Intelegentny_Pszczelarz/.venv/Lib/site-packages/tensorflow/python/pywrap_mlir.py
2023-06-19 00:49:18 +02:00

85 lines
3.6 KiB
Python

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