Update TTS export-onnx.py scripts for handling variable token counts (#…

…1430)
k2-fsa · Dec 25, 2023 · ddd7131 · ddd7131
1 parent c855a58
commit ddd7131
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Showing 2 changed files with 10 additions and 2 deletions.
diff --git a/egs/ljspeech/TTS/vits/export-onnx.py b/egs/ljspeech/TTS/vits/export-onnx.py
@@ -149,6 +149,7 @@ def forward(
 def export_model_onnx(
     model: nn.Module,
     model_filename: str,
+    vocab_size: int,
     opset_version: int = 11,
 ) -> None:
     """Export the given generator model to ONNX format.
@@ -165,10 +166,12 @@ def export_model_onnx(
         The VITS generator.
       model_filename:
         The filename to save the exported ONNX model.
+      vocab_size:
+        Number of tokens used in training.
       opset_version:
         The opset version to use.
     """
-    tokens = torch.randint(low=0, high=79, size=(1, 13), dtype=torch.int64)
+    tokens = torch.randint(low=0, high=vocab_size, size=(1, 13), dtype=torch.int64)
     tokens_lens = torch.tensor([tokens.shape[1]], dtype=torch.int64)
     noise_scale = torch.tensor([1], dtype=torch.float32)
     noise_scale_dur = torch.tensor([1], dtype=torch.float32)
@@ -244,6 +247,7 @@ def main():
     export_model_onnx(
         model,
         model_filename,
+        params.vocab_size,
         opset_version=opset_version,
     )
     logging.info(f"Exported generator to {model_filename}")

diff --git a/egs/vctk/TTS/vits/export-onnx.py b/egs/vctk/TTS/vits/export-onnx.py
@@ -159,6 +159,7 @@ def forward(
 def export_model_onnx(
     model: nn.Module,
     model_filename: str,
+    vocab_size: int,
     opset_version: int = 11,
 ) -> None:
     """Export the given generator model to ONNX format.
@@ -175,10 +176,12 @@ def export_model_onnx(
         The VITS generator.
       model_filename:
         The filename to save the exported ONNX model.
+      vocab_size:
+        Number of tokens used in training.
       opset_version:
         The opset version to use.
     """
-    tokens = torch.randint(low=0, high=79, size=(1, 13), dtype=torch.int64)
+    tokens = torch.randint(low=0, high=vocab_size, size=(1, 13), dtype=torch.int64)
     tokens_lens = torch.tensor([tokens.shape[1]], dtype=torch.int64)
     noise_scale = torch.tensor([1], dtype=torch.float32)
     noise_scale_dur = torch.tensor([1], dtype=torch.float32)
@@ -261,6 +264,7 @@ def main():
     export_model_onnx(
         model,
         model_filename,
+        params.vocab_size,
         opset_version=opset_version,
     )
     logging.info(f"Exported generator to {model_filename}")