predict stop token from rnn out + mel

layers/tacotron.py

@@ -232,11 +232,11 @@ class Decoder(nn.Module):
             [nn.GRUCell(256, 256) for _ in range(2)])
         # RNN_state -> |Linear| -> mel_spec
         self.proj_to_mel = nn.Linear(256, memory_dim * r)
-        self.stopnet = nn.Sequential(nn.Linear(memory_dim * self.r, memory_dim), 
+        self.stopnet = nn.Sequential(nn.Linear(256 + self.r * memory_dim, memory_dim),
                                      nn.ReLU(),
-                                     nn.Linear(memory_dim, memory_dim * self.r),
-                                     nn.ReLU(), 
-                                     nn.Linear(memory_dim * self.r, 1), 
+                                     nn.Linear(memory_dim, 256 + self.r * memory_dim),
+                                     nn.ReLU(),
+                                     nn.Linear(256 + self.r * memory_dim, 1),
                                      nn.Sigmoid())
 
     def forward(self, inputs, memory=None):
@@ -301,11 +301,12 @@ class Decoder(nn.Module):
                     decoder_input, decoder_rnn_hiddens[idx])
                 # Residual connectinon
                 decoder_input = decoder_rnn_hiddens[idx] + decoder_input
-            output = decoder_input
+            decoder_output = decoder_input
             # predict mel vectors from decoder vectors
-            output = self.proj_to_mel(output)
+            output = self.proj_to_mel(decoder_output)
+            stop_input = torch.cat((output, decoder_output), -1)
             # predict stop token
-            stop_token = self.stopnet(output)
+            stop_token = self.stopnet(stop_input)
             outputs += [output]
             alignments += [alignment]
             stop_tokens += [stop_token]
@@ -326,8 +327,3 @@ class Decoder(nn.Module):
         outputs = torch.stack(outputs).transpose(0, 1).contiguous()
         stop_tokens = torch.stack(stop_tokens).transpose(0, 1)
         return outputs, alignments, stop_tokens
-
-
-def is_end_of_frames(output, alignment, eps=0.05):  # 0.2
-    return ((output.data <= eps).prod(0) > 0).any() \
-            and alignment.data[:, int(alignment.shape[1]/2):].sum() > 0.7

notebooks/TacotronPlayGround.ipynb

@@ -76,8 +76,8 @@
    "outputs": [],
    "source": [
     "# Set constants\n",
-    "ROOT_PATH = '/data/shared/erogol_models/May-11-2018_08:38AM-torch4-seed-stop-token-separate-dc3f909/'\n",
-    "MODEL_PATH = ROOT_PATH + '/checkpoint_45872.pth.tar'\n",
+    "ROOT_PATH = '/data/shared/erogol_models/May-14-2018_07:02AM-torch4-seed-stop-token-separate-d629daf/'\n",
+    "MODEL_PATH = ROOT_PATH + '/checkpoint_27448.pth.tar'\n",
     "CONFIG_PATH = ROOT_PATH + '/config.json'\n",
     "OUT_FOLDER = ROOT_PATH + '/test/'\n",
     "CONFIG = load_config(CONFIG_PATH)\n",
@@ -260,9 +260,12 @@
        "    )\n",
        "    (proj_to_mel): Linear(in_features=256, out_features=400, bias=True)\n",
        "    (stopnet): Sequential(\n",
-       "      (0): Dropout(p=0.2)\n",
-       "      (1): Linear(in_features=400, out_features=1, bias=True)\n",
-       "      (2): Sigmoid()\n",
+       "      (0): Linear(in_features=400, out_features=80, bias=True)\n",
+       "      (1): ReLU()\n",
+       "      (2): Linear(in_features=80, out_features=400, bias=True)\n",
+       "      (3): ReLU()\n",
+       "      (4): Linear(in_features=400, out_features=1, bias=True)\n",
+       "      (5): Sigmoid()\n",
        "    )\n",
        "  )\n",
        "  (postnet): CBHG(\n",
@@ -426,7 +429,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " >  Run-time: 14.215009689331055\n"
+      " >  Run-time: 1.7982141971588135\n"
      ]
     },
     {
@@ -434,7 +437,7 @@
       "text/html": [
        "\n",
        "                <audio controls=\"controls\" >\n",
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truncated
+       "                    <source 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truncated
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        "              "
@@ -448,7 +451,7 @@
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truncated
       "text/plain": [
        "<Figure size 1152x1728 with 5 Axes>"
       ]
@@ -490,7 +493,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " >  Run-time: 7.228981256484985\n"
+      " >  Run-time: 2.7674951553344727\n"
      ]
     },
     {
@@ -498,7 +501,7 @@
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truncated
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truncated
        "                    Your browser does not support the audio element.\n",
        "                </audio>\n",
        "              "
@@ -512,7 +515,7 @@
     },
     {
      "data": {
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truncated
+      "image/png": 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truncated
       "text/plain": [
        "<Figure size 1152x1728 with 5 Axes>"
       ]
@@ -932,6 +935,18 @@
    "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": "3.6.5"
   }
  },
  "nbformat": 4,