jainapurva added a commit to jainapurva/pytorch that referenced this pull request Aug 5, 2024 Grouped Query Attention (pytorch#132689) … 2f9dcfd Contributor facebook-github-bot commented Aug 6, 2024 This pull request was exported from Phabricator. Differential Revision: D60772086jain...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Grouped Query Attention · pytorch/pytorch@ff1ee78
jainapurva opened #128898 grouped-query-attention Status Failure Total duration 2h 20m 27s Artifacts 1 pull.yml on: pull_request linux-jammy-py3.8-gcc11 / build 15m 23s linux-focal-cpu-py3.10-gcc9-bazel-test / filter 18s linux-focal-cuda11.8-py3.10-gcc9 / build 26m 17s li...
importtorchfromgrouped_query_attention_pytorch.attentionimportscaled_dot_product_gqa# shapes: (batch_size, seq_len, num_heads, head_dim)query=torch.randn(1,256,8,64,device="cuda",dtype=torch.float16)key=torch.randn(1,128,2,64,device="cuda",dtype=torch.float16)value=torch.randn(1,128,2...
(Unofficial) PyTorch implementation of grouped-query attention (GQA) from "GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints" (https://arxiv.org/pdf/2305.13245.pdf) - Forks · fkodom/grouped-query-attention-pytorch
### Grouped Query-Key L2 Normalization This paper proposes to l2 normalize the queries and keys along the head dimension before the dot product (cosine similarity), with the additional change of the scale being learned rather than static. The normalization prevents the attention operation from ...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Grouped Query Attention · pytorch/pytorch@696e83a
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Grouped Query Attention · pytorch/pytorch@527f104
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Grouped Query Attention · pytorch/pytorch@81a5a7a
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Grouped Query Attention · pytorch/pytorch@679cdf6