156 lines
6.8 KiB
Python
156 lines
6.8 KiB
Python
"""
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######################## inference lenet example ########################
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inference lenet according to model file
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"""
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"""
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######################## 推理环境使用说明 ########################
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1、在推理环境中，需要将数据集从obs拷贝到推理镜像中，推理完以后，需要将输出的结果拷贝到obs.
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(1)将数据集从obs拷贝到推理镜像中：
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obs_data_url = args.data_url
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args.data_url = '/home/work/user-job-dir/data/'
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if not os.path.exists(args.data_url):
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os.mkdir(args.data_url)
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try:
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mox.file.copy_parallel(obs_data_url, args.data_url)
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print("Successfully Download {} to {}".format(obs_data_url,
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args.data_url))
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except Exception as e:
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print('moxing download {} to {} failed: '.format(
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obs_data_url, args.data_url) + str(e))
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(2)将模型文件从obs拷贝到推理镜像中：
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obs_ckpt_url = args.ckpt_url
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args.ckpt_url = '/home/work/user-job-dir/checkpoint.ckpt'
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try:
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mox.file.copy(obs_ckpt_url, args.ckpt_url)
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print("Successfully Download {} to {}".format(obs_ckpt_url,
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args.ckpt_url))
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except Exception as e:
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print('moxing download {} to {} failed: '.format(
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obs_ckpt_url, args.ckpt_url) + str(e))
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(3)将输出的结果拷贝回obs：
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obs_result_url = args.result_url
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args.result_url = '/home/work/user-job-dir/result/'
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if not os.path.exists(args.result_url):
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os.mkdir(args.result_url)
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try:
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mox.file.copy_parallel(args.result_url, obs_result_url)
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print("Successfully Upload {} to {}".format(args.result_url, obs_result_url))
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except Exception as e:
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print('moxing upload {} to {} failed: '.format(args.result_url, obs_result_url) + str(e))
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详细代码可参考以下示例代码：
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"""
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import os
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import argparse
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import moxing as mox
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import mindspore.nn as nn
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from mindspore import context
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from mindspore.train.serialization import load_checkpoint, load_param_into_net
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from mindspore.train import Model
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from mindspore.nn.metrics import Accuracy
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from mindspore import Tensor
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import numpy as np
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from glob import glob
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from dataset import create_dataset
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from config import mnist_cfg as cfg
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from lenet import LeNet5
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description='MindSpore Lenet Example')
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parser.add_argument('--device_target', type=str, default="Ascend", choices=['Ascend', 'GPU', 'CPU'],
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help='device where the code will be implemented (default: Ascend)')
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parser.add_argument('--data_url',
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type=str,
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default="./Data",
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help='path where the dataset is saved')
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parser.add_argument('--ckpt_url',
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help='model to save/load',
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default='./ckpt_url')
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parser.add_argument('--result_url',
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help='result folder to save/load',
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default='./result')
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args = parser.parse_args()
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#将数据集从obs拷贝到推理镜像中：
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obs_data_url = args.data_url
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args.data_url = '/home/work/user-job-dir/data/'
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if not os.path.exists(args.data_url):
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os.mkdir(args.data_url)
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try:
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mox.file.copy_parallel(obs_data_url, args.data_url)
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print("Successfully Download {} to {}".format(obs_data_url,
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args.data_url))
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except Exception as e:
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print('moxing download {} to {} failed: '.format(
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obs_data_url, args.data_url) + str(e))
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#对文件夹进行操作，请使用mox.file.copy_parallel。如果拷贝一个文件。请使用mox.file.copy对文件操作，本次操作是对文件进行操作
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#将模型文件从obs拷贝到推理镜像中：
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obs_ckpt_url = args.ckpt_url
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args.ckpt_url = '/home/work/user-job-dir/checkpoint.ckpt'
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try:
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mox.file.copy(obs_ckpt_url, args.ckpt_url)
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print("Successfully Download {} to {}".format(obs_ckpt_url,
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args.ckpt_url))
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except Exception as e:
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print('moxing download {} to {} failed: '.format(
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obs_ckpt_url, args.ckpt_url) + str(e))
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#设置输出路径result_url
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obs_result_url = args.result_url
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args.result_url = '/home/work/user-job-dir/result/'
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if not os.path.exists(args.result_url):
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os.mkdir(args.result_url)
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args.dataset_path = args.data_url
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args.save_checkpoint_path = args.ckpt_url
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context.set_context(mode=context.GRAPH_MODE, device_target=args.device_target)
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network = LeNet5(cfg.num_classes)
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net_loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction="mean")
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repeat_size = cfg.epoch_size
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net_opt = nn.Momentum(network.trainable_params(), cfg.lr, cfg.momentum)
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model = Model(network, net_loss, net_opt, metrics={"Accuracy": Accuracy()})
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print("============== Starting Testing ==============")
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args.load_ckpt_url = os.path.join(args.save_checkpoint_path)
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print("args.load_ckpt_url is：{}", args.load_ckpt_url )
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param_dict = load_checkpoint(args.load_ckpt_url )
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load_param_into_net(network, param_dict)
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# 定义测试数据集，batch_size设置为1，则取出一张图片
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ds_test = create_dataset(os.path.join(args.dataset_path, "test"), batch_size=1).create_dict_iterator()
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data = next(ds_test)
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# images为测试图片，labels为测试图片的实际分类
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images = data["image"].asnumpy()
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labels = data["label"].asnumpy()
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print('Tensor:', Tensor(data['image']))
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# 使用函数model.predict预测image对应分类
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output = model.predict(Tensor(data['image']))
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predicted = np.argmax(output.asnumpy(), axis=1)
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pred = np.argmax(output.asnumpy(), axis=1)
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print('predicted:', predicted)
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print('pred:', pred)
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# 输出预测分类与实际分类,并输出到result_url
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print(f'Predicted: "{predicted[0]}", Actual: "{labels[0]}"')
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filename = 'result.txt'
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file_path = os.path.join(args.result_url, filename)
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with open(file_path, 'a+') as file:
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file.write(" {}: {:.2f} \n".format("Predicted", predicted[0]))
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# Upload results to obs
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######################## 将输出的结果拷贝到obs（固定写法） ########################
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# 把推理后的结果从本地的运行环境拷贝回obs，在启智平台相对应的推理任务中会提供下载
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try:
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mox.file.copy_parallel(args.result_url, obs_result_url)
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print("Successfully Upload {} to {}".format(args.result_url, obs_result_url))
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except Exception as e:
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print('moxing upload {} to {} failed: '.format(args.result_url, obs_result_url) + str(e))
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######################## 将输出的模型拷贝到obs ######################## |