[ORT 1.17.0 Release] Cherry-pick Final Round (#19327)

### Description
<!-- Describe your changes. -->

Cherry-pick Final Round


### Motivation and Context
<!-- - Why is this change required? What problem does it solve?
- If it fixes an open issue, please link to the issue here. -->

---------

Co-authored-by: Adrian Lizarraga <[email protected]>
Co-authored-by: Changming Sun <[email protected]>
Co-authored-by: Chi Lo <[email protected]>
Co-authored-by: rachguo <[email protected]>
Co-authored-by: Edward Chen <[email protected]>
Co-authored-by: kunal-vaishnavi <[email protected]>
Co-authored-by: aciddelgado <[email protected]>
Co-authored-by: Yufeng Li <[email protected]>

Author: 9 people

Diff for: .pipelines/OneBranch.Nuget-WindowsAI-Pipeline.Official.yml

@@ -29,6 +29,8 @@ extends:
     git:
       submodules: false
     globalSdl: # https://aka.ms/obpipelines/sdl
+      asyncSdl:
+        enabled: false
       tsa:
         enabled: true
       prefast:

Diff for: ThirdPartyNotices.txt

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Diff for: docs/ContribOperators.md

@@ -2398,24 +2398,28 @@ This version of the operator has been available since version 1 of the 'com.micr
 #### Attributes
 
 <dl>
+<dt><tt>do_rotary</tt> : int</dt>
+<dd>Whether to use rotary position embedding. Default value is 0.</dd>
 <dt><tt>kv_num_heads</tt> : int (required)</dt>
 <dd>Number of attention heads for k and v</dd>
 <dt><tt>local_window_size</tt> : int</dt>
 <dd>left_window_size for local attention (like Mistral). Default value is -1 meaning unused.</dd>
 <dt><tt>num_heads</tt> : int (required)</dt>
 <dd>Number of attention heads for q</dd>
+<dt><tt>rotary_interleaved</tt> : int</dt>
+<dd>Rotate using interleaved pattern. Default value is 0 (False).</dd>
 <dt><tt>scale</tt> : float</dt>
 <dd>Custom scale will be used if specified. Default value is 1/sqrt(head_size)</dd>
 </dl>
 
-#### Inputs
+#### Inputs (7 - 9)
 
 <dl>
 <dt><tt>query</tt> : T</dt>
-<dd>Query with shape (batch_size, sequence_length, hidden_size)</dd>
-<dt><tt>key</tt> : T</dt>
+<dd>Query with shape (batch_size, sequence_length, hidden_size), or packed QKV with shape(batch_size, sequence_length, d) where d is (num_heads * head_size + 2 * kv_num_heads * head_size).</dd>
+<dt><tt>key</tt> (optional) : T</dt>
 <dd>Key with shape (batch_size, kv_sequence_length, kv_hidden_size) </dd>
-<dt><tt>value</tt> : T</dt>
+<dt><tt>value</tt> (optional) : T</dt>
 <dd>Value with shape (batch_size, kv_sequence_length, kv_hidden_size)</dd>
 <dt><tt>past_key</tt> (optional) : T</dt>
 <dd>past state key with support for format BNSH. When past_key uses same tensor as present_key(k-v cache), it is of length max_sequence_length... otherwise of length past_sequence_length.</dd>
@@ -2425,6 +2429,10 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dd>1d Tensor of shape (batch_size). Indicates past sequence lengths for token generation case.</dd>
 <dt><tt>total_sequence_length</tt> : M</dt>
 <dd>Scalar tensor of total sequence length (past + new).</dd>
+<dt><tt>cos_cache</tt> (optional) : T</dt>
+<dd>2D tensor with shape (max_sequence_length, head_size / 2).</dd>
+<dt><tt>sin_cache</tt> (optional) : T</dt>
+<dd>2D tensor with shape (max_sequence_length, head_size / 2).</dd>
 </dl>
 
 #### Outputs

Diff for: docs/OperatorKernels.md

@@ -843,7 +843,7 @@ Do not modify directly.*
 |GreedySearch|*in* input_ids:**I**<br> *in* max_length:**I**<br> *in* min_length:**I**<br> *in* repetition_penalty:**T**<br> *in* vocab_mask:**I**<br> *in* prefix_vocab_mask:**I**<br> *in* attention_mask:**I**<br> *out* sequences:**I**|1+|**T** = tensor(float), tensor(float16)|
 |GridSample|*in* X:**T1**<br> *in* Grid:**T1**<br> *out* Y:**T2**|1+|**T1** = tensor(float)<br/> **T2** = tensor(float)|
 |GroupNorm|*in* X:**T**<br> *in* gamma:**M**<br> *in* beta:**M**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
-|GroupQueryAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *in* seqlens_k:**M**<br> *in* total_sequence_length:**M**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(bfloat16), tensor(float16)|
+|GroupQueryAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *in* seqlens_k:**M**<br> *in* total_sequence_length:**M**<br> *in* cos_cache:**T**<br> *in* sin_cache:**T**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(bfloat16), tensor(float16)|
 |Inverse|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(float16)|
 |Irfft|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(double), tensor(float), tensor(float16)|
 |LongformerAttention|*in* input:**T**<br> *in* weight:**T**<br> *in* bias:**T**<br> *in* mask:**T**<br> *in* global_weight:**T**<br> *in* global_bias:**T**<br> *in* global:**G**<br> *out* output:**T**|1+|**T** = tensor(float), tensor(float16)|

Diff for: onnxruntime/contrib_ops/cpu/bert/attention_common.h

@@ -99,10 +99,15 @@ struct GroupQueryAttentionParameters {
   bool is_unidirectional;  // causal
   int local_window_size;
   bool kv_share_buffer;
+  bool is_packed_qkv;
   bool is_prompt;  // determines if seqlens_k is past or kv sequence length tensor
+  bool do_rotary;
+  bool rotary_interleaved;
   float scale;
   AttentionQkvFormat qkv_format;
   AttentionQkvFormat past_kv_format;
+  int zeros_count;
+  int* zero_ptr;
 };
 
 namespace attention {

Diff for: onnxruntime/contrib_ops/cuda/bert/decoder_masked_multihead_attention.cc

@@ -74,6 +74,7 @@ Status DecoderMaskedMultiHeadAttention<T1, T2>::ComputeInternal(OpKernelContext*
   parameters.kv_data_in_flight = ParseEnvironmentVariableWithDefault<bool>(
       attention::kDecoderMaskedAttentionLoadKVDataInFlight, false);
 
+  bool is_unidirectional = false;
   bool is_dmmha_packing = (key == nullptr && value == nullptr);
   ORT_RETURN_IF_ERROR(multihead_attention_helper::CheckInputs<Tensor>(query,
                                                                       key,
@@ -88,6 +89,7 @@ Status DecoderMaskedMultiHeadAttention<T1, T2>::ComputeInternal(OpKernelContext*
                                                                       num_heads_,
                                                                       mask_filter_value_,
                                                                       scale_,
+                                                                      is_unidirectional,
                                                                       past_present_share_buffer_,
                                                                       is_dmmha_packing,  // dmmha_packing
                                                                       device_prop.maxThreadsPerBlock));