67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
# Copyright 2023 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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""" Generates C/C++ source code capable of performing inference for a model. """
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import os
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from absl import app
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from absl import flags
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from collections.abc import Sequence
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from tflite_micro.codegen import inference_generator
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from tflite_micro.codegen import graph
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from tflite_micro.tensorflow.lite.tools import flatbuffer_utils
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# Usage information:
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# Default:
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# `bazel run codegen:code_generator -- \
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# --model=</path/to/my_model.tflite>
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# Output will be located at: /path/to/my_model.h|cc
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_MODEL_PATH = flags.DEFINE_string(name="model",
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default=None,
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help="Path to the TFLite model file.",
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required=True)
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_OUTPUT_DIR = flags.DEFINE_string(
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name="output_dir",
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default=None,
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help="Path to write generated source to. Leave blank to use 'model' path.",
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required=False)
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_OUTPUT_NAME = flags.DEFINE_string(
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name="output_name",
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default=None,
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help=("The output basename for the generated .h/.cc. Leave blank to use "
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"'model' basename."),
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required=False)
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def main(argv: Sequence[str]) -> None:
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output_dir = _OUTPUT_DIR.value or os.path.dirname(_MODEL_PATH.value)
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output_name = _OUTPUT_NAME.value or os.path.splitext(
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os.path.basename(_MODEL_PATH.value))[0]
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model = flatbuffer_utils.read_model(_MODEL_PATH.value)
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print("Generating inference code for model: {}".format(_MODEL_PATH.value))
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inference_generator.generate(output_dir, output_name,
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graph.OpCodeTable([model]), graph.Graph(model))
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if __name__ == "__main__":
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app.run(main)
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