Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into...

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into feature/combine_open_files_and_double_buffer

CMakeLists.txt

@@ -282,7 +282,3 @@ if(WITH_DOC)
     find_python_module(recommonmark REQUIRED)
     add_subdirectory(doc)
 endif()
-
-if (WITH_CONTRIB)
-    add_subdirectory(paddle/contrib)
-endif()

cmake/inference_lib.cmake

@@ -138,25 +138,24 @@ copy(memory_lib
 
 set(inference_deps paddle_fluid_shared paddle_fluid)
 
-if(WITH_CONTRIB)
-    message(STATUS "installing contrib")
-    set(contrib_dst_dir "${FLUID_INSTALL_DIR}/contrib/inference")
-    if (WITH_ANAKIN AND WITH_GPU)
-        copy(contrib_anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
-            SRCS
-            ${PADDLE_BINARY_DIR}/paddle/contrib/inference/libinference_anakin_api* # compiled anakin api
-            ${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release
-            DSTS ${contrib_dst_dir}/anakin ${contrib_dst_dir}/anakin)
-        list(APPEND inference_deps contrib_anakin_inference_lib)
-   endif()
-
-  copy(contrib_inference_lib DEPS paddle_inference_api paddle_inference_api_shared
-        SRCS ${PADDLE_SOURCE_DIR}/paddle/contrib/inference/paddle_inference_api.h
-        ${PADDLE_BINARY_DIR}/paddle/contrib/inference/libpaddle_inference_api*
-        DSTS ${contrib_dst_dir} ${contrib_dst_dir})
-  list(APPEND inference_deps contrib_inference_lib)
+set(module "inference/api")
+if (WITH_ANAKIN AND WITH_GPU)
+    copy(anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
+        SRCS
+        ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
+        ${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release
+        DSTS ${dst_dir}/inference/anakin ${dst_dir}/inference/anakin)
+     list(APPEND inference_deps anakin_inference_lib)
 endif()
 
+copy(inference_api_lib DEPS paddle_inference_api paddle_inference_api_shared
+  SRCS ${src_dir}/${module}/paddle_inference_api.h 
+       ${src_dir}/${module}/demo_ci
+       ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libpaddle_inference_api*
+  DSTS ${dst_dir}/inference ${dst_dir}/inference ${dst_dir}/inference
+)
+list(APPEND inference_deps inference_api_lib)
+
 set(module "inference")
 copy(inference_lib DEPS ${inference_deps}
   SRCS ${src_dir}/${module}/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.*

doc/v2/api/index_en.rst

@@ -4,7 +4,6 @@ API
 ..  toctree::
     :maxdepth: 1
 
-    overview.rst
     model_configs.rst
     data.rst
     run_logic.rst

paddle/fluid/API.spec

+paddle.fluid.Variable.__init__ ArgSpec(args=['self', 'block', 'type', 'name', 'shape', 'dtype', 'lod_level', 'capacity', 'persistable', 'error_clip', 'stop_gradient', 'is_data'], varargs=None, keywords='kwargs', defaults=(VarType.LOD_TENSOR, None, None, None, None, None, None, None, False, False))
+paddle.fluid.Variable.astype ArgSpec(args=['self', 'dtype'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Variable.set_desc ArgSpec(args=['self', 'input'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Variable.set_error_clip ArgSpec(args=['self', 'error_clip'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Variable.to_string ArgSpec(args=['self', 'throw_on_error', 'with_details'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.Program.__init__ ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.block ArgSpec(args=['self', 'index'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.clone ArgSpec(args=['self', 'for_test'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.Program.copy_data_info_from ArgSpec(args=['self', 'other'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.create_block ArgSpec(args=['self', 'parent_idx'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.Program.current_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.get_desc ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.global_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.inference_optimize ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.list_vars ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.optimized_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.Program.parse_from_string ArgSpec(args=['binary_str'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.prune ArgSpec(args=['self', 'targets'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.rollback ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Program.to_string ArgSpec(args=['self', 'throw_on_error', 'with_details'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.Operator.__init__ ArgSpec(args=['self', 'block', 'desc', 'type', 'inputs', 'outputs', 'attrs'], varargs=None, keywords=None, defaults=(None, None, None, None))
+paddle.fluid.Operator.all_attrs ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.attr ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.attr_type ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.block_attr ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.has_attr ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.has_kernel ArgSpec(args=['self', 'op_type'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.input ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.output ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.rename_input ArgSpec(args=['self', 'old_name', 'new_name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.rename_output ArgSpec(args=['self', 'old_name', 'new_name'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.set_attr ArgSpec(args=['self', 'name', 'val'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Operator.to_string ArgSpec(args=['self', 'throw_on_error'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Parameter.__init__ ArgSpec(args=['self', 'block', 'shape', 'dtype'], varargs=None, keywords='kwargs', defaults=None)
+paddle.fluid.Parameter.astype ArgSpec(args=['self', 'dtype'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Parameter.set_desc ArgSpec(args=['self', 'input'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Parameter.set_error_clip ArgSpec(args=['self', 'error_clip'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Parameter.to_string ArgSpec(args=['self', 'throw_on_error', 'with_details'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.default_startup_program ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
+paddle.fluid.default_main_program ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
+paddle.fluid.program_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.get_var ArgSpec(args=['name', 'program'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.Executor.__init__ ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Executor.as_lodtensor ArgSpec(args=['self', 'data'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Executor.begin_pass ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Executor.end_pass ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Executor.run ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False))
+paddle.fluid.global_scope ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
+paddle.fluid.scope_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.fetch_var ArgSpec(args=['name', 'scope', 'return_numpy'], varargs=None, keywords=None, defaults=(None, True))
+paddle.fluid.Go.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.Go.construct_go_op ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.make_channel ArgSpec(args=['dtype', 'capacity'], varargs=None, keywords=None, defaults=(0,))
+paddle.fluid.channel_send ArgSpec(args=['channel', 'value', 'is_copy'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.channel_recv ArgSpec(args=['channel', 'return_value'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.channel_close ArgSpec(args=['channel'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Select.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.Select.case ArgSpec(args=['self', 'channel_action_fn', 'channel', 'value', 'is_copy'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.Select.default ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Trainer.__init__ ArgSpec(args=['self', 'train_func', 'optimizer_func', 'param_path', 'place', 'parallel', 'checkpoint_config'], varargs=None, keywords=None, defaults=(None, None, False, None))
+paddle.fluid.Trainer.save_params ArgSpec(args=['self', 'param_path'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Trainer.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Trainer.test ArgSpec(args=['self', 'reader', 'feed_order'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.Trainer.train ArgSpec(args=['self', 'num_epochs', 'event_handler', 'reader', 'feed_order'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.BeginEpochEvent.__init__ ArgSpec(args=['self', 'epoch_id'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.EndEpochEvent.__init__ ArgSpec(args=['self', 'epoch_id'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.BeginStepEvent.__init__ ArgSpec(args=['self', 'epoch_id', 'step_id'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.EndStepEvent.__init__ ArgSpec(args=['self', 'epoch_id', 'step_id', 'metrics'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.CheckpointConfig.__init__ ArgSpec(args=['self', 'checkpoint_dir', 'max_num_checkpoints', 'epoch_interval', 'step_interval'], varargs=None, keywords=None, defaults=(None, 3, 1, 10))
+paddle.fluid.Inferencer.__init__ ArgSpec(args=['self', 'infer_func', 'param_path', 'place', 'parallel'], varargs=None, keywords=None, defaults=(None, False))
+paddle.fluid.Inferencer.infer ArgSpec(args=['self', 'inputs', 'return_numpy'], varargs=None, keywords=None, defaults=(True,))
+paddle.fluid.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.DistributeTranspiler.create_splited_vars ArgSpec(args=['self', 'source_var', 'block', 'tag'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.DistributeTranspiler.get_startup_program ArgSpec(args=['self', 'endpoint', 'pserver_program'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.DistributeTranspiler.get_trainer_program ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.DistributeTranspiler.transpile ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True))
+paddle.fluid.InferenceTranspiler.__init__ 
+paddle.fluid.InferenceTranspiler.fuse_batch_norm ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.InferenceTranspiler.fuse_relu_mkldnn ArgSpec(args=['self', 'program'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.InferenceTranspiler.transpile ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.memory_optimize ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level'], varargs=None, keywords=None, defaults=(None, False, 0))
+paddle.fluid.release_memory ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.DistributeTranspilerConfig.__init__ 
+paddle.fluid.ParallelExecutor.__init__ ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id'], varargs=None, keywords='kwargs', defaults=(None, None, None, None, None, 1, 0))
+paddle.fluid.ParallelExecutor.bcast_params ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.ParallelExecutor.run ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True))
+paddle.fluid.ExecutionStrategy.__init__ __init__(self: paddle.fluid.core.ExecutionStrategy) -> None
+paddle.fluid.BuildStrategy.GradientScaleStrategy.__init__ __init__(self: paddle.fluid.core.GradientScaleStrategy, arg0: int) -> None
+paddle.fluid.BuildStrategy.ReduceStrategy.__init__ __init__(self: paddle.fluid.core.ReduceStrategy, arg0: int) -> None
+paddle.fluid.BuildStrategy.__init__ __init__(self: paddle.fluid.core.BuildStrategy) -> None
+paddle.fluid.create_lod_tensor ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.create_random_int_lodtensor ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.io.save_vars ArgSpec(args=['executor', 'dirname', 'main_program', 'vars', 'predicate', 'filename'], varargs=None, keywords=None, defaults=(None, None, None, None))
+paddle.fluid.io.save_params ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.io.save_persistables ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.io.load_vars ArgSpec(args=['executor', 'dirname', 'main_program', 'vars', 'predicate', 'filename'], varargs=None, keywords=None, defaults=(None, None, None, None))
+paddle.fluid.io.load_params ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.io.load_persistables ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.io.save_inference_model ArgSpec(args=['dirname', 'feeded_var_names', 'target_vars', 'executor', 'main_program', 'model_filename', 'params_filename'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.io.load_inference_model ArgSpec(args=['dirname', 'executor', 'model_filename', 'params_filename'], varargs=None, keywords=None, defaults=(None, None))
+paddle.fluid.io.get_inference_program ArgSpec(args=['target_vars', 'main_program'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.initializer.ConstantInitializer.__init__ ArgSpec(args=['self', 'value', 'force_cpu'], varargs=None, keywords=None, defaults=(0.0, False))
+paddle.fluid.initializer.UniformInitializer.__init__ ArgSpec(args=['self', 'low', 'high', 'seed'], varargs=None, keywords=None, defaults=(-1.0, 1.0, 0))
+paddle.fluid.initializer.NormalInitializer.__init__ ArgSpec(args=['self', 'loc', 'scale', 'seed'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0))
+paddle.fluid.initializer.XavierInitializer.__init__ ArgSpec(args=['self', 'uniform', 'fan_in', 'fan_out', 'seed'], varargs=None, keywords=None, defaults=(True, None, None, 0))
+paddle.fluid.initializer.BilinearInitializer.__init__ ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.initializer.MSRAInitializer.__init__ ArgSpec(args=['self', 'uniform', 'fan_in', 'seed'], varargs=None, keywords=None, defaults=(True, None, 0))
+paddle.fluid.initializer.force_init_on_cpu ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
+paddle.fluid.initializer.init_on_cpu ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.layers.fc ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'use_mkldnn', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, False, None, False, None))
+paddle.fluid.layers.embedding ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32'))
+paddle.fluid.layers.dynamic_lstm ArgSpec(args=['input', 'size', 'h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'float32', None))
+paddle.fluid.layers.dynamic_lstmp ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None))
+paddle.fluid.layers.dynamic_gru ArgSpec(args=['input', 'size', 'param_attr', 'bias_attr', 'is_reverse', 'gate_activation', 'candidate_activation', 'h_0'], varargs=None, keywords=None, defaults=(None, None, False, 'sigmoid', 'tanh', None))
+paddle.fluid.layers.gru_unit ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid'))
+paddle.fluid.layers.linear_chain_crf ArgSpec(args=['input', 'label', 'param_attr'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.layers.crf_decoding ArgSpec(args=['input', 'param_attr', 'label'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.layers.cos_sim ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.cross_entropy ArgSpec(args=['input', 'label', 'soft_label'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.layers.square_error_cost ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.chunk_eval ArgSpec(args=['input', 'label', 'chunk_scheme', 'num_chunk_types', 'excluded_chunk_types'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.layers.sequence_conv ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'bias_attr', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(3, 1, None, None, None, None))
+paddle.fluid.layers.conv2d ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'use_mkldnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, False, None, None))
+paddle.fluid.layers.conv3d ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'use_mkldnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, False, None, None))
+paddle.fluid.layers.sequence_pool ArgSpec(args=['input', 'pool_type'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.sequence_softmax ArgSpec(args=['input', 'param_attr', 'bias_attr', 'use_cudnn'], varargs=None, keywords=None, defaults=(None, None, True))
+paddle.fluid.layers.softmax ArgSpec(args=['input', 'param_attr', 'bias_attr', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(None, None, True, None))
+paddle.fluid.layers.pool2d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'use_mkldnn', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, False, None))
+paddle.fluid.layers.pool3d ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'use_mkldnn', 'name'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, False, None))
+paddle.fluid.layers.batch_norm ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'use_mkldnn', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, False, None, None, None, False, False))
+paddle.fluid.layers.beam_search_decode ArgSpec(args=['ids', 'scores', 'beam_size', 'end_id', 'name'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.layers.conv2d_transpose ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None))
+paddle.fluid.layers.conv3d_transpose ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None))
+paddle.fluid.layers.sequence_expand ArgSpec(args=['x', 'y', 'ref_level', 'name'], varargs=None, keywords=None, defaults=(-1, None))
+paddle.fluid.layers.lstm_unit ArgSpec(args=['x_t', 'hidden_t_prev', 'cell_t_prev', 'forget_bias', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(0.0, None, None, None))
+paddle.fluid.layers.reduce_sum ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None))
+paddle.fluid.layers.reduce_mean ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None))
+paddle.fluid.layers.reduce_max ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None))
+paddle.fluid.layers.reduce_min ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None))
+paddle.fluid.layers.reduce_prod ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None))
+paddle.fluid.layers.sequence_first_step ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.sequence_last_step ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None)
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+paddle.fluid.layers.target_assign ArgSpec(args=['input', 'matched_indices', 'negative_indices', 'mismatch_value', 'name'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.layers.detection_output ArgSpec(args=['loc', 'scores', 'prior_box', 'prior_box_var', 'background_label', 'nms_threshold', 'nms_top_k', 'keep_top_k', 'score_threshold', 'nms_eta'], varargs=None, keywords=None, defaults=(0, 0.3, 400, 200, 0.01, 1.0))
+paddle.fluid.layers.ssd_loss ArgSpec(args=['location', 'confidence', 'gt_box', 'gt_label', 'prior_box', 'prior_box_var', 'background_label', 'overlap_threshold', 'neg_pos_ratio', 'neg_overlap', 'loc_loss_weight', 'conf_loss_weight', 'match_type', 'mining_type', 'normalize', 'sample_size'], varargs=None, keywords=None, defaults=(None, 0, 0.5, 3.0, 0.5, 1.0, 1.0, 'per_prediction', 'max_negative', True, None))
+paddle.fluid.layers.detection_map ArgSpec(args=['detect_res', 'label', 'class_num', 'background_label', 'overlap_threshold', 'evaluate_difficult', 'has_state', 'input_states', 'out_states', 'ap_version'], varargs=None, keywords=None, defaults=(0, 0.3, True, None, None, None, 'integral'))
+paddle.fluid.layers.rpn_target_assign ArgSpec(args=['loc', 'scores', 'anchor_box', 'gt_box', 'rpn_batch_size_per_im', 'fg_fraction', 'rpn_positive_overlap', 'rpn_negative_overlap'], varargs=None, keywords=None, defaults=(256, 0.25, 0.7, 0.3))
+paddle.fluid.layers.anchor_generator ArgSpec(args=['input', 'anchor_sizes', 'aspect_ratios', 'variance', 'stride', 'offset', 'name'], varargs=None, keywords=None, defaults=(None, None, [0.1, 0.1, 0.2, 0.2], None, 0.5, None))
+paddle.fluid.layers.box_coder ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
+paddle.fluid.layers.accuracy ArgSpec(args=['input', 'label', 'k', 'correct', 'total'], varargs=None, keywords=None, defaults=(1, None, None))
+paddle.fluid.layers.auc ArgSpec(args=['input', 'label', 'curve', 'num_thresholds', 'topk'], varargs=None, keywords=None, defaults=('ROC', 200, 1))
+paddle.fluid.layers.exponential_decay ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.layers.natural_exp_decay ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.layers.inverse_time_decay ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,))
+paddle.fluid.layers.polynomial_decay ArgSpec(args=['learning_rate', 'decay_steps', 'end_learning_rate', 'power', 'cycle'], varargs=None, keywords=None, defaults=(0.0001, 1.0, False))
+paddle.fluid.layers.piecewise_decay ArgSpec(args=['boundaries', 'values'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.noam_decay ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.layers.append_LARS ArgSpec(args=['params_grads', 'learning_rate', 'weight_decay'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.transpiler.DistributeTranspiler.create_splited_vars ArgSpec(args=['self', 'source_var', 'block', 'tag'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspiler.get_startup_program ArgSpec(args=['self', 'endpoint', 'pserver_program'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspiler.transpile ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True))
+paddle.fluid.transpiler.InferenceTranspiler.__init__ 
+paddle.fluid.transpiler.InferenceTranspiler.fuse_batch_norm ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.InferenceTranspiler.fuse_relu_mkldnn ArgSpec(args=['self', 'program'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.InferenceTranspiler.transpile ArgSpec(args=['self', 'program', 'place', 'scope'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.transpiler.memory_optimize ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level'], varargs=None, keywords=None, defaults=(None, False, 0))
+paddle.fluid.transpiler.release_memory ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.transpiler.HashName.__init__ ArgSpec(args=['self', 'pserver_endpoints'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.HashName.dispatch ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.HashName.reset ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.RoundRobin.__init__ ArgSpec(args=['self', 'pserver_endpoints'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.RoundRobin.dispatch ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.RoundRobin.reset ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.transpiler.DistributeTranspilerConfig.__init__ 
+paddle.fluid.nets.simple_img_conv_pool ArgSpec(args=['input', 'num_filters', 'filter_size', 'pool_size', 'pool_stride', 'pool_padding', 'pool_type', 'global_pooling', 'conv_stride', 'conv_padding', 'conv_dilation', 'conv_groups', 'param_attr', 'bias_attr', 'act', 'use_cudnn', 'use_mkldnn'], varargs=None, keywords=None, defaults=(0, 'max', False, 1, 0, 1, 1, None, None, None, True, False))
+paddle.fluid.nets.sequence_conv_pool ArgSpec(args=['input', 'num_filters', 'filter_size', 'param_attr', 'act', 'pool_type'], varargs=None, keywords=None, defaults=(None, 'sigmoid', 'max'))
+paddle.fluid.nets.glu ArgSpec(args=['input', 'dim'], varargs=None, keywords=None, defaults=(-1,))
+paddle.fluid.nets.scaled_dot_product_attention ArgSpec(args=['queries', 'keys', 'values', 'num_heads', 'dropout_rate'], varargs=None, keywords=None, defaults=(1, 0.0))
+paddle.fluid.optimizer.SGDOptimizer.__init__ ArgSpec(args=['self', 'learning_rate'], varargs=None, keywords='kwargs', defaults=None)
+paddle.fluid.optimizer.SGDOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.MomentumOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'momentum', 'use_nesterov'], varargs=None, keywords='kwargs', defaults=(False,))
+paddle.fluid.optimizer.MomentumOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.AdagradOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'epsilon'], varargs=None, keywords='kwargs', defaults=(1e-06,))
+paddle.fluid.optimizer.AdagradOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.AdamOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'beta1', 'beta2', 'epsilon'], varargs=None, keywords='kwargs', defaults=(0.001, 0.9, 0.999, 1e-08))
+paddle.fluid.optimizer.AdamOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.AdamaxOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'beta1', 'beta2', 'epsilon'], varargs=None, keywords='kwargs', defaults=(0.001, 0.9, 0.999, 1e-08))
+paddle.fluid.optimizer.AdamaxOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.DecayedAdagradOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'decay', 'epsilon'], varargs=None, keywords='kwargs', defaults=(0.95, 1e-06))
+paddle.fluid.optimizer.DecayedAdagradOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.FtrlOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'l1', 'l2', 'lr_power'], varargs=None, keywords='kwargs', defaults=(0.0, 0.0, -0.5))
+paddle.fluid.optimizer.FtrlOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.RMSPropOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'rho', 'epsilon', 'momentum'], varargs=None, keywords='kwargs', defaults=(0.95, 1e-06, 0.0))
+paddle.fluid.optimizer.RMSPropOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.AdadeltaOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'epsilon', 'rho'], varargs=None, keywords='kwargs', defaults=(1e-06, 0.95))
+paddle.fluid.optimizer.AdadeltaOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.ModelAverage.__init__ ArgSpec(args=['self', 'average_window_rate', 'min_average_window', 'max_average_window'], varargs=None, keywords='kwargs', defaults=(10000, 10000))
+paddle.fluid.optimizer.ModelAverage.apply ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.optimizer.ModelAverage.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.optimizer.ModelAverage.restore ArgSpec(args=['self', 'executor'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.backward.append_backward ArgSpec(args=['loss', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None))
+paddle.fluid.regularizer.L1DecayRegularizer.__init__ ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,))
+paddle.fluid.regularizer.L2DecayRegularizer.__init__ ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,))
+paddle.fluid.LoDTensor.__init__ 1. __init__(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None  2. __init__(self: paddle.fluid.core.LoDTensor) -> None
+paddle.fluid.LoDTensor.has_valid_recursive_sequence_lengths has_valid_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> bool
+paddle.fluid.LoDTensor.lod lod(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
+paddle.fluid.LoDTensor.recursive_sequence_lengths recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
+paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None  2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None  3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None  4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None  5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None  6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None  7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None  8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPlace) -> None  9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None  10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None  11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None  12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None  13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None  14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None  15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None  16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None  17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None  18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None  19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None  20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None  21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPinnedPlace) -> None
+paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
+paddle.fluid.LoDTensor.set_recursive_sequence_lengths set_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
+paddle.fluid.LoDTensor.shape shape(self: paddle.fluid.core.Tensor) -> List[int]
+paddle.fluid.LoDTensorArray.__init__ __init__(self: paddle.fluid.core.LoDTensorArray) -> None
+paddle.fluid.LoDTensorArray.append append(self: paddle.fluid.core.LoDTensorArray, arg0: paddle.fluid.core.LoDTensor) -> None
+paddle.fluid.CPUPlace.__init__ __init__(self: paddle.fluid.core.CPUPlace) -> None
+paddle.fluid.CUDAPlace.__init__ __init__(self: paddle.fluid.core.CUDAPlace, arg0: int) -> None
+paddle.fluid.CUDAPinnedPlace.__init__ __init__(self: paddle.fluid.core.CUDAPinnedPlace) -> None
+paddle.fluid.ParamAttr.__init__ ArgSpec(args=['self', 'name', 'initializer', 'learning_rate', 'regularizer', 'trainable', 'gradient_clip', 'do_model_average'], varargs=None, keywords=None, defaults=(None, None, 1.0, None, True, None, False))
+paddle.fluid.WeightNormParamAttr.__init__ ArgSpec(args=['self', 'dim'], varargs=None, keywords='kwargs', defaults=(None,))
+paddle.fluid.DataFeeder.__init__ ArgSpec(args=['self', 'feed_list', 'place', 'program'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.DataFeeder.decorate_reader ArgSpec(args=['self', 'reader', 'multi_devices', 'num_places', 'drop_last'], varargs=None, keywords=None, defaults=(None, True))
+paddle.fluid.DataFeeder.feed ArgSpec(args=['self', 'iterable'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.DataFeeder.feed_parallel ArgSpec(args=['self', 'iterable', 'num_places'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.clip.ErrorClipByValue.__init__ ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.clip.GradientClipByValue.__init__ ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.clip.GradientClipByNorm.__init__ ArgSpec(args=['self', 'clip_norm'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.clip.GradientClipByGlobalNorm.__init__ ArgSpec(args=['self', 'clip_norm', 'group_name'], varargs=None, keywords=None, defaults=('default_group',))
+paddle.fluid.profiler.cuda_profiler ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.profiler.reset_profiler ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
+paddle.fluid.profiler.profiler ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.profiler.start_profiler ArgSpec(args=['state'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.profiler.stop_profiler ArgSpec(args=['sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile'))
+paddle.fluid.unique_name.generate ArgSpec(args=['key'], varargs=None, keywords=None, defaults=None)
+paddle.fluid.unique_name.switch ArgSpec(args=['new_generator'], varargs=None, keywords=None, defaults=(None,))
+paddle.fluid.unique_name.guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
+paddle.fluid.recordio_writer.convert_reader_to_recordio_file ArgSpec(args=['filename', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None))
+paddle.fluid.recordio_writer.convert_reader_to_recordio_files ArgSpec(args=['filename', 'batch_per_file', 'reader_creator', 'feeder', 'compressor', 'max_num_records', 'feed_order'], varargs=None, keywords=None, defaults=(Compressor.Snappy, 1000, None))
+paddle.fluid.Scope.__init__ __init__(self: paddle.fluid.core.Scope) -> None
+paddle.fluid.Scope.drop_kids drop_kids(self: paddle.fluid.core.Scope) -> None
+paddle.fluid.Scope.find_var find_var(self: paddle.fluid.core.Scope, arg0: unicode) -> paddle.fluid.core.Variable
+paddle.fluid.Scope.new_scope new_scope(self: paddle.fluid.core.Scope) -> paddle.fluid.core.Scope
+paddle.fluid.Scope.var var(self: paddle.fluid.core.Scope, arg0: unicode) -> paddle.fluid.core.Variable

paddle/fluid/inference/CMakeLists.txt

@@ -5,7 +5,7 @@ if (TENSORRT_FOUND)
   add_subdirectory(tensorrt)
 endif()
 
-set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor )
+set(FLUID_CORE_MODULES proto_desc memory lod_tensor executor)
 
 # TODO(panyx0718): Should this be called paddle_fluid_inference_api_internal?
 cc_library(paddle_fluid_api
@@ -38,3 +38,4 @@ if(WITH_TESTING)
   # both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book
   add_subdirectory(tests/book)
 endif()
+add_subdirectory(api)

paddle/contrib/inference/CMakeLists.txt → paddle/fluid/inference/api/CMakeLists.txt

@@ -43,21 +43,21 @@ function(inference_api_test TARGET_NAME)
 endfunction(inference_api_test)
 
 cc_library(paddle_inference_api
-    SRCS paddle_inference_api.cc paddle_inference_api_impl.cc
+    SRCS api.cc api_impl.cc
     DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
 if(NOT APPLE)
-  set(LINK_FLAGS "-Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/paddle_inference_api.sym")
+  set(LINK_FLAGS "-Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/api.sym")
   set_target_properties(paddle_inference_api PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
 endif()
 
 # Here the shared library doesn't depend on other fluid libraries, or double free will occur.
 cc_library(paddle_inference_api_shared SHARED
-    SRCS paddle_inference_api.cc paddle_inference_api_impl.cc)
+    SRCS api.cc api_impl.cc)
 add_dependencies(paddle_inference_api_shared ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
 set_target_properties(paddle_inference_api_shared PROPERTIES OUTPUT_NAME paddle_inference_api)
 
 if(NOT APPLE)
-  set(LINK_FLAGS "-Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/paddle_inference_api.map")
+  set(LINK_FLAGS "-Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/api.map")
   set_target_properties(paddle_inference_api_shared PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
   FILE(WRITE ${CMAKE_CURRENT_BINARY_DIR}/check_symbol.cmake
     "execute_process(COMMAND bash -c \"${CMAKE_CURRENT_SOURCE_DIR}/check_symbol.sh"
@@ -73,32 +73,32 @@ if(NOT APPLE)
 endif()
 
 cc_test(test_paddle_inference_api
-        SRCS test_paddle_inference_api.cc
+        SRCS test_api.cc
         DEPS paddle_inference_api)
 
-inference_api_test(test_paddle_inference_api_impl
+inference_api_test(test_api_impl
                     ARGS test_word2vec test_image_classification)
 
 if(WITH_GPU AND TENSORRT_FOUND)
 cc_library(paddle_inference_tensorrt_subgraph_engine
-        SRCS paddle_inference_api_tensorrt_subgraph_engine.cc
-        DEPS paddle_inference_api analysis tensorrt_engine paddle_inference_api paddle_fluid_api)
+        SRCS api_tensorrt_subgraph_engine.cc
+        DEPS paddle_inference_api analysis tensorrt_engine paddle_fluid_api)
 
-inference_api_test(test_paddle_inference_api_tensorrt_subgraph_engine ARGS test_word2vec)
+inference_api_test(test_api_tensorrt_subgraph_engine ARGS test_word2vec)
 endif()
 
 if (WITH_ANAKIN) # only needed in CI
     # Due to Anakin do not have official library releases and the versions of protobuf and cuda do not match Paddle's,
     # so anakin library will not be merged to our official inference library. To use anakin prediction API, one need to
     # compile the libinference_anakin_api.a and compile with anakin.so.
-    nv_library(inference_anakin_api SRCS paddle_inference_api.cc paddle_inference_api_anakin_engine.cc)
-    nv_library(inference_anakin_api_shared SHARED SRCS paddle_inference_api.cc paddle_inference_api_anakin_engine.cc)
+    nv_library(inference_anakin_api SRCS api.cc api_anakin_engine.cc)
+    nv_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc)
     target_compile_options(inference_anakin_api BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
     target_compile_options(inference_anakin_api_shared BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
     target_link_libraries(inference_anakin_api anakin anakin_saber_common)
     target_link_libraries(inference_anakin_api_shared anakin anakin_saber_common)
     if (WITH_TESTING)
-        cc_test(inference_anakin_test SRCS paddle_inference_api_anakin_engine_tester.cc
+        cc_test(inference_anakin_test SRCS api_anakin_engine_tester.cc
                                   ARGS --model=${ANAKIN_INSTALL_DIR}/mobilenet_v2.anakin.bin
                                   DEPS inference_anakin_api)
         target_compile_options(inference_anakin_test BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})

paddle/contrib/inference/paddle_inference_api.cc → paddle/fluid/inference/api/api.cc

@@ -12,7 +12,7 @@ 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/contrib/inference/paddle_inference_api.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 namespace paddle {
 

paddle/contrib/inference/paddle_inference_api_anakin_engine.cc → paddle/fluid/inference/api/api_anakin_engine.cc

@@ -12,8 +12,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/contrib/inference/paddle_inference_api_anakin_engine.h"
+#include "paddle/fluid/inference/api/api_anakin_engine.h"
 #include <cuda.h>
+#include <vector>
 
 namespace paddle {
 
@@ -47,8 +48,7 @@ bool PaddleInferenceAnakinPredictor::Run(
     }
     auto d_tensor_in_p = executor_.get_in(input.name);
     float *d_data_p = d_tensor_in_p->mutable_data();
-    if (cudaMemcpy(d_data_p,
-                   static_cast<float *>(input.data.data()),
+    if (cudaMemcpy(d_data_p, static_cast<float *>(input.data.data()),
                    d_tensor_in_p->valid_size() * sizeof(float),
                    cudaMemcpyHostToDevice) != 0) {
       LOG(ERROR) << "copy data from CPU to GPU error";
@@ -70,8 +70,7 @@ bool PaddleInferenceAnakinPredictor::Run(
       output.data.Resize(tensor->valid_size() * sizeof(float));
     }
     // Copy data from GPU -> CPU
-    if (cudaMemcpy(output.data.data(),
-                   tensor->mutable_data(),
+    if (cudaMemcpy(output.data.data(), tensor->mutable_data(),
                    tensor->valid_size() * sizeof(float),
                    cudaMemcpyDeviceToHost) != 0) {
       LOG(ERROR) << "copy data from GPU to CPU error";
@@ -106,13 +105,12 @@ std::unique_ptr<PaddlePredictor> PaddleInferenceAnakinPredictor::Clone() {
 
 // A factory to help create difference predictor.
 template <>
-std::unique_ptr<PaddlePredictor>
-CreatePaddlePredictor<AnakinConfig, PaddleEngineKind::kAnakin>(
-    const AnakinConfig &config) {
+std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
+    AnakinConfig, PaddleEngineKind::kAnakin>(const AnakinConfig &config) {
   VLOG(3) << "Anakin Predictor create.";
   std::unique_ptr<PaddlePredictor> x(
       new PaddleInferenceAnakinPredictor(config));
   return x;
-};
+}
 
 }  // namespace paddle

paddle/contrib/inference/paddle_inference_api_anakin_engine.h → paddle/fluid/inference/api/api_anakin_engine.h

@@ -19,7 +19,8 @@ limitations under the License. */
 
 #pragma once
 
-#include "paddle/contrib/inference/paddle_inference_api.h"
+#include <vector>
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 // from anakin
 #include "framework/core/net/net.h"
@@ -31,7 +32,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
  public:
   PaddleInferenceAnakinPredictor() {}
 
-  PaddleInferenceAnakinPredictor(const AnakinConfig& config);
+  explicit PaddleInferenceAnakinPredictor(const AnakinConfig& config);
 
   // NOTE Unlike the native engine, the buffers of anakin engine's output_data
   // should be allocated first.
@@ -48,8 +49,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
  private:
   bool Init(const AnakinConfig& config);
 
-  anakin::graph::Graph<anakin::NV,
-                       anakin::saber::AK_FLOAT,
+  anakin::graph::Graph<anakin::NV, anakin::saber::AK_FLOAT,
                        anakin::Precision::FP32>
       graph_;
   anakin::Net<anakin::NV, anakin::saber::AK_FLOAT, anakin::Precision::FP32>

paddle/contrib/inference/paddle_inference_api_anakin_engine_tester.cc → paddle/fluid/inference/api/api_anakin_engine_tester.cc

@@ -16,7 +16,7 @@ limitations under the License. */
 #include <glog/logging.h>
 #include <gtest/gtest.h>
 
-#include "paddle/contrib/inference/paddle_inference_api.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 DEFINE_string(model, "", "Directory of the inference model.");
 

paddle/contrib/inference/paddle_inference_api_impl.cc → paddle/fluid/inference/api/api_impl.cc

@@ -21,7 +21,7 @@ limitations under the License. */
 #include <utility>
 #include <vector>
 
-#include "paddle/contrib/inference/paddle_inference_api_impl.h"
+#include "paddle/fluid/inference/api/api_impl.h"
 
 namespace paddle {
 namespace {
@@ -77,8 +77,8 @@ bool NativePaddlePredictor::Init(
   if (!config_.model_dir.empty()) {
     // Parameters are saved in separate files sited in
     // the specified `dirname`.
-    inference_program_ = paddle::inference::Load(
-        executor_.get(), scope_.get(), config_.model_dir);
+    inference_program_ = paddle::inference::Load(executor_.get(), scope_.get(),
+                                                 config_.model_dir);
   } else if (!config_.prog_file.empty() && !config_.param_file.empty()) {
     // All parameters are saved in a single file.
     // The file names should be consistent with that used
@@ -91,8 +91,8 @@ bool NativePaddlePredictor::Init(
   }
 
   ctx_ = executor_->Prepare(*inference_program_, 0);
-  executor_->CreateVariables(
-      *inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0);
+  executor_->CreateVariables(*inference_program_,
+                             sub_scope_ ? sub_scope_ : scope_.get(), 0);
 
   // Get the feed_target_names and fetch_target_names
   feed_target_names_ = inference_program_->GetFeedTargetNames();
@@ -105,7 +105,7 @@ NativePaddlePredictor::~NativePaddlePredictor() {
     PADDLE_ENFORCE_NOT_NULL(scope_, "Should have parent scope!");
     scope_->DeleteScope(sub_scope_);
   }
-};
+}
 
 bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
                                 std::vector<PaddleTensor> *output_data) {
@@ -134,10 +134,8 @@ bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
   // if share variables, we need not create variables
   VLOG(4) << "Run prepared context";
   executor_->RunPreparedContext(
-      ctx_.get(),
-      sub_scope_ != nullptr ? sub_scope_ : scope_.get(),
-      &feed_targets,
-      &fetch_targets,
+      ctx_.get(), sub_scope_ != nullptr ? sub_scope_ : scope_.get(),
+      &feed_targets, &fetch_targets,
       false /* don't create variable eatch time */);
   VLOG(4) << "Finish prepared context";
   if (!GetFetch(fetchs, output_data)) {
@@ -181,8 +179,7 @@ bool NativePaddlePredictor::SetFeed(const std::vector<PaddleTensor> &inputs,
     }
 
     // TODO(panyx0718): Init LoDTensor from existing memcpy to save a copy.
-    std::memcpy(static_cast<void *>(input_ptr),
-                inputs[i].data.data(),
+    std::memcpy(static_cast<void *>(input_ptr), inputs[i].data.data(),
                 inputs[i].data.length());
     feeds->push_back(input);
   }
@@ -232,8 +229,7 @@ bool NativePaddlePredictor::GetFetch(
         size_t start = lod[0][j - 1] * common_dim;
         size_t end = lod[0][j] * common_dim;
         if (end > start) {
-          std::copy(output_ptr + start,
-                    output_ptr + end,
+          std::copy(output_ptr + start, output_ptr + end,
                     data.begin() + (j - 1) * max_dim * common_dim);
         }
       }
@@ -257,15 +253,13 @@ bool NativePaddlePredictor::GetFetch(
 }
 
 template <>
-std::unique_ptr<PaddlePredictor>
-CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>(
-    const NativeConfig &config) {
+std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
+    NativeConfig, PaddleEngineKind::kNative>(const NativeConfig &config) {
   VLOG(3) << "create NativePaddlePredictor";
   if (config.use_gpu) {
     // 1. GPU memeroy
     PADDLE_ENFORCE_GT(
-        config.fraction_of_gpu_memory,
-        0.f,
+        config.fraction_of_gpu_memory, 0.f,
         "fraction_of_gpu_memory in the config should be set to range (0., 1.]");
     PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
     std::vector<std::string> flags;

paddle/contrib/inference/paddle_inference_api_impl.h → paddle/fluid/inference/api/api_impl.h

@@ -19,7 +19,7 @@
 #include <string>
 #include <vector>
 
-#include "paddle/contrib/inference/paddle_inference_api.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 #include "paddle/fluid/framework/ddim.h"
 #include "paddle/fluid/framework/lod_tensor.h"

paddle/contrib/inference/paddle_inference_api_tensorrt_subgraph_engine.cc → paddle/fluid/inference/api/api_tensorrt_subgraph_engine.cc

@@ -12,9 +12,9 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/contrib/inference/paddle_inference_api.h"
-#include "paddle/contrib/inference/paddle_inference_api_impl.h"
 #include "paddle/fluid/inference/analysis/analyzer.h"
+#include "paddle/fluid/inference/api/api_impl.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 #include "paddle/fluid/inference/utils/singleton.h"
 
 namespace paddle {
@@ -77,8 +77,8 @@ class TensorRTSubgraphPredictor : public NativePaddlePredictor {
     ctx_ = executor_->Prepare(*inference_program_, 0);
 
     VLOG(5) << "to create variables";
-    executor_->CreateVariables(
-        *inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0);
+    executor_->CreateVariables(*inference_program_,
+                               sub_scope_ ? sub_scope_ : scope_.get(), 0);
 
     // Get the feed_target_names and fetch_target_names
     feed_target_names_ = inference_program_->GetFeedTargetNames();
@@ -98,8 +98,7 @@ CreatePaddlePredictor<TensorRTConfig, PaddleEngineKind::kAutoMixedTensorRT>(
   if (config.use_gpu) {
     // 1. GPU memeroy
     PADDLE_ENFORCE_GT(
-        config.fraction_of_gpu_memory,
-        0.f,
+        config.fraction_of_gpu_memory, 0.f,
         "fraction_of_gpu_memory in the config should be set to range (0., 1.]");
     PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
     std::vector<std::string> flags;

paddle/contrib/inference/demo_ci/CMakeLists.txt → paddle/fluid/inference/api/demo_ci/CMakeLists.txt

@@ -55,11 +55,11 @@ endif()
 # Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
 if(WITH_STATIC_LIB)
   set(DEPS
-      ${PADDLE_LIB}/contrib/inference/libpaddle_inference_api.a
+      ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_inference_api.a
       ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.a)
 else()
   set(DEPS
-      ${PADDLE_LIB}/contrib/inference/libpaddle_inference_api.so
+      ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_inference_api.so
       ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.so)
 endif()
 set(EXTERNAL_LIB "-lrt -ldl -lpthread")

paddle/contrib/inference/demo_ci/run.sh → paddle/fluid/inference/api/demo_ci/run.sh

@@ -64,7 +64,7 @@ for WITH_STATIC_LIB in ON OFF; do
     -DWITH_GPU=$TEST_GPU_CPU \
     -DWITH_STATIC_LIB=$WITH_STATIC_LIB
   make -j
-  for use_gpu in false; do
+  for use_gpu in $use_gpu_list; do
     for vis_demo_name in $vis_demo_list; do 
       ./vis_demo \
         --modeldir=../data/$vis_demo_name/model \

paddle/contrib/inference/demo_ci/simple_on_word2vec.cc → paddle/fluid/inference/api/demo_ci/simple_on_word2vec.cc

@@ -19,8 +19,8 @@ limitations under the License. */
 #include <gflags/gflags.h>
 #include <glog/logging.h>
 #include <memory>
-#include <thread>
-#include "contrib/inference/paddle_inference_api.h"
+#include <thread>  //NOLINT
+#include "paddle/fluid/inference/paddle_inference_api.h"
 #include "paddle/fluid/platform/enforce.h"
 
 DEFINE_string(dirname, "", "Directory of the inference model.");
@@ -63,8 +63,8 @@ void Main(bool use_gpu) {
     PADDLE_ENFORCE(outputs.size(), 1UL);
     // Check the output buffer size and result of each tid.
     PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
-    float result[5] = {
-        0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706};
+    float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
+                       0.000932706};
     const size_t num_elements = outputs.front().data.length() / sizeof(float);
     // The outputs' buffers are in CPU memory.
     for (size_t i = 0; i < std::min(5UL, num_elements); i++) {
@@ -107,8 +107,8 @@ void MainThreads(int num_threads, bool use_gpu) {
         PADDLE_ENFORCE(outputs.size(), 1UL);
         // Check the output buffer size and result of each tid.
         PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
-        float result[5] = {
-            0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706};
+        float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
+                           0.000932706};
         const size_t num_elements =
             outputs.front().data.length() / sizeof(float);
         // The outputs' buffers are in CPU memory.

paddle/contrib/inference/demo_ci/utils.h → paddle/fluid/inference/api/demo_ci/utils.h

@@ -13,16 +13,15 @@
 // limitations under the License.
 
 #pragma once
+#include <algorithm>
 #include <string>
 #include <vector>
-
-#include "contrib/inference/paddle_inference_api.h"
+#include "paddle/fluid/inference/paddle_inference_api.h"
 
 namespace paddle {
 namespace demo {
 
-static void split(const std::string& str,
-                  char sep,
+static void split(const std::string& str, char sep,
                   std::vector<std::string>* pieces) {
   pieces->clear();
   if (str.empty()) {

paddle/contrib/inference/demo_ci/vis_demo.cc → paddle/fluid/inference/api/demo_ci/vis_demo.cc

@@ -29,8 +29,7 @@ DECLARE_double(fraction_of_gpu_memory_to_use);
 DEFINE_string(modeldir, "", "Directory of the inference model.");
 DEFINE_string(refer, "", "path to reference result for comparison.");
 DEFINE_string(
-    data,
-    "",
+    data, "",
     "path of data; each line is a record, format is "
     "'<space splitted floats as data>\t<space splitted ints as shape'");
 DEFINE_bool(use_gpu, false, "Whether use gpu.");

paddle/contrib/inference/test_paddle_inference_api.cc → paddle/fluid/inference/api/test_api.cc

@@ -12,10 +12,9 @@ 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/contrib/inference/paddle_inference_api.h"
-
 #include <glog/logging.h>
 #include <gtest/gtest.h>
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 namespace paddle {
 

paddle/contrib/inference/test_paddle_inference_api_impl.cc → paddle/fluid/inference/api/test_api_impl.cc

@@ -15,10 +15,10 @@ limitations under the License. */
 #include <glog/logging.h>
 #include <gtest/gtest.h>
 
-#include <thread>
+#include <thread>  // NOLINT
 
 #include "gflags/gflags.h"
-#include "paddle/contrib/inference/paddle_inference_api_impl.h"
+#include "paddle/fluid/inference/api/api_impl.h"
 #include "paddle/fluid/inference/tests/test_helper.h"
 
 DEFINE_string(dirname, "", "Directory of the inference model.");
@@ -121,8 +121,8 @@ void MainImageClassification(bool use_gpu) {
   // which should be in the range [0.0, 1.0].
   feed_target_shapes[0][0] = batch_size;
   framework::DDim input_dims = framework::make_ddim(feed_target_shapes[0]);
-  SetupTensor<float>(
-      &input, input_dims, static_cast<float>(0), static_cast<float>(1));
+  SetupTensor<float>(&input, input_dims, static_cast<float>(0),
+                     static_cast<float>(1));
   std::vector<framework::LoDTensor*> cpu_feeds;
   cpu_feeds.push_back(&input);
 

paddle/contrib/inference/test_paddle_inference_api_tensorrt_subgraph_engine.cc → paddle/fluid/inference/api/test_api_tensorrt_subgraph_engine.cc

@@ -15,7 +15,7 @@
 #include <gflags/gflags.h>
 #include <glog/logging.h>
 #include <gtest/gtest.h>
-#include "paddle/contrib/inference/paddle_inference_api.h"
+#include "paddle/fluid/inference/api/paddle_inference_api.h"
 
 namespace paddle {
 
@@ -61,4 +61,4 @@ void Main(bool use_gpu) {
 
 TEST(paddle_inference_api_tensorrt_subgraph_engine, main) { Main(true); }
 
-}  // namespace paddle
+}  // namespace paddle
\ No newline at end of file

paddle/fluid/operators/im2sequence_op.cc

@@ -33,22 +33,14 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
 
     PADDLE_ENFORCE_EQ(in_dim.size(), 4,
                       "Input(X) format must be 4D tensor, eg., NCHW.");
-    int batch_size = in_dim[0];
     int img_channels = in_dim[1];
-    int img_height = in_dim[2];
-    int img_width = in_dim[3];
 
     auto kernels = ctx->Attrs().Get<std::vector<int>>("kernels");
     auto strides = ctx->Attrs().Get<std::vector<int>>("strides");
     auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
 
-    int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
-                                         paddings[2], strides[0]);
-    int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
-                                        paddings[3], strides[1]);
-
-    ctx->SetOutputDim("Out", {batch_size * output_height * output_width,
-                              img_channels * kernels[0] * kernels[1]});
+    ctx->SetOutputDim("Out",
+                      {in_dim[0], img_channels * kernels[0] * kernels[1]});
   }
 };
 

paddle/fluid/operators/im2sequence_op.h

@@ -109,12 +109,13 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
       }
       out->set_lod(lod);
     } else {
-      out->mutable_data<T>(ctx.GetPlace());
       int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
                                            paddings[2], strides[0]);
       int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
                                           paddings[3], strides[1]);
-
+      out->mutable_data<T>({batch_size * output_height * output_width,
+                            img_channels * kernels[0] * kernels[1]},
+                           ctx.GetPlace());
       const std::vector<int> dilations({1, 1});
       auto out_dims = out->dims();
       out->Resize({batch_size, out->numel() / batch_size});

paddle/fluid/operators/sum_mkldnn_op.cc

@@ -88,7 +88,7 @@ class SumMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
         input_format = memory::format::nc;
       }
 
-      for (int i = in_place ? 1 : 0; i < N; i++) {
+      for (int i = 0; i < N; i++) {
         PADDLE_ENFORCE(in_vars[i]->IsType<LoDTensor>(),
                        "all inputs must be all LoDTensors");
         auto& input = in_vars[i]->Get<LoDTensor>();

paddle/scripts/paddle_build.sh

@@ -19,6 +19,8 @@
 #                   Utils
 #=================================================
 
+set -ex
+
 function print_usage() {
     echo -e "\n${RED}Usage${NONE}:
     ${BOLD}${SCRIPT_NAME}${NONE} [OPTION]"
@@ -37,6 +39,7 @@ function print_usage() {
     ${BLUE}fluid_inference_lib${NONE}: deploy fluid inference library
     ${BLUE}check_style${NONE}: run code style check
     ${BLUE}cicheck${NONE}: run CI tasks
+    ${BLUE}assert_api_not_changed${NONE}: check api compability
     "
 }
 
@@ -326,11 +329,22 @@ function assert_api_not_changed() {
     virtualenv .env
     source .env/bin/activate
     pip install ${PADDLE_ROOT}/build/python/dist/*whl
-    curl ${PADDLE_API_SPEC_URL:-https://raw.githubusercontent.com/PaddlePaddle/FluidAPISpec/master/API.spec} \
-        > origin.spec
     python ${PADDLE_ROOT}/tools/print_signatures.py paddle.fluid > new.spec
-    python ${PADDLE_ROOT}/tools/diff_api.py origin.spec new.spec
+    python ${PADDLE_ROOT}/tools/diff_api.py ${PADDLE_ROOT}/paddle/fluid/API.spec new.spec
     deactivate
+
+    API_CHANGE=`git diff --name-only HEAD^ | grep "paddle/fluid/API.spec" || true`
+    echo "checking API.spec change, PR: ${GIT_PR_ID}, changes: ${API_CHANGE}"
+    if [ ${API_CHANGE} ] && [ "${GIT_PR_ID}" != "" ]; then
+        # TODO: curl -H 'Authorization: token ${TOKEN}'
+        APPROVALS=`curl -H "Authorization: token ${GITHUB_API_TOKEN}" https://api.github.com/repos/PaddlePaddle/Paddle/pulls/${GIT_PR_ID}/reviews | \
+        python ${PADDLE_ROOT}/tools/check_pr_approval.py 2 7845005 2887803 728699 13348433`
+        echo "current pr ${GIT_PR_ID} got approvals: ${APPROVALS}"
+        if [ "${APPROVALS}" == "FALSE" ]; then
+            echo "You must have at least 2 approvals for the api change!"
+        exit 1
+        fi
+    fi
 }
 
 
@@ -531,13 +545,12 @@ function test_fluid_inference_lib() {
     Testing fluid inference library ...
     ========================================
 EOF
-        cd ${PADDLE_ROOT}/paddle/contrib/inference/demo_ci
+        cd ${PADDLE_ROOT}/paddle/fluid/inference/api/demo_ci
         ./run.sh ${PADDLE_ROOT} ${WITH_MKL:-ON} ${WITH_GPU:-OFF}
       fi
 }
 
 function main() {
-    set -e
     local CMD=$1
     init
     case $CMD in

python/paddle/fluid/layers/io.py

@@ -26,8 +26,7 @@ from ..layer_helper import LayerHelper
 from ..unique_name import generate as unique_name
 
 __all__ = [
-    'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'Recv',
-    'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
+    'data', 'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
     'double_buffer', 'random_data_generator', 'py_reader', 'Preprocessor',
     'load'
 ]
@@ -908,7 +907,7 @@ class Preprocessor(object):
         self.sink_var_names = None
         self.status = Preprocessor.BEFORE_SUB_BLOCK
 
-    def is_completed(self):
+    def _is_completed(self):
         return self.sub_block and self.source_var_names and self.sink_var_names
 
     @contextlib.contextmanager
@@ -918,7 +917,7 @@ class Preprocessor(object):
         yield
         self.main_prog.rollback()
         self.status = Preprocessor.AFTER_SUB_BLOCK
-        if not self.is_completed():
+        if not self._is_completed():
             raise RuntimeError(
                 "The definition of preprocessor is incompleted! "
                 "Please make sure that you have set input and output "

python/paddle/fluid/optimizer.py

@@ -1180,16 +1180,16 @@ class ModelAverage(Optimizer):
                 self._add_average_restore_op(block, param_grad)
 
     def _add_average_apply_op(self, block, param_grad):
-        param = block.clone_variable(param_grad[0])
-        grad = block.clone_variable(param_grad[1])
-        sum_1 = block.clone_variable(self._get_accumulator('sum_1', param))
-        sum_2 = block.clone_variable(self._get_accumulator('sum_2', param))
-        sum_3 = block.clone_variable(self._get_accumulator('sum_3', param))
-        num_accumulates = block.clone_variable(
+        param = block._clone_variable(param_grad[0])
+        grad = block._clone_variable(param_grad[1])
+        sum_1 = block._clone_variable(self._get_accumulator('sum_1', param))
+        sum_2 = block._clone_variable(self._get_accumulator('sum_2', param))
+        sum_3 = block._clone_variable(self._get_accumulator('sum_3', param))
+        num_accumulates = block._clone_variable(
             self._get_accumulator('num_accumulates', param))
-        old_num_accumulates = block.clone_variable(
+        old_num_accumulates = block._clone_variable(
             self._get_accumulator('old_num_accumulates', param))
-        num_updates = block.clone_variable(
+        num_updates = block._clone_variable(
             self._get_accumulator('num_updates', param))
         # backup param value to grad
         layers.assign(input=param, output=grad)
@@ -1203,8 +1203,8 @@ class ModelAverage(Optimizer):
         layers.elementwise_div(x=sum, y=tmp, out=param)
 
     def _add_average_restore_op(self, block, param_grad):
-        param = block.clone_variable(param_grad[0])
-        grad = block.clone_variable(param_grad[1])
+        param = block._clone_variable(param_grad[0])
+        grad = block._clone_variable(param_grad[1])
         layers.assign(input=grad, output=param)
 
     def _append_average_accumulate_op(self, param):

python/paddle/fluid/tests/unittests/test_dist_train.py

@@ -22,6 +22,9 @@ import numpy
 
 import paddle.fluid as fluid
 import paddle.fluid.layers as layers
+from paddle.fluid.layers.io import ListenAndServ
+from paddle.fluid.layers.io import Recv
+from paddle.fluid.layers.io import Send
 
 
 class TestSendOp(unittest.TestCase):
@@ -65,8 +68,7 @@ class TestSendOp(unittest.TestCase):
         main = fluid.Program()
 
         with fluid.program_guard(main):
-            serv = layers.ListenAndServ(
-                "127.0.0.1:0", ["X"], optimizer_mode=False)
+            serv = ListenAndServ("127.0.0.1:0", ["X"], optimizer_mode=False)
             with serv.do():
                 out_var = main.global_block().create_var(
                     name="scale_0.tmp_0",
@@ -99,8 +101,8 @@ class TestSendOp(unittest.TestCase):
                 persistable=False,
                 shape=[32, 32])
             fluid.initializer.Constant(value=2.3)(get_var, main.global_block())
-            layers.Send("127.0.0.1:%d" % port, [x])
-            o = layers.Recv("127.0.0.1:%d" % port, [get_var])
+            Send("127.0.0.1:%d" % port, [x])
+            o = Recv("127.0.0.1:%d" % port, [get_var])
 
         exe = fluid.Executor(place)
         self.dist_out = exe.run(main, fetch_list=o)  # o is a list

paddle/contrib/CMakeLists.txt → tools/check_pr_approval.py

-# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+# Copyright (c) 2018 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
+#     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.
-#
 
-add_subdirectory(inference)
+from __future__ import print_function
+import sys
+import json
+
+
+def check_approval(count, required_reviewers):
+    json_buff = ""
+    for line in sys.stdin:
+        json_buff = "".join([json_buff, line])
+    json_resp = json.loads(json_buff)
+    approves = 0
+    approved_user_ids = []
+    for review in json_resp:
+        if review["state"] == "APPROVED":
+            approves += 1
+            approved_user_ids.append(review["user"]["id"])
+
+    # convert to int
+    required_reviewers_int = set()
+    for rr in required_reviewers:
+        required_reviewers_int.add(int(rr))
+
+    if len(set(approved_user_ids) & required_reviewers_int) >= count:
+        print("TRUE")
+    else:
+        print("FALSE")
+
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1 and sys.argv[1].isdigit():
+        check_approval(int(sys.argv[1]), sys.argv[2:])
+    else:
+        print(
+            "Usage: python check_pr_approval.py [count] [required reviewer id] ..."
+        )