wehub-resource-sync
82 lines
2.6 KiB
Python
82 lines
2.6 KiB
Python
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for const op compilation."""
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import numpy as np
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from tensorflow.python.eager import def_function
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from tensorflow.python.framework import constant_op
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import test_util
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from tensorflow.python.platform import test
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# This test doesn't use XLATestCase like the other tests in this directory.
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# The Const op xla op kernel is compilation only and therefore is not executed
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# with XLA in the on demand compilation mode. Instead we use
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# tf.function(jit_compile=True)
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class ConstOpTest(test_util.TensorFlowTestCase):
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# Verifies that the Const op works
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# @test_util.run_v2_only
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def testConst(self):
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types = {
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dtypes.bool,
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dtypes.int8,
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dtypes.int16,
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dtypes.int32,
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dtypes.int64,
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dtypes.uint8,
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dtypes.uint16,
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dtypes.uint32,
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dtypes.uint64,
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dtypes.float16,
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dtypes.bfloat16,
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dtypes.float32,
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dtypes.float64,
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dtypes.float8_e5m2,
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dtypes.float8_e4m3fn,
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dtypes.float8_e4m3fnuz,
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dtypes.float8_e4m3b11fnuz,
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dtypes.float8_e5m2fnuz,
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}
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for dtype in types:
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with self.subTest(dtype=dtype):
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if dtype == dtypes.bool:
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values = [True, False]
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elif dtype in [
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dtypes.uint8,
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dtypes.uint16,
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dtypes.uint32,
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dtypes.uint64,
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]:
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values = [0., 1., dtype.min, dtype.max]
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else:
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values = [0., 1., -1., dtype.min, dtype.max]
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if dtype.is_floating:
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values.extend([float("Inf"), -float("Inf"), float("NaN")])
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values = np.array(values, dtype=dtype.as_numpy_dtype)
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@def_function.function(jit_compile=True)
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def f():
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return constant_op.constant(values, dtype) # pylint: disable=cell-var-from-loop
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result = f()
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self.assertAllEqual(self.evaluate(result), values)
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if __name__ == "__main__":
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test.main()
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