Refine api doc

paddle/fluid/API.spec

@@ -146,7 +146,7 @@ paddle.fluid.layers.pad (ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], va
 paddle.fluid.layers.pad_constant_like (ArgSpec(args=['x', 'y', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None)), ('document', 'd2e1f45fef51b2c214e3f2aa8976c46c'))
 paddle.fluid.layers.label_smooth (ArgSpec(args=['label', 'prior_dist', 'epsilon', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 0.1, 'float32', None)), ('document', '70c113658102a11cc5d8e3d45145737a'))
 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', 'c317aa595deb31649083c8faa91cdb97'))
-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', '12c5bbb8b38c42e623fbc47611d766e1'))
+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.dice_loss (ArgSpec(args=['input', 'label', 'epsilon'], varargs=None, keywords=None, defaults=(1e-05,)), ('document', '1ba0508d573f65feecf3564dce22aa1d'))
 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', 'd1b08c11bb9277386fcf6ae70b6622d1'))
 paddle.fluid.layers.image_resize_short (ArgSpec(args=['input', 'out_short_len', 'resample'], varargs=None, keywords=None, defaults=('BILINEAR',)), ('document', '06211aefc50c5a3e940d7204d859cdf7'))
@@ -206,7 +206,7 @@ paddle.fluid.layers.clip_by_norm (ArgSpec(args=['x', 'max_norm', 'name'], vararg
 paddle.fluid.layers.mean (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd638d915195ce86a8d7963b81110d4c8'))
 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', 'ccd37fa6b53f074adbfb732d738c4c2d'))
 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', '891870d069a6aea746d34cc53b61690c'))
+paddle.fluid.layers.maxout (ArgSpec(args=['x', 'groups', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '71426e02d240d0daedae81a02ca1c191'))
 paddle.fluid.layers.space_to_depth (ArgSpec(args=['x', 'blocksize', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a9221eaef53884a00654e028551b78e2'))
 paddle.fluid.layers.affine_grid (ArgSpec(args=['theta', 'out_shape', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '51def402b8910e163cbace9d0c0526ed'))
 paddle.fluid.layers.sequence_reverse (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '77a6d80aa5551ca70324fc975c44507f'))
@@ -340,7 +340,7 @@ paddle.fluid.layers.detection_output (ArgSpec(args=['loc', 'scores', 'prior_box'
 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', '6d5028fd09d01ab82d296adc0ea95aee'))
 paddle.fluid.layers.detection_map (ArgSpec(args=['detect_res', 'label', 'class_num', 'background_label', 'overlap_threshold', 'evaluate_difficult', 'has_state', 'input_states', 'out_states', 'ap_version'], varargs=None, keywords=None, defaults=(0, 0.3, True, None, None, None, 'integral')), ('document', '1467d91b50c22cd52103b4aa1ee9d0a1'))
 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', '1dddef3eb4b3cbd4df8e03ac480dbf97'))
-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', '23337cc57bbf5be73884b6bd0f849603'))
+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', '82b2aefeeb1b706bc4afec70928a259a'))
 paddle.fluid.layers.roi_perspective_transform (ArgSpec(args=['input', 'rois', 'transformed_height', 'transformed_width', 'spatial_scale'], varargs=None, keywords=None, defaults=(1.0,)), ('document', '5761f9ed83654314416e24372b33bb84'))
 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'], varargs=None, keywords=None, defaults=(256, 0.25, 0.25, 0.5, 0.0, [0.1, 0.1, 0.2, 0.2], None, True)), ('document', '87863717edeb7fe87a1268976cbc015d'))
 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', '57ab49f3f324f310b7eed322e7c1057a'))
@@ -350,10 +350,10 @@ paddle.fluid.layers.box_coder (ArgSpec(args=['prior_box', 'prior_box_var', 'targ
 paddle.fluid.layers.polygon_box_transform (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0e5ac2507723a0b5adec473f9556799b'))
 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.yolo_box (ArgSpec(args=['x', 'img_size', 'anchors', 'class_num', 'conf_thresh', 'downsample_ratio', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '5566169a5ab993d177792c023c7fb340'))
-paddle.fluid.layers.box_clip (ArgSpec(args=['input', 'im_info', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '397e9e02b451d99c56e20f268fa03f2e'))
+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.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', '005a5ae47d6c8fff721931d69d072b9f'))
+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.accuracy (ArgSpec(args=['input', 'label', 'k', 'correct', 'total'], varargs=None, keywords=None, defaults=(1, None, None)), ('document', '9808534c12c5e739a10f73ebb0b4eafd'))
 paddle.fluid.layers.auc (ArgSpec(args=['input', 'label', 'curve', 'num_thresholds', 'topk', 'slide_steps'], varargs=None, keywords=None, defaults=('ROC', 4095, 1, 1)), ('document', 'e0e95334fce92d16c2d9db6e7caffc47'))
 paddle.fluid.layers.exponential_decay (ArgSpec(args=['learning_rate', 'decay_steps', 'decay_rate', 'staircase'], varargs=None, keywords=None, defaults=(False,)), ('document', '98a5050bee8522fcea81aa795adaba51'))

paddle/fluid/operators/maxout_op.cc

@@ -36,25 +36,23 @@ class MaxOutOpMaker : public framework::OpProtoAndCheckerMaker {
               "width of feature.");
     AddAttr<int>(
         "groups",
-        R"DOC("Specifies how many groups the input tensor will be split"
+        "(int),"
+        "Specifies how many groups the input tensor will be split"
         "in the channel dimension. And the number of output channel is "
-        "the number of channels divided by groups.."
-        )DOC");
+        "the number of channels divided by groups.");
     AddComment(R"DOC(
 MaxOut Operator.
 
 Assumed the input shape is (N, Ci, H, W).
 The output shape is (N, Co, H, W).
 Then $Co = Ci / groups$ and the operator formula is as follows:
 
-$$
-y_{si+j} = \max_k x_{gsi + sk + j} \\
-g = groups \\
-s = \frac{input.size}{num\_channels} \\
-0 \le i < \frac{num\_channels}{groups} \\
-0 \le j < s \\
-0 \le k < groups
-$$
+$$ y_{si+j} = \max_{k} x_{gsi + sk + j} $$
+$$ g = groups $$
+$$ s = \\frac{input.size}{num\\_channels} $$
+$$ 0 \\le i < \\frac{num\\_channels}{groups} $$
+$$ 0 \\le j < s $$
+$$ 0 \\le k < groups $$
 
 Please refer to Paper:
   - Maxout Networks: http://www.jmlr.org/proceedings/papers/v28/goodfellow13.pdf

python/paddle/fluid/layers/detection.py

@@ -1747,7 +1747,8 @@ def anchor_generator(input,
 
         .. code-block:: python
 
-            anchor, var = anchor_generator(
+            conv1 = fluid.layers.data(name='conv1', shape=[48, 16, 16], dtype='float32')
+            anchor, var = fluid.layers.anchor_generator(
                 input=conv1,
                 anchor_sizes=[64, 128, 256, 512],
                 aspect_ratios=[0.5, 1.0, 2.0],
@@ -2198,10 +2199,10 @@ def box_clip(input, im_info, name=None):
         .. code-block:: python
 
             boxes = fluid.layers.data(
-                name='data', shape=[8, 4], dtype='float32', lod_level=1)
+                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)
     """
 
     helper = LayerHelper("box_clip", **locals())
@@ -2431,13 +2432,14 @@ def box_decoder_and_assign(prior_box,
         .. code-block:: python
 
             pb = fluid.layers.data(
-                name='prior_box', shape=[20, 4], dtype='float32')
+                name='prior_box', shape=[4], dtype='float32')
             pbv = fluid.layers.data(
-                name='prior_box_var', shape=[1, 4], dtype='float32')
+                name='prior_box_var', shape=[4], 
+                dtype='float32', append_batch_size=False)
             loc = fluid.layers.data(
-                name='target_box', shape=[20, 4*81], dtype='float32')
+                name='target_box', shape=[4*81], dtype='float32')
             scores = fluid.layers.data(
-                name='scores', shape=[20, 81], dtype='float32')
+                name='scores', shape=[81], dtype='float32')
             decoded_box, output_assign_box = fluid.layers.box_decoder_and_assign(
                 pb, pbv, loc, scores, 4.135)
 

python/paddle/fluid/layers/nn.py

@@ -7088,6 +7088,10 @@ def roi_align(input,
     Examples:
         .. code-block:: python
 
+            x = fluid.layers.data(
+                name='data', shape=[256, 32, 32], dtype='float32')
+            rois = fluid.layers.data(
+                name='rois', shape=[4], dtype='float32')
             align_out = fluid.layers.roi_align(input=x,
                                                rois=rois,
                                                pooled_height=7,
@@ -9862,6 +9866,15 @@ def maxout(x, groups, name=None):
 
     Returns:
         out(${out_type}): ${out_comment}
+
+    Examples:
+        .. code-block:: python
+
+            input = fluid.layers.data(
+                name='data', 
+                shape=[256, 32, 32], 
+                dtype='float32')
+            out = fluid.layers.maxout(input, groups=2)
     """
     helper = LayerHelper("maxout", **locals())