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cherry-pick kunlun PR: 29458, 29539 (#29583)
* support mobilenet for kunlun (#29458) * add xpu ops for training transformer in kunlun (#29539) * 1.fix matmul bug 2. add one hot * add xpu error msg Co-authored-by: procr <[email protected]> Co-authored-by: taixiurong <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,170 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #pragma once | ||
| #ifdef PADDLE_WITH_XPU | ||
| #include <algorithm> | ||
| #include <string> | ||
| #include <vector> | ||
|
|
||
| #include "paddle/fluid/framework/op_registry.h" | ||
| #include "xpu/refactor/math.h" | ||
|
|
||
| namespace paddle { | ||
|
|
||
| namespace operators { | ||
| typedef enum { XPU_OR, XPU_AND } XpuLogicalType; | ||
|
|
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| std::string XpuLogicalType2Str(XpuLogicalType ty) { | ||
| switch (ty) { | ||
| case XpuLogicalType::XPU_OR: | ||
| return std::string("logical or"); | ||
| case XpuLogicalType::XPU_AND: | ||
| return std::string("logical and"); | ||
| default: | ||
| return std::string("unknown type"); | ||
| } | ||
| return std::string("unknown"); | ||
| } | ||
|
|
||
| template <XpuLogicalType xpu_type, typename T> | ||
| class BinaryLogicalOpXPUKernel : public framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const framework::ExecutionContext& context) const override { | ||
| auto* x = context.Input<framework::Tensor>("X"); | ||
| auto* y = context.Input<framework::Tensor>("Y"); | ||
| auto* out = context.Output<framework::Tensor>("Out"); | ||
| T* out_ptr = out->mutable_data<T>(context.GetPlace()); | ||
| const T* x_ptr = x->data<T>(); | ||
| const T* y_ptr = y->data<T>(); | ||
| auto& dev_ctx = | ||
| context.template device_context<paddle::platform::XPUDeviceContext>(); | ||
| framework::Tensor broadcast_x; | ||
| framework::Tensor broadcast_y; | ||
| bool need_broad_cast = false; | ||
| if (x->numel() != out->numel()) { | ||
| // x need broadcast | ||
| T* broadcast_x_ptr = | ||
| broadcast_x.mutable_data<T>(context.GetPlace(), out->numel()); | ||
| auto& out_dim = out->dims(); | ||
| auto& x_dim = x->dims(); | ||
| int dims = out_dim.size(); | ||
| std::vector<int> bcast_xdims; | ||
| std::vector<int> bcast_ydims; | ||
| for (int i = 0; i < dims; ++i) { | ||
| if (out_dim[i] == x_dim[i]) { | ||
| bcast_xdims.push_back(x_dim[i]); | ||
| bcast_ydims.push_back(x_dim[i]); | ||
| continue; | ||
| } | ||
| bcast_xdims.push_back(1); | ||
| bcast_xdims.push_back(x_dim[i]); | ||
| bcast_ydims.push_back(out_dim[i] / x_dim[i]); | ||
| bcast_ydims.push_back(x_dim[i]); | ||
| } | ||
|
|
||
| int ret = xpu::broadcast<int8_t>( | ||
| dev_ctx.x_context(), reinterpret_cast<const int8_t*> x_ptr, | ||
| reinterpret_cast<int8_t*> broadcast_x_ptr, bcast_xdims, bcast_ydims); | ||
| PADDLE_ENFORCE_EQ(ret, XPU_SUCCESS, | ||
| platform::errors::External( | ||
| "XPU broadcast kernel return wrong value[%d %s]", | ||
| ret, XPUAPIErrorMsg[ret])); | ||
| x_ptr = (const T*)broadcast_x_ptr; | ||
| need_broad_cast = true; | ||
| } | ||
| if (y->numel() != out->numel()) { | ||
| // y need broadcast | ||
| T* broadcast_y_ptr = | ||
| broadcast_y.mutable_data<T>(context.GetPlace(), out->numel()); | ||
| auto& out_dim = out->dims(); | ||
| auto& y_dim = y->dims(); | ||
| int dims = out_dim.size(); | ||
| std::vector<int> bcast_xdims; | ||
| std::vector<int> bcast_ydims; | ||
| for (int i = 0; i < dims; ++i) { | ||
| if (out_dim[i] == y_dim[i]) { | ||
| bcast_xdims.push_back(y_dim[i]); | ||
| bcast_ydims.push_back(y_dim[i]); | ||
| continue; | ||
| } | ||
| bcast_xdims.push_back(1); | ||
| bcast_xdims.push_back(y_dim[i]); | ||
| bcast_ydims.push_back(out_dim[i] / y_dim[i]); | ||
| bcast_ydims.push_back(y_dim[i]); | ||
| } | ||
|
|
||
| int ret = xpu::broadcast<int8_t>( | ||
| dev_ctx.x_context(), reinterpret_cast<const int8_t*> y_ptr, | ||
| reinterpret_cast<int8_t*> broadcast_y_ptr, bcast_xdims, bcast_ydims); | ||
| PADDLE_ENFORCE_EQ(ret, XPU_SUCCESS, | ||
| platform::errors::External( | ||
| "XPU broadcast kernel return wrong value[%d %s]", | ||
| ret, XPUAPIErrorMsg[ret])); | ||
| y_ptr = (const T*)broadcast_y_ptr; | ||
| need_broad_cast = true; | ||
| } | ||
|
|
||
| // logical kernel | ||
| int ret = XPU_SUCCESS; | ||
| switch (xpu_type) { | ||
| case XpuLogicalType::XPU_OR: | ||
| ret = xpu::logical_or<bool>(dev_ctx.x_context(), x_ptr, y_ptr, out_ptr, | ||
| out->numel()); | ||
| break; | ||
| case XpuLogicalType::XPU_AND: | ||
| ret = xpu::logical_and<bool>(dev_ctx.x_context(), x_ptr, y_ptr, out_ptr, | ||
| out->numel()); | ||
| default: | ||
| LOG(ERROR) << "xpu not support logical xpu type = " | ||
| << XpuLogicalType2Str(xpu_type); | ||
| break; | ||
| } | ||
| PADDLE_ENFORCE_EQ( | ||
| ret, XPU_SUCCESS, | ||
| platform::errors::External("XPU API return wrong value[%d %s] in " | ||
| "op_name[%s].", | ||
| ret, XPUAPIErrorMsg[ret], | ||
| XpuLogicalType2Str(xpu_type))); | ||
|
|
||
| if (need_broad_cast && dev_ctx.x_context()->xpu_stream != nullptr) { | ||
| xpu_wait(); | ||
| } | ||
| } | ||
| }; | ||
|
|
||
| template <typename T> | ||
| class UnaryLogicalOpXPUKernel : public framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const framework::ExecutionContext& context) const override { | ||
| auto* x = context.Input<framework::Tensor>("X"); | ||
| auto* out = context.Output<framework::Tensor>("Out"); | ||
| if (x->numel() == 0) { | ||
| return; | ||
| } | ||
| out->mutable_data<T>(context.GetPlace()); | ||
| auto& dev_ctx = | ||
| context.template device_context<paddle::platform::XPUDeviceContext>(); | ||
| int ret = xpu::logical_not<bool>(dev_ctx.x_context(), x->data<T>(), | ||
| out->data<T>(), x->numel()); | ||
| PADDLE_ENFORCE_EQ( | ||
| ret, XPU_SUCCESS, | ||
| platform::errors::External("XPU API return wrong value[%d %s].", ret, | ||
| XPUAPIErrorMsg[ret])); | ||
| } | ||
| }; | ||
|
|
||
| } // namespace operators | ||
| } // namespace paddle | ||
| #endif |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,21 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #ifdef PADDLE_WITH_XPU | ||
| #include "paddle/fluid/operators/controlflow/logical_op_xpu.h" | ||
| namespace ops = paddle::operators; | ||
| REGISTER_OP_XPU_KERNEL( | ||
| logical_and, | ||
| ops::BinaryLogicalOpXPUKernel<ops::XpuLogicalType::XPU_AND, bool>); | ||
| #endif |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,19 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #ifdef PADDLE_WITH_XPU | ||
| #include "paddle/fluid/operators/controlflow/logical_op_xpu.h" | ||
| namespace ops = paddle::operators; | ||
| REGISTER_OP_XPU_KERNEL(logicalnot, ops::UnaryLogicalOpXPUKernel<bool>); | ||
| #endif |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,22 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #ifdef PADDLE_WITH_XPU | ||
| #include "paddle/fluid/operators/controlflow/logical_op_xpu.h" | ||
|
|
||
| namespace ops = paddle::operators; | ||
| REGISTER_OP_XPU_KERNEL( | ||
| logical_or, | ||
| ops::BinaryLogicalOpXPUKernel<ops::XpuLogicalType::XPU_OR, bool>); | ||
| #endif |
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