Support mask_filter_value attribute in DecoderMaskedMultiheadAttention (#15158)

docs/ContribOperators.md

@@ -1126,6 +1126,8 @@ This version of the operator has been available since version 1 of the 'com.micr
 #### Attributes
 
 <dl>
+<dt><tt>mask_filter_value</tt> : float</dt>
+<dd>The value to be filled in the attention mask. Default value is -10000.0f</dd>
 <dt><tt>num_heads</tt> : int (required)</dt>
 <dd>Number of attention heads</dd>
 <dt><tt>past_present_share_buffer</tt> : int</dt>

onnxruntime/core/graph/contrib_ops/bert_defs.cc

@@ -473,6 +473,10 @@ ONNX_MS_OPERATOR_SET_SCHEMA(
               "Custom scale will be used if specified. Default value is 1/sqrt(head_size)",
               AttributeProto::FLOAT,
               OPTIONAL_VALUE)
+        .Attr("mask_filter_value",
+              "The value to be filled in the attention mask. Default value is -10000.0f",
+              AttributeProto::FLOAT,
+              OPTIONAL_VALUE)
         .Input(0,
                "input",
                "Input tensor with shape (batch_size, 1, input_hidden_size)",
@@ -571,7 +575,7 @@ ONNX_MS_OPERATOR_SET_SCHEMA(
         .Input(1,
                "key",
                "Key with shape (batch_size, kv_sequence_length, hidden_size), or packed KV with shape (batch_size, kv_sequence_length, num_heads, 2, head_size), "
-                "or past_key with shape (batch_size, num_heads, kv_sequence_length, head_size)",
+               "or past_key with shape (batch_size, num_heads, kv_sequence_length, head_size)",
                "T",
                OpSchema::Optional)
         .Input(2,

onnxruntime/python/tools/transformers/convert_generation.py

@@ -1106,6 +1106,7 @@ def update_decoder_subgraph_use_decoder_masked_multihead_attention(
             "past_present_share_buffer",
             "num_heads",
             "scale",
+            "mask_filter_value",
             "domain",
         ]