From adb61b7bbd936b56509f4a744fd06419ade30c12 Mon Sep 17 00:00:00 2001 From: zyfncg Date: Fri, 12 Aug 2022 14:34:18 +0800 Subject: [PATCH] Remove some custom_impl api (#45066) * remove some custom_impl api and make them generated by yaml completely * delete useless code * fix adamw bug * fix infermeta * revert adamw * polish code * fix bug --- paddle/phi/api/lib/CMakeLists.txt | 3 +- paddle/phi/api/lib/api_custom_impl.cc | 410 ----------------------- paddle/phi/api/lib/api_custom_impl.h | 54 --- paddle/phi/api/yaml/legacy_api.yaml | 12 +- paddle/phi/api/yaml/legacy_backward.yaml | 14 +- paddle/phi/infermeta/binary.cc | 1 - 6 files changed, 24 insertions(+), 470 deletions(-) diff --git a/paddle/phi/api/lib/CMakeLists.txt b/paddle/phi/api/lib/CMakeLists.txt index 845af87fd5..dfbf5aaba4 100644 --- a/paddle/phi/api/lib/CMakeLists.txt +++ b/paddle/phi/api/lib/CMakeLists.txt @@ -337,7 +337,8 @@ add_custom_command( ${api_yaml_file} ${legacy_api_yaml_file} --wrapped_infermeta_header_path ${wrapped_infermeta_header_file} --wrapped_infermeta_source_path ${wrapped_infermeta_source_file} - DEPENDS ${api_yaml_file} ${wrapped_infermeta_gen_file} ${api_gen_base} + DEPENDS ${api_yaml_file} ${legacy_api_yaml_file} ${wrapped_infermeta_gen_file} + ${api_gen_base} VERBATIM) cc_library( diff --git a/paddle/phi/api/lib/api_custom_impl.cc b/paddle/phi/api/lib/api_custom_impl.cc index 056b9d79c8..f23db10ac7 100644 --- a/paddle/phi/api/lib/api_custom_impl.cc +++ b/paddle/phi/api/lib/api_custom_impl.cc @@ -198,416 +198,6 @@ std::tuple adamw_impl( return api_output; } -Tensor conv2d_impl(const Tensor& input, - const Tensor& filter, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search) { - Backend kernel_backend = Backend::UNDEFINED; - DataLayout kernel_layout = DataLayout::UNDEFINED; - DataType kernel_data_type = DataType::UNDEFINED; - - kernel_data_type = ParseDataType(input); - - if (kernel_backend == Backend::UNDEFINED || - kernel_layout == DataLayout::UNDEFINED || - kernel_data_type == DataType::UNDEFINED) { - auto kernel_key_set = ParseKernelKeyByInputArgs(input, filter); - auto kernel_key = kernel_key_set.GetHighestPriorityKernelKey(); - if (kernel_backend == Backend::UNDEFINED) { - kernel_backend = kernel_key.backend(); - } - if (kernel_layout == DataLayout::UNDEFINED) { - kernel_layout = kernel_key.layout(); - } - if (kernel_data_type == DataType::UNDEFINED) { - kernel_data_type = kernel_key.dtype(); - } - } - - VLOG(6) << "conv2d API kernel key: [" << kernel_backend << ", " - << kernel_layout << ", " << kernel_data_type << "]"; - auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError( - "conv2d", {kernel_backend, kernel_layout, kernel_data_type}, true); - const auto& kernel = kernel_result.kernel; - VLOG(6) << "conv2d API kernel: " << kernel; - - auto* dev_ctx = GetDeviceContextByBackend(kernel_backend); - - phi::TensorArgDef args0 = kernel.InputAt(0); - phi::TensorArgDef args1 = kernel.InputAt(1); - if (kernel_backend == Backend::GPU) { - args0.backend = Backend::GPU; - args1.backend = Backend::GPU; - } - - auto input_input = PrepareData(input, args0, {}); - auto input_filter = PrepareData(filter, args1, {}); - - Tensor api_output; - auto kernel_out = SetKernelOutput(kernel_backend, &api_output); - phi::MetaTensor meta_out(kernel_out); - - phi::ConvInferMeta(MakeMetaTensor(*input_input), - MakeMetaTensor(*input_filter), - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - &meta_out); - - using kernel_signature = void (*)(const platform::DeviceContext&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const std::vector&, - const std::vector&, - const std::string&, - int, - const std::vector&, - const std::string&, - bool, - int, - bool, - phi::DenseTensor*); - auto* kernel_fn = kernel.GetVariadicKernelFn(); - - { - (*kernel_fn)(*dev_ctx, - *input_input, - *input_filter, - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - kernel_out); - } - - return api_output; -} - -Tensor conv3d_impl(const Tensor& input, - const Tensor& filter, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search) { - Backend kernel_backend = Backend::UNDEFINED; - DataLayout kernel_layout = DataLayout::UNDEFINED; - DataType kernel_data_type = DataType::UNDEFINED; - - kernel_data_type = ParseDataType(input); - - if (kernel_backend == Backend::UNDEFINED || - kernel_layout == DataLayout::UNDEFINED || - kernel_data_type == DataType::UNDEFINED) { - auto kernel_key_set = ParseKernelKeyByInputArgs(input, filter); - auto kernel_key = kernel_key_set.GetHighestPriorityKernelKey(); - if (kernel_backend == Backend::UNDEFINED) { - kernel_backend = kernel_key.backend(); - } - if (kernel_layout == DataLayout::UNDEFINED) { - kernel_layout = kernel_key.layout(); - } - if (kernel_data_type == DataType::UNDEFINED) { - kernel_data_type = kernel_key.dtype(); - } - } - - VLOG(6) << "conv3d API kernel key: [" << kernel_backend << ", " - << kernel_layout << ", " << kernel_data_type << "]"; - auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError( - "conv3d", {kernel_backend, kernel_layout, kernel_data_type}, true); - const auto& kernel = kernel_result.kernel; - VLOG(6) << "conv3d API kernel: " << kernel; - - auto* dev_ctx = GetDeviceContextByBackend(kernel_backend); - - phi::TensorArgDef args0 = kernel.InputAt(0); - phi::TensorArgDef args1 = kernel.InputAt(1); - if (kernel_backend == Backend::GPU) { - args0.backend = Backend::GPU; - args1.backend = Backend::GPU; - } - - auto input_input = PrepareData(input, args0, {}); - auto input_filter = PrepareData(filter, args1, {}); - - Tensor api_output; - auto kernel_out = SetKernelOutput(kernel_backend, &api_output); - phi::MetaTensor meta_out(kernel_out); - - phi::ConvInferMeta(MakeMetaTensor(*input_input), - MakeMetaTensor(*input_filter), - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - &meta_out); - - using kernel_signature = void (*)(const platform::DeviceContext&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const std::vector&, - const std::vector&, - const std::string&, - int, - const std::vector&, - const std::string&, - bool, - int, - bool, - phi::DenseTensor*); - auto* kernel_fn = kernel.GetVariadicKernelFn(); - - { - (*kernel_fn)(*dev_ctx, - *input_input, - *input_filter, - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - kernel_out); - } - - return api_output; -} - -void conv2d_grad_impl(const Tensor& input, - const Tensor& filter, - const Tensor& out_grad, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search, - Tensor* input_grad, - Tensor* filter_grad) { - Backend kernel_backend = Backend::UNDEFINED; - DataLayout kernel_layout = DataLayout::UNDEFINED; - DataType kernel_data_type = DataType::UNDEFINED; - - if (kernel_backend == Backend::UNDEFINED || - kernel_layout == DataLayout::UNDEFINED || - kernel_data_type == DataType::UNDEFINED) { - auto kernel_key_set = ParseKernelKeyByInputArgs(input, filter, out_grad); - auto kernel_key = kernel_key_set.GetHighestPriorityKernelKey(); - if (kernel_backend == Backend::UNDEFINED) { - kernel_backend = kernel_key.backend(); - } - if (kernel_layout == DataLayout::UNDEFINED) { - kernel_layout = kernel_key.layout(); - } - if (kernel_data_type == DataType::UNDEFINED) { - kernel_data_type = kernel_key.dtype(); - } - } - - VLOG(6) << "conv2d_grad API kernel key: [" << kernel_backend << ", " - << kernel_layout << ", " << kernel_data_type << "]"; - auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError( - "conv2d_grad", {kernel_backend, kernel_layout, kernel_data_type}, true); - const auto& kernel = kernel_result.kernel; - VLOG(6) << "conv2d_grad API kernel: " << kernel; - - auto* dev_ctx = GetDeviceContextByBackend(kernel_backend); - - phi::TensorArgDef args0 = kernel.InputAt(0); - phi::TensorArgDef args1 = kernel.InputAt(1); - phi::TensorArgDef args2 = kernel.InputAt(2); - if (kernel_backend == Backend::GPU) { - args0.backend = Backend::GPU; - args1.backend = Backend::GPU; - args2.backend = Backend::GPU; - } - - auto input_input = PrepareData(input, args0, {}); - auto input_filter = PrepareData(filter, args1, {}); - auto input_out_grad = PrepareData(out_grad, args2, {}); - - auto kernel_out_0 = SetKernelOutput(kernel_backend, input_grad); - auto kernel_out_1 = SetKernelOutput(kernel_backend, filter_grad); - phi::MetaTensor meta_out_0(kernel_out_0); - phi::MetaTensor meta_out_1(kernel_out_1); - - phi::GeneralBinaryGradInferMeta(MakeMetaTensor(*input_input), - MakeMetaTensor(*input_filter), - kernel_out_0 ? &meta_out_0 : nullptr, - kernel_out_1 ? &meta_out_1 : nullptr); - - using kernel_signature = void (*)(const platform::DeviceContext&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const std::vector&, - const std::vector&, - const std::string&, - int, - const std::vector&, - const std::string&, - bool, - int, - bool, - phi::DenseTensor*, - phi::DenseTensor*); - auto* kernel_fn = kernel.GetVariadicKernelFn(); - - { - (*kernel_fn)(*dev_ctx, - *input_input, - *input_filter, - *input_out_grad, - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - kernel_out_0, - kernel_out_1); - } -} - -void conv3d_grad_impl(const Tensor& input, - const Tensor& filter, - const Tensor& out_grad, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search, - Tensor* input_grad, - Tensor* filter_grad) { - Backend kernel_backend = Backend::UNDEFINED; - DataLayout kernel_layout = DataLayout::UNDEFINED; - DataType kernel_data_type = DataType::UNDEFINED; - - if (kernel_backend == Backend::UNDEFINED || - kernel_layout == DataLayout::UNDEFINED || - kernel_data_type == DataType::UNDEFINED) { - auto kernel_key_set = ParseKernelKeyByInputArgs(input, filter, out_grad); - auto kernel_key = kernel_key_set.GetHighestPriorityKernelKey(); - if (kernel_backend == Backend::UNDEFINED) { - kernel_backend = kernel_key.backend(); - } - if (kernel_layout == DataLayout::UNDEFINED) { - kernel_layout = kernel_key.layout(); - } - if (kernel_data_type == DataType::UNDEFINED) { - kernel_data_type = kernel_key.dtype(); - } - } - - VLOG(6) << "conv3d_grad API kernel key: [" << kernel_backend << ", " - << kernel_layout << ", " << kernel_data_type << "]"; - auto kernel_result = phi::KernelFactory::Instance().SelectKernelOrThrowError( - "conv3d_grad", {kernel_backend, kernel_layout, kernel_data_type}, true); - const auto& kernel = kernel_result.kernel; - VLOG(6) << "conv3d_grad API kernel: " << kernel; - - auto* dev_ctx = GetDeviceContextByBackend(kernel_backend); - - phi::TensorArgDef args0 = kernel.InputAt(0); - phi::TensorArgDef args1 = kernel.InputAt(1); - phi::TensorArgDef args2 = kernel.InputAt(2); - if (kernel_backend == Backend::GPU) { - args0.backend = Backend::GPU; - args1.backend = Backend::GPU; - args2.backend = Backend::GPU; - } - - auto input_input = PrepareData(input, args0, {}); - auto input_filter = PrepareData(filter, args1, {}); - auto input_out_grad = PrepareData(out_grad, args2, {}); - - auto kernel_out_0 = SetKernelOutput(kernel_backend, input_grad); - auto kernel_out_1 = SetKernelOutput(kernel_backend, filter_grad); - phi::MetaTensor meta_out_0(kernel_out_0); - phi::MetaTensor meta_out_1(kernel_out_1); - - phi::GeneralBinaryGradInferMeta(MakeMetaTensor(*input_input), - MakeMetaTensor(*input_filter), - kernel_out_0 ? &meta_out_0 : nullptr, - kernel_out_1 ? &meta_out_1 : nullptr); - - using kernel_signature = void (*)(const platform::DeviceContext&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const phi::DenseTensor&, - const std::vector&, - const std::vector&, - const std::string&, - int, - const std::vector&, - const std::string&, - bool, - int, - bool, - phi::DenseTensor*, - phi::DenseTensor*); - auto* kernel_fn = kernel.GetVariadicKernelFn(); - - { - (*kernel_fn)(*dev_ctx, - *input_input, - *input_filter, - *input_out_grad, - strides, - paddings, - paddding_algorithm, - groups, - dilations, - data_format, - use_addto, - workspace_size_MB, - exhaustive_search, - kernel_out_0, - kernel_out_1); - } -} - Tensor copy_to_impl(const Tensor& x, Place place, bool blocking) { Tensor out; copy(x, place, blocking, &out); diff --git a/paddle/phi/api/lib/api_custom_impl.h b/paddle/phi/api/lib/api_custom_impl.h index ef695580a0..b4b09e0e29 100644 --- a/paddle/phi/api/lib/api_custom_impl.h +++ b/paddle/phi/api/lib/api_custom_impl.h @@ -66,30 +66,6 @@ std::tuple batch_norm_impl( bool trainable_statistics, bool fuse_with_relu); -Tensor conv2d_impl(const Tensor& input, - const Tensor& filter, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search); - -Tensor conv3d_impl(const Tensor& input, - const Tensor& filter, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search); - Tensor copy_to_impl(const Tensor& x, Place place, bool blocking); Tensor embedding_impl(const Tensor& x, @@ -116,36 +92,6 @@ std::tuple momentum_impl( ////////////////// Backward(grad) api impls ////////////////////// -void conv2d_grad_impl(const Tensor& input, - const Tensor& filter, - const Tensor& out_grad, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search, - Tensor* input_grad, - Tensor* filter_grad); - -void conv3d_grad_impl(const Tensor& input, - const Tensor& filter, - const Tensor& out_grad, - const std::vector& strides, - const std::vector& paddings, - const std::string& paddding_algorithm, - int groups, - const std::vector& dilations, - const std::string& data_format, - bool use_addto, - int workspace_size_MB, - bool exhaustive_search, - Tensor* input_grad, - Tensor* filter_grad); - void imag_grad_impl(const Tensor& out_grad, Tensor* x_grad); void embedding_grad_impl(const Tensor& x, diff --git a/paddle/phi/api/yaml/legacy_api.yaml b/paddle/phi/api/yaml/legacy_api.yaml index edd5699f6d..88fca869d0 100755 --- a/paddle/phi/api/yaml/legacy_api.yaml +++ b/paddle/phi/api/yaml/legacy_api.yaml @@ -513,7 +513,11 @@ - api : conv2d args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) output : Tensor - invoke : conv2d_impl(input, filter, strides, paddings, paddding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search) + infer_meta : + func : ConvInferMeta + kernel : + func : conv2d + use_gpudnn : true backward : conv2d_grad - api : conv2d_transpose @@ -529,7 +533,11 @@ - api : conv3d args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) output : Tensor - invoke : conv3d_impl(input, filter, strides, paddings, paddding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search) + infer_meta : + func : ConvInferMeta + kernel : + func : conv3d + use_gpudnn : true backward : conv3d_grad - api : conv3d_transpose diff --git a/paddle/phi/api/yaml/legacy_backward.yaml b/paddle/phi/api/yaml/legacy_backward.yaml index 39360232e0..12e2d4ab90 100755 --- a/paddle/phi/api/yaml/legacy_backward.yaml +++ b/paddle/phi/api/yaml/legacy_backward.yaml @@ -438,7 +438,12 @@ forward : conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_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 paddding_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) - invoke : conv2d_grad_impl(input, filter, out_grad, strides, paddings, paddding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search, input_grad, filter_grad) + infer_meta : + func : GeneralBinaryGradInferMeta + param : [input, filter] + kernel : + func : conv2d_grad + use_gpudnn : true backward : conv2d_grad_grad - backward_api : conv2d_grad_grad @@ -478,7 +483,12 @@ forward : conv3d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_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 paddding_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) - invoke : conv3d_grad_impl(input, filter, out_grad, strides, paddings, paddding_algorithm, groups, dilations, data_format, use_addto, workspace_size_MB, exhaustive_search, input_grad, filter_grad) + infer_meta : + func : GeneralBinaryGradInferMeta + param : [input, filter] + kernel : + func : conv3d_grad + use_gpudnn : true backward : conv3d_grad_grad - backward_api : conv3d_grad_grad diff --git a/paddle/phi/infermeta/binary.cc b/paddle/phi/infermeta/binary.cc index 46a76e3dc3..909eee908b 100644 --- a/paddle/phi/infermeta/binary.cc +++ b/paddle/phi/infermeta/binary.cc @@ -2736,5 +2736,4 @@ void Unpool3dInferMeta(const MetaTensor& x, } // namespace phi PD_REGISTER_INFER_META_FN(add_raw, phi::ElementwiseRawInferMeta); -PD_REGISTER_INFER_META_FN(conv2d, phi::ConvInferMeta); PD_REGISTER_INFER_META_FN(conv2d_infer, phi::ConvInferInferMeta); -- GitLab