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"""Tests for SparseConcat."""
import tensorflow.python.platform
import numpy as np
import tensorflow as tf
class SparseConcatTest(tf.test.TestCase):
def _SparseTensor_UnknownShape(self, ind_shape=None, val_shape=None,
shape_shape=None):
return tf.SparseTensor(
tf.placeholder(tf.int64, shape=ind_shape),
tf.placeholder(tf.float32, shape=val_shape),
tf.placeholder(tf.int64, shape=shape_shape))
def _SparseTensor_3x3(self):
# [ 1]
# [2 ]
# [3 4]
ind = np.array([[0, 2], [1, 0], [2, 0], [2, 2]])
val = np.array([1, 2, 3, 4])
shape = np.array([3, 3])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.float32),
tf.constant(shape, tf.int64))
def _SparseTensor_3x5(self):
# [ ]
# [ 1 ]
# [2 1 0]
ind = np.array([[1, 1], [2, 0], [2, 3], [2, 4]])
val = np.array([1, 2, 1, 0])
shape = np.array([3, 5])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.float32),
tf.constant(shape, tf.int64))
def _SparseTensor_3x2(self):
# [ ]
# [1 ]
# [2 ]
ind = np.array([[1, 0], [2, 0]])
val = np.array([1, 2])
shape = np.array([3, 2])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.float32),
tf.constant(shape, tf.int64))
def _SparseTensor_2x3(self):
# [ 1 ]
# [1 2]
ind = np.array([[0, 1], [1, 0], [1, 2]])
val = np.array([1, 1, 2])
shape = np.array([2, 3])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.float32),
tf.constant(shape, tf.int64))
def _SparseTensor_2x3x4(self):
ind = np.array([
[0, 0, 1],
[0, 1, 0], [0, 1, 2],
[1, 0, 3],
[1, 1, 1], [1, 1, 3],
[1, 2, 2]])
val = np.array([1, 10, 12, 103, 111, 113, 122])
shape = np.array([2, 3, 4])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.float32),
tf.constant(shape, tf.int64))
def _SparseTensor_String3x3(self):
# [ a]
# [b ]
# [c d]
ind = np.array([[0, 2], [1, 0], [2, 0], [2, 2]])
val = np.array(["a", "b", "c", "d"])
shape = np.array([3, 3])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.string),
tf.constant(shape, tf.int64))
def _SparseTensor_String3x5(self):
# [ ]
# [ e ]
# [f g h]
ind = np.array([[1, 1], [2, 0], [2, 3], [2, 4]])
val = np.array(["e", "f", "g", "h"])
shape = np.array([3, 5])
return tf.SparseTensor(
tf.constant(ind, tf.int64),
tf.constant(val, tf.string),
tf.constant(shape, tf.int64))
def testConcat1(self):
with self.test_session(use_gpu=False) as sess:
# concat(A):
# [ 1]
# [2 ]
# [3 4]
sp_a = self._SparseTensor_3x3()
sp_concat = tf.sparse_concat(1, [sp_a])
self.assertEqual(sp_concat.indices.get_shape(), [4, 2])
self.assertEqual(sp_concat.values.get_shape(), [4])
self.assertEqual(sp_concat.shape.get_shape(), [2])
concat_out = sess.run(sp_concat)
self.assertAllEqual(
concat_out.indices, [[0, 2], [1, 0], [2, 0], [2, 2]])
self.assertAllEqual(concat_out.values, [1, 2, 3, 4])
self.assertAllEqual(concat_out.shape, [3, 3])
def testConcat2(self):
with self.test_session(use_gpu=False) as sess:
# concat(A, B):
# [ 1 ]
# [2 1 ]
# [3 4 2 1 0]
sp_a = self._SparseTensor_3x3()
sp_b = self._SparseTensor_3x5()
sp_concat = tf.sparse_concat(1, [sp_a, sp_b])
self.assertEqual(sp_concat.indices.get_shape(), [8, 2])
self.assertEqual(sp_concat.values.get_shape(), [8])
self.assertEqual(sp_concat.shape.get_shape(), [2])
concat_out = sess.run(sp_concat)
self.assertAllEqual(
concat_out.indices,
[[0, 2], [1, 0], [1, 4], [2, 0], [2, 2], [2, 3], [2, 6], [2, 7]])
self.assertAllEqual(concat_out.values, [1, 2, 1, 3, 4, 2, 1, 0])
self.assertAllEqual(concat_out.shape, [3, 8])
def testConcatDim0(self):
with self.test_session(use_gpu=False) as sess:
# concat(A, D):
# [ 1]
# [2 ]
# [3 4]
# [ 1 ]
# [1 2]
sp_a = self._SparseTensor_3x3()
sp_d = self._SparseTensor_2x3()
sp_concat = tf.sparse_concat(0, [sp_a, sp_d])
self.assertEqual(sp_concat.indices.get_shape(), [7, 2])
self.assertEqual(sp_concat.values.get_shape(), [7])
self.assertEqual(sp_concat.shape.get_shape(), [2])
concat_out = sess.run(sp_concat)
self.assertAllEqual(
concat_out.indices,
[[0, 2], [1, 0], [2, 0], [2, 2], [3, 1], [4, 0], [4, 2]])
self.assertAllEqual(
concat_out.values, np.array([1, 2, 3, 4, 1, 1, 2]))
self.assertAllEqual(
concat_out.shape, np.array([5, 3]))
def testConcat3(self):
with self.test_session(use_gpu=False) as sess:
# concat(A, B, C):
# [ 1 ]
# [2 1 1 ]
# [3 4 2 1 0 2 ]
sp_a = self._SparseTensor_3x3()
sp_b = self._SparseTensor_3x5()
sp_c = self._SparseTensor_3x2()
sp_concat = tf.sparse_concat(1, [sp_a, sp_b, sp_c])
self.assertEqual(sp_concat.indices.get_shape(), [10, 2])
self.assertEqual(sp_concat.values.get_shape(), [10])
self.assertEqual(sp_concat.shape.get_shape(), [2])
concat_out = sess.run(sp_concat)
self.assertAllEqual(
concat_out.indices,
[[0, 2], [1, 0], [1, 4], [1, 8], [2, 0], [2, 2], [2, 3], [2, 6],
[2, 7], [2, 8]])
self.assertAllEqual(concat_out.values, [1, 2, 1, 1, 3, 4, 2, 1, 0, 2])
self.assertAllEqual(concat_out.shape, [3, 10])
def testConcatNonNumeric(self):
with self.test_session(use_gpu=False) as sess:
# concat(A, B):
# [ a ]
# [b e ]
# [c d f g h]
sp_a = self._SparseTensor_String3x3()
sp_b = self._SparseTensor_String3x5()
sp_concat = tf.sparse_concat(1, [sp_a, sp_b])
self.assertEqual(sp_concat.indices.get_shape(), [8, 2])
self.assertEqual(sp_concat.values.get_shape(), [8])
self.assertEqual(sp_concat.shape.get_shape(), [2])
concat_out = sess.run(sp_concat)
self.assertAllEqual(
concat_out.indices,
[[0, 2], [1, 0], [1, 4], [2, 0], [2, 2], [2, 3], [2, 6], [2, 7]])
self.assertAllEqual(
concat_out.values, ["a", "b", "e", "c", "d", "f", "g", "h"])
self.assertAllEqual(concat_out.shape, [3, 8])
def testMismatchedRank(self):
with self.test_session(use_gpu=False):
sp_a = self._SparseTensor_3x3()
sp_e = self._SparseTensor_2x3x4()
# Rank mismatches can be caught at shape-inference time
with self.assertRaises(ValueError):
tf.sparse_concat(1, [sp_a, sp_e])
def testMismatchedShapes(self):
with self.test_session(use_gpu=False) as sess:
sp_a = self._SparseTensor_3x3()
sp_b = self._SparseTensor_3x5()
sp_c = self._SparseTensor_3x2()
sp_d = self._SparseTensor_2x3()
sp_concat = tf.sparse_concat(1, [sp_a, sp_b, sp_c, sp_d])
# Shape mismatches can only be caught when the op is run
with self.assertRaisesOpError("Input shapes must match"):
sess.run(sp_concat)
def testShapeInferenceUnknownShapes(self):
with self.test_session(use_gpu=False):
sp_inputs = [
self._SparseTensor_UnknownShape(),
self._SparseTensor_UnknownShape(val_shape=[3]),
self._SparseTensor_UnknownShape(ind_shape=[1, 3]),
self._SparseTensor_UnknownShape(shape_shape=[3])]
sp_concat = tf.sparse_concat(0, sp_inputs)
self.assertEqual(sp_concat.indices.get_shape().as_list(), [None, 3])
self.assertEqual(sp_concat.values.get_shape().as_list(), [None])
self.assertEqual(sp_concat.shape.get_shape(), [3])
if __name__ == "__main__":
tf.test.main()
|
