wehub-resource-sync
60 lines
2.0 KiB
C++
60 lines
2.0 KiB
C++
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/increment_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/common/memory_utils.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void IncrementKernel(const Context& dev_ctx,
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const DenseTensor& x,
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float value,
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DenseTensor* out) {
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if (x.numel() == 0) {
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dev_ctx.template Alloc<T>(out);
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return;
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}
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// check input
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PADDLE_ENFORCE_EQ(x.numel(),
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1,
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common::errors::InvalidArgument(
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"input tensor x's numel should be EXACTLY 1."));
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const T* x_data = x.data<T>();
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T* out_data = dev_ctx.template Alloc<T>(out);
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// allocation for "value" on xpu
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T value_as_t = static_cast<T>(value);
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xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
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T* value_xpu = RAII_GUARD.alloc_l3_or_gm<T>(1);
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memory_utils::Copy(dev_ctx.GetPlace(),
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value_xpu,
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CPUPlace(),
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reinterpret_cast<void*>(&value_as_t),
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sizeof(T));
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// int add(Context* xpu_ctx, const T* x, const T* y, T* z, int64_t len);
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int ret = xpu::add(dev_ctx.x_context(), x_data, value_xpu, out_data, 1);
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PADDLE_ENFORCE_XDNN_SUCCESS(ret, "add");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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increment, XPU, ALL_LAYOUT, phi::IncrementKernel, float, int, int64_t) {}
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