[API change] Scaled_dot_product_flash_attention_attributes, Scaled_dot_product_flash_attention_backward_attributes now accepts K, V tensors instead of K-transpose and V-transpose. This is a deviation from the backend API. This change is made based on multiple customer feedback.
[New API] Add tensor_like python API which accepts a DLPack-compstible tensor. This simplifies the cudnn tensor creation.
[New Feature] Setting CUDNN_FRONTEND_ATTN_DP_WORKSPACE_LIMIT environment variable allows to choose between different optimized cudnn backend kernels. See docs/operations/mha for more details.
[New Feature] Add RMSNorm and InstanceNorm forward and backward implementations.
[New Feature] Add alibi, padding, layout support for attention bprop node.
[New Feature] Introduce python bindings for plans. Allows validate graph, filter plans.
[Bug Fix] Fix relative includes of filenames in cudnn_frontend headers. This resolves compilation issues in certain toolchains
[Bug Fix] Fix Segfault when dropout was set for some scaled dot product flash attention nodes.
[New samples] Add new samples for apply_rope, layernorm forward and backward, rmsnorm forward and backward