onnxruntime

[CUDA] Attention kernel provider option (#21344)

### Description
* Add a cuda provider option `sdpa_kernel` to choose which attention kernel to run for testing purpose. 
* Allow dump which attention kernel is used per node.
* Reserve  a flag for cudnn flash attention which will be added soon.

#### CUDA provider option sdpa_kernel
Instead of setting environment variable, we also support setting it in
provider option. Note that the setting is global per session. That could
help performance testing of each kernel.

#### Attention Kernel Debug Info
Set an environment variable `ORT_ENABLE_ATTENTION_KERNEL_DEBUG_INFO=1`,
and ORT will print sdpa kernel used in each node:

For example 
```
ORT_ENABLE_ATTENTION_KERNEL_DEBUG_INFO=1 ./onnxruntime_test_all --gtest_filter=MultiHeadAttentionTest*
```
It will show debug information of kernel used in testing:
```
[ RUN      ] MultiHeadAttentionTest.SelfAttention_Batch2_HeadSize32_NoBias_NoMask_PackedQKV
AttentionKernelOptions: FLASH_ATTENTION=0 EFFICIENT_ATTENTION=0 TRT_FUSED_ATTENTION=1 CUDNN_FLASH_ATTENTION=0 TRT_FLASH_ATTENTION=1 TRT_CROSS_ATTENTION=0 TRT_CAUSAL_ATTENTION=0 MATH=1
Operator=MultiHeadAttention Node=node1 DataType=fp16 TRT_FUSED_ATTENTION=1
AttentionKernelOptions: FLASH_ATTENTION=0 EFFICIENT_ATTENTION=1 TRT_FUSED_ATTENTION=0 CUDNN_FLASH_ATTENTION=0 TRT_FLASH_ATTENTION=0 TRT_CROSS_ATTENTION=0 TRT_CAUSAL_ATTENTION=0 MATH=1
Operator=MultiHeadAttention Node=node1 DataType=fp16 EFFICIENT_ATTENTION=1
```
In this test case, the debug info shows that one session uses trt fused
attention and another session use efficient attention.