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ConvNeXt

Image Classification
ONNX
Classification
arxiv:<2201.03545>
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+ ---
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+ datasets:
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+ - timm/mini-imagenet
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+ metrics:
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+ - accuracy
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+ tags:
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+ - Classification
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+ - arxiv:<2201.03545> # A ConvNet for the 2020s
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+ pipeline_tag: image-classification
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+ Operators:
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+ - Add: 12
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+ - Conv2D: 40
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+ - Flatten: 1
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+ - Gemme: 1
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+ - ReLu: 12
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+
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+ features:
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+ - name: "ONNX import"
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+ tested_in_CI: true
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+ - name: "ONNX export"
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+ tested_in_CI: true
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+ - name: "Backend CPU"
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+ tested_in_CI: true
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+ - name: "Export CPP"
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+ tested_in_CI: true
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+
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+
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+ Source: PyTorch
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+ Input:
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+ - size:
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+ - [N, 3, 300, 300]
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+ - format: NCHW
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+ - preprocessing:
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+ - Resize
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+ - Normalise
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+ Output:
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+ - size:
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+ - [N*100]
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+
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+ ---
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+
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+ ---
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+ datasets:
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+ - timm/mini-imagenet
45
+ metrics:
46
+ - accuracy
47
+ tags:
48
+ - Classification
49
+ - arxiv:<2201.03545> # A ConvNet for the 2020s
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+ pipeline_tag: image-classification
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+ Operators:
52
+ - Add: 12
53
+ - Conv2D: 40
54
+ - Flatten: 1
55
+ - Gemme: 1
56
+ - ReLu: 12
57
+
58
+ features:
59
+ - name: "ONNX import"
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+ tested_in_CI: true
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+ - name: "Export CPP"
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+ tested_in_CI: true
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+
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+
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+ Source: PyTorch
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+ Input:
67
+ - size:
68
+ - [N, 3, 300, 300]
69
+ - format: NCHW
70
+ - preprocessing:
71
+ - Resize
72
+ - Normalise
73
+ Output:
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+ - size:
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+ - [N*100]
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+
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+ ---
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+