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Call the logits probs in `create_inference_graph` after they go thru softmax

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Catalin Voss 2020-11-03 09:49:27 -08:00 committed by GitHub
parent 9a92fa40ca
commit 98e75c3c03
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1 changed files with 3 additions and 3 deletions
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6
training/deepspeech_training/train.py
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@ -730,7 +730,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
logits = tf.squeeze(logits, [1]) logits = tf.squeeze(logits, [1])
# Apply softmax for CTC decoder # Apply softmax for CTC decoder
logits = tf.nn.softmax(logits, name='logits') probs = tf.nn.softmax(logits, name='logits')
if batch_size <= 0: if batch_size <= 0:
if tflite: if tflite:
@ -743,7 +743,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
'input_lengths': seq_length, 'input_lengths': seq_length,
}, },
{ {
'outputs': logits, 'outputs': probs,
}, },
layers layers
) )
@ -763,7 +763,7 @@ def create_inference_graph(batch_size=1, n_steps=16, tflite=False):
inputs['input_lengths'] = seq_length inputs['input_lengths'] = seq_length
outputs = { outputs = {
'outputs': logits, 'outputs': probs,
'new_state_c': new_state_c, 'new_state_c': new_state_c,
'new_state_h': new_state_h, 'new_state_h': new_state_h,
'mfccs': mfccs, 'mfccs': mfccs,