MichaelJKlaiber commented on code in PR #12087: URL: https://github.com/apache/tvm/pull/12087#discussion_r930017268
########## python/tvm/relay/backend/contrib/uma/_template/run.py: ########## @@ -0,0 +1,88 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. +from tvm.micro.testing.aot_test_utils import AOT_DEFAULT_RUNNER + +from tvm.testing.aot import compile_and_run, AOTTestModel, AOTTestRunner + +import tvm +from tvm import relay +from tvm.relay.backend.contrib.uma._template.backend import MyAiHwBackend +from tvm.relay import transform +from collections import OrderedDict + +import numpy as np +import tarfile +from pathlib import Path +import onnx + +from tvm.testing.aot import ( + AOTTestModel, + AOTTestRunner, + generate_ref_data, + compile_and_run, +) + + +def create_conv2d(groups=1, test_runner=AOT_DEFAULT_RUNNER, weight_shape=32): + dtype = "float32" + ishape = (1, 32, 14, 14) + wshape = (32, weight_shape, 3, 3) + pass_config = {"tir.usmp.enable": True} + test_runner = AOTTestRunner( + makefile=test_runner.makefile, + prologue=test_runner.prologue, + epilogue=test_runner.epilogue, + includes=test_runner.includes, + parameters=test_runner.parameters, + pass_config=pass_config, + ) + data0 = relay.var("data", shape=ishape, dtype=dtype) + weight0 = relay.var("weight", shape=wshape, dtype=dtype) + out = relay.nn.conv2d(data0, weight0, kernel_size=(3, 3), padding=(1, 1), groups=groups) + main_f = relay.Function([data0, weight0], out) + mod = tvm.IRModule() + mod["main"] = main_f + mod = transform.InferType()(mod) + i_data = np.random.uniform(0, 1, ishape).astype(dtype) + w1_data = np.random.uniform(0, 1, wshape).astype(dtype) + inputs = OrderedDict([("data", i_data), ("weight", w1_data)]) + output_list = generate_ref_data(mod, inputs) + return mod, inputs, output_list, test_runner + + +def main(): + mod, inputs, output_list, test_runner = create_conv2d() + + uma_backend = MyAiHwBackend() + uma_backend.register() + mod = uma_backend.partition(mod) + target = tvm.target.Target("my_ai_hw", host=tvm.target.Target("c")) + + export_directory = tvm.contrib.utils.tempdir(keep_for_debug=True).path + print(f"Generated files are in {export_directory}") + compile_and_run( + AOTTestModel(module=mod, inputs=inputs, outputs=output_list), + test_runner, + interface_api="c", + use_unpacked_api=True, + target=target, + test_dir=str(export_directory), + ) + + +if __name__ == "__main__": + main() Review Comment: we would tend to move anything TVMC and CLI related to the next PR ########## python/tvm/relay/backend/contrib/uma/uma_cli.py: ########## @@ -0,0 +1,92 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +""" + UMA Command Line Interface (CLI) + + Tool to create code skeletons for an easy integration of + new AI hardware accelerators/libraries into TVM using UMA +""" + +import argparse +import os +import shutil +import sys +from inflection import camelize, underscore + + +def _parse_args(): + parser = argparse.ArgumentParser(description="UMA Interface command line interface") + parser.add_argument( + "--add_hardware", + type=str, + required=True, + ) + parser.add_argument( + "--tutorial", + type=str, + ) + args = parser.parse_args() + return args + + +def replace_template_name( + files: list, template_name: str, add_hw_name: str, template_source: str = "_template" +) -> None: + """ + Replace names in template skeleton code by new name + """ + for f in files: + with open(f) as read_file: + data = read_file.read() + for case in [underscore, camelize]: + data = data.replace(case(template_name), case(add_hw_name)) + data = data.replace(template_source, underscore(add_hw_name)) + with open(f, "w") as write_file: + write_file.write(data) + + +def main(): Review Comment: we would tend to move anything TVMC and CLI related to the next PR -- This is an automated message from the Apache Git Service. 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