shithub: opus

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dump_lpcnet.py should work the same for end2end

--- a/dnn/training_tf2/dump_lpcnet.py

+++ b/dnn/training_tf2/dump_lpcnet.py

@@ -32,6 +32,7 @@

 from tensorflow.keras.layers import Layer, GRU, Dense, Conv1D, Embedding

 from ulaw import ulaw2lin, lin2ulaw

 from mdense import MDense

+from diffembed import diff_Embed

 import h5py

 import re

@@ -234,6 +235,7 @@

     dump_embedding_layer_impl(name, weights, f, hf)

     return False

 Embedding.dump_layer = dump_embedding_layer

+diff_Embed.dump_layer = dump_embedding_layer

 filename = sys.argv[1]

 with h5py.File(filename, "r") as f:

@@ -244,7 +246,7 @@

 model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])

 #model.summary()

-model.load_weights(filename)

+model.load_weights(filename, by_name=True)

 if len(sys.argv) > 2:

     cfile = sys.argv[2];

-- 

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