diff --git a/doc/fluid/api_cn/clip_cn/GradientClipByValue_cn.rst b/doc/fluid/api_cn/clip_cn/GradientClipByValue_cn.rst index c7e45476716dac02a1d87d1bdde0f3843f7d16ca..37e07d29a182372de2cd37d806ad2f1b0ecc5dea 100644 --- a/doc/fluid/api_cn/clip_cn/GradientClipByValue_cn.rst +++ b/doc/fluid/api_cn/clip_cn/GradientClipByValue_cn.rst @@ -26,7 +26,7 @@ GradientClipByValue w_param_attrs = fluid.ParamAttr(name=None, initializer=fluid.initializer.UniformInitializer(low=-1.0, high=1.0, seed=0), learning_rate=1.0, - regularizer=fluid.regualrizer.L1Decay(1.0), + regularizer=fluid.regularizer.L1Decay(1.0), trainable=True, gradient_clip=fluid.clip.GradientClipByValue(-1.0, 1.0)) x = fluid.layers.data(name='x', shape=[10], dtype='float32') diff --git a/doc/fluid/api_cn/dataset_cn/DatasetFactory_cn.rst b/doc/fluid/api_cn/dataset_cn/DatasetFactory_cn.rst index 3bfe36bb4f51026b541bccf241021e31a83c564b..9641efa1cdb61d4b6eec7a986f8ebaa31ee553ec 100644 --- a/doc/fluid/api_cn/dataset_cn/DatasetFactory_cn.rst +++ b/doc/fluid/api_cn/dataset_cn/DatasetFactory_cn.rst @@ -13,7 +13,7 @@ DatasetFactory是一个按数据集名称创建数据集的 "工厂"，可以创 .. code-block:: python import paddle.fluid as fluid - dataset = paddle.fluid.DatasetFactory().create_dataset("InMemoryDataset") + dataset = fluid.DatasetFactory().create_dataset("InMemoryDataset") .. py:method:: create_dataset(datafeed_class='QueueDataset') diff --git a/doc/fluid/api_cn/dataset_cn/InMemoryDataset_cn.rst b/doc/fluid/api_cn/dataset_cn/InMemoryDataset_cn.rst index 8f06579b864b972a761dba563540658cb8547dbb..e35defef0a8e7983038d4dab8ec3c20bb6af6ac6 100644 --- a/doc/fluid/api_cn/dataset_cn/InMemoryDataset_cn.rst +++ b/doc/fluid/api_cn/dataset_cn/InMemoryDataset_cn.rst @@ -84,7 +84,7 @@ InMemoryDataset会向内存中加载数据并在训练前缓冲数据。此类 dataset.global_shuffle(fleet) exe = fluid.Executor(fluid.CPUPlace()) exe.run(fluid.default_startup_program()) - exe.train_from_dataset(fluid.default_main_program(), dataset)dataset.release_memory() + exe.train_from_dataset(fluid.default_main_program(), dataset) dataset.release_memory() .. py:method:: get_memory_data_size(fleet=None) diff --git a/doc/fluid/api_cn/executor_cn/Executor_cn.rst b/doc/fluid/api_cn/executor_cn/Executor_cn.rst index d5591a863a1d91937adb2ad63334fb063d43527e..1ea7c1ac2ef4af47c4453650ea659ae0d75d2dd6 100644 --- a/doc/fluid/api_cn/executor_cn/Executor_cn.rst +++ b/doc/fluid/api_cn/executor_cn/Executor_cn.rst @@ -211,7 +211,7 @@ infer_from_dataset的文档与train_from_dataset几乎完全相同，只是在 filelist = [] # 您可以设置您自己的filelist，如filelist = ["dataA.txt"] dataset.set_filelist(filelist) exe.run(fluid.default_startup_program()) - exe.infer_from_dataset(program=fluid.default_main_program(), + exe.train_from_dataset(program=fluid.default_main_program(), dataset=dataset) diff --git a/doc/fluid/api_cn/fluid_cn/DataFeeder_cn.rst b/doc/fluid/api_cn/fluid_cn/DataFeeder_cn.rst index 083390a8fd83e290528abf5c3cb676238a399747..a00aadc7dbf29270651b631bb8f03e40368e345b 100644 --- a/doc/fluid/api_cn/fluid_cn/DataFeeder_cn.rst +++ b/doc/fluid/api_cn/fluid_cn/DataFeeder_cn.rst @@ -78,7 +78,7 @@ reader通常返回一个minibatch条目列表。在列表中每一条目都是 for data in reader(): outs = exe.run(program=main_program, feed=feeder.feed(data), - fetch_list=[out])) + fetch_list=[out]) .. py:method:: feed(iterable) diff --git a/doc/fluid/api_cn/fluid_cn/ParallelExecutor_cn.rst b/doc/fluid/api_cn/fluid_cn/ParallelExecutor_cn.rst index bd7102dd0871a4a209ea9dcc9616f4adadd916b8..2d8ee05a819c0ef8d660480508dc976adc18f91d 100644 --- a/doc/fluid/api_cn/fluid_cn/ParallelExecutor_cn.rst +++ b/doc/fluid/api_cn/fluid_cn/ParallelExecutor_cn.rst @@ -190,6 +190,7 @@ ParallelExecutor loss = fluid.layers.mean(hidden) place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() + exe = fluid.Executor(place) exe.run(startup_program) parallel_exe = fluid.ParallelExecutor(use_cuda=use_cuda, diff --git a/doc/fluid/api_cn/fluid_cn/ParamAttr_cn.rst b/doc/fluid/api_cn/fluid_cn/ParamAttr_cn.rst index 192a8f5bc8931680dbb555bf17ff6553c01d5dcd..4a59bcb8b851d370191d89f5aef4aeebc19f0603 100644 --- a/doc/fluid/api_cn/fluid_cn/ParamAttr_cn.rst +++ b/doc/fluid/api_cn/fluid_cn/ParamAttr_cn.rst @@ -26,8 +26,9 @@ ParamAttr w_param_attrs = fluid.ParamAttr(name="fc_weight", learning_rate=0.5, - regularizer=fluid.L2Decay(1.0), + regularizer=fluid.regularizer.L2Decay(1.0), trainable=True) + x = fluid.layers.data(name='X', shape=[1], dtype='float32') y_predict = fluid.layers.fc(input=x, size=10, param_attr=w_param_attrs) diff --git a/doc/fluid/api_cn/initializer_cn/NormalInitializer_cn.rst b/doc/fluid/api_cn/initializer_cn/NormalInitializer_cn.rst index fce83359e7d1d38dddd99fffd688f17ea0872761..51bb56952ab27e99288b6fa163f138b505513a35 100644 --- a/doc/fluid/api_cn/initializer_cn/NormalInitializer_cn.rst +++ b/doc/fluid/api_cn/initializer_cn/NormalInitializer_cn.rst @@ -19,6 +19,6 @@ NormalInitializer 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) + param_attr=fluid.initializer.Normal(loc=0.0, scale=2.0)) diff --git a/doc/fluid/api_cn/layers_cn/adaptive_pool3d_cn.rst b/doc/fluid/api_cn/layers_cn/adaptive_pool3d_cn.rst index 8c3c820260a01868c9411730e816282230411440..a78f76a8c1dbd8d26362abc84f5ba78ef22c67fd 100644 --- a/doc/fluid/api_cn/layers_cn/adaptive_pool3d_cn.rst +++ b/doc/fluid/api_cn/layers_cn/adaptive_pool3d_cn.rst @@ -71,7 +71,7 @@ pooling3d操作根据输入 ``input`` ，``pool_size`` ， ``pool_type`` 参数 data = fluid.layers.data( name='data', shape=[3, 32, 32, 32], dtype='float32') - pool_out, mask = fluid.layers.adaptive_pool3d( + pool_out = fluid.layers.adaptive_pool3d( input=data, pool_size=[3, 3, 3], pool_type='avg') diff --git a/doc/fluid/api_cn/layers_cn/argmax_cn.rst b/doc/fluid/api_cn/layers_cn/argmax_cn.rst index 4ddf2498bc6c70bc958b3aaa7785b51f2cff09d3..74132b83e1530e876c5f76ece21f4ea755b3a7d1 100644 --- a/doc/fluid/api_cn/layers_cn/argmax_cn.rst +++ b/doc/fluid/api_cn/layers_cn/argmax_cn.rst @@ -23,8 +23,8 @@ argmax import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") - out = fluid.layers.argmax(x=in, axis=0) - out = fluid.layers.argmax(x=in, axis=-1) + out = fluid.layers.argmax(x, axis=0) + out = fluid.layers.argmax(x, axis=-1) diff --git a/doc/fluid/api_cn/layers_cn/argmin_cn.rst b/doc/fluid/api_cn/layers_cn/argmin_cn.rst index 4eb4feaf91a65e248ca0845f35f6a9ff6752ae9e..b4efc5889858e1ed1b80dc938115498e6538bd53 100644 --- a/doc/fluid/api_cn/layers_cn/argmin_cn.rst +++ b/doc/fluid/api_cn/layers_cn/argmin_cn.rst @@ -23,8 +23,8 @@ argmin import paddle.fluid as fluid x = fluid.layers.data(name="x", shape=[3, 4], dtype="float32") - out = fluid.layers.argmin(x=in, axis=0) - out = fluid.layers.argmin(x=in, axis=-1) + out = fluid.layers.argmin(x, axis=0) + out = fluid.layers.argmin(x, axis=-1) diff --git a/doc/fluid/api_cn/layers_cn/auc_cn.rst b/doc/fluid/api_cn/layers_cn/auc_cn.rst index ccc25bd9e2d47f1115f119455c354f5bf0edff45..f49683671bbd0cbaa5777243139e063353d6d7bd 100644 --- a/doc/fluid/api_cn/layers_cn/auc_cn.rst +++ b/doc/fluid/api_cn/layers_cn/auc_cn.rst @@ -37,7 +37,7 @@ auc data = fluid.layers.data(name="data", shape=[32, 32], dtype="float32") label = fluid.layers.data(name="label", shape=[1], dtype="int32") predict = fluid.layers.fc(input=data, size=2) - auc_out=fluid.layers.auc(input=prediction, label=label) + auc_out=fluid.layers.auc(input=predict, label=label) diff --git a/doc/fluid/api_cn/layers_cn/beam_search_cn.rst b/doc/fluid/api_cn/layers_cn/beam_search_cn.rst index 052f01bb38c2f167685db64f8e27c64d8bb37936..7bb2e241be96dc5638463d601732c53dfe6a7986 100644 --- a/doc/fluid/api_cn/layers_cn/beam_search_cn.rst +++ b/doc/fluid/api_cn/layers_cn/beam_search_cn.rst @@ -54,7 +54,7 @@ beam_search name='probs', shape=[10000], dtype='float32') topk_scores, topk_indices = fluid.layers.topk(probs, k=beam_size) accu_scores = fluid.layers.elementwise_add( - x=fluid.layers.log(x=topk_scores)), + x=fluid.layers.log(x=topk_scores), y=fluid.layers.reshape( pre_scores, shape=[-1]), axis=0) diff --git a/doc/fluid/api_cn/layers_cn/box_clip_cn.rst b/doc/fluid/api_cn/layers_cn/box_clip_cn.rst index b3e6bd80c12aa2e678562c09de30422ff84a68a2..34557712c1a531ff3fed990403d9a118ab73a2e4 100644 --- a/doc/fluid/api_cn/layers_cn/box_clip_cn.rst +++ b/doc/fluid/api_cn/layers_cn/box_clip_cn.rst @@ -41,7 +41,7 @@ box_clip name='boxes', shape=[8, 4], dtype='float32', lod_level=1) im_info = fluid.layers.data(name='im_info', shape=[3]) out = fluid.layers.box_clip( - input=boxes, im_info=im_info, inplace=True) + input=boxes, im_info=im_info) diff --git a/doc/fluid/api_cn/layers_cn/brelu_cn.rst b/doc/fluid/api_cn/layers_cn/brelu_cn.rst index f9339245d519a41121d13f6a32c2c2b3e77110b6..7394286e58ab1a71cef1902420e52412ccbd0bf8 100644 --- a/doc/fluid/api_cn/layers_cn/brelu_cn.rst +++ b/doc/fluid/api_cn/layers_cn/brelu_cn.rst @@ -22,7 +22,7 @@ BRelu 激活函数 .. code-block:: python import paddle.fluid as fluid - x = fluid.layers.data(name="x", shape=[2,3,16,16], dtype=”float32”) + 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) diff --git a/doc/fluid/api_cn/layers_cn/concat_cn.rst b/doc/fluid/api_cn/layers_cn/concat_cn.rst index f482dc9c6a3b2c7dd4715352078cb0cee8f906b9..e863fe5db6344e5265b28759c2237b4a31ee5c5e 100644 --- a/doc/fluid/api_cn/layers_cn/concat_cn.rst +++ b/doc/fluid/api_cn/layers_cn/concat_cn.rst @@ -27,7 +27,7 @@ concat b = fluid.layers.data(name='b', shape=[2, 3], dtype='float32') c = fluid.layers.data(name='c', shape=[2, 2], dtype='float32') d = fluid.layers.data(name='d', shape=[2, 5], dtype='float32') - out = fluid.layers.concat(input=[Efirst, Esecond, Ethird, Efourth]) + out = fluid.layers.concat(input=[a, b, c, d], axis=2) diff --git a/doc/fluid/api_cn/layers_cn/create_parameter_cn.rst b/doc/fluid/api_cn/layers_cn/create_parameter_cn.rst index 4eb381c69bb4bd2c487d5bbb53cd35c9fe288460..e4faa6c17eaa7073ee14d7026554fa4c589ed57e 100644 --- a/doc/fluid/api_cn/layers_cn/create_parameter_cn.rst +++ b/doc/fluid/api_cn/layers_cn/create_parameter_cn.rst @@ -24,7 +24,7 @@ create_parameter import paddle.fluid as fluid import paddle.fluid.layers as layers - W = fluid.layers.create_parameter(shape=[784, 200], dtype='float32') + W = layers.create_parameter(shape=[784, 200], dtype='float32') diff --git a/doc/fluid/api_cn/layers_cn/create_py_reader_by_data_cn.rst b/doc/fluid/api_cn/layers_cn/create_py_reader_by_data_cn.rst index 45d2b401e3d953f79770755df665423eaa6e4b93..ccc96f8720897bf0ffd4873693f0d9dc42ca0381 100644 --- a/doc/fluid/api_cn/layers_cn/create_py_reader_by_data_cn.rst +++ b/doc/fluid/api_cn/layers_cn/create_py_reader_by_data_cn.rst @@ -33,8 +33,8 @@ create_py_reader_by_data loss = fluid.layers.cross_entropy(input=predict, label=label) return fluid.layers.mean(loss) - image = fluid.layers.data(name='image', shape=[1, 28, 28], dtypes='float32') - label = fluid.layers.data(name='label', shape=[1], dtypes='int64') + image = fluid.layers.data(name='image', shape=[1, 28, 28], dtype='float32') + label = fluid.layers.data(name='label', shape=[1], dtype='int64') reader = fluid.layers.create_py_reader_by_data(capacity=64, feed_list=[image, label]) reader.decorate_paddle_reader( diff --git a/doc/fluid/api_cn/layers_cn/crop_cn.rst b/doc/fluid/api_cn/layers_cn/crop_cn.rst index 113477ee7342e3dc50899d23e66848dec9cf5698..32c145b213fcc5f117a4958bbbafbf9138e0e752 100644 --- a/doc/fluid/api_cn/layers_cn/crop_cn.rst +++ b/doc/fluid/api_cn/layers_cn/crop_cn.rst @@ -63,7 +63,7 @@ crop ## or z = fluid.layers.data(name="z", shape=[3, 5], dtype="float32") - crop = fluid.layers.crop(z, shape=[2, 3]) + crop = fluid.layers.crop(z, shape=[-1, 2, 3]) diff --git a/doc/fluid/api_cn/layers_cn/gaussian_random_cn.rst b/doc/fluid/api_cn/layers_cn/gaussian_random_cn.rst index 4e91ef8a934657c6a36cbddc89246325a1d5b1dc..9fbdaf15752fc1fdbc4f227e50f144981d94ac9c 100644 --- a/doc/fluid/api_cn/layers_cn/gaussian_random_cn.rst +++ b/doc/fluid/api_cn/layers_cn/gaussian_random_cn.rst @@ -26,7 +26,7 @@ gaussian_random算子。 import paddle.fluid as fluid import paddle.fluid.layers as layers - out = fluid.layers.gaussian_random(shape=[20, 30]) + out = layers.gaussian_random(shape=[20, 30]) diff --git a/doc/fluid/api_cn/layers_cn/grid_sampler_cn.rst b/doc/fluid/api_cn/layers_cn/grid_sampler_cn.rst index cd6620f6ae0736822ce25fb768843015d32855ab..3ffbc5e570df32b2eff4f4886e518975fa7e3b9a 100644 --- a/doc/fluid/api_cn/layers_cn/grid_sampler_cn.rst +++ b/doc/fluid/api_cn/layers_cn/grid_sampler_cn.rst @@ -63,9 +63,9 @@ step 2： import paddle.fluid as fluid - x = fluid.layers.data(name='x', shape=[3, 10, 32, 32], dtype='float32') - theta = fluid.layers.data(name='theta', shape=[3, 2, 3], dtype='float32') - grid = fluid.layers.affine_grid(theta=theta, out_shape=[3, 10, 32, 32]}) + x = fluid.layers.data(name='x', shape=[10, 32, 32], dtype='float32') + theta = fluid.layers.data(name='theta', shape=[2, 3], dtype='float32') + grid = fluid.layers.affine_grid(theta=theta, out_shape=[3, 10, 32, 32]) out = fluid.layers.grid_sampler(x=x, grid=grid) diff --git a/doc/fluid/api_cn/layers_cn/inverse_time_decay_cn.rst b/doc/fluid/api_cn/layers_cn/inverse_time_decay_cn.rst index 2d3c081598233f252002ec50141161ecea251462..c3387cbd4d09bc343fc990e9eee408f0c1ad7241 100644 --- a/doc/fluid/api_cn/layers_cn/inverse_time_decay_cn.rst +++ b/doc/fluid/api_cn/layers_cn/inverse_time_decay_cn.rst @@ -38,7 +38,7 @@ inverse_time_decay decay_steps=10000, decay_rate=0.5, staircase=True)) - sgd_optimizer.minimize(avg_cost) + diff --git a/doc/fluid/api_cn/layers_cn/label_smooth_cn.rst b/doc/fluid/api_cn/layers_cn/label_smooth_cn.rst index fb551d7e77c86742ae6fabbbcf783442d6986e9e..b9da0d0f6ed93c63859c0d4b4f033ae35acd0d12 100644 --- a/doc/fluid/api_cn/layers_cn/label_smooth_cn.rst +++ b/doc/fluid/api_cn/layers_cn/label_smooth_cn.rst @@ -37,9 +37,9 @@ label_smooth import paddle.fluid as fluid import paddle.fluid.layers as layers - label = fluid.layers.data(name="label", shape=[1], dtype="float32") - one_hot_label = fluid.layers.one_hot(input=label, depth=10) - smooth_label = fluid.layers.label_smooth( + label = layers.data(name="label", shape=[1], dtype="float32") + one_hot_label = layers.one_hot(input=label, depth=10) + smooth_label = layers.label_smooth( label=one_hot_label, epsilon=0.1, dtype="float32") diff --git a/doc/fluid/api_cn/layers_cn/lstm_cn.rst b/doc/fluid/api_cn/layers_cn/lstm_cn.rst index 58610ea1b469cd61866236b1bef5300b11915ad3..a99cc7affd564cecd0f8c4a533ecbfb48db336ae 100644 --- a/doc/fluid/api_cn/layers_cn/lstm_cn.rst +++ b/doc/fluid/api_cn/layers_cn/lstm_cn.rst @@ -71,7 +71,7 @@ sigmoid的计算公式为： :math:`sigmoid(x) = 1 / (1 + e^{-x})` 。 init_h = layers.fill_constant( [num_layers, batch_size, hidden_size], 'float32', 0.0 ) init_c = layers.fill_constant( [num_layers, batch_size, hidden_size], 'float32', 0.0 ) - rnn_out, last_h, last_c = fluid.layers.lstm(emb, init_h, init_c, max_len, hidden_size, num_layers, dropout_prob=dropout_prob) + rnn_out, last_h, last_c = layers.lstm(emb, init_h, init_c, max_len, hidden_size, num_layers, dropout_prob=dropout_prob) diff --git a/doc/fluid/api_cn/layers_cn/lstm_unit_cn.rst b/doc/fluid/api_cn/layers_cn/lstm_unit_cn.rst index a57623a8faa865ea1b45a0a8f4e0e93b2bedefef..e0858f17496e123b849fe2feb04d66a996d42fc4 100644 --- a/doc/fluid/api_cn/layers_cn/lstm_unit_cn.rst +++ b/doc/fluid/api_cn/layers_cn/lstm_unit_cn.rst @@ -60,8 +60,8 @@ lstm单元的输入包括 :math:`x_{t}` ， :math:`h_{t-1}` 和 :math:`c_{t-1}` pre_cell = fluid.layers.data(name='pre_cell', shape=[hidden_dim], dtype='float32') hidden = fluid.layers.lstm_unit( x_t=x, - hidden_t_prev=prev_hidden, - cell_t_prev=prev_cell) + hidden_t_prev=pre_hidden, + cell_t_prev=pre_cell) diff --git a/doc/fluid/api_cn/layers_cn/mean_iou_cn.rst b/doc/fluid/api_cn/layers_cn/mean_iou_cn.rst index 90ab9852c89ff594d30fd50e4c448bc51bc4f8ca..c41b1617ee23e7e86b4661da84e67941fce477a9 100644 --- a/doc/fluid/api_cn/layers_cn/mean_iou_cn.rst +++ b/doc/fluid/api_cn/layers_cn/mean_iou_cn.rst @@ -33,7 +33,7 @@ mean_iou import paddle.fluid as fluid predict = fluid.layers.data(name='predict', shape=[3, 32, 32]) label = fluid.layers.data(name='label', shape=[1]) - iou, wrongs, corrects = fluid.layers.mean_iou(predict, label, num_classes) + iou, wrongs, corrects = fluid.layers.mean_iou(predict, label, num_classes=5) diff --git a/doc/fluid/api_cn/layers_cn/py_reader_cn.rst b/doc/fluid/api_cn/layers_cn/py_reader_cn.rst index 4f163bb576b0e237f971c80b0255c0768b8647d8..f812263fe136420f2e084b8a59b5fb31ee5ab1cf 100644 --- a/doc/fluid/api_cn/layers_cn/py_reader_cn.rst +++ b/doc/fluid/api_cn/layers_cn/py_reader_cn.rst @@ -50,7 +50,7 @@ py_reader fluid.Executor(fluid.CUDAPlace(0)).run(fluid.default_startup_program()) - exe = fluid.ParallelExecutor(use_cuda=True, loss_name=loss.name) + exe = fluid.ParallelExecutor(use_cuda=True) for epoch_id in range(10): reader.start() try: diff --git a/doc/fluid/api_cn/layers_cn/rpn_target_assign_cn.rst b/doc/fluid/api_cn/layers_cn/rpn_target_assign_cn.rst index 1febde8469331beff9b1151ef0efd814551d2962..74c2761e006a3d85437ffc15ddd1b4a1ef31799a 100644 --- a/doc/fluid/api_cn/layers_cn/rpn_target_assign_cn.rst +++ b/doc/fluid/api_cn/layers_cn/rpn_target_assign_cn.rst @@ -45,14 +45,16 @@ rpn_target_assign .. code-block:: python import paddle.fluid as fluid - bbox_pred = fluid.layers.data(name=’bbox_pred’, shape=[100, 4], - append_batch_size=False, dtype=’float32’) - cls_logits = fluid.layers.data(name=’cls_logits’, shape=[100, 1], - append_batch_size=False, dtype=’float32’) - anchor_box = fluid.layers.data(name=’anchor_box’, shape=[20, 4], - append_batch_size=False, dtype=’float32’) - gt_boxes = fluid.layers.data(name=’gt_boxes’, shape=[10, 4], - append_batch_size=False, dtype=’float32’) + bbox_pred = fluid.layers.data(name='bbox_pred', shape=[100, 4], + append_batch_size=False, dtype='float32') + cls_logits = fluid.layers.data(name='cls_logits', shape=[100, 1], + append_batch_size=False, dtype='float32') + anchor_box = fluid.layers.data(name='anchor_box', shape=[20, 4], + append_batch_size=False, dtype='float32') + anchor_var = fluid.layers.data(name='anchor_var', shape=[20, 4], + append_batch_size=False, dtype='float32') + gt_boxes = fluid.layers.data(name='gt_boxes', shape=[10, 4], + append_batch_size=False, dtype='float32') is_crowd = fluid.layers.data(name='is_crowd', shape=[1], append_batch_size=False, dtype='float32') im_info = fluid.layers.data(name='im_infoss', shape=[1, 3], diff --git a/doc/fluid/api_cn/layers_cn/sequence_expand_cn.rst b/doc/fluid/api_cn/layers_cn/sequence_expand_cn.rst index 3fd1e8a8e6b771bb3f7f63d7753b7f09ec5df378..ba8981575b60bffa69106d259c9e7f8b3067b28a 100644 --- a/doc/fluid/api_cn/layers_cn/sequence_expand_cn.rst +++ b/doc/fluid/api_cn/layers_cn/sequence_expand_cn.rst @@ -62,7 +62,7 @@ sequence_expand x = fluid.layers.data(name='x', shape=[10], dtype='float32') y = fluid.layers.data(name='y', shape=[10, 20], dtype='float32', lod_level=1) - out = fluid.layers.sequence_expand(x=x, y=y, ref_level=0) + out = layers.sequence_expand(x=x, y=y, ref_level=0) diff --git a/doc/fluid/api_cn/layers_cn/soft_relu_cn.rst b/doc/fluid/api_cn/layers_cn/soft_relu_cn.rst index 0ad8fff24f7fad60daceb9d9f60a2230dbd3843d..c9e678cc61f1cd338638b57944d1ac602464f857 100644 --- a/doc/fluid/api_cn/layers_cn/soft_relu_cn.rst +++ b/doc/fluid/api_cn/layers_cn/soft_relu_cn.rst @@ -20,7 +20,7 @@ SoftRelu 激活函数 import paddle.fluid as fluid - x = fluid.layers.data(name=”x”, shape=[2,3,16,16], dtype=”float32”) + x = fluid.layers.data(name="x", shape=[3,16,16], dtype="float32") y = fluid.layers.soft_relu(x, threshold=20.0) diff --git a/doc/fluid/api_cn/layers_cn/split_cn.rst b/doc/fluid/api_cn/layers_cn/split_cn.rst index e6004df3e3ecef16e4676f30c34cf37fd492deb6..ad7fca6094155389428241f4207e3be739421fe4 100644 --- a/doc/fluid/api_cn/layers_cn/split_cn.rst +++ b/doc/fluid/api_cn/layers_cn/split_cn.rst @@ -32,7 +32,7 @@ split # x1.shape [-1, 3, 3, 5] # x2.shape [-1, 3, 3, 5] - x0, x1, x2 = fluid.layers.split(input, num_or_sections=[2, 3, 4], dim=2) + x0, x1, x2 = fluid.layers.split(input, num_or_sections=3, dim=2) # x0.shape [-1, 3, 2, 5] # x1.shape [-1, 3, 3, 5] # x2.shape [-1, 3, 4, 5] diff --git a/doc/fluid/api_cn/layers_cn/squeeze_cn.rst b/doc/fluid/api_cn/layers_cn/squeeze_cn.rst index 8b3e651324aa85d31bd5def0aa0af811718700b0..8b882cb858a184b31e9ceed70a4fe5942f8b2c45 100644 --- a/doc/fluid/api_cn/layers_cn/squeeze_cn.rst +++ b/doc/fluid/api_cn/layers_cn/squeeze_cn.rst @@ -40,8 +40,8 @@ squeeze import paddle.fluid as fluid import paddle.fluid.layers as layers - x = fluid.layers.data(name='x', shape=[5, 1, 10]) - y = fluid.layers.sequeeze(input=x, axes=[1]) + x = layers.data(name='x', shape=[5, 1, 10]) + y = layers.squeeze(input=x, axes=[1]) diff --git a/doc/fluid/api_cn/layers_cn/sum_cn.rst b/doc/fluid/api_cn/layers_cn/sum_cn.rst index 08e13c13449e4c66d54bfe2564b3547f4df51700..677266021c3cb75aa1510f5040f96e55e4dda89d 100644 --- a/doc/fluid/api_cn/layers_cn/sum_cn.rst +++ b/doc/fluid/api_cn/layers_cn/sum_cn.rst @@ -23,9 +23,9 @@ sum算子。 import paddle.fluid as fluid import paddle.fluid.layers as layers - input0 = fluid.layers.data(name="input0", shape=[13, 11], dtype='float32') + input0 = layers.data(name="input0", shape=[13, 11], dtype='float32') input1 = layers.data(name="input1", shape=[13, 11], dtype='float32') - out = fluid.layers.sum([input0,input1]) + out = layers.sum([input0,input1]) diff --git a/doc/fluid/api_cn/layers_cn/topk_cn.rst b/doc/fluid/api_cn/layers_cn/topk_cn.rst index 15367e65c2a97add03f847a75ece11e846b1fe90..0cb245dff4c4d93bfb004718d4643fe63d4c0db9 100644 --- a/doc/fluid/api_cn/layers_cn/topk_cn.rst +++ b/doc/fluid/api_cn/layers_cn/topk_cn.rst @@ -49,7 +49,7 @@ topk 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 = fluid.layers.topk(input, k=5) + top5_values, top5_indices = layers.topk(input, k=5) diff --git a/doc/fluid/api_cn/layers_cn/uniform_random_batch_size_like_cn.rst b/doc/fluid/api_cn/layers_cn/uniform_random_batch_size_like_cn.rst index 84f1995e3346111157a0c97db37cbe84271b25c1..e2149af5cb941adf199772eb3217f48e7f6225b5 100644 --- a/doc/fluid/api_cn/layers_cn/uniform_random_batch_size_like_cn.rst +++ b/doc/fluid/api_cn/layers_cn/uniform_random_batch_size_like_cn.rst @@ -31,8 +31,8 @@ uniform_random_batch_size_like算子。 import paddle.fluid as fluid import paddle.fluid.layers as layers - input = fluid.layers.data(name="input", shape=[13, 11], dtype='float32') - out = fluid.layers.uniform_random_batch_size_like(input, [-1, 11]) + input = layers.data(name="input", shape=[13, 11], dtype='float32') + out = layers.uniform_random_batch_size_like(input, [-1, 11]) diff --git a/doc/fluid/api_cn/layers_cn/unsqueeze_cn.rst b/doc/fluid/api_cn/layers_cn/unsqueeze_cn.rst index 508a8ebf0a47b67e032a575c09ba46803142e6c4..40409df734e926fca3470c5f3c257638adfd6f62 100644 --- a/doc/fluid/api_cn/layers_cn/unsqueeze_cn.rst +++ b/doc/fluid/api_cn/layers_cn/unsqueeze_cn.rst @@ -25,7 +25,7 @@ unsqueeze import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[5, 10]) - y = fluid.layers.unsequeeze(input=x, axes=[1]) + y = fluid.layers.unsqueeze(input=x, axes=[1]) diff --git a/doc/fluid/api_cn/layers_cn/yolov3_loss_cn.rst b/doc/fluid/api_cn/layers_cn/yolov3_loss_cn.rst index 5dfcbd2fc2a5d91dbc2fc440d63e76b615032e04..4cea1be6ab99ce51044c3622701a34a3e08f5f59 100644 --- a/doc/fluid/api_cn/layers_cn/yolov3_loss_cn.rst +++ b/doc/fluid/api_cn/layers_cn/yolov3_loss_cn.rst @@ -86,9 +86,9 @@ yolov3_loss import paddle.fluid as fluid x = fluid.layers.data(name='x', shape=[255, 13, 13], dtype='float32') - gt_box = fluid.layers.data(name='gtbox', shape=[6, 4], dtype='float32') - gt_label = fluid.layers.data(name='gtlabel', shape=[6], dtype='int32') - gt_score = fluid.layers.data(name='gtscore', shape=[6], 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') + gt_score = fluid.layers.data(name='gt_score', shape=[6], dtype='float32') anchors = [10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326] anchor_mask = [0, 1, 2] loss = fluid.layers.yolov3_loss(x=x, gt_box=gt_box, gt_label=gt_label, diff --git a/doc/fluid/api_cn/metrics_cn/EditDistance_cn.rst b/doc/fluid/api_cn/metrics_cn/EditDistance_cn.rst index c7900c401e3cbb1e03fa3fc8ab69a459cb4c784d..0846fc4bc976adab35727094aee066e03bd57a00 100644 --- a/doc/fluid/api_cn/metrics_cn/EditDistance_cn.rst +++ b/doc/fluid/api_cn/metrics_cn/EditDistance_cn.rst @@ -31,7 +31,6 @@ EditDistance seq_num_batch0 = batch_size distance_evaluator.update(edit_distances_batch0, seq_num_batch0) - distance, instance_error = distance_evaluator.eval() avg_distance, wrong_instance_ratio = distance_evaluator.eval() print("the average edit distance for batch0 is %.2f and the wrong instance ratio is %.2f " % (avg_distance, wrong_instance_ratio)) edit_distances_batch1 = np.random.randint(low = 0, high = 10, size = (batch_size, 1))