[DML] MatrixMultiplyIntegerToFloat

docs/ContribOperators.md

@@ -2795,7 +2795,7 @@ This version of the operator has been available since version 1 of the 'com.micr
 <dd>Constrain input A data type to 8-bit integer tensor.</dd>
 <dt><tt>T2</tt> : tensor(int8), tensor(uint8)</dt>
 <dd>Constrain input B data type to 8-bit integer tensor.</dd>
-<dt><tt>T3</tt> : tensor(float)</dt>
+<dt><tt>T3</tt> : tensor(float), tensor(float16)</dt>
 <dd>Constrain input a_scale, b_scale and output Y data type as float tensor.</dd>
 </dl>
 

docs/OperatorKernels.md

@@ -1267,6 +1267,7 @@ Do not modify directly.*
 |FusedMatMulActivation|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
 |Gelu|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
 |GroupNorm|*in* X:**T**<br> *in* gamma:**M**<br> *in* beta:**M**<br> *out* Y:**T**|1+|**M** = tensor(float), tensor(float16)<br/> **T** = tensor(float), tensor(float16)|
+|MatMulIntegerToFloat|*in* A:**T1**<br> *in* B:**T2**<br> *in* a_scale:**T3**<br> *in* b_scale:**T3**<br> *in* a_zero_point:**T1**<br> *in* b_zero_point:**T2**<br> *in* bias:**T3**<br> *out* Y:**T3**|1+|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(float), tensor(float16)|
 |MultiHeadAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* bias:**T**<br> *in* key_padding_mask:**M**<br> *in* relative_position_bias:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(float), tensor(float16)|
 |NhwcConv|*in* X:**T**<br> *in* W:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
 |QLinearAdd|*in* A:**T**<br> *in* A_scale:**tensor(float)**<br> *in* A_zero_point:**T**<br> *in* B:**T**<br> *in* B_scale:**tensor(float)**<br> *in* B_zero_point:**T**<br> *in* C_scale:**tensor(float)**<br> *in* C_zero_point:**T**<br> *out* C:**T**|1+|**T** = tensor(int8), tensor(uint8)|

onnxruntime/core/graph/contrib_ops/quantization_defs.cc

@@ -434,7 +434,7 @@ ONNX_MS_OPERATOR_SET_SCHEMA(
         .Output(0, "Y", "Matrix multiply results from A * B", "T3")
         .TypeConstraint("T1", {"tensor(int8)", "tensor(uint8)"}, "Constrain input A data type to 8-bit integer tensor.")
         .TypeConstraint("T2", {"tensor(int8)", "tensor(uint8)"}, "Constrain input B data type to 8-bit integer tensor.")
-        .TypeConstraint("T3", {"tensor(float)"},
+        .TypeConstraint("T3", {"tensor(float)", "tensor(float16)"},
                         "Constrain input a_scale, b_scale and output Y data type as float tensor.")
         .TypeAndShapeInferenceFunction([](ONNX_NAMESPACE::InferenceContext& ctx) {
           propagateElemTypeFromInputToOutput(ctx, 2, 0);

onnxruntime/core/optimizer/graph_transformer_utils.cc

@@ -279,7 +279,8 @@ InlinedVector<std::unique_ptr<GraphTransformer>> GenerateTransformers(
                                                                                onnxruntime::kAclExecutionProvider,
                                                                                onnxruntime::kArmNNExecutionProvider,
                                                                                onnxruntime::kJsExecutionProvider};
-
+      const InlinedHashSet<std::string_view> cpu_dml_eps = {onnxruntime::kCpuExecutionProvider,
+                                                            onnxruntime::kDmlExecutionProvider};
 #ifdef MLAS_TARGET_AMD64_IX86
       const bool avx2_precision_mode =
           session_options.config_options.GetConfigOrDefault(kOrtSessionOptionsAvx2PrecisionMode, "0") == "1" && MlasPlatformU8S8Overflow();
@@ -297,7 +298,7 @@ InlinedVector<std::unique_ptr<GraphTransformer>> GenerateTransformers(
       }
 
       transformers.emplace_back(std::make_unique<GemmActivationFusion>(cpu_ep));
-      transformers.emplace_back(std::make_unique<MatMulIntegerToFloatFusion>(cpu_ep));
+      transformers.emplace_back(std::make_unique<MatMulIntegerToFloatFusion>(cpu_dml_eps));
       transformers.emplace_back(std::make_unique<DynamicQuantizeMatMulFusion>(cpu_ep));
 
       transformers.emplace_back(std::make_unique<ConvActivationFusion>(cpu_cuda_rocm_acl_armnn_js_eps));

onnxruntime/core/optimizer/matmul_integer_to_float.cc

@@ -31,6 +31,24 @@ static bool CheckBiasShape(const TensorShapeProto* bias_shape) {
   return bias_last_dim > 1;
 }
 
+bool HasElementDataType(const NodeArg& node_arg, int32_t data_type) {
+  if (!node_arg.Exists()) {
+    return false;
+  }
+
+  const auto* type_proto = node_arg.TypeAsProto();
+  if (!type_proto) {
+    return false;
+  }
+
+  int32_t actual_data_type;
+  if (!utils::TryGetElementDataType(*type_proto, actual_data_type)) {
+    return false;
+  }
+
+  return data_type == actual_data_type;
+}
+
 /**
 MatMulIntegerToFloatFusion will fuse subgraph like below into MatMulIntegerToFloat:
 
@@ -63,9 +81,10 @@ Status MatMulIntegerToFloatFusion::ApplyImpl(Graph& graph, bool& modified, int g
     auto& mul_node = *node_ptr;
 
     ORT_RETURN_IF_ERROR(Recurse(mul_node, modified, graph_level, logger));
-
+    const bool is_dml_ep = node_ptr->GetExecutionProviderType() == kDmlExecutionProvider;
     if (!graph_utils::IsSupportedOptypeVersionAndDomain(mul_node, "Mul", {7, 13, 14}) ||
-        !graph_utils::IsSupportedProvider(mul_node, GetCompatibleExecutionProviders())) {
+        !graph_utils::IsSupportedProvider(mul_node, GetCompatibleExecutionProviders()) ||
+        (!is_dml_ep && HasElementDataType(*mul_node.InputDefs()[0], ONNX_NAMESPACE::TensorProto_DataType_FLOAT16))) {
       continue;
     }
 

onnxruntime/core/providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/ApiTraits.h

@@ -879,6 +879,12 @@ struct OperatorDescTraits<DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_DESC>
     static constexpr DML_OPERATOR_TYPE Type = DML_OPERATOR_QUANTIZED_LINEAR_MATRIX_MULTIPLY;
 };
 
+template <>
+struct OperatorDescTraits<DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC>
+{
+    static constexpr DML_OPERATOR_TYPE Type = DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT;
+};
+
 template <>
 struct OperatorDescTraits<DML_CONVOLUTION_INTEGER_OPERATOR_DESC>
 {
@@ -1041,12 +1047,6 @@ struct OperatorDescTraits<DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC>
     static constexpr DML_OPERATOR_TYPE Type = DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING;
 };
 
-template <>
-struct OperatorDescTraits<DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC>
-{
-    static constexpr DML_OPERATOR_TYPE Type = DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT;
-};
-
 template <>
 struct OperatorDescTraits<DML_ACTIVATION_ELU_OPERATOR_DESC>
 {

onnxruntime/core/providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/DirectMLSchema.h

@@ -1885,6 +1885,25 @@ constexpr DML_OPERATOR_SCHEMA DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_SCHE
     DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_SCHEMA_FIELDS,
 };
 
+constexpr DML_SCHEMA_FIELD DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA_FIELDS[8] {
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "ATensor", false },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "AScaleTensor", false },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "AZeroPointTensor", true },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BTensor", false },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BScaleTensor", false },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BZeroPointTensor", true },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BiasTensor", true },
+    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_OUTPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputTensor", false },
+};
+
+constexpr DML_OPERATOR_SCHEMA DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA {
+    "DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT",
+    static_cast<DML_OPERATOR_TYPE>(DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT),
+    DML_SCHEMA_OPERATOR_SUPPORT_FLAG_NONE,
+    8,
+    DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA_FIELDS,
+};
+
 constexpr DML_SCHEMA_FIELD DML_CONVOLUTION_INTEGER_OPERATOR_SCHEMA_FIELDS[11] {
     DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputTensor", false },
     DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputZeroPointTensor", true },
@@ -2395,24 +2414,6 @@ constexpr DML_OPERATOR_SCHEMA DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHE
     DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA_FIELDS,
 };
 
-constexpr DML_SCHEMA_FIELD DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA_FIELDS[8] {
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "ATensor", false },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "AScaleTensor", false },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "AZeroPointTensor", true },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BTensor", false },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BScaleTensor", false },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BZeroPointTensor", true },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "BiasTensor", true },
-    DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_OUTPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputTensor", false },
-};
-
-constexpr DML_OPERATOR_SCHEMA DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA {
-    "DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT",
-    DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT,
-    DML_SCHEMA_OPERATOR_SUPPORT_FLAG_NONE,
-    8,
-    DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA_FIELDS,
-};
 constexpr DML_SCHEMA_FIELD DML_ACTIVATION_ELU_OPERATOR_SCHEMA_FIELDS[3] {
     DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_INPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "InputTensor", false },
     DML_SCHEMA_FIELD { DML_SCHEMA_FIELD_KIND_OUTPUT_TENSOR, DML_SCHEMA_FIELD_TYPE_TENSOR_DESC, "OutputTensor", false },

onnxruntime/core/providers/dml/DmlExecutionProvider/src/External/DirectMLHelpers/GeneratedSchemaHelpers.h

@@ -1139,6 +1139,19 @@ inline std::vector<OperatorField> GetFields(const DML_QUANTIZED_LINEAR_MATRIX_MU
         OperatorField(&DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_SCHEMA.Fields[8], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputTensor))),
     };
 }
+inline std::vector<OperatorField> GetFields(const DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC& desc)
+{
+    return {
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[0], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.ATensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[1], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.AScaleTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[2], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.AZeroPointTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[3], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[4], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BScaleTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[5], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BZeroPointTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[6], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BiasTensor))),
+        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[7], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputTensor))),
+    };
+}
 inline std::vector<OperatorField> GetFields(const DML_CONVOLUTION_INTEGER_OPERATOR_DESC& desc)
 {
     return {
@@ -1487,19 +1500,6 @@ inline std::vector<OperatorField> GetFields(const DML_QUANTIZED_LINEAR_AVERAGE_P
         OperatorField(&DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA.Fields[12], ToOperatorFieldType(static_cast<UINT>(desc.IncludePadding))),
     };
 }
-inline std::vector<OperatorField> GetFields(const DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC& desc)
-{
-    return {
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[0], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.ATensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[1], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.AScaleTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[2], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.AZeroPointTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[3], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[4], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BScaleTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[5], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BZeroPointTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[6], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.BiasTensor))),
-        OperatorField(&DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA.Fields[7], ToOperatorFieldType(static_cast<const DML_TENSOR_DESC*>(desc.OutputTensor))),
-    };
-}
 inline std::vector<OperatorField> GetFields(const DML_ACTIVATION_ELU_OPERATOR_DESC& desc)
 {
     return {
@@ -1829,6 +1829,7 @@ inline const DML_OPERATOR_SCHEMA& GetSchema(DML_OPERATOR_TYPE operatorType)
     case DML_OPERATOR_RESAMPLE1: return DML_RESAMPLE1_OPERATOR_SCHEMA;
     case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER: return DML_MATRIX_MULTIPLY_INTEGER_OPERATOR_SCHEMA;
     case DML_OPERATOR_QUANTIZED_LINEAR_MATRIX_MULTIPLY: return DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_SCHEMA;
+    case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT: return DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA;
     case DML_OPERATOR_CONVOLUTION_INTEGER: return DML_CONVOLUTION_INTEGER_OPERATOR_SCHEMA;
     case DML_OPERATOR_QUANTIZED_LINEAR_CONVOLUTION: return DML_QUANTIZED_LINEAR_CONVOLUTION_OPERATOR_SCHEMA;
     case DML_OPERATOR_ELEMENT_WISE_BIT_AND: return DML_ELEMENT_WISE_BIT_AND_OPERATOR_SCHEMA;
@@ -1856,7 +1857,6 @@ inline const DML_OPERATOR_SCHEMA& GetSchema(DML_OPERATOR_TYPE operatorType)
     case DML_OPERATOR_DIAGONAL_MATRIX1: return DML_DIAGONAL_MATRIX1_OPERATOR_SCHEMA;
     case DML_OPERATOR_MULTIHEAD_ATTENTION: return DML_MULTIHEAD_ATTENTION_OPERATOR_SCHEMA;
     case DML_OPERATOR_QUANTIZED_LINEAR_AVERAGE_POOLING: return DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA;
-    case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT: return DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA;
     case DML_OPERATOR_ACTIVATION_ELU: return DML_ACTIVATION_ELU_OPERATOR_SCHEMA;
     case DML_OPERATOR_ACTIVATION_CELU: return DML_ACTIVATION_CELU_OPERATOR_SCHEMA;
     case DML_OPERATOR_ACTIVATION_HARDMAX: return DML_ACTIVATION_HARDMAX_OPERATOR_SCHEMA;
@@ -2360,6 +2360,10 @@ inline AbstractOperatorDesc ConvertOperatorDesc(const DML_OPERATOR_DESC& opDesc)
         return AbstractOperatorDesc(
             &DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_SCHEMA,
             GetFields(*static_cast<const DML_QUANTIZED_LINEAR_MATRIX_MULTIPLY_OPERATOR_DESC*>(opDesc.Desc)));
+    case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT:
+        return AbstractOperatorDesc(
+            &DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA,
+            GetFields(*static_cast<const DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC*>(opDesc.Desc)));
     case DML_OPERATOR_CONVOLUTION_INTEGER:
         return AbstractOperatorDesc(
             &DML_CONVOLUTION_INTEGER_OPERATOR_SCHEMA,
@@ -2468,10 +2472,6 @@ inline AbstractOperatorDesc ConvertOperatorDesc(const DML_OPERATOR_DESC& opDesc)
         return AbstractOperatorDesc(
             &DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_SCHEMA,
             GetFields(*static_cast<const DML_QUANTIZED_LINEAR_AVERAGE_POOLING_OPERATOR_DESC*>(opDesc.Desc)));
-    case DML_OPERATOR_MATRIX_MULTIPLY_INTEGER_TO_FLOAT:
-        return AbstractOperatorDesc(
-            &DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_SCHEMA,
-            GetFields(*static_cast<const DML_MATRIX_MULTIPLY_INTEGER_TO_FLOAT_OPERATOR_DESC*>(opDesc.Desc)));
     case DML_OPERATOR_ACTIVATION_ELU:
         return AbstractOperatorDesc(
             &DML_ACTIVATION_ELU_OPERATOR_SCHEMA,