Revert "[Eager] coreops to 495 (#37926)"

This reverts commit aff7397b.

paddle/fluid/eager/tests/performance_tests/CMakeLists.txt

-cc_library(performance_benchmark_utils SRCS benchmark_utils.cc DEPS ${eager_deps} ${fluid_deps} ${generated_deps} eager_scale scale_node scale_op matmul_v2_op dygraph_function)
+cc_library(performance_benchmark_utils SRCS benchmark_utils.cc DEPS ${eager_deps} ${fluid_deps} ${generated_deps} eager_scale scale_node scale_op matmul_v2_op)
 
 cc_test(test_egr_performance_benchmark_eager_cpu SRCS benchmark_eager_cpu.cc DEPS performance_benchmark_utils ${eager_deps} ${fluid_deps})
 cc_test(test_egr_performance_benchmark_fluid_cpu SRCS benchmark_fluid_cpu.cc DEPS performance_benchmark_utils ${eager_deps} ${fluid_deps})

paddle/fluid/pybind/eager_op_function_generator.cc

@@ -32,502 +32,8 @@
 #endif
 #include "paddle/fluid/pybind/op_function_generator.h"
 
-std::set<std::string> gen_list = {
-    "sigmoid",
-    "matmul_v2",
-    "reduce_sum",
-    "elementwise_add",
-    "rsqrt",
-    "multihead_matmul",
-    "addmm",
-    "gru",
-    "round",
-    "push_dense",
-    "rank_attention",
-    "fused_embedding_fc_lstm",
-    "where_index",
-    "bicubic_interp",
-    "arg_min",
-    "tile",
-    "bilinear_tensor_product",
-    "ctc_align",
-    "pow2_decay_with_linear_warmup",
-    "marker",
-    "split",
-    "fc",
-    "clear_float_status",
-    "load",
-    "elementwise_max",
-    "adadelta",
-    "sparse_momentum",
-    "tan",
-    "adam",
-    "fsp",
-    "where",
-    "logical_xor",
-    "multiclass_nms3",
-    "one_hot_v2",
-    "sequence_softmax",
-    "affine_channel",
-    "triangular_solve",
-    "sequence_topk_avg_pooling",
-    "space_to_depth",
-    "reverse",
-    "fused_embedding_eltwise_layernorm",
-    "expand_v2",
-    "lgamma",
-    "solve",
-    "deformable_psroi_pooling",
-    "instance_norm",
-    "decode_jpeg",
-    "gather_nd",
-    "reduce_prod",
-    "matrix_rank",
-    "asin",
-    "lstmp",
-    "iou_similarity",
-    "huber_loss",
-    "one_hot",
-    "sequence_slice",
-    "lookup_table",
-    "softplus",
-    "depthwise_conv2d",
-    "fused_fc_elementwise_layernorm",
-    "sigmoid_cross_entropy_with_logits",
-    "exp",
-    "scatter",
-    "equal_all",
-    "searchsorted",
-    "fusion_squared_mat_sub",
-    "unique",
-    "log",
-    "conv_shift",
-    "smooth_l1_loss",
-    "linear_interp_v2",
-    "momentum",
-    "temporal_shift",
-    "nce",
-    "mv",
-    "proximal_gd",
-    "memcpy_h2d",
-    "add_position_encoding",
-    "cosh",
-    "hash",
-    "grad_add",
-    "sign",
-    "prelu",
-    "linspace",
-    "fill_diagonal",
-    "logsigmoid",
-    "load_combine",
-    "fetch_v2",
-    "randperm",
-    "sequence_scatter",
-    "partial_sum",
-    "relu6",
-    "conv3d",
-    "lstm_unit",
-    "not_equal",
-    "transpose2",
-    "uniform_random_batch_size_like",
-    "unfold",
-    "lrn",
-    "softmax_with_cross_entropy",
-    "isfinite_v2",
-    "bernoulli",
-    "max_pool3d_with_index",
-    "gaussian_random",
-    "flatten2",
-    "matmul",
-    "cvm",
-    "adamax",
-    "masked_select",
-    "range",
-    "bitwise_not",
-    "trace",
-    "multinomial",
-    "modified_huber_loss",
-    "roll",
-    "squared_l2_distance",
-    "conv3d_transpose",
-    "share_data",
-    "fake_quantize_abs_max",
-    "unique_with_counts",
-    "fill",
-    "concat",
-    "fill_zeros_like",
-    "hierarchical_sigmoid",
-    "isinf_v2",
-    "squeeze",
-    "multiclass_nms2",
-    "bpr_loss",
-    "fft_c2c",
-    "bicubic_interp_v2",
-    "reshape",
-    "coalesce_tensor",
-    "roi_align",
-    "reshape2",
-    "reduce_any",
-    "unstack",
-    "scatter_nd_add",
-    "sequence_reshape",
-    "bilateral_slice",
-    "fill_any_like",
-    "empty",
-    "pad_constant_like",
-    "pool2d",
-    "size",
-    "imag",
-    "eigh",
-    "stack",
-    "dgc_momentum",
-    "lamb",
-    "generate_proposals_v2",
-    "bitwise_or",
-    "gru_unit",
-    "fake_channel_wise_quantize_dequantize_abs_max",
-    "sampling_id",
-    "unsqueeze2",
-    "average_accumulates",
-    "sequence_enumerate",
-    "fusion_seqconv_eltadd_relu",
-    "bce_loss",
-    "generate_proposal_labels",
-    "im2sequence",
-    "isinf",
-    "adagrad",
-    "linear_chain_crf",
-    "retinanet_target_assign",
-    "fusion_group",
-    "teacher_student_sigmoid_loss",
-    "random_crop",
-    "lookup_table_v2",
-    "detection_map",
-    "l1_norm",
-    "sqrt",
-    "fused_elemwise_activation",
-    "slogdeterminant",
-    "share_buffer",
-    "bitwise_and",
-    "diag_embed",
-    "unbind",
-    "dropout",
-    "moving_average_abs_max_scale",
-    "beam_search",
-    "log_loss",
-    "greater_than",
-    "kron",
-    "sigmoid_focal_loss",
-    "rmsprop",
-    "conv2d",
-    "uniform_random_inplace",
-    "maxout",
-    "linear_interp",
-    "auc",
-    "logical_or",
-    "batch_norm",
-    "acos",
-    "unpool",
-    "cumprod",
-    "sample_logits",
-    "crop_tensor",
-    "fill_constant",
-    "deformable_conv",
-    "generate_mask_labels",
-    "locality_aware_nms",
-    "expand_as",
-    "matrix_power",
-    "greater_equal",
-    "generate_proposals",
-    "bilinear_interp",
-    "inplace_abn",
-    "softshrink",
-    "mul",
-    "data_norm",
-    "get_tensor_from_selected_rows",
-    "spp",
-    "floor",
-    "gelu",
-    "retinanet_detection_output",
-    "push_dense",
-    "silu",
-    "sequence_erase",
-    "real",
-    "nearest_interp_v2",
-    "dgc_clip_by_norm",
-    "squeeze2",
-    "strided_slice",
-    "conj",
-    "precision_recall",
-    "save",
-    "fusion_seqexpand_concat_fc",
-    "fake_quantize_range_abs_max",
-    "depthwise_conv2d_transpose",
-    "positive_negative_pair",
-    "square",
-    "var_conv_2d",
-    "log1p",
-    "fused_softmax_mask_upper_triangle",
-    "clip_by_norm",
-    "atan2",
-    "box_decoder_and_assign",
-    "fft_r2c",
-    "roi_pool",
-    "overlap_add",
-    "fill_constant_batch_size_like",
-    "fill_any",
-    "dequantize_log",
-    "max_pool2d_with_index",
-    "pad3d",
-    "norm",
-    "viterbi_decode",
-    "mish",
-    "box_coder",
-    "flatten",
-    "elementwise_mod",
-    "margin_cross_entropy",
-    "logical_and",
-    "pow",
-    "stanh",
-    "label_smooth",
-    "merged_momentum",
-    "ascend_trigger",
-    "fused_feedforward",
-    "rpn_target_assign",
-    "roi_perspective_transform",
-    "expand",
-    "prroi_pool",
-    "pool3d",
-    "memcpy",
-    "distribute_fpn_proposals",
-    "frame",
-    "bincount",
-    "shape",
-    "group_norm",
-    "resnet_unit",
-    "sequence_expand_as",
-    "cos_sim",
-    "eigvals",
-    "save_combine",
-    "class_center_sample",
-    "read_file",
-    "isfinite",
-    "arg_max",
-    "equal",
-    "fake_dequantize_max_abs",
-    "qr",
-    "anchor_generator",
-    "layer_norm",
-    "merge_selected_rows",
-    "less_equal",
-    "rnn",
-    "fusion_lstm",
-    "lars_momentum",
-    "hard_sigmoid",
-    "isnan",
-    "elementwise_floordiv",
-    "correlation",
-    "histogram",
-    "gather_tree",
-    "segment_pool",
-    "sync_batch_norm",
-    "fusion_repeated_fc_relu",
-    "nop",
-    "expand_as_v2",
-    "filter_by_instag",
-    "nll_loss",
-    "dot",
-    "scale",
-    "ncclBcast",
-    "shuffle_batch",
-    "ncclReduce",
-    "diag",
-    "multiplex",
-    "leaky_relu",
-    "allclose",
-    "adamw",
-    "elementwise_pow",
-    "prior_box",
-    "p_norm",
-    "unique_consecutive",
-    "lod_reset",
-    "pad",
-    "sequence_conv",
-    "log10",
-    "set_value",
-    "bitwise_xor",
-    "center_loss",
-    "randint",
-    "attention_lstm",
-    "uniform_random",
-    "slice",
-    "meshgrid",
-    "hard_swish",
-    "sin",
-    "mean_iou",
-    "pad2d",
-    "inverse",
-    "spectral_norm",
-    "shuffle_channel",
-    "psroi_pool",
-    "seed",
-    "ceil",
-    "eig",
-    "reduce_min",
-    "cos",
-    "ncclAllReduce",
-    "cudnn_lstm",
-    "digamma",
-    "assign_value",
-    "increment",
-    "tdm_sampler",
-    "fused_softmax_mask",
-    "sequence_reverse",
-    "eigvalsh",
-    "diagonal",
-    "trunc",
-    "log2",
-    "tanh",
-    "yolov3_loss",
-    "graph_send_recv",
-    "accuracy",
-    "atan",
-    "less_than",
-    "unsqueeze",
-    "crf_decoding",
-    "log_softmax",
-    "ftrl",
-    "matrix_nms",
-    "top_k_v2",
-    "cast",
-    "tanh_shrink",
-    "hard_shrink",
-    "multiclass_nms",
-    "fusion_transpose_flatten_concat",
-    "sequence_unpad",
-    "fused_elemwise_add_activation",
-    "frobenius_norm",
-    "crop",
-    "cross_entropy2",
-    "skip_layernorm",
-    "tdm_child",
-    "fused_embedding_seq_pool",
-    "erf",
-    "conv2d_inception_fusion",
-    "trilinear_interp",
-    "logsumexp",
-    "fusion_seqpool_concat",
-    "alloc_float_status",
-    "sequence_concat",
-    "fusion_seqpool_cvm_concat",
-    "similarity_focus",
-    "argsort",
-    "sequence_expand",
-    "sgd",
-    "fused_bn_add_activation",
-    "bilinear_interp_v2",
-    "clip",
-    "deformable_conv_v1",
-    "hinge_loss",
-    "determinant",
-    "conv2d_transpose",
-    "memcpy_d2h",
-    "softsign",
-    "fake_quantize_dequantize_abs_max",
-    "broadcast_tensors",
-    "grid_sampler",
-    "fft_c2r",
-    "pyramid_hash",
-    "fake_quantize_dequantize_moving_average_abs_max",
-    "multi_dot",
-    "sequence_pool",
-    "transpose",
-    "top_k",
-    "dist",
-    "affine_grid",
-    "gaussian_random_batch_size_like",
-    "fake_channel_wise_dequantize_max_abs",
-    "reciprocal",
-    "sequence_mask",
-    "fill_diagonal_tensor",
-    "abs",
-    "partial_concat",
-    "elu",
-    "index_select",
-    "row_conv",
-    "cross",
-    "elementwise_mul",
-    "decayed_adagrad",
-    "bipartite_match",
-    "fake_quantize_moving_average_abs_max",
-    "mine_hard_examples",
-    "target_assign",
-    "lstm",
-    "truncated_gaussian_random",
-    "match_matrix_tensor",
-    "elementwise_div",
-    "kldiv_loss",
-    "cumsum",
-    "sum",
-    "proximal_adagrad",
-    "shard_index",
-    "selu",
-    "mean",
-    "gumbel_softmax",
-    "sequence_pad",
-    "tree_conv",
-    "assign",
-    "flatten_contiguous_range",
-    "tril_triu",
-    "brelu",
-    "celu",
-    "reduce_mean",
-    "sinh",
-    "rank_loss",
-    "reduce_max",
-    "fusion_gru",
-    "fill_zeros_like2",
-    "expm1",
-    "squared_l2_norm",
-    "elementwise_sub",
-    "margin_rank_loss",
-    "faster_tokenizer",
-    "relu",
-    "is_empty",
-    "reduce_all",
-    "edit_distance",
-    "bmm",
-    "yolo_box",
-    "soft_relu",
-    "density_prior_box",
-    "eye",
-    "swish",
-    "cross_entropy",
-    "dpsgd",
-    "cholesky",
-    "batch_fc",
-    "nearest_interp",
-    "gather",
-    "trilinear_interp_v2",
-    "box_clip",
-    "isnan_v2",
-    "softmax",
-    "conv2d_fusion",
-    "fused_batch_norm_act",
-    "get_float_status",
-    "index_sample",
-    "elementwise_min",
-    "logical_not",
-    "collect_fpn_proposals",
-    "pixel_shuffle",
-    "thresholded_relu",
-    "polygon_box_transform",
-    "lookup_table_dequant",
-    "warpctc",
-    "fake_channel_wise_quantize_abs_max",
-    "dequantize_abs_max",
-    "svd",
-    "flip"};
+std::set<std::string> gen_list = {"elementwise_add", "reduce_sum", "matmul_v2",
+                                  "sigmoid"};
 
 // clang-format off
 const char* OUT_INITIALIZER_TEMPLATE =
@@ -672,7 +178,15 @@ std::string GenerateOpFunctionsBody(
     ins_cast_str += paddle::string::Sprintf(in_cast_type, in_name, op_type,
                                             in_name, arg_idx++, dispensable);
 
-    call_api_str += in_name + ", ";
+    if (input.dispensable()) {
+      const auto in_template = input.duplicable()
+                                   ? INPUT_INITIALIZER_TEMPLATE_WITH_NULL_LIST
+                                   : INPUT_INITIALIZER_TEMPLATE_WITH_NULL;
+      ins_initializer_with_null +=
+          paddle::string::Sprintf(in_template, in_name, in_name, in_name);
+    } else {
+      call_api_str += in_name + ", ";
+    }
   }
 
   if (!input_args.empty() && input_args.back() == ',') {
@@ -723,8 +237,6 @@ std::string GenerateOpFunctionsBody(
       auto dispensable = output.dispensable() ? "true" : "false";
       ins_cast_str += paddle::string::Sprintf(in_cast_type, out_name, op_type,
                                               out_name, arg_idx++, dispensable);
-
-      // call_api_str += out_name + ", ";
     } else {
       // There are few Operators that have duplicable output, like `Out` in
       // split op. We need to specify the number of variables for the
@@ -769,9 +281,11 @@ std::string GenerateOpFunctionsBody(
         HANDLE_VIEW_BETWEEN_INPUT_AND_OUTPUT, viwe_input_name, viwe_output_name,
         viwe_input_name, viwe_output_name);
   }
-
-  return_str = "return ToPyObject(out);";
-
+  if (outs_num == 0) {
+    return_str = "Py_INCREF(Py_None);\n    return Py_None;";
+  } else {
+    return_str = "return ToPyObject(out);";
+  }
   std::string function_args = "";
   if (input_args == "") {
     function_args = FUNCTION_ARGS_NO_INPUT;

paddle/fluid/pybind/eager_utils.cc

@@ -370,15 +370,6 @@ PyObject* ToPyObject(const platform::Place& value) {
   return obj.ptr();
 }
 
-PyObject* ToPyObject(const void* value) {
-  if (value == nullptr) {
-    Py_INCREF(Py_None);
-    return Py_None;
-  }
-  PADDLE_THROW(
-      platform::errors::Fatal("ToPyObject do not support void* with value."));
-}
-
 egr::EagerTensor GetEagerTensorFromArgs(const std::string& op_type,
                                         const std::string& arg_name,
                                         PyObject* args, ssize_t arg_idx,

paddle/fluid/pybind/eager_utils.h

@@ -51,7 +51,6 @@ PyObject* ToPyObject(const std::vector<float>& value);
 PyObject* ToPyObject(const std::vector<double>& value);
 PyObject* ToPyObject(const std::vector<egr::EagerTensor>& value);
 PyObject* ToPyObject(const platform::Place& value);
-PyObject* ToPyObject(const void* value);
 
 template <typename Tuple, size_t N>
 struct TupleEagerTensorResult {

paddle/fluid/pybind/pybind.cc

@@ -75,9 +75,7 @@ limitations under the License. */
 #include "paddle/fluid/platform/place.h"
 #include "paddle/fluid/platform/profiler.h"
 #include "paddle/fluid/pybind/cuda_streams_py.h"
-#ifndef PADDLE_ON_INFERENCE
 #include "paddle/fluid/pybind/eager.h"
-#endif
 #include "paddle/fluid/pybind/io.h"
 #include "paddle/utils/none.h"
 #ifdef PADDLE_WITH_ASCEND
@@ -543,9 +541,7 @@ PYBIND11_MODULE(core_avx, m) {
 PYBIND11_MODULE(core_noavx, m) {
 #endif
 
-#ifndef PADDLE_ON_INFERENCE
   BindEager(&m);
-#endif
   BindCudaStream(&m);
 
   // Not used, just make sure cpu_info.cc is linked.