130 lines
3.8 KiB
Python
130 lines
3.8 KiB
Python
# Copyright 2020 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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"""Python module for MLIR functions exported by pybind11."""
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# pylint: disable=invalid-import-order, g-bad-import-order, wildcard-import, unused-import, undefined-variable
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from tensorflow.python import pywrap_tensorflow
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from tensorflow.python.eager import context
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from tensorflow.python._pywrap_mlir import *
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def import_graphdef(
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graphdef,
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pass_pipeline,
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show_debug_info,
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input_names=None,
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input_data_types=None,
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input_data_shapes=None,
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output_names=[],
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):
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if input_names is not None:
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return ImportGraphDef(
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str(graphdef).encode('utf-8'),
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pass_pipeline.encode('utf-8'),
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show_debug_info,
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','.join(input_names).encode('utf-8'),
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','.join(input_data_types).encode('utf-8'),
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':'.join(input_data_shapes).encode('utf-8'),
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','.join(output_names).encode('utf-8'),
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)
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return ImportGraphDef(
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str(graphdef).encode('utf-8'),
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pass_pipeline.encode('utf-8'),
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show_debug_info,
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)
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def import_function(concrete_function, pass_pipeline, show_debug_info):
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ctxt = context.context()
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ctxt.ensure_initialized()
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return ImportFunction(
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ctxt._handle,
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str(concrete_function.function_def).encode('utf-8'),
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pass_pipeline.encode('utf-8'),
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show_debug_info,
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)
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def experimental_convert_saved_model_to_mlir(
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saved_model_path, exported_names, show_debug_info
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):
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return ExperimentalConvertSavedModelToMlir(
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str(saved_model_path).encode('utf-8'),
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str(exported_names).encode('utf-8'),
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show_debug_info,
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)
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def experimental_convert_saved_model_v1_to_mlir_lite(
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saved_model_path, exported_names, tags, upgrade_legacy, show_debug_info
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):
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return ExperimentalConvertSavedModelV1ToMlirLite(
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str(saved_model_path).encode('utf-8'),
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str(exported_names).encode('utf-8'),
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str(tags).encode('utf-8'),
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upgrade_legacy,
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show_debug_info,
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)
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def experimental_convert_saved_model_v1_to_mlir(
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saved_model_path,
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exported_names,
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tags,
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lift_variables,
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include_variables_in_initializers,
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upgrade_legacy,
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show_debug_info,
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):
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return ExperimentalConvertSavedModelV1ToMlir(
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str(saved_model_path).encode('utf-8'),
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str(exported_names).encode('utf-8'),
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str(tags).encode('utf-8'),
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lift_variables,
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include_variables_in_initializers,
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upgrade_legacy,
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show_debug_info,
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)
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def experimental_run_pass_pipeline(mlir_txt, pass_pipeline, show_debug_info):
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return ExperimentalRunPassPipeline(
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mlir_txt.encode('utf-8'), pass_pipeline.encode('utf-8'), show_debug_info
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)
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def experimental_write_bytecode(filename, mlir_txt):
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return ExperimentalWriteBytecode(filename.encode('utf-8'), mlir_txt.encode())
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def experimental_tflite_to_tosa_bytecode(
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flatbuffer,
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bytecode,
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use_external_constant=False,
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ordered_input_arrays=None,
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ordered_output_arrays=None,
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):
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if ordered_input_arrays is None:
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ordered_input_arrays = []
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if ordered_output_arrays is None:
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ordered_output_arrays = []
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return ExperimentalTFLiteToTosaBytecode(
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flatbuffer.encode('utf-8'),
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bytecode.encode('utf-8'),
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use_external_constant,
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ordered_input_arrays,
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ordered_output_arrays,
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)
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