wehub-resource-sync
89 lines
3.2 KiB
Plaintext
89 lines
3.2 KiB
Plaintext
/* Copyright (c) 2023 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. */
|
|
|
|
#include "paddle/phi/kernels/weight_only_linear_grad_kernel.h"
|
|
#include "paddle/phi/backends/gpu/gpu_context.h"
|
|
#include "paddle/phi/common/datatype_traits.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
#include "paddle/phi/kernels/full_kernel.h"
|
|
#include "paddle/phi/kernels/matmul_kernel.h"
|
|
|
|
#if defined(PADDLE_WITH_CUTLASS)
|
|
#include "paddle/phi/kernels/funcs/weight_dequant_functor.h"
|
|
#endif
|
|
|
|
namespace phi {
|
|
|
|
template <typename T, typename Context>
|
|
void WeightOnlyLinearGradKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
const DenseTensor& weight,
|
|
const optional<DenseTensor>& bias,
|
|
const DenseTensor& weight_scale,
|
|
const DenseTensor& out_grad,
|
|
const std::string& weight_dtype,
|
|
const int32_t arch,
|
|
const int32_t group_size,
|
|
DenseTensor* x_grad) {
|
|
#if defined(PADDLE_WITH_CUTLASS)
|
|
PADDLE_ENFORCE_EQ(
|
|
((arch == 80) || (arch == 86) || (arch == 90 || (arch == 100))),
|
|
true,
|
|
common::errors::InvalidArgument("Currently weightonly linear grad only "
|
|
"support arch = 80, 86, 90 or 100. "));
|
|
|
|
PADDLE_ENFORCE_EQ(
|
|
group_size,
|
|
-1,
|
|
common::errors::InvalidArgument(
|
|
"Currently weightonly linear grad only support per-channel mode. "));
|
|
|
|
int64_t n = weight_scale.dims()[0];
|
|
|
|
int64_t k = weight.dims()[1];
|
|
|
|
dev_ctx.template Alloc<T>(x_grad);
|
|
if (x_grad->numel() == 0 || out_grad.numel() == 0 || weight.numel() == 0) {
|
|
Full<T, Context>(dev_ctx, x_grad->dims(), 0, x_grad);
|
|
return;
|
|
}
|
|
DenseTensor weight_dequantized;
|
|
weight_dequantized.Resize({n, k});
|
|
dev_ctx.template Alloc<T>(&weight_dequantized);
|
|
std::string algo =
|
|
weight_dtype == "int8" ? "weight_only_int8" : "weight_only_int4";
|
|
WeightDequantize<T, Context>(dev_ctx,
|
|
weight,
|
|
weight_scale,
|
|
algo,
|
|
true,
|
|
group_size,
|
|
&weight_dequantized);
|
|
MatmulKernel<T, Context>(
|
|
dev_ctx, out_grad, weight_dequantized, false, false, x_grad);
|
|
#else
|
|
PADDLE_THROW(
|
|
common::errors::PreconditionNotMet("Not compiled with WITH_CUTLASS=ON"));
|
|
#endif
|
|
}
|
|
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(weight_only_linear_grad,
|
|
GPU,
|
|
ALL_LAYOUT,
|
|
phi::WeightOnlyLinearGradKernel,
|
|
phi::float16,
|
|
phi::bfloat16) {}
|