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25 lines
966 B
Python
25 lines
966 B
Python
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import numpy as np
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import tensorflow.compat.v1 as tf
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def create_sparse_tensor(batch_size, input_size, num_values, dtype=tf.float32):
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random_indices = np.sort(np.random.randint(batch_size * input_size, size=num_values))
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test_indices_i = random_indices // input_size
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test_indices_j = random_indices % input_size
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test_indices = np.stack([test_indices_i, test_indices_j], axis=1)
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test_values = np.random.random(num_values).astype(dtype.as_numpy_dtype)
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return tf.SparseTensor(indices=tf.constant(test_indices),
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values=tf.constant(test_values),
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dense_shape=(batch_size, input_size))
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def create_reference_input(sparse_input, use_binary_values):
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if use_binary_values:
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sp_a = tf.SparseTensor(indices=sparse_input.indices,
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values=tf.ones_like(sparse_input.values),
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dense_shape=sparse_input.dense_shape)
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else:
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sp_a = sparse_input
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return sp_a
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