cudnn frontend v1.13 release notes

cudnn frontend v1.13 is the preferred cudnn frontend version for cudnn version 9.11.0 and above.

New API

Introduces device descriptor, which allows for device-less compilation of cudnn graph on a target GPU. See newly added sample and documentation.

Introduced generate_stats as a replacement for is_inference, to improve clarity. When generate_stats is true, the output will contain the stats tensor. When migrating from is_inference (which is now deprecated), note that generate_stats has the opposite meaning, so pass it the negation of the bool that was passed to is_inference.
Improved support checks for left and right diagonal bands in conjunction with the diagonal alignment.
Improved error handling for large head dimension (d > 128) in sdpa bprop.

Added support for fused Layernorm with Relu and samples for Layernorm with relu bitmask dump

Published improved SDPA training benchmarks for fp8 and fp16/bf16 graph patterns.
Enable int4 Weight only Quantization for matmul. See example
Allow block scale dequantize (required for low precision matmul) to take 2-D scale factor.
Allow reductions to accept deterministic as a attribute.
Added pybinds for block scale dequantize.

Fixed the sliding window attn_score_modifier function allowing it to set true negative infinity.