[Eager] coreops to 495 (#37926)

* refine a test case, test=develop

* publish python c api for eager, test=develop

* revert modify about test_allclose_layer.py, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* delete numpy includes, use pybind11 numpy.h, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* suport eager error msg, and add grad test case, test=develop

* refine, test=develop

* refine, test=develop

* generate eager core ops, only 4 ops, test=develop

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* open 500 list

* refine, test=develop

* refine, test=develop

* refine, test=develop

* fix auto code gen, test=develop

* Enabled generation for Operators without Grad/Inputs/Outputs

* refine, test=develop

* refine, test=develop

* refine, test=develop

* add to pyobject, test=develop

* Resolved operators without input

* merge pr 37837

* refine

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* refine,test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>

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)
+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_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

@@ -32,8 +32,502 @@
 #endif
 #include "paddle/fluid/pybind/op_function_generator.h"
 
-std::set<std::string> gen_list = {"elementwise_add", "reduce_sum", "matmul_v2",
-                                  "sigmoid"};
+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"};
 
 // clang-format off
 const char* OUT_INITIALIZER_TEMPLATE =
@@ -178,15 +672,7 @@ std::string GenerateOpFunctionsBody(
     ins_cast_str += paddle::string::Sprintf(in_cast_type, in_name, op_type,
                                             in_name, arg_idx++, dispensable);
 
-    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 + ", ";
-    }
+    call_api_str += in_name + ", ";
   }
 
   if (!input_args.empty() && input_args.back() == ',') {
@@ -237,6 +723,8 @@ 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
@@ -281,11 +769,9 @@ std::string GenerateOpFunctionsBody(
         HANDLE_VIEW_BETWEEN_INPUT_AND_OUTPUT, viwe_input_name, viwe_output_name,
         viwe_input_name, viwe_output_name);
   }
-  if (outs_num == 0) {
-    return_str = "Py_INCREF(Py_None);\n    return Py_None;";
-  } else {
-    return_str = "return ToPyObject(out);";
-  }
+
+  return_str = "return ToPyObject(out);";
+
   std::string function_args = "";
   if (input_args == "") {
     function_args = FUNCTION_ARGS_NO_INPUT;

paddle/fluid/pybind/eager_utils.cc

@@ -370,6 +370,15 @@ 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

@@ -51,6 +51,7 @@ 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

@@ -75,7 +75,9 @@ 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
@@ -541,7 +543,9 @@ 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.