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Lce benchmark and interpreter flags #717

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Mar 10, 2022
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b9e9e9f
add boolean flag allowing to register indirect BGEMM kernel
simonmaurer Mar 3, 2022
bf8ce6a
added boolean flag to LceInterpreter allowing to register indirect B…
simonmaurer Mar 3, 2022
e25c392
fix comment
simonmaurer Mar 3, 2022
1a23b0c
added boolean flag use_xnnpack in LceInterpreter to explicitly activa…
simonmaurer Mar 4, 2022
72a2ce7
lce_benchmark_model:
simonmaurer Mar 7, 2022
f5bdf7b
formatted code using black code style
simonmaurer Mar 7, 2022
c00a56b
removed uncommented code for lint checks
simonmaurer Mar 7, 2022
b1afcf6
reformatted code, parameter fix in LiteInterpreterWrapper
simonmaurer Mar 7, 2022
b275955
second parameter fix in LiteInterpreterWrapper
simonmaurer Mar 7, 2022
4afb363
reformat files for proper linting
simonmaurer Mar 7, 2022
060d39c
reformat code for linting
simonmaurer Mar 7, 2022
33b8a78
add include of LceBenchmarkTfLiteModel for cmake build
simonmaurer Mar 7, 2022
cddcad1
reformat code for linting
simonmaurer Mar 7, 2022
2d136ea
fix intent in lce_benchmark_tflite_mode.cc
simonmaurer Mar 7, 2022
3bf5817
typo fix
simonmaurer Mar 7, 2022
4be5503
format code in lce_benchmark_tflite_model.cc
simonmaurer Mar 7, 2022
e669c8b
buildifier check for BUILD
simonmaurer Mar 7, 2022
82951a6
srcs for Makefile
simonmaurer Mar 7, 2022
1c50317
removed include
simonmaurer Mar 7, 2022
71d3b35
added warning when use_reference_bconv and use_indirect_bgemm are bot…
simonmaurer Mar 9, 2022
e43b84d
reformat code for linting
simonmaurer Mar 9, 2022
a2be814
adapted BUILD file to include TFLite logging header
simonmaurer Mar 9, 2022
039c531
include TFLite logging header for interpreter_wrapper_lite build
simonmaurer Mar 9, 2022
cb2c344
typo fix: adapted BUILD file to include TFLite logging
simonmaurer Mar 9, 2022
038a603
typo fix: include TFLite logging header for interpreter_wrapper_lite …
simonmaurer Mar 9, 2022
7a08381
fix: remove unused header file, logging package dependency
simonmaurer Mar 9, 2022
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15 changes: 15 additions & 0 deletions larq_compute_engine/tflite/benchmark/BUILD
Original file line number Diff line number Diff line change
Expand Up @@ -29,8 +29,23 @@ tf_cc_binary(
],
}),
deps = [
"//larq_compute_engine/tflite/benchmark:lce_benchmark_tflite_model_lib",
"//larq_compute_engine/tflite/kernels:lce_op_kernels",
"@org_tensorflow//tensorflow/lite/tools:logging",
],
)

cc_library(
name = "lce_benchmark_tflite_model_lib",
srcs = ["lce_benchmark_tflite_model.cc"],
hdrs = ["lce_benchmark_tflite_model.h"],
copts = tflite_copts() + select({
"@org_tensorflow//tensorflow:ios": [
"-xobjective-c++",
],
"//conditions:default": [],
}),
deps = [
"@org_tensorflow//tensorflow/lite/tools/benchmark:benchmark_tflite_model_lib",
],
)
12 changes: 9 additions & 3 deletions larq_compute_engine/tflite/benchmark/lce_benchmark_main.cc
Original file line number Diff line number Diff line change
Expand Up @@ -15,23 +15,29 @@ limitations under the License.
==============================================================================*/

#include <iostream>
#include <string>

#include "absl/base/attributes.h"
#include "larq_compute_engine/tflite/benchmark/lce_benchmark_tflite_model.h"
#include "larq_compute_engine/tflite/kernels/lce_ops_register.h"
#include "tensorflow/lite/tools/benchmark/benchmark_tflite_model.h"
#include "tensorflow/lite/tools/logging.h"

bool use_reference_bconv = false;
bool use_indirect_bgemm = false;

void ABSL_ATTRIBUTE_WEAK
RegisterSelectedOps(::tflite::MutableOpResolver* resolver) {
compute_engine::tflite::RegisterLCECustomOps(resolver);
compute_engine::tflite::RegisterLCECustomOps(resolver, use_reference_bconv,
use_indirect_bgemm);
}

namespace tflite {
namespace benchmark {

int Main(int argc, char** argv) {
TFLITE_LOG(INFO) << "STARTING!";
BenchmarkTfLiteModel benchmark;
LceBenchmarkTfLiteModel benchmark(LceBenchmarkTfLiteModel::DefaultParams(),
use_reference_bconv, use_indirect_bgemm);
if (benchmark.Run(argc, argv) != kTfLiteOk) {
TFLITE_LOG(ERROR) << "Benchmarking failed.";
return EXIT_FAILURE;
Expand Down
74 changes: 74 additions & 0 deletions larq_compute_engine/tflite/benchmark/lce_benchmark_tflite_model.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,74 @@
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Modifications copyright (C) 2022 Larq Contributors.

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.
==============================================================================*/

#include "larq_compute_engine/tflite/benchmark/lce_benchmark_tflite_model.h"

#include "tensorflow/lite/tools/logging.h"

namespace tflite {
namespace benchmark {

BenchmarkParams LceBenchmarkTfLiteModel::DefaultParams() {
BenchmarkParams default_params = BenchmarkTfLiteModel::DefaultParams();
default_params.AddParam("use_reference_bconv",
BenchmarkParam::Create<bool>(false));
default_params.AddParam("use_indirect_bgemm",
BenchmarkParam::Create<bool>(false));

return default_params;
}

LceBenchmarkTfLiteModel::LceBenchmarkTfLiteModel(BenchmarkParams params,
bool& use_reference_bconv,
bool& use_indirect_bgemm)
: BenchmarkTfLiteModel(std::move(params)),
use_reference_bconv(use_reference_bconv),
use_indirect_bgemm(use_indirect_bgemm) {}

std::vector<Flag> LceBenchmarkTfLiteModel::GetFlags() {
std::vector<Flag> flags = BenchmarkTfLiteModel::GetFlags();
std::vector<Flag> lce_flags = {
CreateFlag<bool>(
"use_reference_bconv", &params_,
"When true, uses the reference implementation of LceBconv2d."),
CreateFlag<bool>("use_indirect_bgemm", &params_,
"When true, uses the optimized indirect BGEMM kernel of"
"LceBconv2d.")};

flags.insert(flags.end(), lce_flags.begin(), lce_flags.end());

return flags;
}

void LceBenchmarkTfLiteModel::LogParams() {
BenchmarkTfLiteModel::LogParams();
const bool verbose = params_.Get<bool>("verbose");
LOG_BENCHMARK_PARAM(bool, "use_reference_bconv", "Use reference Bconv",
verbose);
LOG_BENCHMARK_PARAM(bool, "use_indirect_bgemm", "Use indirect BGEMM",
verbose);
}

TfLiteStatus LceBenchmarkTfLiteModel::Run(int argc, char** argv) {
TF_LITE_ENSURE_STATUS(ParseFlags(argc, argv));
use_reference_bconv = params_.Get<bool>("use_reference_bconv");
use_indirect_bgemm = params_.Get<bool>("use_indirect_bgemm");

return BenchmarkTfLiteModel::Run();
}

} // namespace benchmark
} // namespace tflite
47 changes: 47 additions & 0 deletions larq_compute_engine/tflite/benchmark/lce_benchmark_tflite_model.h
Original file line number Diff line number Diff line change
@@ -0,0 +1,47 @@
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
Modifications copyright (C) 2022 Larq Contributors.

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.
==============================================================================*/

#ifndef COMPUTE_ENGINE_TFLITE_BENCHMARK_LCE_BENCHMARK_TFLITE_MODEL_H_
#define COMPUTE_ENGINE_TFLITE_BENCHMARK_LCE_BENCHMARK_TFLITE_MODEL_H_

#include "tensorflow/lite/tools/benchmark/benchmark_tflite_model.h"

namespace tflite {
namespace benchmark {

// Benchmarks a TFLite model by running tflite interpreter.
class LceBenchmarkTfLiteModel : public BenchmarkTfLiteModel {
public:
explicit LceBenchmarkTfLiteModel(BenchmarkParams params,
bool& use_reference_bconv,
bool& use_indirect_bgemm);

std::vector<Flag> GetFlags() override;
void LogParams() override;
static BenchmarkParams DefaultParams();

using BenchmarkTfLiteModel::Run;
TfLiteStatus Run(int argc, char** argv);

private:
bool& use_reference_bconv;
bool& use_indirect_bgemm;
};

} // namespace benchmark
} // namespace tflite

#endif // COMPUTE_ENGINE_TFLITE_BENCHMARK_LCE_BENCHMARK_TFLITE_MODEL_H_
1 change: 1 addition & 0 deletions larq_compute_engine/tflite/build_make/Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,7 @@ LCE_EXAMPLE_SRCS := \
examples/lce_minimal.cc

LCE_BENCHMARK_SRCS := \
larq_compute_engine/tflite/benchmark/lce_benchmark_tflite_model.cc \
larq_compute_engine/tflite/benchmark/lce_benchmark_main.cc

# These target-specific makefiles should modify or replace options like
Expand Down
1 change: 1 addition & 0 deletions larq_compute_engine/tflite/kernels/BUILD
Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,7 @@ cc_library(
"@org_tensorflow//tensorflow/lite:type_to_tflitetype",
"@org_tensorflow//tensorflow/lite/kernels/internal:kernel_utils",
"@org_tensorflow//tensorflow/lite/kernels/internal:tensor",
"@org_tensorflow//tensorflow/lite/tools:logging",
"@ruy//ruy/profiler:instrumentation",
],
alwayslink = 1,
Expand Down
23 changes: 20 additions & 3 deletions larq_compute_engine/tflite/kernels/lce_ops_register.h
Original file line number Diff line number Diff line change
Expand Up @@ -3,23 +3,34 @@

#include "tensorflow/lite/context.h"
#include "tensorflow/lite/op_resolver.h"
#include "tensorflow/lite/tools/logging.h"

// This file contains forward declaration of all custom ops
// implemented in LCE which can be used to link against LCE library.

namespace compute_engine {
namespace tflite {

using namespace ::tflite;

TfLiteRegistration* Register_QUANTIZE();
TfLiteRegistration* Register_DEQUANTIZE();
TfLiteRegistration* Register_BCONV_2D();
TfLiteRegistration* Register_BCONV_2D_REF();
TfLiteRegistration* Register_BCONV_2D_OPT_INDIRECT_BGEMM();
TfLiteRegistration* Register_BMAXPOOL_2D();

// By calling this function on TF lite mutable op resolver, all LCE custom ops
// will be registerd to the op resolver.
inline void RegisterLCECustomOps(::tflite::MutableOpResolver* resolver,
const bool use_reference_bconv = false) {
const bool use_reference_bconv = false,
const bool use_indirect_bgemm = false) {
if (use_reference_bconv && use_indirect_bgemm) {
TFLITE_LOG(WARN)
<< "WARNING: 'use_reference_bconv' and `use_indirect_bgemm` "
"are both set to true. use_indirect_bgemm==true "
"will have no effect.";
}
resolver->AddCustom("LceQuantize",
compute_engine::tflite::Register_QUANTIZE());
resolver->AddCustom("LceDequantize",
Expand All @@ -28,8 +39,14 @@ inline void RegisterLCECustomOps(::tflite::MutableOpResolver* resolver,
resolver->AddCustom("LceBconv2d",
compute_engine::tflite::Register_BCONV_2D_REF());
} else {
resolver->AddCustom("LceBconv2d",
compute_engine::tflite::Register_BCONV_2D());
if (use_indirect_bgemm) {
resolver->AddCustom(
"LceBconv2d",
compute_engine::tflite::Register_BCONV_2D_OPT_INDIRECT_BGEMM());
} else {
resolver->AddCustom("LceBconv2d",
compute_engine::tflite::Register_BCONV_2D());
}
}
resolver->AddCustom("LceBMaxPool2d",
compute_engine::tflite::Register_BMAXPOOL_2D());
Expand Down
10 changes: 9 additions & 1 deletion larq_compute_engine/tflite/python/interpreter.py
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,8 @@ class Interpreter(InterpreterBase):
flatbuffer_model: A serialized Larq Compute Engine model in the flatbuffer format.
num_threads: The number of threads used by the interpreter.
use_reference_bconv: When True, uses the reference implementation of LceBconv2d.
use_indirect_bgemm: When True, uses the optimized indirect BGEMM kernel of LceBconv2d.
use_xnnpack: When True, uses the XNNPack delegate of TFLite.

# Attributes
input_types: Returns a list of input types.
Expand All @@ -40,11 +42,17 @@ def __init__(
flatbuffer_model: bytes,
num_threads: int = 1,
use_reference_bconv: bool = False,
use_indirect_bgemm: bool = False,
use_xnnpack: bool = False,
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I think this changes the default or am I missing something? I think that's fine, but can you explain the reasoning behind it?

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@simonmaurer simonmaurer Mar 8, 2022

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hi @lgeiger. you're correct. following the discussion on #713 I've implemented it like this.
A) one reason to include this flag in the LceInterpreter is to make it reflect more the behavior of the benchmark binary.
B) the second reason is dynamic allocation, thus having models with allocation_type==kTfLiteDynamic.
we had models like this and when we set use_xnnpack=true in the benchmark_model there will be an error thrown. this would be true for LCEInterpreter as well, as under the hood XNNPACK is "silently" applied.

):
from larq_compute_engine.tflite.python import interpreter_wrapper_lite

super().__init__(
interpreter_wrapper_lite.LiteInterpreter(
flatbuffer_model, num_threads, use_reference_bconv
flatbuffer_model,
num_threads,
use_reference_bconv,
use_indirect_bgemm,
use_xnnpack,
)
)
21 changes: 15 additions & 6 deletions larq_compute_engine/tflite/python/interpreter_wrapper_lite.cc
Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,9 @@ class LiteInterpreterWrapper
public:
LiteInterpreterWrapper(const pybind11::bytes& flatbuffer,
const int num_threads = 1,
const bool use_reference_bconv = false);
const bool use_reference_bconv = false,
const bool use_indirect_bgemm = false,
const bool use_xnnpack = false);
~LiteInterpreterWrapper(){};

private:
Expand All @@ -25,7 +27,8 @@ class LiteInterpreterWrapper

LiteInterpreterWrapper::LiteInterpreterWrapper(
const pybind11::bytes& flatbuffer, const int num_threads,
const bool use_reference_bconv) {
const bool use_reference_bconv, const bool use_indirect_bgemm,
const bool use_xnnpack) {
// Make a copy of the flatbuffer because it can get deallocated after the
// constructor is done
flatbuffer_ = static_cast<std::string>(flatbuffer);
Expand All @@ -37,9 +40,14 @@ LiteInterpreterWrapper::LiteInterpreterWrapper(
}

// Build the interpreter
resolver_ = std::make_unique<tflite::ops::builtin::BuiltinOpResolver>();
compute_engine::tflite::RegisterLCECustomOps(resolver_.get(),
use_reference_bconv);
if (use_xnnpack) {
resolver_ = std::make_unique<tflite::ops::builtin::BuiltinOpResolver>();
} else {
resolver_ = std::make_unique<
tflite::ops::builtin::BuiltinOpResolverWithoutDefaultDelegates>();
}
compute_engine::tflite::RegisterLCECustomOps(
resolver_.get(), use_reference_bconv, use_indirect_bgemm);

tflite::InterpreterBuilder builder(*model_, *resolver_);
builder(&interpreter_, num_threads);
Expand All @@ -51,7 +59,8 @@ LiteInterpreterWrapper::LiteInterpreterWrapper(

PYBIND11_MODULE(interpreter_wrapper_lite, m) {
pybind11::class_<LiteInterpreterWrapper>(m, "LiteInterpreter")
.def(pybind11::init<const pybind11::bytes&, const int, const bool>())
.def(pybind11::init<const pybind11::bytes&, const int, const bool,
const bool, const bool>())
.def_property("input_types", &LiteInterpreterWrapper::get_input_types,
nullptr)
.def_property("output_types", &LiteInterpreterWrapper::get_output_types,
Expand Down