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PaddleDetection

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PaddleDetection
未验证 提交 e9c8d930 编写于 作者: Y yuyang18
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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
上级 10b3cbfb 16403342
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Showing with 603 addition and 135 deletion
CMakeLists.txt
浏览文件 @ e9c8d930
...@@ -282,7 +282,3 @@ if(WITH_DOC) ...@@ -282,7 +282,3 @@ if(WITH_DOC)
find_python_module(recommonmark REQUIRED) find_python_module(recommonmark REQUIRED)
add_subdirectory(doc) add_subdirectory(doc)
endif() endif()
if (WITH_CONTRIB)
add_subdirectory(paddle/contrib)
endif()
cmake/inference_lib.cmake
浏览文件 @ e9c8d930
...@@ -138,25 +138,24 @@ copy(memory_lib ...@@ -138,25 +138,24 @@ copy(memory_lib
set(inference_deps paddle_fluid_shared paddle_fluid) set(inference_deps paddle_fluid_shared paddle_fluid)
if(WITH_CONTRIB) set(module "inference/api")
message(STATUS "installing contrib") if (WITH_ANAKIN AND WITH_GPU)
set(contrib_dst_dir "${FLUID_INSTALL_DIR}/contrib/inference") copy(anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
if (WITH_ANAKIN AND WITH_GPU)
copy(contrib_anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS SRCS
${PADDLE_BINARY_DIR}/paddle/contrib/inference/libinference_anakin_api* # compiled anakin api ${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release ${PADDLE_BINARY_DIR}/third_party/install/anakin/*.tar.gz # anakin release
DSTS ${contrib_dst_dir}/anakin ${contrib_dst_dir}/anakin) DSTS ${dst_dir}/inference/anakin ${dst_dir}/inference/anakin)
list(APPEND inference_deps contrib_anakin_inference_lib) list(APPEND inference_deps 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)
endif() 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") set(module "inference")
copy(inference_lib DEPS ${inference_deps} copy(inference_lib DEPS ${inference_deps}
SRCS ${src_dir}/${module}/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.* SRCS ${src_dir}/${module}/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/inference/libpaddle_fluid.*
......
doc/v2/api/index_en.rst
浏览文件 @ e9c8d930
...@@ -4,7 +4,6 @@ API ...@@ -4,7 +4,6 @@ API
.. toctree:: .. toctree::
:maxdepth: 1 :maxdepth: 1
overview.rst
model_configs.rst model_configs.rst
data.rst data.rst
run_logic.rst run_logic.rst
paddle/fluid/API.spec 0 → 100644
浏览文件 @ e9c8d930
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)
paddle.fluid.layers.dropout ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name'], varargs=None, keywords=None, defaults=(False, None, None))
paddle.fluid.layers.split ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None))
paddle.fluid.layers.ctc_greedy_decoder ArgSpec(args=['input', 'blank', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.edit_distance ArgSpec(args=['input', 'label', 'normalized', 'ignored_tokens'], varargs=None, keywords=None, defaults=(True, None))
paddle.fluid.layers.l2_normalize ArgSpec(args=['x', 'axis', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(1e-12, None))
paddle.fluid.layers.matmul ArgSpec(args=['x', 'y', 'transpose_x', 'transpose_y', 'name'], varargs=None, keywords=None, defaults=(False, False, None))
paddle.fluid.layers.topk ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.warpctc ArgSpec(args=['input', 'label', 'blank', 'norm_by_times'], varargs=None, keywords=None, defaults=(0, False))
paddle.fluid.layers.sequence_reshape ArgSpec(args=['input', 'new_dim'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.transpose ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.im2sequence ArgSpec(args=['input', 'filter_size', 'stride', 'padding', 'input_image_size', 'out_stride', 'name'], varargs=None, keywords=None, defaults=(1, 1, 0, None, 1, None))
paddle.fluid.layers.nce ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.layers.hsigmoid ArgSpec(args=['input', 'label', 'num_classes', 'param_attr', 'bias_attr'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.beam_search ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 'scores', 'beam_size', 'end_id', 'level', 'name'], varargs=None, keywords=None, defaults=(0, None))
paddle.fluid.layers.row_conv ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.multiplex ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.layer_norm ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None))
paddle.fluid.layers.softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'soft_label'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.layers.smooth_l1 ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None))
paddle.fluid.layers.one_hot ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.autoincreased_step_counter ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1))
paddle.fluid.layers.reshape ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, True, None))
paddle.fluid.layers.lod_reset ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.lrn ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None))
paddle.fluid.layers.pad ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None))
paddle.fluid.layers.label_smooth ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None))
paddle.fluid.layers.roi_pool ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0))
paddle.fluid.layers.dice_loss ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,))
paddle.fluid.layers.image_resize ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'resample'], varargs=None, keywords=None, defaults=(None, None, None, 'BILINEAR'))
paddle.fluid.layers.image_resize_short ArgSpec(args=['input', 'out_short_len', 'resample'], varargs=None, keywords=None, defaults=('BILINEAR',))
paddle.fluid.layers.resize_bilinear ArgSpec(args=['input', 'out_shape', 'scale', 'name'], varargs=None, keywords=None, defaults=(None, None, None))
paddle.fluid.layers.gather ArgSpec(args=['input', 'index'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.random_crop ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.mean_iou ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.relu ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.log ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.crop ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None))
paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True))
paddle.fluid.layers.open_recordio_file ArgSpec(args=['filename', 'shapes', 'lod_levels', 'dtypes', 'pass_num', 'for_parallel'], varargs=None, keywords=None, defaults=(1, True))
paddle.fluid.layers.open_files ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'for_parallel'], varargs=None, keywords=None, defaults=(1, None, 1, True))
paddle.fluid.layers.read_file ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.shuffle ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.batch ArgSpec(args=['reader', 'batch_size'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.double_buffer ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.random_data_generator ArgSpec(args=['low', 'high', 'shapes', 'lod_levels', 'for_parallel'], varargs=None, keywords=None, defaults=(True,))
paddle.fluid.layers.py_reader ArgSpec(args=['capacity', 'shapes', 'dtypes', 'lod_levels'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.Preprocessor.__init__ ArgSpec(args=['self', 'reader', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.Preprocessor.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
paddle.fluid.layers.Preprocessor.inputs ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.Preprocessor.outputs ArgSpec(args=['self'], varargs='outs', keywords=None, defaults=None)
paddle.fluid.layers.load ArgSpec(args=['out', 'file_path', 'load_as_fp16'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.create_tensor ArgSpec(args=['dtype', 'name', 'persistable'], varargs=None, keywords=None, defaults=(None, False))
paddle.fluid.layers.create_parameter ArgSpec(args=['shape', 'dtype', 'name', 'attr', 'is_bias', 'default_initializer'], varargs=None, keywords=None, defaults=(None, None, False, None))
paddle.fluid.layers.create_global_var ArgSpec(args=['shape', 'value', 'dtype', 'persistable', 'force_cpu', 'name'], varargs=None, keywords=None, defaults=(False, False, None))
paddle.fluid.layers.cast ArgSpec(args=['x', 'dtype'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.concat ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(0, None))
paddle.fluid.layers.sums ArgSpec(args=['input', 'out'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.assign ArgSpec(args=['input', 'output'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.fill_constant_batch_size_like ArgSpec(args=['input', 'shape', 'dtype', 'value', 'input_dim_idx', 'output_dim_idx'], varargs=None, keywords=None, defaults=(0, 0))
paddle.fluid.layers.fill_constant ArgSpec(args=['shape', 'dtype', 'value', 'force_cpu', 'out'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.argmin ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.layers.argmax ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.layers.argsort ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(-1, None))
paddle.fluid.layers.ones ArgSpec(args=['shape', 'dtype', 'force_cpu'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.layers.zeros ArgSpec(args=['shape', 'dtype', 'force_cpu'], varargs=None, keywords=None, defaults=(False,))
paddle.fluid.layers.reverse ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.split_lod_tensor ArgSpec(args=['input', 'mask', 'level'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.layers.merge_lod_tensor ArgSpec(args=['in_true', 'in_false', 'x', 'mask', 'level'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.layers.BlockGuard.__init__ ArgSpec(args=['self', 'main_program'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.BlockGuardWithCompletion.__init__ ArgSpec(args=['self', 'rnn'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.WhileGuard.__init__ ArgSpec(args=['self', 'while_op'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.While.__init__ ArgSpec(args=['self', 'cond', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.While.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.While.complete ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.Switch.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.Switch.case ArgSpec(args=['self', 'condition'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.Switch.default ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.lod_rank_table ArgSpec(args=['x', 'level'], varargs=None, keywords=None, defaults=(0,))
paddle.fluid.layers.max_sequence_len ArgSpec(args=['rank_table'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.lod_tensor_to_array ArgSpec(args=['x', 'table'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.array_to_lod_tensor ArgSpec(args=['x', 'table'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.increment ArgSpec(args=['x', 'value', 'in_place'], varargs=None, keywords=None, defaults=(1.0, True))
paddle.fluid.layers.array_write ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.create_array ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.less_than ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], varargs=None, keywords='ignored', defaults=(None, None))
paddle.fluid.layers.equal ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords='ignored', defaults=(None,))
paddle.fluid.layers.array_read ArgSpec(args=['array', 'i'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.shrink_memory ArgSpec(args=['x', 'i', 'table'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.array_length ArgSpec(args=['array'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.IfElse.__init__ ArgSpec(args=['self', 'cond', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.IfElse.false_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.IfElse.input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.IfElse.output ArgSpec(args=['self'], varargs='outs', keywords=None, defaults=None)
paddle.fluid.layers.IfElse.parent_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.IfElse.true_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.DynamicRNN.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.DynamicRNN.block ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
paddle.fluid.layers.DynamicRNN.memory ArgSpec(args=['self', 'init', 'shape', 'value', 'need_reorder', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 0.0, False, 'float32'))
paddle.fluid.layers.DynamicRNN.output ArgSpec(args=['self'], varargs='outputs', keywords=None, defaults=None)
paddle.fluid.layers.DynamicRNN.static_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.DynamicRNN.step_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.DynamicRNN.update_memory ArgSpec(args=['self', 'ex_mem', 'new_mem'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ConditionalBlock.__init__ ArgSpec(args=['self', 'inputs', 'is_scalar_condition', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.ConditionalBlock.block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ConditionalBlock.complete ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.__init__ ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.StaticRNN.complete_op ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.memory ArgSpec(args=['self', 'init', 'shape', 'batch_ref', 'init_value', 'init_batch_dim_idx', 'ref_batch_dim_idx'], varargs=None, keywords=None, defaults=(None, None, None, 0.0, 0, 1))
paddle.fluid.layers.StaticRNN.output ArgSpec(args=['self'], varargs='outputs', keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.parent_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.step ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.step_input ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.step_output ArgSpec(args=['self', 'o'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.StaticRNN.update_memory ArgSpec(args=['self', 'mem', 'var'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.reorder_lod_tensor_by_rank ArgSpec(args=['x', 'rank_table'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.__init__ ArgSpec(args=['self', 'places', 'use_nccl', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.ParallelDo.complete_op ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.do ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.get_parameters ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.parent_block ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.read_input ArgSpec(args=['self', 'var'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.ParallelDo.write_output ArgSpec(args=['self', 'var'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.Print ArgSpec(args=['input', 'first_n', 'message', 'summarize', 'print_tensor_name', 'print_tensor_type', 'print_tensor_shape', 'print_tensor_lod', 'print_phase'], varargs=None, keywords=None, defaults=(-1, None, -1, True, True, True, True, 'both'))
paddle.fluid.layers.is_empty ArgSpec(args=['x', 'cond'], varargs=None, keywords='ignored', defaults=(None,))
paddle.fluid.layers.mean ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.mul ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.scale ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid_cross_entropy_with_logits ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_add ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_div ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_sub ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_mul ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_max ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_min ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elementwise_pow ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.clip ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.clip_by_norm ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_and ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_or ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_xor ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logical_not ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.uniform_random_batch_size_like ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.gaussian_random ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.gaussian_random_batch_size_like ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.scatter ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sum ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.slice ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.polygon_box_transform ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.shape ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.iou_similarity ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.maxout ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.logsigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.exp ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.tanh ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.tanh_shrink ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softshrink ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sqrt ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.abs ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.ceil ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.floor ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.cos ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.sin ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.round ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.reciprocal ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.square ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softplus ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.softsign ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.brelu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.leaky_relu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.soft_relu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.elu ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.relu6 ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.pow ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.stanh ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.hard_sigmoid ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.swish ArgSpec(args=[], varargs='args', keywords='kwargs', defaults=None)
paddle.fluid.layers.uniform_random ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.layers.hard_shrink ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.cumsum ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None))
paddle.fluid.layers.thresholded_relu ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.prior_box ArgSpec(args=['input', 'image', 'min_sizes', 'max_sizes', 'aspect_ratios', 'variance', 'flip', 'clip', 'steps', 'offset', 'name', 'min_max_aspect_ratios_order'], varargs=None, keywords=None, defaults=(None, [1.0], [0.1, 0.1, 0.2, 0.2], False, False, [0.0, 0.0], 0.5, None, False))
paddle.fluid.layers.multi_box_head ArgSpec(args=['inputs', 'image', 'base_size', 'num_classes', 'aspect_ratios', 'min_ratio', 'max_ratio', 'min_sizes', 'max_sizes', 'steps', 'step_w', 'step_h', 'offset', 'variance', 'flip', 'clip', 'kernel_size', 'pad', 'stride', 'name', 'min_max_aspect_ratios_order'], varargs=None, keywords=None, defaults=(None, None, None, None, None, None, None, 0.5, [0.1, 0.1, 0.2, 0.2], True, False, 1, 0, 1, None, False))
paddle.fluid.layers.bipartite_match ArgSpec(args=['dist_matrix', 'match_type', 'dist_threshold', 'name'], varargs=None, keywords=None, defaults=(None, None, None))
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
浏览文件 @ e9c8d930
...@@ -5,7 +5,7 @@ if (TENSORRT_FOUND) ...@@ -5,7 +5,7 @@ if (TENSORRT_FOUND)
add_subdirectory(tensorrt) add_subdirectory(tensorrt)
endif() 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? # TODO(panyx0718): Should this be called paddle_fluid_inference_api_internal?
cc_library(paddle_fluid_api cc_library(paddle_fluid_api
...@@ -38,3 +38,4 @@ if(WITH_TESTING) ...@@ -38,3 +38,4 @@ if(WITH_TESTING)
# both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book # both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book
add_subdirectory(tests/book) add_subdirectory(tests/book)
endif() endif()
add_subdirectory(api)
paddle/contrib/inference/CMakeLists.txt → paddle/fluid/inference/api/CMakeLists.txt
浏览文件 @ e9c8d930
...@@ -43,21 +43,21 @@ function(inference_api_test TARGET_NAME) ...@@ -43,21 +43,21 @@ function(inference_api_test TARGET_NAME)
endfunction(inference_api_test) endfunction(inference_api_test)
cc_library(paddle_inference_api 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}) DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
if(NOT APPLE) 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}") set_target_properties(paddle_inference_api PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
endif() endif()
# Here the shared library doesn't depend on other fluid libraries, or double free will occur. # Here the shared library doesn't depend on other fluid libraries, or double free will occur.
cc_library(paddle_inference_api_shared SHARED 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}) 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) set_target_properties(paddle_inference_api_shared PROPERTIES OUTPUT_NAME paddle_inference_api)
if(NOT APPLE) 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}") set_target_properties(paddle_inference_api_shared PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
FILE(WRITE ${CMAKE_CURRENT_BINARY_DIR}/check_symbol.cmake FILE(WRITE ${CMAKE_CURRENT_BINARY_DIR}/check_symbol.cmake
"execute_process(COMMAND bash -c \"${CMAKE_CURRENT_SOURCE_DIR}/check_symbol.sh" "execute_process(COMMAND bash -c \"${CMAKE_CURRENT_SOURCE_DIR}/check_symbol.sh"
...@@ -73,32 +73,32 @@ if(NOT APPLE) ...@@ -73,32 +73,32 @@ if(NOT APPLE)
endif() endif()
cc_test(test_paddle_inference_api cc_test(test_paddle_inference_api
SRCS test_paddle_inference_api.cc SRCS test_api.cc
DEPS paddle_inference_api) DEPS paddle_inference_api)
inference_api_test(test_paddle_inference_api_impl inference_api_test(test_api_impl
ARGS test_word2vec test_image_classification) ARGS test_word2vec test_image_classification)
if(WITH_GPU AND TENSORRT_FOUND) if(WITH_GPU AND TENSORRT_FOUND)
cc_library(paddle_inference_tensorrt_subgraph_engine cc_library(paddle_inference_tensorrt_subgraph_engine
SRCS paddle_inference_api_tensorrt_subgraph_engine.cc SRCS api_tensorrt_subgraph_engine.cc
DEPS paddle_inference_api analysis tensorrt_engine paddle_inference_api paddle_fluid_api) 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() endif()
if (WITH_ANAKIN) # only needed in CI 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, # 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 # 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. # 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 SRCS api.cc 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_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 BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
target_compile_options(inference_anakin_api_shared BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS}) target_compile_options(inference_anakin_api_shared BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS})
target_link_libraries(inference_anakin_api anakin anakin_saber_common) target_link_libraries(inference_anakin_api anakin anakin_saber_common)
target_link_libraries(inference_anakin_api_shared anakin anakin_saber_common) target_link_libraries(inference_anakin_api_shared anakin anakin_saber_common)
if (WITH_TESTING) if (WITH_TESTING)
cc_test(inference_anakin_test SRCS paddle_inference_api_anakin_engine_tester.cc cc_test(inference_anakin_test SRCS api_anakin_engine_tester.cc
ARGS --model=${ANAKIN_INSTALL_DIR}/mobilenet_v2.anakin.bin ARGS --model=${ANAKIN_INSTALL_DIR}/mobilenet_v2.anakin.bin
DEPS inference_anakin_api) DEPS inference_anakin_api)
target_compile_options(inference_anakin_test BEFORE PUBLIC ${ANAKIN_COMPILE_EXTRA_FLAGS}) 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
浏览文件 @ e9c8d930
...@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -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 See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/contrib/inference/paddle_inference_api.h" #include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle { namespace paddle {
......
paddle/contrib/inference/paddle_inference_api_anakin_engine.cc → paddle/fluid/inference/api/api_anakin_engine.cc
浏览文件 @ e9c8d930
...@@ -12,8 +12,9 @@ ...@@ -12,8 +12,9 @@
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // 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 <cuda.h>
#include <vector>
namespace paddle { namespace paddle {
...@@ -47,8 +48,7 @@ bool PaddleInferenceAnakinPredictor::Run( ...@@ -47,8 +48,7 @@ bool PaddleInferenceAnakinPredictor::Run(
} }
auto d_tensor_in_p = executor_.get_in(input.name); auto d_tensor_in_p = executor_.get_in(input.name);
float *d_data_p = d_tensor_in_p->mutable_data(); float *d_data_p = d_tensor_in_p->mutable_data();
if (cudaMemcpy(d_data_p, if (cudaMemcpy(d_data_p, static_cast<float *>(input.data.data()),
static_cast<float *>(input.data.data()),
d_tensor_in_p->valid_size() * sizeof(float), d_tensor_in_p->valid_size() * sizeof(float),
cudaMemcpyHostToDevice) != 0) { cudaMemcpyHostToDevice) != 0) {
LOG(ERROR) << "copy data from CPU to GPU error"; LOG(ERROR) << "copy data from CPU to GPU error";
...@@ -70,8 +70,7 @@ bool PaddleInferenceAnakinPredictor::Run( ...@@ -70,8 +70,7 @@ bool PaddleInferenceAnakinPredictor::Run(
output.data.Resize(tensor->valid_size() * sizeof(float)); output.data.Resize(tensor->valid_size() * sizeof(float));
} }
// Copy data from GPU -> CPU // Copy data from GPU -> CPU
if (cudaMemcpy(output.data.data(), if (cudaMemcpy(output.data.data(), tensor->mutable_data(),
tensor->mutable_data(),
tensor->valid_size() * sizeof(float), tensor->valid_size() * sizeof(float),
cudaMemcpyDeviceToHost) != 0) { cudaMemcpyDeviceToHost) != 0) {
LOG(ERROR) << "copy data from GPU to CPU error"; LOG(ERROR) << "copy data from GPU to CPU error";
...@@ -106,13 +105,12 @@ std::unique_ptr<PaddlePredictor> PaddleInferenceAnakinPredictor::Clone() { ...@@ -106,13 +105,12 @@ std::unique_ptr<PaddlePredictor> PaddleInferenceAnakinPredictor::Clone() {
// A factory to help create difference predictor. // A factory to help create difference predictor.
template <> template <>
std::unique_ptr<PaddlePredictor> std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
CreatePaddlePredictor<AnakinConfig, PaddleEngineKind::kAnakin>( AnakinConfig, PaddleEngineKind::kAnakin>(const AnakinConfig &config) {
const AnakinConfig &config) {
VLOG(3) << "Anakin Predictor create."; VLOG(3) << "Anakin Predictor create.";
std::unique_ptr<PaddlePredictor> x( std::unique_ptr<PaddlePredictor> x(
new PaddleInferenceAnakinPredictor(config)); new PaddleInferenceAnakinPredictor(config));
return x; return x;
}; }
} // namespace paddle } // namespace paddle
paddle/contrib/inference/paddle_inference_api_anakin_engine.h → paddle/fluid/inference/api/api_anakin_engine.h
浏览文件 @ e9c8d930
...@@ -19,7 +19,8 @@ limitations under the License. */ ...@@ -19,7 +19,8 @@ limitations under the License. */
#pragma once #pragma once
#include "paddle/contrib/inference/paddle_inference_api.h" #include <vector>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
// from anakin // from anakin
#include "framework/core/net/net.h" #include "framework/core/net/net.h"
...@@ -31,7 +32,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor { ...@@ -31,7 +32,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
public: public:
PaddleInferenceAnakinPredictor() {} PaddleInferenceAnakinPredictor() {}
PaddleInferenceAnakinPredictor(const AnakinConfig& config); explicit PaddleInferenceAnakinPredictor(const AnakinConfig& config);
// NOTE Unlike the native engine, the buffers of anakin engine's output_data // NOTE Unlike the native engine, the buffers of anakin engine's output_data
// should be allocated first. // should be allocated first.
...@@ -48,8 +49,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor { ...@@ -48,8 +49,7 @@ class PaddleInferenceAnakinPredictor : public PaddlePredictor {
private: private:
bool Init(const AnakinConfig& config); bool Init(const AnakinConfig& config);
anakin::graph::Graph<anakin::NV, anakin::graph::Graph<anakin::NV, anakin::saber::AK_FLOAT,
anakin::saber::AK_FLOAT,
anakin::Precision::FP32> anakin::Precision::FP32>
graph_; graph_;
anakin::Net<anakin::NV, anakin::saber::AK_FLOAT, anakin::Precision::FP32> 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
浏览文件 @ e9c8d930
...@@ -16,7 +16,7 @@ limitations under the License. */ ...@@ -16,7 +16,7 @@ limitations under the License. */
#include <glog/logging.h> #include <glog/logging.h>
#include <gtest/gtest.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."); DEFINE_string(model, "", "Directory of the inference model.");
......
paddle/contrib/inference/paddle_inference_api_impl.cc → paddle/fluid/inference/api/api_impl.cc
浏览文件 @ e9c8d930
...@@ -21,7 +21,7 @@ limitations under the License. */ ...@@ -21,7 +21,7 @@ limitations under the License. */
#include <utility> #include <utility>
#include <vector> #include <vector>
#include "paddle/contrib/inference/paddle_inference_api_impl.h" #include "paddle/fluid/inference/api/api_impl.h"
namespace paddle { namespace paddle {
namespace { namespace {
...@@ -77,8 +77,8 @@ bool NativePaddlePredictor::Init( ...@@ -77,8 +77,8 @@ bool NativePaddlePredictor::Init(
if (!config_.model_dir.empty()) { if (!config_.model_dir.empty()) {
// Parameters are saved in separate files sited in // Parameters are saved in separate files sited in
// the specified `dirname`. // the specified `dirname`.
inference_program_ = paddle::inference::Load( inference_program_ = paddle::inference::Load(executor_.get(), scope_.get(),
executor_.get(), scope_.get(), config_.model_dir); config_.model_dir);
} else if (!config_.prog_file.empty() && !config_.param_file.empty()) { } else if (!config_.prog_file.empty() && !config_.param_file.empty()) {
// All parameters are saved in a single file. // All parameters are saved in a single file.
// The file names should be consistent with that used // The file names should be consistent with that used
...@@ -91,8 +91,8 @@ bool NativePaddlePredictor::Init( ...@@ -91,8 +91,8 @@ bool NativePaddlePredictor::Init(
} }
ctx_ = executor_->Prepare(*inference_program_, 0); ctx_ = executor_->Prepare(*inference_program_, 0);
executor_->CreateVariables( executor_->CreateVariables(*inference_program_,
*inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0); sub_scope_ ? sub_scope_ : scope_.get(), 0);
// Get the feed_target_names and fetch_target_names // Get the feed_target_names and fetch_target_names
feed_target_names_ = inference_program_->GetFeedTargetNames(); feed_target_names_ = inference_program_->GetFeedTargetNames();
...@@ -105,7 +105,7 @@ NativePaddlePredictor::~NativePaddlePredictor() { ...@@ -105,7 +105,7 @@ NativePaddlePredictor::~NativePaddlePredictor() {
PADDLE_ENFORCE_NOT_NULL(scope_, "Should have parent scope!"); PADDLE_ENFORCE_NOT_NULL(scope_, "Should have parent scope!");
scope_->DeleteScope(sub_scope_); scope_->DeleteScope(sub_scope_);
} }
}; }
bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs, bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
std::vector<PaddleTensor> *output_data) { std::vector<PaddleTensor> *output_data) {
...@@ -134,10 +134,8 @@ bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs, ...@@ -134,10 +134,8 @@ bool NativePaddlePredictor::Run(const std::vector<PaddleTensor> &inputs,
// if share variables, we need not create variables // if share variables, we need not create variables
VLOG(4) << "Run prepared context"; VLOG(4) << "Run prepared context";
executor_->RunPreparedContext( executor_->RunPreparedContext(
ctx_.get(), ctx_.get(), sub_scope_ != nullptr ? sub_scope_ : scope_.get(),
sub_scope_ != nullptr ? sub_scope_ : scope_.get(), &feed_targets, &fetch_targets,
&feed_targets,
&fetch_targets,
false /* don't create variable eatch time */); false /* don't create variable eatch time */);
VLOG(4) << "Finish prepared context"; VLOG(4) << "Finish prepared context";
if (!GetFetch(fetchs, output_data)) { if (!GetFetch(fetchs, output_data)) {
...@@ -181,8 +179,7 @@ bool NativePaddlePredictor::SetFeed(const std::vector<PaddleTensor> &inputs, ...@@ -181,8 +179,7 @@ bool NativePaddlePredictor::SetFeed(const std::vector<PaddleTensor> &inputs,
} }
// TODO(panyx0718): Init LoDTensor from existing memcpy to save a copy. // TODO(panyx0718): Init LoDTensor from existing memcpy to save a copy.
std::memcpy(static_cast<void *>(input_ptr), std::memcpy(static_cast<void *>(input_ptr), inputs[i].data.data(),
inputs[i].data.data(),
inputs[i].data.length()); inputs[i].data.length());
feeds->push_back(input); feeds->push_back(input);
} }
...@@ -232,8 +229,7 @@ bool NativePaddlePredictor::GetFetch( ...@@ -232,8 +229,7 @@ bool NativePaddlePredictor::GetFetch(
size_t start = lod[0][j - 1] * common_dim; size_t start = lod[0][j - 1] * common_dim;
size_t end = lod[0][j] * common_dim; size_t end = lod[0][j] * common_dim;
if (end > start) { if (end > start) {
std::copy(output_ptr + start, std::copy(output_ptr + start, output_ptr + end,
output_ptr + end,
data.begin() + (j - 1) * max_dim * common_dim); data.begin() + (j - 1) * max_dim * common_dim);
} }
} }
...@@ -257,15 +253,13 @@ bool NativePaddlePredictor::GetFetch( ...@@ -257,15 +253,13 @@ bool NativePaddlePredictor::GetFetch(
} }
template <> template <>
std::unique_ptr<PaddlePredictor> std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
CreatePaddlePredictor<NativeConfig, PaddleEngineKind::kNative>( NativeConfig, PaddleEngineKind::kNative>(const NativeConfig &config) {
const NativeConfig &config) {
VLOG(3) << "create NativePaddlePredictor"; VLOG(3) << "create NativePaddlePredictor";
if (config.use_gpu) { if (config.use_gpu) {
// 1. GPU memeroy // 1. GPU memeroy
PADDLE_ENFORCE_GT( PADDLE_ENFORCE_GT(
config.fraction_of_gpu_memory, config.fraction_of_gpu_memory, 0.f,
0.f,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]"); "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); PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
std::vector<std::string> flags; std::vector<std::string> flags;
......
paddle/contrib/inference/paddle_inference_api_impl.h → paddle/fluid/inference/api/api_impl.h
浏览文件 @ e9c8d930
...@@ -19,7 +19,7 @@ ...@@ -19,7 +19,7 @@
#include <string> #include <string>
#include <vector> #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/ddim.h"
#include "paddle/fluid/framework/lod_tensor.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
浏览文件 @ e9c8d930
...@@ -12,9 +12,9 @@ ...@@ -12,9 +12,9 @@
// See the License for the specific language governing permissions and // See the License for the specific language governing permissions and
// limitations under the License. // 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/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" #include "paddle/fluid/inference/utils/singleton.h"
namespace paddle { namespace paddle {
...@@ -77,8 +77,8 @@ class TensorRTSubgraphPredictor : public NativePaddlePredictor { ...@@ -77,8 +77,8 @@ class TensorRTSubgraphPredictor : public NativePaddlePredictor {
ctx_ = executor_->Prepare(*inference_program_, 0); ctx_ = executor_->Prepare(*inference_program_, 0);
VLOG(5) << "to create variables"; VLOG(5) << "to create variables";
executor_->CreateVariables( executor_->CreateVariables(*inference_program_,
*inference_program_, sub_scope_ ? sub_scope_ : scope_.get(), 0); sub_scope_ ? sub_scope_ : scope_.get(), 0);
// Get the feed_target_names and fetch_target_names // Get the feed_target_names and fetch_target_names
feed_target_names_ = inference_program_->GetFeedTargetNames(); feed_target_names_ = inference_program_->GetFeedTargetNames();
...@@ -98,8 +98,7 @@ CreatePaddlePredictor<TensorRTConfig, PaddleEngineKind::kAutoMixedTensorRT>( ...@@ -98,8 +98,7 @@ CreatePaddlePredictor<TensorRTConfig, PaddleEngineKind::kAutoMixedTensorRT>(
if (config.use_gpu) { if (config.use_gpu) {
// 1. GPU memeroy // 1. GPU memeroy
PADDLE_ENFORCE_GT( PADDLE_ENFORCE_GT(
config.fraction_of_gpu_memory, config.fraction_of_gpu_memory, 0.f,
0.f,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]"); "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); PADDLE_ENFORCE_GE(config.device, 0, "Invalid device id %d", config.device);
std::vector<std::string> flags; std::vector<std::string> flags;
......
paddle/contrib/inference/demo_ci/CMakeLists.txt → paddle/fluid/inference/api/demo_ci/CMakeLists.txt
浏览文件 @ e9c8d930
...@@ -55,11 +55,11 @@ endif() ...@@ -55,11 +55,11 @@ endif()
# Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a # Note: libpaddle_inference_api.so/a must put before libpaddle_fluid.so/a
if(WITH_STATIC_LIB) if(WITH_STATIC_LIB)
set(DEPS 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) ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.a)
else() else()
set(DEPS 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) ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.so)
endif() endif()
set(EXTERNAL_LIB "-lrt -ldl -lpthread") set(EXTERNAL_LIB "-lrt -ldl -lpthread")
......
paddle/contrib/inference/demo_ci/run.sh → paddle/fluid/inference/api/demo_ci/run.sh
浏览文件 @ e9c8d930
...@@ -64,7 +64,7 @@ for WITH_STATIC_LIB in ON OFF; do ...@@ -64,7 +64,7 @@ for WITH_STATIC_LIB in ON OFF; do
-DWITH_GPU=$TEST_GPU_CPU \ -DWITH_GPU=$TEST_GPU_CPU \
-DWITH_STATIC_LIB=$WITH_STATIC_LIB -DWITH_STATIC_LIB=$WITH_STATIC_LIB
make -j 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 for vis_demo_name in $vis_demo_list; do
./vis_demo \ ./vis_demo \
--modeldir=../data/$vis_demo_name/model \ --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
浏览文件 @ e9c8d930
...@@ -19,8 +19,8 @@ limitations under the License. */ ...@@ -19,8 +19,8 @@ limitations under the License. */
#include <gflags/gflags.h> #include <gflags/gflags.h>
#include <glog/logging.h> #include <glog/logging.h>
#include <memory> #include <memory>
#include <thread> #include <thread> //NOLINT
#include "contrib/inference/paddle_inference_api.h" #include "paddle/fluid/inference/paddle_inference_api.h"
#include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/platform/enforce.h"
DEFINE_string(dirname, "", "Directory of the inference model."); DEFINE_string(dirname, "", "Directory of the inference model.");
...@@ -63,8 +63,8 @@ void Main(bool use_gpu) { ...@@ -63,8 +63,8 @@ void Main(bool use_gpu) {
PADDLE_ENFORCE(outputs.size(), 1UL); PADDLE_ENFORCE(outputs.size(), 1UL);
// Check the output buffer size and result of each tid. // Check the output buffer size and result of each tid.
PADDLE_ENFORCE(outputs.front().data.length(), 33168UL); PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
float result[5] = { float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706}; 0.000932706};
const size_t num_elements = outputs.front().data.length() / sizeof(float); const size_t num_elements = outputs.front().data.length() / sizeof(float);
// The outputs' buffers are in CPU memory. // The outputs' buffers are in CPU memory.
for (size_t i = 0; i < std::min(5UL, num_elements); i++) { for (size_t i = 0; i < std::min(5UL, num_elements); i++) {
...@@ -107,8 +107,8 @@ void MainThreads(int num_threads, bool use_gpu) { ...@@ -107,8 +107,8 @@ void MainThreads(int num_threads, bool use_gpu) {
PADDLE_ENFORCE(outputs.size(), 1UL); PADDLE_ENFORCE(outputs.size(), 1UL);
// Check the output buffer size and result of each tid. // Check the output buffer size and result of each tid.
PADDLE_ENFORCE(outputs.front().data.length(), 33168UL); PADDLE_ENFORCE(outputs.front().data.length(), 33168UL);
float result[5] = { float result[5] = {0.00129761, 0.00151112, 0.000423564, 0.00108815,
0.00129761, 0.00151112, 0.000423564, 0.00108815, 0.000932706}; 0.000932706};
const size_t num_elements = const size_t num_elements =
outputs.front().data.length() / sizeof(float); outputs.front().data.length() / sizeof(float);
// The outputs' buffers are in CPU memory. // The outputs' buffers are in CPU memory.
......
paddle/contrib/inference/demo_ci/utils.h → paddle/fluid/inference/api/demo_ci/utils.h
浏览文件 @ e9c8d930
...@@ -13,16 +13,15 @@ ...@@ -13,16 +13,15 @@
// limitations under the License. // limitations under the License.
#pragma once #pragma once
#include <algorithm>
#include <string> #include <string>
#include <vector> #include <vector>
#include "paddle/fluid/inference/paddle_inference_api.h"
#include "contrib/inference/paddle_inference_api.h"
namespace paddle { namespace paddle {
namespace demo { namespace demo {
static void split(const std::string& str, static void split(const std::string& str, char sep,
char sep,
std::vector<std::string>* pieces) { std::vector<std::string>* pieces) {
pieces->clear(); pieces->clear();
if (str.empty()) { if (str.empty()) {
......
paddle/contrib/inference/demo_ci/vis_demo.cc → paddle/fluid/inference/api/demo_ci/vis_demo.cc
浏览文件 @ e9c8d930
...@@ -29,8 +29,7 @@ DECLARE_double(fraction_of_gpu_memory_to_use); ...@@ -29,8 +29,7 @@ DECLARE_double(fraction_of_gpu_memory_to_use);
DEFINE_string(modeldir, "", "Directory of the inference model."); DEFINE_string(modeldir, "", "Directory of the inference model.");
DEFINE_string(refer, "", "path to reference result for comparison."); DEFINE_string(refer, "", "path to reference result for comparison.");
DEFINE_string( DEFINE_string(
data, data, "",
"",
"path of data; each line is a record, format is " "path of data; each line is a record, format is "
"'<space splitted floats as data>\t<space splitted ints as shape'"); "'<space splitted floats as data>\t<space splitted ints as shape'");
DEFINE_bool(use_gpu, false, "Whether use gpu."); DEFINE_bool(use_gpu, false, "Whether use gpu.");
......
paddle/contrib/inference/test_paddle_inference_api.cc → paddle/fluid/inference/api/test_api.cc
浏览文件 @ e9c8d930
...@@ -12,10 +12,9 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. ...@@ -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 See the License for the specific language governing permissions and
limitations under the License. */ limitations under the License. */
#include "paddle/contrib/inference/paddle_inference_api.h"
#include <glog/logging.h> #include <glog/logging.h>
#include <gtest/gtest.h> #include <gtest/gtest.h>
#include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle { namespace paddle {
......
paddle/contrib/inference/test_paddle_inference_api_impl.cc → paddle/fluid/inference/api/test_api_impl.cc
浏览文件 @ e9c8d930
...@@ -15,10 +15,10 @@ limitations under the License. */ ...@@ -15,10 +15,10 @@ limitations under the License. */
#include <glog/logging.h> #include <glog/logging.h>
#include <gtest/gtest.h> #include <gtest/gtest.h>
#include <thread> #include <thread> // NOLINT
#include "gflags/gflags.h" #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" #include "paddle/fluid/inference/tests/test_helper.h"
DEFINE_string(dirname, "", "Directory of the inference model."); DEFINE_string(dirname, "", "Directory of the inference model.");
...@@ -121,8 +121,8 @@ void MainImageClassification(bool use_gpu) { ...@@ -121,8 +121,8 @@ void MainImageClassification(bool use_gpu) {
// which should be in the range [0.0, 1.0]. // which should be in the range [0.0, 1.0].
feed_target_shapes[0][0] = batch_size; feed_target_shapes[0][0] = batch_size;
framework::DDim input_dims = framework::make_ddim(feed_target_shapes[0]); framework::DDim input_dims = framework::make_ddim(feed_target_shapes[0]);
SetupTensor<float>( SetupTensor<float>(&input, input_dims, static_cast<float>(0),
&input, input_dims, static_cast<float>(0), static_cast<float>(1)); static_cast<float>(1));
std::vector<framework::LoDTensor*> cpu_feeds; std::vector<framework::LoDTensor*> cpu_feeds;
cpu_feeds.push_back(&input); 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
浏览文件 @ e9c8d930
...@@ -15,7 +15,7 @@ ...@@ -15,7 +15,7 @@
#include <gflags/gflags.h> #include <gflags/gflags.h>
#include <glog/logging.h> #include <glog/logging.h>
#include <gtest/gtest.h> #include <gtest/gtest.h>
#include "paddle/contrib/inference/paddle_inference_api.h" #include "paddle/fluid/inference/api/paddle_inference_api.h"
namespace paddle { namespace paddle {
......
paddle/fluid/operators/im2sequence_op.cc
浏览文件 @ e9c8d930
...@@ -33,22 +33,14 @@ class Im2SequenceOp : public framework::OperatorWithKernel { ...@@ -33,22 +33,14 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(in_dim.size(), 4, PADDLE_ENFORCE_EQ(in_dim.size(), 4,
"Input(X) format must be 4D tensor, eg., NCHW."); "Input(X) format must be 4D tensor, eg., NCHW.");
int batch_size = in_dim[0];
int img_channels = in_dim[1]; 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 kernels = ctx->Attrs().Get<std::vector<int>>("kernels");
auto strides = ctx->Attrs().Get<std::vector<int>>("strides"); auto strides = ctx->Attrs().Get<std::vector<int>>("strides");
auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings"); auto paddings = ctx->Attrs().Get<std::vector<int>>("paddings");
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0], ctx->SetOutputDim("Out",
paddings[2], strides[0]); {in_dim[0], img_channels * kernels[0] * kernels[1]});
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]});
} }
}; };
......
paddle/fluid/operators/im2sequence_op.h
浏览文件 @ e9c8d930
...@@ -109,12 +109,13 @@ class Im2SequenceKernel : public framework::OpKernel<T> { ...@@ -109,12 +109,13 @@ class Im2SequenceKernel : public framework::OpKernel<T> {
} }
out->set_lod(lod); out->set_lod(lod);
} else { } else {
out->mutable_data<T>(ctx.GetPlace());
int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0], int output_height = Im2SeqOutputSize(img_height, kernels[0], paddings[0],
paddings[2], strides[0]); paddings[2], strides[0]);
int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1], int output_width = Im2SeqOutputSize(img_width, kernels[1], paddings[1],
paddings[3], strides[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}); const std::vector<int> dilations({1, 1});
auto out_dims = out->dims(); auto out_dims = out->dims();
out->Resize({batch_size, out->numel() / batch_size}); out->Resize({batch_size, out->numel() / batch_size});
......
paddle/fluid/operators/sum_mkldnn_op.cc
浏览文件 @ e9c8d930
...@@ -88,7 +88,7 @@ class SumMKLDNNOpKernel : public paddle::framework::OpKernel<T> { ...@@ -88,7 +88,7 @@ class SumMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
input_format = memory::format::nc; 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>(), PADDLE_ENFORCE(in_vars[i]->IsType<LoDTensor>(),
"all inputs must be all LoDTensors"); "all inputs must be all LoDTensors");
auto& input = in_vars[i]->Get<LoDTensor>(); auto& input = in_vars[i]->Get<LoDTensor>();
......
paddle/scripts/paddle_build.sh
浏览文件 @ e9c8d930
...@@ -19,6 +19,8 @@ ...@@ -19,6 +19,8 @@
# Utils # Utils
#================================================= #=================================================
set -ex
function print_usage() { function print_usage() {
echo -e "\n${RED}Usage${NONE}: echo -e "\n${RED}Usage${NONE}:
${BOLD}${SCRIPT_NAME}${NONE} [OPTION]" ${BOLD}${SCRIPT_NAME}${NONE} [OPTION]"
...@@ -37,6 +39,7 @@ function print_usage() { ...@@ -37,6 +39,7 @@ function print_usage() {
${BLUE}fluid_inference_lib${NONE}: deploy fluid inference library ${BLUE}fluid_inference_lib${NONE}: deploy fluid inference library
${BLUE}check_style${NONE}: run code style check ${BLUE}check_style${NONE}: run code style check
${BLUE}cicheck${NONE}: run CI tasks ${BLUE}cicheck${NONE}: run CI tasks
${BLUE}assert_api_not_changed${NONE}: check api compability
" "
} }
...@@ -326,11 +329,22 @@ function assert_api_not_changed() { ...@@ -326,11 +329,22 @@ function assert_api_not_changed() {
virtualenv .env virtualenv .env
source .env/bin/activate source .env/bin/activate
pip install ${PADDLE_ROOT}/build/python/dist/*whl 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/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 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() { ...@@ -531,13 +545,12 @@ function test_fluid_inference_lib() {
Testing fluid inference library ... Testing fluid inference library ...
======================================== ========================================
EOF 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} ./run.sh ${PADDLE_ROOT} ${WITH_MKL:-ON} ${WITH_GPU:-OFF}
fi fi
} }
function main() { function main() {
set -e
local CMD=$1 local CMD=$1
init init
case $CMD in case $CMD in
......
python/paddle/fluid/layers/io.py
浏览文件 @ e9c8d930
...@@ -26,8 +26,7 @@ from ..layer_helper import LayerHelper ...@@ -26,8 +26,7 @@ from ..layer_helper import LayerHelper
from ..unique_name import generate as unique_name from ..unique_name import generate as unique_name
__all__ = [ __all__ = [
'data', 'BlockGuardServ', 'ListenAndServ', 'Send', 'Recv', 'data', 'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
'open_recordio_file', 'open_files', 'read_file', 'shuffle', 'batch',
'double_buffer', 'random_data_generator', 'py_reader', 'Preprocessor', 'double_buffer', 'random_data_generator', 'py_reader', 'Preprocessor',
'load' 'load'
] ]
...@@ -908,7 +907,7 @@ class Preprocessor(object): ...@@ -908,7 +907,7 @@ class Preprocessor(object):
self.sink_var_names = None self.sink_var_names = None
self.status = Preprocessor.BEFORE_SUB_BLOCK 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 return self.sub_block and self.source_var_names and self.sink_var_names
@contextlib.contextmanager @contextlib.contextmanager
...@@ -918,7 +917,7 @@ class Preprocessor(object): ...@@ -918,7 +917,7 @@ class Preprocessor(object):
yield yield
self.main_prog.rollback() self.main_prog.rollback()
self.status = Preprocessor.AFTER_SUB_BLOCK self.status = Preprocessor.AFTER_SUB_BLOCK
if not self.is_completed(): if not self._is_completed():
raise RuntimeError( raise RuntimeError(
"The definition of preprocessor is incompleted! " "The definition of preprocessor is incompleted! "
"Please make sure that you have set input and output " "Please make sure that you have set input and output "
......
python/paddle/fluid/optimizer.py
浏览文件 @ e9c8d930
...@@ -1180,16 +1180,16 @@ class ModelAverage(Optimizer): ...@@ -1180,16 +1180,16 @@ class ModelAverage(Optimizer):
self._add_average_restore_op(block, param_grad) self._add_average_restore_op(block, param_grad)
def _add_average_apply_op(self, block, param_grad): def _add_average_apply_op(self, block, param_grad):
param = block.clone_variable(param_grad[0]) param = block._clone_variable(param_grad[0])
grad = block.clone_variable(param_grad[1]) grad = block._clone_variable(param_grad[1])
sum_1 = block.clone_variable(self._get_accumulator('sum_1', param)) sum_1 = block._clone_variable(self._get_accumulator('sum_1', param))
sum_2 = block.clone_variable(self._get_accumulator('sum_2', param)) sum_2 = block._clone_variable(self._get_accumulator('sum_2', param))
sum_3 = block.clone_variable(self._get_accumulator('sum_3', param)) sum_3 = block._clone_variable(self._get_accumulator('sum_3', param))
num_accumulates = block.clone_variable( num_accumulates = block._clone_variable(
self._get_accumulator('num_accumulates', param)) 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)) self._get_accumulator('old_num_accumulates', param))
num_updates = block.clone_variable( num_updates = block._clone_variable(
self._get_accumulator('num_updates', param)) self._get_accumulator('num_updates', param))
# backup param value to grad # backup param value to grad
layers.assign(input=param, output=grad) layers.assign(input=param, output=grad)
...@@ -1203,8 +1203,8 @@ class ModelAverage(Optimizer): ...@@ -1203,8 +1203,8 @@ class ModelAverage(Optimizer):
layers.elementwise_div(x=sum, y=tmp, out=param) layers.elementwise_div(x=sum, y=tmp, out=param)
def _add_average_restore_op(self, block, param_grad): def _add_average_restore_op(self, block, param_grad):
param = block.clone_variable(param_grad[0]) param = block._clone_variable(param_grad[0])
grad = block.clone_variable(param_grad[1]) grad = block._clone_variable(param_grad[1])
layers.assign(input=grad, output=param) layers.assign(input=grad, output=param)
def _append_average_accumulate_op(self, param): def _append_average_accumulate_op(self, param):
......
python/paddle/fluid/tests/unittests/test_dist_train.py
浏览文件 @ e9c8d930
...@@ -22,6 +22,9 @@ import numpy ...@@ -22,6 +22,9 @@ import numpy
import paddle.fluid as fluid import paddle.fluid as fluid
import paddle.fluid.layers as layers 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): class TestSendOp(unittest.TestCase):
...@@ -65,8 +68,7 @@ class TestSendOp(unittest.TestCase): ...@@ -65,8 +68,7 @@ class TestSendOp(unittest.TestCase):
main = fluid.Program() main = fluid.Program()
with fluid.program_guard(main): with fluid.program_guard(main):
serv = layers.ListenAndServ( serv = ListenAndServ("127.0.0.1:0", ["X"], optimizer_mode=False)
"127.0.0.1:0", ["X"], optimizer_mode=False)
with serv.do(): with serv.do():
out_var = main.global_block().create_var( out_var = main.global_block().create_var(
name="scale_0.tmp_0", name="scale_0.tmp_0",
...@@ -99,8 +101,8 @@ class TestSendOp(unittest.TestCase): ...@@ -99,8 +101,8 @@ class TestSendOp(unittest.TestCase):
persistable=False, persistable=False,
shape=[32, 32]) shape=[32, 32])
fluid.initializer.Constant(value=2.3)(get_var, main.global_block()) fluid.initializer.Constant(value=2.3)(get_var, main.global_block())
layers.Send("127.0.0.1:%d" % port, [x]) Send("127.0.0.1:%d" % port, [x])
o = layers.Recv("127.0.0.1:%d" % port, [get_var]) o = Recv("127.0.0.1:%d" % port, [get_var])
exe = fluid.Executor(place) exe = fluid.Executor(place)
self.dist_out = exe.run(main, fetch_list=o) # o is a list self.dist_out = exe.run(main, fetch_list=o) # o is a list
......
paddle/contrib/CMakeLists.txt → tools/check_pr_approval.py
浏览文件 @ e9c8d930
# 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"); # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. # you may not use this file except in compliance with the License.
...@@ -11,6 +11,39 @@ ...@@ -11,6 +11,39 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # 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] ..."
)
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