Skip to content
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

Jump to bottom

[cherry-pick] fix attr missing in conv cudnn kernel #38832

Merged
merged 1 commit into from
Jan 11, 2022
Merged

[cherry-pick] fix attr missing in conv cudnn kernel #38832

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
19 changes: 12 additions & 7 deletions paddle/fluid/operators/conv_cudnn_op.cu
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,8 @@ class CUDNNConvOpKernel : public framework::OpKernel<T> {
int groups = ctx.Attr<int>("groups");

bool exhaustive_search =
FLAGS_cudnn_exhaustive_search || ctx.Attr<bool>("exhaustive_search");
FLAGS_cudnn_exhaustive_search || (ctx.HasAttr("exhaustive_search") &&
ctx.Attr<bool>("exhaustive_search"));
bool deterministic = FLAGS_cudnn_deterministic;
auto exhaustive_deterministic = exhaustive_search && deterministic;
PADDLE_ENFORCE_EQ(exhaustive_deterministic, false,
Expand Down Expand Up @@ -386,7 +387,8 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
int groups = ctx.Attr<int>("groups");

bool exhaustive_search =
FLAGS_cudnn_exhaustive_search || ctx.Attr<bool>("exhaustive_search");
FLAGS_cudnn_exhaustive_search || (ctx.HasAttr("exhaustive_search") &&
ctx.Attr<bool>("exhaustive_search"));
bool deterministic = FLAGS_cudnn_deterministic;
auto exhaustive_deterministic = exhaustive_search && deterministic;
PADDLE_ENFORCE_EQ(exhaustive_deterministic, false,
Expand Down Expand Up @@ -437,7 +439,7 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
ctx, input_grad, &transformed_input_grad_channel);
// NOTE(zhiqiu): If inplace_addto strategy is enabled, we need to copy
// the data of input_grad to transformed_input_grad_channel.
if (ctx.Attr<bool>("use_addto")) {
if (ctx.HasAttr("use_addto") && ctx.Attr<bool>("use_addto")) {
TransToChannelFirst<platform::CUDADeviceContext, T>(
ctx, input_grad, &transformed_input_grad_channel);
}
Expand Down Expand Up @@ -703,15 +705,17 @@ class CUDNNConvGradOpKernel : public framework::OpKernel<T> {
// MIOPEN ONLY support beta to be 0.0f
ScalingParamType<T> beta = 0.0f;
#else
ScalingParamType<T> beta = ctx.Attr<bool>("use_addto") ? 1.0f : 0.0f;
ScalingParamType<T> beta =
(ctx.HasAttr("use_addto") && ctx.Attr<bool>("use_addto")) ? 1.0f : 0.0f;
#endif
VLOG(4) << "Conv_grad: use_addto = " << ctx.Attr<bool>("use_addto");
VLOG(4) << "Conv_grad: use_addto = "
<< (ctx.HasAttr("use_addto") && ctx.Attr<bool>("use_addto"));

if (input_grad) {
// When beta is 0, it is unnecessary to reset input_grad.
// When beta is 1, the output cannot be reset since addt strategy used.
#ifdef PADDLE_WITH_HIP
if (ctx.Attr<bool>("use_addto")) {
if (ctx.HasAttr("use_addto") && ctx.Attr<bool>("use_addto")) {
Tensor temp_tensor(transformed_input_grad.type());
temp_tensor.Resize(transformed_input_grad.dims());
T* temp_tensor_data = temp_tensor.mutable_data<T>(ctx.GetPlace());
Expand Down Expand Up @@ -878,7 +882,8 @@ class CUDNNConvDoubleGradOpKernel : public framework::OpKernel<T> {
int groups = ctx.Attr<int>("groups");

bool exhaustive_search =
FLAGS_cudnn_exhaustive_search || ctx.Attr<bool>("exhaustive_search");
FLAGS_cudnn_exhaustive_search || (ctx.HasAttr("exhaustive_search") &&
ctx.Attr<bool>("exhaustive_search"));
bool deterministic = FLAGS_cudnn_deterministic;
auto exhaustive_deterministic = exhaustive_search && deterministic;
PADDLE_ENFORCE_EQ(exhaustive_deterministic, false,
Expand Down