STT-tensorflow/tensorflow/python/eager/wrap_function_device_test.py
Zheng Xu f91bc3c0f2 Add wrap_function tests with explicit device placement.
PiperOrigin-RevId: 334215093
Change-Id: I0f9e2a7819a480d10ec1bf41db91b8511bac2318
2020-09-28 12:38:47 -07:00

87 lines
2.8 KiB
Python

# Copyright 2018 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.
# ==============================================================================
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import parameterized
from tensorflow.python.data.ops import dataset_ops
from tensorflow.python.eager import def_function
from tensorflow.python.eager import wrap_function
from tensorflow.python.framework import config
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import importer as graph_def_importer
from tensorflow.python.framework import ops
from tensorflow.python.platform import test
def _dataset_reduce_sum(dataset):
return dataset.reduce(
constant_op.constant(0, dtype=dtypes.int64), lambda x, y: x + y)
def _loop_dataset_sum(dataset):
value = constant_op.constant(0, dtype=dtypes.int64)
for d in dataset:
value += d
return value
def _iter_dataset_sum(dataset):
value = constant_op.constant(0, dtype=dtypes.int64)
for d in iter(dataset):
value += d
return value
class WrappedGraphTest(test.TestCase, parameterized.TestCase):
@parameterized.named_parameters(
('cpu_reduce', 'CPU', _dataset_reduce_sum),
('gpu_reduce', 'GPU', _dataset_reduce_sum),
('cpu_loop', 'CPU', _loop_dataset_sum),
('gpu_loop', 'GPU', _loop_dataset_sum),
('cpu_iter', 'CPU', _iter_dataset_sum),
('gpu_iter', 'GPU', _iter_dataset_sum),
)
def testWrapFuncDatasetDevice(self, device_type, dataset_reduce_fn):
devices = config.list_logical_devices(device_type=device_type)
if not devices:
self.skipTest('Skip when {} is not detected by TF'.format(device_type))
@def_function.function
def comp():
return dataset_reduce_fn(dataset_ops.Dataset.range(10))
graph = comp.get_concrete_function().graph
def function_to_wrap():
with ops.device(devices[0].name):
return graph_def_importer.import_graph_def(graph.as_graph_def())
with ops.device(devices[0].name):
wrapped_noarg_fn = wrap_function.wrap_function(
function_to_wrap, signature=[])
wrapped_noarg_fn()
if __name__ == '__main__':
ops.enable_eager_execution()
test.main()