"""Benchmark script for ImageNet models on ARM CPU. see README.md for the usage and results of this script. """ import argparse import numpy as np import tvm from tvm.contrib.util import tempdir import tvm.contrib.graph_runtime as runtime import nnvm.compiler import nnvm.testing from util import get_network, print_progress def evaluate_network(network, target, target_host, number): # connect to remote device tracker = tvm.rpc.connect_tracker(args.host, args.port) remote = tracker.request(args.rpc_key) print_progress(network) net, params, input_shape, output_shape = get_network(network, batch_size=1) print_progress("%-20s building..." % network) with nnvm.compiler.build_config(opt_level=3): graph, lib, params = nnvm.compiler.build( net, target=target, target_host=target_host, shape={'data': input_shape}, params=params, dtype=dtype) tmp = tempdir() if 'android' in str(target): from tvm.contrib import ndk filename = "%s.so" % network lib.export_library(tmp.relpath(filename), ndk.create_shared) else: filename = "%s.tar" % network lib.export_library(tmp.relpath(filename)) # upload library and params print_progress("%-20s uploading..." % network) ctx = remote.context(str(target), 0) remote.upload(tmp.relpath(filename)) rlib = remote.load_module(filename) module = runtime.create(graph, rlib, ctx) data_tvm = tvm.nd.array((np.random.uniform(size=input_shape)).astype(dtype)) module.set_input('data', data_tvm) module.set_input(**params) # evaluate print_progress("%-20s evaluating..." % network) ftimer = module.module.time_evaluator("run", ctx, number=args.number, repeat=3) prof_res = np.array(ftimer().results) * 1000 # multiply 1000 for converting to millisecond print("%-20s %-19s (%s)" % (network, "%.2f ms" % np.mean(prof_res), "%.2f ms" % np.std(prof_res))) if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--network", type=str, choices= ['resnet-18', 'resnet-34', 'vgg-16', 'mobilenet', 'mobilenet_v2', 'squeezenet v1.0', 'squeezenet v1.1']) parser.add_argument("--model", type=str, choices= ['rk3399', 'mate10', 'mate10pro', 'p20', 'p20pro', 'pixel2', 'rasp3b', 'pynq'], default='rk3399', help="The model of the test device. If your device is not listed in " "the choices list, pick the most similar one as argument.") parser.add_argument("--host", type=str, default='localhost') parser.add_argument("--port", type=int, default=9190) parser.add_argument("--rpc-key", type=str, required=True) parser.add_argument("--number", type=int, default=6) args = parser.parse_args() dtype = 'float32' if args.network is None: networks = ['squeezenet_v1.1', 'mobilenet', 'resnet-18', 'vgg-16'] else: networks = [args.network] target = tvm.target.arm_cpu(model=args.model) target_host = None print("--------------------------------------------------") print("%-20s %-20s" % ("Network Name", "Mean Inference Time (std dev)")) print("--------------------------------------------------") for network in networks: evaluate_network(network, target, target_host, args.number)