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  ## Resnet50-v1.5
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- - Origin : https://github.com/mlcommons/inference/tree/master/vision/classification_and_detection
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- - Article : https://arxiv.org/abs/1512.03385
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- - Input size : \[N, 3, 224, 224\]
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- - Format : NCHW
 
 
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  - ONNX attributes:
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  - opset : 11
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  - Operators: 233 (11 types)
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  - ReLU: 49
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  - ReduceMean: 1
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  - Softmax: 1
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- - Squeeze: 1
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- - Note : https://catalog.ngc.nvidia.com/orgs/nvidia/resources/resnet_50_v1_5_for_pytorch
 
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  ## Resnet50-v1.5
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+ - Origin: https://github.com/mlcommons/inference/tree/master/vision/classification_and_detection
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+ - Note : https://catalog.ngc.nvidia.com/orgs/nvidia/resources/resnet_50_v1_5_for_pytorch
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+ - Article: https://arxiv.org/abs/1512.03385
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+ - Input:
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+ - size: \[N, 3, 224, 224\]
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+ - format : NCHW
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  - ONNX attributes:
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  - opset : 11
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  - Operators: 233 (11 types)
 
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  - ReLU: 49
25
  - ReduceMean: 1
26
  - Softmax: 1
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+ - Squeeze: 1