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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 lists module."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.contrib.autograph import utils
from tensorflow.contrib.autograph.converters import lists
from tensorflow.contrib.autograph.core import converter_testing
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import list_ops
from tensorflow.python.platform import test
class ListTest(converter_testing.TestCase):
def test_empty_list(self):
def test_fn():
return []
node = self.parse_and_analyze(test_fn, {})
node = lists.transform(node, self.ctx)
with self.compiled(node) as result:
tl = result.test_fn()
# Empty tensor lists cannot be evaluated or stacked.
self.assertTrue(isinstance(tl, ops.Tensor))
self.assertEqual(tl.dtype, dtypes.variant)
def test_initialized_list(self):
def test_fn():
return [1, 2, 3]
node = self.parse_and_analyze(test_fn, {})
node = lists.transform(node, self.ctx)
with self.compiled(node) as result:
with self.test_session() as sess:
tl = result.test_fn()
r = list_ops.tensor_list_stack(tl, dtypes.int32)
self.assertAllEqual(sess.run(r), [1, 2, 3])
def test_list_append(self):
def test_fn():
l = [1]
l.append(2)
l.append(3)
return l
node = self.parse_and_analyze(test_fn, {})
node = lists.transform(node, self.ctx)
with self.compiled(node) as result:
with self.test_session() as sess:
tl = result.test_fn()
r = list_ops.tensor_list_stack(tl, dtypes.int32)
self.assertAllEqual(sess.run(r), [1, 2, 3])
def test_list_pop(self):
def test_fn():
l = [1, 2, 3]
utils.set_element_type(l, dtypes.int32, ())
s = l.pop()
return s, l
node = self.parse_and_analyze(
test_fn,
{
'utils': utils,
'dtypes': dtypes
},
include_type_analysis=True,
)
node = lists.transform(node, self.ctx)
with self.compiled(node) as result:
result.utils = utils
result.dtypes = dtypes
with self.test_session() as sess:
ts, tl = result.test_fn()
r = list_ops.tensor_list_stack(tl, dtypes.int32)
self.assertAllEqual(sess.run(r), [1, 2])
self.assertAllEqual(sess.run(ts), 3)
def test_double_list_pop(self):
def test_fn(l):
s = l.pop().pop()
return s
node = self.parse_and_analyze(test_fn, {})
node = lists.transform(node, self.ctx)
with self.compiled(node) as result:
test_input = [1, 2, [1, 2, 3]]
# TODO(mdan): Pass a list of lists of tensor when we fully support that.
# For now, we just pass a regular Python list of lists just to verify that
# the two pop calls are sequenced properly.
self.assertAllEqual(result.test_fn(test_input), 3)
def test_list_stack(self):
tf = None # Will be replaced with a mock.
def test_fn():
l = [1, 2, 3]
utils.set_element_type(l, dtypes.int32)
return tf.stack(l)
node = self.parse_and_analyze(
test_fn,
{
'utils': utils,
'dtypes': dtypes
},
include_type_analysis=True,
)
node = lists.transform(node, self.ctx)
with self.compiled(node, array_ops.stack, dtypes.int32) as result:
result.utils = utils
result.dtypes = dtypes
with self.test_session() as sess:
self.assertAllEqual(sess.run(result.test_fn()), [1, 2, 3])
if __name__ == '__main__':
test.main()
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