Resnet50-v1.5

• Origin: https://github.com/mlcommons/inference/tree/master/vision/classification_and_detection
• Note : https://catalog.ngc.nvidia.com/orgs/nvidia/resources/resnet_50_v1_5_for_pytorch

Model

• ONNX attributes:
  • opset : 11
  • Operators: 233 (11 types)
    • Add: 17
    • ArgMax: 1
    • Conv2D: 36
    • MatMul: 1
    • PaddedConv2D: 17
    • PaddedMaxPooling2D: 1
    • Producer: 108
    • ReLU: 49
    • ReduceMean: 1
    • Softmax: 1
    • Squeeze: 1

Aidge support

Note: We tested this network for the following features. If you encounter any error please open an issue. Features not tested in CI may not be functional.

Feature	Tested in CI
ONNX import	✔
Backend CPU	✔

ImageNet1k

• Input:
  • size: [N, 3, 224, 224]
  • format : NCHW
• Output
  • size: [N, 1000]