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@ -19,10 +19,9 @@ def init_parameter(network):
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assert isinstance(network, api.GradientMachine)
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for each_param in network.getParameters():
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assert isinstance(each_param, api.Parameter)
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array = each_param.getBuf(api.PARAMETER_VALUE).toNumpyArrayInplace()
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assert isinstance(array, np.ndarray)
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for i in xrange(len(array)):
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array[i] = np.random.uniform(-1.0, 1.0)
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array_size = len(each_param)
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array = np.random.uniform(-1.0, 1.0, array_size).astype('float32')
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each_param.getBuf(api.PARAMETER_VALUE).copyFromNumpyArray(array)
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def generator_to_batch(generator, batch_size):
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@ -175,7 +174,7 @@ def main():
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for each_param in params:
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assert isinstance(each_param, api.Parameter)
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value = each_param.getBuf(api.PARAMETER_VALUE)
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value = value.toNumpyArrayInplace()
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value = value.copyToNumpyArray()
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# Here, we could save parameter to every where you want
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print each_param.getName(), value
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