[BUG] nvpf4 tensor creation looks incorrect
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Description
Which component has the problem?
CuTe DSL
Bug Report
Describe the bug
The functions used for creating tensors , create_tensors_abc_for_all_groups () and create_tensor_and_stride () , in cutlass/examples/python/CuTeDSL/blackwell/grouped_blockscaled_gemm.py seem incorrect for cutlass.Float4E2M1FN and torch.float4_e2m1fn_x2. The 4 bit packing does not appear to have been coded.
Steps/Code to reproduce bug
See above functions
Expected behavior
k//2 vs k , for example in create_tensor_and_stride(l, m, k, a_major == "m", ab_dtype)
Environment details (please complete the following information):
cutlass master
Additional context
N/A
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
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- Open a pull request that references the issue number.
Research direction
Read cutlass/examples/python/CuTeDSL/blackwell/grouped_blockscaled_gemm.py, focusing first on create_tensors_abc_for_all_groups() and create_tensor_and_stride(). Reproduce the tensor creation with cutlass.Float4E2M1FN and torch.float4_e2m1fn_x2, then verify that 4-bit packing is reflected in the dimensions and strides, including k//2 rather than k where expected.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- hpc
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 55/100