Medix-AI/coqui-tts
Medix-AI
/
coqui-tts
mirror of https://github.com/coqui-ai/TTS.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

reduce glowtts size for testing

This commit is contained in:
Eren Gölge 2021-02-08 11:42:19 +00:00 committed by Eren Gölge
parent d684375291
commit d57560dcd3
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
tests/test_glow_tts.py
View File

@ -44,8 +44,8 @@ class GlowTTSTrainTest(unittest.TestCase):
# model to train # model to train
model = GlowTts( model = GlowTts(
num_chars=32, num_chars=32,
hidden_channels_enc=128, hidden_channels_enc=48,
hidden_channels_dec=128, hidden_channels_dec=48,
hidden_channels_dp=32, hidden_channels_dp=32,
out_channels=80, out_channels=80,
encoder_type='rel_pos_transformer', encoder_type='rel_pos_transformer',
@ -54,7 +54,7 @@ class GlowTTSTrainTest(unittest.TestCase):
'dropout_p': 0.1, 'dropout_p': 0.1,
'num_layers': 6, 'num_layers': 6,
'num_heads': 2, 'num_heads': 2,
'hidden_channels_ffn': 768, # 4 times the hidden_channels 'hidden_channels_ffn': 16, # 4 times the hidden_channels
'input_length': None 'input_length': None
}, },
use_encoder_prenet=True, use_encoder_prenet=True,
@ -73,8 +73,8 @@ class GlowTTSTrainTest(unittest.TestCase):
# reference model to compare model weights # reference model to compare model weights
model_ref = GlowTts( model_ref = GlowTts(
num_chars=32, num_chars=32,
hidden_channels_enc=128, hidden_channels_enc=48,
hidden_channels_dec=128, hidden_channels_dec=48,
hidden_channels_dp=32, hidden_channels_dp=32,
out_channels=80, out_channels=80,
encoder_type='rel_pos_transformer', encoder_type='rel_pos_transformer',
@ -83,7 +83,7 @@ class GlowTTSTrainTest(unittest.TestCase):
'dropout_p': 0.1, 'dropout_p': 0.1,
'num_layers': 6, 'num_layers': 6,
'num_heads': 2, 'num_heads': 2,
'hidden_channels_ffn': 768, # 4 times the hidden_channels 'hidden_channels_ffn': 16, # 4 times the hidden_channels
'input_length': None 'input_length': None
}, },
use_encoder_prenet=True, use_encoder_prenet=True,