From 0fa8309aed4f47d52f39ab808bf51242a2c7e016 Mon Sep 17 00:00:00 2001 From: zhangkaihuo Date: Fri, 28 Oct 2022 11:21:58 +0800 Subject: [PATCH] [cherry-pick]add sync_batch_norm_bn and deliver indices_dict (#47407) add sync_batch_norm_bn and deliver indices_dict --- paddle/fluid/operators/sparse_manual_op.cc | 2 +- .../phi/api/yaml/generator/sparse_api_gen.py | 169 ++++++++++++------ paddle/phi/api/yaml/sparse_backward.yaml | 12 ++ paddle/phi/api/yaml/sparse_ops.yaml | 15 +- paddle/phi/kernels/sparse/empty_kernel.cc | 2 + .../phi/kernels/sparse/gpu/coalesce_kernel.cu | 1 + .../sparse/gpu/sync_batch_norm_grad_kernel.cu | 85 +++++++++ .../sparse/gpu/sync_batch_norm_kernel.cu | 84 +++++++++ .../kernels/sparse/impl/unary_kernel_impl.h | 3 + .../sparse/sync_batch_norm_grad_kernel.h | 47 +++++ .../kernels/sparse/sync_batch_norm_kernel.h | 47 +++++ python/paddle/sparse/nn/layer/norm.py | 21 ++- 12 files changed, 424 insertions(+), 64 deletions(-) create mode 100644 paddle/phi/kernels/sparse/gpu/sync_batch_norm_grad_kernel.cu create mode 100644 paddle/phi/kernels/sparse/gpu/sync_batch_norm_kernel.cu create mode 100644 paddle/phi/kernels/sparse/sync_batch_norm_grad_kernel.h create mode 100644 paddle/phi/kernels/sparse/sync_batch_norm_kernel.h diff --git a/paddle/fluid/operators/sparse_manual_op.cc b/paddle/fluid/operators/sparse_manual_op.cc index 04e12391b42..327e03af805 100644 --- a/paddle/fluid/operators/sparse_manual_op.cc +++ b/paddle/fluid/operators/sparse_manual_op.cc @@ -213,7 +213,7 @@ class SparseBatchNormOpMaker : public framework::OpProtoAndCheckerMaker { AddAttr("fuse_with_relu", "(bool), attribute 4 for sparse_batch_norm op."); AddComment(R"DOC( -TODO: Documentation of sparse_conv3d op. +TODO: Documentation of sparse_batch_norm op. )DOC"); } }; diff --git a/paddle/phi/api/yaml/generator/sparse_api_gen.py b/paddle/phi/api/yaml/generator/sparse_api_gen.py index 9123cf7fff5..cfd3c698b04 100644 --- a/paddle/phi/api/yaml/generator/sparse_api_gen.py +++ b/paddle/phi/api/yaml/generator/sparse_api_gen.py @@ -22,7 +22,6 @@ from api_base import PREFIX_TENSOR_NAME class SparseAPI(ForwardAPI): - def __init__(self, api_item_yaml): super(SparseAPI, self).__init__(api_item_yaml) @@ -32,11 +31,13 @@ class SparseAPI(ForwardAPI): {super(SparseAPI, self).gene_api_declaration()} """ - def gene_output(self, - out_dtype_list, - out_tensor_type_list=None, - code_indent='', - inplace_flag=False): + def gene_output( + self, + out_dtype_list, + out_tensor_type_list=None, + code_indent='', + inplace_flag=False, + ): kernel_output = [] output_names = [] output_create = "" @@ -44,15 +45,19 @@ class SparseAPI(ForwardAPI): output_type_map = { 'dense': 'TensorType::DENSE_TENSOR', 'sparse_coo': 'TensorType::SPARSE_COO', - 'sparse_csr': 'TensorType::SPARSE_CSR' + 'sparse_csr': 'TensorType::SPARSE_CSR', } if len(out_dtype_list) == 1: kernel_output.append('kernel_out') output_names.append('kernel_out') - inplace_assign = " = " + self.inplace_map[self.outputs['names'][ - 0]] if inplace_flag and self.inplace_map is not None and self.outputs[ - 'names'][0] in self.inplace_map else "" + inplace_assign = ( + " = " + self.inplace_map[self.outputs['names'][0]] + if inplace_flag + and self.inplace_map is not None + and self.outputs['names'][0] in self.inplace_map + else "" + ) output_create = f""" {return_type} api_output{inplace_assign}; auto* kernel_out = SetSparseKernelOutput(&api_output, {output_type_map[out_dtype_list[0]]});""" @@ -67,8 +72,9 @@ class SparseAPI(ForwardAPI): for out_name in self.outputs['names']: if out_name in self.inplace_map: - output_create = output_create + self.inplace_map[ - out_name] + ', ' + output_create = ( + output_create + self.inplace_map[out_name] + ', ' + ) else: output_create += 'Tensor(), ' output_create = output_create[:-2] + '};' @@ -76,28 +82,30 @@ class SparseAPI(ForwardAPI): for i in range(len(out_dtype_list)): kernel_output.append(f'kernel_out_{i}') output_names.append(f'kernel_out_{i}') - output_create = output_create + f""" + output_create = ( + output_create + + f""" auto* kernel_out_{i} = SetSparseKernelOutput(&std::get<{i}>(api_output), {output_type_map[out_dtype_list[i]]});""" + ) else: raise ValueError( "{} : Output error: the output should not be empty.".format( - self.api)) + self.api + ) + ) return kernel_output, output_names, output_create def gen_sparse_kernel_context(self, kernel_output_names): input_trans_map = { - 'const Tensor&': - 'const phi::TenseBase&', - 'const std::vector&': - 'const std::vector&', - 'const paddle::optional&': - 'paddle::optional' + 'const Tensor&': 'const phi::TenseBase&', + 'const std::vector&': 'const std::vector&', + 'const paddle::optional&': 'paddle::optional', } out_trans_map = { 'Tensor': 'phi::TenseBase*', - 'std::vector': 'std::vector' + 'std::vector': 'std::vector', } input_names = self.inputs['names'] input_infos = self.inputs['input_info'] @@ -111,11 +119,17 @@ class SparseAPI(ForwardAPI): for param in kernel_param: if param in input_names: if param in self.optional_vars: - kernel_context_code = kernel_context_code + f""" + kernel_context_code = ( + kernel_context_code + + f""" kernel_context.EmplaceBackInput({param} ? {param}->impl().get() : nullptr);""" + ) else: - kernel_context_code = kernel_context_code + f""" + kernel_context_code = ( + kernel_context_code + + f""" kernel_context.EmplaceBackInput({param}.impl().get());""" + ) continue if param in attr_names: @@ -128,12 +142,18 @@ class SparseAPI(ForwardAPI): param = str(param).lower() else: param + str(param) + ", " - kernel_context_code = kernel_context_code + f""" + kernel_context_code = ( + kernel_context_code + + f""" kernel_context.EmplaceBackAttr({param});""" + ) for out_name in kernel_output_names: - kernel_context_code = kernel_context_code + f""" + kernel_context_code = ( + kernel_context_code + + f""" kernel_context.EmplaceBackOutput({out_name});""" + ) return kernel_context_code @@ -143,20 +163,25 @@ class SparseAPI(ForwardAPI): attr_names = self.attrs['names'] infer_meta = self.infer_meta - infer_meta_params = infer_meta['param'] if infer_meta[ - 'param'] is not None else input_names + attr_names + infer_meta_params = ( + infer_meta['param'] + if infer_meta['param'] is not None + else input_names + attr_names + ) create_input_var_code = "" tensor_type_map = { 'dense': 'phi::DenseTensor', 'sparse_coo': 'phi::SparseCooTensor', - 'sparse_csr': 'phi::SparseCsrTensor' + 'sparse_csr': 'phi::SparseCsrTensor', } for param in infer_meta_params: if param in input_names: var_name = "auto " + PREFIX_TENSOR_NAME + param + " = " if self.inputs['input_info'][param] == "const Tensor&": - create_input_var_code = create_input_var_code + var_name + param + ".impl();\n" + create_input_var_code = ( + create_input_var_code + var_name + param + ".impl();\n" + ) elif param in self.optional_vars: tensor_type = 'phi::DenseTensor' for name, input_type in zip(input_names, input_types): @@ -164,17 +189,35 @@ class SparseAPI(ForwardAPI): tensor_type = tensor_type_map[input_type] break optional_var = "paddle::optional<" + tensor_type + ">(" - create_input_var_code = create_input_var_code + var_name + param + " ? " + optional_var + "*static_cast<" + tensor_type + "*>((*" + param + ").impl().get())) : " + optional_var + "paddle::none);\n" + create_input_var_code = ( + create_input_var_code + + var_name + + param + + " ? " + + optional_var + + "*static_cast<" + + tensor_type + + "*>((*" + + param + + ").impl().get())) : " + + optional_var + + "paddle::none);\n" + ) return f"""{create_input_var_code}""" def gen_sparse_kernel_code(self, kernel_name, inplace_flag=False): _, kernel_output_names, output_create = self.gene_output( - self.kernel['dispatch'][kernel_name][1], None, '', inplace_flag) + self.kernel['dispatch'][kernel_name][1], None, '', inplace_flag + ) kernel_context_code = self.gen_sparse_kernel_context( - kernel_output_names) - return_code = "" if len( - self.gene_return_code()) == 0 else " " + self.gene_return_code() + kernel_output_names + ) + return_code = ( + "" + if len(self.gene_return_code()) == 0 + else " " + self.gene_return_code() + ) return f""" VLOG(6) << "{self.api} api sparse kernel key: [" << kernel_backend << ", " << kernel_layout << ", "<< kernel_data_type << "]"; auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError( @@ -192,12 +235,13 @@ class SparseAPI(ForwardAPI): {return_code}""" def get_condition_code(self, kernel_name): - assert self.kernel['dispatch'][kernel_name], \ - f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'conv3d' in sparse_ops.yaml." + assert self.kernel['dispatch'][ + kernel_name + ], f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'conv3d' in sparse_ops.yaml." input_types = self.kernel['dispatch'][kernel_name][0] sparse_type_map = { 'sparse_coo': 'DataLayout::SPARSE_COO', - 'sparse_csr': 'DataLayout::SPARSE_CSR' + 'sparse_csr': 'DataLayout::SPARSE_CSR', } condition_list = [] tensor_type_list = [] @@ -214,10 +258,12 @@ class SparseAPI(ForwardAPI): else: if in_type == 'sparse_coo': condition_list.append( - f"{self.inputs['names'][i]}.is_sparse_coo_tensor()") + f"{self.inputs['names'][i]}.is_sparse_coo_tensor()" + ) else: condition_list.append( - f"{self.inputs['names'][i]}.is_sparse_csr_tensor()") + f"{self.inputs['names'][i]}.is_sparse_csr_tensor()" + ) tensor_type_list.append(in_type) self.inputs['tensor_type'] = tensor_type_list @@ -237,10 +283,11 @@ class SparseAPI(ForwardAPI): kernel_dispatch_code = f"{self.gene_kernel_select()}\n" for kernel_name in self.kernel['func']: kernel_dispatch_code += self.gene_dispatch_code( - kernel_name, inplace_flag) + kernel_name, inplace_flag + ) return f""" -PADDLE_API {self.get_return_type()} {api_func_name}({self.get_define_args()}) {{ +PADDLE_API {self.get_return_type(inplace_flag)} {api_func_name}({self.get_define_args(inplace_flag)}) {{ {kernel_dispatch_code} PADDLE_THROW(phi::errors::Unimplemented( "The kernel of ({self.api}) for input tensors is unimplemented, please check the type of input tensors.")); @@ -283,17 +330,20 @@ def source_include(header_file_path): def api_namespace(): - return (""" + return ( + """ namespace paddle { namespace experimental { namespace sparse { -""", """ +""", + """ } // namespace sparse } // namespace experimental } // namespace paddle -""") +""", + ) def generate_api(api_yaml_path, header_file_path, source_file_path): @@ -329,18 +379,25 @@ def generate_api(api_yaml_path, header_file_path, source_file_path): def main(): parser = argparse.ArgumentParser( - description='Generate PaddlePaddle C++ Sparse API files') - parser.add_argument('--api_yaml_path', - help='path to sparse api yaml file', - default='paddle/phi/api/yaml/sparse_ops.yaml') - - parser.add_argument('--api_header_path', - help='output of generated api header code file', - default='paddle/phi/api/include/sparse_api.h') - - parser.add_argument('--api_source_path', - help='output of generated api source code file', - default='paddle/phi/api/lib/sparse_api.cc') + description='Generate PaddlePaddle C++ Sparse API files' + ) + parser.add_argument( + '--api_yaml_path', + help='path to sparse api yaml file', + default='paddle/phi/api/yaml/sparse_ops.yaml', + ) + + parser.add_argument( + '--api_header_path', + help='output of generated api header code file', + default='paddle/phi/api/include/sparse_api.h', + ) + + parser.add_argument( + '--api_source_path', + help='output of generated api source code file', + default='paddle/phi/api/lib/sparse_api.cc', + ) options = parser.parse_args() diff --git a/paddle/phi/api/yaml/sparse_backward.yaml b/paddle/phi/api/yaml/sparse_backward.yaml index 13b44546264..5bb52b92168 100644 --- a/paddle/phi/api/yaml/sparse_backward.yaml +++ b/paddle/phi/api/yaml/sparse_backward.yaml @@ -367,6 +367,18 @@ func : subtract_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}, subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr} +- 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) + output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) + infer_meta : + func : GeneralTernaryGradInferMeta + param : [x, scale, bias] + kernel : + func : sync_batch_norm_coo_grad{sparse_coo, dense, dense, dense, dense, dense, sparse_coo -> sparse_coo, dense, dense} + data_type : out_grad + optional : reserve_space + - backward_op : tan_grad forward : tan(Tensor x) -> Tensor(out) args : (Tensor x, Tensor out_grad) diff --git a/paddle/phi/api/yaml/sparse_ops.yaml b/paddle/phi/api/yaml/sparse_ops.yaml index 2d96b22e5a2..5ef29bdcb16 100644 --- a/paddle/phi/api/yaml/sparse_ops.yaml +++ b/paddle/phi/api/yaml/sparse_ops.yaml @@ -95,6 +95,7 @@ kernel : func : batch_norm_coo {sparse_coo, dense, dense, dense, dense -> sparse_coo, dense, dense, dense, dense, dense} data_type : x + view : (mean -> mean_out), (variance -> variance_out) backward : batch_norm_grad - op : cast @@ -378,7 +379,8 @@ args : (Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) output : Tensor(out) infer_meta : - func : AddmmInferMeta + func : UnchangedInferMeta + param : [input] kernel : func : addmm_csr_dense {dense, sparse_csr, dense -> dense}, addmm_csr_csr {sparse_csr, sparse_csr, sparse_csr -> sparse_csr}, @@ -480,6 +482,17 @@ layout : x backward : transpose_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) + output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space) + infer_meta : + func : BatchNormInferMeta + kernel : + func : sync_batch_norm_coo{sparse_coo, dense, dense, dense, dense -> sparse_coo, dense, dense, dense, dense, dense} + data_type : x + backward : sync_batch_norm_grad + inplace : (mean -> mean_out), (variance -> variance_out) + - op : reshape args : (Tensor x, IntArray shape) output : Tensor(out) diff --git a/paddle/phi/kernels/sparse/empty_kernel.cc b/paddle/phi/kernels/sparse/empty_kernel.cc index 96a7301c589..49a377ca70f 100644 --- a/paddle/phi/kernels/sparse/empty_kernel.cc +++ b/paddle/phi/kernels/sparse/empty_kernel.cc @@ -31,6 +31,7 @@ void EmptyLikeCooKernel(const Context& dev_ctx, const DenseTensor& x_values = x.values(); DenseTensor* out_values = out->mutable_values(); out_values->Resize(x_values.dims()); + out->set_meta(x.meta()); dev_ctx.template Alloc(out_values); } @@ -44,6 +45,7 @@ void EmptyLikeCsrKernel(const Context& dev_ctx, const DenseTensor& x_values = x.values(); DenseTensor* out_values = out->mutable_values(); out_values->Resize(x_values.dims()); + out->set_meta(x.meta()); dev_ctx.template Alloc(out_values); } diff --git a/paddle/phi/kernels/sparse/gpu/coalesce_kernel.cu b/paddle/phi/kernels/sparse/gpu/coalesce_kernel.cu index d369c0ecd99..a348c6aa11e 100644 --- a/paddle/phi/kernels/sparse/gpu/coalesce_kernel.cu +++ b/paddle/phi/kernels/sparse/gpu/coalesce_kernel.cu @@ -169,6 +169,7 @@ void CoalesceGPUKernel(const GPUContext& dev_ctx, indexs_ptr, const_dims, out_nnz, sparse_dim, out_indices.data()); out->SetMember(out_indices, out_values, x.dims(), true); + out->SetIndicesDict(x.GetIndicesDict()); } template diff --git a/paddle/phi/kernels/sparse/gpu/sync_batch_norm_grad_kernel.cu b/paddle/phi/kernels/sparse/gpu/sync_batch_norm_grad_kernel.cu new file mode 100644 index 00000000000..e0805578a0f --- /dev/null +++ b/paddle/phi/kernels/sparse/gpu/sync_batch_norm_grad_kernel.cu @@ -0,0 +1,85 @@ +/* Copyright (c) 2022 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/sparse/sync_batch_norm_grad_kernel.h" +#include "paddle/phi/core/kernel_registry.h" +#include "paddle/phi/kernels/empty_kernel.h" +#include "paddle/phi/kernels/sparse/empty_kernel.h" +#include "paddle/phi/kernels/sync_batch_norm_grad_kernel.h" + +namespace phi { +namespace sparse { + +template +void SyncBatchNormCooGradKernel( + const Context& dev_ctx, + const SparseCooTensor& x, + const DenseTensor& scale, + const DenseTensor& bias, + const DenseTensor& saved_mean, + const DenseTensor& saved_variance, + const paddle::optional& reserve_space, + const SparseCooTensor& y_grad, + float momentum, + float epsilon, + const std::string& data_layout, + bool is_test, + bool use_global_stats, + bool trainable_statistics, + bool fuse_with_relu, + SparseCooTensor* x_grad, + DenseTensor* scale_grad, + DenseTensor* bias_grad) { + EmptyLikeCooKernel(dev_ctx, x, x_grad); + *scale_grad = phi::EmptyLike(dev_ctx, scale); + *bias_grad = phi::EmptyLike(dev_ctx, bias); + phi::SyncBatchNormGradKernel(dev_ctx, + x.values(), + scale, + bias, + saved_mean, + saved_variance, + reserve_space, + y_grad.values(), + momentum, + epsilon, + data_layout, + is_test, + use_global_stats, + trainable_statistics, + fuse_with_relu, + x_grad->mutable_values(), + scale_grad, + bias_grad); +} + +} // namespace sparse +} // namespace phi + +#ifdef PADDLE_WITH_HIP +PD_REGISTER_KERNEL(sync_batch_norm_coo_grad, + GPU, + ALL_LAYOUT, + phi::sparse::SyncBatchNormCooGradKernel, + float, + phi::dtype::float16) {} +#else +PD_REGISTER_KERNEL(sync_batch_norm_coo_grad, + GPU, + ALL_LAYOUT, + phi::sparse::SyncBatchNormCooGradKernel, + float, + double, + phi::dtype::float16) {} +#endif diff --git a/paddle/phi/kernels/sparse/gpu/sync_batch_norm_kernel.cu b/paddle/phi/kernels/sparse/gpu/sync_batch_norm_kernel.cu new file mode 100644 index 00000000000..a518148f2c9 --- /dev/null +++ b/paddle/phi/kernels/sparse/gpu/sync_batch_norm_kernel.cu @@ -0,0 +1,84 @@ +/* Copyright (c) 2022 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/sparse/sync_batch_norm_kernel.h" +#include "paddle/phi/core/kernel_registry.h" +#include "paddle/phi/kernels/sparse/empty_kernel.h" +#include "paddle/phi/kernels/sync_batch_norm_kernel.h" + +namespace phi { +namespace sparse { + +template +void SyncBatchNormCooKernel(const Context& dev_ctx, + const SparseCooTensor& x, + const DenseTensor& scale, + const DenseTensor& bias, + const DenseTensor& mean, + const DenseTensor& variance, + float momentum, + float epsilon, + const std::string& data_layout, + bool is_test, + bool use_global_stats, + bool trainable_statistics, + bool fuse_with_relu, + SparseCooTensor* y, + DenseTensor* mean_out, + DenseTensor* variance_out, + DenseTensor* saved_mean, + DenseTensor* saved_variance, + DenseTensor* reserve_space) { + EmptyLikeCooKernel(dev_ctx, x, y); + phi::SyncBatchNormKernel(dev_ctx, + x.values(), + scale, + bias, + mean, + variance, + momentum, + epsilon, + data_layout, + is_test, + use_global_stats, + trainable_statistics, + fuse_with_relu, + y->mutable_values(), + mean_out, + variance_out, + saved_mean, + saved_variance, + reserve_space); + y->SetIndicesDict(x.GetIndicesDict()); +} + +} // namespace sparse +} // namespace phi + +#ifdef PADDLE_WITH_HIP +PD_REGISTER_KERNEL(sync_batch_norm_coo, + GPU, + ALL_LAYOUT, + phi::sparse::SyncBatchNormCooKernel, + float, + phi::dtype::float16) {} +#else +PD_REGISTER_KERNEL(sync_batch_norm_coo, + GPU, + ALL_LAYOUT, + phi::sparse::SyncBatchNormCooKernel, + float, + double, + phi::dtype::float16) {} +#endif diff --git a/paddle/phi/kernels/sparse/impl/unary_kernel_impl.h b/paddle/phi/kernels/sparse/impl/unary_kernel_impl.h index 9b8b33d4d3a..a4b89fd8132 100644 --- a/paddle/phi/kernels/sparse/impl/unary_kernel_impl.h +++ b/paddle/phi/kernels/sparse/impl/unary_kernel_impl.h @@ -37,6 +37,7 @@ namespace sparse { EmptyLikeCooKernel(dev_ctx, x, out); \ phi::prefix##Kernel( \ dev_ctx, x.non_zero_elements(), out->mutable_non_zero_elements()); \ + out->SetIndicesDict(x.GetIndicesDict()); \ } \ \ template \ @@ -105,6 +106,7 @@ void ScaleCooKernel(const Context& dev_ctx, bias, bias_after_scale, out->mutable_non_zero_elements()); + out->SetIndicesDict(x.GetIndicesDict()); } template @@ -155,6 +157,7 @@ void CastCooKernel(const Context& dev_ctx, meta.set_dtype(value_dtype); phi::CastKernel(dev_ctx, x_values, value_dtype, out_values); } + out->SetIndicesDict(x.GetIndicesDict()); } template diff --git a/paddle/phi/kernels/sparse/sync_batch_norm_grad_kernel.h b/paddle/phi/kernels/sparse/sync_batch_norm_grad_kernel.h new file mode 100644 index 00000000000..9591e6f035c --- /dev/null +++ b/paddle/phi/kernels/sparse/sync_batch_norm_grad_kernel.h @@ -0,0 +1,47 @@ +/* Copyright (c) 2022 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. */ + +#pragma once + +#include + +#include "paddle/phi/core/dense_tensor.h" +#include "paddle/phi/core/sparse_coo_tensor.h" + +namespace phi { +namespace sparse { + +template +void SyncBatchNormCooGradKernel( + const Context& dev_ctx, + const SparseCooTensor& x, + const DenseTensor& scale, + const DenseTensor& bias, + const DenseTensor& saved_mean, + const DenseTensor& saved_variance, + const paddle::optional& reserve_space, + const SparseCooTensor& y_grad, + float momentum, + float epsilon, + const std::string& data_layout, + bool is_test, + bool use_global_stats, + bool trainable_statistics, + bool fuse_with_relu, + SparseCooTensor* x_grad, + DenseTensor* scale_grad, + DenseTensor* bias_grad); + +} // namespace sparse +} // namespace phi diff --git a/paddle/phi/kernels/sparse/sync_batch_norm_kernel.h b/paddle/phi/kernels/sparse/sync_batch_norm_kernel.h new file mode 100644 index 00000000000..7ee4baa1079 --- /dev/null +++ b/paddle/phi/kernels/sparse/sync_batch_norm_kernel.h @@ -0,0 +1,47 @@ +/* Copyright (c) 2022 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. */ + +#pragma once + +#include + +#include "paddle/phi/core/dense_tensor.h" +#include "paddle/phi/core/sparse_coo_tensor.h" + +namespace phi { +namespace sparse { + +template +void SyncBatchNormCooKernel(const Context& dev_ctx, + const SparseCooTensor& x, + const DenseTensor& scale, + const DenseTensor& bias, + const DenseTensor& mean, + const DenseTensor& variance, + float momentum, + float epsilon, + const std::string& data_layout, + bool is_test, + bool use_global_stats, + bool trainable_statistics, + bool fuse_with_relu, + SparseCooTensor* y, + DenseTensor* mean_out, + DenseTensor* variance_out, + DenseTensor* saved_mean, + DenseTensor* saved_variance, + DenseTensor* reserve_space); + +} // namespace sparse +} // namespace phi diff --git a/python/paddle/sparse/nn/layer/norm.py b/python/paddle/sparse/nn/layer/norm.py index 617ea1a78d2..7166906f11f 100644 --- a/python/paddle/sparse/nn/layer/norm.py +++ b/python/paddle/sparse/nn/layer/norm.py @@ -323,13 +323,22 @@ class SyncBatchNorm(paddle.nn.SyncBatchNorm): ) def forward(self, x): - assert ( - x.is_sparse_coo() - ), "SyncBatchNorm only support SparseTensor in COO format." - out = super(SyncBatchNorm, self).forward(x.values()) - return paddle.sparse.sparse_coo_tensor( - x.indices(), out, shape=x.shape, stop_gradient=x.stop_gradient + self._check_data_format() + sync_batch_norm_out, _, _, _, _, _ = _C_ops.sparse_sync_batch_norm_( + x, + self.weight, + self.bias, + self._mean, + self._variance, + self._momentum, + self._epsilon, + self._data_format, + not self.training, + False, + False, + False, ) + return sync_batch_norm_out @classmethod def convert_sync_batchnorm(cls, layer): -- GitLab