diff options
| -rw-r--r-- | applications/baremetal/CMakeLists.txt | 10 | ||||
| -rw-r--r-- | applications/baremetal/main.cpp | 4 | ||||
| -rwxr-xr-x | scripts/run_platform.py | 162 |
3 files changed, 173 insertions, 3 deletions
diff --git a/applications/baremetal/CMakeLists.txt b/applications/baremetal/CMakeLists.txt index 129fd3f..c9d965b 100644 --- a/applications/baremetal/CMakeLists.txt +++ b/applications/baremetal/CMakeLists.txt @@ -16,6 +16,14 @@ # limitations under the License. # +set(BAREMETAL_PATH "" CACHE PATH "Path to input, output and network for baremetal") + +if (IS_DIRECTORY ${BAREMETAL_PATH}) + ethosu_add_executable_test(baremetal_custom PRIVATE + SOURCES main.cpp) + target_include_directories(baremetal_custom PRIVATE ${BAREMETAL_PATH}) +endif() + ethosu_add_executable_test(baremetal_keyword_cnn PRIVATE SOURCES main.cpp) target_include_directories(baremetal_keyword_cnn PRIVATE models/keyword_spotting_cnn_small_int8) @@ -26,4 +34,4 @@ target_include_directories(baremetal_keyword_dnn PRIVATE models/keyword_spotting ethosu_add_executable_test(baremetal_keyword_ds_dnn PRIVATE SOURCES main.cpp) -target_include_directories(baremetal_keyword_ds_dnn PRIVATE models/keyword_spotting_ds_dnn_large_clustered_int8)
\ No newline at end of file +target_include_directories(baremetal_keyword_ds_dnn PRIVATE models/keyword_spotting_ds_dnn_large_clustered_int8) diff --git a/applications/baremetal/main.cpp b/applications/baremetal/main.cpp index e1e01de..4c0bf50 100644 --- a/applications/baremetal/main.cpp +++ b/applications/baremetal/main.cpp @@ -47,7 +47,7 @@ __attribute__((section(".bss.tensor_arena"), aligned(16))) uint8_t TFLuTensorAre InferenceProcess::InferenceProcess inferenceProcess(TFLuTensorArena, TENSOR_ARENA_SIZE); -uint8_t outputData[176] __attribute__((aligned(16), section("output_data_sec"))); +uint8_t outputData[sizeof(expectedOutputData)] __attribute__((aligned(16), section("output_data_sec"))); int runInference() { // Load inference data @@ -81,4 +81,4 @@ int runInference() { int main() { int ret = runInference(); return ret; -}
\ No newline at end of file +} diff --git a/scripts/run_platform.py b/scripts/run_platform.py new file mode 100755 index 0000000..0600828 --- /dev/null +++ b/scripts/run_platform.py @@ -0,0 +1,162 @@ +#!/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 + + +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()}"] + 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())) + + 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()) |