Spaces:
Running
Running
call supers
Browse files
README.md
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@@ -1,6 +1,6 @@
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---
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title: Speech analysis
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emoji:
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colorFrom: gray
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colorTo: gray
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sdk: gradio
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---
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title: Speech analysis
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emoji:
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colorFrom: gray
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colorTo: gray
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sdk: gradio
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app.py
CHANGED
@@ -89,15 +89,13 @@ def _forward(
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hidden_states, mask_time_indices=mask_time_indices, attention_mask=attention_mask
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)
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hidden_states,
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attention_mask=attention_mask,
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output_attentions=output_attentions,
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output_hidden_states=output_hidden_states,
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return_dict=return_dict,
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)
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hidden_states = encoder_outputs[0]
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if self.adapter is not None:
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raise ValueError
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@@ -111,29 +109,27 @@ def _forward_and_cnn7(
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input_values,
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attention_mask=None):
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frozen_cnn7 = self.feature_extractor(input_values)
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frozen_cnn7 = frozen_cnn7.transpose(1, 2)
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if attention_mask is not None:
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# compute reduced attention_mask corresponding to feature vectors
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attention_mask = self._get_feature_vector_attention_mask(
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frozen_cnn7.shape[1], attention_mask, add_adapter=False
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)
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hidden_states, _ = self.feature_projection(frozen_cnn7) # grad=True non frozen
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hidden_states = self._mask_hidden_states(
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hidden_states, mask_time_indices=mask_time_indices, attention_mask=attention_mask
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)
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-
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hidden_states,
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attention_mask=attention_mask,
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output_attentions=output_attentions,
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output_hidden_states=output_hidden_states,
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return_dict=return_dict,
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)
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hidden_states = encoder_outputs[0]
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if self.adapter is not None:
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raise ValueError
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hidden_states, mask_time_indices=mask_time_indices, attention_mask=attention_mask
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)
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hidden_states = self.wav2vec2.encoder(
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hidden_states,
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attention_mask=attention_mask,
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output_attentions=output_attentions,
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output_hidden_states=output_hidden_states,
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return_dict=return_dict,
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)[0]
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if self.adapter is not None:
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raise ValueError
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input_values,
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attention_mask=None):
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frozen_cnn7 = self.wav2vec2.feature_extractor(input_values)
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frozen_cnn7 = frozen_cnn7.transpose(1, 2)
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if attention_mask is not None:
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# compute reduced attention_mask corresponding to feature vectors
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attention_mask = self.wav2vec2._get_feature_vector_attention_mask(
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frozen_cnn7.shape[1], attention_mask, add_adapter=False
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)
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hidden_states, _ = self.wav2vec2.feature_projection(frozen_cnn7) # grad=True non frozen
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hidden_states = self.wav2vec2._mask_hidden_states(
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hidden_states, mask_time_indices=mask_time_indices, attention_mask=attention_mask
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)
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hidden_states = self.wav2vec2.encoder(
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hidden_states,
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attention_mask=attention_mask,
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output_attentions=output_attentions,
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output_hidden_states=output_hidden_states,
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return_dict=return_dict,
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)[0]
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if self.adapter is not None:
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raise ValueError
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