d33cb73389
This is to prepare the 16 bits activation quantization release. The data type specified by this flag is only applied on the activations. PiperOrigin-RevId: 311478782 Change-Id: I5f63f0508011cc0b1b47a0debb35c17d3284eae9
81 lines
3.4 KiB
C++
81 lines
3.4 KiB
C++
/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "pybind11/pybind11.h"
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#include "tensorflow/lite/toco/python/toco_python_api.h"
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#include "tensorflow/python/lib/core/pybind11_lib.h"
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namespace py = pybind11;
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PYBIND11_MODULE(_pywrap_toco_api, m) {
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m.def(
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"TocoConvert",
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[](py::object model_flags_proto_txt_raw,
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py::object toco_flags_proto_txt_raw, py::object input_contents_txt_raw,
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bool extended_return, py::object debug_info_txt_raw,
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bool enable_mlir_converter) {
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return tensorflow::PyoOrThrow(toco::TocoConvert(
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model_flags_proto_txt_raw.ptr(), toco_flags_proto_txt_raw.ptr(),
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input_contents_txt_raw.ptr(), extended_return,
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debug_info_txt_raw.ptr(), enable_mlir_converter));
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},
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py::arg("model_flags_proto_txt_raw"), py::arg("toco_flags_proto_txt_raw"),
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py::arg("input_contents_txt_raw"), py::arg("extended_return") = false,
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py::arg("debug_info_txt_raw") = py::none(),
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py::arg("enable_mlir_converter") = false,
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R"pbdoc(
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Convert a model represented in `input_contents`. `model_flags_proto`
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describes model parameters. `toco_flags_proto` describes conversion
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parameters (see relevant .protos for more information). Returns a string
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representing the contents of the converted model. When extended_return
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flag is set to true returns a dictionary that contains string representation
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of the converted model and some statistics like arithmetic ops count.
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`debug_info_str` contains the `GraphDebugInfo` proto. When
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`enable_mlir_converter` is True, tuse MLIR-based conversion instead of
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TOCO conversion.
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)pbdoc");
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m.def(
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"TocoGetPotentiallySupportedOps",
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[]() {
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return tensorflow::PyoOrThrow(toco::TocoGetPotentiallySupportedOps());
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},
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R"pbdoc(
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Returns a list of names of all ops potentially supported by tflite.
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)pbdoc");
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m.def(
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"ExperimentalMlirQuantizeModel",
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[](py::object input_contents_txt_raw, bool disable_per_channel,
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bool fully_quantize, int inference_type) {
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return tensorflow::PyoOrThrow(toco::MlirQuantizeModel(
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input_contents_txt_raw.ptr(), disable_per_channel, fully_quantize,
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inference_type));
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},
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py::arg("input_contents_txt_raw"), py::arg("disable_per_channel") = false,
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py::arg("fully_quantize") = true, py::arg("inference_type") = 9,
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R"pbdoc(
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Returns a quantized model.
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)pbdoc");
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m.def(
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"ExperimentalMlirSparsifyModel",
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[](py::object input_contents_txt_raw) {
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return tensorflow::PyoOrThrow(
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toco::MlirSparsifyModel(input_contents_txt_raw.ptr()));
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},
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py::arg("input_contents_txt_raw"),
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R"pbdoc(
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Returns a sparsified model.
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)pbdoc");
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}
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