From 47e2ef38e98389c4f2c6606b6dd6dd5c4eb28f9d Mon Sep 17 00:00:00 2001 From: xsrobin <50069408+xsrobin@users.noreply.github.com> Date: Mon, 1 Jul 2019 12:09:09 +0800 Subject: [PATCH] add "import paddle.fluid as fluid" to examples lack of it --- paddle/fluid/API.spec | 358 +++++++++--------- paddle/fluid/pybind/pybind.cc | 5 + python/paddle/fluid/average.py | 1 + python/paddle/fluid/backward.py | 1 + python/paddle/fluid/data_feed_desc.py | 6 + python/paddle/fluid/executor.py | 1 + python/paddle/fluid/framework.py | 9 + python/paddle/fluid/initializer.py | 19 +- python/paddle/fluid/io.py | 8 + python/paddle/fluid/layers/control_flow.py | 8 + python/paddle/fluid/layers/detection.py | 13 + python/paddle/fluid/layers/io.py | 5 + .../fluid/layers/layer_function_generator.py | 1 + .../fluid/layers/learning_rate_scheduler.py | 5 +- python/paddle/fluid/layers/nn.py | 91 ++++- python/paddle/fluid/layers/ops.py | 3 + python/paddle/fluid/layers/tensor.py | 13 + python/paddle/fluid/metrics.py | 8 + python/paddle/fluid/nets.py | 2 + python/paddle/fluid/optimizer.py | 4 + python/paddle/fluid/profiler.py | 4 + 21 files changed, 378 insertions(+), 187 deletions(-) diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 83c76078344..b0eeb368ebd 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -9,11 +9,11 @@ paddle.fluid.Program.to_string (ArgSpec(args=['self', 'throw_on_error', 'with_de paddle.fluid.default_startup_program (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'ba609cb02e4e55e8d626723567ef1778')) paddle.fluid.default_main_program (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '853718df675e59aea7104f3d61bbf11d')) paddle.fluid.program_guard (ArgSpec(args=['main_program', 'startup_program'], varargs=None, keywords=None, defaults=(None,)), ('document', '78fb5c7f70ef76bcf4a1862c3f6b8191')) -paddle.fluid.name_scope (ArgSpec(args=['prefix'], varargs=None, keywords=None, defaults=(None,)), ('document', '61660461e1f44e0480ca22fa8a482c41')) -paddle.fluid.cuda_places (ArgSpec(args=['device_ids'], varargs=None, keywords=None, defaults=(None,)), ('document', '7f3068b82fc427bfa04b1af953610992')) -paddle.fluid.cpu_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'dad57e8624794766d770cea905dec1c2')) -paddle.fluid.cuda_pinned_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'cc83b6c5ba8be38ff3ee87e9cec9de5f')) -paddle.fluid.in_dygraph_mode (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'eddb7a1f0083dcc70e9f6c71ee003cb9')) +paddle.fluid.name_scope (ArgSpec(args=['prefix'], varargs=None, keywords=None, defaults=(None,)), ('document', '917d313881ff990de5fb18d98a9c7b42')) +paddle.fluid.cuda_places (ArgSpec(args=['device_ids'], varargs=None, keywords=None, defaults=(None,)), ('document', '1f2bb6ece651e44117652d2d7bedecf5')) +paddle.fluid.cpu_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', '956bab564ebc69ffd17195c08cc8ffa0')) +paddle.fluid.cuda_pinned_places (ArgSpec(args=['device_count'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c2562241744aabe3fff1b59af22dd281')) +paddle.fluid.in_dygraph_mode (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '301bae0d8e02cc9eec5be02f052f11c6')) paddle.fluid.is_compiled_with_cuda (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '60c7f107a5050aeb58bb74eb175672b5')) paddle.fluid.Executor.__init__ (ArgSpec(args=['self', 'place'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.Executor.close (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '3a584496aa1343f36eebf3c46b323a74')) @@ -21,7 +21,7 @@ paddle.fluid.Executor.infer_from_dataset (ArgSpec(args=['self', 'program', 'data 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)), ('document', '4cfcd9c15b766a51b584cc46d38f1ad8')) paddle.fluid.Executor.train_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100)), ('document', '28f50904a0213f110947a30e0438529c')) paddle.fluid.global_scope (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'f65788d9ead293ada47551339df12203')) -paddle.fluid.scope_guard (ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None), ('document', '6e19f92e2f185320a3a86b77e85eb3b3')) +paddle.fluid.scope_guard (ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None), ('document', 'e6c073ed237001aaba7bff976b62b122')) paddle.fluid.DistributeTranspiler.__init__ (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.DistributeTranspiler.get_pserver_program (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'b1951949c6d21698290aa8ac69afee32')) paddle.fluid.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'c89fc350f975ef827f5448d68af388cf')) @@ -37,10 +37,10 @@ paddle.fluid.ParallelExecutor.run (ArgSpec(args=['self', 'fetch_list', 'feed', ' paddle.fluid.create_lod_tensor (ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None), ('document', 'b82ea20e2dc5ff2372e0643169ca47ff')) paddle.fluid.create_random_int_lodtensor (ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '74dc6d23185d90a7a50fbac19f5b65fb')) paddle.fluid.DataFeedDesc.__init__ (ArgSpec(args=['self', 'proto_file'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.DataFeedDesc.desc (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '75283b5f03ec7b6f74bfca9881a37428')) -paddle.fluid.DataFeedDesc.set_batch_size (ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', '68df53d3ea0f24063bf7689e82c2b82e')) -paddle.fluid.DataFeedDesc.set_dense_slots (ArgSpec(args=['self', 'dense_slots_name'], varargs=None, keywords=None, defaults=None), ('document', 'd5a78553cd94fe64148399797055d8ad')) -paddle.fluid.DataFeedDesc.set_use_slots (ArgSpec(args=['self', 'use_slots_name'], varargs=None, keywords=None, defaults=None), ('document', '88d229ea9f892ce8d2922cf028c8bb3a')) +paddle.fluid.DataFeedDesc.desc (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '9c6615854b61caa5f0d3e6ccc5e51338')) +paddle.fluid.DataFeedDesc.set_batch_size (ArgSpec(args=['self', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', 'a34790bff4a2891713ddd644db56418d')) +paddle.fluid.DataFeedDesc.set_dense_slots (ArgSpec(args=['self', 'dense_slots_name'], varargs=None, keywords=None, defaults=None), ('document', 'fdd07ce63e72bed57f2c0db5bec5720f')) +paddle.fluid.DataFeedDesc.set_use_slots (ArgSpec(args=['self', 'use_slots_name'], varargs=None, keywords=None, defaults=None), ('document', 'c23a79dfa04edd014b477bd4b183da06')) paddle.fluid.CompiledProgram.__init__ (ArgSpec(args=['self', 'program_or_graph'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.CompiledProgram.with_data_parallel (ArgSpec(args=['self', 'loss_name', 'build_strategy', 'exec_strategy', 'share_vars_from', 'places'], varargs=None, keywords=None, defaults=(None, None, None, None, None)), ('document', '0e17773521634ef798fddd7d2ea3ef96')) paddle.fluid.CompiledProgram.with_inference_optimize (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=None), ('document', '9e5b009d850191a010e859189c127fd8')) @@ -53,8 +53,8 @@ paddle.fluid.io.save_vars (ArgSpec(args=['executor', 'dirname', 'main_program', paddle.fluid.io.save_params (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', '046d7c43d67e08c2660bb3bd7e081015')) paddle.fluid.io.save_persistables (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'ffcee38044975c29f2ab2fec0576f963')) paddle.fluid.io.load_vars (ArgSpec(args=['executor', 'dirname', 'main_program', 'vars', 'predicate', 'filename'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', '1bb9454cf09d71f190bb51550c5a3ac9')) -paddle.fluid.io.load_params (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', '944291120d37bdb037a689d2c86d0a6e')) -paddle.fluid.io.load_persistables (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', '28df5bfe26ca7a077f91156abb0fe6d2')) +paddle.fluid.io.load_params (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', '116a9ed169e7ff0226faccff3c29364c')) +paddle.fluid.io.load_persistables (ArgSpec(args=['executor', 'dirname', 'main_program', 'filename'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cfa84ef7c5435625bff4cc132cb8a0e3')) paddle.fluid.io.save_inference_model (ArgSpec(args=['dirname', 'feeded_var_names', 'target_vars', 'executor', 'main_program', 'model_filename', 'params_filename', 'export_for_deployment', 'program_only'], varargs=None, keywords=None, defaults=(None, None, None, True, False)), ('document', 'fc82bfd137a9b1ab8ebd1651bd35b6e5')) paddle.fluid.io.load_inference_model (ArgSpec(args=['dirname', 'executor', 'model_filename', 'params_filename', 'pserver_endpoints'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '2f54d7c206b62f8c10f4f9d78c731cfd')) paddle.fluid.io.PyReader.__init__ (ArgSpec(args=['self', 'feed_list', 'capacity', 'use_double_buffer', 'iterable', 'return_list'], varargs=None, keywords=None, defaults=(None, None, True, True, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -70,115 +70,115 @@ paddle.fluid.initializer.TruncatedNormalInitializer.__init__ (ArgSpec(args=['sel paddle.fluid.initializer.XavierInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'fan_out', 'seed'], varargs=None, keywords=None, defaults=(True, None, None, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.initializer.BilinearInitializer.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'd389912dc079cbef432335a00017cec0')) paddle.fluid.initializer.MSRAInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'seed'], varargs=None, keywords=None, defaults=(True, None, 0)), ('document', '53c757bed9345f2ad3361902531e7cf5')) -paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '2c6748c1dd1d85f800462869ea7a747f')) -paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '280b581f5a77e746e47decbc57a7b30a')) +paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '53c01b661feb8e60d0efa2066976c1a8')) +paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '68bebc3963526880a07c98a5d6226794')) paddle.fluid.initializer.NumpyArrayInitializer.__init__ (ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None)), ('document', '424e898365195e3ccbc2e7dc8b63605e')) +paddle.fluid.layers.fc (ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None)), ('document', '1c74f52549814235077ecc34856a95eb')) 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')), ('document', '6f9f96d2a1517cd1affebc960c3526f7')) -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)), ('document', '246ff18abc877dd576653006991918e9')) -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', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None)), ('document', '4f63053354bcc6c743b4d2f4e7104e25')) +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)), ('document', '6d3ee14da70adfa36d85c40b18716ef2')) +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', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None)), ('document', 'c37d51aad655c8a9f9b045c64717320a')) paddle.fluid.layers.dynamic_gru (ArgSpec(args=['input', 'size', 'param_attr', 'bias_attr', 'is_reverse', 'gate_activation', 'candidate_activation', 'h_0', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, False, 'sigmoid', 'tanh', None, False)), ('document', '83617c165827e030636c80486d5de6f3')) paddle.fluid.layers.gru_unit (ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid', False)), ('document', '33974b9bfa69f2f1eb85e6f956dff04e')) paddle.fluid.layers.linear_chain_crf (ArgSpec(args=['input', 'label', 'param_attr'], varargs=None, keywords=None, defaults=(None,)), ('document', '34f96be41684b0959897a9e735997e20')) -paddle.fluid.layers.crf_decoding (ArgSpec(args=['input', 'param_attr', 'label'], varargs=None, keywords=None, defaults=(None,)), ('document', '462ddf2435e3392334e0c05ae57a01c4')) -paddle.fluid.layers.cos_sim (ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None), ('document', 'cefab7c23ee5582727e8b22dffbafac8')) -paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100)), ('document', '535f1f6213dd7ca0fe5ed7cb4718c0e3')) +paddle.fluid.layers.crf_decoding (ArgSpec(args=['input', 'param_attr', 'label'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c469f22029f7b5d41ecd44dfa1e81ffd')) +paddle.fluid.layers.cos_sim (ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None), ('document', '8e6ce424cf9e261ef32ee229c06a6e66')) +paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100)), ('document', 'f43c659ca1749a3f0ff2231e6dfda07d')) paddle.fluid.layers.bpr_loss (ArgSpec(args=['input', 'label', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6263dfdeb6c670fa0922c9cbc8fb1bf4')) -paddle.fluid.layers.square_error_cost (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'f273bb26833ee88b349c4b8083e1dc67')) +paddle.fluid.layers.square_error_cost (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'bbb9e708bab250359864fefbdf48e9d9')) paddle.fluid.layers.chunk_eval (ArgSpec(args=['input', 'label', 'chunk_scheme', 'num_chunk_types', 'excluded_chunk_types'], varargs=None, keywords=None, defaults=(None,)), ('document', '5aa25d023acea1fb49a0de56be86990b')) paddle.fluid.layers.sequence_conv (ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'bias_attr', 'param_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(3, 1, None, None, None, None, None)), ('document', '3d8e8f3e0e1cf520156be37605e83ccd')) -paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '8ca6121acd6d23cd8806a93f493c2e17')) -paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', 'd2990494eaf531fb584321b7edfb5104')) +paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '114c7fe6b0adfc6d6371122f9b9f506e')) +paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None)), ('document', '367293b5bada54136a91621078d38334')) paddle.fluid.layers.sequence_pool (ArgSpec(args=['input', 'pool_type', 'is_test', 'pad_value'], varargs=None, keywords=None, defaults=(False, 0.0)), ('document', 'e90a93251c52dc4e6fb34fb3991b3f82')) -paddle.fluid.layers.sequence_softmax (ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '19ef6f9cdd27feac8a1ae060f19c10b4')) +paddle.fluid.layers.sequence_softmax (ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', 'eaa9d0bbd3d4e017c8bc4ecdac483711')) paddle.fluid.layers.softmax (ArgSpec(args=['input', 'use_cudnn', 'name', 'axis'], varargs=None, keywords=None, defaults=(False, None, -1)), ('document', 'cee673c79e3ff4582656a24e04f841e5')) -paddle.fluid.layers.pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', 'bbd84e855e660cd1084bb71a2fd0cdaa')) -paddle.fluid.layers.pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', '043de7333b79ee0ac55053c14ed81625')) -paddle.fluid.layers.adaptive_pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '859b887174d06f361658f69cb7c06d95')) +paddle.fluid.layers.pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', 'be7e530dcbd603962e25573a63eb145e')) +paddle.fluid.layers.pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True)), ('document', '053b1a855f13a066d005759171724bc6')) +paddle.fluid.layers.adaptive_pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '52343203de40afe29607397e13aaf0d2')) paddle.fluid.layers.adaptive_pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '55db6ae7275fb9678a6814aebab81a9c')) -paddle.fluid.layers.batch_norm (ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu', 'use_global_stats'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, None, None, None, False, False, False)), ('document', '9cf79315d3423dddba0404e8f85a89b8')) +paddle.fluid.layers.batch_norm (ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu', 'use_global_stats'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, None, None, None, False, False, False)), ('document', '4cc22c3553e73a958e8b9a240d894431')) paddle.fluid.layers.data_norm (ArgSpec(args=['input', 'act', 'epsilon', 'param_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var'], varargs=None, keywords=None, defaults=(None, 1e-05, None, 'NCHW', False, None, None, None, False)), ('document', '2460b30fb87037555208fa8ac6fc1787')) paddle.fluid.layers.beam_search_decode (ArgSpec(args=['ids', 'scores', 'beam_size', 'end_id', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '83e08f21af41ac8bac37aeab1f86fdd0')) -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)), ('document', '03993955ab1e6d3044c44e6f17fc85e9')) -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)), ('document', 'ec113c6a3686ac94f8fccd1a7953d445')) -paddle.fluid.layers.sequence_expand (ArgSpec(args=['x', 'y', 'ref_level', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', 'e91c4b68cc4d8e9f7787b76032a85e75')) -paddle.fluid.layers.sequence_expand_as (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0ecf8d24cf4fd5c035406ee46afccfa0')) -paddle.fluid.layers.sequence_pad (ArgSpec(args=['x', 'pad_value', 'maxlen', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '6a1adf3067b20f6e4bcb354d71c19184')) -paddle.fluid.layers.sequence_unpad (ArgSpec(args=['x', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd12803c903c99aa36ec03aaac5f0cc5b')) +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)), ('document', '903ac9a778e0bf1bf649bd71e9d0ba0c')) +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)), ('document', '9b1f13c1fc872f76f8f84cf11e955f53')) +paddle.fluid.layers.sequence_expand (ArgSpec(args=['x', 'y', 'ref_level', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '10e122eb755c2bd1f78ef2332b28f1a0')) +paddle.fluid.layers.sequence_expand_as (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '858c432e7cbd8bb952cc2eb555457d50')) +paddle.fluid.layers.sequence_pad (ArgSpec(args=['x', 'pad_value', 'maxlen', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '1ba3ccfe13ed5091e113c09c13dc3a20')) +paddle.fluid.layers.sequence_unpad (ArgSpec(args=['x', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7f5ce36fb0016621e6bc001f4236d978')) 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)), ('document', 'fe126c58e4339410e875ab1eba246d21')) paddle.fluid.layers.reduce_sum (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'dd5f06fb7cf39ca06cbab4abd03e6893')) paddle.fluid.layers.reduce_mean (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'a3024789eba11a70c2ef27c358173400')) paddle.fluid.layers.reduce_max (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '10023caec4d7f78c3b901f023a1feaa7')) paddle.fluid.layers.reduce_min (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '1a1c91625ce3c32646f69ca10d4d1da7')) paddle.fluid.layers.reduce_prod (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'b386471f0476c80c61d8c8672278063d')) -paddle.fluid.layers.reduce_all (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '86420219be38e6e5c11f5fdf9dacb657')) -paddle.fluid.layers.reduce_any (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'cc1f965017029427832a05e31a5c759b')) -paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '2b290d3d77882bfe9bb8d331cac8cdd3')) -paddle.fluid.layers.sequence_last_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'c16a892f44f7fe71bfa5afc32d3f34ce')) -paddle.fluid.layers.sequence_slice (ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fdcea0e8b5bc7d8d4b1b072c521014e6')) -paddle.fluid.layers.dropout (ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name', 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, 'downgrade_in_infer')), ('document', 'f1dd22f7351f7f9853212958e0d8aa7a')) +paddle.fluid.layers.reduce_all (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '8ab17ab51f68a6e76302b27f928cedf3')) +paddle.fluid.layers.reduce_any (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '0483ac3b7a99e879ccde583ae8d7a60d')) +paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'f2dfd65b859de9844e7261e7a4503f63')) +paddle.fluid.layers.sequence_last_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '1af2e3a887e4f914f9d6650406186ab6')) +paddle.fluid.layers.sequence_slice (ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '39fbc5437be389f6c0c769f82fc1fba2')) +paddle.fluid.layers.dropout (ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name', 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, 'downgrade_in_infer')), ('document', '558d13133596209190df9a624264f28f')) paddle.fluid.layers.split (ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '78cf3a7323d1a7697658242e13f63759')) paddle.fluid.layers.ctc_greedy_decoder (ArgSpec(args=['input', 'blank', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2bc3a59efa9d52b628a6255422d9f0e8')) paddle.fluid.layers.edit_distance (ArgSpec(args=['input', 'label', 'normalized', 'ignored_tokens'], varargs=None, keywords=None, defaults=(True, None)), ('document', 'f2c252aa2f83f8e503ffaf79668eaa28')) -paddle.fluid.layers.l2_normalize (ArgSpec(args=['x', 'axis', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(1e-12, None)), ('document', 'd0484a1f85b40009a794d45a1a298c12')) -paddle.fluid.layers.matmul (ArgSpec(args=['x', 'y', 'transpose_x', 'transpose_y', 'alpha', 'name'], varargs=None, keywords=None, defaults=(False, False, 1.0, None)), ('document', 'aa27ca4405e70c6a733cb9806a76af30')) -paddle.fluid.layers.topk (ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2a1e9ea041ff4d6a9948bb8d03b743ea')) +paddle.fluid.layers.l2_normalize (ArgSpec(args=['x', 'axis', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(1e-12, None)), ('document', 'c1df110ea65998984f564c5c10abc54a')) +paddle.fluid.layers.matmul (ArgSpec(args=['x', 'y', 'transpose_x', 'transpose_y', 'alpha', 'name'], varargs=None, keywords=None, defaults=(False, False, 1.0, None)), ('document', 'fa2081f6e731bb9de7cd535ca07f523a')) +paddle.fluid.layers.topk (ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e50940f3ce5a08cc477b72f517491bf3')) paddle.fluid.layers.warpctc (ArgSpec(args=['input', 'label', 'blank', 'norm_by_times', 'use_cudnn'], varargs=None, keywords=None, defaults=(0, False, False)), ('document', '4aa9df890b47eb67d5442f04aaf9eeec')) paddle.fluid.layers.sequence_reshape (ArgSpec(args=['input', 'new_dim'], varargs=None, keywords=None, defaults=None), ('document', 'f568714a876425004aca4ea2d4a27701')) paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '8e72db173d4c082e27cb11f31d8c9bfa')) 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)), ('document', '33134416fc27dd65a767e5f15116ee16')) -paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '32b3c442da0f3df682b5fcac10468116')) +paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '11a544a6e3fd0482509712dd54377fa1')) paddle.fluid.layers.sampled_softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0)), ('document', 'd4435a63d34203339831ee6a86ef9242')) paddle.fluid.layers.hsigmoid (ArgSpec(args=['input', 'label', 'num_classes', 'param_attr', 'bias_attr', 'name', 'path_table', 'path_code', 'is_custom', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, False, False)), ('document', 'b83e7dfa81059b39bb137922dc914f50')) paddle.fluid.layers.beam_search (ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 'scores', 'beam_size', 'end_id', 'level', 'is_accumulated', 'name', 'return_parent_idx'], varargs=None, keywords=None, defaults=(0, True, None, False)), ('document', '1270395ce97a4e1b556104abbb14f096')) paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None)), ('document', '17485788fffe4e2d36dc58c2ac8d174e')) paddle.fluid.layers.multiplex (ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None), ('document', '2c4d1ae83da6ed35e3b36ba1b3b51d23')) -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)), ('document', 'de6a906950bae9f3c245cb744d22b94e')) -paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '419c3a24a83cc89219a029cf4092788b')) +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)), ('document', '79797f827d89ae72c77960e9696883a9')) +paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '96b24820e8863d6044d5be4eaaddb9fd')) paddle.fluid.layers.spectral_norm (ArgSpec(args=['weight', 'dim', 'power_iters', 'eps', 'name'], varargs=None, keywords=None, defaults=(0, 1, 1e-12, None)), ('document', '9461e67095a6fc5d568fb2ce8fef66ff')) paddle.fluid.layers.softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode', 'return_softmax', 'axis'], varargs=None, keywords=None, defaults=(False, -100, True, False, -1)), ('document', '54e1675aa0364f4a78fa72804ec0f413')) -paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'c6b175d253c55baf4b9c0eca9b1dda88')) -paddle.fluid.layers.one_hot (ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None), ('document', '960fc799549c202da1e85d626cb2c962')) -paddle.fluid.layers.autoincreased_step_counter (ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1)), ('document', '67afefa80b6cc38801bd5b631fed8a4a')) -paddle.fluid.layers.reshape (ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', '323c019f257e55ddea4a824a362de62f')) -paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '06588973f613e9dcd592724322864589')) +paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'ecb75c1b00c4c76c98b482f633b7a10c')) +paddle.fluid.layers.one_hot (ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None), ('document', '52db6229214fc6ab167d7009df29170d')) +paddle.fluid.layers.autoincreased_step_counter (ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1)), ('document', '98e7927f09ee2270535b29f048e481ec')) +paddle.fluid.layers.reshape (ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', '6196c9ec3075ca5a9c058ea1f8492256')) +paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ebbac07662a6e22e8e299ced880c7775')) paddle.fluid.layers.unsqueeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b9bd3129d36a70e7c4385df51ff71c62')) -paddle.fluid.layers.lod_reset (ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None)), ('document', '395e6ba041ccfacfe1d534c3e107fd66')) -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)), ('document', '330241f0bc57e9d16973ec322a6aef71')) +paddle.fluid.layers.lod_reset (ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None)), ('document', '9a72a7c8c80926150ea826e94efd7e9b')) +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)), ('document', '73d297256da8954617996958d26ee93d')) paddle.fluid.layers.pad (ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', '2f189f8ef61f1c23779e1593b78755c0')) paddle.fluid.layers.pad_constant_like (ArgSpec(args=['x', 'y', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', '95aa1972983f30fe9b5a3713e523e20f')) -paddle.fluid.layers.label_smooth (ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None)), ('document', '9060f4cab873c4ab2deed5211080698e')) +paddle.fluid.layers.label_smooth (ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None)), ('document', '214f1dfbe95a628600bbe99e836319cf')) paddle.fluid.layers.roi_pool (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1, 1, 1.0)), ('document', 'ceedc8c22752c623d6e1ea2e8df0f43f')) -paddle.fluid.layers.roi_align (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale', 'sampling_ratio', 'name'], varargs=None, keywords=None, defaults=(1, 1, 1.0, -1, None)), ('document', '3d8f4891c1d5e890a4e574371027dd35')) +paddle.fluid.layers.roi_align (ArgSpec(args=['input', 'rois', 'pooled_height', 'pooled_width', 'spatial_scale', 'sampling_ratio', 'name'], varargs=None, keywords=None, defaults=(1, 1, 1.0, -1, None)), ('document', '6f65342f646ef04ae705080a7dfee63f')) paddle.fluid.layers.dice_loss (ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,)), ('document', '7e8e4bf1f0f8612961ed113e8af8f0c5')) -paddle.fluid.layers.image_resize (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'resample', 'actual_shape', 'align_corners', 'align_mode'], varargs=None, keywords=None, defaults=(None, None, None, 'BILINEAR', None, True, 1)), ('document', 'f1bc5eb7198175d2b79197a681d98b43')) -paddle.fluid.layers.image_resize_short (ArgSpec(args=['input', 'out_short_len', 'resample'], varargs=None, keywords=None, defaults=('BILINEAR',)), ('document', '099b9f051e6247ae661e4a7b4fd3f89a')) -paddle.fluid.layers.resize_bilinear (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'align_mode'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 1)), ('document', '746bf58fdb1bd475f8c5f996b05b0e52')) -paddle.fluid.layers.resize_nearest (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners'], varargs=None, keywords=None, defaults=(None, None, None, None, True)), ('document', '9baf9288c862161ff850d45228047a5e')) -paddle.fluid.layers.gather (ArgSpec(args=['input', 'index', 'overwrite'], varargs=None, keywords=None, defaults=(True,)), ('document', '3569a6002a96c7f6b5e5bcfdc402df13')) +paddle.fluid.layers.image_resize (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'resample', 'actual_shape', 'align_corners', 'align_mode'], varargs=None, keywords=None, defaults=(None, None, None, 'BILINEAR', None, True, 1)), ('document', 'a29488d94d9a4bc4434d8a3529b4c6fe')) +paddle.fluid.layers.image_resize_short (ArgSpec(args=['input', 'out_short_len', 'resample'], varargs=None, keywords=None, defaults=('BILINEAR',)), ('document', 'bd97ebfe4bdf5110a5fcb8ecb626a447')) +paddle.fluid.layers.resize_bilinear (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'align_mode'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 1)), ('document', '548c7c2ead5771d15abbaad505f901e9')) +paddle.fluid.layers.resize_nearest (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners'], varargs=None, keywords=None, defaults=(None, None, None, None, True)), ('document', 'b7d810d1e251c5957c1efa6aa699d2d0')) +paddle.fluid.layers.gather (ArgSpec(args=['input', 'index', 'overwrite'], varargs=None, keywords=None, defaults=(True,)), ('document', 'f985c9b66e3aec96fa753a8eb44c991c')) paddle.fluid.layers.scatter (ArgSpec(args=['input', 'index', 'updates', 'name', 'overwrite'], varargs=None, keywords=None, defaults=(None, True)), ('document', '69b22affd4a6326502af166f04c095ab')) -paddle.fluid.layers.sequence_scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '71df5136cf03b06c65027b692fe78f1a')) -paddle.fluid.layers.random_crop (ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c9ab9e460ef0a1823249935a30e82c66')) +paddle.fluid.layers.sequence_scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'abe3f714120117a5a3d3e639853932bf')) +paddle.fluid.layers.random_crop (ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)), ('document', '042af0b8abea96b40c22f6e70d99e042')) paddle.fluid.layers.mean_iou (ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None), ('document', 'e3b6630ba43cb13dfeeb1601cb64d671')) -paddle.fluid.layers.relu (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'bf1676268df8ef100b8ab01d51336b25')) +paddle.fluid.layers.relu (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0942c174f4f6fb274976d4357356f6a2')) paddle.fluid.layers.selu (ArgSpec(args=['x', 'scale', 'alpha', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'f93c61f5b0bf933cd425a64dca2c4fdd')) -paddle.fluid.layers.log (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '056af2c0e6e22d94e8df7fc39677707f')) +paddle.fluid.layers.log (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '02f668664e3bfc4df6c00d7363467140')) paddle.fluid.layers.crop (ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'ddf9837ee83e549119210a3d714d5f44')) -paddle.fluid.layers.rank_loss (ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '1098b7a70c7696cc7437d6d57b5d89ed')) -paddle.fluid.layers.margin_rank_loss (ArgSpec(args=['label', 'left', 'right', 'margin', 'name'], varargs=None, keywords=None, defaults=(0.1, None)), ('document', '99b3fee0daee04911d2bee8871b26435')) -paddle.fluid.layers.elu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '463258ee9f8b60760eb1e26357cc9bfa')) -paddle.fluid.layers.relu6 (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(6.0, None)), ('document', '6f367339caf6c7124bc262fe1475df70')) +paddle.fluid.layers.rank_loss (ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '8eb36596bb43d7a907d3397c7aedbdb3')) +paddle.fluid.layers.margin_rank_loss (ArgSpec(args=['label', 'left', 'right', 'margin', 'name'], varargs=None, keywords=None, defaults=(0.1, None)), ('document', '6fc86ed23b420c8a0f6c043563cf3937')) +paddle.fluid.layers.elu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '9af1926c06711eacef9e82d7a9e4d308')) +paddle.fluid.layers.relu6 (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(6.0, None)), ('document', '538fc860b2a1734e118b94e4a1a3ee67')) paddle.fluid.layers.pow (ArgSpec(args=['x', 'factor', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', '35fa2b79b1ae6968d4a69788051c1d27')) -paddle.fluid.layers.stanh (ArgSpec(args=['x', 'scale_a', 'scale_b', 'name'], varargs=None, keywords=None, defaults=(0.6666666666666666, 1.7159, None)), ('document', '959936a477efc6c1447a9c8bf8ce94bb')) +paddle.fluid.layers.stanh (ArgSpec(args=['x', 'scale_a', 'scale_b', 'name'], varargs=None, keywords=None, defaults=(0.6666666666666666, 1.7159, None)), ('document', '1e1efad868714425da15c785dfb533a1')) paddle.fluid.layers.hard_sigmoid (ArgSpec(args=['x', 'slope', 'offset', 'name'], varargs=None, keywords=None, defaults=(0.2, 0.5, None)), ('document', '607d79ca873bee40eed1c79a96611591')) -paddle.fluid.layers.swish (ArgSpec(args=['x', 'beta', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', 'ef745e55a48763ee7b46b21a81dc7e84')) +paddle.fluid.layers.swish (ArgSpec(args=['x', 'beta', 'name'], varargs=None, keywords=None, defaults=(1.0, None)), ('document', 'b511609e3e0e8b636bf19f8b98249897')) paddle.fluid.layers.prelu (ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '2da40e447716338affebfe058d05d9a9')) -paddle.fluid.layers.brelu (ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None)), ('document', '3db337c195e156e6ef2b8b4a57113600')) -paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None)), ('document', 'f878486c82b576938151daad0de995a0')) +paddle.fluid.layers.brelu (ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None)), ('document', '49580538249a52c857fce75c94ad8af7')) +paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None)), ('document', '1eb3009c69060299ec87949ee0d4b9ae')) paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', '6455afd2498b00198f53f83d63d6c6a4')) -paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'cb295c13cb957db85cd9609269d7784d')) -paddle.fluid.layers.sequence_mask (ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None)), ('document', '767cea598dee8e2b94f04110fa6b7e67')) -paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', 'e8d86c47e92bcb878ff8022b6f66cec2')) +paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'b52306659a21e6b118eed49fe2c155a1')) +paddle.fluid.layers.sequence_mask (ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None)), ('document', '6c3f916921b24edaad220f1fcbf039de')) +paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', 'a76f347bf27ffe21b990340d5d9524d5')) paddle.fluid.layers.pad2d (ArgSpec(args=['input', 'paddings', 'mode', 'pad_value', 'data_format', 'name'], varargs=None, keywords=None, defaults=([0, 0, 0, 0], 'constant', 0.0, 'NCHW', None)), ('document', '3f3abdb795a5c2aad8c2312249551ce5')) paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'b0c4ca08d4eb295189e1b107c920d093')) paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'b870fed41abd2aecf929ece65f555fa1')) @@ -194,61 +194,61 @@ paddle.fluid.layers.elementwise_min (ArgSpec(args=['x', 'y', 'axis', 'act', 'nam paddle.fluid.layers.elementwise_pow (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'b9e7e9fa1ca28d8b6f07cc59eadb4a02')) paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '614984304f810f3ddae6b489ec01296b')) paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'a8c4b26d899246378e878f169582c7a4')) -paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0)), ('document', 'c8c7518358cfbb3822a019e6b5fbea52')) -paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '8c78ccb77e291e4a0f0673d34823ce4b')) -paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '35428949368cad5121dd37f8522ef8b0')) -paddle.fluid.layers.gaussian_random_batch_size_like (ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32')), ('document', '7536418f4cf0360a1a897c265f06e77e')) -paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '4527fd90e222f67b5f7451fb0cf7c845')) +paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0)), ('document', 'cfa120e583cd4a5bfa120c8a26f98a28')) +paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'ebbf399d4e03190ce5dc9488f05c92f4')) +paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'c39b647b6cf08e058d96ee503d5284fe')) +paddle.fluid.layers.gaussian_random_batch_size_like (ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32')), ('document', 'b24d0b21361c4bb8ef2cec8c26fb12b2')) +paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', 'f4b60847cb0f1ae00823ba6fb1b11310')) paddle.fluid.layers.slice (ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None), ('document', '3ca6a761570d86e303e473afba99bb49')) paddle.fluid.layers.shape (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'bf61c8f79d795a8371bdb3b5468aa82b')) paddle.fluid.layers.rank (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '096df0e0273145ab80ed119a4c294db3')) -paddle.fluid.layers.logical_and (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cdcf20c494c92060d10feb9374532f42')) -paddle.fluid.layers.logical_or (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '0eae3f726a4afe590757552fa3ced012')) -paddle.fluid.layers.logical_xor (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'b0daaa3fa4a0aa62f9b58c43d959eb25')) -paddle.fluid.layers.logical_not (ArgSpec(args=['x', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cd1c8cf31e040427d4e05711044caeb6')) +paddle.fluid.layers.logical_and (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '1d6777f61831c54bea3a0029e2118448')) +paddle.fluid.layers.logical_or (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '4d51a5a453755e0eb8c5ff6910a00dca')) +paddle.fluid.layers.logical_xor (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '1840f54c5bd5338bdf854980d47bf771')) +paddle.fluid.layers.logical_not (ArgSpec(args=['x', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'd8fc1c5a5535736d4cd44c893a9701c9')) paddle.fluid.layers.clip (ArgSpec(args=['x', 'min', 'max', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0ce33756573c572da67302499455dbcd')) -paddle.fluid.layers.clip_by_norm (ArgSpec(args=['x', 'max_norm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a1ea0bc5a926f427458c4254ca022749')) -paddle.fluid.layers.mean (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '9562845452b0455fa23ab64334415417')) +paddle.fluid.layers.clip_by_norm (ArgSpec(args=['x', 'max_norm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5302d0494071e43f270c45acd50b03fd')) +paddle.fluid.layers.mean (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '597257fb94d0597c404a6a5c91ab5258')) paddle.fluid.layers.mul (ArgSpec(args=['x', 'y', 'x_num_col_dims', 'y_num_col_dims', 'name'], varargs=None, keywords=None, defaults=(1, 1, None)), ('document', '784b7e36cea88493f9e37a41b10fbf4d')) -paddle.fluid.layers.sigmoid_cross_entropy_with_logits (ArgSpec(args=['x', 'label', 'ignore_index', 'name', 'normalize'], varargs=None, keywords=None, defaults=(-100, None, False)), ('document', '180c284317ea45ef89a460d8d79c0b72')) -paddle.fluid.layers.maxout (ArgSpec(args=['x', 'groups', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '71426e02d240d0daedae81a02ca1c191')) +paddle.fluid.layers.sigmoid_cross_entropy_with_logits (ArgSpec(args=['x', 'label', 'ignore_index', 'name', 'normalize'], varargs=None, keywords=None, defaults=(-100, None, False)), ('document', '7637c974f2d749d359acae9062c4d96f')) +paddle.fluid.layers.maxout (ArgSpec(args=['x', 'groups', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '22df6542f3f9aa3f34c0c2dab5dc1d80')) paddle.fluid.layers.space_to_depth (ArgSpec(args=['x', 'blocksize', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '26decdea9376b6b9a0d3432d82ca207b')) paddle.fluid.layers.affine_grid (ArgSpec(args=['theta', 'out_shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f85b263b7b6698d000977529a28f202b')) paddle.fluid.layers.sequence_reverse (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '65c8362e48810b8226e311c5d046db51')) paddle.fluid.layers.affine_channel (ArgSpec(args=['x', 'scale', 'bias', 'data_layout', 'name', 'act'], varargs=None, keywords=None, defaults=(None, None, 'NCHW', None, None)), ('document', '9f303c67538e468a36c5904a0a3aa110')) -paddle.fluid.layers.similarity_focus (ArgSpec(args=['input', 'axis', 'indexes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6f90d6ff76bf4f5e592332c1ef28494e')) +paddle.fluid.layers.similarity_focus (ArgSpec(args=['input', 'axis', 'indexes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '18ec2e3afeb90e70c8b73d2b71c40fdb')) paddle.fluid.layers.hash (ArgSpec(args=['input', 'hash_size', 'num_hash', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'da621ba1363e8f5fe7b702526bbae18f')) paddle.fluid.layers.grid_sampler (ArgSpec(args=['x', 'grid', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5d16663e096d7f04954c70ce1cc5e195')) -paddle.fluid.layers.log_loss (ArgSpec(args=['input', 'label', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(0.0001, None)), ('document', 'af541e9263be61ce0e40df58d1b69294')) +paddle.fluid.layers.log_loss (ArgSpec(args=['input', 'label', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(0.0001, None)), ('document', 'e3993a477c94729526040ff65d95728e')) paddle.fluid.layers.add_position_encoding (ArgSpec(args=['input', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e399f9436fed5f7ff480d8532e42c937')) -paddle.fluid.layers.bilinear_tensor_product (ArgSpec(args=['x', 'y', 'size', 'act', 'name', 'param_attr', 'bias_attr'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'cd0bd55ef1e1762aca25ec972d34d378')) -paddle.fluid.layers.merge_selected_rows (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c2a9c00d5c22e156d92ffa2e8736adf3')) +paddle.fluid.layers.bilinear_tensor_product (ArgSpec(args=['x', 'y', 'size', 'act', 'name', 'param_attr', 'bias_attr'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', '45fc3652a8e1aeffbe4eba371c54f756')) +paddle.fluid.layers.merge_selected_rows (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b2b0e5d5c155ce24bafc38b78cd0b164')) paddle.fluid.layers.get_tensor_from_selected_rows (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3e60aec040a6f740a130353323580bff')) paddle.fluid.layers.lstm (ArgSpec(args=['input', 'init_h', 'init_c', 'max_len', 'hidden_size', 'num_layers', 'dropout_prob', 'is_bidirec', 'is_test', 'name', 'default_initializer', 'seed'], varargs=None, keywords=None, defaults=(0.0, False, False, None, None, -1)), ('document', 'baa7327ed89df6b7bdd32f9ffdb62f63')) -paddle.fluid.layers.shuffle_channel (ArgSpec(args=['x', 'group', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2fa6782d43d02ae64482d21235a82949')) -paddle.fluid.layers.temporal_shift (ArgSpec(args=['x', 'seg_num', 'shift_ratio', 'name'], varargs=None, keywords=None, defaults=(0.25, None)), ('document', 'fe4481fb31363b09cfdd228fc6776ddf')) +paddle.fluid.layers.shuffle_channel (ArgSpec(args=['x', 'group', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '276a1213dd431228cefa33c3146df34a')) +paddle.fluid.layers.temporal_shift (ArgSpec(args=['x', 'seg_num', 'shift_ratio', 'name'], varargs=None, keywords=None, defaults=(0.25, None)), ('document', '13b1cdcb01f5ffdc26591ff9a2ec4669')) paddle.fluid.layers.py_func (ArgSpec(args=['func', 'x', 'out', 'backward_func', 'skip_vars_in_backward_input'], varargs=None, keywords=None, defaults=(None, None)), ('document', '8404e472ac12b4a30a505d3d3a3e5fdb')) paddle.fluid.layers.psroi_pool (ArgSpec(args=['input', 'rois', 'output_channels', 'spatial_scale', 'pooled_height', 'pooled_width', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '42d5155374f69786300d90d751956998')) paddle.fluid.layers.teacher_student_sigmoid_loss (ArgSpec(args=['input', 'label', 'soft_max_up_bound', 'soft_max_lower_bound'], varargs=None, keywords=None, defaults=(15.0, -15.0)), ('document', '07cb0d95a646dba1b9cc7cdce89e59f0')) paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '11bb8e62cc9256958eff3991fe4834da')) -paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '776d536cac47c89073abc7ee524d5aec')) -paddle.fluid.layers.tree_conv (ArgSpec(args=['nodes_vector', 'edge_set', 'output_size', 'num_filters', 'max_depth', 'act', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 2, 'tanh', None, None, None)), ('document', '2985a372ac897ea4e13aced7f930d6f8')) -paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', '46994d10276dd4cb803b4062b5d14329')) -paddle.fluid.layers.pixel_shuffle (ArgSpec(args=['x', 'upscale_factor'], varargs=None, keywords=None, defaults=None), ('document', '132b6e74ff642a392bd6b14c10aedc65')) +paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '18bc95c62d3300456c3c7da5278b47bb')) +paddle.fluid.layers.tree_conv (ArgSpec(args=['nodes_vector', 'edge_set', 'output_size', 'num_filters', 'max_depth', 'act', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 2, 'tanh', None, None, None)), ('document', '864f3cdc5e0c6152e2a39b136171644f')) +paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', '6b6ee1170fe20a79cf0631a1f49b0df2')) +paddle.fluid.layers.pixel_shuffle (ArgSpec(args=['x', 'upscale_factor'], varargs=None, keywords=None, defaults=None), ('document', '7e5cac851fd9bad344230e1044b6a565')) paddle.fluid.layers.fsp_matrix (ArgSpec(args=['x', 'y'], varargs=None, keywords=None, defaults=None), ('document', '20992b20d19c2e5983f366150827b4a6')) -paddle.fluid.layers.continuous_value_model (ArgSpec(args=['input', 'cvm', 'use_cvm'], varargs=None, keywords=None, defaults=(True,)), ('document', '94e2819b7c9715ea71b62e9c78f36b29')) -paddle.fluid.layers.where (ArgSpec(args=['condition'], varargs=None, keywords=None, defaults=None), ('document', 'a477a6434faaa1917b84e8e1e3e114c8')) +paddle.fluid.layers.continuous_value_model (ArgSpec(args=['input', 'cvm', 'use_cvm'], varargs=None, keywords=None, defaults=(True,)), ('document', 'c03490ffaa1b78258747157c313db4cd')) +paddle.fluid.layers.where (ArgSpec(args=['condition'], varargs=None, keywords=None, defaults=None), ('document', 'b1e1487760295e1ff55307b880a99e18')) paddle.fluid.layers.sign (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', 'fa2f457a81714430c5677c2d68744728')) -paddle.fluid.layers.deformable_conv (ArgSpec(args=['input', 'offset', 'mask', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'deformable_groups', 'im2col_step', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, None, None, None)), ('document', 'c896b66265a60bd3c5510f66e6e02919')) +paddle.fluid.layers.deformable_conv (ArgSpec(args=['input', 'offset', 'mask', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'deformable_groups', 'im2col_step', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, None, None, None)), ('document', '4d83ba6b971cfd590493b0925b3e081e')) paddle.fluid.layers.unfold (ArgSpec(args=['x', 'kernel_sizes', 'strides', 'paddings', 'dilations', 'name'], varargs=None, keywords=None, defaults=(1, 0, 1, None)), ('document', '3f884662ad443d9ecc2b3734b4f61ad6')) -paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'trans', 'no_trans', 'spatial_scale', 'group_size', 'pooled_height', 'pooled_width', 'part_size', 'sample_per_part', 'trans_std', 'position_sensitive', 'name'], varargs=None, keywords=None, defaults=(False, 1.0, [1, 1], 1, 1, None, 1, 0.1, False, None)), ('document', '65b8dbe13e00c4dc8224652f6ff89540')) -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)), ('document', '9e87163ba32003f21d2c9d8c6a605ada')) +paddle.fluid.layers.deformable_roi_pooling (ArgSpec(args=['input', 'rois', 'trans', 'no_trans', 'spatial_scale', 'group_size', 'pooled_height', 'pooled_width', 'part_size', 'sample_per_part', 'trans_std', 'position_sensitive', 'name'], varargs=None, keywords=None, defaults=(False, 1.0, [1, 1], 1, 1, None, 1, 0.1, False, None)), ('document', '99c03e3f249e36854f87dedaa17c8f35')) +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)), ('document', '9d7806e31bdf727c1a23b8782a09b545')) paddle.fluid.layers.open_files (ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None)), ('document', 'cccb6eb5410c822e5307c947aca2c899')) paddle.fluid.layers.read_file (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', '32181f6037e387fb6e68a5beaafe33b6')) -paddle.fluid.layers.shuffle (ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None), ('document', 'f29d7d159e114f73fc988d9a86805841')) -paddle.fluid.layers.batch (ArgSpec(args=['reader', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', 'fcb24383c6eef2ca040ee824c26e22fd')) +paddle.fluid.layers.shuffle (ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None), ('document', 'aa5803d1eccdaef03cdfb0b7ca088071')) +paddle.fluid.layers.batch (ArgSpec(args=['reader', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', '3007211c84c5c77eda8dc83619a6eaf8')) paddle.fluid.layers.double_buffer (ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '7241dd1c142f4c65c8d7f66948140aa7')) -paddle.fluid.layers.random_data_generator (ArgSpec(args=['low', 'high', 'shapes', 'lod_levels', 'for_parallel'], varargs=None, keywords=None, defaults=(True,)), ('document', '9b7f0f86ec24bbc97643cadcb6499cff')) +paddle.fluid.layers.random_data_generator (ArgSpec(args=['low', 'high', 'shapes', 'lod_levels', 'for_parallel'], varargs=None, keywords=None, defaults=(True,)), ('document', '290f5b97f24f0022e195f7228dd56fd9')) paddle.fluid.layers.py_reader (ArgSpec(args=['capacity', 'shapes', 'dtypes', 'lod_levels', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', 'd78a1c7344955c5caed8dc13adb7beb6')) paddle.fluid.layers.create_py_reader_by_data (ArgSpec(args=['capacity', 'feed_list', 'name', 'use_double_buffer'], varargs=None, keywords=None, defaults=(None, True)), ('document', '2edf37d57862b24a7a26aa19a3573f73')) paddle.fluid.layers.Preprocessor.__init__ (ArgSpec(args=['self', 'reader', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -256,28 +256,28 @@ paddle.fluid.layers.Preprocessor.block (ArgSpec(args=['self'], varargs=None, key paddle.fluid.layers.Preprocessor.inputs (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.layers.Preprocessor.outputs (ArgSpec(args=['self'], varargs='outs', keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.layers.load (ArgSpec(args=['out', 'file_path', 'load_as_fp16'], varargs=None, keywords=None, defaults=(None,)), ('document', '9d1a4bc97bbce9fa1d4f7a4200a771ff')) -paddle.fluid.layers.create_tensor (ArgSpec(args=['dtype', 'name', 'persistable'], varargs=None, keywords=None, defaults=(None, False)), ('document', 'c0c3d0194f83fff8ea99ce0820657dae')) -paddle.fluid.layers.create_parameter (ArgSpec(args=['shape', 'dtype', 'name', 'attr', 'is_bias', 'default_initializer'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', 'b6fe28cffff32d15e45c411bcf815cb7')) -paddle.fluid.layers.create_global_var (ArgSpec(args=['shape', 'value', 'dtype', 'persistable', 'force_cpu', 'name'], varargs=None, keywords=None, defaults=(False, False, None)), ('document', '90eb79e0d1261ec2bac7c775ee4f459b')) -paddle.fluid.layers.cast (ArgSpec(args=['x', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '992eb42590fc1c380841a6db72ce78b3')) +paddle.fluid.layers.create_tensor (ArgSpec(args=['dtype', 'name', 'persistable'], varargs=None, keywords=None, defaults=(None, False)), ('document', 'aaf0176c743c43e9bc684dd7dfac25c5')) +paddle.fluid.layers.create_parameter (ArgSpec(args=['shape', 'dtype', 'name', 'attr', 'is_bias', 'default_initializer'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', '021272f30e0cdf7503586815378abfb8')) +paddle.fluid.layers.create_global_var (ArgSpec(args=['shape', 'value', 'dtype', 'persistable', 'force_cpu', 'name'], varargs=None, keywords=None, defaults=(False, False, None)), ('document', '47ea8b8c91879e50c9036e418b00ef4a')) +paddle.fluid.layers.cast (ArgSpec(args=['x', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '1e44a534cf7d26ab230aa9f5e4e0525a')) paddle.fluid.layers.tensor_array_to_tensor (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', '764c095ba4562ae740f979e970152d6e')) -paddle.fluid.layers.concat (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'f9e905b48123914c78055a45fe23106a')) +paddle.fluid.layers.concat (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'b3f30feb5dec8f110d7393ffeb30dbd9')) paddle.fluid.layers.sums (ArgSpec(args=['input', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', '5df743d578638cd2bbb9369499b44af4')) paddle.fluid.layers.assign (ArgSpec(args=['input', 'output'], varargs=None, keywords=None, defaults=(None,)), ('document', '8bd94aef4e123986d9a8c29f67b5532b')) 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)), ('document', '3551aa494e88d0f271e40cd45d6e3020')) paddle.fluid.layers.fill_constant (ArgSpec(args=['shape', 'dtype', 'value', 'force_cpu', 'out'], varargs=None, keywords=None, defaults=(False, None)), ('document', 'd6b76c7d2c7129f8d713ca74f1c2c287')) -paddle.fluid.layers.argmin (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '677c09cc0fd7381974bfc845c4d9f0f2')) -paddle.fluid.layers.argmax (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', 'ef64ee883998e7e246a854a845e11e2c')) -paddle.fluid.layers.argsort (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '0a85a9a145d2e24e05958a3f1322d68a')) +paddle.fluid.layers.argmin (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '3dd54487232d05df4d70fba94b7d0b79')) +paddle.fluid.layers.argmax (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '7f47cc9aa7531b6bd37c5c96bc7f0469')) +paddle.fluid.layers.argsort (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '9792371e3b66258531225a5551de8961')) paddle.fluid.layers.ones (ArgSpec(args=['shape', 'dtype', 'force_cpu'], varargs=None, keywords=None, defaults=(False,)), ('document', '812c623ed52610b9773f9fc05413bc34')) paddle.fluid.layers.zeros (ArgSpec(args=['shape', 'dtype', 'force_cpu'], varargs=None, keywords=None, defaults=(False,)), ('document', '95379f9288c2d05356ec0e2375c6bc57')) paddle.fluid.layers.reverse (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=None), ('document', '628135603692137d52bcf5a8d8d6816d')) paddle.fluid.layers.has_inf (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '51a0fa1cfaf2507c00a215adacdb8a63')) paddle.fluid.layers.has_nan (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '129cf426e71452fe8276d616a6dc21ae')) -paddle.fluid.layers.isfinite (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '548a0ae317105e6dbfed321d7e37c03d')) -paddle.fluid.layers.range (ArgSpec(args=['start', 'end', 'step', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '2ec937ede953ded2fdff2675883900bb')) -paddle.fluid.layers.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '495e21e9a848c2d075a102802fc67756')) -paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c7e4cfffc93ae89c8f6f53b6d650f923')) +paddle.fluid.layers.isfinite (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', '23c66e5918040fcc11c8fa8c5da1b38e')) +paddle.fluid.layers.range (ArgSpec(args=['start', 'end', 'step', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', 'a45b42f21bc5a4e84b60981a3d629ab3')) +paddle.fluid.layers.linspace (ArgSpec(args=['start', 'stop', 'num', 'dtype'], varargs=None, keywords=None, defaults=None), ('document', '3663d1148946eed4c1c34c81be586b9e')) +paddle.fluid.layers.zeros_like (ArgSpec(args=['x', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd88a23bcdc443719b3953593f7cef14a')) paddle.fluid.layers.diag (ArgSpec(args=['diagonal'], varargs=None, keywords=None, defaults=None), ('document', '88a15e15f0098d549f07a01eaebf9ce3')) paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.layers.While.block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -286,8 +286,8 @@ paddle.fluid.layers.Switch.case (ArgSpec(args=['self', 'condition'], varargs=Non paddle.fluid.layers.Switch.default (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.layers.increment (ArgSpec(args=['x', 'value', 'in_place'], varargs=None, keywords=None, defaults=(1.0, True)), ('document', 'f88b5787bb80ae6b8bf513a70dabbdc1')) paddle.fluid.layers.array_write (ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,)), ('document', '3f913b5069ad40bd85d89b33e4aa5939')) -paddle.fluid.layers.create_array (ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None), ('document', '2d4f20087080ba5105b55205ad5c5b6a')) -paddle.fluid.layers.less_than (ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'eb41e5993f705fcfa354024054a75f5f')) +paddle.fluid.layers.create_array (ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None), ('document', '556de793fdf24d515f3fc91260e2c048')) +paddle.fluid.layers.less_than (ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], varargs=None, keywords=None, defaults=(None, None)), ('document', '04af32422c3a3d8f6040aeb406c82768')) paddle.fluid.layers.less_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '7b6d952a9f6340a044cfb91c16aad842')) paddle.fluid.layers.greater_than (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '55710e2fafeda70cd1b53d7509712499')) paddle.fluid.layers.greater_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '14bff27b2be5e60eaa30e41925265beb')) @@ -317,57 +317,57 @@ paddle.fluid.layers.StaticRNN.update_memory (ArgSpec(args=['self', 'mem', 'var'] paddle.fluid.layers.reorder_lod_tensor_by_rank (ArgSpec(args=['x', 'rank_table'], varargs=None, keywords=None, defaults=None), ('document', '5b552a1f0f7eb4dacb768a975ba15d08')) 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')), ('document', 'ee6c70867d317b0a87094ed23546215f')) paddle.fluid.layers.is_empty (ArgSpec(args=['x', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '3011dc695f490afdf504dc24f628319a')) -paddle.fluid.layers.sigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a4e395ab004e7da34e94a0a1f9eee183')) -paddle.fluid.layers.logsigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5f2508c52e0a797bb9bd5e29d79ede78')) -paddle.fluid.layers.exp (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '41c976b68542f4cbee178640f765d845')) -paddle.fluid.layers.tanh (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a64a80b8ab637e33fc5d0dd63fdbdc47')) -paddle.fluid.layers.atan (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fe8b8bf36a726362b2a8c1fa01fd2590')) -paddle.fluid.layers.tanh_shrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7767e47ffee21281ed5e1f399ef4224b')) -paddle.fluid.layers.softshrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c6af2e21ce4fbc4d19dc51ab2acef6e1')) -paddle.fluid.layers.sqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '33aa2c16c320406237f40aa44de5d6bc')) -paddle.fluid.layers.rsqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fd30d2ab9df5e905832ac9ee31ca382f')) -paddle.fluid.layers.abs (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c66fcec5f16e4a1fe8c74d183446946e')) -paddle.fluid.layers.ceil (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '57435860b214ffafa9b05e8ebb7ced7a')) -paddle.fluid.layers.floor (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b3d6334262f7cc9f39cd4b1d10369ab0')) -paddle.fluid.layers.cos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3e78bba17de597f224d01f1f20e6fc63')) -paddle.fluid.layers.acos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3b24ef9e5aca6e0ebba3e473be589b00')) -paddle.fluid.layers.asin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e691d4df018ef6bc05487e85714171c1')) -paddle.fluid.layers.sin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e71a4f10c099159ccc0f5a69d443ad68')) -paddle.fluid.layers.round (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e0e36682b9717322fe111dda7d328d34')) -paddle.fluid.layers.reciprocal (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3b6b463c0a01694f4322b5d4521c3944')) -paddle.fluid.layers.square (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fcc0d8ec2d2983f5d2ae0196fa83916b')) -paddle.fluid.layers.softplus (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a9bef6674dc20af1ae901656ed041cdf')) -paddle.fluid.layers.softsign (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5c1e9c619db82d6392826d0c2908ea55')) +paddle.fluid.layers.sigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd894323f31a913c4a5bd4cc764f6a76a')) +paddle.fluid.layers.logsigmoid (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd083538e3439ed6b28b00207e0f321d5')) +paddle.fluid.layers.exp (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '9ef0909adb4d8c9430fcd595bab72dc1')) +paddle.fluid.layers.tanh (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f820eeaf81dfbdd1c360122cd5795cc8')) +paddle.fluid.layers.atan (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2dde114018cbcaff9b24c566bf6704a5')) +paddle.fluid.layers.tanh_shrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '63d198e36e1d85dcfb454c1a3cb3b38e')) +paddle.fluid.layers.softshrink (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '4f53a5e7f50c55ea516375ef8f46316b')) +paddle.fluid.layers.sqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '893ec81a025f3c82f1c8fca6aa84d39f')) +paddle.fluid.layers.rsqrt (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c629f5163fa04f80abb3d0240c462fa6')) +paddle.fluid.layers.abs (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'f6d5642f52e357f3cec89cc9c15dc66c')) +paddle.fluid.layers.ceil (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e5ccc5339056e947272c1921d11e6cfe')) +paddle.fluid.layers.floor (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b9c1474e5d0f83e4a15a5cd827abbf9c')) +paddle.fluid.layers.cos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd7d3af92e8c1d93aeeb4d6bc2e0fc9b6')) +paddle.fluid.layers.acos (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5c9a00178c5c28bb824f7d6c25060d3b')) +paddle.fluid.layers.asin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '20d1d49fe4d13430a63c57fc4b29a677')) +paddle.fluid.layers.sin (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0da9ea1a725c3d91ca0c37cea951ba29')) +paddle.fluid.layers.round (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e91cb3422c0ffdc04375752143179b47')) +paddle.fluid.layers.reciprocal (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '30bd7174c21294230616a22cd87b0035')) +paddle.fluid.layers.square (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '200916f013bad0b052b13dc43901f0b8')) +paddle.fluid.layers.softplus (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'be4533a4cd97c84424512dca76142083')) +paddle.fluid.layers.softsign (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '410f27a44b7365cc60d5d5ff5a53407e')) paddle.fluid.layers.uniform_random (ArgSpec(args=['shape', 'dtype', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', -1.0, 1.0, 0)), ('document', '6de6775d9e9ed885056e764982130cfd')) -paddle.fluid.layers.hard_shrink (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c142f5884f3255e0d6075c286bbd531e')) -paddle.fluid.layers.cumsum (ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '944d7c03057f5fc88bc78acd4d82f926')) -paddle.fluid.layers.thresholded_relu (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', '90566ea449ea4c681435546e2f70610a')) -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)), ('document', 'b351a05b758f7e5370898cc7d7d40dca')) -paddle.fluid.layers.density_prior_box (ArgSpec(args=['input', 'image', 'densities', 'fixed_sizes', 'fixed_ratios', 'variance', 'clip', 'steps', 'offset', 'flatten_to_2d', 'name'], varargs=None, keywords=None, defaults=(None, None, None, [0.1, 0.1, 0.2, 0.2], False, [0.0, 0.0], 0.5, False, None)), ('document', '05c43e8fd25efe34f75e35a2c045ded3')) +paddle.fluid.layers.hard_shrink (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', '386a4103d2884b2f1312ebc1e8ee6486')) +paddle.fluid.layers.cumsum (ArgSpec(args=['x', 'axis', 'exclusive', 'reverse'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '5ab9d5721a6734fe127069e4314e1309')) +paddle.fluid.layers.thresholded_relu (ArgSpec(args=['x', 'threshold'], varargs=None, keywords=None, defaults=(None,)), ('document', '9a0464425426a9b9c1b7500ede2836c1')) +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)), ('document', '0fdf82762fd0a5acb2578a72771b5b44')) +paddle.fluid.layers.density_prior_box (ArgSpec(args=['input', 'image', 'densities', 'fixed_sizes', 'fixed_ratios', 'variance', 'clip', 'steps', 'offset', 'flatten_to_2d', 'name'], varargs=None, keywords=None, defaults=(None, None, None, [0.1, 0.1, 0.2, 0.2], False, [0.0, 0.0], 0.5, False, None)), ('document', '7a484a0da5e993a7734867a3dfa86571')) 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)), ('document', 'fd58078fdfffd899b91f992ba224628f')) -paddle.fluid.layers.bipartite_match (ArgSpec(args=['dist_matrix', 'match_type', 'dist_threshold', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '3ddb9b966f193900193a95a3df77c3c1')) +paddle.fluid.layers.bipartite_match (ArgSpec(args=['dist_matrix', 'match_type', 'dist_threshold', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '080ce0d54d3f1950ad5a3a8e5ae529e9')) paddle.fluid.layers.target_assign (ArgSpec(args=['input', 'matched_indices', 'negative_indices', 'mismatch_value', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'e9685f32d21bec8c013626c0254502c5')) 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)), ('document', 'efae414c1137c7944d6174dd08c5347a')) -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)), ('document', '055bd5070ad72dccc0949b4ed036f39c')) +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)), ('document', '8edacd4b9bd02dd68931b9fa6bfe0cbd')) paddle.fluid.layers.rpn_target_assign (ArgSpec(args=['bbox_pred', 'cls_logits', 'anchor_box', 'anchor_var', 'gt_boxes', 'is_crowd', 'im_info', 'rpn_batch_size_per_im', 'rpn_straddle_thresh', 'rpn_fg_fraction', 'rpn_positive_overlap', 'rpn_negative_overlap', 'use_random'], varargs=None, keywords=None, defaults=(256, 0.0, 0.5, 0.7, 0.3, True)), ('document', '651d98d51879dfa1bc1cd40391786a41')) paddle.fluid.layers.retinanet_target_assign (ArgSpec(args=['bbox_pred', 'cls_logits', 'anchor_box', 'anchor_var', 'gt_boxes', 'gt_labels', 'is_crowd', 'im_info', 'num_classes', 'positive_overlap', 'negative_overlap'], varargs=None, keywords=None, defaults=(1, 0.5, 0.4)), ('document', 'fa1d1c9d5e0111684c0db705f86a2595')) paddle.fluid.layers.sigmoid_focal_loss (ArgSpec(args=['x', 'label', 'fg_num', 'gamma', 'alpha'], varargs=None, keywords=None, defaults=(2, 0.25)), ('document', 'aeac6aae100173b3fc7f102cf3023a3d')) -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)), ('document', 'acc23232f4c8c03791598500b5bf7790')) +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)), ('document', '0aaacaf9858b8270a8ab5b0aacdd94b7')) paddle.fluid.layers.roi_perspective_transform (ArgSpec(args=['input', 'rois', 'transformed_height', 'transformed_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1.0,)), ('document', 'd1ddc75629fedee46f82e631e22c79dc')) paddle.fluid.layers.generate_proposal_labels (ArgSpec(args=['rpn_rois', 'gt_classes', 'is_crowd', 'gt_boxes', 'im_info', 'batch_size_per_im', 'fg_fraction', 'fg_thresh', 'bg_thresh_hi', 'bg_thresh_lo', 'bbox_reg_weights', 'class_nums', 'use_random', 'is_cls_agnostic', 'is_cascade_rcnn'], varargs=None, keywords=None, defaults=(256, 0.25, 0.25, 0.5, 0.0, [0.1, 0.1, 0.2, 0.2], None, True, False, False)), ('document', '69def376b42ef0681d0cc7f53a2dac4b')) paddle.fluid.layers.generate_proposals (ArgSpec(args=['scores', 'bbox_deltas', 'im_info', 'anchors', 'variances', 'pre_nms_top_n', 'post_nms_top_n', 'nms_thresh', 'min_size', 'eta', 'name'], varargs=None, keywords=None, defaults=(6000, 1000, 0.5, 0.1, 1.0, None)), ('document', 'b7d707822b6af2a586bce608040235b1')) paddle.fluid.layers.generate_mask_labels (ArgSpec(args=['im_info', 'gt_classes', 'is_crowd', 'gt_segms', 'rois', 'labels_int32', 'num_classes', 'resolution'], varargs=None, keywords=None, defaults=None), ('document', 'b319b10ddaf17fb4ddf03518685a17ef')) paddle.fluid.layers.iou_similarity (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '72fca4a39ccf82d5c746ae62d1868a99')) -paddle.fluid.layers.box_coder (ArgSpec(args=['prior_box', 'prior_box_var', 'target_box', 'code_type', 'box_normalized', 'name', 'axis'], varargs=None, keywords=None, defaults=('encode_center_size', True, None, 0)), ('document', '032d0f4b7d8f6235ee5d91e473344f0e')) +paddle.fluid.layers.box_coder (ArgSpec(args=['prior_box', 'prior_box_var', 'target_box', 'code_type', 'box_normalized', 'name', 'axis'], varargs=None, keywords=None, defaults=('encode_center_size', True, None, 0)), ('document', '4c6225fc1a1c0b84955a8f0013008243')) paddle.fluid.layers.polygon_box_transform (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'e308ce1661cb722b220a6f482f85b9e4')) -paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gt_box', 'gt_label', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'gt_score', 'use_label_smooth', 'name'], varargs=None, keywords=None, defaults=(None, True, None)), ('document', 'eb62b1ff7cc981f3483a62321a491f2e')) +paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gt_box', 'gt_label', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'gt_score', 'use_label_smooth', 'name'], varargs=None, keywords=None, defaults=(None, True, None)), ('document', '400403175718d5a632402cdae88b01b8')) paddle.fluid.layers.yolo_box (ArgSpec(args=['x', 'img_size', 'anchors', 'class_num', 'conf_thresh', 'downsample_ratio', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '11b463ae2ad4c797fb91b3ee9864c4b4')) -paddle.fluid.layers.box_clip (ArgSpec(args=['input', 'im_info', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '04384378ff00a42ade8fabd52e27cbc5')) -paddle.fluid.layers.multiclass_nms (ArgSpec(args=['bboxes', 'scores', 'score_threshold', 'nms_top_k', 'keep_top_k', 'nms_threshold', 'normalized', 'nms_eta', 'background_label', 'name'], varargs=None, keywords=None, defaults=(0.3, True, 1.0, 0, None)), ('document', 'ca7d1107b6c5d2d6d8221039a220fde0')) +paddle.fluid.layers.box_clip (ArgSpec(args=['input', 'im_info', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '9ddee76cb808db83768bf68010e39b2b')) +paddle.fluid.layers.multiclass_nms (ArgSpec(args=['bboxes', 'scores', 'score_threshold', 'nms_top_k', 'keep_top_k', 'nms_threshold', 'normalized', 'nms_eta', 'background_label', 'name'], varargs=None, keywords=None, defaults=(0.3, True, 1.0, 0, None)), ('document', '76d74056e9eedcacf013d8e3b115cbd3')) paddle.fluid.layers.retinanet_detection_output (ArgSpec(args=['bboxes', 'scores', 'anchors', 'im_info', 'score_threshold', 'nms_top_k', 'keep_top_k', 'nms_threshold', 'nms_eta'], varargs=None, keywords=None, defaults=(0.05, 1000, 100, 0.3, 1.0)), ('document', '078d28607ce261a0cba2b965a79f6bb8')) -paddle.fluid.layers.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7bb011ec26bace2bc23235aa4a17647d')) -paddle.fluid.layers.box_decoder_and_assign (ArgSpec(args=['prior_box', 'prior_box_var', 'target_box', 'box_score', 'box_clip', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'dfc953994fd8fef35c49dd9c6eea37a5')) -paddle.fluid.layers.collect_fpn_proposals (ArgSpec(args=['multi_rois', 'multi_scores', 'min_level', 'max_level', 'post_nms_top_n', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '82ffd896ecc3c005ae1cad40854dcace')) +paddle.fluid.layers.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6c023b9401214ae387a8b2d92638e5e4')) +paddle.fluid.layers.box_decoder_and_assign (ArgSpec(args=['prior_box', 'prior_box_var', 'target_box', 'box_score', 'box_clip', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3619a7847709f5868f5e929065947b38')) +paddle.fluid.layers.collect_fpn_proposals (ArgSpec(args=['multi_rois', 'multi_scores', 'min_level', 'max_level', 'post_nms_top_n', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '80a75103e001ca1ba056fbbe0c6a19f3')) paddle.fluid.layers.accuracy (ArgSpec(args=['input', 'label', 'k', 'correct', 'total'], varargs=None, keywords=None, defaults=(1, None, None)), ('document', 'ef799022a6040597462ae2b3d2f1c407')) paddle.fluid.layers.auc (ArgSpec(args=['input', 'label', 'curve', 'num_thresholds', 'topk', 'slide_steps'], varargs=None, keywords=None, defaults=('ROC', 4095, 1, 1)), ('document', '300537e259bba86fdefa13a133a0587d')) paddle.fluid.layers.exponential_decay (ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,)), ('document', 'eaf430c5a0380fb11bfe9a8922cd6295')) @@ -375,9 +375,9 @@ paddle.fluid.layers.natural_exp_decay (ArgSpec(args=['learning_rate', 'decay_ste paddle.fluid.layers.inverse_time_decay (ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,)), ('document', 'ea37a3a8a0b3ce2254e7bc49a0951dbe')) 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)), ('document', 'a343254c36c2e89512cd8cd8a1960ead')) paddle.fluid.layers.piecewise_decay (ArgSpec(args=['boundaries', 'values'], varargs=None, keywords=None, defaults=None), ('document', 'd9f654117542c6b702963dda107a247f')) -paddle.fluid.layers.noam_decay (ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None), ('document', 'f96805b1a64f9a12f4627497e5fcb920')) -paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', 'f8b2727bccf0f368c997d7cf05847e49')) -paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', '2ef3f5ca5cd71ea4217c418e5a7a0565')) +paddle.fluid.layers.noam_decay (ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None), ('document', 'fd57228fb76195e66bbcc8d8e42c494d')) +paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', 'f0d65d8c89d0fe78051ca689daa15e35')) +paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', '0b529386b62cc73d27b711a5f618f3e4')) paddle.fluid.contrib.InitState.__init__ (ArgSpec(args=['self', 'init', 'shape', 'value', 'init_boot', 'need_reorder', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 0.0, None, False, 'float32')), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.contrib.StateCell.__init__ (ArgSpec(args=['self', 'inputs', 'states', 'out_state', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.contrib.StateCell.compute_state (ArgSpec(args=['self', 'inputs'], varargs=None, keywords=None, defaults=None), ('document', '92973b3f222081a1d17069c683cf4a99')) @@ -771,67 +771,67 @@ paddle.fluid.transpiler.RoundRobin.reset (ArgSpec(args=['self'], varargs=None, k 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'], varargs=None, keywords=None, defaults=(0, 'max', False, 1, 0, 1, 1, None, None, None, True)), ('document', '13f01ff80e8dfbd3427d90cf49bc62eb')) paddle.fluid.nets.sequence_conv_pool (ArgSpec(args=['input', 'num_filters', 'filter_size', 'param_attr', 'act', 'pool_type', 'bias_attr'], varargs=None, keywords=None, defaults=(None, 'sigmoid', 'max', None)), ('document', 'd6a1e527b53f5cc15594fee307dfc5cf')) -paddle.fluid.nets.glu (ArgSpec(args=['input', 'dim'], varargs=None, keywords=None, defaults=(-1,)), ('document', '6486b2595300fc3305b5a1f0ac363dce')) +paddle.fluid.nets.glu (ArgSpec(args=['input', 'dim'], varargs=None, keywords=None, defaults=(-1,)), ('document', 'b87bacfc70dd3477ed25ef14aa01389a')) paddle.fluid.nets.scaled_dot_product_attention (ArgSpec(args=['queries', 'keys', 'values', 'num_heads', 'dropout_rate'], varargs=None, keywords=None, defaults=(1, 0.0)), ('document', 'b1a07a0000eb9103e3a143ca8c13de5b')) -paddle.fluid.nets.img_conv_group (ArgSpec(args=['input', 'conv_num_filter', 'pool_size', 'conv_padding', 'conv_filter_size', 'conv_act', 'param_attr', 'conv_with_batchnorm', 'conv_batchnorm_drop_rate', 'pool_stride', 'pool_type', 'use_cudnn'], varargs=None, keywords=None, defaults=(1, 3, None, None, False, 0.0, 1, 'max', True)), ('document', '5178bc1b4d302192597a5efbae13d902')) +paddle.fluid.nets.img_conv_group (ArgSpec(args=['input', 'conv_num_filter', 'pool_size', 'conv_padding', 'conv_filter_size', 'conv_act', 'param_attr', 'conv_with_batchnorm', 'conv_batchnorm_drop_rate', 'pool_stride', 'pool_type', 'use_cudnn'], varargs=None, keywords=None, defaults=(1, 3, None, None, False, 0.0, 1, 'max', True)), ('document', '4913d846264f17112bf7bc04273388cc')) paddle.fluid.optimizer.SGDOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'regularization', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.SGDOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.SGDOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.SGDOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.SGDOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.SGDOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.SGDOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.SGDOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.MomentumOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'momentum', 'use_nesterov', 'regularization', 'name'], varargs=None, keywords=None, defaults=(False, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.MomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.MomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.MomentumOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.MomentumOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.MomentumOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.MomentumOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.MomentumOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.AdagradOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'epsilon', 'regularization', 'name', 'initial_accumulator_value'], varargs=None, keywords=None, defaults=(1e-06, None, None, 0.0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.AdagradOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.AdagradOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.AdagradOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.AdagradOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.AdagradOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.AdagradOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.AdagradOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.AdamOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'beta1', 'beta2', 'epsilon', 'regularization', 'name', 'lazy_mode'], varargs=None, keywords=None, defaults=(0.001, 0.9, 0.999, 1e-08, None, None, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.AdamOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.AdamOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.AdamOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.AdamOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.AdamOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.AdamOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.AdamOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.AdamaxOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'beta1', 'beta2', 'epsilon', 'regularization', 'name'], varargs=None, keywords=None, defaults=(0.001, 0.9, 0.999, 1e-08, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.AdamaxOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.AdamaxOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.AdamaxOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.AdamaxOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.AdamaxOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.AdamaxOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.AdamaxOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.DecayedAdagradOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'decay', 'epsilon', 'regularization', 'name'], varargs=None, keywords=None, defaults=(0.95, 1e-06, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.DecayedAdagradOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.DecayedAdagradOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.DecayedAdagradOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.DecayedAdagradOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.DecayedAdagradOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.DecayedAdagradOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.DecayedAdagradOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.FtrlOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'l1', 'l2', 'lr_power', 'regularization', 'name'], varargs=None, keywords=None, defaults=(0.0, 0.0, -0.5, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.FtrlOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.FtrlOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.FtrlOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.FtrlOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.FtrlOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.FtrlOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.FtrlOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.RMSPropOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'rho', 'epsilon', 'momentum', 'centered', 'regularization', 'name'], varargs=None, keywords=None, defaults=(0.95, 1e-06, 0.0, False, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.RMSPropOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.RMSPropOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.RMSPropOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.RMSPropOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.RMSPropOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.RMSPropOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.RMSPropOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.AdadeltaOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'epsilon', 'rho', 'regularization', 'name'], varargs=None, keywords=None, defaults=(1e-06, 0.95, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.AdadeltaOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.AdadeltaOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.AdadeltaOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.AdadeltaOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.AdadeltaOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -839,7 +839,7 @@ paddle.fluid.optimizer.AdadeltaOptimizer.load (ArgSpec(args=['self', 'stat_dict' paddle.fluid.optimizer.AdadeltaOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.ModelAverage.__init__ (ArgSpec(args=['self', 'average_window_rate', 'min_average_window', 'max_average_window', 'regularization', 'name'], varargs=None, keywords=None, defaults=(10000, 10000, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.ModelAverage.apply (ArgSpec(args=['self', 'executor', 'need_restore'], varargs=None, keywords=None, defaults=(True,)), ('document', '648010d0ac1fa707dac0b89f74b0e35c')) -paddle.fluid.optimizer.ModelAverage.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.ModelAverage.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.ModelAverage.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.ModelAverage.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.ModelAverage.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -847,21 +847,21 @@ paddle.fluid.optimizer.ModelAverage.load (ArgSpec(args=['self', 'stat_dict'], va paddle.fluid.optimizer.ModelAverage.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.ModelAverage.restore (ArgSpec(args=['self', 'executor'], varargs=None, keywords=None, defaults=None), ('document', '5f14ea4adda2791e1c3b37ff327f6a83')) paddle.fluid.optimizer.LarsMomentumOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'momentum', 'lars_coeff', 'lars_weight_decay', 'regularization', 'name'], varargs=None, keywords=None, defaults=(0.001, 0.0005, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.LarsMomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.LarsMomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.LarsMomentumOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.LarsMomentumOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.LarsMomentumOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.LarsMomentumOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.LarsMomentumOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.DGCMomentumOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'momentum', 'rampup_begin_step', 'rampup_step', 'sparsity', 'use_nesterov', 'local_grad_clip_norm', 'num_trainers', 'regularization', 'name'], varargs=None, keywords=None, defaults=(1, [0.999], False, None, None, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.DGCMomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.DGCMomentumOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.DGCMomentumOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.DGCMomentumOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.DGCMomentumOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.DGCMomentumOptimizer.load (ArgSpec(args=['self', 'stat_dict'], varargs=None, keywords=None, defaults=None), ('document', '649a92cf7f1ea28666fd00c4ea01acde')) paddle.fluid.optimizer.DGCMomentumOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'grad_clip'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'b15cffad0903fc81af77a0580ceb2a9b')) paddle.fluid.optimizer.LambOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'lamb_weight_decay', 'beta1', 'beta2', 'epsilon', 'regularization', 'exclude_from_weight_decay_fn', 'name'], varargs=None, keywords=None, defaults=(0.001, 0.01, 0.9, 0.999, 1e-06, None, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.optimizer.LambOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', 'bfe7305918552aaecfdaa22411dbe871')) +paddle.fluid.optimizer.LambOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610')) paddle.fluid.optimizer.LambOptimizer.apply_optimize (ArgSpec(args=['self', 'loss', 'startup_program', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '5c46d1926a40f1f873ffe9f37ac89dae')) paddle.fluid.optimizer.LambOptimizer.backward (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None)), ('document', 'ba3a113d0229ff7bc9d39bda0a6d947f')) paddle.fluid.optimizer.LambOptimizer.get_opti_var_name_list (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -873,7 +873,7 @@ paddle.fluid.optimizer.ExponentialMovingAverage.restore (ArgSpec(args=['self', ' paddle.fluid.optimizer.ExponentialMovingAverage.update (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'ea10f08af6d7aac3b7974aa976e4085f')) paddle.fluid.optimizer.PipelineOptimizer.__init__ (ArgSpec(args=['self', 'optimizer', 'cut_list', 'place_list', 'concurrency_list', 'queue_size', 'sync_steps', 'start_cpu_core_id'], varargs=None, keywords=None, defaults=(None, None, None, 30, 1, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.optimizer.PipelineOptimizer.minimize (ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) -paddle.fluid.backward.append_backward (ArgSpec(args=['loss', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '08a5dd9f6f376ff3d55e0b1d92115cbd')) +paddle.fluid.backward.append_backward (ArgSpec(args=['loss', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '1b7b2bfb986e93048e75ba69f2f490ab')) paddle.fluid.backward.gradients (ArgSpec(args=['targets', 'inputs', 'target_gradients', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'e2097e1e0ed84ae44951437bfe269a1b')) paddle.fluid.regularizer.L1DecayRegularizer.__init__ (ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.regularizer.L2DecayRegularizer.__init__ (ArgSpec(args=['self', 'regularization_coeff'], varargs=None, keywords=None, defaults=(0.0,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) @@ -903,10 +903,10 @@ paddle.fluid.dygraph_grad_clip.GradClipByValue.__init__ (ArgSpec(args=['self', ' paddle.fluid.dygraph_grad_clip.GradClipByNorm.__init__ (ArgSpec(args=['self', 'clip_norm'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.dygraph_grad_clip.GradClipByGlobalNorm.__init__ (ArgSpec(args=['self', 'max_global_norm'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754')) paddle.fluid.profiler.cuda_profiler (ArgSpec(args=['output_file', 'output_mode', 'config'], varargs=None, keywords=None, defaults=(None, None)), ('document', '49f5db5da13cfd8c069754dd11be3901')) -paddle.fluid.profiler.reset_profiler (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'd33483b1781e47c4c5d5fefa7b7debcb')) -paddle.fluid.profiler.profiler (ArgSpec(args=['state', 'sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile')), ('document', 'd8db46bf9a579bec476d09dea80eb23d')) -paddle.fluid.profiler.start_profiler (ArgSpec(args=['state'], varargs=None, keywords=None, defaults=None), ('document', '88da8fb6dbebaee2f7520188a09574f9')) -paddle.fluid.profiler.stop_profiler (ArgSpec(args=['sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile')), ('document', 'a7500e39dd033f1e64f562e909333a8a')) +paddle.fluid.profiler.reset_profiler (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'fd1f25a7a06516ca9a1f4ab0783a4d70')) +paddle.fluid.profiler.profiler (ArgSpec(args=['state', 'sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile')), ('document', 'a2be24e028dffa06ab28cc55a27c59e4')) +paddle.fluid.profiler.start_profiler (ArgSpec(args=['state'], varargs=None, keywords=None, defaults=None), ('document', '4c192ea399e6e80b1ab47a8265b022a5')) +paddle.fluid.profiler.stop_profiler (ArgSpec(args=['sorted_key', 'profile_path'], varargs=None, keywords=None, defaults=(None, '/tmp/profile')), ('document', 'bc8628b859b04242200e48a458c971c4')) paddle.fluid.unique_name.generate (ArgSpec(args=['key'], varargs=None, keywords=None, defaults=None), ('document', '4d68cde4c4df8f1b8018620b4dc19b42')) paddle.fluid.unique_name.switch (ArgSpec(args=['new_generator'], varargs=None, keywords=None, defaults=(None,)), ('document', '695a6e91afbcdbafac69a069038811be')) paddle.fluid.unique_name.guard (ArgSpec(args=['new_generator'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ead717d6d440a1eb11971695cd1727f4')) diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index d9e9df1e0b5..b346c62d811 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -625,6 +625,7 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python + import paddle.fluid as fluid # create tensor from a scope and set value to it. param = scope.var('Param').get_tensor() param_array = np.full((height, row_numel), 5.0).astype("float32") @@ -781,6 +782,7 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python + import paddle.fluid as fluid gpu_place = fluid.CUDAPlace(0) )DOC") @@ -839,6 +841,7 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python + import paddle.fluid as fluid cpu_place = fluid.CPUPlace() )DOC") @@ -858,6 +861,7 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python + import paddle.fluid as fluid place = fluid.CUDAPinnedPlace() )DOC") @@ -1156,6 +1160,7 @@ All parameter, weight, gradient are variables in Paddle. Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[13], dtype='float32') y = fluid.layers.data(name='y', shape=[1], dtype='float32') y_predict = fluid.layers.fc(input=x, size=1, act=None) diff --git a/python/paddle/fluid/average.py b/python/paddle/fluid/average.py index 40a734af311..a7d64d37bc7 100644 --- a/python/paddle/fluid/average.py +++ b/python/paddle/fluid/average.py @@ -49,6 +49,7 @@ class WeightedAverage(object): Examples: .. code-block:: python + import paddle.fluid as fluid avg = fluid.average.WeightedAverage() avg.add(value=2.0, weight=1) avg.add(value=4.0, weight=2) diff --git a/python/paddle/fluid/backward.py b/python/paddle/fluid/backward.py index 9de001849b9..3771361cd2d 100644 --- a/python/paddle/fluid/backward.py +++ b/python/paddle/fluid/backward.py @@ -489,6 +489,7 @@ def append_backward(loss, parameter_list=None, no_grad_set=None, # network configuration code # loss from ... + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[13], dtype='float32') y = fluid.layers.data(name='y', shape=[1], dtype='float32') diff --git a/python/paddle/fluid/data_feed_desc.py b/python/paddle/fluid/data_feed_desc.py index 5ed38f9999f..fa4e35a44c4 100644 --- a/python/paddle/fluid/data_feed_desc.py +++ b/python/paddle/fluid/data_feed_desc.py @@ -31,6 +31,7 @@ class DataFeedDesc(object): .. code-block:: python + import paddle.fluid as fluid f = open("data.proto", "w") print >> f, 'name: "MultiSlotDataFeed"' print >> f, 'batch_size: 2' @@ -61,6 +62,7 @@ class DataFeedDesc(object): .. code-block:: python + import paddle.fluid as fluid data_feed = fluid.DataFeedDesc('data.proto') data_feed.set_batch_size(128) data_feed.set_dense_slots('wd') # The slot named 'wd' will be dense @@ -95,6 +97,7 @@ class DataFeedDesc(object): Example: .. code-block:: python + import paddle.fluid as fluid f = open("data.proto", "w") print >> f, 'name: "MultiSlotDataFeed"' print >> f, 'batch_size: 2' @@ -131,6 +134,7 @@ class DataFeedDesc(object): Example: .. code-block:: python + import paddle.fluid as fluid f = open("data.proto", "w") print >> f, 'name: "MultiSlotDataFeed"' print >> f, 'batch_size: 2' @@ -175,6 +179,7 @@ class DataFeedDesc(object): Example: .. code-block:: python + import paddle.fluid as fluid f = open("data.proto", "w") print >> f, 'name: "MultiSlotDataFeed"' print >> f, 'batch_size: 2' @@ -217,6 +222,7 @@ class DataFeedDesc(object): Example: .. code-block:: python + import paddle.fluid as fluid f = open("data.proto", "w") print >> f, 'name: "MultiSlotDataFeed"' print >> f, 'batch_size: 2' diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py index 286ec7d1f7a..80719e9b39c 100644 --- a/python/paddle/fluid/executor.py +++ b/python/paddle/fluid/executor.py @@ -72,6 +72,7 @@ def scope_guard(scope): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy new_scope = fluid.Scope() diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 56680ae6d0d..49d75eface8 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -67,6 +67,7 @@ def in_dygraph_mode(): Examples: .. code-block:: python + import paddle.fluid as fluid if fluid.in_dygraph_mode(): pass @@ -143,6 +144,7 @@ def cuda_places(device_ids=None): Examples: .. code-block:: python + import paddle.fluid as fluid cuda_places = fluid.cuda_places() """ @@ -173,6 +175,7 @@ def cpu_places(device_count=None): Examples: .. code-block:: python + import paddle.fluid as fluid cpu_places = fluid.cpu_places() """ @@ -199,6 +202,7 @@ def cuda_pinned_places(device_count=None): Examples: .. code-block:: python + import paddle.fluid as fluid cuda_pinned_places_cpu_num = fluid.cuda_pinned_places() # or cuda_pinned_places = fluid.cuda_pinned_places(1) @@ -251,6 +255,7 @@ def name_scope(prefix=None): Examples: .. code-block:: python + import paddle.fluid as fluid with fluid.name_scope("s1"): a = fluid.layers.data(name='data', shape=[1], dtype='int32') b = a + 1 @@ -412,6 +417,7 @@ class Variable(object): Examples: .. code-block:: python + import paddle.fluid as fluid cur_program = Program() cur_block = cur_program.current_block() new_variable = cur_block.create_var(name="X", @@ -1011,6 +1017,7 @@ class Operator(object): Examples: .. code-block:: python + import paddle.fluid as fluid cur_program = Program() cur_block = cur_program.current_block() # var1 += var2 + var3 @@ -2918,6 +2925,7 @@ class Program(object): Examples: + >>> import paddle.fluid as fluid >>> p, g = backward(...) >>> with program._optimized_guard([p,g]): >>> p = p - 0.001 * g @@ -2951,6 +2959,7 @@ class Program(object): Examples: + >>> import paddle.fluid as fluid >>> p, g = backward(...) >>> with program.lr_schedule_guard(): >>> lr = lr * decay diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py index ce55237d07b..a5a50732a41 100644 --- a/python/paddle/fluid/initializer.py +++ b/python/paddle/fluid/initializer.py @@ -42,7 +42,8 @@ def force_init_on_cpu(): .. code-block:: python - if fluid.initializer.force_init_on_cpu(): + import paddle.fluid as fluid + if fluid.initializer.force_init_on_cpu(): step = fluid.layers.create_global_var( shape=[2,3], value=1.0, dtype='float32') @@ -58,7 +59,8 @@ def init_on_cpu(): Examples: .. code-block:: python - with fluid.initializer.init_on_cpu(): + import paddle.fluid as fluid + with fluid.initializer.init_on_cpu(): step = fluid.layers.create_global_var( shape=[2,3], value=1.0, dtype='float32') @@ -133,7 +135,8 @@ class ConstantInitializer(Initializer): Examples: .. code-block:: python - x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") + import paddle.fluid as fluid + x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") fc = fluid.layers.fc(input=x, size=10, param_attr=fluid.initializer.Constant(value=2.0)) @@ -292,7 +295,8 @@ class NormalInitializer(Initializer): Examples: .. code-block:: python - x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") + import paddle.fluid as fluid + x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") fc = fluid.layers.fc(input=x, size=10, param_attr=fluid.initializer.Normal(loc=0.0, scale=2.0)) @@ -608,7 +612,8 @@ class MSRAInitializer(Initializer): Examples: .. code-block:: python - x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") + import paddle.fluid as fluid + x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") fc = fluid.layers.fc(input=x, size=10, param_attr=fluid.initializer.MSRA(uniform=False)) @@ -710,7 +715,8 @@ class BilinearInitializer(Initializer): .. code-block:: python - factor = 2 + import paddle.fluid as fluid + factor = 2 C = 2 w_attr = fluid.param_attr.ParamAttr( learning_rate=0., @@ -836,6 +842,7 @@ class NumpyArrayInitializer(Initializer): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[5], dtype='float32') fc = fluid.layers.fc(input=x, size=10, param_attr=fluid.initializer.NumpyArrayInitializer(numpy.array([1,2]))) diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index a0573881b79..d4694f5daa2 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -54,6 +54,7 @@ def is_parameter(var): Examples: .. code-block:: python + import paddle.fluid as fluid param = fluid.default_main_program().global_block().var('fc.w') res = fluid.io.is_parameter(param) """ @@ -74,6 +75,7 @@ def is_persistable(var): Examples: .. code-block:: python + import paddle.fluid as fluid param = fluid.default_main_program().global_block().var('fc.b') res = fluid.io.is_persistable(param) """ @@ -311,6 +313,7 @@ def _save_distributed_persistables(executor, dirname, main_program): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) param_path = "./my_paddle_model" t = distribute_transpiler.DistributeTranspiler() @@ -693,6 +696,7 @@ def load_params(executor, dirname, main_program=None, filename=None): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) param_path = "./my_paddle_model" prog = fluid.default_main_program() @@ -735,6 +739,7 @@ def load_persistables(executor, dirname, main_program=None, filename=None): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) param_path = "./my_paddle_model" prog = fluid.default_main_program() @@ -772,6 +777,7 @@ def _load_distributed_persistables(executor, dirname, main_program=None): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) param_path = "./my_paddle_model" t = distribute_transpiler.DistributeTranspiler() @@ -1242,6 +1248,7 @@ def get_parameter_value(para, executor): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) param = fluid.default_main_program().global_block().var('fc.w') p = fluid.io.get_parameter_value(param, exe) @@ -1279,6 +1286,7 @@ def get_parameter_value_by_name(name, executor, program=None): Examples: .. code-block:: python + import paddle.fluid as fluid exe = fluid.Executor(fluid.CPUPlace()) p = fluid.io.get_parameter_value('fc.w', exe) """ diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py index d8022526401..535c13b98b2 100644 --- a/python/paddle/fluid/layers/control_flow.py +++ b/python/paddle/fluid/layers/control_flow.py @@ -58,6 +58,7 @@ def split_lod_tensor(input, mask, level=0): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[1]) x.persistable = True @@ -107,6 +108,7 @@ def merge_lod_tensor(in_true, in_false, x, mask, level=0): Examples: .. code-block:: python + import paddle.fluid as fluid x = layers.data( name='x', shape=[1], dtype='float32', stop_gradient=False) y = layers.data( @@ -757,6 +759,7 @@ def lod_rank_table(x, level=0): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[10], dtype='float32', lod_level=1) out = layers.lod_rank_table(x=x, level=0) @@ -823,6 +826,7 @@ def lod_tensor_to_array(x, table): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[10]) table = fluid.layers.lod_rank_table(x, level=0) array = fluid.layers.lod_tensor_to_array(x, table) @@ -856,6 +860,7 @@ def array_to_lod_tensor(x, table): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[10]) table = fluid.layers.lod_rank_table(x, level=0) array = fluid.layers.lod_tensor_to_array(x, table) @@ -965,6 +970,7 @@ def create_array(dtype): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.create_array(dtype='float32') """ @@ -992,6 +998,7 @@ def less_than(x, y, force_cpu=None, cond=None): Examples: .. code-block:: python + import paddle.fluid as fluid label = fluid.layers.data(name='y', shape=[1], dtype='int64') limit = fluid.layers.fill_constant(shape=[1], dtype='int64', value=5) cond = fluid.layers.less_than(x=label, y=limit) @@ -1357,6 +1364,7 @@ class ConditionalBlock(object): Examples: .. code-block:: python + import paddle.fluid as fluid cond = layers.less_than(x=label, y=limit) true_image, false_image = layers.split_lod_tensor( input=image, mask=cond) diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py index 27a28f30c86..671b2192397 100644 --- a/python/paddle/fluid/layers/detection.py +++ b/python/paddle/fluid/layers/detection.py @@ -680,6 +680,7 @@ def box_coder(prior_box, .. code-block:: python + import paddle.fluid as fluid prior_box = fluid.layers.data(name='prior_box', shape=[512, 4], dtype='float32', @@ -811,6 +812,7 @@ def yolov3_loss(x, Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[255, 13, 13], dtype='float32') gt_box = fluid.layers.data(name='gt_box', shape=[6, 4], dtype='float32') gt_label = fluid.layers.data(name='gt_label', shape=[6], dtype='int32') @@ -1001,6 +1003,7 @@ def detection_map(detect_res, Examples: .. code-block:: python + import paddle.fluid as fluid from fluid.layers import detection detect_res = fluid.layers.data( name='detect_res', @@ -1119,6 +1122,7 @@ def bipartite_match(dist_matrix, Examples: + >>> import paddle.fluid as fluid >>> x = fluid.layers.data(name='x', shape=[4], dtype='float32') >>> y = fluid.layers.data(name='y', shape=[4], dtype='float32') >>> iou = fluid.layers.iou_similarity(x=x, y=y) @@ -1340,6 +1344,7 @@ def ssd_loss(location, type of `max_negative`. Examples: + >>> import paddle.fluid as fluid >>> pb = fluid.layers.data( >>> name='prior_box', >>> shape=[10, 4], @@ -1542,6 +1547,7 @@ def prior_box(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9]) images = fluid.layers.data(name="images", shape=[3,9,12]) box, var = fluid.layers.prior_box( @@ -1668,6 +1674,7 @@ def density_prior_box(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9]) images = fluid.layers.data(name="images", shape=[3,9,12]) box, var = fluid.layers.density_prior_box( @@ -2019,6 +2026,7 @@ def anchor_generator(input, .. code-block:: python + import paddle.fluid as fluid conv1 = fluid.layers.data(name='conv1', shape=[48, 16, 16], dtype='float32') anchor, var = fluid.layers.anchor_generator( input=conv1, @@ -2525,6 +2533,7 @@ def box_clip(input, im_info, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid boxes = fluid.layers.data( name='boxes', shape=[8, 4], dtype='float32', lod_level=1) im_info = fluid.layers.data(name='im_info', shape=[3]) @@ -2729,6 +2738,7 @@ def multiclass_nms(bboxes, .. code-block:: python + import paddle.fluid as fluid boxes = fluid.layers.data(name='bboxes', shape=[81, 4], dtype='float32', lod_level=1) scores = fluid.layers.data(name='scores', shape=[81], @@ -2807,6 +2817,7 @@ def distribute_fpn_proposals(fpn_rois, Examples: .. code-block:: python + import paddle.fluid as fluid fpn_rois = fluid.layers.data( name='data', shape=[4], dtype='float32', lod_level=1) multi_rois, restore_ind = fluid.layers.distribute_fpn_proposals( @@ -2865,6 +2876,7 @@ def box_decoder_and_assign(prior_box, Examples: .. code-block:: python + import paddle.fluid as fluid pb = fluid.layers.data( name='prior_box', shape=[4], dtype='float32') pbv = fluid.layers.data( @@ -2931,6 +2943,7 @@ def collect_fpn_proposals(multi_rois, Examples: .. code-block:: python + import paddle.fluid as fluid multi_rois = [] multi_scores = [] for i in range(4): diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py index dcb99d8aa95..c79f788de73 100644 --- a/python/paddle/fluid/layers/io.py +++ b/python/paddle/fluid/layers/io.py @@ -84,6 +84,7 @@ def data(name, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='x', shape=[784], dtype='float32') """ helper = LayerHelper('data', **locals()) @@ -147,6 +148,7 @@ class ListenAndServ(object): Examples: .. code-block:: python + import paddle.fluid as fluid with fluid.program_guard(main): serv = layers.ListenAndServ( "127.0.0.1:6170", ["X"], optimizer_mode=False) @@ -449,6 +451,7 @@ def random_data_generator(low, high, shapes, lod_levels, for_parallel=True): .. code-block:: python + import paddle.fluid as fluid reader = fluid.layers.random_data_generator( low=0.0, high=1.0, @@ -1017,6 +1020,7 @@ def shuffle(reader, buffer_size): Examples: .. code-block:: python + import paddle.fluid as fluid raw_reader = fluid.layers.io.open_files(filenames=['./data1.recordio', './data2.recordio'], shapes=[(3,224,224), (1,)], @@ -1048,6 +1052,7 @@ def batch(reader, batch_size): Examples: .. code-block:: python + import paddle.fluid as fluid raw_reader = fluid.layers.io.open_files(filenames=['./data1.recordio', './data2.recordio'], shapes=[(3,224,224), (1,)], diff --git a/python/paddle/fluid/layers/layer_function_generator.py b/python/paddle/fluid/layers/layer_function_generator.py index 7391974b14f..b6678088f79 100644 --- a/python/paddle/fluid/layers/layer_function_generator.py +++ b/python/paddle/fluid/layers/layer_function_generator.py @@ -253,6 +253,7 @@ def generate_activation_fn(op_type): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name="input", shape=[32, 784]) result = fluid.layers.%s(data) """ % op_type diff --git a/python/paddle/fluid/layers/learning_rate_scheduler.py b/python/paddle/fluid/layers/learning_rate_scheduler.py index 278830c8e27..ae7611fd6d9 100644 --- a/python/paddle/fluid/layers/learning_rate_scheduler.py +++ b/python/paddle/fluid/layers/learning_rate_scheduler.py @@ -54,6 +54,7 @@ def noam_decay(d_model, warmup_steps): .. code-block:: python + import padde.fluid as fluid import numpy as np # set hyper parameters d_model = 2 @@ -415,7 +416,8 @@ def cosine_decay(learning_rate, step_each_epoch, epochs): Examples: .. code-block:: python - base_lr = 0.1 + import paddle.fluid as fluid + base_lr = 0.1 lr = fluid.layers.cosine_decay( learning_rate = base_lr, step_each_epoch=10000, epochs=120) """ @@ -457,6 +459,7 @@ def linear_lr_warmup(learning_rate, warmup_steps, start_lr, end_lr): Examples: .. code-block:: python + import paddle.fluid as fluid boundaries = [100, 200] lr_steps = [0.1, 0.01, 0.001] warmup_steps = 50 diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 8aeb0573d80..d1d4ae40f43 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -302,6 +302,7 @@ def fc(input, Examples: .. code-block:: python + import paddle.fluid as fluid # when input is single tensor data = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") fc = fluid.layers.fc(input=data, size=1000, act="tanh") @@ -487,6 +488,7 @@ def dynamic_lstm(input, Examples: .. code-block:: python + import paddle.fluid as fluid emb_dim = 256 vocab_size = 10000 hidden_dim = 512 @@ -877,6 +879,7 @@ def dynamic_lstmp(input, .. code-block:: python + import paddle.fluid as fluid dict_dim, emb_dim = 128, 64 data = fluid.layers.data(name='sequence', shape=[1], dtype='int32', lod_level=1) @@ -1332,6 +1335,7 @@ def crf_decoding(input, param_attr, label=None): Examples: .. code-block:: python + import paddle.fluid as fluid images = fluid.layers.data(name='pixel', shape=[784], dtype='float32') label = fluid.layers.data(name='label', shape=[1], dtype='int32') hidden = fluid.layers.fc(input=images, size=2) @@ -1369,6 +1373,7 @@ def cos_sim(X, Y): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[3, 7], dtype='float32', append_batch_size=False) y = fluid.layers.data(name='y', shape=[1, 7], dtype='float32', append_batch_size=False) out = fluid.layers.cos_sim(x, y) @@ -1439,6 +1444,7 @@ def dropout(x, .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") droped = fluid.layers.dropout(x, dropout_prob=0.5) """ @@ -1532,6 +1538,7 @@ def cross_entropy(input, label, soft_label=False, ignore_index=kIgnoreIndex): Examples: .. code-block:: python + import paddle.fluid as fluid classdim = 7 x = fluid.layers.data(name='x', shape=[3, 7], dtype='float32', append_batch_size=False) label = fluid.layers.data(name='label', shape=[3, 1], dtype='float32', append_batch_size=False) @@ -1644,6 +1651,7 @@ def square_error_cost(input, label): Examples: .. code-block:: python + import paddle.fluid as fluid y = fluid.layers.data(name='y', shape=[1], dtype='float32') y_predict = fluid.layers.data(name='y_predict', shape=[1], dtype='float32') cost = fluid.layers.square_error_cost(input=y_predict, label=y) @@ -1906,6 +1914,7 @@ def sequence_softmax(input, use_cudnn=False, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[7, 1], dtype='float32', lod_level=1) x_sequence_softmax = fluid.layers.sequence_softmax(input=x) @@ -2099,6 +2108,7 @@ def conv2d(input, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32') conv2d = fluid.layers.conv2d(input=data, num_filters=2, filter_size=3, act="relu") """ @@ -2287,6 +2297,7 @@ def conv3d(input, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[3, 12, 32, 32], dtype='float32') conv3d = fluid.layers.conv3d(input=data, num_filters=2, filter_size=3, act="relu") """ @@ -2493,6 +2504,7 @@ def sequence_first_step(input): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[7, 1], dtype='float32', lod_level=1) x_first_step = fluid.layers.sequence_first_step(input=x) @@ -2526,6 +2538,7 @@ def sequence_last_step(input): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[7, 1], dtype='float32', lod_level=1) x_last_step = fluid.layers.sequence_last_step(input=x) @@ -2579,6 +2592,7 @@ def sequence_slice(input, offset, length, name=None): .. code-block:: python + import paddle.fluid as fluid import numpy as np seqs = fluid.layers.data(name='x', shape=[10, 5], dtype='float32', lod_level=1) @@ -2655,6 +2669,7 @@ def pool2d(input, .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name='data', shape=[3, 32, 32], dtype='float32') pool2d = fluid.layers.pool2d( @@ -2748,6 +2763,7 @@ def pool3d(input, .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name='data', shape=[3, 32, 32, 32], dtype='float32') pool3d = fluid.layers.pool3d( @@ -2865,6 +2881,7 @@ def adaptive_pool2d(input, # wend = ceil((i + 1) * W / n) # output[:, :, i, j] = avg(input[:, :, hstart: hend, wstart: wend]) # + import paddle.fluid as fluid data = fluid.layers.data( name='data', shape=[3, 32, 32], dtype='float32') pool_out = fluid.layers.adaptive_pool2d( @@ -3134,6 +3151,7 @@ def batch_norm(input, .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[3, 7, 3, 7], dtype='float32', append_batch_size=False) hidden1 = fluid.layers.fc(input=x, size=200, param_attr='fc1.w') hidden2 = fluid.layers.batch_norm(input=hidden1) @@ -3417,6 +3435,7 @@ def layer_norm(input, Examples: + >>> import paddle.fluid as fluid >>> data = fluid.layers.data(name='data', shape=[3, 32, 32], >>> dtype='float32') >>> x = fluid.layers.layer_norm(input=data, begin_norm_axis=1) @@ -3498,6 +3517,7 @@ def group_norm(input, Examples: + >>> import paddle.fluid as fluid >>> data = fluid.layers.data(name='data', shape=[8, 32, 32], >>> dtype='float32') >>> x = fluid.layers.group_norm(input=data, groups=4) @@ -3755,6 +3775,7 @@ def conv2d_transpose(input, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32') conv2d_transpose = fluid.layers.conv2d_transpose(input=data, num_filters=2, filter_size=3) """ @@ -3943,6 +3964,7 @@ def conv3d_transpose(input, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[3, 12, 32, 32], dtype='float32') conv3d_transpose = fluid.layers.conv3d_transpose(input=data, num_filters=2, filter_size=3) """ @@ -4058,6 +4080,7 @@ def sequence_expand(x, y, ref_level=-1, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers x = fluid.layers.data(name='x', shape=[10], dtype='float32') y = fluid.layers.data(name='y', shape=[10, 20], @@ -4126,6 +4149,8 @@ def sequence_expand_as(x, y, name=None): Examples: .. code-block:: python + + import paddle.fluid as fluid import paddle.fluid.layers as layers x = fluid.layers.data(name='x', shape=[10], dtype='float32') @@ -4172,6 +4197,7 @@ def sequence_pad(x, pad_value, maxlen=None, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy x = fluid.layers.data(name='y', shape=[10, 5], @@ -4244,6 +4270,7 @@ def sequence_unpad(x, length, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[10, 5], dtype='float32') len = fluid.layers.data(name='length', shape=[1], dtype='int64') out = fluid.layers.sequence_unpad(x=x, length=len) @@ -4914,6 +4941,7 @@ def reduce_all(input, dim=None, keep_dim=False, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers import numpy as np @@ -4968,6 +4996,7 @@ def reduce_any(input, dim=None, keep_dim=False, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers import numpy as np @@ -5097,6 +5126,7 @@ def l2_normalize(x, axis, epsilon=1e-12, name=None): .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name="data", shape=(3, 17, 13), dtype="float32") @@ -5187,6 +5217,7 @@ def matmul(x, y, transpose_x=False, transpose_y=False, alpha=1.0, name=None): # x: [M], y: [N] # fluid.layers.matmul(x, y, True, True) # out: [M, N] + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[2, 3], dtype='float32') y = fluid.layers.data(name='y', shape=[3, 2], dtype='float32') out = fluid.layers.matmul(x, y, True, True) @@ -5289,6 +5320,7 @@ def topk(input, k, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers input = layers.data(name="input", shape=[13, 11], dtype='float32') top5_values, top5_indices = layers.topk(input, k=5) @@ -5668,7 +5700,8 @@ def nce(input, .. code-block:: python - import numpy as np + import paddle.fluid as fluid + import numpy as np window_size = 5 words = [] @@ -6571,6 +6604,7 @@ def smooth_l1(x, y, inside_weight=None, outside_weight=None, sigma=None): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[128], dtype='float32') label = fluid.layers.data( name='label', shape=[100], dtype='float32') @@ -6609,6 +6643,7 @@ def one_hot(input, depth): Examples: .. code-block:: python + import paddle.fluid as fluid label = fluid.layers.data(name="label", shape=[1], dtype="int64") one_hot_label = fluid.layers.one_hot(input=label, depth=10) """ @@ -6654,6 +6689,7 @@ def autoincreased_step_counter(counter_name=None, begin=1, step=1): Examples: .. code-block:: python + import paddle.fluid as fluid global_step = fluid.layers.autoincreased_step_counter( counter_name='@LR_DECAY_COUNTER@', begin=0, step=1) """ @@ -6745,6 +6781,7 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=False, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name='data', shape=[2, 4, 6], dtype='float32') reshaped = fluid.layers.reshape( @@ -6856,6 +6893,7 @@ def squeeze(input, axes, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers x = layers.data(name='x', shape=[5, 1, 10]) y = layers.squeeze(input=x, axes=[1]) @@ -6990,6 +7028,7 @@ def lod_reset(x, y=None, target_lod=None): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[10]) y = fluid.layers.data(name='y', shape=[10, 20], lod_level=2) out = fluid.layers.lod_reset(x=x, y=y) @@ -7050,6 +7089,7 @@ def lrn(input, n=5, k=1.0, alpha=1e-4, beta=0.75, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name="data", shape=[3, 112, 112], dtype="float32") lrn = fluid.layers.lrn(input=data) @@ -7271,6 +7311,7 @@ def label_smooth(label, Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers label = layers.data(name="label", shape=[1], dtype="float32") @@ -7366,6 +7407,7 @@ def roi_align(input, Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data( name='data', shape=[256, 32, 32], dtype='float32') rois = fluid.layers.data( @@ -7588,6 +7630,7 @@ def image_resize(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9], dtype="float32") out = fluid.layers.image_resize(input, out_shape=[12, 12], resample="NEAREST") """ @@ -7755,6 +7798,7 @@ def resize_bilinear(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9], dtype="float32") out = fluid.layers.resize_bilinear(input, out_shape=[12, 12]) """ @@ -7849,6 +7893,7 @@ def resize_nearest(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9], dtype="float32") out = fluid.layers.resize_nearest(input, out_shape=[12, 12]) """ @@ -7878,6 +7923,7 @@ def image_resize_short(input, out_short_len, resample='BILINEAR'): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[3,6,9], dtype="float32") out = fluid.layers.image_resize_short(input, out_short_len=3) """ @@ -7941,6 +7987,7 @@ def gather(input, index, overwrite=True): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[-1, 5], dtype='float32') index = fluid.layers.data(name='index', shape=[-1, 1], dtype='int32') output = fluid.layers.gather(x, index) @@ -8058,6 +8105,7 @@ def sequence_scatter(input, index, updates, name=None): .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers input = layers.data( name="x", shape=[3, 6], append_batch_size=False, dtype='float32' ) @@ -8095,6 +8143,7 @@ def random_crop(x, shape, seed=None): ${out_comment} Examples: + >>> import paddle.fluid as fluid >>> img = fluid.layers.data("img", [3, 256, 256]) >>> cropped_img = fluid.layers.random_crop(img, shape=[3, 224, 224]) """ @@ -8142,6 +8191,7 @@ def log(x, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") output = fluid.layers.log(x) """ @@ -8174,6 +8224,7 @@ def relu(x, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") output = fluid.layers.relu(x) """ @@ -8553,6 +8604,7 @@ def rank_loss(label, left, right, name=None): .. code-block:: python + import paddle.fluid as fluid label = fluid.layers.data(name="label", shape=[-1, 1], dtype="float32") left = fluid.layers.data(name="left", shape=[-1, 1], dtype="float32") right = fluid.layers.data(name="right", shape=[-1, 1], dtype="float32") @@ -8609,6 +8661,7 @@ def margin_rank_loss(label, left, right, margin=0.1, name=None): .. code-block:: python + import paddle.fluid as fluid label = fluid.layers.data(name="label", shape=[-1, 1], dtype="float32") left = fluid.layers.data(name="left", shape=[-1, 1], dtype="float32") right = fluid.layers.data(name="right", shape=[-1, 1], dtype="float32") @@ -8744,6 +8797,7 @@ def elu(x, alpha=1.0, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32") y = fluid.layers.elu(x, alpha=0.2) """ @@ -8774,6 +8828,7 @@ def relu6(x, threshold=6.0, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32") y = fluid.layers.relu6(x, threshold=6.0) """ @@ -8836,6 +8891,7 @@ def stanh(x, scale_a=2.0 / 3.0, scale_b=1.7159, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32") y = fluid.layers.stanh(x, scale_a=0.67, scale_b=1.72) """ @@ -8900,6 +8956,7 @@ def swish(x, beta=1.0, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3,10,32,32], dtype="float32") y = fluid.layers.swish(x, beta=2.0) """ @@ -8993,6 +9050,7 @@ def brelu(x, t_min=0.0, t_max=24.0, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[2,3,16,16], dtype="float32") y = fluid.layers.brelu(x, t_min=1.0, t_max=20.0) """ @@ -9023,6 +9081,7 @@ def leaky_relu(x, alpha=0.02, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[2,3,16,16], dtype="float32") y = fluid.layers.leaky_relu(x, alpha=0.01) """ @@ -9123,6 +9182,7 @@ def flatten(x, axis=1, name=None): .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[4, 4, 3], dtype="float32") out = fluid.layers.flatten(x=x, axis=2) """ @@ -9229,6 +9289,7 @@ def sequence_mask(x, maxlen=None, dtype='int64', name=None): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers x = fluid.layers.data(name='x', shape=[10], dtype='float32', lod_level=1) @@ -9324,6 +9385,7 @@ def stack(x, axis=0): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers x1 = layers.data(name='x1', shape=[1, 2], dtype='int32') x2 = layers.data(name='x2', shape=[1, 2], dtype='int32') @@ -9501,6 +9563,7 @@ def uniform_random_batch_size_like(input, Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers input = layers.data(name="input", shape=[13, 11], dtype='float32') @@ -9545,6 +9608,7 @@ def gaussian_random(shape, mean=0.0, std=1.0, seed=0, dtype='float32'): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers out = layers.gaussian_random(shape=[20, 30]) """ @@ -9585,6 +9649,7 @@ def sampling_id(x, min=0.0, max=1.0, seed=0, dtype='float32'): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data( name="X", shape=[13, 11], @@ -9635,6 +9700,7 @@ def gaussian_random_batch_size_like(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[13, 11], dtype='float32') out = fluid.layers.gaussian_random_batch_size_like( @@ -9675,6 +9741,7 @@ def sum(x): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers input0 = layers.data(name="input0", shape=[13, 11], dtype='float32') input1 = layers.data(name="input1", shape=[13, 11], dtype='float32') @@ -10030,6 +10097,7 @@ def logical_and(x, y, out=None, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid left = fluid.layers.data( name='left', shape=[1], dtype='int32') right = fluid.layers.data( @@ -10058,6 +10126,7 @@ def logical_or(x, y, out=None, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid left = fluid.layers.data( name='left', shape=[1], dtype='int32') right = fluid.layers.data( @@ -10086,6 +10155,7 @@ def logical_xor(x, y, out=None, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid left = fluid.layers.data( name='left', shape=[1], dtype='int32') right = fluid.layers.data( @@ -10113,6 +10183,7 @@ def logical_not(x, out=None, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid left = fluid.layers.data( name='left', shape=[1], dtype='int32') result = fluid.layers.logical_not(x=left) @@ -10180,6 +10251,7 @@ def clip_by_norm(x, max_norm, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data( name='data', shape=[1], dtype='float32') reward = fluid.layers.clip_by_norm(x=input, max_norm=1.0) @@ -10218,6 +10290,7 @@ def mean(x, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data( name='data', shape=[2, 3], dtype='float32') mean = fluid.layers.mean(input) @@ -10252,6 +10325,7 @@ def merge_selected_rows(x, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid b = fluid.default_main_program().global_block() var = b.create_var( name="X", dtype="float32", persistable=True, @@ -10340,6 +10414,7 @@ def sigmoid_cross_entropy_with_logits(x, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data( name='data', shape=[10], dtype='float32') label = fluid.layers.data( @@ -10386,6 +10461,7 @@ def maxout(x, groups, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data( name='data', shape=[256, 32, 32], @@ -10660,6 +10736,7 @@ def similarity_focus(input, axis, indexes, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name='data', shape=[-1, 3, 2, 2], dtype='float32') fluid.layers.similarity_focus(input=data, axis=1, indexes=[0]) @@ -10887,6 +10964,7 @@ def log_loss(input, label, epsilon=1e-4, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid label = fluid.layers.data(name='label', shape=[1], dtype='int64') prob = fluid.layers.data(name='prob', shape=[10], dtype='float32') cost = fluid.layers.log_loss(input=prob, label=label) @@ -11057,6 +11135,7 @@ def bilinear_tensor_product(x, Examples: .. code-block:: python + import paddle.fluid as fluid layer1 = fluid.layers.data("t1", shape=[-1, 5], dtype="float32") layer2 = fluid.layers.data("t2", shape=[-1, 4], dtype="float32") tensor = fluid.layers.bilinear_tensor_product(x=layer1, y=layer2, size=1000) @@ -11173,6 +11252,7 @@ def shuffle_channel(x, group, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name='input', shape=[4,2,2], dtype='float32') out = fluid.layers.shuffle_channel(x=input, group=2) """ @@ -11214,6 +11294,7 @@ def temporal_shift(x, seg_num, shift_ratio=0.25, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name='input', shape=[4,2,2], dtype='float32') out = fluid.layers.temporal_shift(x=input, seg_num=2, shift_ratio=0.2) """ @@ -11584,6 +11665,7 @@ def kldiv_loss(x, target, reduction='mean', name=None): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[4,2,2], dtype='float32') target = fluid.layers.data(name='target', shape=[4,2,2], dtype='float32') loss = fluid.layers.kldiv_loss(x=x, target=target, reduction='batchmean') @@ -11629,6 +11711,7 @@ def tree_conv(nodes_vector, Examples: .. code-block:: python + import paddle.fluid as fluid # 10 for max_node_size of dataset, 5 for vector width nodes_vector = fluid.layers.data(name='vectors', shape=[10, 5], dtype='float32') # 10 for max_node_size of dataset, 2 for every edge has two nodes @@ -11693,6 +11776,7 @@ def npair_loss(anchor, positive, labels, l2_reg=0.002): Examples: .. code-block:: python + import paddle.fluid as fluid anchor = fluid.layers.data( name = 'anchor', shape = [18, 6], dtype = 'float32', append_batch_size=False) positive = fluid.layers.data( @@ -11764,6 +11848,7 @@ def pixel_shuffle(x, upscale_factor): .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[9,4,4]) output = fluid.layers.pixel_shuffle(x=input, upscale_factor=3) @@ -11859,6 +11944,7 @@ def continuous_value_model(input, cvm, use_cvm=True): .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[-1, 1], lod_level=1, append_batch_size=False, dtype="int64")#, stop_gradient=False) label = fluid.layers.data(name="label", shape=[-1, 1], append_batch_size=False, dtype="int64") embed = fluid.layers.embedding( @@ -11898,6 +11984,7 @@ def where(condition): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers import numpy as np @@ -12064,6 +12151,7 @@ def deformable_conv(input, Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32') offset = fluid.layers.data(name='offset', shape=[18, 32, 32], dtype='float32') mask = fluid.layers.data(name='mask', shape=[9, 32, 32], dtype='float32') @@ -12295,6 +12383,7 @@ def deformable_roi_pooling(input, Examples: .. code-block:: python + import paddle.fluid as fluid input = fluid.layers.data(name="input", shape=[2, 192, 64, 64], dtype='float32', diff --git a/python/paddle/fluid/layers/ops.py b/python/paddle/fluid/layers/ops.py index 6c944da560d..9f5012f5c9d 100644 --- a/python/paddle/fluid/layers/ops.py +++ b/python/paddle/fluid/layers/ops.py @@ -114,6 +114,7 @@ def hard_shrink(x, threshold=None): hard_shrink.__doc__ = _hard_shrink_.__doc__ + """ Examples: + >>> import paddle.fluid as fluid >>> data = fluid.layers.data(name="input", shape=[784]) >>> result = fluid.layers.hard_shrink(x=data, threshold=0.3) """ @@ -135,6 +136,7 @@ def cumsum(x, axis=None, exclusive=None, reverse=None): cumsum.__doc__ = _cum_sum_.__doc__ + """ Examples: + >>> import paddle.fluid as fluid >>> data = fluid.layers.data(name="input", shape=[32, 784]) >>> result = fluid.layers.cumsum(data, axis=0) """ @@ -157,6 +159,7 @@ def thresholded_relu(x, threshold=None): thresholded_relu.__doc__ = _thresholded_relu_.__doc__ + """ Examples: + >>> import paddle.fluid as fluid >>> data = fluid.layers.data(name="input", shape=[1]) >>> result = fluid.layers.thresholded_relu(data, threshold=0.4) """ diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py index 69b00f5242f..aacfbdb4cab 100644 --- a/python/paddle/fluid/layers/tensor.py +++ b/python/paddle/fluid/layers/tensor.py @@ -49,6 +49,7 @@ def create_tensor(dtype, name=None, persistable=False): Examples: .. code-block:: python + import paddle.fluid as fluid tensor = fluid.layers.create_tensor(dtype='float32') """ helper = LayerHelper("create_tensor", **locals()) @@ -85,6 +86,7 @@ def create_parameter(shape, Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers W = layers.create_parameter(shape=[784, 200], dtype='float32') """ @@ -123,6 +125,7 @@ def create_global_var(shape, Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers var = layers.create_global_var(shape=[2,3], value=1.0, dtype='float32', persistable=True, force_cpu=True, name='new_var') @@ -157,6 +160,7 @@ def cast(x, dtype): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data(name='x', shape=[13], dtype='float32') result = fluid.layers.cast(x=data, dtype='float64') """ @@ -190,6 +194,7 @@ def concat(input, axis=0, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid a = fluid.layers.data(name='a', shape=[2, 13], dtype='float32') b = fluid.layers.data(name='b', shape=[2, 3], dtype='float32') c = fluid.layers.data(name='c', shape=[2, 2], dtype='float32') @@ -482,6 +487,7 @@ def argmin(x, axis=0): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") out = fluid.layers.argmin(x, axis=0) out = fluid.layers.argmin(x, axis=-1) @@ -514,6 +520,7 @@ def argmax(x, axis=0): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") out = fluid.layers.argmax(x, axis=0) out = fluid.layers.argmax(x, axis=-1) @@ -565,6 +572,7 @@ def argsort(input, axis=-1, name=None): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") out, indices = fluid.layers.argsort(input=x, axis=0) """ @@ -712,6 +720,7 @@ def save_combine(x, file_path, overwrite=True): .. code-block:: python + import paddle.fluid as fluid v1 = fluid.layers.data(name="data", shape=(4, 6), dtype="float32") @@ -808,6 +817,7 @@ def isfinite(x): .. code-block:: python + import paddle.fluid as fluid var = fluid.layers.data(name="data", shape=(4, 6), dtype="float32") @@ -843,6 +853,7 @@ def range(start, end, step, dtype): .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.range(0, 10, 2, 'int32') """ @@ -884,6 +895,7 @@ def linspace(start, stop, num, dtype): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.linspace(0, 10, 5, 'float32') # [0.0, 2.5, 5.0, 7.5, 10.0] data = fluid.layers.linspace(0, 10, 1, 'float32') # [0.0] @@ -925,6 +937,7 @@ def zeros_like(x, out=None): Examples: .. code-block:: python + import paddle.fluid as fluid x = fluid.layers.data(name='x', dtype='float32', shape=[3], append_batch_size=False) data = fluid.layers.zeros_like(x) # [0.0, 0.0, 0.0] diff --git a/python/paddle/fluid/metrics.py b/python/paddle/fluid/metrics.py index d871b24f8b9..6748f32fe5b 100644 --- a/python/paddle/fluid/metrics.py +++ b/python/paddle/fluid/metrics.py @@ -154,6 +154,7 @@ class CompositeMetric(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy as np preds = [[0.1], [0.7], [0.8], [0.9], [0.2], [0.2], [0.3], [0.5], [0.8], [0.6]] @@ -226,6 +227,7 @@ class Precision(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy as np metric = fluid.metrics.Precision() @@ -287,6 +289,7 @@ class Recall(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy as np metric = fluid.metrics.Recall() @@ -346,6 +349,7 @@ class Accuracy(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid #suppose we have batch_size = 128 batch_size=128 accuracy_manager = fluid.metrics.Accuracy() @@ -416,6 +420,7 @@ class ChunkEvaluator(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid # init the chunck-level evaluation manager metric = fluid.metrics.ChunkEvaluator() @@ -505,6 +510,7 @@ class EditDistance(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy as np # suppose that batch_size is 128 @@ -605,6 +611,7 @@ class Auc(MetricBase): Examples: .. code-block:: python + import paddle.fluid as fluid import numpy as np # init the auc metric auc_metric = fluid.metrics.Auc("ROC") @@ -729,6 +736,7 @@ class DetectionMAP(object): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers batch_size = -1 # can be any size diff --git a/python/paddle/fluid/nets.py b/python/paddle/fluid/nets.py index 20fbd079f76..e340f03161e 100644 --- a/python/paddle/fluid/nets.py +++ b/python/paddle/fluid/nets.py @@ -190,6 +190,7 @@ def img_conv_group(input, Examples: .. code-block:: python + import paddle.fluid as fluid img = fluid.layers.data(name='img', shape=[1, 28, 28], dtype='float32') conv_pool = fluid.nets.img_conv_group(input=img, conv_padding=1, @@ -328,6 +329,7 @@ def glu(input, dim=-1): Examples: .. code-block:: python + import paddle.fluid as fluid data = fluid.layers.data( name="words", shape=[-1, 6, 3, 9], dtype="float32") # shape of output: [-1, 3, 3, 9] diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py index 2f4de672b9c..46425cfce6e 100644 --- a/python/paddle/fluid/optimizer.py +++ b/python/paddle/fluid/optimizer.py @@ -510,6 +510,7 @@ class Optimizer(object): Examples: .. code-block:: python + import paddle.fluid as fluid loss = network() optimizer = fluid.optimizer.SGD(learning_rate=0.1) params_grads = optimizer.backward(loss) @@ -827,6 +828,7 @@ class DGCMomentumOptimizer(MomentumOptimizer): Examples: .. code-block:: python + import paddle.fluid as fluid optimizer = fluid.optimizer.DGCMomentumOptimizer( learning_rate=0.0001, momentum=0.9, @@ -1699,6 +1701,7 @@ class AdadeltaOptimizer(Optimizer): Examples: .. code-block:: python + import paddle.fluid as fluid optimizer = fluid.optimizer.Adadelta( learning_rate=0.0003, epsilon=1.0e-6, rho=0.95) _, params_grads = optimizer.minimize(cost) @@ -2688,6 +2691,7 @@ class PipelineOptimizer(object): Examples: .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.layers as layers x = fluid.layers.data(name='x', shape=[1], dtype='int64', lod_level=0) diff --git a/python/paddle/fluid/profiler.py b/python/paddle/fluid/profiler.py index 5b50ef9fc8f..b961a655130 100644 --- a/python/paddle/fluid/profiler.py +++ b/python/paddle/fluid/profiler.py @@ -113,6 +113,7 @@ def reset_profiler(): .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.profiler as profiler with profiler.profiler('CPU', 'total', '/tmp/profile'): for iter in range(10): @@ -141,6 +142,7 @@ def start_profiler(state): .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.profiler as profiler profiler.start_profiler('GPU') @@ -190,6 +192,7 @@ def stop_profiler(sorted_key=None, profile_path='/tmp/profile'): .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.profiler as profiler profiler.start_profiler('GPU') @@ -257,6 +260,7 @@ def profiler(state, sorted_key=None, profile_path='/tmp/profile'): .. code-block:: python + import paddle.fluid as fluid import paddle.fluid.profiler as profiler import numpy as np -- GitLab