ref: 7fdca7f01dc1c5974b38c0ad77e0174a2c010577
parent: 0e523aa3f40c5e84aa60d70eea1a5fc4a9ff46c8
author: Jean-Marc Valin <jmvalin@amazon.com>
date: Wed Oct 20 19:16:44 EDT 2021
Minor cleanup
--- a/dnn/training_tf2/lpcnet.py
+++ b/dnn/training_tf2/lpcnet.py
@@ -258,20 +258,18 @@
cfeat = fdense2(fdense1(cfeat))
- Input_extractor = Lambda(lambda x: K.expand_dims(x[0][:,:,x[1]],axis = -1))
error_calc = Lambda(lambda x: tf_l2u(x[0] - tf.roll(x[1],1,axis = 1)))
if flag_e2e:
lpcoeffs = diff_rc2lpc(name = "rc2lpc")(cfeat)
else:
lpcoeffs = Input(shape=(None, lpc_order), batch_size=batch_size)
- tensor_preds = diff_pred(name = "lpc2preds")([Input_extractor([pcm,0]),lpcoeffs])
- past_errors = error_calc([Input_extractor([pcm,0]),tensor_preds])
+ tensor_preds = diff_pred(name = "lpc2preds")([pcm,lpcoeffs])
+ past_errors = error_calc([pcm,tensor_preds])
embed = diff_Embed(name='embed_sig',initializer = PCMInit())
- cpcm = Concatenate()([tf_l2u(Input_extractor([pcm,0])),tf_l2u(tensor_preds),past_errors])
+ cpcm = Concatenate()([tf_l2u(pcm),tf_l2u(tensor_preds),past_errors])
cpcm = GaussianNoise(.3)(cpcm)
cpcm = Reshape((-1, embed_size*3))(embed(cpcm))
- cpcm_decoder = Concatenate()([Input_extractor([dpcm,0]),Input_extractor([dpcm,1]),Input_extractor([dpcm,2])])
- cpcm_decoder = Reshape((-1, embed_size*3))(embed(cpcm_decoder))
+ cpcm_decoder = Reshape((-1, embed_size*3))(embed(dpcm))
rep = Lambda(lambda x: K.repeat_elements(x, frame_size, 1))
--
⑨