[QST] 2D Convolution for NCHW Row-Major images, kernels and output
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- Dominant language
- C++
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Description
I am trying to implement 2D Convolutions for NCHW Row-Major images, kernels and outputs. According to the documentation for implicit_gemm_convolution only NHWC inputs are supported with a mix of row-major and column-major inputs. What is the best way to compute a 2D convolution given my layout?
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Research direction
The issue names implicit_gemm_convolution and NCHW row-major image, kernel, and output layouts. Start with the implicit_gemm_convolution documentation and its stated layout constraints. Done should be a confirmed supported computation path or a clearly scoped missing-layout support request.
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Assessment
- Tech stack
- cpp
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100