forked from huawei/mindspore2022
modify model_zoo resnet50 for R1.3
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@ -230,9 +230,10 @@ If you want to run in modelarts, please check the official documentation of [mod
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├── resnet18_imagenet2012_config.yaml # parameter configuration
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├── resnet34_imagenet2012_config.yaml # parameter configuration
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├── resnet50_cifar10_config.yaml # parameter configuration
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├── resnet50_imagenet2012_Ascend_config.yaml # parameter configuration
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├── resnet50_imagenet2012_Acc_config.yaml # parameter configuration
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├── resnet50_imagenet2012_Ascend_Thor_config.yaml # parameter configuration
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├── resnet50_imagenet2012_config.yaml # parameter configuration
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├── resnet50_imagenet2012_GPU_config.yaml # parameter configuration
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├── resnet50_imagenet2012_GPU_Thor_config.yaml # parameter configuration
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├── resnet101_imagenet2012_config.yaml # parameter configuration
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├── se-resnet50_imagenet2012_config.yaml # parameter configuration
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├── export.py # export model for inference
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@ -213,9 +213,10 @@ bash run_eval_gpu.sh [DATASET_PATH] [CHECKPOINT_PATH] [CONFIG_PATH]
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├── resnet18_imagenet2012_config.yaml # 参数配置
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├── resnet34_imagenet2012_config.yaml # 参数配置
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├── resnet50_cifar10_config.yaml # 参数配置
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├── resnet50_imagenet2012_Ascend_config.yaml # 参数配置
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├── resnet50_imagenet2012_Acc_config.yaml # 参数配置
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├── resnet50_imagenet2012_Ascend_Thor_config.yaml # 参数配置
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├── resnet50_imagenet2012_config.yaml # 参数配置
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├── resnet50_imagenet2012_GPU_config.yaml # 参数配置
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├── resnet50_imagenet2012_GPU_Thor_config.yaml # 参数配置
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├── resnet101_imagenet2012_config.yaml # 参数配置
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├── se-resnet50_imagenet2012_config.yaml # 参数配置
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├── eval.py # 评估网络
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@ -16,7 +16,7 @@ checkpoint_file_path: ""
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# ==============================================================================
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# Training options
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optimizer: "Momentum"
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optimizer: "Thor"
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infer_label: ""
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class_num: 1001
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batch_size: 32
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@ -16,7 +16,7 @@ checkpoint_file_path: ""
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# ==============================================================================
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# Training options
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optimizer: "Momentum"
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optimizer: "Thor"
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infer_label: ""
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class_num: 1001
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batch_size: 32
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