| # 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.""" |
| |
| 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.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.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.session() as sess: |
| with self.test_scope(): |
| x = gen_control_flow_ops.control_trigger() |
| self.evaluate(x) |
| |
| |
| if __name__ == "__main__": |
| test.main() |