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[WebGPU EP] Flatten implementation (#22964)

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Implements flatten operator for native webgpu.
This commit is contained in:
Prathik Rao 2024-12-03 14:40:57 -08:00 committed by GitHub
parent 9ed0c7fe26
commit 5c644d3747
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GPG key ID: B5690EEEBB952194
3 changed files with 122 additions and 5 deletions
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52
onnxruntime/core/providers/webgpu/tensor/flatten.cc Normal file
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@ -0,0 +1,52 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
#include "core/providers/webgpu/tensor/flatten.h"
#include "core/providers/webgpu/webgpu_execution_provider.h"
#include "core/providers/webgpu/webgpu_supported_types.h"
namespace onnxruntime {
namespace webgpu {
ONNX_OPERATOR_VERSIONED_KERNEL_EX(
Flatten,
kOnnxDomain,
1, 8,
kWebGpuExecutionProvider,
(*KernelDefBuilder::Create()).TypeConstraint("T", WebGpuSupportedFloatTypes()).InputMemoryType(OrtMemTypeCPU, 1),
Flatten);
ONNX_OPERATOR_VERSIONED_KERNEL_EX(
Flatten,
kOnnxDomain,
9, 10,
kWebGpuExecutionProvider,
(*KernelDefBuilder::Create()).TypeConstraint("T", WebGpuSupportedFloatTypes()).InputMemoryType(OrtMemTypeCPU, 1),
Flatten);
ONNX_OPERATOR_VERSIONED_KERNEL_EX(
Flatten,
kOnnxDomain,
11, 12,
kWebGpuExecutionProvider,
(*KernelDefBuilder::Create()).TypeConstraint("T", WebGpuSupportedFloatTypes()).InputMemoryType(OrtMemTypeCPU, 1),
Flatten);
ONNX_OPERATOR_VERSIONED_KERNEL_EX(
Flatten,
kOnnxDomain,
13, 20,
kWebGpuExecutionProvider,
(*KernelDefBuilder::Create()).TypeConstraint("T", WebGpuSupportedFloatTypes()).InputMemoryType(OrtMemTypeCPU, 1),
Flatten);
ONNX_OPERATOR_KERNEL_EX(
Flatten,
kOnnxDomain,
21,
kWebGpuExecutionProvider,
(*KernelDefBuilder::Create()).TypeConstraint("T", WebGpuSupportedFloatTypes()).InputMemoryType(OrtMemTypeCPU, 1),
Flatten);
} // namespace webgpu
} // namespace onnxruntime

62
onnxruntime/core/providers/webgpu/tensor/flatten.h Normal file
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@ -0,0 +1,62 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
#pragma once
#include "core/framework/op_kernel.h"
#include "core/providers/cpu/nn/flatten.h"
#include "core/framework/data_transfer_manager.h"
namespace onnxruntime {
namespace webgpu {
class Flatten final : public OpKernel {
public:
explicit Flatten(const OpKernelInfo& info) : OpKernel{info} {
axis_ = info.GetAttrOrDefault<int64_t>("axis", 1);
}
Status Compute(OpKernelContext* context) const override {
const Tensor* input_tensor = context->Input<Tensor>(0);
const TensorShape& input_shape = input_tensor->Shape();
int64_t input_rank = input_shape.NumDimensions();
// Handle negative axis
int64_t axis = axis_;
if (axis < 0) {
axis += input_rank;
}
if (axis > input_rank) {
return Status(common::ONNXRUNTIME, common::FAIL, "Invalid value for axis, must be less than or equal to input_rank");
}
int64_t first_dim = 1;
for (int64_t i = 0; i < axis; i++) {
first_dim *= input_shape[i];
}
int64_t second_dim = 1;
for (int64_t i = axis; i < input_rank; i++) {
second_dim *= input_shape[i];
}
TensorShape output_shape({first_dim, second_dim});
Tensor* output_tensor = context->Output(0, output_shape);
const void* source = input_tensor->DataRaw();
void* target = output_tensor->MutableDataRaw();
// If source and target pointers are not equal (non-inplace operation), we need to copy the data.
if (target != source) {
ORT_RETURN_IF_ERROR(Info().GetDataTransferManager().CopyTensor(*input_tensor, *output_tensor));
}
return Status::OK();
}
private:
int64_t axis_;
};
} // namespace webgpu
} // namespace onnxruntime

13
onnxruntime/core/providers/webgpu/webgpu_execution_provider.cc
View file

@ -347,7 +347,8 @@ class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13,
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 8, Flatten);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 9, 10, Flatten);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, Flatten);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Flatten);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 20, Flatten);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 21, Flatten);
class ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 6, 12, Tile);
class ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Tile);
@ -667,10 +668,12 @@ std::unique_ptr<KernelRegistry> RegisterKernels() {
// BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, Slice)>,
// BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Slice)>,
// BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 8, Flatten)>,
// BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 9, 10, Flatten)>,
// BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, Flatten)>,
// BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 1, 8, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 9, 10, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 11, 12, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, 20, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 21, Flatten)>,
BuildKernelCreateInfo<ONNX_OPERATOR_VERSIONED_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 6, 12, Tile)>,
BuildKernelCreateInfo<ONNX_OPERATOR_KERNEL_CLASS_NAME(kWebGpuExecutionProvider, kOnnxDomain, 13, Tile)>,