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Bring test_lpcnet.py up-to-date

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This commit is contained in:
Jean-Marc Valin 2021-10-20 04:01:12 -04:00
parent 144b7311bc
commit 3f7756c53f
2 changed files with 16 additions and 10 deletions
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22
dnn/training_tf2/test_lpcnet.py
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@ -31,16 +31,22 @@ import numpy as np
from ulaw import ulaw2lin, lin2ulaw
import h5py
# Flag for synthesizing e2e (differentiable lpc) model
flag_e2e = False
filename = sys.argv[1]
with h5py.File(filename, "r") as f:
units = min(f['model_weights']['gru_a']['gru_a']['recurrent_kernel:0'].shape)
units2 = min(f['model_weights']['gru_b']['gru_b']['recurrent_kernel:0'].shape)
cond_size = min(f['model_weights']['feature_dense1']['feature_dense1']['kernel:0'].shape)
e2e = 'rc2lpc' in f['model_weights']
model, enc, dec = lpcnet.new_lpcnet_model(training = False, flag_e2e = flag_e2e)
model, enc, dec = lpcnet.new_lpcnet_model(training = False, rnn_units1=units, rnn_units2=units2, flag_e2e = e2e, cond_size=cond_size, batch_size=1)
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['sparse_categorical_accuracy'])
#model.summary()
feature_file = sys.argv[1]
out_file = sys.argv[2]
feature_file = sys.argv[2]
out_file = sys.argv[3]
frame_size = model.frame_size
nb_features = 36
nb_used_features = model.nb_used_features
@ -56,7 +62,7 @@ periods = (.1 + 50*features[:,:,18:19]+100).astype('int16')
model.load_weights('lpcnet38Sn_384_02.h5');
model.load_weights(filename);
order = 16
@ -72,13 +78,13 @@ fout = open(out_file, 'wb')
skip = order + 1
for c in range(0, nb_frames):
if not flag_e2e:
if not e2e:
cfeat = enc.predict([features[c:c+1, :, :nb_used_features], periods[c:c+1, :, :]])
else:
cfeat,lpcs = enc.predict([features[c:c+1, :, :nb_used_features], periods[c:c+1, :, :]])
for fr in range(0, feature_chunk_size):
f = c*feature_chunk_size + fr
if not flag_e2e:
if not e2e:
a = features[c, fr, nb_features-order:]
else:
a = lpcs[c,fr]