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# Copyright 2015 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 SavedModel utils."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.core.framework import types_pb2
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import sparse_tensor
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
from tensorflow.python.saved_model import utils
class UtilsTest(test.TestCase):
def testBuildTensorInfoDense(self):
x = array_ops.placeholder(dtypes.float32, 1, name="x")
x_tensor_info = utils.build_tensor_info(x)
self.assertEqual("x:0", x_tensor_info.name)
self.assertEqual(types_pb2.DT_FLOAT, x_tensor_info.dtype)
self.assertEqual(1, len(x_tensor_info.tensor_shape.dim))
self.assertEqual(1, x_tensor_info.tensor_shape.dim[0].size)
def testBuildTensorInfoSparse(self):
x = array_ops.sparse_placeholder(dtypes.float32, [42, 69], name="x")
x_tensor_info = utils.build_tensor_info(x)
self.assertEqual(x.values.name,
x_tensor_info.coo_sparse.values_tensor_name)
self.assertEqual(x.indices.name,
x_tensor_info.coo_sparse.indices_tensor_name)
self.assertEqual(x.dense_shape.name,
x_tensor_info.coo_sparse.dense_shape_tensor_name)
self.assertEqual(types_pb2.DT_FLOAT, x_tensor_info.dtype)
self.assertEqual(2, len(x_tensor_info.tensor_shape.dim))
self.assertEqual(42, x_tensor_info.tensor_shape.dim[0].size)
self.assertEqual(69, x_tensor_info.tensor_shape.dim[1].size)
def testGetTensorFromInfoDense(self):
expected = array_ops.placeholder(dtypes.float32, 1, name="x")
tensor_info = utils.build_tensor_info(expected)
actual = utils.get_tensor_from_tensor_info(tensor_info)
self.assertIsInstance(actual, ops.Tensor)
self.assertEqual(expected.name, actual.name)
def testGetTensorFromInfoSparse(self):
expected = array_ops.sparse_placeholder(dtypes.float32, name="x")
tensor_info = utils.build_tensor_info(expected)
actual = utils.get_tensor_from_tensor_info(tensor_info)
self.assertIsInstance(actual, sparse_tensor.SparseTensor)
self.assertEqual(expected.values.name, actual.values.name)
self.assertEqual(expected.indices.name, actual.indices.name)
self.assertEqual(expected.dense_shape.name, actual.dense_shape.name)
def testGetTensorFromInfoInOtherGraph(self):
with ops.Graph().as_default() as expected_graph:
expected = array_ops.placeholder(dtypes.float32, 1, name="right")
tensor_info = utils.build_tensor_info(expected)
with ops.Graph().as_default(): # Some other graph.
array_ops.placeholder(dtypes.float32, 1, name="other")
actual = utils.get_tensor_from_tensor_info(tensor_info,
graph=expected_graph)
self.assertIsInstance(actual, ops.Tensor)
self.assertIs(actual.graph, expected_graph)
self.assertEqual(expected.name, actual.name)
def testGetTensorFromInfoInScope(self):
# Build a TensorInfo with name "bar/x:0".
with ops.Graph().as_default():
with ops.name_scope("bar"):
unscoped = array_ops.placeholder(dtypes.float32, 1, name="x")
tensor_info = utils.build_tensor_info(unscoped)
self.assertEqual("bar/x:0", tensor_info.name)
# Build a graph with node "foo/bar/x:0", akin to importing into scope foo.
with ops.Graph().as_default():
with ops.name_scope("foo"):
with ops.name_scope("bar"):
expected = array_ops.placeholder(dtypes.float32, 1, name="x")
self.assertEqual("foo/bar/x:0", expected.name)
# Test that tensor is found by prepending the import scope.
actual = utils.get_tensor_from_tensor_info(tensor_info,
import_scope="foo")
self.assertEqual(expected.name, actual.name)
def testGetTensorFromInfoRaisesErrors(self):
expected = array_ops.placeholder(dtypes.float32, 1, name="x")
tensor_info = utils.build_tensor_info(expected)
tensor_info.name = "blah:0" # Nonexistant name.
with self.assertRaises(KeyError):
utils.get_tensor_from_tensor_info(tensor_info)
tensor_info.ClearField("name") # Malformed (missing encoding).
with self.assertRaises(ValueError):
utils.get_tensor_from_tensor_info(tensor_info)
if __name__ == "__main__":
test.main()
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