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import tensorflow.python.platform
import numpy as np
import tensorflow as tf
class SparseMaskTest(tf.test.TestCase):
def testBasic(self):
values = np.random.rand(4, 4).astype(np.single)
indices = np.array([0, 2, 3, 4], dtype=np.int32)
mask_indices = np.array([0], dtype=np.int32)
out_values = values[1:, :]
out_indices = np.array([2, 3, 4], dtype=np.int32)
with self.test_session() as sess:
values_tensor = tf.convert_to_tensor(values)
indices_tensor = tf.convert_to_tensor(indices)
mask_indices_tensor = tf.convert_to_tensor(mask_indices)
t = tf.IndexedSlices(values_tensor, indices_tensor)
masked_t = tf.sparse_mask(t, mask_indices_tensor)
tf_out_values, tf_out_indices = sess.run([masked_t.values,
masked_t.indices])
self.assertAllEqual(tf_out_values, out_values)
self.assertAllEqual(tf_out_indices, out_indices)
if __name__ == "__main__":
tf.test.main()
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