Skip to content

【Hackathon 7th PPSCI No.12】Adam、AdamW 优化器支持 amsgrad #1484

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
xiaoguoguo626807 merged 4 commits into from
Dec 9, 2024
Merged

【Hackathon 7th PPSCI No.12】Adam、AdamW 优化器支持 amsgrad #1484

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
7a7b534
[Update] npu amsgrad raise errors
megemini Nov 27, 2024
ffebaa7
[Fix] no_check_set_white_list with adam adamw
megemini Nov 27, 2024
cf5963c
Merge branch 'develop' of https://github.com/PaddlePaddle/PaddleCusto…
megemini Dec 4, 2024
0790d2e
[Update] ut add amsgrad inputs
megemini Dec 4, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
130 changes: 75 additions & 55 deletions backends/npu/kernels/adam_kernel.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -233,29 +233,38 @@ void CastFP64toFP32Kernel(const Context& dev_ctx,
}

template <typename T, typename Context>
void AdamKernel(const Context& dev_ctx,
const phi::DenseTensor& param,
const phi::DenseTensor& grad,
const phi::DenseTensor& learning_rate,
const phi::DenseTensor& moment1,
const phi::DenseTensor& moment2,
const phi::DenseTensor& beta1_pow_in,
const phi::DenseTensor& beta2_pow_in,
const paddle::optional<phi::DenseTensor>& master_param,
const paddle::optional<phi::DenseTensor>& skip_update,
const phi::Scalar& beta1_in,
const phi::Scalar& beta2_in,
const phi::Scalar& epsilon_in,
bool lazy_mode,
int64_t min_row_size_to_use_multithread,
bool multi_precision,
bool use_global_beta_pow,
phi::DenseTensor* param_out,
phi::DenseTensor* moment1_out,
phi::DenseTensor* moment2_out,
phi::DenseTensor* beta1_pow_out,
phi::DenseTensor* beta2_pow_out,
phi::DenseTensor* master_param_out) {
void AdamKernel(
const Context& dev_ctx,
const phi::DenseTensor& param,
const phi::DenseTensor& grad,
const phi::DenseTensor& learning_rate,
const phi::DenseTensor& moment1,
const phi::DenseTensor& moment2,
const paddle::optional<phi::DenseTensor>& moment2_max, // UNUSED
const phi::DenseTensor& beta1_pow_in,
const phi::DenseTensor& beta2_pow_in,
const paddle::optional<phi::DenseTensor>& master_param,
const paddle::optional<phi::DenseTensor>& skip_update,
const phi::Scalar& beta1_in,
const phi::Scalar& beta2_in,
const phi::Scalar& epsilon_in,
bool lazy_mode,
int64_t min_row_size_to_use_multithread,
bool multi_precision,
bool use_global_beta_pow,
bool amsgrad, // UNUSED
phi::DenseTensor* param_out,
phi::DenseTensor* moment1_out,
phi::DenseTensor* moment2_out,
phi::DenseTensor* moment2_max_out, // UNUSED
phi::DenseTensor* beta1_pow_out,
phi::DenseTensor* beta2_pow_out,
phi::DenseTensor* master_param_out) {
PADDLE_ENFORCE_NE(
amsgrad,
true,
phi::errors::Unimplemented("Operation amsgrad is not supported yet."));

bool skip_update_ = false;
if (skip_update.is_initialized()) {
PADDLE_ENFORCE_EQ(skip_update->numel(),
Expand Down Expand Up @@ -358,32 +367,41 @@ void AdamKernel(const Context& dev_ctx,
}

template <typename T, typename Context>
void AdamwKernel(const Context& dev_ctx,
const phi::DenseTensor& param,
const phi::DenseTensor& grad,
const phi::DenseTensor& learning_rate,
const phi::DenseTensor& moment1,
const phi::DenseTensor& moment2,
const phi::DenseTensor& beta1_pow,
const phi::DenseTensor& beta2_pow,
const paddle::optional<phi::DenseTensor>& master_param,
const paddle::optional<phi::DenseTensor>& skip_update,
const phi::Scalar& beta1,
const phi::Scalar& beta2,
const phi::Scalar& epsilon,
float lr_ratio,
float coeff,
bool with_decay,
bool lazy_mode,
int64_t min_row_size_to_use_multithread,
bool multi_precision,
bool use_global_beta_pow,
phi::DenseTensor* param_out,
phi::DenseTensor* moment1_out,
phi::DenseTensor* moment2_out,
phi::DenseTensor* beta1_pow_out,
phi::DenseTensor* beta2_pow_out,
phi::DenseTensor* master_param_outs) {
void AdamwKernel(
const Context& dev_ctx,
const phi::DenseTensor& param,
const phi::DenseTensor& grad,
const phi::DenseTensor& learning_rate,
const phi::DenseTensor& moment1,
const phi::DenseTensor& moment2,
const paddle::optional<phi::DenseTensor>& moment2_max, // UNUSED
const phi::DenseTensor& beta1_pow,
const phi::DenseTensor& beta2_pow,
const paddle::optional<phi::DenseTensor>& master_param,
const paddle::optional<phi::DenseTensor>& skip_update,
const phi::Scalar& beta1,
const phi::Scalar& beta2,
const phi::Scalar& epsilon,
float lr_ratio,
float coeff,
bool with_decay,
bool lazy_mode,
int64_t min_row_size_to_use_multithread,
bool multi_precision,
bool use_global_beta_pow,
bool amsgrad, // UNUSED
phi::DenseTensor* param_out,
phi::DenseTensor* moment1_out,
phi::DenseTensor* moment2_out,
phi::DenseTensor* moment2_max_out, // UNUSED
phi::DenseTensor* beta1_pow_out,
phi::DenseTensor* beta2_pow_out,
phi::DenseTensor* master_param_outs) {
PADDLE_ENFORCE_NE(
amsgrad,
true,
phi::errors::Unimplemented("Operation amsgrad is not supported yet."));

using MPDType = typename phi::dtype::MPTypeTrait<T>::Type;

bool skip_update_ = false;
Expand Down Expand Up @@ -514,18 +532,19 @@ PD_REGISTER_PLUGIN_KERNEL(adam,
float,
double) {
// Skip beta1_pow, beta2_pow, skip_update data transform
kernel->InputAt(5).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(6).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(8).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(7).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(9).SetBackend(phi::Backend::ALL_BACKEND);
if (kernel_key.dtype() == phi::DataType::FLOAT16) {
kernel->OutputAt(1).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(2).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(3).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(4).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(5).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(6).SetDataType(phi::DataType::FLOAT32);
}
kernel->OutputAt(3).SetBackend(phi::Backend::UNDEFINED);
kernel->OutputAt(4).SetBackend(phi::Backend::UNDEFINED);
kernel->OutputAt(5).SetBackend(phi::Backend::UNDEFINED);
}

PD_REGISTER_PLUGIN_KERNEL(adamw,
Expand All @@ -537,16 +556,17 @@ PD_REGISTER_PLUGIN_KERNEL(adamw,
float,
double) {
// Skip beta1_pow, beta2_pow, skip_update data transform
kernel->InputAt(5).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(6).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(8).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(7).SetBackend(phi::Backend::ALL_BACKEND);
kernel->InputAt(9).SetBackend(phi::Backend::ALL_BACKEND);
if (kernel_key.dtype() == phi::DataType::FLOAT16) {
kernel->OutputAt(1).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(2).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(3).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(4).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(5).SetDataType(phi::DataType::FLOAT32);
kernel->OutputAt(6).SetDataType(phi::DataType::FLOAT32);
}
kernel->OutputAt(3).SetBackend(phi::Backend::UNDEFINED);
kernel->OutputAt(4).SetBackend(phi::Backend::UNDEFINED);
kernel->OutputAt(5).SetBackend(phi::Backend::UNDEFINED);
}
Loading