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# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for data_structures module."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.autograph.operators import data_structures
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import list_ops
from tensorflow.python.ops import tensor_array_ops
from tensorflow.python.platform import test
class ListTest(test.TestCase):
def test_new_list_empty(self):
l = data_structures.new_list()
# Can't evaluate an empty list.
# TODO(mdan): sess.run should allow tf.variant maybe?
self.assertTrue(isinstance(l, ops.Tensor))
def test_new_list_tensor(self):
l = data_structures.new_list([3, 4, 5])
self.assertAllEqual(l, [3, 4, 5])
def test_tf_tensor_list_new(self):
l = data_structures.tf_tensor_list_new([3, 4, 5])
t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32)
with self.cached_session() as sess:
self.assertAllEqual(sess.run(t), [3, 4, 5])
def test_tf_tensor_list_new_empty(self):
l = data_structures.tf_tensor_list_new([],
element_dtype=dtypes.int32,
element_shape=())
t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32)
with self.cached_session() as sess:
self.assertAllEqual(sess.run(t), [])
def test_tf_tensor_list_new_from_tensor(self):
l = data_structures.tf_tensor_list_new(constant_op.constant([3, 4, 5]))
t = list_ops.tensor_list_stack(l, element_dtype=dtypes.int32)
with self.cached_session() as sess:
self.assertAllEqual(sess.run(t), [3, 4, 5])
def test_tf_tensor_list_new_illegal_input(self):
with self.assertRaises(ValueError):
data_structures.tf_tensor_list_new([3, 4.0])
# TODO(mdan): It might make more sense to type cast in this case.
with self.assertRaises(ValueError):
data_structures.tf_tensor_list_new([3, 4], element_dtype=dtypes.float32)
# Tensor lists do support heterogeneous lists.
self.assertIsNot(data_structures.tf_tensor_list_new([3, [4, 5]]), None)
with self.assertRaises(ValueError):
data_structures.tf_tensor_list_new([3, 4], element_shape=(2,))
with self.assertRaises(ValueError):
data_structures.tf_tensor_list_new(
constant_op.constant([1, 2, 3]), element_shape=[1])
def test_tf_tensor_array_new(self):
l = data_structures.tf_tensor_array_new([3, 4, 5])
t = l.stack()
with self.cached_session() as sess:
self.assertAllEqual(sess.run(t), [3, 4, 5])
def test_tf_tensor_array_new_illegal_input(self):
with self.assertRaises(ValueError):
data_structures.tf_tensor_array_new([3, 4.0])
with self.assertRaises(ValueError):
data_structures.tf_tensor_array_new([3, 4], element_dtype=dtypes.float32)
with self.assertRaises(ValueError):
data_structures.tf_tensor_array_new([3, [4, 5]])
with self.assertRaises(ValueError):
data_structures.tf_tensor_array_new([3, 4], element_shape=(2,))
with self.assertRaises(ValueError):
data_structures.tf_tensor_array_new([], element_shape=(2,))
# TAs can infer the shape.
self.assertIsNot(
data_structures.tf_tensor_array_new([], element_dtype=dtypes.float32),
None)
def test_append_tensor_list(self):
l = data_structures.new_list()
x = constant_op.constant([1, 2, 3])
l = data_structures.list_append(l, x)
t = list_ops.tensor_list_stack(l, element_dtype=x.dtype)
with self.cached_session() as sess:
self.assertAllEqual(sess.run(t), [[1, 2, 3]])
def test_append_tensorarray(self):
l = tensor_array_ops.TensorArray(dtypes.int32, size=0, dynamic_size=True)
l1 = data_structures.list_append(l, 1)
l2 = data_structures.list_append(l1, 2)
with self.cached_session() as sess:
self.assertAllEqual(sess.run(l1.stack()), [1])
self.assertAllEqual(sess.run(l2.stack()), [1, 2])
def test_append_python(self):
l = []
self.assertAllEqual(data_structures.list_append(l, 1), [1])
self.assertAllEqual(data_structures.list_append(l, 2), [1, 2])
def test_pop_tensor_list(self):
initial_list = constant_op.constant([[1, 2], [3, 4]])
elem_shape = constant_op.constant([2])
l = list_ops.tensor_list_from_tensor(initial_list, element_shape=elem_shape)
opts = data_structures.ListPopOpts(
element_dtype=initial_list.dtype,
element_shape=(2,))
with self.assertRaises(NotImplementedError):
data_structures.list_pop(l, 0, opts)
with self.cached_session() as sess:
l, x = data_structures.list_pop(l, None, opts)
self.assertAllEqual(sess.run(x), [3, 4])
t = list_ops.tensor_list_stack(l, element_dtype=initial_list.dtype)
self.assertAllEqual(sess.run(t), [[1, 2]])
def test_pop_python(self):
l = [1, 2, 3]
opts = data_structures.ListPopOpts(element_dtype=None, element_shape=())
self.assertAllEqual(data_structures.list_pop(l, None, opts), ([1, 2], 3))
self.assertAllEqual(data_structures.list_pop(l, None, opts), ([1], 2))
def test_stack_tensor_list(self):
initial_list = constant_op.constant([[1, 2], [3, 4]])
elem_shape = constant_op.constant([2])
l = list_ops.tensor_list_from_tensor(initial_list, element_shape=elem_shape)
opts = data_structures.ListStackOpts(
element_dtype=initial_list.dtype, original_call=None)
with self.cached_session() as sess:
t = data_structures.list_stack(l, opts)
self.assertAllEqual(sess.run(t), sess.run(initial_list))
def test_stack_tensor_list_empty(self):
l = list_ops.empty_tensor_list(
element_shape=-1,
element_dtype=dtypes.variant)
opts = data_structures.ListStackOpts(
element_dtype=dtypes.int32, original_call=None)
# TODO(mdan): Allow stacking empty lists if the dtype and shape are known.
with self.assertRaises(ValueError):
data_structures.list_stack(l, opts)
def test_stack_fallback(self):
def dummy_function(l):
# Lazy person's mock: just transform the argument in a way in which we
# can check that this function was indeed called.
return [x * 2 for x in l]
opts = data_structures.ListStackOpts(
element_dtype=None, original_call=dummy_function)
self.assertAllEqual(data_structures.list_stack([1, 2], opts), [2, 4])
if __name__ == '__main__':
test.main()
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