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# 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.
# ==============================================================================
"""Test cases for XLA devices."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.compiler.tests import xla_test
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_control_flow_ops
from tensorflow.python.platform import test
class XlaDeviceTest(xla_test.XLATestCase):
def testCopies(self):
"""Tests that copies onto and off XLA devices work."""
shapes = [[0], [1], [1, 0], [1024, 0], [1024, 1], [3, 777], [777, 3],
[16384, 1], [1, 16384], [1, 20000, 1, 1]]
for dtype in self.numeric_types:
for shape in shapes:
with self.cached_session() as sess:
with ops.device("CPU"):
x = array_ops.placeholder(dtype, shape)
with self.test_scope():
y = x + x
with ops.device("CPU"):
z = array_ops.identity(y)
inputs = np.random.randint(-100, 100, shape).astype(dtype)
result = sess.run(z, {x: inputs})
self.assertAllCloseAccordingToType(result, inputs + inputs)
def testCopiesOfUnsupportedTypesFailGracefully(self):
"""Tests that copies of unsupported types don't crash."""
test_types = set([
np.uint8, np.uint16, np.uint32, np.uint64, np.int8, np.int16, np.int32,
np.int64, np.float16, np.float32, np.float16,
dtypes.bfloat16.as_numpy_dtype
])
shape = (10, 10)
for unsupported_dtype in test_types - self.all_types:
with self.cached_session() as sess:
with ops.device("CPU"):
x = array_ops.placeholder(unsupported_dtype, shape)
with self.test_scope():
y, = array_ops.identity_n([x])
with ops.device("CPU"):
z = array_ops.identity(y)
inputs = np.random.randint(-100, 100, shape)
inputs = inputs.astype(unsupported_dtype)
# Execution should either succeed or raise an InvalidArgumentError,
# but not crash. Even "unsupported types" may succeed here since some
# backends (e.g., the CPU backend) are happy to handle buffers of
# unsupported types, even if they cannot compute with them.
try:
sess.run(z, {x: inputs})
except errors.InvalidArgumentError:
pass
def testControlTrigger(self):
with self.cached_session() as sess:
with self.test_scope():
x = gen_control_flow_ops.control_trigger()
sess.run(x)
if __name__ == "__main__":
test.main()
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