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fixed bug in train.py when using longer training examples than normal [skip ci]

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dscripka 2024-02-22 21:14:20 -05:00
parent fe57debecc
commit c40fe924ff
1 changed files with 2 additions and 2 deletions
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openwakeword/train.py
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@ -813,13 +813,13 @@ if __name__ == '__main__':
# Create openwakeword model
if args.train_model is True:
F = openwakeword.utils.AudioFeatures(device='cpu')
input_shape = F.get_embedding_shape(config["total_length"]//16000) # training data is always 16 khz
input_shape = np.load(os.path.join(feature_save_dir, "positive_features_test.npy")).shape[1:]
oww = Model(n_classes=1, input_shape=input_shape, model_type=config["model_type"],
layer_dim=config["layer_size"], seconds_per_example=1280*input_shape[0]/16000)
# Create data transform function for batch generation to handle differ clip lengths (todo: write tests for this)
def f(x, n=16):
def f(x, n=input_shape[0]):
"""Simple transformation function to ensure negative data is the appropriate shape for the model size"""
if n > x.shape[1] or n < x.shape[1]:
x = np.vstack(x)