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[PHI]Standardise some C++ API (Part3) #47532

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Nov 2, 2022
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[PHI]Standardise some C++ API (Part3) #47532

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708a5f0
Standardise batch norm
YuanRisheng Nov 1, 2022
7d5bf96
standardize conv3d and depwise_conv2d
YuanRisheng Nov 1, 2022
19d10c4
fix ci bugs
YuanRisheng Nov 1, 2022
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10 changes: 3 additions & 7 deletions paddle/fluid/operators/inplace_abn_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -242,7 +242,6 @@ class InplaceABNKernel : public framework::OpKernel<T> {
auto is_test = ctx.Attr<bool>("is_test");
auto use_global_stats = ctx.Attr<bool>("use_global_stats");
auto trainable_statistics = ctx.Attr<bool>("trainable_statistics");
auto fuse_with_relu = ctx.Attr<bool>("fuse_with_relu");

auto* mean_out = ctx.Output<phi::DenseTensor>("MeanOut");
auto* variance_out = ctx.Output<phi::DenseTensor>("VarianceOut");
Expand All @@ -255,17 +254,16 @@ class InplaceABNKernel : public framework::OpKernel<T> {
static_cast<const typename framework::ConvertToPhiContext<
DeviceContext>::TYPE&>(dev_ctx),
*x,
*scale,
*bias,
*mean,
*variance,
*scale,
*bias,
is_test,
momentum,
epsilon,
data_layout,
is_test,
use_global_stats,
trainable_statistics,
fuse_with_relu,
y,
mean_out,
variance_out,
Expand Down Expand Up @@ -315,7 +313,6 @@ class InplaceABNGradKernel : public framework::OpKernel<T> {
auto is_test = ctx.Attr<bool>("is_test");
auto use_global_stats = ctx.Attr<bool>("use_global_stats");
auto trainable_statistics = ctx.Attr<bool>("trainable_statistics");
auto fuse_with_relu = ctx.Attr<bool>("fuse_with_relu");

auto* scale_grad =
ctx.Output<phi::DenseTensor>(framework::GradVarName("Scale"));
Expand Down Expand Up @@ -361,7 +358,6 @@ class InplaceABNGradKernel : public framework::OpKernel<T> {
is_test,
use_global_stats,
trainable_statistics,
fuse_with_relu,
true,
d_x,
scale_grad,
Expand Down
17 changes: 6 additions & 11 deletions paddle/fluid/operators/inplace_abn_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -48,7 +48,6 @@ class InplaceABNKernel : public framework::OpKernel<T> {
auto is_test = ctx.Attr<bool>("is_test");
auto use_global_stats = ctx.Attr<bool>("use_global_stats");
auto trainable_statistics = ctx.Attr<bool>("trainable_statistics");
auto fuse_with_relu = ctx.Attr<bool>("fuse_with_relu");

auto* mean_out = ctx.Output<phi::DenseTensor>("MeanOut");
auto* variance_out = ctx.Output<phi::DenseTensor>("VarianceOut");
Expand All @@ -62,17 +61,16 @@ class InplaceABNKernel : public framework::OpKernel<T> {
static_cast<const typename framework::ConvertToPhiContext<
DeviceContext>::TYPE&>(dev_ctx),
*x,
*scale,
*bias,
*mean,
*variance,
*scale,
*bias,
is_test,
momentum,
epsilon,
data_layout,
is_test,
use_global_stats,
trainable_statistics,
fuse_with_relu,
y,
mean_out,
variance_out,
Expand All @@ -85,17 +83,16 @@ class InplaceABNKernel : public framework::OpKernel<T> {
static_cast<const typename framework::ConvertToPhiContext<
DeviceContext>::TYPE&>(dev_ctx),
*x,
*scale,
*bias,
*mean,
*variance,
*scale,
*bias,
is_test,
momentum,
epsilon,
data_layout,
is_test,
use_global_stats,
trainable_statistics,
fuse_with_relu,
y,
mean_out,
variance_out,
Expand Down Expand Up @@ -146,7 +143,6 @@ class InplaceABNGradKernel : public framework::OpKernel<T> {
auto is_test = ctx.Attr<bool>("is_test");
auto use_global_stats = ctx.Attr<bool>("use_global_stats");
auto trainable_statistics = ctx.Attr<bool>("trainable_statistics");
auto fuse_with_relu = ctx.Attr<bool>("fuse_with_relu");

auto* scale_grad =
ctx.Output<phi::DenseTensor>(framework::GradVarName("Scale"));
Expand Down Expand Up @@ -210,7 +206,6 @@ class InplaceABNGradKernel : public framework::OpKernel<T> {
is_test,
use_global_stats,
trainable_statistics,
fuse_with_relu,
true,
d_x,
scale_grad,
Expand Down
72 changes: 36 additions & 36 deletions paddle/phi/api/yaml/legacy_backward.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -129,8 +129,8 @@
inplace : (out_grad -> x_grad)

- backward_op : batch_norm_double_grad
forward : batch_norm_grad (Tensor x, Tensor scale, Tensor bias, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor grad_out, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias)
args : (Tensor x, Tensor scale, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor grad_out, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
forward : batch_norm_grad (Tensor x, Tensor scale, Tensor bias, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor grad_out, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias)
args : (Tensor x, Tensor scale, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor grad_out, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(grad_out_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
Expand All @@ -142,8 +142,8 @@
inplace : (grad_out -> grad_out_grad)

- backward_op : batch_norm_grad
forward : batch_norm (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean_out, Tensor variance_out, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
forward : batch_norm (Tensor x, Tensor mean, Tensor variance, Tensor scale, Tensor bias, bool is_test, float momentum, float epsilon, str data_layout, bool use_global_stats, bool trainable_statistics) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean_out, Tensor variance_out, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
Expand Down Expand Up @@ -345,29 +345,29 @@
use_gpudnn : true
backward : conv2d_transpose_double_grad

- backward_op : conv3d_double_grad
forward : conv3d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
param: [input, filter, grad_out]
kernel :
func : conv3d_double_grad
use_gpudnn : true
optional : grad_input_grad, grad_filter_grad

- backward_op : conv3d_grad
forward : conv3d (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
forward : conv3d (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(input_grad), Tensor(filter_grad)
infer_meta :
func : GeneralBinaryGradInferMeta
param : [input, filter]
kernel :
func : conv3d_grad
use_gpudnn : true
backward : conv3d_grad_grad

- backward_op : conv3d_grad_grad
forward : conv3d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
param: [input, filter, grad_out]
kernel :
func : conv3d_grad_grad
use_gpudnn : true
optional : grad_input_grad, grad_filter_grad
backward : conv3d_double_grad

- backward_op : conv3d_transpose_grad
forward : conv3d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
Expand Down Expand Up @@ -427,29 +427,29 @@
data_type : x
optional : mask

- backward_op : depthwise_conv2d_double_grad
forward : depthwise_conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_gpudnn) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
param: [input, filter, grad_out]
kernel :
func : depthwise_conv2d_double_grad
optional : grad_input_grad, grad_filter_grad

- backward_op : depthwise_conv2d_grad
forward : depthwise_conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn)
forward : depthwise_conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_gpudnn) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_gpudnn)
output : Tensor(input_grad), Tensor(filter_grad)
infer_meta :
func : GeneralBinaryGradInferMeta
param : [input, filter]
kernel :
func : depthwise_conv2d_grad
param : [input, filter, out_grad, strides, paddings, padding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search, fuse_relu]
param : [input, filter, out_grad, strides, paddings, padding_algorithm, groups, dilations, data_format]
use_gpudnn : use_gpudnn
backward : depthwise_conv2d_grad_grad

- backward_op : depthwise_conv2d_grad_grad
forward : depthwise_conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
param: [input, filter, grad_out]
kernel :
func : depthwise_conv2d_grad_grad
optional : grad_input_grad, grad_filter_grad
backward : depthwise_conv2d_double_grad

- backward_op : depthwise_conv2d_transpose_grad
forward : depthwise_conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
Expand Down Expand Up @@ -2091,8 +2091,8 @@
inplace : (out_grad -> x_grad)

- backward_op : sync_batch_norm_grad
forward : sync_batch_norm_ (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
forward : sync_batch_norm_ (Tensor x, Tensor mean, Tensor variance, Tensor scale, Tensor bias, bool is_test, float momentum, float epsilon, str data_layout, bool use_global_stats, bool trainable_statistics) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
infer_meta :
func : GeneralTernaryGradInferMeta
Expand Down
12 changes: 6 additions & 6 deletions paddle/phi/api/yaml/legacy_ops.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -254,7 +254,7 @@
inplace : (in_sum_1 -> out_sum_1), (in_sum_2 -> out_sum_2), (in_sum_3 -> out_sum_3), (in_num_accumulates -> out_num_accumulates), (in_old_num_accumulates -> out_old_num_accumulates), (in_num_updates -> out_num_updates)

- op : batch_norm
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
args : (Tensor x, Tensor mean, Tensor variance, Tensor scale, Tensor bias, bool is_test, float momentum, float epsilon, str data_layout, bool use_global_stats, bool trainable_statistics)
output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
infer_meta:
func : BatchNormInferMeta
Expand Down Expand Up @@ -464,7 +464,7 @@
backward : conv2d_transpose_grad

- op : conv3d
args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor
infer_meta :
func : Conv3DInferMeta
Expand Down Expand Up @@ -551,14 +551,14 @@
backward : deformable_conv_grad

- op : depthwise_conv2d
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn)
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_gpudnn)
output : Tensor(out)
infer_meta :
func : DepthwiseConvInferMeta
param : [x, filter, strides, paddings, padding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search]
param : [x, filter, strides, paddings, padding_algorithm, groups, dilations, data_format]
kernel :
func : depthwise_conv2d
param : [x, filter, strides, paddings, padding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search, fuse_relu]
param : [x, filter, strides, paddings, padding_algorithm, groups, dilations, data_format]
use_gpudnn : use_gpudnn
backward : depthwise_conv2d_grad

Expand Down Expand Up @@ -2365,7 +2365,7 @@
backward : swish_grad

- op : sync_batch_norm_
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
args : (Tensor x, Tensor mean, Tensor variance, Tensor scale, Tensor bias, bool is_test, float momentum, float epsilon, str data_layout, bool use_global_stats, bool trainable_statistics)
output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
infer_meta :
func : BatchNormInferMeta
Expand Down
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