n",
" 6.4853e-07\n",
" 3.3042e-10\n",
" 5.1054e-02\n",
" 2.2896e-07\n",
" 1.1318e-07\n",
" 7.8123e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.2.conv1d.weight', \n",
" (0 ,.,.) = \n",
" -1.4133e+00 1.9358e+00 -2.2761e+00\n",
" -2.6115e-01 -6.4256e-01 -9.4213e-01\n",
" -5.8635e-02 2.6985e-01 -3.4424e-01\n",
" ⋮ \n",
" -3.3533e-01 -2.6463e-01 -6.2940e-01\n",
" -4.1993e-01 -4.0857e-01 -5.8928e-01\n",
" 2.4180e-01 8.2423e-01 3.4042e-01\n",
" \n",
" (1 ,.,.) = \n",
" -6.3384e-01 5.0494e-01 6.8654e-01\n",
" -6.1688e-02 2.3843e-01 8.5413e-02\n",
" 1.7572e-01 7.3334e-02 -3.5420e-01\n",
" ⋮ \n",
" 1.0617e-02 3.4396e-02 1.1085e-01\n",
" 1.0521e-01 1.0961e-01 1.7268e-01\n",
" -9.4826e-02 2.1547e-01 3.2199e-01\n",
" \n",
" (2 ,.,.) = \n",
" 5.9874e-01 1.4641e+00 -2.4349e-01\n",
" -1.1605e-01 7.6056e-02 -4.8551e-01\n",
" -4.4155e-02 9.2776e-02 -2.0977e-01\n",
" ⋮ \n",
" -5.5105e-02 1.1099e-01 3.2921e-01\n",
" -3.0498e-03 1.0972e-01 3.7460e-01\n",
" 2.8244e-01 5.9271e-01 1.1813e+00\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" -3.3863e-01 3.4396e-02 -9.0110e-01\n",
" 2.6420e-01 -1.7286e-01 -2.4213e-02\n",
" 4.7889e-02 3.2799e-01 -6.6698e-02\n",
" ⋮ \n",
" -1.3399e-01 -9.5224e-02 -7.3040e-02\n",
" -1.1115e-02 2.4881e-02 -3.5365e-02\n",
" 2.4877e-01 1.2823e-01 1.5913e-01\n",
" \n",
" (78,.,.) = \n",
" 2.5783e-01 3.3355e-01 8.9789e-02\n",
" -7.6974e-03 -5.6598e-02 -2.3089e-02\n",
" 2.2232e-02 5.1629e-03 -3.7251e-02\n",
" ⋮ \n",
" -9.2541e-02 1.7696e-02 3.5425e-02\n",
" -6.2737e-02 -5.6951e-02 -3.3937e-02\n",
" 1.1730e-01 3.1792e-01 3.2876e-01\n",
" \n",
" (79,.,.) = \n",
" 7.1183e-01 -4.5185e-02 4.4113e-01\n",
" -3.0985e-01 1.8060e-01 -7.5757e-02\n",
" -9.0891e-02 8.3236e-02 -4.6741e-02\n",
" ⋮ \n",
" -2.8031e-02 3.6725e-02 -1.4995e-01\n",
" -2.8456e-01 -4.5680e-02 -8.1578e-02\n",
" 3.2646e-01 4.2007e-01 4.3912e-01\n",
" [torch.FloatTensor of size 80x80x3]),\n",
" ('module.postnet.conv1d_banks.2.bn.weight', \n",
" 1.1050\n",
" -12.6208\n",
" -0.6726\n",
" -4.5285\n",
" 0.1909\n",
" 0.4239\n",
" -0.0046\n",
" -4.7432\n",
" -7.8804\n",
" -4.4433\n",
" -14.6568\n",
" 0.5739\n",
" 1.0171\n",
" -5.0379\n",
" -11.2187\n",
" -4.2271\n",
" -7.7085\n",
" -8.0594\n",
" -1.3077\n",
" 0.9681\n",
" -3.9361\n",
" -17.2516\n",
" -5.4521\n",
" 0.0564\n",
" 0.2879\n",
" 0.4618\n",
" -13.9111\n",
" -3.3999\n",
" 0.1262\n",
" -14.1449\n",
" -15.6368\n",
" -3.6486\n",
" 0.4093\n",
" 0.1321\n",
" 0.0248\n",
" -4.5585\n",
" -20.8631\n",
" -3.5994\n",
" -11.6284\n",
" -14.0767\n",
" -4.4640\n",
" -13.8108\n",
" -12.9264\n",
" 0.2905\n",
" -15.1739\n",
" -1.8180\n",
" -11.9922\n",
" -8.4710\n",
" -0.0151\n",
" -0.5992\n",
" 0.2398\n",
" -12.1313\n",
" -3.7233\n",
" 0.7356\n",
" -14.2762\n",
" -18.0932\n",
" -2.5095\n",
" 0.6036\n",
" -12.8876\n",
" 1.1553\n",
" -11.8942\n",
" 0.9971\n",
" -4.0731\n",
" 0.5014\n",
" -4.7933\n",
" 0.9338\n",
" 0.3654\n",
" -12.9173\n",
" 0.1026\n",
" -14.0002\n",
" -8.5936\n",
" 0.5326\n",
" -2.1148\n",
" -3.5482\n",
" -13.0111\n",
" -18.3692\n",
" 0.5072\n",
" -0.8550\n",
" -4.5312\n",
" -8.0246\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.2.bn.bias', \n",
" -0.5262\n",
" -0.2552\n",
" -0.3539\n",
" -2.0449\n",
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" -0.2403\n",
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" -4.1398\n",
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" -0.7255\n",
" -4.6119\n",
" -0.0156\n",
" -3.2841\n",
" 0.1398\n",
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" -0.3197\n",
" -0.6035\n",
" -3.9686\n",
" -0.2954\n",
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" -0.2325\n",
" -0.3792\n",
" -0.0235\n",
" -0.2452\n",
" -0.1333\n",
" 1.4335\n",
" -0.5091\n",
" -0.3646\n",
" -3.0977\n",
" -0.4734\n",
" 0.4052\n",
" -1.2922\n",
" -3.6614\n",
" -0.4880\n",
" -0.1273\n",
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" -0.4922\n",
" -0.1440\n",
" -0.4297\n",
" -0.4102\n",
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" -0.3347\n",
" -0.2140\n",
" -0.3307\n",
" -0.1347\n",
" 0.5467\n",
" 0.2248\n",
" -0.1635\n",
" -0.4661\n",
" -1.5422\n",
" -0.0478\n",
" -0.3919\n",
" -0.2397\n",
" 0.9143\n",
" -0.2806\n",
" -0.3381\n",
" -0.7008\n",
" -0.1280\n",
" -0.6332\n",
" -1.0078\n",
" -0.1564\n",
" -4.5764\n",
" -0.5432\n",
" -0.1128\n",
" -0.3690\n",
" 1.3157\n",
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" -0.4705\n",
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" -0.3958\n",
" -0.0910\n",
" 0.0476\n",
" -3.5011\n",
" -0.9231\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.2.bn.running_mean', \n",
" 5.6327e-01\n",
" 1.1281e-05\n",
" 3.5915e-01\n",
" 1.2443e-06\n",
" 3.6771e-02\n",
" 1.0874e+00\n",
" 4.7118e+00\n",
" 1.7777e-06\n",
" 4.6231e-06\n",
" 5.6352e-07\n",
" 3.9949e-05\n",
" 1.0184e-01\n",
" 2.5457e-01\n",
" 1.4301e-06\n",
" 5.0850e-06\n",
" 5.9391e-06\n",
" 5.5783e-06\n",
" 1.1063e-06\n",
" 2.1314e-04\n",
" 5.6636e-01\n",
" 1.9147e-07\n",
" 3.6496e-05\n",
" 3.3147e-05\n",
" 5.0854e+00\n",
" 2.1090e-02\n",
" 1.9207e-01\n",
" 3.2702e-05\n",
" 3.6508e-05\n",
" 8.4609e+00\n",
" 2.1203e-05\n",
" 1.6400e-05\n",
" 1.8826e-06\n",
" 1.6477e-01\n",
" 7.0851e+00\n",
" 8.7817e+00\n",
" 1.2372e-07\n",
" 5.8524e-05\n",
" 2.7282e-05\n",
" 7.8823e-06\n",
" 1.8508e-05\n",
" 2.0674e-05\n",
" 1.2403e-06\n",
" 7.4226e-06\n",
" 8.3879e-02\n",
" 5.3513e-05\n",
" 1.0964e-04\n",
" 2.9298e-06\n",
" 2.0372e-05\n",
" 5.7011e+00\n",
" 3.3937e-01\n",
" 4.5090e-02\n",
" 2.0355e-05\n",
" 7.5500e-06\n",
" 7.9768e-02\n",
" 1.0328e-05\n",
" 3.2163e-05\n",
" 3.6317e-05\n",
" 2.8576e-01\n",
" 7.1058e-06\n",
" 8.7182e-01\n",
" 6.5551e-06\n",
" 5.9124e-01\n",
" 3.8902e-07\n",
" 1.0481e+00\n",
" 3.0005e-06\n",
" 3.4302e-01\n",
" 1.0958e-01\n",
" 1.8918e-05\n",
" 7.7344e+00\n",
" 4.7039e-05\n",
" 1.6219e-05\n",
" 6.2909e-01\n",
" 2.4814e-05\n",
" 6.8329e-06\n",
" 4.5856e-05\n",
" 8.4643e-05\n",
" 5.9838e-01\n",
" 8.4416e-01\n",
" 1.6249e-07\n",
" 4.5940e-07\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.2.bn.running_var', \n",
" 8.5514e-02\n",
" 1.8193e-07\n",
" 3.7855e-01\n",
" 1.5033e-08\n",
" 6.3139e-03\n",
" 8.5694e-01\n",
" 4.1488e+00\n",
" 3.2303e-08\n",
" 3.3413e-08\n",
" 4.2499e-10\n",
" 9.4977e-07\n",
" 3.7310e-02\n",
" 2.6780e-02\n",
" 4.3901e-09\n",
" 5.3359e-08\n",
" 1.7452e-08\n",
" 7.7886e-08\n",
" 8.0926e-09\n",
" 4.5635e-06\n",
" 8.2369e-02\n",
" 3.3076e-10\n",
" 1.0183e-06\n",
" 8.9923e-07\n",
" 5.0726e+00\n",
" 5.1358e-03\n",
" 1.1375e-01\n",
" 8.6792e-07\n",
" 5.6404e-07\n",
" 1.4767e+01\n",
" 2.7675e-07\n",
" 2.7659e-07\n",
" 1.7719e-08\n",
" 5.3666e-02\n",
" 1.0820e+01\n",
" 1.5185e+01\n",
" 1.0127e-10\n",
" 1.6437e-06\n",
" 2.5839e-07\n",
" 1.6270e-07\n",
" 6.3398e-07\n",
" 5.0490e-07\n",
" 3.4103e-09\n",
" 6.3605e-08\n",
" 4.0738e-02\n",
" 1.3719e-06\n",
" 3.3032e-06\n",
" 1.4438e-08\n",
" 1.9050e-07\n",
" 6.0625e+00\n",
" 4.8638e-02\n",
" 1.6690e-02\n",
" 2.1606e-07\n",
" 4.0492e-08\n",
" 1.8964e-02\n",
" 1.5395e-07\n",
" 1.0584e-06\n",
" 1.5166e-06\n",
" 1.5925e-01\n",
" 1.2890e-07\n",
" 1.4933e-01\n",
" 5.4070e-08\n",
" 1.1468e-01\n",
" 2.1891e-09\n",
" 9.0264e-01\n",
" 1.4358e-07\n",
" 4.5188e-02\n",
" 1.1012e-01\n",
" 4.2025e-07\n",
" 1.2277e+01\n",
" 1.3405e-06\n",
" 4.2785e-07\n",
" 1.9064e-01\n",
" 4.0780e-07\n",
" 1.0703e-07\n",
" 1.2103e-07\n",
" 2.4075e-06\n",
" 4.2777e-01\n",
" 2.8713e-01\n",
" 8.7225e-10\n",
" 4.4934e-09\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.3.conv1d.weight', \n",
" (0 ,.,.) = \n",
" -1.3261e+00 -2.0517e-01 -4.4074e-01 7.2879e-02\n",
" 2.4019e-01 -1.9528e-01 -1.5823e-02 -2.8905e-01\n",
" 2.7706e-01 -4.2438e-01 -6.4276e-02 6.8291e-02\n",
" ⋮ \n",
" -5.1208e-02 -1.0592e-01 1.4846e-02 -3.9983e-03\n",
" 8.5784e-02 1.0458e-01 1.7470e-01 8.6012e-02\n",
" -2.6250e-02 -1.8079e-02 1.5872e-02 1.1640e-01\n",
" \n",
" (1 ,.,.) = \n",
" -3.0618e-01 1.9623e-01 -4.7689e-01 3.7074e-02\n",
" -5.9695e-01 -5.6618e-01 2.5753e-02 -5.4921e-02\n",
" 5.4218e-02 2.6022e-02 1.5518e-02 1.4428e-01\n",
" ⋮ \n",
" 1.2883e-01 9.6835e-02 6.7881e-02 -1.6458e-01\n",
" 1.4528e-01 4.6192e-02 1.0268e-01 -1.5206e-01\n",
" -1.3590e-02 -5.6363e-02 3.4911e-03 -3.2345e-01\n",
" \n",
" (2 ,.,.) = \n",
" -4.5412e-02 2.2586e-01 3.5024e-01 5.4553e-01\n",
" 2.3056e-02 1.1484e-02 6.0658e-02 -6.6450e-02\n",
" -9.8695e-02 7.8628e-02 6.5969e-03 3.2407e-02\n",
" ⋮ \n",
" 4.2043e-02 -1.1394e-02 -1.5054e-01 -2.1846e-02\n",
" -5.7694e-02 7.4430e-02 4.4309e-02 -1.0059e-01\n",
" 3.6066e-02 2.2695e-01 1.2893e-01 1.8071e-01\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" 9.2358e-01 -3.5119e-02 -5.9368e-01 -1.1777e-01\n",
" -4.0169e-01 2.6219e-01 3.1201e-01 -3.7066e-01\n",
" -7.5183e-02 4.6646e-02 -3.9222e-02 2.0479e-02\n",
" ⋮ \n",
" 2.2368e-02 3.6631e-02 -1.6998e-01 4.6614e-02\n",
" 2.6064e-02 5.3832e-02 9.7212e-03 1.9178e-01\n",
" 6.9384e-02 3.0382e-03 6.0725e-02 4.4700e-01\n",
" \n",
" (78,.,.) = \n",
" -1.0538e-01 -1.1898e-01 -1.0235e-01 -1.4249e-01\n",
" -8.1546e-02 -1.5799e-02 -8.2799e-02 -8.0971e-02\n",
" 5.4072e-03 3.2377e-02 5.7772e-03 4.8725e-02\n",
" ⋮ \n",
" -1.5251e-02 -5.8531e-02 2.1212e-02 -6.8767e-02\n",
" 7.3147e-03 3.5619e-03 1.1491e-01 1.1213e-01\n",
" -1.4844e-01 -1.1175e-01 -5.2830e-02 -1.0134e-01\n",
" \n",
" (79,.,.) = \n",
" 1.3038e-01 2.6935e-01 1.2239e-01 -1.0109e-01\n",
" -1.2836e-02 -2.7897e-02 6.5750e-02 1.0875e-01\n",
" -8.8257e-04 2.9252e-02 -3.2304e-02 2.3341e-02\n",
" ⋮ \n",
" -5.9310e-02 -1.7101e-02 -9.5936e-02 -2.6483e-02\n",
" 3.8124e-02 -5.4581e-02 -2.2384e-02 1.0250e-01\n",
" 1.1930e-01 1.7073e-01 5.8444e-02 2.3007e-01\n",
" [torch.FloatTensor of size 80x80x4]),\n",
" ('module.postnet.conv1d_banks.3.bn.weight', \n",
" -2.5268\n",
" 0.4578\n",
" -12.8922\n",
" 0.0399\n",
" 0.0035\n",
" 0.5769\n",
" -4.0805\n",
" -4.1822\n",
" 0.0547\n",
" -3.5851\n",
" -9.6606\n",
" -3.9226\n",
" -4.4454\n",
" -13.0319\n",
" 0.4712\n",
" -4.4964\n",
" -11.3242\n",
" 0.3891\n",
" -3.9971\n",
" -14.5917\n",
" -3.2207\n",
" -1.1421\n",
" -4.2382\n",
" -12.9617\n",
" -4.2000\n",
" 0.3799\n",
" -4.8247\n",
" -2.3899\n",
" -3.1779\n",
" -4.3621\n",
" 0.1742\n",
" -4.8606\n",
" -3.2211\n",
" 0.4293\n",
" 0.4671\n",
" 0.6593\n",
" -0.0235\n",
" 0.0619\n",
" 0.2185\n",
" -4.0747\n",
" -4.9047\n",
" 0.1288\n",
" -4.2326\n",
" 0.4182\n",
" 0.6918\n",
" 0.5098\n",
" -8.0619\n",
" 0.4858\n",
" -11.1034\n",
" -4.1302\n",
" -3.1056\n",
" 0.0811\n",
" 0.3427\n",
" -2.8402\n",
" -11.3985\n",
" -11.4768\n",
" 0.0237\n",
" -2.0880\n",
" -0.0084\n",
" -4.7499\n",
" 0.4351\n",
" -0.3997\n",
" 0.4541\n",
" -4.9137\n",
" -11.7080\n",
" 0.9272\n",
" 0.0016\n",
" -4.0587\n",
" -14.6625\n",
" -0.1130\n",
" -4.9753\n",
" 0.2320\n",
" -11.6048\n",
" -1.7832\n",
" -2.4467\n",
" -12.0570\n",
" -4.6870\n",
" -15.0827\n",
" -1.8075\n",
" -4.0728\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.3.bn.bias', \n",
" -0.1262\n",
" -0.3013\n",
" -0.8146\n",
" 0.6035\n",
" -0.3680\n",
" -0.2605\n",
" -0.3404\n",
" -3.5481\n",
" 0.0310\n",
" -0.1748\n",
" -0.4248\n",
" -0.3888\n",
" -1.1308\n",
" -0.5568\n",
" -0.5755\n",
" -3.9179\n",
" -0.4536\n",
" -0.4253\n",
" -1.2827\n",
" -0.4353\n",
" -0.3216\n",
" -3.5588\n",
" -3.9900\n",
" -0.1729\n",
" -0.7320\n",
" -0.1958\n",
" -3.7417\n",
" 0.1820\n",
" -0.3782\n",
" -3.8825\n",
" -0.0597\n",
" -4.7667\n",
" -0.2451\n",
" -0.2762\n",
" 0.2594\n",
" -0.5799\n",
" 0.0799\n",
" 0.0899\n",
" -0.0234\n",
" -0.8848\n",
" -3.8244\n",
" -0.1071\n",
" -3.9127\n",
" -0.4297\n",
" -0.1180\n",
" -0.2737\n",
" -0.5355\n",
" -0.0077\n",
" -0.1744\n",
" -4.1097\n",
" -0.0084\n",
" -0.2154\n",
" -0.4333\n",
" -0.5057\n",
" -1.2638\n",
" -0.5293\n",
" -0.3836\n",
" 0.0018\n",
" -2.3551\n",
" -4.5227\n",
" -0.0428\n",
" 0.4557\n",
" -0.3260\n",
" -3.9979\n",
" -0.1996\n",
" -0.0859\n",
" -1.3325\n",
" -4.4337\n",
" -0.5358\n",
" 1.0591\n",
" -4.1141\n",
" -0.3156\n",
" -0.1987\n",
" -0.3252\n",
" -0.3384\n",
" -0.6654\n",
" -4.1062\n",
" -0.3360\n",
" -2.9950\n",
" -3.3073\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.3.bn.running_mean', \n",
" 9.0527e-05\n",
" 6.7213e-01\n",
" 2.2939e-06\n",
" 9.4556e+00\n",
" 7.7267e+00\n",
" 2.5540e-01\n",
" 7.7247e-06\n",
" 1.1427e-08\n",
" 1.0398e+01\n",
" 9.6055e-05\n",
" 3.0045e-06\n",
" 2.4925e-06\n",
" 8.6642e-06\n",
" 3.0603e-06\n",
" 3.1670e-01\n",
" 4.4633e-06\n",
" 1.0813e-06\n",
" 3.3733e-01\n",
" 5.9336e-06\n",
" 1.1803e-05\n",
" 5.7429e-06\n",
" 1.4443e-05\n",
" 1.2036e-06\n",
" 7.2304e-06\n",
" 5.8735e-06\n",
" 3.4058e-01\n",
" 7.3811e-06\n",
" 1.1589e-04\n",
" 2.6694e-05\n",
" 1.2107e-10\n",
" 1.3585e+01\n",
" 2.1797e-06\n",
" 1.2628e-05\n",
" 2.9931e+00\n",
" 2.0679e-01\n",
" 9.1944e-01\n",
" 4.9761e+00\n",
" 1.2069e+01\n",
" 3.6748e+00\n",
" 5.5600e-06\n",
" 1.0438e-08\n",
" 7.5946e+00\n",
" 6.3475e-06\n",
" 2.8479e-01\n",
" 3.9223e-01\n",
" 1.1487e+00\n",
" 3.7495e-06\n",
" 4.1301e-01\n",
" 4.5427e-07\n",
" 5.0823e-07\n",
" 1.7342e-05\n",
" 9.3364e+00\n",
" 2.5754e-01\n",
" 1.1765e-05\n",
" 1.9680e-06\n",
" 1.3843e-06\n",
" 8.1019e+00\n",
" 1.7430e-05\n",
" 1.4960e+00\n",
" 1.1329e-06\n",
" 3.1432e-02\n",
" 8.6991e-01\n",
" 6.7299e-02\n",
" 3.7045e-06\n",
" 2.1253e-06\n",
" 8.8729e-01\n",
" 9.0992e+00\n",
" 3.5421e-07\n",
" 2.4848e-05\n",
" 2.8979e-05\n",
" 4.1043e-07\n",
" 2.8082e+00\n",
" 2.6206e-06\n",
" 1.7932e-04\n",
" 7.1267e-05\n",
" 4.8661e-07\n",
" 1.7040e-07\n",
" 4.4248e-06\n",
" 1.5325e-05\n",
" 2.1064e-06\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.3.bn.running_var', \n",
" 1.2437e-06\n",
" 3.6682e-01\n",
" 1.5979e-08\n",
" 1.6722e+01\n",
" 1.1510e+01\n",
" 3.1597e-01\n",
" 7.3698e-08\n",
" 2.7022e-12\n",
" 2.3216e+01\n",
" 2.7142e-05\n",
" 5.0977e-08\n",
" 3.0948e-08\n",
" 6.7951e-08\n",
" 3.4256e-08\n",
" 9.0787e-02\n",
" 1.9166e-07\n",
" 9.8555e-09\n",
" 1.4556e-01\n",
" 3.7993e-08\n",
" 2.0463e-07\n",
" 9.7002e-08\n",
" 6.5270e-08\n",
" 1.2219e-08\n",
" 1.5361e-07\n",
" 7.6163e-08\n",
" 1.8414e-01\n",
" 4.5620e-08\n",
" 2.9798e-06\n",
" 7.6708e-07\n",
" 3.0188e-13\n",
" 3.2307e+01\n",
" 7.0671e-08\n",
" 4.0008e-07\n",
" 1.7935e+00\n",
" 3.5820e-01\n",
" 2.9136e-01\n",
" 5.2004e+00\n",
" 3.2772e+01\n",
" 2.9079e+00\n",
" 7.3876e-08\n",
" 8.5879e-12\n",
" 1.1208e+01\n",
" 6.4916e-08\n",
" 6.4894e-02\n",
" 2.0577e-01\n",
" 5.4269e-01\n",
" 4.1126e-08\n",
" 1.7521e-01\n",
" 9.4886e-10\n",
" 2.7684e-09\n",
" 9.6865e-07\n",
" 1.6125e+01\n",
" 1.5095e-01\n",
" 1.8722e-07\n",
" 3.4655e-08\n",
" 2.8854e-08\n",
" 1.2195e+01\n",
" 2.7359e-07\n",
" 9.6612e-01\n",
" 6.5774e-09\n",
" 9.0307e-03\n",
" 3.8151e-01\n",
" 2.9937e-02\n",
" 1.8729e-07\n",
" 2.4018e-08\n",
" 1.7031e-01\n",
" 1.5647e+01\n",
" 2.8821e-09\n",
" 1.3710e-06\n",
" 6.7044e-07\n",
" 3.3338e-09\n",
" 4.7245e+00\n",
" 1.7651e-08\n",
" 4.5999e-06\n",
" 3.1728e-06\n",
" 2.7243e-09\n",
" 4.4030e-10\n",
" 4.1070e-08\n",
" 1.1915e-07\n",
" 5.6752e-08\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.4.conv1d.weight', \n",
" (0 ,.,.) = \n",
" 1.5686e+00 -6.4739e-01 1.4181e-01 4.0395e-01 -7.0657e-01\n",
" -4.1751e-01 -2.0063e-02 1.7128e-01 -4.3060e-01 9.8187e-02\n",
" -4.4967e-02 1.4617e-01 1.0732e-01 1.3728e-01 1.6912e-01\n",
" ⋮ \n",
" 1.5863e-01 1.4459e-02 -3.8073e-03 -1.2433e-01 -3.4891e-02\n",
" 1.5925e-01 6.6438e-02 -9.0607e-03 -6.1685e-02 3.7638e-03\n",
" 1.9384e-01 1.6836e-01 -5.1740e-02 -1.5689e-01 1.0534e-03\n",
" \n",
" (1 ,.,.) = \n",
" -1.7182e-01 -1.8121e-01 -1.7164e-01 -1.9797e-01 -3.2164e-01\n",
" -2.1415e-02 3.4693e-02 -2.7767e-02 1.8646e-01 9.8169e-02\n",
" -6.0786e-02 -4.2094e-02 -4.6286e-02 6.9078e-02 9.2483e-02\n",
" ⋮ \n",
" 5.5376e-02 6.4676e-02 -3.8600e-02 5.1214e-02 -8.2247e-02\n",
" 7.9675e-02 6.6527e-02 -3.0137e-02 4.3228e-02 -6.6019e-02\n",
" 2.2593e-01 1.6549e-01 1.3740e-01 1.9141e-01 7.4694e-02\n",
" \n",
" (2 ,.,.) = \n",
" 5.8797e-01 1.1582e-01 2.7823e-01 1.8149e-01 4.8132e-02\n",
" 1.1961e-01 2.0705e-01 -5.0408e-02 3.7282e-02 -1.9043e-01\n",
" -1.5806e-01 4.0247e-02 8.6887e-02 1.2589e-01 -1.8701e-01\n",
" ⋮ \n",
" -8.8763e-02 1.3013e-02 -1.0821e-02 1.5986e-02 3.8196e-02\n",
" 1.5440e-04 -5.4442e-02 8.4634e-03 -1.2476e-01 5.0944e-02\n",
" 3.9365e-01 1.0105e-01 1.2978e-01 2.1548e-02 6.2940e-02\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" -1.5847e-01 2.6119e-01 -5.9377e-02 -1.8277e+00 -1.5449e+00\n",
" 2.7968e-01 2.7494e-01 -2.2583e-01 1.4109e-01 -7.7504e-01\n",
" -6.5495e-02 -6.3089e-02 1.9451e-01 2.7907e-01 -4.3442e-02\n",
" ⋮ \n",
" 4.2854e-02 5.0023e-02 -6.5699e-02 -7.9344e-02 -1.7509e-01\n",
" 6.1825e-02 1.6443e-01 -1.5240e-02 1.2528e-01 1.4501e-01\n",
" -1.0310e-01 3.6294e-01 -8.2844e-04 1.3113e-01 1.6783e-01\n",
" \n",
" (78,.,.) = \n",
" -9.2892e-02 -2.0476e-01 -1.9328e-01 -1.6904e-01 -3.7297e-01\n",
" 6.4856e-02 -2.9276e-02 6.3521e-02 -1.6848e-02 -3.5620e-02\n",
" 1.7215e-02 6.9829e-02 -1.4160e-01 3.9499e-02 4.0538e-02\n",
" ⋮ \n",
" 3.3965e-02 6.5948e-02 2.1840e-02 5.3068e-02 -3.8973e-02\n",
" 6.9934e-02 -3.0774e-02 3.1385e-03 3.4650e-02 -5.8947e-02\n",
" 7.1828e-02 4.0206e-02 1.0805e-01 2.2138e-01 1.2469e-01\n",
" \n",
" (79,.,.) = \n",
" -1.5203e-01 -3.8435e-02 1.3500e-02 1.6194e-02 -1.2227e-01\n",
" 6.4620e-02 2.8093e-02 1.2704e-02 4.0136e-02 -2.4529e-01\n",
" -3.5442e-02 2.9202e-02 2.3826e-02 4.1322e-03 -1.2359e-01\n",
" ⋮ \n",
" -5.1499e-02 3.8150e-02 4.7023e-03 4.8181e-02 -3.8601e-02\n",
" -4.0502e-02 2.0468e-03 -5.0560e-02 5.2808e-02 8.2607e-03\n",
" 3.4581e-02 -1.8643e-03 7.2634e-02 1.5115e-01 5.9412e-02\n",
" [torch.FloatTensor of size 80x80x5]),\n",
" ('module.postnet.conv1d_banks.4.bn.weight', \n",
" -3.1114\n",
" -3.6436\n",
" -11.5585\n",
" -10.4227\n",
" -0.4435\n",
" -4.2407\n",
" -2.6719\n",
" 0.5268\n",
" -21.6844\n",
" 1.4152\n",
" 0.8414\n",
" -7.4078\n",
" 0.0875\n",
" -0.8201\n",
" -2.0815\n",
" -4.2865\n",
" 0.9424\n",
" 1.1091\n",
" -4.4419\n",
" -11.9075\n",
" -8.4086\n",
" -2.7601\n",
" 0.4206\n",
" 0.4259\n",
" 0.3753\n",
" -4.8195\n",
" 0.7709\n",
" -11.3462\n",
" 0.5276\n",
" 0.9512\n",
" -11.5833\n",
" -1.1161\n",
" 0.4165\n",
" 0.9368\n",
" 0.7865\n",
" -4.8721\n",
" -2.7109\n",
" -3.8780\n",
" -4.2648\n",
" -12.0094\n",
" 0.0308\n",
" 0.6082\n",
" -10.4139\n",
" 0.0122\n",
" 0.6591\n",
" 0.6041\n",
" -1.3099\n",
" -0.8088\n",
" 0.0389\n",
" 0.8472\n",
" -13.2373\n",
" -3.2597\n",
" -12.4455\n",
" 0.1006\n",
" -2.6336\n",
" -11.6239\n",
" -4.3382\n",
" -0.7267\n",
" 0.3470\n",
" -10.8323\n",
" 0.5100\n",
" -0.0568\n",
" 0.6117\n",
" -3.5144\n",
" 0.3754\n",
" 0.0783\n",
" -1.6908\n",
" 0.7457\n",
" -13.5645\n",
" -3.8569\n",
" -0.6424\n",
" -4.6047\n",
" -1.3007\n",
" 0.6398\n",
" 0.5641\n",
" -13.1959\n",
" -1.5564\n",
" -15.4920\n",
" -1.1279\n",
" -0.0059\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.4.bn.bias', \n",
" -0.0907\n",
" 0.1247\n",
" -0.6848\n",
" -0.6421\n",
" -0.1463\n",
" -1.9022\n",
" -0.4610\n",
" -0.3081\n",
" -0.4921\n",
" -0.6449\n",
" -0.4662\n",
" -0.1597\n",
" -0.0268\n",
" -0.0688\n",
" -0.1862\n",
" -3.4868\n",
" -0.3786\n",
" -0.2628\n",
" -1.9394\n",
" -0.4781\n",
" -0.5795\n",
" -3.9740\n",
" -0.2431\n",
" -0.3317\n",
" -0.3059\n",
" -4.1944\n",
" -0.4192\n",
" -0.4415\n",
" -0.2498\n",
" -0.1404\n",
" -0.5222\n",
" -0.0211\n",
" -0.2708\n",
" -0.6674\n",
" -0.6530\n",
" -0.5205\n",
" -0.1410\n",
" -0.2570\n",
" -0.2570\n",
" -0.4062\n",
" 0.8527\n",
" -0.5576\n",
" -0.1164\n",
" -0.2757\n",
" -0.1256\n",
" -0.6343\n",
" -0.2397\n",
" 0.1046\n",
" 1.1796\n",
" -0.1107\n",
" -0.2626\n",
" -0.7130\n",
" -0.5751\n",
" -0.1367\n",
" -0.2514\n",
" -0.5131\n",
" -2.3786\n",
" 0.1182\n",
" 0.0462\n",
" -0.6482\n",
" -0.3057\n",
" -1.7059\n",
" 0.0097\n",
" -0.2467\n",
" -0.1131\n",
" -0.2379\n",
" -0.2998\n",
" -0.0255\n",
" -0.4650\n",
" -2.1786\n",
" -0.1979\n",
" -4.2684\n",
" -0.0443\n",
" -0.1549\n",
" -0.4398\n",
" -0.5989\n",
" -0.1807\n",
" -0.5320\n",
" 0.3008\n",
" -4.1098\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.4.bn.running_mean', \n",
" 1.4791e-05\n",
" 7.1580e-06\n",
" 5.4625e-07\n",
" 1.5165e-06\n",
" 2.9518e-01\n",
" 1.1891e-05\n",
" 4.3821e-02\n",
" 1.6258e-01\n",
" 9.1277e-05\n",
" 4.3748e-01\n",
" 4.9826e-01\n",
" 4.8062e-06\n",
" 1.0348e+01\n",
" 1.1714e-01\n",
" 1.5927e-05\n",
" 1.1033e-06\n",
" 6.1062e-01\n",
" 3.8079e-01\n",
" 5.2303e-06\n",
" 8.5180e-06\n",
" 1.2921e-08\n",
" 8.4226e-07\n",
" 8.1688e-02\n",
" 1.3962e+00\n",
" 6.3438e-02\n",
" 2.4138e-06\n",
" 1.9679e+00\n",
" 1.0141e-06\n",
" 2.7648e-01\n",
" 3.3054e-01\n",
" 1.9053e-06\n",
" 2.1194e-01\n",
" 7.0494e-02\n",
" 8.1467e-01\n",
" 2.8048e-01\n",
" 7.4746e-06\n",
" 3.4446e-05\n",
" 4.9036e-05\n",
" 4.3190e-04\n",
" 3.0069e-06\n",
" 8.9921e+00\n",
" 3.8910e-01\n",
" 7.9356e-06\n",
" 1.2102e+01\n",
" 1.1947e+00\n",
" 9.2566e-01\n",
" 1.3713e-05\n",
" 4.0264e-01\n",
" 1.3412e+01\n",
" 8.5061e-01\n",
" 1.3104e-06\n",
" 3.8468e-06\n",
" 2.3956e-06\n",
" 1.9958e+01\n",
" 1.2555e-04\n",
" 1.4633e-06\n",
" 2.1924e-07\n",
" 3.1256e-01\n",
" 3.9039e+00\n",
" 3.6868e-06\n",
" 4.6208e-01\n",
" 4.9890e-01\n",
" 8.7584e-02\n",
" 2.2797e-05\n",
" 6.0309e-02\n",
" 1.0651e+01\n",
" 2.3329e-01\n",
" 3.6643e-01\n",
" 6.9491e-06\n",
" 7.5810e-06\n",
" 4.1290e-01\n",
" 3.0629e-06\n",
" 2.8954e-01\n",
" 4.0581e-01\n",
" 7.8708e-02\n",
" 8.6479e-06\n",
" 1.9115e-05\n",
" 1.5491e-05\n",
" 1.8777e-05\n",
" 3.3491e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.4.bn.running_var', \n",
" 1.5262e-06\n",
" 1.3771e-07\n",
" 5.3700e-09\n",
" 2.2306e-08\n",
" 8.0874e-02\n",
" 6.9410e-08\n",
" 3.0631e-03\n",
" 1.6535e-01\n",
" 2.8116e-06\n",
" 6.4422e-02\n",
" 1.4913e-01\n",
" 5.5257e-08\n",
" 2.0834e+01\n",
" 1.7277e-02\n",
" 2.9805e-07\n",
" 1.5038e-08\n",
" 1.0679e-01\n",
" 4.8342e-02\n",
" 8.1840e-09\n",
" 6.3791e-07\n",
" 2.6678e-11\n",
" 2.2232e-09\n",
" 5.4488e-02\n",
" 6.7553e-01\n",
" 1.8869e-02\n",
" 1.2107e-07\n",
" 2.3370e+00\n",
" 3.0896e-09\n",
" 7.6846e-02\n",
" 7.0930e-02\n",
" 2.5471e-08\n",
" 2.4525e-02\n",
" 2.3188e-02\n",
" 1.3394e-01\n",
" 7.9304e-02\n",
" 2.3824e-07\n",
" 2.9613e-06\n",
" 9.3945e-07\n",
" 4.6336e-05\n",
" 4.3658e-08\n",
" 1.5431e+01\n",
" 9.4522e-02\n",
" 1.2893e-07\n",
" 2.6148e+01\n",
" 4.4857e-01\n",
" 5.1562e-01\n",
" 6.7592e-07\n",
" 9.9170e-02\n",
" 3.2691e+01\n",
" 4.5267e-01\n",
" 3.0760e-09\n",
" 3.3099e-08\n",
" 2.6102e-08\n",
" 7.2174e+01\n",
" 5.0823e-06\n",
" 1.1059e-08\n",
" 9.1769e-10\n",
" 6.5382e-02\n",
" 5.2364e+00\n",
" 6.6680e-08\n",
" 1.0776e-01\n",
" 1.1825e-01\n",
" 3.3046e-02\n",
" 4.7272e-07\n",
" 3.1214e-02\n",
" 2.3556e+01\n",
" 1.5954e-02\n",
" 2.6601e-01\n",
" 1.4740e-07\n",
" 7.1719e-08\n",
" 9.2206e-02\n",
" 9.0131e-08\n",
" 4.1669e-02\n",
" 2.6487e-01\n",
" 3.4801e-02\n",
" 1.5547e-07\n",
" 7.8035e-07\n",
" 4.5604e-07\n",
" 3.1844e-07\n",
" 2.0638e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.5.conv1d.weight', \n",
" (0 ,.,.) = \n",
" -5.4860e-01 2.0713e-01 1.6055e+00 -5.2223e-01 1.8030e+00 2.6348e-01\n",
" -2.0093e-01 4.5769e-02 6.3496e-01 2.9092e-01 1.0631e-01 1.8241e-01\n",
" -1.3228e-01 7.9001e-02 4.3514e-02 1.4466e-01 -8.5870e-02 -1.6509e-01\n",
" ⋮ \n",
" -1.5503e-02 4.7154e-02 5.2289e-02 1.6896e-02 2.2193e-02 1.3157e-01\n",
" -1.2542e-01 -3.9076e-02 -4.4819e-02 2.0163e-01 2.1832e-01 3.3319e-01\n",
" -2.2883e-01 -2.0393e-01 -7.0349e-02 -2.6324e-02 -5.9681e-02 3.6948e-01\n",
" \n",
" (1 ,.,.) = \n",
" -1.7623e-01 -1.3750e-01 -3.1823e-02 -1.9775e-01 5.8317e-02 1.9174e-01\n",
" -3.5452e-02 -2.3127e-02 -2.1820e-02 2.3226e-02 1.4172e-01 2.6835e-01\n",
" -1.3102e-01 -2.6183e-02 -6.7891e-02 -1.7501e-02 -8.8783e-02 -5.0563e-02\n",
" ⋮ \n",
" -4.0606e-02 2.6082e-02 6.4175e-02 4.1513e-02 9.5760e-02 5.5027e-02\n",
" -1.0897e-02 9.1545e-02 4.0820e-02 5.1575e-02 4.0873e-02 -2.8130e-02\n",
" 3.7406e-02 -4.9818e-03 1.2074e-02 -1.0079e-02 1.5794e-02 3.5829e-03\n",
" \n",
" (2 ,.,.) = \n",
" 8.6653e-01 7.1018e-01 1.1930e-01 6.7257e-01 3.2135e-01 2.2231e-01\n",
" -5.5292e-01 -1.8671e-01 1.7102e-01 1.4232e-01 2.1184e-01 -8.6735e-02\n",
" 6.7562e-02 1.0823e-02 1.7989e-01 1.9343e-01 2.2654e-01 -5.1714e-02\n",
" ⋮ \n",
" -9.9573e-02 -6.6490e-02 -2.6533e-02 6.5583e-02 2.2089e-02 3.8572e-02\n",
" 5.8930e-02 -1.1670e-02 1.4769e-02 7.4453e-02 5.9849e-03 7.0727e-02\n",
" 3.0224e-01 5.2385e-03 2.7315e-01 2.0238e-01 1.1285e-01 3.0515e-01\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" -1.4380e-01 -1.2970e-01 -7.8037e-02 -1.1121e-01 -9.8119e-02 4.0675e-01\n",
" -2.5799e-01 -3.3438e-01 -2.3150e-01 -2.2831e-01 -1.6482e-01 1.7353e-01\n",
" -4.2796e-02 -4.1783e-02 1.7217e-02 3.3401e-02 4.2506e-02 -6.9167e-02\n",
" ⋮ \n",
" 2.7723e-02 3.0782e-02 9.9269e-03 3.5218e-02 -4.7910e-02 -3.2218e-02\n",
" -5.2994e-03 2.0554e-02 2.8580e-02 3.0602e-02 -1.3117e-02 -5.0382e-02\n",
" -6.8279e-02 -1.0015e-02 -1.8131e-02 -7.6639e-02 -7.6285e-02 -2.6653e-01\n",
" \n",
" (78,.,.) = \n",
" 1.0527e-01 9.4512e-02 1.0673e-01 1.6742e-01 5.7785e-02 -2.8438e-02\n",
" 7.4955e-02 3.0069e-02 6.6862e-02 3.0888e-02 3.1180e-02 1.3977e-01\n",
" 9.2024e-03 2.2835e-02 -4.1930e-02 1.0184e-01 7.6296e-02 6.0169e-03\n",
" ⋮ \n",
" -9.7722e-02 -1.0904e-03 -6.9749e-02 -6.9405e-03 -1.2642e-01 -9.5243e-02\n",
" 5.8125e-03 -6.7751e-02 1.1047e-01 8.2299e-03 -4.2008e-02 5.1742e-02\n",
" 7.3912e-02 8.3876e-02 6.2410e-02 7.7047e-02 6.0862e-02 7.4805e-02\n",
" \n",
" (79,.,.) = \n",
" -1.0010e+00 -9.8334e-02 -1.6020e+00 7.5413e-01 -4.1561e-01 1.0840e+00\n",
" 2.4568e-01 3.1564e-01 -3.4452e-01 -4.6273e-02 1.0520e+00 -9.7148e-01\n",
" -7.6527e-02 -2.2401e-01 7.9422e-02 -2.6896e-01 3.6150e-01 6.4700e-02\n",
" ⋮ \n",
" 1.4473e-01 3.2172e-01 2.0931e-01 1.8520e-01 -2.2031e-01 -1.4759e-01\n",
" -6.1705e-02 -6.6544e-03 -1.3486e-01 -9.8805e-02 -1.5604e-01 -6.9360e-02\n",
" -3.2565e-01 -4.4507e-01 -4.6296e-01 2.4712e-01 3.9803e-01 7.2480e-01\n",
" [torch.FloatTensor of size 80x80x6]),\n",
" ('module.postnet.conv1d_banks.5.bn.weight', \n",
" -1.9655\n",
" -0.9887\n",
" -10.7031\n",
" 0.2270\n",
" -2.5000\n",
" -10.3362\n",
" -5.2901\n",
" -10.6125\n",
" -4.5590\n",
" -11.7356\n",
" 0.3789\n",
" -12.5152\n",
" -2.9383\n",
" -4.9282\n",
" -1.7910\n",
" -10.5731\n",
" 0.5355\n",
" -12.9075\n",
" 0.5282\n",
" 0.5553\n",
" 0.3319\n",
" 0.1124\n",
" -4.7897\n",
" 0.2692\n",
" 0.8829\n",
" 0.3214\n",
" -9.8628\n",
" -1.3829\n",
" -0.0948\n",
" 0.1667\n",
" 0.0405\n",
" -3.3630\n",
" -9.5162\n",
" 0.5304\n",
" -11.7365\n",
" -2.2216\n",
" 0.1461\n",
" 0.5525\n",
" 0.3589\n",
" -6.6794\n",
" -0.0055\n",
" -4.9119\n",
" -10.5283\n",
" 0.9588\n",
" 0.4601\n",
" 0.3697\n",
" 0.5197\n",
" -1.0671\n",
" 0.0264\n",
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" -2.6943\n",
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" -0.7154\n",
" -11.4747\n",
" -10.0193\n",
" 0.6377\n",
" 1.0143\n",
" 0.4361\n",
" -4.1749\n",
" 0.5932\n",
" 0.4845\n",
" -8.0335\n",
" -11.2354\n",
" -8.8210\n",
" -3.1390\n",
" -11.2160\n",
" 0.0663\n",
" 0.6004\n",
" -12.1574\n",
" -2.4649\n",
" -9.8693\n",
" -10.7270\n",
" 0.5790\n",
" -0.7557\n",
" 0.9959\n",
" -3.4245\n",
" -0.0401\n",
" -4.1284\n",
" -4.7673\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.5.bn.bias', \n",
" 0.0029\n",
" -4.3787\n",
" -0.2540\n",
" -0.2102\n",
" -0.3568\n",
" -0.0817\n",
" 0.2838\n",
" -0.2897\n",
" -1.2939\n",
" -0.1694\n",
" -0.0895\n",
" 0.3677\n",
" -0.2739\n",
" -4.3863\n",
" 0.1692\n",
" -0.5726\n",
" -0.4461\n",
" -0.2443\n",
" -0.2804\n",
" 0.1098\n",
" -0.1973\n",
" 1.5201\n",
" -4.3825\n",
" -1.7465\n",
" -0.3371\n",
" -0.3231\n",
" -0.3295\n",
" -0.1735\n",
" 0.5555\n",
" -0.2971\n",
" -1.6905\n",
" -4.2038\n",
" -0.4203\n",
" -0.2420\n",
" -0.5524\n",
" -0.0997\n",
" -0.2813\n",
" -0.4033\n",
" -0.4262\n",
" -0.2482\n",
" 0.7620\n",
" -4.1580\n",
" -0.7885\n",
" -0.6467\n",
" -0.1021\n",
" -0.0127\n",
" -0.3365\n",
" -0.4070\n",
" -1.0600\n",
" 0.1982\n",
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" -0.2539\n",
" -0.3529\n",
" 0.3436\n",
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" -0.3083\n",
" -0.6688\n",
" -0.2550\n",
" -0.1713\n",
" 0.0910\n",
" -0.3509\n",
" -0.3530\n",
" -0.6210\n",
" -0.4778\n",
" -4.2850\n",
" -0.3199\n",
" 1.1630\n",
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" -0.4239\n",
" -0.2612\n",
" -0.4558\n",
" -0.3260\n",
" -0.5247\n",
" 0.0129\n",
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" -4.2348\n",
" -4.2263\n",
" -4.3344\n",
" -0.0833\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.5.bn.running_mean', \n",
" 6.6881e-05\n",
" 1.9716e-05\n",
" 4.1062e-06\n",
" 1.0871e+01\n",
" 3.4829e-05\n",
" 5.4487e-06\n",
" 1.9180e-05\n",
" 7.2671e-06\n",
" 9.0508e-06\n",
" 3.4231e-06\n",
" 3.3783e-02\n",
" 3.4214e-06\n",
" 4.0916e-05\n",
" 1.5526e-06\n",
" 1.4476e-04\n",
" 2.3460e-06\n",
" 1.0616e+00\n",
" 1.0300e-06\n",
" 1.0699e+00\n",
" 9.0276e-01\n",
" 1.0792e-01\n",
" 1.4327e+01\n",
" 2.2017e-07\n",
" 4.1265e+00\n",
" 6.1647e-01\n",
" 4.5485e-02\n",
" 1.0817e-05\n",
" 3.3503e-01\n",
" 1.6846e-05\n",
" 1.7599e+01\n",
" 1.5968e+01\n",
" 2.5268e-07\n",
" 2.2920e-06\n",
" 2.3139e-01\n",
" 6.2033e-07\n",
" 4.5507e-05\n",
" 7.7429e+00\n",
" 1.5459e-01\n",
" 7.0055e+00\n",
" 9.1036e-06\n",
" 9.9461e+00\n",
" 4.3763e-06\n",
" 1.2773e-08\n",
" 7.7017e-01\n",
" 5.2742e+00\n",
" 7.2511e-02\n",
" 2.0556e-01\n",
" 3.8826e-01\n",
" 1.4060e+01\n",
" 6.8772e+00\n",
" 2.5492e-06\n",
" 1.2919e-05\n",
" 6.1022e-06\n",
" 9.8789e-01\n",
" 1.6830e-06\n",
" 3.6800e-06\n",
" 8.8781e-01\n",
" 4.8203e-01\n",
" 1.0681e-01\n",
" 4.1911e-07\n",
" 1.6110e-01\n",
" 9.8968e-01\n",
" 4.5397e-06\n",
" 2.4744e-06\n",
" 4.6496e-06\n",
" 6.7548e-08\n",
" 5.9375e-07\n",
" 1.5855e+01\n",
" 1.8195e-01\n",
" 1.4893e-06\n",
" 2.1666e-05\n",
" 3.2978e-06\n",
" 4.4232e-05\n",
" 4.8400e-01\n",
" 6.3990e-01\n",
" 4.5483e-01\n",
" 1.0750e-07\n",
" 3.2715e-01\n",
" 2.9006e-07\n",
" 4.9801e-05\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.5.bn.running_var', \n",
" 1.2244e-06\n",
" 5.9879e-08\n",
" 4.1235e-08\n",
" 2.1726e+01\n",
" 7.6592e-07\n",
" 7.7188e-08\n",
" 1.0208e-07\n",
" 1.2389e-07\n",
" 6.8075e-08\n",
" 2.7681e-08\n",
" 3.5808e-02\n",
" 2.7561e-08\n",
" 5.8326e-07\n",
" 4.8485e-08\n",
" 3.2186e-06\n",
" 2.3307e-08\n",
" 5.5778e-01\n",
" 9.4557e-09\n",
" 6.2819e-01\n",
" 7.9096e-01\n",
" 1.0496e-01\n",
" 3.8622e+01\n",
" 1.9758e-09\n",
" 3.9146e+00\n",
" 3.4936e-01\n",
" 2.1316e-02\n",
" 2.4903e-07\n",
" 5.6055e-02\n",
" 2.3548e-07\n",
" 5.9798e+01\n",
" 4.5718e+01\n",
" 1.8836e-09\n",
" 4.9038e-08\n",
" 6.8371e-02\n",
" 5.3013e-09\n",
" 6.8085e-07\n",
" 1.2107e+01\n",
" 7.2701e-02\n",
" 8.8856e+00\n",
" 2.6411e-07\n",
" 1.7349e+01\n",
" 2.9812e-07\n",
" 1.6223e-10\n",
" 2.3136e-01\n",
" 4.9386e+00\n",
" 2.3262e-02\n",
" 1.1678e-01\n",
" 1.1364e-01\n",
" 3.5626e+01\n",
" 2.2471e+01\n",
" 3.4680e-08\n",
" 3.9239e-07\n",
" 4.5764e-08\n",
" 4.5338e-01\n",
" 2.8175e-08\n",
" 6.0937e-08\n",
" 5.9102e-01\n",
" 1.1198e-01\n",
" 4.9348e-02\n",
" 9.3823e-10\n",
" 1.3880e-01\n",
" 1.2235e+00\n",
" 5.1027e-08\n",
" 5.1064e-08\n",
" 3.4925e-08\n",
" 2.1195e-11\n",
" 7.2309e-09\n",
" 4.6023e+01\n",
" 4.7265e-02\n",
" 1.1407e-08\n",
" 7.4242e-07\n",
" 1.9322e-07\n",
" 5.6772e-07\n",
" 1.6085e-01\n",
" 4.4126e-01\n",
" 7.5727e-02\n",
" 3.8255e-10\n",
" 3.3904e-02\n",
" 3.7415e-10\n",
" 1.2396e-06\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.6.conv1d.weight', \n",
" (0 ,.,.) = \n",
" -1.0649e+00 1.3727e+00 1.9003e-01 ... -1.9994e-01 3.3153e+00 -5.1286e+00\n",
" 6.0406e-02 -2.1307e-01 1.3011e-01 ... -7.6565e-01 1.6152e-01 5.9789e-01\n",
" 7.5477e-01 -1.1030e-01 3.3991e-01 ... -9.8794e-02 1.3341e-01 -1.6148e+00\n",
" ... ⋱ ... \n",
" -2.2227e-02 1.5231e-02 1.0512e-01 ... 2.2787e-01 2.4669e-01 4.8626e-01\n",
" -6.6963e-02 -2.3941e-02 -4.3805e-03 ... 4.8652e-02 5.6056e-04 3.2899e-01\n",
" -1.3463e-01 1.1059e-01 -2.1093e-01 ... -3.8216e-01 -2.2131e-01 -4.6672e-03\n",
" \n",
" (1 ,.,.) = \n",
" 1.9496e+00 -1.3853e+00 2.4915e+00 ... -2.8040e+00 2.5646e+00 -3.2165e+00\n",
" -4.1844e-01 -4.0175e-01 1.6977e-01 ... 2.6866e-01 6.1458e-01 1.1135e-01\n",
" -5.1263e-01 -3.4525e-01 -3.1196e-02 ... -2.3048e-02 3.7472e-01 4.6155e-01\n",
" ... ⋱ ... \n",
" 1.7881e-01 1.0789e-01 2.4740e-01 ... 2.3902e-02 8.6342e-02 1.2528e-02\n",
" 1.9066e-02 -2.1986e-03 7.4409e-02 ... 1.1230e-02 6.7261e-02 1.5289e-01\n",
" -2.4646e-01 -3.2945e-01 -6.5856e-02 ... 1.2225e-01 -8.9026e-02 -9.9658e-02\n",
" \n",
" (2 ,.,.) = \n",
" 3.6556e-01 1.9130e-01 4.4784e-01 ... -1.6449e-01 6.8066e-02 -1.1009e-02\n",
" 4.2291e-02 1.3204e-01 1.5855e-01 ... 3.1037e-01 1.4537e-01 2.1174e-01\n",
" 1.3034e-01 -7.7696e-02 4.2838e-02 ... -8.1076e-02 6.7180e-02 -8.8425e-02\n",
" ... ⋱ ... \n",
" 1.0065e-03 9.5219e-02 -1.1813e-02 ... 6.7723e-03 3.1524e-02 2.6009e-02\n",
" 1.0982e-01 -1.3729e-01 4.4807e-02 ... 7.5306e-02 5.6696e-02 -1.8068e-01\n",
" 1.8904e-01 1.3797e-01 2.5836e-01 ... 2.0835e-01 1.6837e-01 1.1935e-02\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" 1.0173e+00 7.1137e-01 -7.3726e-02 ... -5.4410e-02 -4.9887e-02 -3.7306e-01\n",
" -6.0327e-01 -3.2560e-01 1.6308e-02 ... -2.2698e-01 -2.2651e-01 -4.7624e-01\n",
" -1.3541e-02 -1.5023e-02 1.1122e-01 ... 2.3900e-01 2.5451e-02 -1.3337e-01\n",
" ... ⋱ ... \n",
" -1.1223e-01 -1.4351e-03 -5.6440e-03 ... 2.6192e-02 1.3253e-02 -8.7034e-02\n",
" 3.0891e-03 1.4962e-01 5.6578e-02 ... 6.6190e-02 9.9097e-02 1.1227e-01\n",
" 1.1993e-01 1.4432e-01 6.9030e-02 ... 5.5823e-02 3.9141e-02 3.2510e-02\n",
" \n",
" (78,.,.) = \n",
" 1.6438e+00 -1.2697e-01 -4.9258e-01 ... -7.0856e-01 -3.7720e+00 -6.7071e+00\n",
" -4.9945e-01 -1.7624e-01 2.3253e-01 ... -2.7442e-01 2.8344e-01 5.4155e-01\n",
" -7.6488e-03 9.0009e-02 -7.3368e-02 ... -1.9346e-02 -5.6370e-02 -1.0089e-01\n",
" ... ⋱ ... \n",
" 3.8947e-02 8.0353e-02 7.6696e-02 ... 6.1145e-02 -1.6484e-01 -2.6345e-01\n",
" 7.9000e-02 7.5109e-02 6.8631e-02 ... 3.8451e-02 -9.6734e-02 -2.5716e-01\n",
" 2.6664e-01 1.3880e-01 2.1747e-01 ... 1.8959e-01 -2.9664e-02 -4.0854e-01\n",
" \n",
" (79,.,.) = \n",
" 6.4669e-01 9.4086e-02 -5.0195e-01 ... -2.7949e-01 -3.9004e-01 -4.9352e-01\n",
" -2.8771e-01 -1.7709e-01 -3.3198e-01 ... -6.6746e-02 1.3041e-01 -1.3144e-01\n",
" 1.8937e-01 2.3438e-01 8.7372e-02 ... -7.0633e-02 -2.0086e-01 -3.7153e-02\n",
" ... ⋱ ... \n",
" 4.0741e-02 2.6941e-02 1.8963e-01 ... 1.4338e-01 1.1682e-01 2.5949e-01\n",
" 1.1112e-01 -7.1629e-03 9.1774e-02 ... 1.5254e-01 9.0325e-03 1.7725e-01\n",
" 1.6518e-01 3.6820e-02 1.0384e-01 ... -3.3557e-02 -4.4994e-02 2.1228e-02\n",
" [torch.FloatTensor of size 80x80x7]),\n",
" ('module.postnet.conv1d_banks.6.bn.weight', \n",
" 1.1234\n",
" -1.2926\n",
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" 0.7360\n",
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" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.6.bn.running_mean', \n",
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" 9.9729e-06\n",
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" 4.5262e-01\n",
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" 5.1499e-01\n",
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" 4.1153e-01\n",
" 5.2981e-06\n",
" 2.7974e-01\n",
" 1.8517e-06\n",
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" 3.6116e-01\n",
" 3.1202e-01\n",
" 7.7057e+00\n",
" 6.4928e-06\n",
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" 2.1568e+00\n",
" 8.6376e-01\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.6.bn.running_var', \n",
" 6.9108e-02\n",
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" 6.0707e-01\n",
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" 5.9941e-01\n",
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" 3.2148e-01\n",
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" 8.8278e-02\n",
" 6.7437e-08\n",
" 1.2995e-09\n",
" 2.4064e+01\n",
" 2.4312e-07\n",
" 1.4615e-01\n",
" 1.0230e-06\n",
" 9.2319e-08\n",
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" 3.6997e-08\n",
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" 7.0912e-08\n",
" 3.2873e-01\n",
" 5.6683e-02\n",
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" 5.3004e-08\n",
" 1.1316e-01\n",
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" 2.5476e-07\n",
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" 5.3841e-02\n",
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" 9.7681e-02\n",
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" 7.7248e-08\n",
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" 9.6119e-08\n",
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" 3.4932e-01\n",
" 5.6417e-02\n",
" 1.1625e+01\n",
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" 5.8041e-01\n",
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" 2.4081e-08\n",
" 1.9565e+00\n",
" 7.4052e-01\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.7.conv1d.weight', \n",
" (0 ,.,.) = \n",
" 1.0529e+00 3.8757e+00 3.7754e+00 ... 4.4254e-01 -3.4523e-01 -1.0291e-01\n",
" 1.5095e+00 2.4575e+00 1.6089e+00 ... 1.7952e-01 -1.2080e+00 -6.9600e-01\n",
" 6.5311e-01 1.1343e+00 1.4454e+00 ... 8.3564e-01 7.0717e-01 -1.5440e-01\n",
" ... ⋱ ... \n",
" -5.8892e-01 -6.6297e-01 -3.7407e-01 ... -2.4059e-03 4.1757e-01 3.0214e-01\n",
" -2.3222e-01 -4.4655e-01 -4.5594e-01 ... 1.1238e-02 4.7837e-01 1.5670e-01\n",
" 1.1653e+00 3.5081e-01 -2.5347e-01 ... -2.3556e-01 2.3423e-01 -1.9039e-01\n",
" \n",
" (1 ,.,.) = \n",
" -1.6885e+00 1.9148e+00 -8.8712e-01 ... -5.7404e-01 9.3855e-01 -1.8792e+00\n",
" 6.1432e-02 -4.1108e-01 4.7087e-02 ... -8.2081e-01 -6.1591e-01 -9.2098e-02\n",
" 1.9864e-02 2.4329e-02 -9.4784e-03 ... 3.0884e-01 1.7533e-01 1.2645e-01\n",
" ... ⋱ ... \n",
" 8.2526e-02 8.2653e-02 -5.7011e-02 ... 3.6185e-01 3.3817e-01 4.4439e-01\n",
" 1.6853e-01 7.1762e-02 -3.8038e-02 ... 2.2377e-01 1.5718e-01 1.7180e-01\n",
" 1.4553e-01 -1.6342e-01 -1.1863e-01 ... 1.0773e-01 -2.1940e-01 -9.9362e-02\n",
" \n",
" (2 ,.,.) = \n",
" -5.3311e-02 2.3856e-01 3.6569e-01 ... 9.0417e-02 3.6500e-01 6.7456e-01\n",
" 1.5800e-01 1.5400e-01 -1.4746e-01 ... -1.0636e-02 9.1024e-02 -7.5079e-03\n",
" -1.4288e-01 4.5058e-02 7.4069e-02 ... 7.3295e-02 7.5404e-02 2.2525e-01\n",
" ... ⋱ ... \n",
" 8.2440e-02 6.3924e-02 -1.6160e-01 ... 5.9316e-02 2.6346e-02 -2.0503e-02\n",
" -1.0922e-03 1.1213e-01 -1.8133e-01 ... 4.4410e-02 1.0853e-01 -4.5268e-02\n",
" 3.2731e-01 3.3002e-01 -1.4442e-01 ... 7.0902e-02 1.3694e-01 2.7840e-01\n",
" ...\n",
" \n",
" (77,.,.) = \n",
" 4.3486e-01 3.6720e-01 1.1861e-01 ... -1.2157e-01 3.8807e-01 1.3101e+00\n",
" -4.6372e-02 5.2028e-02 2.9571e-01 ... 4.1118e-01 1.7782e-01 2.5223e-01\n",
" -1.6780e-01 -3.2026e-01 7.4724e-02 ... -2.3654e-01 -3.5995e-01 5.3968e-02\n",
" ... ⋱ ... \n",
" -1.0499e-01 -2.9694e-02 -3.1468e-02 ... -1.5553e-01 -1.7116e-01 -1.2240e-01\n",
" -2.0299e-01 -7.8974e-02 -2.1433e-02 ... -1.7333e-01 -1.5325e-01 -1.1611e-01\n",
" -1.4810e-01 -8.7836e-02 4.9869e-01 ... 2.8257e-01 2.5560e-01 3.3153e-01\n",
" \n",
" (78,.,.) = \n",
" 3.1916e-01 -5.1179e-01 -5.4707e-01 ... 5.5400e-01 -5.0809e-01 -2.0861e+00\n",
" -1.9279e+00 -7.0329e-01 -8.3487e-01 ... -4.5820e-02 1.2540e+00 1.3178e+00\n",
" 2.2729e-01 3.3453e-01 9.6079e-02 ... -3.1711e-01 2.8326e-01 2.2800e-01\n",
" ... ⋱ ... \n",
" 7.6057e-03 -1.9277e-01 5.0295e-02 ... 8.5391e-02 1.8244e-01 3.4017e-01\n",
" 3.2960e-02 -1.0860e-01 5.6157e-02 ... 1.4160e-01 3.2270e-01 3.4672e-01\n",
" 3.1290e-01 7.7094e-02 1.4394e-01 ... 2.8697e-01 1.1527e-01 1.4380e-01\n",
" \n",
" (79,.,.) = \n",
" 4.3437e-02 -1.3139e-01 -2.8921e-01 ... -3.6401e-01 -3.9041e-01 -3.4898e-01\n",
" -6.4615e-02 -1.1073e-01 -9.7782e-02 ... -1.9688e-02 -5.5769e-02 2.3761e-02\n",
" -1.0203e-01 -7.6795e-02 -6.0822e-02 ... -8.2102e-02 1.5033e-01 2.0831e-01\n",
" ... ⋱ ... \n",
" 2.2731e-01 1.8507e-01 1.3185e-01 ... 8.3878e-02 -2.1591e-02 -6.5322e-02\n",
" 1.1341e-01 4.7051e-02 5.4270e-02 ... 4.8335e-04 -4.4908e-02 -1.3254e-01\n",
" -1.3947e-03 6.5450e-02 6.8548e-02 ... -5.2640e-02 -6.0732e-02 -1.5454e-01\n",
" [torch.FloatTensor of size 80x80x8]),\n",
" ('module.postnet.conv1d_banks.7.bn.weight', \n",
" 0.2272\n",
" -1.2905\n",
" -11.5955\n",
" -10.1562\n",
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" [torch.FloatTensor of size 80]),\n",
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" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.7.bn.running_mean', \n",
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" 1.1157e-02\n",
" 4.1637e-01\n",
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" 7.8001e-01\n",
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" 1.6747e-06\n",
" 2.0335e-05\n",
" 5.0371e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_banks.7.bn.running_var', \n",
" 3.5441e-02\n",
" 2.7839e-02\n",
" 8.9386e-09\n",
" 9.2294e-08\n",
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" 4.8367e-07\n",
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" 6.9106e-08\n",
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" 2.1669e-01\n",
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" 5.0283e-08\n",
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" 3.4354e-09\n",
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" 8.2092e-02\n",
" 8.8085e-07\n",
" 2.4429e-02\n",
" 5.6086e-10\n",
" 1.5524e-02\n",
" 8.6545e-02\n",
" 7.6177e-02\n",
" 2.7218e-01\n",
" 1.9632e-07\n",
" 2.0211e-01\n",
" 6.7753e+01\n",
" 1.6525e-01\n",
" 1.1700e-01\n",
" 3.5328e-02\n",
" 9.9202e+01\n",
" 4.7470e-02\n",
" 6.9109e-08\n",
" 1.7118e-11\n",
" 9.1332e-08\n",
" 1.7900e-01\n",
" 5.3306e-11\n",
" 6.9717e-02\n",
" 1.6193e-08\n",
" 3.3868e-06\n",
" 5.5110e-07\n",
" 3.8218e-02\n",
" 1.4721e-11\n",
" 8.3060e-02\n",
" 2.7641e-01\n",
" 1.0380e-01\n",
" 2.5674e-02\n",
" 1.8893e-06\n",
" 3.2152e-01\n",
" 1.8757e+01\n",
" 9.2221e-09\n",
" 7.9450e-07\n",
" 4.9587e+00\n",
" [torch.FloatTensor of size 80]),\n",
" ('module.postnet.conv1d_projections.0.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" -1.3957e-01 -1.2377e-01 -7.3275e-02\n",
" -1.4006e-02 1.5525e-01 2.0347e-01\n",
" 3.1622e-02 -1.2623e-02 2.2276e-01\n",
" ⋮ \n",
" 5.6694e-03 6.4154e-02 1.2554e-01\n",
" -1.9284e-01 -2.1595e-01 -3.1800e-01\n",
" -5.1342e-02 -7.2566e-02 -8.4694e-02\n",
" \n",
" ( 1 ,.,.) = \n",
" 1.2366e-01 4.6452e-02 4.3532e-02\n",
" -3.3146e-02 1.1825e-01 4.0882e-02\n",
" 1.7882e-01 8.2681e-02 -2.3802e-01\n",
" ⋮ \n",
" -2.5566e-02 6.5342e-02 2.3106e-02\n",
" 6.9835e-02 1.1464e-01 9.0261e-02\n",
" -1.3521e-01 -1.4328e-01 -2.3939e-01\n",
" \n",
" ( 2 ,.,.) = \n",
" 4.3039e-02 1.7098e-01 2.8486e-01\n",
" -1.0624e-01 -4.0530e-02 -2.6259e-02\n",
" 3.6910e-01 2.5975e-01 3.2112e-01\n",
" ⋮ \n",
" 5.4088e-03 -2.3620e-02 -1.2758e-02\n",
" -2.0870e-02 -7.2901e-02 8.4686e-02\n",
" -4.1611e-02 -5.8244e-02 -1.3187e-01\n",
" ... \n",
" \n",
" (253,.,.) = \n",
" 6.7897e-02 3.1555e-01 -1.0163e-01\n",
" 8.5174e-02 9.9121e-03 -2.6476e-02\n",
" -1.3393e-01 -4.0839e-01 -1.3982e-01\n",
" ⋮ \n",
" 1.8264e-01 3.2260e-02 2.5612e-02\n",
" 2.6153e-02 -5.8576e-02 -7.5391e-02\n",
" -8.1473e-02 -6.3125e-02 -1.1814e-01\n",
" \n",
" (254,.,.) = \n",
" 3.1201e-02 1.7619e-01 5.9133e-02\n",
" 8.9054e-02 -8.6981e-03 -2.5639e-02\n",
" 1.9719e-02 4.4718e-01 1.6546e-01\n",
" ⋮ \n",
" -1.0220e-02 -8.4788e-02 1.4365e-01\n",
" -3.9882e-01 7.7564e-03 2.0031e-02\n",
" -1.8677e-01 -2.0325e-01 -2.1621e-01\n",
" \n",
" (255,.,.) = \n",
" 1.5317e-01 3.0041e-02 4.7304e-01\n",
" 1.6127e-02 -9.4994e-02 1.3071e-01\n",
" -8.1051e-02 -1.4608e-01 -1.1953e-01\n",
" ⋮ \n",
" -1.0212e-01 6.9462e-02 1.4669e-01\n",
" 1.3095e-01 2.4410e-01 1.6540e-01\n",
" -7.0448e-02 -2.9191e-03 -5.3479e-02\n",
" [torch.FloatTensor of size 256x640x3]),\n",
" ('module.postnet.conv1d_projections.0.bn.weight', \n",
" 1.0064\n",
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" 0.6797\n",
" 0.1785\n",
" 1.0887\n",
" 0.8183\n",
" 0.8454\n",
" 0.6532\n",
" 1.1385\n",
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" 1.1892\n",
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" 0.6308\n",
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" 1.4810\n",
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" 0.5903\n",
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" 1.2013\n",
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" [torch.FloatTensor of size 256]),\n",
" ('module.postnet.conv1d_projections.0.bn.bias', \n",
" 1.2812\n",
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" 7.9118\n",
" [torch.FloatTensor of size 256]),\n",
" ('module.postnet.conv1d_projections.1.conv1d.weight', \n",
" ( 0 ,.,.) = \n",
" 5.2195e-02 1.9907e-02 -7.0854e-02\n",
" 2.7770e-01 1.4073e+00 1.1054e+00\n",
" 5.4670e-01 4.2194e-01 -1.3198e-01\n",
" ⋮ \n",
" 1.9469e-01 1.1500e-01 -1.7242e-01\n",
" 6.7335e-01 1.2255e+00 3.9269e-01\n",
" 1.7183e-03 4.5895e-01 5.6313e-01\n",
" \n",
" ( 1 ,.,.) = \n",
" -1.0461e-01 -1.1721e-01 -2.7959e-01\n",
" 2.5528e-01 7.7451e-01 4.1646e-01\n",
" 9.0024e-02 4.9471e-01 6.7004e-01\n",
" ⋮ \n",
" -1.1452e-01 3.7357e-01 -5.2436e-01\n",
" 8.3869e-01 1.3527e+00 6.5560e-01\n",
" 3.7751e-01 6.1575e-01 5.9562e-02\n",
" \n",
" ( 2 ,.,.) = \n",
" 9.4125e-02 8.5159e-02 1.2492e-01\n",
" 8.1844e-01 1.6799e+00 1.2010e+00\n",
" 6.1985e-01 8.4654e-01 5.3842e-01\n",
" ⋮ \n",
" 1.4908e-02 1.7344e-01 -2.5035e-03\n",
" 1.3253e+00 1.9885e+00 1.3415e+00\n",
" 6.8385e-01 7.1794e-01 3.1948e-01\n",
" ... \n",
" \n",
" (77 ,.,.) = \n",
" -1.0669e-01 -8.0844e-02 -2.5232e-01\n",
" 1.1422e-02 1.0861e+00 5.3154e-01\n",
" 5.2617e-01 6.5394e-01 -6.2136e-02\n",
" ⋮ \n",
" 4.6888e-01 4.8954e-01 2.3976e-01\n",
" 9.7884e-01 1.8881e+00 5.1218e-01\n",
" 1.9927e-01 7.5671e-01 6.0120e-03\n",
" \n",
" (78 ,.,.) = \n",
" -1.1719e-01 4.8443e-02 9.3944e-02\n",
" 5.3119e-01 1.1578e+00 4.9808e-01\n",
" 8.0624e-01 1.2984e+00 4.4143e-01\n",
" ⋮ \n",
" 3.4782e-01 4.7327e-01 1.8600e-01\n",
" 8.2889e-01 1.0548e+00 4.3066e-01\n",
" 2.2504e-01 2.0290e-01 2.1498e-01\n",
" \n",
" (79 ,.,.) = \n",
" 1.1439e-01 -1.7348e-02 -3.0525e-01\n",
" 2.0294e-01 7.2653e-01 4.0443e-01\n",
" 4.9828e-01 4.0238e-01 1.2768e-01\n",
" ⋮ \n",
" 2.4098e-01 1.2117e-01 4.9355e-01\n",
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" 3.7854e-01 4.1184e-01 3.0943e-01\n",
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" ('module.postnet.pre_highway.weight', \n",
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" -3.6340e-04 -6.7453e-02 -8.3466e-02 ... -7.3356e-02 5.7696e-02 -4.9411e-02\n",
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" [torch.FloatTensor of size 240]),\n",
" ('module.last_linear.weight', \n",
" 9.0400e-03 -7.2088e-03 -1.4630e-02 ... 6.1971e-03 -1.5822e-03 -2.7374e-03\n",
" 1.1868e-02 -4.7611e-03 -1.6505e-02 ... 6.2229e-03 -1.4371e-03 -2.4970e-03\n",
" 1.3643e-02 -4.6501e-03 -2.1297e-02 ... 1.0202e-02 -2.7155e-03 -2.3471e-03\n",
" ... ⋱ ... \n",
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" 2.5341e-03 -6.8375e-03 1.1034e-02 ... -4.8485e-03 -3.2630e-02 -2.1417e-03\n",
" 2.9717e-03 -7.6311e-03 9.8761e-03 ... -4.5076e-03 -3.3754e-02 -2.9296e-03\n",
" [torch.FloatTensor of size 1025x160]),\n",
" ('module.last_linear.bias', \n",
" 1.00000e-04 *\n",
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" ⋮ \n",
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" [torch.FloatTensor of size 1025])])"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cp['model']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### EXAMPLES FROM TRAINING SET"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"df = pd.read_csv('/data/shared/KeithIto/LJSpeech-1.0/metadata.csv', delimiter='|')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"that he has a 5 an 8 or a 3 before him unless the press work is of the best:\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/miniconda3/envs/pytorch/lib/python3.6/site-packages/librosa/util/utils.py:1725: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" if np.issubdtype(x.dtype, float) or np.issubdtype(x.dtype, complex):\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" > Run-time: 8.474236488342285\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/miniconda3/envs/pytorch/lib/python3.6/site-packages/librosa/display.py:656: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n",
" if np.issubdtype(data.dtype, np.complex):\n"
]
},
{
"data": {
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" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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eMr9WAAAAYARJhCTTbfG4tx//PZLcNM9GAA4oNW5BoG2HHz58qhGLJi5de+2o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\nHYUAKFBlBCaY3rDI4pxHxTJnoWHu/whTsPqAaiGk6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rLnBL1Py+S0Zxq+h86M+r6XXgEQ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78tBuBbeI+VOYoC5pYsmMnnCEDozCazrlZ3WC+fsURoLFRwrrPVGI8pXc4LLRAeanzYtI/l\nPCqTqvCJPAZnMmKwgtPMfWi+4xTq3PbFjCk69l6klZzb29bbvPJEaEnp9JXV7vfBgz2nEEBZAR4i\nSwT9f2QFFJWfO3VG8Xe0O0NzsUfaVSawROi5RY5oJl7XzLCftUSorr41/hO7L9Q4UCXldT6+xi5z\ntsZywibFLgRpPE/EZaHsOTdlaYiAIm/c20CKbhPfBHS39c3PSm8QgYi8retH+ucLMwsaWQyM41k8\n6IXyuKc84y0qxt8Nz+utI4ZgBkyYJR08zvtPNfESHbrqtfZuZDWiojkPNkVXSJ1iwkqflgrxGR0D\n4ThWJrdea4/VLDV+7/QiwX+VvEwVK0JCxPCiEFKve23whRsug48PSkZQxjlx11rirQMjWpWtvPke\nZavy6kGwIGKiNeCVMtxrGNa43jO0Yn6KPtSvoug7GWFV1p4sGrEKMBz/cXBd1kC263lbHo59rSmN\n2uUJN73//WfiDp11Y6j32/9HFu/H+IsBDCKtpaznkRYyktO961wCghWiMdZAWOT3byqy/5vsDBin\n5mnB6igrQy91cLT3W+DQGW98jOakdmeIfC2gwrxnEwBwB6H3O/eFWLe0bcXfRHOWCKP1dgQc6Hui\ndhBZ0HzGcED2CzOm2JJDKQR2jqvBe2bbjz2qxbfrE1Iz7oJyw6DFnfcMXVOVawK6/0o2tfLeT7W2\nXtq/xViG+fMy7iKFHpHd8KSMdqzulKrbT27vCZvjrc3BvTJv31ka3uTQG0QIaCrAz4totEDXDTeL\nFgMtESS1Y3KWhoghiRatThdMbSa8EFN/I2qQYr5WjrxJPgmfaZusr0X3aM2dcV8YvI4GODBVZGTO\n7W2AUT1a4zO7adXPVQUd3MD5+D2z5coOZSQVxd3v4ztI918FvnwhW2tLTXaLL7ah5c74i2gnOhUT\n4Qo1Psb6OjAoMzQD6KFlAoEw/iqMdgYgwGCfUcBSfT1D+0danF69XhsxS4vxu5Vjlv8FTCrtFGG3\nPMTpfr8LKG1NVkfkuvzcAOj23BheQTNzEy0RMIL7R0p2PVpof/127ZxAwaYbd2EPxFA1MFnwq8JH\nOS7s5xFw2GYCagXzSCBvLOWgDdiflwIrqsZXwASPfpE6S8PsFuMFU+2BbxHdEYi5N76HY9/rR3Ot\nX0imNNy7LCAVVztDq+tP487A7rcwJ7PwJHWd1c8Txa44bePgo/IcZIBQOssOmJHl0Kt98r8Yi/Xl\n6N0/B71BBCCToznVgCzVF/w4iAnwL+VyMUXaN2sWbHLMShC0LNdrQEWfQdjg/yN9HkeTLYwIgAeo\ntVwiMYuuz1sBsy1XMyGRRtv2ie3zBAIm+prORDSPzrk1D2djQB/7JIwjP5Ppm4mmXdoEXIA+xTgA\nsiVjG/n/DvAQmjKqfaoycuvfHa1bwowlLSIAx3bOJCjr+N2WFwE5W7qW234lFsIdhH7fSNX8ch6i\n1L6tNnhqO97QTF//h+4M8r/jzjC0dv0Cm6iMzXL+AWNUA67mWQNmHcdnhzmL0pPOUAQ49EDGyH9e\na6u/4UQqi+PvlUKeHAOGXYx+7SkZOjSam5psbIl6RHeGMJ1np1xugsRegKO4M5yVFYKXxHWizTj0\nYyY1xoWQvVoLYaMFZ9a3RFGWYwt87Pp39u8l+P8sjeKRPIP/NSEYh4KuTq0cN+QKArFO3ew6wdzb\nnMmAvFsESEq66bSLGwPyyR+wOD7YzYB0isdSHvltOpNW3SPekyMwwY/zw88iUHme0PryTW/S9AYR\nAqr5ueOJcyXdzUwE9Rp48PzkNc9qs0C0PPjO3CamhjqHekbPRJYI1ecsm411BqVHBjE615t+9FZG\nM+FUHMnPKwJvZFbcY0xG9eScTPtrPmy/3ss0sKPUY2F2kz3Tn37da9evlEmkhYT5OWNjMEyUP1gX\nGg06joeJtWuVOW7cT6AM1GAyo3cEAT2uzfoEu/esNPQEoRvQrHX5Utk5G4kxChCpwQxZf0o5GvAk\nInqUG9giIdGagKLbeDehGbZHuPbOtOXM9zAgYzkyYKMFmtDdrlM+7hMfMI8lJgIIOERqvpoBt/vX\n91xTPOLcL+eS9pDNo1VqYK2Rd6tVhOXaZ2APUt/TgGRBB2ZlvpDLeyW+GfkXuc+zNsJz/z3zBGbR\ns0L6ilpK2TcEbAz4P5EKtnqN3RlKDC40qZ+ywDLndhLh+hpRawnTHk2ZDq9tXFJhL/X2VtzD0MWt\nKqnqHKoWfqVcLpYXXu5Xv+lNxWhJlB2FHVPe2/H9pnupDV7+26Y3iEDtBOb19ZuTAQGDkDEJss+a\nnod6JmD0vXRsYkolVgUta4yWCoc7Q2qetQEW+XppowqsiBLrHVNC/MAXSvOEcdTWRM/0BMyRJULO\ntQK0cMDNRbcHo57zOZsLewymKAsB0FghFEqjIJqeJcJ4U7bjEDdatBxp/iy20zXFY3vvFSDs10yz\nwq9msj/LxcrMgcH9XY36i/dbIzhLvZY5vCMV5hmK1qw6V5KyymnXdaMFU+8rr8H7Tyn/W/nje/n/\nl0/6Fp9F3ty5wzoGxyzGRPjYbPDKYZnqN8/fmvUBQYT2mzc0Ams7MRHQtN+00alP9spA+96aoCf3\n3h7x2P8GQI1Za3ofe/dXUc2nGXcGtDwQkJCrSy2fMElfwTpLk+ZbovXbBKhEgGqBGldKLv/Es4Yn\nhHvPZNBJal5JVgawmOTz/Hw0189QI2RiTIQttefo1rBAnpJv1hJhz/Pf501v8ugNIgQULV6vpNlY\nCN17AlPnyQYQ0UULCzcgWxG2B8uVNk2ezVE/449tfO27Jbcki7MS2NHkEgECgnqvatKjoFNcrNdX\nRksiqPmNCLVuUG7HjoeWR4/bQJXOveXIAP5dfXsX9Uz9ZoS2MKAeHI/I0ktNA4uE9mHUlNxNobty\nOX8ky8S8khHPOU2DB54lh5zf2agFMvFY1DUlNhJRFUZ/V74tBwM8AIpWWAuDan2R+dWjVwX8wrhI\njSUCmDLPgEwYWwGP3/C6l2ovIrAuzHu2ygKgUcYC95le1aCZnQEe0GoL97KmjVFkVQQTFB+D6x1q\nj83/N2sXzyyrrwD5tIvokBTjlNkqNRh/d/DHWoGBliGvolWA/CxVy78WLJCYCLxwdExQR/PYrRcs\nEVYDiL9pTO/sDAe9QQQg9AM/GIbo5vao1+iqXTqO4qcMWRJ0rvKRTy76Prcp3FrQABH9MDfwSQot\nLMoxp7Qc5V8DHyb4nkm7VuopR2/TQSAI1+CUyEQht24UOB60BcJxD2uonnJviyboMiNLhBVmI8kR\nUAsuK1uGLWTsJhbCKJBQ26jyfbb2Xi/eBX4XYcjBkkMrWJ/UPjNjhi19Xc5lDjIjKZY/E4WdoAi8\nilJB9kgDLSjUjIrrpUKMrKt6bXjV1hlFhO8RalowHV/tc7W2wFpY49K0x17GmZk+wC5dmePeHDjO\njzZpywssV/pgZzChrFcqG6vJBR60EcfWXXPlswIpXiEENx9qLzBWWsEaqdeAuh8eF9Hi4G94HL3/\ne9uzXC9a0rMpHoFEBgcQ7e4AbSZAKbZD/daxXoiqRQLyOkFFZ5toqCdkRfPWA7JNbKVBGaPyzhJ2\nzUZ2PVouRBHyk3o+nB2qR9QG/+E7Ldo2ZV1s43LNdz66hi4BRnwzpHTM+9xeTLQGePG+8fVX3Tf9\nbPQGEQrhhJQAXWrBiUgCoIiksz5VV6Kiz1DXjDySMO/clLPyq2ThUKphdLZ9Zy1cjtwZzpCszUpz\nh+4Low38aBszfwBs4LE8M+t3TFS1aroZ3EYRKEDzaIRl0v6nLSLNnxiBqj0n2rf23vrfwgu8mFY2\nagz9UcsYgwej1I71vrht1leyLXtPqc4JeNYEYlXz4Q5LBLRAmMohL0DUTJ1z110fazx2KuR3w4CH\nTGcCS2HMFi1kodlzj+4w7ojirjT38A94V9Zs/w7XK6ccM3a5bO/78Pg98Y1nwYOc47kW9avXHixD\nAERnPkfWRBic8yNZUEfuDUBi3d/opiCBFMXEOjfHtsHBXu39H1gWVjAhllb4EQ7KCeEGFHhf08vV\ndIl+k55O06O9E9tKub6HBHkW7W7UJxUwQSC5Zivy2/jM9d1xz7TAvKrSNqGtV84zv0z4bET+mtnO\nyUcwDt2C2NpA1tLN3jPMFFBvj6w8TJEohGf93+BZqsdovGH5FVCet9TV7i/T8RrU+6MVAc5Frl5b\nKgiQErksdcCDMP4TcNK9lL2Bt/M7sCLQz2Cl9xn0BhGAUHN1BFEqE9xENOcFxo4m8UnaxgKLeVZW\nltSeTxCavhsm2gs7LMxGOeeATJI/+lW6x5a0hjWMgn7DxNXagdUAWdqdwcZGOK7rzYqPVxB0/Kbf\nRPKsQgG2OWJ0eu4MsznqXQJ3hh5d8ek/A8ycIbYWYGavjr9U6s9wv/oNFhUIiHHZK5ohnX0A451E\ndCoYqgNmIqBxZij3xhCP0dlyNTAWBb49M996/XXGzHnWEmFlb7CxWrIS+Nv9guPOfSs3aDcsA1IB\nA4n/6zYm7+JJ+iyAcos0nJQMc1zX07ofEbUWCaFLGxSircUQjKjxl45e/4DAir35jX7srrn5wLXs\nLtc2k9oxiDvgEe5pmFaTSQdWrBu4LzXmve5F+O6ReferA7P+KNIWMmY8Be4hnDac9qx4wZaPnVF6\nVb4VBNjOSl+VHz7d5eqBPPUZsBmF7Yfzv0mrWoKVi+LxO89jNfDxe+xt3+8Q20QHRF01csy2uje9\naYneIAKQaBvKuQ6sWG8qR+ActNBoUtuJ1hqFj3J9y4Koo+8ktk2nYROwQoDtshlzhGdMT7lCup5F\ngUX3wcidAU3JN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OsK4h4p7L10jisCZkS9T33GncHcO0rxSET5e/uSV5RGpr/4qNizCkiN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\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JzPGRXNqosNT9lDEqOngOxp/ISIJQvhFm9hoePOcjCw+1B6Y8CIYn4Inx04AyYIkgcSSq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JxzR7hpFtQLUNP0wWoBfg5H6fDfCHH/K7veeynvv9mvasBXNi0PY0l1FXv26Ms6Zk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CRI/WzNSit3dLxkM2luvU3nCMXzORdGpVITP5LRyzK9g2BILjtEEjD0+R5rAEp2Xn48ajWO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"text/plain": [
"<matplotlib.figure.Figure at 0x7ff5ab09f4a8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = df.iloc[120, 1].lower().replace(',','')\n",
"print(sentence)\n",
"align = tts(model, sentence, CONFIG, use_cuda, ap)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### NEW EXAMPLES"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/miniconda3/envs/pytorch/lib/python3.6/site-packages/librosa/util/utils.py:1725: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
" if np.issubdtype(x.dtype, float) or np.issubdtype(x.dtype, complex):\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" > Run-time: 1.5912322998046875\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/erogol/miniconda3/envs/pytorch/lib/python3.6/site-packages/librosa/display.py:656: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n",
" if np.issubdtype(data.dtype, np.complex):\n"
]
},
{
"data": {
"text/html": [
"\n",
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AE8AiQBbABAA/P4y/xoA8v95/+z/lADQADMAzf+eALv/Df9h/5v/cgAsAAgAswC/ANIA8v9w/5P/tf9n/1b/dgBgAA0BBgCD/24A9f/A/3b+KP80AKoAdAASAP8A7QDL/0H/VP8P/wAAif+l/wABNQEfAZz/9v/d/7f+if+P/zAAawA+ACcBIQH6/4b/pf9S/zn/U//C/44AJAFUAEkAQQABACEAGP9C/hr/YwHMAFj/uAAxAUMA2/+G/lD/agCG/kAAMAFPAKcApQCoAIb+Vf8WAGX+aP/OAA8BNQEJABIAJAGm/1v/3P4P/8n/OAABAbP/swDpAVH/T/6wAA0BMv6B/hcBjQF0AKT9CwDVAVj/Ev8h/xUBYgDy/1QA6v80AtH/9fzZ/qgB8ABS/pz/YgIUAvP+/P6BANr/s/4V/4oASQBJ/40A3AHh/44A8/8S/Z3/8QAWACoA3/+n/+IAagGO/wv/YP+RAEcAK/5xAM8BiwAx/07+ewEFAZD+Jv95ACgBp/9Y/z3/2gFjALn9rwCk/wkBaAA1/2kBVv/v/sIA5ACH/uT/4gBU/5sBH/+e/m0CZ//+/vz+2/8CAtv/+f7z/jgCHwHb/QL/UgFrAU7+jf5HAEkClABe/aYApgEAAHf/F//sAA8AT/8m/2AAJwEP/0oAqP8/Af4AQf2nAdv/jv4sAbD+TwHS/lr/IANU/oQAfQAt/gUCmf8d/u0AWAAH/97/rgG//1X+XwJt/zf/zv/Z/mMEefyJ/SgE8v8j/6L+2QDZAj/+NvxvA+0BIP2FAPX/gQBEAIv9GAMhARv87v8HAq4CeP21+7YD7wEe/nb/Xv/AAbr+wgHiAKj72gH9ANX/KwBk/r3/nAIlAJr+iv+T/4YBGgBg/3f/AAAVAFgB4P+I/tAA4v84AKgAU/9r//f/ZwBlARv+Ff9jArb+0QByALr9VwKS/qz+yQOj/Sn/GAF+/54Cl/1h/8cCIP2Z/8IBhP8KAKj/HwArAnL+L/7KAZcAFv/J/fn/gwMHAo76WACqBJX+Rf7F/rEBFwBx/5//MwASAhX/+v5FArf9cP/EAvD9zACZ/sz9NQY1/8n6ugMB/90AvACu/I8B9/8xAPn/xv+C/x8CSgHn+2sAdwLQ/swAHf1e/2sGBvwK/6wCbf73Afr8agAGAnz92gFi/rIALQJP/WECAf4SAGABnPy9AuH+ev9iAg3+EQDVAa4AyvwX/3AEw/2I/uwBY/+rABIA0gDc/qEA/f4BAB8CIvzMA8j95/9pBIz6HgJzAEEAbf9O/c0B3ADJAM/92/6bAoACJfze/vwCIv7sARv+N/6sBGf9Af7BBN3+Zvy9AkkB6P02/3YBowD8/uv+nQKsAM38ZwCqAQkAqv3fAU3/9f+DAfP8NQOpAFr7/gDfAvH+o/+E/2AANf8qAWQDefqi/2IDSf9gAN38fQEaBCf93vxAA40CpPyN/n8BCQLY/VIA1gD6/IAE3v7A/FQDTf9e/8j/kf9dAgoAYfuSArMDqfxq/qkAPQRi/I78mAay/oP7lAJ7A2P9W/0OAj0B/v7H/xr/YgGxAd77tgLjAJn7Ngcs+yX7bAmJ/cX8c//CBOMAyPf5BKsD3/opAIQAUgHIAc77ggBXBCv9d/7UAnX9s/8hBL39tftrBKQC2vzj/uj/pAI4AO377f/qBbP8J/2uBCH9SwH8AFH9zwHB/lUASwKT/hT9SAJBAk7/tv22/OsG5AAs+aIB5wK7APH89f2MBQ7+zPzmArf+xQGmAOr8HgE0AtL9kQCi/0f+0QLl/3L+1f/+Av796P6oAxj8pAASAD0BvAAJ/J0Dx/95/0QAqv+p/h8BEgG9/bIBtf8J/4IB4wHg+0v/GAXq/qD6ZwNaAx78bwCq/+UBdQBA/PD/dwV//fD6cgURACcBDfuP/jMJA/sv/MkD1wDj/esCz/2E/QEHH/oDAJUEy/m2BIz/9fycA5P+s/+qANz+wP81A9L7XgH5AeX9iwJt/O4B6AAG/73+iv8OBZf51QF3Bdf35QVj/nn9BgWz+X0GHfsL/s8KRfQhA9AFXPg2BaP9Mf/6Ajr9bQH5/zz+VQGJA5P42QKxBSr5iQEcAeoAkP47/hQFx/zF/BwG4vuhAUcCZfl6BEECnf2T/hr/WQM3Ajn5HwAqCBP5+v46CO32tAJwBDP6HgV3+i8BpwYl90UDDwOi+nsG+/nA/5sKD/M9AxwGzfeeBhX8Pv/mBUz5eAOqAEn9YgKy/OYCmgLO+BsCLAaW+1f9fQL5ATD/zfxSAIwF1PvM/M4Glf0d/DgGVfwT/tYGRvlKAfsC2f0bAKD/CQFJAR79mQC0Asb8/QCHAHoBVfolBrQAufcaCLP+9/0V/8cB9gF4+4ABnQPy+kMBFgV0+HkCOgVn+a//eQWs/P/93wR5/Gb/LwUb+hwBYwT2+YoDAABf/MkE3P5c/kwA9AA9AIb/DQHp+rwGIwDP9V8NIfkY/DkM9/IPBtsCWvkjBED/2AC4+y4FKAAE+9QCTwCzAav8XP9fBGD+e/y7AsQC1fz3/8H9+QTeA5nyqgU5ClT0BACSBuL7lAIA/IQBNAS1+X4DK/9jAFAAOP0FBEP+qP6/AsP7sgMMAjH5LwPjAkz+mvxzA9wA7vtbBef7p/6wBjb7WP7IBGT9s/7cBD358gOrA/L1wwgA/176ggb9+4kBggKn+KcF1QIp+MMEUwDU/I4E6ft1AN8E7Pg4AoAEOPuTARv9aQUx/8P4jAgH/gr9KQD5Aw7/E/pDBrAA0/ucAE4BIgIt/iD7FwZxAhf3qwMBBlP5tv4WBKEBs/23+dUHMQQ289oE+Qb1+HYABwGmAY7/tPsABpP9CP2HBaL8Wv/HAZ7/IAGc/DcB2AXe9xv/sgl0/Nz2mwYGCQHykACuC1f3hwES/5v/RQiq88UDFwiq9/L+dQVhAHD60ALTAbb/h/sGBDoDhfY/B3IB+vdoBq4AlvqHBMj+Nf6SBNf6AwFAA2/+Wv0IAKcGtfrF/RkDwQIQ/XP7SgjI+5f+ywST+X0DWAWo9bICmgl19EsCcwZn+DcDUQHk/GAEd/oLAX8I6fbx/K4IBQPc8/oAJQ6o9Zn64gtt+if+/wT/+XYEHQH7+RkDrQTS+a/+MghG+aoAjQPx+mgEtP0dAPcAAv+uAAIAagDC/CwGfPqFABAEM/t3AxL9wgU099gFswVV7V4UdPfH+NkOlvO0Bjn/SPsACMn58v8jBR35twRnAGj67AWx/8n8IQG0ANQAx/2BAMsBovutBiT80/1+BBv+bABS/sEB6P5uAaf8BgUHAJb1yg1D/Yz0XA6D+Vf7mAvO9fABzgad9/ABDQaJ+IAB3wRu+C8GQf42/CoHqvoOAFICfwBV/tj8EAXvAav4JAHTCAr3IADYBa78p/1pA1sB9/keBYUAI/xpAQAD1vz2/WMGk/xr/GwEKAIh/K37wgnR/Rn3Twkt/5z70gEYAQABBv1QANIBGAHU/P39MgnP91X9BA0V9DoAUAoV9ZADgAQB+CcGSv/R+pwHsvv+/W8GD/k3A3kEhvUgB9YC8vfABfL8kQELA+z3RwRRBvL0iATBBLv3AQc5+60BNgLR/Mv/BQLJAb34OQhw/YH51Qu6+SX6lgtx+Sj/5gLJ/uIAFf52Ad7/ngJf+EgHQwE69hMJ1f5P+xUFF/3v/0ADTfyOAcP9WgYR+zv6Hg2++Zj6KgbMAXL8MPxhBgMDZ/Yt/9kOBPY+978PbPvE+iICDgMS/2v9qAG4ANf9BQFNBpfxiQlrCLzrVA2PAkD19gdg/s39tgIm/rgBF/7n/70EVfcAB+8BQPPqD/v4e/cyEsnyQ/5BDKn0mARwASH6/giQ918CkgUz+YD/owT9A9PwTQ04AaLxaxG/9JoApglZ8RkLJ/8t9zgLPfmrALoDJPlUB/L8e/vwCIz6zPsQCtr7oPkLBzwBxPx5+9AH1gAw9QkKM/+M+ZQGQ/1y/5MD2vmlA7UEIvfPAAoKf/fc+4QM8fjc+i4KPf1D+AoJrP7G+PgKW/nW+jAO+/bB+7gJw/u9/mAALgG5AF7+T/80ADUFlflA/qIJjfkN/VcF/AA1+/j/dgbB+TEBvQLQ+7cEU/x1AC0Cav0bA2T7BQS1/177mwg/9z8CYQd69OQHM/2r/9YFRfJlDSQAJ/I3DXn/C/bcCJ0BOfYXCFn+vP57ApL41wra+774dwlo/ub89f5EA7oDXfaDAoQILvgG/6MCsQIG/kf6TgdkAUL4yQEOCDz5A/rEDhr51vaoDiD7NPnuCQ/5SQEbB8vxWAwVAHvyBRC2+TT71Aar/MED+PhfBA8ECfguBMH/3gDA/TEAJgKn/pT/aAAkAA8ALgEa/YYAWQTv+338QArn95r9qwwP9Ob/Kwo0+SL8MAY+Atj3KQLQBzL3SAEBBSn6AwSE/pf9XwUl+xsCgABI/GYIEfYBA88H+/TuA0UCe//e/Z//KQKqAYX8W/yrC2L4Hvk+EMz1Ivz/C731WQSGAmj3gQhF/2v6YAQC/7kAWwCB+6wFEwCw+bMF0P7WAAL9zf7+CQD1AwEoCLr4NQCGBIj79QIl/uD+Bgbo90YD2ANS/Nv6ewqJ/grzTw4t/9j1sQbFA7/3ZgQnAWv8awSn+joEkQBL+qUF9/9p+tkEMwK290IHd/9F+roHzPkZA8UAi/qeCOH5gP7sBlf8xfvJBSEC0fXaCLP/sPgUCmX4rQCiB7D1bAOXBon3swBRBgb7Q/8LBPr7kAO//Tf+ggY0+RUB+AUD+CcClgfZ8+AFrgUI9RgGvAFa+wACpgBIADn+I//uA+T/wvg2Bh4FnvEOC5oAL/fSB5L9qP9f/4cCxftIBYD9kvo1DSbzfAKYCv/xOwPUCiD0Dv/1C9P1aQGTBA75uwf1+476JQ0Z9nL+bAh9+kQBCf33BAkABfl1BRwECPYuBX0DFfkABp35kQad/mf5GQq0+G4CJgJp+TsIVvxI/DUFMgCE/Sv9pwbb/Uv8rwJAAb7/I/vcBQ0BWvbaCov8U/qtCTX4uQMG/0L/xwJM/JsCPv3MBED9YfqeCqD7gPpFBxL+VP4LAl39SwJ5Atb33QXdBLX0OQQKCCj2mAAYB9/5oQHTAAL+7AKA/u3+AAGkAa/+r/woBlX+sPmlCOz80/umB0X5egF/BgD1AgfBABP6vAhw9XoF1ge87zoHVgo58XcBwAqv+Fr9NQScAar7cgEJAoj92QFt/bcCkACN+7UDggDH/e7/xgFMAO78LAGXBBL5wgA6CKf1vgQSAZ/8QgU6+F8H/v29+akMDPVu/10NBPH1A8YI0PP5BNsECvgvAjoFi/qi/hEHAfuW/SwGIf5g/JwA8Aax+kP6EgpY/5D32QRaAz78V/8u/4AGAfuJ+jMNcvdh+4kNrfYS/LULKPoW+y0HCv8M/UYBNQCMAGcAG/3mApv/of50AjH8+gN2/nL9QwYU+aYBiQee83oGkgVK858Jbv98+IkJ0vsD/OwGUv1b/gAAjQNJ/2n4sQpW/uH08gx9/mf20Ak0/ar85wVa+6wAVgFIACgAevpoCK39DflwCRX7SQCLAun5/AYrAJj29QdFBOj0dgOmBob7L/s2BtUAoPsaATUBIgGO/cj/6gFBAbr6HAQcAUT7wQQ0/MACxAAA+oUHff3J+/kEAADI/HQAtgPC+58BRgFH/cYBigAM/nABJADx/ZYDBf3V/0sD2fx9/1sEfvtrAGcEUvm3BaH+dvuqBg/94v6MAF8BWACc+xkFyf9o+iEGn/4J/UsDAv/4/iEBTAB1/gAC5f1hAJ0EIfhrAn4IUfP2BGQG1fQkCGL+UvsEBz/+a/mvBssE8PA5CqsFNvHZCPIBevprAyD9IAMtAXz4yAYAAsj3eAPfBcH4C//ABw/6uwAWASb+ZgSC+3f+CAeb+y/9pwU1/a0Al/09A9kBdvdRB3ACyfaFBSsDV/lWA6IAq//V/SsCGQHN+xAFVPzSAPkBdP2GASr+FwP1/eL+/AHa/+YAXfpMBwX/ofjhB3D/QftdAZMFm/n///UFVfoHAmn/bwEEAMj7OwXI/1z8uv8JBnv8PvtUBzj+3vzlARIBQP8X/7L/6wK7/eH9GwXs/Bb+jQRD/bL+rgOf/e/+nAL+/mb/VwDD/noE/frz/tAITPYQAm4GifgIAtUBAf9lAPD9UgEoA137af+KBsL6Dv5uBjj9KfzHBFEB1PguBp4Aqfl+Bn78ygGJ/7789gZB+kEAvQNn/OsBvP57AOgACv+l/+T+RgUf+tX/igZa+fwB1gE1/ckBhABY/YgBCwPU+qgA2QWv+foAEAP//N0C5Ps+AvIDF/nsAI8HAvkg/fkI8PxW+awG/QKo9a4H+QCK+B8IBvyM/YQH5/hbAAoH9fe4Ag0D7PqcBDP90P41BoT5gP9zBxH7X/wOBvIABvplAIcIV/j2/GoKUPm0/uoDg/4dAOH+DwGBADP/P/83AaIAeP24AagBKfw3AdUDAPtrAI0EdfsdAMUDnfxbAEwB0/5DAjv8PgFfBKH6If9pBhf86fxCBk380f9kAj/8FQTI/kT87AXr++oB5v/4+qkLufU//aQPh/Kv/XYOhfXp/IMK4vk1/lQE/f3Y/2QAAAB//zMBUP9T/uAClf///SEA5wL//ef+awJ//VgC3P/7/EUCJAI7/L//DwTd/UX9WwN1AV367wN3ARX7twOOAKf7RAS2AGP5XAco/9v4Ugh8/sn6KwWf/zH9OgIbACf+BQLF/qgAuP+3/nsDwvz2/+ICOP3kAI0B1fuCBBMAz/lYB5T9Jv3NBE77owO+/1379gb5+8z9Zgep+NkAAQeE9woCUwQH/Ov/KwGDAPf/Lf3XAiUCA/liBWUBs/lPBSL/Fv3DA8z+mf3hAmsAPfy5A7//p/soBuf90/pyCFb8OvvjCJT6i/77BQP7xf/iBF78Jf5RBCb/ev2kAMACV/79/bYB5gGN/iL8vAS8Alb3MgO+Bqf4ZP5jBpH/NflwBGUER/dEBBQDXPkzBdn+wfzdBdH7sv6bBcz7nv8FArv/FAB1/RIDIQCn/UQAKgL8/7H7CwQgAZD74wEZApX9FwCHAfP9+gHp/7P8rQRt/qn8fQXE/Ev/xgJK/vz/tv9AAlL9hgDMAZv9ygJQ/FICvALU+QwDiQK5/b384ARCAbz45AQcAun7NgBvAdYBXvzv/2YE8/tlABoC0P1bAaf/mv73Ar/9Lv9jA078XwK8/yX+qgEXATf+ev1hBrD88/wtBBQAAv6L/4UBBgFK/i/+9AM2/5v9XADNAqz/f/uIA0ACG/yi/8MCuwBq++kCcAIZ+uoEzf6//YEDUv3JAN4A3/73/+QAvv9S/4gAMgCV/wUAzwCz/k4AnAGE/uz+pwKI//X8XANXABT9dgA7A3D+KfwpBav/t/ttA2sA3P2DAP0ARAB3/ZUBTwI5/LX/ogQb/c78XwUA/5z8igFZAyP8QP89BKz8dAFQ/twBkgAh/PsE7fx7/8EDt/vLAYwBuPzEAsb/b/0vAkYCA/ulAGQGmfmC/k4HE/xo/DwG2/x8//ECU/p5Bqj+8PjbCYD8C/vQBq79dv49ARsAmABP/pcAfgFM/hAAHwFH/wMA//8DAMEAMv/4/roCm/5A/ggDp/5E/ygBif+8ADD+3QD8AsX6hwH7A4v8kf02BO8BFfjyBLcD/PcZBBkCgfsKAzL/7/72AkX8QQFxA4f6sQFABDb6VQE/BGf6RgJYAnn7sgJ8AYr8ggDhA9X8qv3xBIP/kfuoAqgCjfy3/+4BBgB9/1/+SQHRAsX7Vf+wBUr8hf2yBOf+7P1sAKYCYv50/cwD/v9i/BEC3QK6+oQChgL7+jADuADR/LUCr/9o/tsBn/7pAHMAT/3hAlwAFvx5A5wAa/wWAjYBEv7n/yYBvP98/zoAfP/hAAQBFfxrAo4D7vlSAHgGEPv8/DwH0PzN/NcEef55/pEB2v/z/5P/3v+mAUX+2P/+AZP9bAIj/uP+9wRD+4D/xQSZ/IP+XARe/ST+rgT8/GD+rAQi/fr9uATF/dz9tgMS/rT/WAGk/uYAAAAA/xkBMgBf/gkBnwBy/2r+GgK7APL7gQOjADn8LQLNAQ/9FwBXAhD/Nv5WAXICoPsSAU8EsPrjAMIDNPzEACkBAv+OAd38EwItAxL5QQOFBM34TQKrAyf7GAJVAX38fQM7/wD9gwRA/gj9cQR8/8H7wwOQAdb6pwLtAtz61gHNAkH8CgGBAXD+6v+dAXn+j/9UAj3+bv+TAd3/tv5YAIIBm/58/0cBkf+///L/aACg/1n/RQLF/br+6gRX/AD+uwV8/Db+nwQm/R7/twKn/uX+PwIC/y3+8wMP/an/wgL0/KECZP4I/7IDrPweACYCyv4//+4AbgDg/lwAgAARAD/+DgJ2AKP8ogKuAA3+IQCwAL8A4f4S/7cBUACK/kr/LgKCADr8TAIiAnz8sgDQAdj+bf+kALQAgf7fAMoA3f3MAYgAgv2XAWIBBP2fAbkANv48AcL/+f+V/6EACQAC/xwB1v85/5kASgCz/2D/7gBbACL+xAEuALb9SwIwAND9HAH2AO3/D/5TAKAD8vyV/dsEBQDo+mwCTgRP+xD+EQU+AKj62gEEBfn6Sf5xBUD+y/z1AuX/nv+6/zT+AQSm/kj8lgOdAXD8Xv+vA17/svwRAuQBXf3c/6YBoQDZ/HkB1wIt/HMA1QEUAAn+CgDIAjL+m/4RAkEAmv7u/0MBa//V/zcAqf6SAmv/kfxVA9YBwPoKAncDIfu5AZIBq/1MAc7/tP9uAJH/RQAdAHT/kwAnAOb+NwEfAET+vwFmALD9cwF2AQz9OAEnAqD84gCOAlf9tP9LAp/+tv+gAJL/GQF5/l3/qgOx/Uz8wwWwAPP4RgMcBcH6ZP1bBSoBG/oYAS0Fo/yL/QEDsQDM/p3+CgFKAmL9Kf+pAmP/zf5bAJsAUQA6/1X/cwFAAFv+bAAjAZH/LP9DAMAADgDb/vv/nwGF/0L+DAE9AfH+U//a/yYCSP8N/SUDfQCV/YkA+ACjAD7+af/4AiD/FP2IAqsB8PyM/1ADLf/a/HUC+gGV/M//dQMT/pX+HQJE/xkA6f9O/4ABJv8I/7sBj/9s/scBFQA7/jYBjgDO/h4A7AAS/ygAywCM/pwAagHj/cj/ngKb/kH+6QGIANL+xP9IAOMAnv/+/rYArQAk/wQAowAy/2oAhwAb//z/3wDa/9b+yQA1AQz+9f8mAqP+7/7WAbH/2P78ACUAb/8HAGkAJwAF/7IA5gA3/mMAngH6/rH+ZgETAVH+Q//hAWgA8/09AHYBBwBk/u//NAIL/w3+FALDAED9NQHZAW39GwAFAsf+/f6XAbj/0v4oAfb/d//I/7kALAD+/moAcwDo/4H/OABzAL//0v8mAEUA/P+Y/18ANgCF/4EArP+q/y0BSv/y/qoBGgAj/uMAYAFc/qD/pwE5/3L/uAC3/1MAp//E/9sAZf/x/4UASf+BAIoAnP6HABsB3f6i/9AAJgBV/8T/vgDw/zP/XwBrAJH/pv+CABMAMv/ZAPL/Af/hAFEAbP+M/5IAyQAY/0H/YwFqAEj+eABQAQ3/Y//6ABcAGv9eAMkAE/+e/3QBVP8J/0MB5P9i/1QAv/+aAPv/zv4MAYwA0f4GAPYAwf8f/7UAaQAl/14ANQCU/3gA4/+t/z4AIAADAN7/pv+VADQAAv+AAKsA6/43AM4AHf8VAGQAv/8AAPn/8P8AADIA0f/g//r/WQAhABr/bwDeAOf+7P//AIb/lP+DADAAdv9lAAQAlf/AAKf/bP/rABYA9P6pAKYA8f4lAOIAW/+C//IA8v8J/6sAaQBM//D/PwCDAEr/bP91AYT/5v4bATMAFf82AJUAt/+J/zUApgCJ/1n/4AA/ACb/GwC3ANb/WP9OANMAU/9Y/xIBNwDt/iwA4QCR/2//bgBcAKH/pv9iAFwARP8GAM8AQf/j/40A0f/M/+b/YgAKAFX/bQB3ADL/IACE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type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
],
"text/plain": [
"<IPython.lib.display.Audio object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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8w+Sfv5jkWSuO16rze2wLAAAAMLoxmgi/MMI9AQAA4BbrHruCzWHuTYTuPmve9wQAAAD2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\nkUgkEolEIpFIJBKJhIX/H3l9ReFMtzw7AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7ff5a9a16d30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sentence = \"That's all folks.\"\n",
"model.decoder.max_decoder_steps = 300\n",
"alignment = tts(model, sentence, CONFIG, use_cuda, ap)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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