def _test_concat_v2(data, dim):
""" One iteration of ConcatV2 """
with tf.Graph().as_default():
gen_array_ops._concat_v2(data, dim)
compare_tf_with_tvm(data, ['ConcatV2/values_0:0', 'ConcatV2/values_1:0'],
'ConcatV2:0')
def _test_concat_v2(data, dim):
""" One iteration of ConcatV2 """
with tf.Graph().as_default():
gen_array_ops._concat_v2(data, dim)
compare_tf_with_tvm(data, ['ConcatV2/values_0:0', 'ConcatV2/values_1:0'],
'ConcatV2:0')
def testConcatV2NegativeAxis(self):
with self.test_session(use_gpu=True):
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
output = gen_array_ops._concat_v2([t1, t2], -2).eval()
self.assertAllEqual(
[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]], output)
output = gen_array_ops._concat_v2([t1, t2], -1).eval()
self.assertAllEqual([[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]],
output)
def testConcatV2NegativeAxis(self):
with self.test_session(use_gpu=True):
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
output = gen_array_ops._concat_v2([t1, t2], -2).eval()
self.assertAllEqual(
[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],
output)
output = gen_array_ops._concat_v2([t1, t2], -1).eval()
self.assertAllEqual(
[[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]],
output)
def testConcatNegativeAxis(self):
with self.test_session(use_gpu=True):
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
c = gen_array_ops._concat_v2([t1, t2], -2)
self.assertEqual([4, 3], c.get_shape().as_list())
output = c.eval()
self.assertAllEqual([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]],
output)
c = gen_array_ops._concat_v2([t1, t2], -1)
self.assertEqual([2, 6], c.get_shape().as_list())
output = c.eval()
self.assertAllEqual([[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]], output)
def testConcatNegativeAxis(self):
with self.test_session(use_gpu=True):
t1 = [[1, 2, 3], [4, 5, 6]]
t2 = [[7, 8, 9], [10, 11, 12]]
c = gen_array_ops._concat_v2([t1, t2], -2)
self.assertEqual([4, 3], c.get_shape().as_list())
output = c.eval()
self.assertAllEqual(
[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]], output)
c = gen_array_ops._concat_v2([t1, t2], -1)
self.assertEqual([2, 6], c.get_shape().as_list())
output = c.eval()
self.assertAllEqual([[1, 2, 3, 7, 8, 9], [4, 5, 6, 10, 11, 12]],
output)
def _test_concat_v2(data, dim):
""" One iteration of ConcatV2 """
with tf.Graph().as_default():
# pylint: disable=unused-variable
concat_out = gen_array_ops._concat_v2(data, dim)
# pylint: enable=unused-variable
with tf.Session() as sess:
graph_def = tf.graph_util.convert_variables_to_constants(
sess,
sess.graph.as_graph_def(add_shapes=True),
['ConcatV2'],
)
tf_output = run_tf_graph(
sess, data, ['ConcatV2/values_0:0', 'ConcatV2/values_1:0'],
'ConcatV2:0')
tvm_output = run_tvm_graph(
graph_def, data, ["ConcatV2/values_0", 'ConcatV2/values_1'],
tf_output.shape, tf_output.dtype)
np.testing.assert_allclose(tf_output, tvm_output)
sess.close()
def testConcatInvalidAxis(self):
with self.assertRaises(ValueError):
with self.test_session(use_gpu=True):
t1 = [1]
t2 = [2]
gen_array_ops._concat_v2([t1, t2], 1).eval()
def testConcatEmpty(self):
with self.test_session(use_gpu=True):
t1 = []
t2 = []
output = gen_array_ops._concat_v2([t1, t2], 0).eval()
self.assertFalse(output) # Checks that output is empty
def testConcatV2InvalidAxis(self):
with self.assertRaises(ValueError):
with self.test_session(use_gpu=True):
t1 = [1]
t2 = [2]
gen_array_ops._concat_v2([t1, t2], 1).eval()
def testConcatV2Empty(self):
with self.test_session(use_gpu=True):
t1 = []
t2 = []
output = gen_array_ops._concat_v2([t1, t2], 0).eval()
self.assertFalse(output) # Checks that output is empty
def _call_concat(values, axis, use_concat_v2):
if use_concat_v2:
return gen_array_ops._concat_v2(values, axis)
else:
return tf.concat(axis, values)
def _call_concat(values, axis, use_concat_v2):
if use_concat_v2:
return gen_array_ops._concat_v2(values, axis)
else:
return tf.concat(axis, values)