From 5629292bde3fd5bf7c81d242274bc2c8aa07c6e5 Mon Sep 17 00:00:00 2001
From: Eren Golge <egolge@mozilla.com>
Date: Fri, 16 Aug 2019 15:08:04 +0200
Subject: [PATCH] bug fixes

---
 layers/tacotron.py     | 8 ++++----
 tests/symbols_tests.py | 4 +++-
 tests/test_loader.py   | 8 +++++---
 utils/text/symbols.py  | 2 +-
 4 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/layers/tacotron.py b/layers/tacotron.py
index 09c7e923..b5b6e132 100644
--- a/layers/tacotron.py
+++ b/layers/tacotron.py
@@ -364,13 +364,13 @@ class Decoder(nn.Module):
         processed_memory = self.prenet(self.memory_input)
         # Attention RNN
         self.attention_rnn_hidden = self.attention_rnn(
-            torch.cat((processed_memory, self.current_context_vec), -1),
+            torch.cat((processed_memory, self.context_vec), -1),
             self.attention_rnn_hidden)
-        self.context_vec = self.attention_layer(
+        self.context_vec = self.attention(
             self.attention_rnn_hidden, inputs, self.processed_inputs, mask)
         # Concat RNN output and attention context vector
         decoder_input = self.project_to_decoder_in(
-            torch.cat((self.query, self.context_vec), -1))
+            torch.cat((self.attention_rnn_hidden, self.context_vec), -1))
 
         # Pass through the decoder RNNs
         for idx in range(len(self.decoder_rnns)):
@@ -390,7 +390,7 @@ class Decoder(nn.Module):
         else:
             stop_token = self.stopnet(stopnet_input)
         output = output[:, : self.r * self.memory_dim]
-        return output, stop_token, self.attention_layer.attention_weights
+        return output, stop_token, self.attention.attention_weights
 
     def _update_memory_input(self, new_memory):
         if self.use_memory_queue:
diff --git a/tests/symbols_tests.py b/tests/symbols_tests.py
index 68c909c5..9bec0f18 100644
--- a/tests/symbols_tests.py
+++ b/tests/symbols_tests.py
@@ -1,7 +1,9 @@
 import unittest
 
 from utils.text import phonemes
+from collections import Counter
 
 class SymbolsTest(unittest.TestCase):
     def test_uniqueness(self):
-        assert sorted(phonemes) == sorted(list(set(phonemes)))
+        assert sorted(phonemes) == sorted(list(set(phonemes))), " {} vs {} ".format(len(phonemes), len(set(phonemes)))
+        
\ No newline at end of file
diff --git a/tests/test_loader.py b/tests/test_loader.py
index 92d6f7e2..4051c463 100644
--- a/tests/test_loader.py
+++ b/tests/test_loader.py
@@ -1,6 +1,7 @@
 import os
 import unittest
 import shutil
+import torch
 
 from torch.utils.data import DataLoader
 from utils.generic_utils import load_config
@@ -130,10 +131,11 @@ class TestTTSDataset(unittest.TestCase):
                 # check mel_spec consistency
                 wav = self.ap.load_wav(item_idx[0])
                 mel = self.ap.melspectrogram(wav)
-                mel_dl = mel_input[0].cpu().numpy()
-                assert (abs(mel.T).astype("float32")
+                mel = torch.FloatTensor(mel)
+                mel_dl = mel_input[0]
+                assert (abs(mel.T)
                         - abs(mel_dl[:-1])
-                        ).sum() == 0
+                        ).sum() == 0, (abs(mel.T)- abs(mel_dl[:-1])).sum()
 
                 # check mel-spec correctness
                 mel_spec = mel_input[0].cpu().numpy()
diff --git a/utils/text/symbols.py b/utils/text/symbols.py
index 9b7a36b4..ee6fd2cf 100644
--- a/utils/text/symbols.py
+++ b/utils/text/symbols.py
@@ -18,7 +18,7 @@ _vowels = 'iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻ'
 _non_pulmonic_consonants = 'ʘɓǀɗǃʄǂɠǁʛ'
 _pulmonic_consonants = 'pbtdʈɖcɟkɡqɢʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟ'
 _suprasegmentals = 'ˈˌːˑ'
-_other_symbols = 'ʍwɥʜʢʡɕʑɺɧ '
+_other_symbols = 'ʍwɥʜʢʡɕʑɺɧ'
 _diacrilics = 'ɚ˞ɫ'
 _phonemes = sorted(list(_vowels + _non_pulmonic_consonants + _pulmonic_consonants + _suprasegmentals + _other_symbols + _diacrilics))