wehub-resource-sync
78 lines
2.6 KiB
C++
78 lines
2.6 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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#if defined(PADDLE_WITH_XPU_XFT)
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#include <xft/xdnn_plugin.h>
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#endif
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#include "paddle/common/enforce.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/cast_kernel.h"
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#include "paddle/phi/kernels/transpose_kernel.h"
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namespace phi {
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template <typename T, typename Context>
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void WeightQuantizeKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const std::string& algo,
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const int32_t arch,
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const int32_t group_size,
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DenseTensor* out,
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DenseTensor* scale) {
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#if defined(PADDLE_WITH_XPU_XFT)
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto xpu_ctx = static_cast<const XPUContext*>(&dev_ctx);
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int k = x.dims()[0];
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int n = x.dims()[1];
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scale->Resize({static_cast<int64_t>(n)});
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dev_ctx.template Alloc<float>(scale);
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if (out->numel() == 0) {
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dev_ctx.template Alloc<int8_t>(out);
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return;
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}
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if (algo == "weight_only_int8") {
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out->Resize({static_cast<int64_t>(k), static_cast<int64_t>(n)});
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dev_ctx.template Alloc<int8_t>(out);
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int ret = baidu::xpu::xftkernel::xft_quant2d_per_channel<XPUType, float>(
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xpu_ctx->x_context(),
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reinterpret_cast<const XPUType*>(x.template data<T>()),
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nullptr,
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out->data<int8_t>(),
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scale->data<float>(),
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k,
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n);
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PADDLE_ENFORCE_XDNN_SUCCESS(ret, "quant2d");
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} else {
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PADDLE_THROW(common::errors::Unimplemented(
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"Weight quantize only supports weight_only_int8 on XPU now."));
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}
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#else
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PADDLE_THROW(common::errors::Unimplemented(
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"weight_quantize is not supported since it's not "
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"compiled with XPU_XFT"));
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#endif
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}
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} // namespace phi
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PD_REGISTER_KERNEL(weight_quantize,
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XPU,
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ALL_LAYOUT,
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phi::WeightQuantizeKernel,
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phi::float16,
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phi::bfloat16) {}
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