| # Copyright 2023 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 utility functions.""" |
| import tensorflow as tf |
| from tensorflow.python.framework import load_library |
| from tensorflow.python.platform import resource_loader |
| from tflite_micro.python.tflite_micro import runtime |
| |
| |
| # TODO(b/286889497): find better name and place for this function. |
| def get_tflm_interpreter(concrete_function, trackable_obj): |
| """Initialize a TFLite interpreter with a concerte function. |
| |
| Args: |
| concrete_function: A concrete function |
| |
| Returns: |
| TFLite interpreter object |
| """ |
| converter = tf.lite.TFLiteConverter.from_concrete_functions( |
| [concrete_function], trackable_obj) |
| converter.allow_custom_ops = True |
| tflite_model = converter.convert() |
| |
| return runtime.Interpreter.from_bytes(tflite_model, arena_size=500000) |
| |
| |
| def load_custom_op(name): |
| return load_library.load_op_library( |
| resource_loader.get_path_to_datafile('../ops/_' + name)) |
