[WebGPU EP] Implements Gelu, BiasSplitGelu, and QuickGelu

onnxruntime/contrib_ops/webgpu/bert/bias_split_gelu.cc

@@ -0,0 +1,80 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "core/providers/webgpu/shader_helper.h"
+#include "core/providers/webgpu/webgpu_supported_types.h"
+#include "contrib_ops/webgpu/bert/bias_split_gelu.h"
+#include "contrib_ops/webgpu/webgpu_contrib_kernels.h"
+#include "core/providers/webgpu/webgpu_utils.h"
+#include "core/providers/webgpu/math/unary_elementwise_ops.h"
+
+namespace onnxruntime {
+namespace contrib {
+namespace webgpu {
+
+ONNX_OPERATOR_KERNEL_EX(
+    BiasSplitGelu,
+    kMSDomain,
+    1,
+    kWebGpuExecutionProvider,
+    (*KernelDefBuilder::Create())
+        .TypeConstraint("T", WebGpuSupportedFloatTypes()),
+    BiasSplitGelu);
+
+Status BiasSplitGeluProgram::GenerateShaderCode(ShaderHelper& shader) const {
+  const ShaderVariableHelper& input = shader.AddInput("input");
+  const ShaderVariableHelper& bias = shader.AddInput("bias");
+  const ShaderVariableHelper& output = shader.AddOutput("output");
+
+  shader.AdditionalImplementation() << ErfImpl;
+
+  shader.MainFunctionBody() << shader.GuardAgainstOutOfBoundsWorkgroupSizes("uniforms.output_size")
+                            << "const M_SQRT2: f32 = sqrt(2.0);\n"
+                            << "const halfChannels = uniforms.channels / 2u;\n"
+                            << "let biasIdx = global_idx % halfChannels;\n"
+                            << "let batchIndex = global_idx / halfChannels;\n"
+                            << "let inputOffset = biasIdx + batchIndex * halfChannels * 2;\n"
+                            << "let valueLeft = " << input.GetByOffset("inputOffset") << " + " << bias.GetByOffset("biasIdx") << ";\n"
+                            << "let valueRight = " << input.GetByOffset("inputOffset + halfChannels") << " + " << bias.GetByOffset("biasIdx + halfChannels") << ";\n"
+                            << "let geluRight = valueRight * 0.5 * (erf_v(valueRight / M_SQRT2) + 1);\n"
+                            << output.SetByOffset("global_idx", "valueLeft * geluRight");
+
+  return Status::OK();
+}
+
+Status BiasSplitGelu::ComputeInternal(onnxruntime::webgpu::ComputeContext& context) const {
+  const auto* input = context.Input(0);
+  const auto* bias = context.Input(1);
+
+  TensorShape input_shape = input->Shape();
+
+  if (input_shape.NumDimensions() != 3) {
+    return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "BiasSplitGelu input should have 3 dimensions.");
+  }
+
+  int64_t channels = input_shape[2];
+  int64_t components = GetMaxComponents(channels);
+  channels /= components;
+  input_shape[2] = channels / 2;  // for output shape calculation (N,S,D) -> (N,S,D/2)
+
+  TensorShape bias_shape = bias->Shape();
+  if (bias_shape.NumDimensions() != 1 || bias_shape[0] != channels) {
+    return ORT_MAKE_STATUS(ONNXRUNTIME, INVALID_ARGUMENT, "BiasSplitGelu bias should have 1 dimension with size equal to the number of channels.");
+  }
+
+  auto* output = context.Output(0, input_shape);
+  int64_t output_size = output->Shape().Size() / components;
+
+  BiasSplitGeluProgram program{};
+  program.AddInputs({{input, ProgramTensorMetadataDependency::TypeAndRank},
+                     {bias}})
+      .AddOutput({output})
+      .SetDispatchGroupSize((output_size + WORKGROUP_SIZE - 1) / WORKGROUP_SIZE)
+      .AddUniformVariables({{static_cast<uint32_t>(output_size)},
+                            {static_cast<uint32_t>(channels)}});
+  return context.RunProgram(program);
+}
+
+}  // namespace webgpu
+}  // namespace contrib
+}  // namespace onnxruntime

onnxruntime/contrib_ops/webgpu/bert/bias_split_gelu.h

@@ -0,0 +1,32 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#pragma once
+
+#include "core/providers/webgpu/program.h"
+#include "core/providers/webgpu/webgpu_kernel.h"
+
+namespace onnxruntime {
+namespace contrib {
+namespace webgpu {
+
+using namespace onnxruntime::webgpu;
+using onnxruntime::webgpu::ComputeContext;
+
+class BiasSplitGeluProgram final : public Program<BiasSplitGeluProgram> {
+ public:
+  BiasSplitGeluProgram() : Program{"BiasSplitGelu"} {}
+  Status GenerateShaderCode(ShaderHelper& sh) const override;
+  WEBGPU_PROGRAM_DEFINE_UNIFORM_VARIABLES({"output_size", ProgramUniformVariableDataType::Uint32},
+                                          {"channels", ProgramUniformVariableDataType::Uint32});
+};
+
+class BiasSplitGelu final : public WebGpuKernel {
+ public:
+  BiasSplitGelu(const OpKernelInfo& info) : WebGpuKernel(info) {}
+  Status ComputeInternal(ComputeContext& context) const override;
+};
+
+}  // namespace webgpu
+}  // namespace contrib
+}  // namespace onnxruntime

onnxruntime/contrib_ops/webgpu/bert/gelu.cc

@@ -0,0 +1,27 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "core/providers/webgpu/shader_helper.h"
+#include "core/providers/webgpu/webgpu_supported_types.h"
+#include "core/providers/webgpu/math/unary_elementwise_ops.h"  // contains Gelu definition
+#include "contrib_ops/webgpu/webgpu_contrib_kernels.h"
+
+namespace onnxruntime {
+namespace contrib {
+namespace webgpu {
+
+using namespace onnxruntime::webgpu;
+using onnxruntime::webgpu::ComputeContext;
+
+ONNX_OPERATOR_KERNEL_EX(
+    Gelu,
+    kMSDomain,
+    1,
+    kWebGpuExecutionProvider,
+    (*KernelDefBuilder::Create())
+        .TypeConstraint("T", WebGpuSupportedFloatTypes()),
+    Gelu);
+
+}  // namespace webgpu
+}  // namespace contrib
+}  // namespace onnxruntime

onnxruntime/contrib_ops/webgpu/bert/quick_gelu.cc

@@ -0,0 +1,27 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include "core/providers/webgpu/shader_helper.h"
+#include "core/providers/webgpu/webgpu_supported_types.h"
+#include "core/providers/webgpu/math/unary_elementwise_ops.h"  // contained Gelu definition
+#include "contrib_ops/webgpu/webgpu_contrib_kernels.h"
+
+namespace onnxruntime {
+namespace contrib {
+namespace webgpu {
+
+using namespace onnxruntime::webgpu;
+using onnxruntime::webgpu::ComputeContext;
+
+ONNX_OPERATOR_KERNEL_EX(
+    QuickGelu,
+    kMSDomain,
+    1,
+    kWebGpuExecutionProvider,
+    (*KernelDefBuilder::Create())
+        .TypeConstraint("T", WebGpuSupportedFloatTypes()),
+    QuickGelu);
+
+}  // namespace webgpu
+}  // namespace contrib
+}  // namespace onnxruntime

onnxruntime/contrib_ops/webgpu/webgpu_contrib_kernels.cc

@@ -38,14 +38,14 @@ Status RegisterWebGpuContribKernels(KernelRegistry& kernel_registry) {
       BuildKernelCreateInfo<void>,  // default entry to avoid the list become empty after ops-reducing
                                     // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, Attention)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, BiasAdd)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, BiasSplitGelu)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, BiasSplitGelu)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, FastGelu)>,
       // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, FusedConv)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, Gelu)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, Gelu)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, GroupQueryAttention)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, MatMulNBits)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, MultiHeadAttention)>,
-      // BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, QuickGelu)>,
+      BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, QuickGelu)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, RotaryEmbedding)>,
       BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kMSDomain, 1, SkipLayerNormalization)>,
       // LayerNormalization used to be a contrib op that (incorrectly) used kOnnxDomain so we need to version it

onnxruntime/core/providers/webgpu/math/unary_elementwise_ops.cc

@@ -256,26 +256,6 @@
 // activation
 //
 
-class LinearUnit : public UnaryElementwise {
- public:
-  LinearUnit(const OpKernelInfo& info,
-             const std::string& kernel_name,
-             const std::string& expression,
-             const std::string& additional_impl,
-             float default_alpha)
-      : UnaryElementwise{info, kernel_name, expression, additional_impl, ShaderUsage::UseElementTypeAlias} {
-    info.GetAttrOrDefault("alpha", &alpha_, default_alpha);
-  }
-
-  Status ConfigureProgram(const ComputeContext& /*context*/, UnaryElementwiseProgram& program) const override {
-    program.AddUniformVariables({alpha_});
-    return Status::OK();
-  }
-
- protected:
-  float alpha_;
-};
-
 #define WEBGPU_LU_IMPL(OP_TYPE, ...)                                               \
   class OP_TYPE final : public LinearUnit {                                        \
    public:                                                                         \
@@ -285,17 +265,17 @@
 WEBGPU_LU_IMPL(Elu, "elu_v(a)", EluImpl, 1.0)
 WEBGPU_ELEMENTWISE_KERNEL(Elu, 6, WebGpuSupportedFloatTypes())
 
-class Gelu : public UnaryElementwise {
- public:
-  Gelu(const OpKernelInfo& info)
-      : UnaryElementwise{info,
-                         "Gelu",
-                         info.GetAttrOrDefault<std::string>("approximate", "none") == "tanh" ? FastGeluExpr : GeluExpr,
-                         info.GetAttrOrDefault<std::string>("approximate", "none") == "tanh" ? TanhImpl : ErfImpl,
-                         ShaderUsage::UseValueTypeAlias} {
-    cache_hint = info.GetAttrOrDefault<std::string>("approximate", "none");
-  }
-};
+Gelu::Gelu(const OpKernelInfo& info)
+    : UnaryElementwise{info,
+                       "Gelu",
+                       info.GetAttrOrDefault<std::string>("approximate", "none") == "tanh" ? FastGeluExpr : GeluExpr,
+                       info.GetAttrOrDefault<std::string>("approximate", "none") == "tanh" ? TanhImpl : ErfImpl,
+                       ShaderUsage::UseValueTypeAlias} {
+  cache_hint = info.GetAttrOrDefault<std::string>("approximate", "none");
+}
+
+QuickGelu::QuickGelu(const OpKernelInfo& info)
+    : LinearUnit{info, "QuickGelu", "quick_gelu_v(a)", QuickGeluImpl, 1.702f} {}
 
 WEBGPU_ELEMENTWISE_KERNEL(Gelu, 20, WebGpuSupportedFloatTypes())
 
@@ -312,4 +292,4 @@
 WEBGPU_ELEMENTWISE_KERNEL(ThresholdedRelu, 10, WebGpuSupportedFloatTypes())
 
 }  // namespace webgpu
-}  // namespace onnxruntime
+}  // namespace onnxruntime

onnxruntime/core/providers/webgpu/math/unary_elementwise_ops.h

@@ -60,6 +60,36 @@
   ShaderUsage additional_usage_;
 };
 
+class Gelu : public UnaryElementwise {
+ public:
+  Gelu(const OpKernelInfo& info);
+};
+
+class LinearUnit : public UnaryElementwise {
+ public:
+  LinearUnit(const OpKernelInfo& info,
+             const std::string& kernel_name,
+             const std::string& expression,
+             const std::string& additional_impl,
+             float default_alpha)
+      : UnaryElementwise{info, kernel_name, expression, additional_impl, ShaderUsage::UseElementTypeAlias} {
+    info.GetAttrOrDefault("alpha", &alpha_, default_alpha);
+  }
+
+  Status ConfigureProgram(const ComputeContext& /*context*/, UnaryElementwiseProgram& program) const override {
+    program.AddUniformVariables({alpha_});
+    return Status::OK();
+  }
+
+ protected:
+  float alpha_;
+};
+
+class QuickGelu : public LinearUnit {
+ public:
+  QuickGelu(const OpKernelInfo& info);
+};
+
 constexpr const char ErfImpl[] = R"(
 const r0 = 0.3275911;
 const r1 = 0.254829592;
@@ -104,11 +134,29 @@
 }
 )";
 
+constexpr const char QuickGeluImpl[] = R"(
+fn quick_gelu_v(a: vec4<x_element_t>) -> vec4<x_element_t> {
+  let one = 1.0;
+  let zero = 0.0;
+  let alpha_vec = vec4<x_element_t>(uniforms.attr);
+  let v = a * alpha_vec;
+  var x1 : vec4<x_element_t>;
+  for (var i = 0; i < 4; i = i + 1) {
+    if (v[i] >= zero) {
+      x1[i] = one / (one + exp(-v[i]));
+    } else {
+      x1[i] = one - one / (one + exp(v[i]));
+    }
+  }
+  return a * x1;
+}
+)";
+
 // default GELU expression, depending on ErfImpl
 constexpr const char GeluExpr[] = "0.5 * a * (1.0 + erf_v(a * 0.7071067811865475))";
 
 // fast GELU expression, depending on TanhImpl
 constexpr const char FastGeluExpr[] = "a * (0.5 + 0.5 * tanh_v(a * (0.035677408136300125 * a * a + 0.7978845608028654)))";
 
 }  // namespace webgpu
-}  // namespace onnxruntime
+}  // namespace onnxruntime

onnxruntime/core/providers/webgpu/webgpu_utils.h

@@ -0,0 +1,20 @@
+// Licensed under the MIT License.
+
+#pragma once
+
+#include <cstdint>
+
+namespace onnxruntime {
+namespace webgpu {
+
+inline int64_t GetMaxComponents(int64_t size) {
+  if (size % 4 == 0) {
+    return 4;
+  } else if (size % 2 == 0) {
+    return 2;
+  }
+  return 1;
+}
+
+}  // namespace webgpu
+}  // namespace onnxruntime