fix f16 for attention, enable slice and flatten for more types (#19262)

Author: guschmue

js/web/lib/wasm/jsep/webgpu/ops/attention.ts

@@ -297,7 +297,7 @@ export const computeInPlaceSoftmax = (context: ComputeContext, input: TensorView
 
     if (sum == 0) {
       for (var i: u32 = 0; i < uniforms.elements_per_wg && i + localOffset < uniforms.d_comp; i++) {
-        x[offset + i] = ${fillVector('f32', components, 'uniforms.d_inv')};
+        x[offset + i] = ${fillVector(elemValueType, components, 'uniforms.d_inv')};
       }
     } else {
       for (var i: u32 = 0; i < uniforms.elements_per_wg && i + localOffset < uniforms.d_comp; i++) {

onnxruntime/core/providers/js/operators/flatten.cc

@@ -13,7 +13,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
     kJsExecutionProvider,
     (*KernelDefBuilder::Create())
         .Alias(0, 0)
-        .TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
+        .TypeConstraint("T", JsepSupportedFloatTypes()),
     Flatten);
 
 ONNX_OPERATOR_VERSIONED_KERNEL_EX(
@@ -23,7 +23,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
     kJsExecutionProvider,
     (*KernelDefBuilder::Create())
         .Alias(0, 0)
-        .TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
+        .TypeConstraint("T", JsepSupportedFloatTypes()),
     Flatten);
 
 ONNX_OPERATOR_VERSIONED_KERNEL_EX(
@@ -33,7 +33,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
     kJsExecutionProvider,
     (*KernelDefBuilder::Create())
         .Alias(0, 0)
-        .TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
+        .TypeConstraint("T", JsepSupportedFloatTypes()),
     Flatten);
 
 ONNX_OPERATOR_KERNEL_EX(
@@ -43,7 +43,7 @@ ONNX_OPERATOR_KERNEL_EX(
     kJsExecutionProvider,
     (*KernelDefBuilder::Create())
         .Alias(0, 0)
-        .TypeConstraint("T", DataTypeImpl::GetTensorType<float>()),
+        .TypeConstraint("T", JsepSupportedFloatTypes()),
     Flatten);
 
 }  // namespace js

onnxruntime/core/providers/js/operators/slice.cc

@@ -12,8 +12,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
     1, 9,
     kJsExecutionProvider,
     (*KernelDefBuilder::Create())
-        .TypeConstraint("T", {DataTypeImpl::GetTensorType<float>(),
-                              DataTypeImpl::GetTensorType<int32_t>()}),
+        .TypeConstraint("T", JsepSupportedDataTypes()),
     Slice_1);
 
 ONNX_OPERATOR_VERSIONED_KERNEL_EX(
@@ -26,8 +25,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
         .InputMemoryType(OrtMemTypeCPU, 2)
         .InputMemoryType(OrtMemTypeCPU, 3)
         .InputMemoryType(OrtMemTypeCPU, 4)
-        .TypeConstraint("T", {DataTypeImpl::GetTensorType<float>(),
-                              DataTypeImpl::GetTensorType<int32_t>()}),
+        .TypeConstraint("T", JsepSupportedDataTypes()),
     Slice);
 
 ONNX_OPERATOR_VERSIONED_KERNEL_EX(
@@ -40,8 +38,7 @@ ONNX_OPERATOR_VERSIONED_KERNEL_EX(
         .InputMemoryType(OrtMemTypeCPU, 2)
         .InputMemoryType(OrtMemTypeCPU, 3)
         .InputMemoryType(OrtMemTypeCPU, 4)
-        .TypeConstraint("T", {DataTypeImpl::GetTensorType<float>(),
-                              DataTypeImpl::GetTensorType<int32_t>()}),
+        .TypeConstraint("T", JsepSupportedDataTypes()),
     Slice);
 
 ONNX_OPERATOR_KERNEL_EX(
@@ -54,8 +51,7 @@ ONNX_OPERATOR_KERNEL_EX(
         .InputMemoryType(OrtMemTypeCPU, 2)
         .InputMemoryType(OrtMemTypeCPU, 3)
         .InputMemoryType(OrtMemTypeCPU, 4)
-        .TypeConstraint("T", {DataTypeImpl::GetTensorType<float>(),
-                              DataTypeImpl::GetTensorType<int32_t>()}),
+        .TypeConstraint("T", JsepSupportedDataTypes()),
     Slice);
 
 }  // namespace js