| #!/usr/bin/env python3 |
| |
| # |
| # Copyright (c) 2021 Arm Limited. All rights reserved. |
| # |
| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # 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 |
| # |
| # 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. |
| # |
| |
| import argparse |
| import multiprocessing |
| import numpy |
| import os |
| import pathlib |
| import re |
| import shutil |
| import subprocess |
| import sys |
| |
| os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' |
| from tensorflow.lite.python.interpreter import Interpreter, OpResolverType |
| |
| CORE_PLATFORM_PATH = pathlib.Path(__file__).resolve().parents[1] |
| |
| def run_cmd(cmd, **kwargs): |
| # str() is called to handle pathlib.Path objects |
| cmd_str = " ".join([str(arg) for arg in cmd]) |
| print(f"Running command: {cmd_str}") |
| return subprocess.run(cmd, check=True, **kwargs) |
| |
| def build_core_platform(output_folder, target, toolchain): |
| build_folder = output_folder/"model"/"build" |
| cmake_cmd = ["cmake", |
| CORE_PLATFORM_PATH/"targets"/target, |
| f"-B{build_folder}", |
| f"-DCMAKE_TOOLCHAIN_FILE={CORE_PLATFORM_PATH/'cmake'/'toolchain'/(toolchain + '.cmake')}", |
| f"-DBAREMETAL_PATH={output_folder}"] |
| |
| run_cmd(cmake_cmd) |
| |
| make_cmd = ["make", "-C", build_folder, f"-j{multiprocessing.cpu_count()}", "baremetal_custom"] |
| run_cmd(make_cmd) |
| |
| def generate_reference_data(output_folder, non_optimized_model_path, input_path, expected_output_path): |
| interpreter = Interpreter(model_path=str(non_optimized_model_path.resolve()), experimental_op_resolver_type=OpResolverType.BUILTIN_REF) |
| |
| interpreter.allocate_tensors() |
| input_detail = interpreter.get_input_details()[0] |
| output_detail = interpreter.get_output_details()[0] |
| |
| input_data = None |
| if input_path is None: |
| # Randomly generate input data |
| dtype = input_detail["dtype"] |
| if dtype is numpy.float32: |
| rand = numpy.random.default_rng() |
| input_data = rand.random(size=input_detail["shape"], dtype=numpy.float32) |
| else: |
| input_data = numpy.random.randint(low=numpy.iinfo(dtype).min, high=numpy.iinfo(dtype).max, size=input_detail["shape"], dtype=dtype) |
| else: |
| # Load user provided input data |
| input_data = numpy.load(input_path) |
| |
| output_data = None |
| if expected_output_path is None: |
| # Run the network with input_data to get reference output |
| interpreter.set_tensor(input_detail["index"], input_data) |
| interpreter.invoke() |
| output_data = interpreter.get_tensor(output_detail["index"]) |
| else: |
| # Load user provided output data |
| output_data = numpy.load(expected_output_path) |
| |
| network_input_path = output_folder/"ref_input.bin" |
| network_output_path = output_folder/"ref_output.bin" |
| |
| with network_input_path.open("wb") as fp: |
| fp.write(input_data.tobytes()) |
| with network_output_path.open("wb") as fp: |
| fp.write(output_data.tobytes()) |
| |
| output_folder = pathlib.Path(output_folder) |
| dump_c_header(network_input_path, output_folder/"input.h", "inputData", "input_data_sec", 4) |
| dump_c_header(network_output_path, output_folder/"output.h", "expectedOutputData", "expected_output_data_sec", 4) |
| |
| def dump_c_header(input_path, output_path, array_name, section, alignment, extra_data=""): |
| byte_array = [] |
| with open(input_path, "rb") as fp: |
| byte_string = fp.read() |
| byte_array = [f"0x{format(byte, '02x')}" for byte in byte_string] |
| |
| last = byte_array[-1] |
| byte_array = [byte + "," for byte in byte_array[:-1]] + [last] |
| |
| byte_array = [" " + byte if idx % 12 == 0 else byte |
| for idx, byte in enumerate(byte_array)] |
| |
| byte_array = [byte + "\n" if (idx + 1) % 12 == 0 else byte + " " |
| for idx, byte in enumerate(byte_array)] |
| |
| with open(output_path, "w") as carray: |
| header = f"uint8_t {array_name}[] __attribute__((section(\"{section}\"), aligned({alignment}))) = {{\n" |
| carray.write(extra_data) |
| carray.write(header) |
| carray.write("".join(byte_array)) |
| carray.write("\n};\n") |
| |
| def optimize_network(output_folder, network_path, accelerator_conf): |
| vela_cmd = ["vela", |
| network_path, |
| "--output-dir", output_folder, |
| "--accelerator-config", accelerator_conf] |
| res = run_cmd(vela_cmd) |
| optimized_model_path = output_folder/(network_path.stem + "_vela.tflite") |
| model_name = network_path.stem |
| dump_c_header(optimized_model_path, output_folder/"model.h", "networkModelData", "network_model_sec", 16, extra_data=f"const char *modelName=\"{model_name}\";\n") |
| |
| def run_model(output_folder): |
| build_folder = output_folder/"model"/"build" |
| model_cmd = ["ctest", "-V", "-R", "^baremetal_custom$" ] |
| res = run_cmd(model_cmd, cwd=build_folder) |
| |
| def main(): |
| target_mapping = { |
| "corstone-300": "ethos-u55-128" |
| } |
| parser = argparse.ArgumentParser() |
| parser.add_argument("-o", "--output-folder", type=pathlib.Path, default="output", help="Output folder for build and generated files") |
| parser.add_argument("--network-path", type=pathlib.Path, required=True, help="Path to .tflite file") |
| parser.add_argument("--target", choices=target_mapping, default="corstone-300", help=f"Configure target") |
| parser.add_argument("--toolchain", choices=["armclang", "arm-none-eabi-gcc"], default="armclang", help=f"Configure toolchain") |
| parser.add_argument("--custom-input", type=pathlib.Path, help="Custom input to network") |
| parser.add_argument("--custom-output", type=pathlib.Path, help="Custom expected output data for network") |
| |
| args = parser.parse_args() |
| |
| args.output_folder.mkdir(exist_ok=True) |
| |
| try: |
| optimize_network(args.output_folder, args.network_path, target_mapping[args.target]) |
| generate_reference_data(args.output_folder, args.network_path, args.custom_input, args.custom_output) |
| build_core_platform(args.output_folder, args.target, args.toolchain) |
| run_model(args.output_folder) |
| except subprocess.CalledProcessError as err: |
| print(f"Command: '{err.cmd}' failed", file=sys.stderr) |
| return 1 |
| return 0 |
| |
| if __name__ == "__main__": |
| sys.exit(main()) |