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[nvfp4_training] Optimize CuteDSL kernels for NVFP4 training
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#14360:
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Add generalized int1-int8 weight-only MPS quantization with simdgroup GEMM
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Add generalized int1-int8 weight-only MPS quantization with simdgroup GEMM
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[nvfp4_training] Optimize CuteDSL kernels for NVFP4 training
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Warn when Int4WeightOnlyConfig uses the PLAIN packing format
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Fix cvt_packfloat compatibility with nvidia-cutlass-dsl 4.6.0+ (#4766)
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Fix cvt_packfloat compatibility with nvidia-cutlass-dsl 4.6.0+
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Honor range-learned scales in the tied embedding quantization path (#…
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Add opt-in KleidiAI support to BUCK (#4828)
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Fold away num_batches_tracked when the +1 is a lifted constant (#4834)
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[Draft][xpu] Route per-block FP8 GEMM through torch._scaled_mm on XPU
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Honor range-learned scales in the tied embedding quantization path (#4863)
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Remove Float8 allow-in-graph custom autograd wrappers (#4840) (#4840)
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Honor range-learned scales in the tied embedding quantization path (#4863)
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Honor range-learned scales in the tied embedding quantization path (#4863)
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Add core support for static Range Quantization (SRQ) and sub-byte embedding optimizations
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Add MoE-safe Int4PlainInt32Tensor op coverage and harden backend/index semantics
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Fix MXFP8 quantize failing when it is the first CUDA call on a thread…
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