ba167d161e
This takes a ConcreteFunction, collects a FunctionDef for the function and an associated FunctionDefLibrary, and imports the FunctionDef and FunctionDefLibrary via `ConvertFunctionToMlir`. Control rets/target nodes of the entry function are also now supported in `ConvertFunctionToMlir`. PiperOrigin-RevId: 331195841 Change-Id: Ib3a7264e90ca303ab7a850bf18c8d5e330063a4f
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
# Copyright 2019 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 python.compiler.mlir."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from tensorflow.python.compiler.mlir import mlir
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from tensorflow.python.eager import def_function
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import errors
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from tensorflow.python.framework import tensor_spec
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from tensorflow.python.ops import logging_ops
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from tensorflow.python.platform import test
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class MLIRGraphDefImportTest(test.TestCase):
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def testImport(self):
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"""Tests the basic flow of `tf.mlir.experimental.convert_graph_def`."""
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mlir_module = mlir.convert_graph_def('')
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# An empty graph should contain at least an empty main function.
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self.assertIn('func @main', mlir_module)
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def testInvalidPbtxt(self):
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with self.assertRaisesRegex(errors.InvalidArgumentError,
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'Could not parse input proto'):
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mlir.convert_graph_def('some invalid proto')
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class MLIRConcreteFunctionImportTest(test.TestCase):
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def testImport(self):
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@def_function.function
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def identity(i):
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return i
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concrete_function = identity.get_concrete_function(
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tensor_spec.TensorSpec(None, dtypes.float32))
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mlir_module = mlir.convert_function(concrete_function)
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self.assertRegex(mlir_module, r'func @.*identity.*\(')
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def testImportWithCall(self):
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@def_function.function
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def callee(i):
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return i
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@def_function.function
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def caller(i):
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return callee(i)
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concrete_function = caller.get_concrete_function(
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tensor_spec.TensorSpec(None, dtypes.float32))
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mlir_module = mlir.convert_function(concrete_function)
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self.assertRegex(mlir_module, r'func @.*caller.*\(')
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self.assertRegex(mlir_module, r'func @.*callee.*\(')
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def testImportWithControlRet(self):
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@def_function.function
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def logging():
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logging_ops.print_v2('some message')
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concrete_function = logging.get_concrete_function()
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mlir_module = mlir.convert_function(concrete_function, pass_pipeline='')
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self.assertRegex(mlir_module, r'tf\.PrintV2')
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self.assertRegex(mlir_module, r'tf_executor.fetch.*: !tf_executor.control')
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if __name__ == '__main__':
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test.main()
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