DecoderMaskedMultiHeadAttention CPU kernel. (#22292)

### Description
DecoderMaskedMultiHeadAttention CPU kernel.

docs/ContribOperators.md

@@ -1167,17 +1167,17 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dt><tt>mask_index</tt> (optional) : M</dt>
 <dd>Mask values of shape (batch_size, total_sequence_length) or (batch_size, kv_sequence_length)</dd>
 <dt><tt>attention_bias</tt> (optional) : T</dt>
-<dd>additional add to QxK' with shape (batch_size, num_heads, sequence_length, total_sequence_length)</dd>
+<dd>additional add to QxK' with shape (batch_size or 1, num_heads or 1, sequence_length, total_sequence_length)</dd>
 <dt><tt>past_key</tt> (optional) : T</dt>
 <dd>past state for key with shape (batch_size, num_heads, past_sequence_length, head_size) for self attentionWhen past_present_share_buffer is set, its shape is (batch_size, num_heads, max_sequence_length, head_size). The keys buffer is re-ordered in such a way that its virtual sub-tensor of shape (batch_size, num_heads, max_sequence_length, head_size) which may be perceived as being of shape (batch_size, num_heads, max_sequence_length, head_size / x, x) is reordered to become (batch_size, num_heads, head_size / x, max_sequence_length, x) where `x = 16 / sizeof(T)`.</dd>
 <dt><tt>past_value</tt> (optional) : T</dt>
 <dd>past state for value with shape (batch_size, num_heads, past_sequence_length, head_size) for self attentionWhen past_present_share_buffer is set, its shape is (batch_size, num_heads, max_sequence_length, head_size). </dd>
 <dt><tt>past_sequence_length</tt> (optional) : M</dt>
 <dd>When past_present_share_buffer is used, it is required to specify past_sequence_length (could be 0).Cross Attention doesn't need this input.</dd>
 <dt><tt>beam_width</tt> (optional) : M</dt>
-<dd>The beam width that is being used while decoding.If not provided, the beam width will be assumed to be 1.</dd>
+<dd>The beam width that is being used while decoding. If not provided, the beam width will be assumed to be 1.</dd>
 <dt><tt>cache_indirection</tt> (optional) : M</dt>
-<dd>A buffer of shape [batch_size, beam_width, max_output_length] where an [i, j, k] entry specifieswhich beam the 'k' th token came from for the 'j' th beam for batch 'i' in the current iteration</dd>
+<dd>A buffer of shape [batch_size, beam_width, max_output_length] where an `[i, j, k]` entry specifies which beam the `k`-th token came from for the `j`-th beam for batch `i` in the current iteration</dd>
 <dt><tt>bias</tt> (optional) : T</dt>
 <dd>Bias tensor with shape (hidden_size + hidden_size + v_hidden_size) from input projection</dd>
 </dl>
@@ -1192,7 +1192,7 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dt><tt>present_value</tt> (optional) : T</dt>
 <dd>present state for value with shape (batch_size, num_heads, total_sequence_length, head_size). If past_present_share_buffer is set, its shape is (batch_size, num_heads, max_sequence_length, head_size), while effective_seq_length = (past_sequence_length + kv_sequence_length).</dd>
 <dt><tt>qk</tt> (optional) : V</dt>
-<dd>normalized Q * K, of shape (batch_size, num_heads, 1, head_size). </dd>
+<dd>normalized Q * K, of shape (batch_size, num_heads, 1, total_sequence_length). </dd>
 </dl>
 
 #### Type Constraints
@@ -1261,9 +1261,9 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dt><tt>past_sequence_length</tt> : M</dt>
 <dd>When past_present_share_buffer is used, it is required to specify past_sequence_length (could be 0).</dd>
 <dt><tt>beam_width</tt> (optional) : M</dt>
-<dd>The beam width that is being used while decoding.If not provided, the beam width will be assumed to be 1.</dd>
+<dd>The beam width that is being used while decoding. If not provided, the beam width will be assumed to be 1.</dd>
 <dt><tt>cache_indirection</tt> (optional) : M</dt>
-<dd>A buffer of shape [batch_size, beam_width, max_output_length] where an [i, j, k] entry specifieswhich beam the 'k' th token came from for the 'j' th beam for batch 'i' in the current iteration</dd>
+<dd>A buffer of shape [batch_size, beam_width, max_output_length] where an `[i, j, k]` entry specifies which beam the `k`-th token came from for the `j`-th beam for batch `i` in the current iteration</dd>
 </dl>
 
 #### Outputs

docs/OperatorKernels.md

@@ -468,6 +468,7 @@ Do not modify directly.*
 |CDist|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T**|1+|**T** = tensor(double), tensor(float)|
 |ConvTransposeWithDynamicPads|*in* X:**T**<br> *in* W:**T**<br> *in* Pads:**tensor(int64)**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float)|
 |CropAndResize|*in* X:**T1**<br> *in* rois:**T1**<br> *in* batch_indices:**T2**<br> *in* crop_size:**T2**<br> *out* Y:**T1**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int32)|
+|DecoderMaskedMultiHeadAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* mask_index:**M**<br> *in* attention_bias:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *in* past_sequence_length:**M**<br> *in* beam_width:**M**<br> *in* cache_indirection:**M**<br> *in* bias:**T**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**<br> *out* qk:**V**|1+|**T** = tensor(float)|
 |DequantizeLinear|*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**|1+|**T1** = tensor(int16), tensor(int32), tensor(int4), tensor(int8), tensor(uint16), tensor(uint4), tensor(uint8)<br/> **T2** = tensor(float)|
 |DynamicQuantizeLSTM|*in* X:**T**<br> *in* W:**T2**<br> *in* R:**T2**<br> *in* B:**T**<br> *in* sequence_lens:**T1**<br> *in* initial_h:**T**<br> *in* initial_c:**T**<br> *in* P:**T**<br> *in* W_scale:**T**<br> *in* W_zero_point:**T2**<br> *in* R_scale:**T**<br> *in* R_zero_point:**T2**<br> *out* Y:**T**<br> *out* Y_h:**T**<br> *out* Y_c:**T**|1+|**T** = tensor(float)<br/> **T1** = tensor(int32)<br/> **T2** = tensor(int8), tensor(uint8)|
 |DynamicQuantizeMatMul|*in* A:**T1**<br> *in* B:**T2**<br> *in* b_scale:**T1**<br> *in* b_zero_point:**T2**<br> *in* bias:**T1**<br> *out* Y:**T1**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int8), tensor(uint8)|

onnxruntime/contrib_ops/cpu/bert/attention_common.h

@@ -79,6 +79,45 @@ struct AttentionParameters {
   AttentionQkvFormat qkv_format;
 };
 
+struct DecoderMaskedMultiHeadAttentionParams : AttentionParameters {
+  int beam_width = 1;
+
+  // Only NeoX style rotary embedding is supported
+  int rotary_embedding_dim = 0;
+  int t_step = 0;
+
+  // Whether to use multihead attention(excludes matmul and bias)
+  bool is_mha = false;
+  bool is_cross_attention = false;
+  bool is_packed_qkv = false;
+
+  // Useful to better use global memory bandwidth on certain CUDA architectures.
+  // Turned off by default for now until we fully understand performance implications
+  // for all types of workloads.
+  // Can be turned on by appropriate environment variable (see attention_common.h).
+  bool kv_data_in_flight = false;
+
+  void* q = nullptr;
+  void* q_bias = nullptr;
+
+  void* k = nullptr;
+  void* k_bias = nullptr;
+
+  void* v = nullptr;
+  void* v_bias = nullptr;
+
+  void* attention_bias = nullptr;
+
+  void* k_cache = nullptr;
+  void* v_cache = nullptr;
+
+  void* out = nullptr;
+  void* out_qk = nullptr;
+
+  const int32_t* cache_indir = nullptr;
+  const int32_t* mask = nullptr;  // [B, total_sequence_length]
+};
+
 // Parameters deduced from node attributes and inputs/outputs.
 struct PackedAttentionParameters {
   int batch_size;