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Generating PyTorch Transformer Masks | James D. McCaffrey
pytorch 中x.masked_fill(mask, value)用value填充x中对应mask位置处为True的元素-CSDN博客
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Performance gains w/ nanoGPT using SDPA Custom Kernel - performance - PyTorch Dev Discussions
PyTorch Release v1.2.0 | Exxact Blog
Accelerating Large Language Models with Accelerated Transformers | PyTorch
Transformer — A detailed explanation from perspectives of tensor shapes and PyTorch implementation. | by Huili Yu | MLearning.ai | Jan, 2024 | Medium
torch中的mask：masked_fill, masked_select, masked_scatter - YIYUYI - 博客园
masked_fill_ (and possibly others) produces a different output than masked_fill on cpu · Issue #39639 · pytorch/pytorch · GitHub
jit] Support tracing of Tensor.masked_fill_() · Issue #11555 · pytorch/pytorch · GitHub
An Example Of Using The PyTorch masked_fill() Function | James D. McCaffrey
![P] Modifying open-sourced matrix multiplication kernel : r/MachineLearning](https://raw.githubusercontent.com/DeMoriarty/custom_matmul_kernels/main/imgs/min_bmm_A%5B1%2CN%2C64%5D%20B%5B1%2C64%2CN%5D.png "P] Modifying open-sourced matrix multiplication kernel : r/MachineLearning")
P] Modifying open-sourced matrix multiplication kernel : r/MachineLearning
Can torch.Tensor have different precision element-wisely? - PyTorch Forums
Using F.scaled_dot_product_attention gives the error - PyTorch Forums
An Example Of Using The PyTorch masked_fill() Function | James D. McCaffrey
torch.masked — PyTorch 2.2 documentation
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Understanding and Coding Self-Attention, Multi-Head Attention, Cross-Attention, and Causal-Attention in LLMs
python - pytorch masked_fill: why can't I mask all zeros? - Stack Overflow
Accelerating Large Language Models with Accelerated Transformers | PyTorch
Pytorch for Beginners: #8 | Understanding Masking in Pytorch - YouTube
ONNX] support masked_select masked_fill and masked_scatter · Issue #26034 · pytorch/pytorch · GitHub
masked_fill` with `FloatTensor` mask will never mask but fails silently. · Issue #89320 · pytorch/pytorch · GitHub
primtorch] `torch.masked_fill` ref does not match eager's device promotion semantics. · Issue #81018 · pytorch/pytorch · GitHub
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