fix sample code diff for OP(retinanet_detection_output,...

fix sample code diff for OP(retinanet_detection_output, retinanet_target_assign), fix `gamma` default value for OP(sigmoid_focal_loss) (#1971)

* fix sample code diff for OP(retinanet_detection_output, retinanet_target_assign), fix  default value for OP(sigmoid_focal_loss). test=develop

* fix float value. test=develop

doc/fluid/api_cn/layers_cn/retinanet_detection_output_cn.rst

@@ -34,27 +34,27 @@ retinanet_detection_output
 
   import paddle.fluid as fluid
 
-  bboxes_low = fluid.data(name='bboxes_low', shape=[1, 44, 4],
-      dtype='float32')
-  bboxes_high = fluid.data(name='bboxes_high', shape=[1, 11, 4],
-      dtype='float32')
-  scores_low = fluid.data(name='scores_low', shape=[1, 44, 10],
-      dtype='float32')
-  scores_high = fluid.data(name='scores_high', shape=[1, 11, 10],
-      dtype='float32')
-  anchors_low = fluid.data(name='anchors_low', shape=[44, 4],
-      dtype='float32')
-  anchors_high = fluid.data(name='anchors_high', shape=[11, 4],
-      dtype='float32')
-  im_info = fluid.data(name="im_info", shape=[1, 3],
-      dtype='float32')
+  bboxes_low = fluid.data(
+      name='bboxes_low', shape=[1, 44, 4], dtype='float32')
+  bboxes_high = fluid.data(
+      name='bboxes_high', shape=[1, 11, 4], dtype='float32')
+  scores_low = fluid.data(
+      name='scores_low', shape=[1, 44, 10], dtype='float32')
+  scores_high = fluid.data(
+      name='scores_high', shape=[1, 11, 10], dtype='float32')
+  anchors_low = fluid.data(
+      name='anchors_low', shape=[44, 4], dtype='float32')
+  anchors_high = fluid.data(
+      name='anchors_high', shape=[11, 4], dtype='float32')
+  im_info = fluid.data(
+      name="im_info", shape=[1, 3], dtype='float32')
   nmsed_outs = fluid.layers.retinanet_detection_output(
-                                          bboxes=[bboxes_low, bboxes_high],
-                                          scores=[scores_low, scores_high],
-                                          anchors=[anchors_low, anchors_high],
-                                          im_info=im_info,
-                                          score_threshold=0.05,
-                                          nms_top_k=1000,
-                                          keep_top_k=100,
-                                          nms_threshold=0.45,
-                                          nms_eta=1.)
+      bboxes=[bboxes_low, bboxes_high],
+      scores=[scores_low, scores_high],
+      anchors=[anchors_low, anchors_high],
+      im_info=im_info,
+      score_threshold=0.05,
+      nms_top_k=1000,
+      keep_top_k=100,
+      nms_threshold=0.45,
+      nms_eta=1.0)

doc/fluid/api_cn/layers_cn/retinanet_target_assign_cn.rst

@@ -50,7 +50,6 @@ retinanet_target_assign
 .. code-block:: python
 
     import paddle.fluid as fluid
-    import numpy as np
  
     bbox_pred = fluid.data(name='bbox_pred', shape=[1, 100, 4],
                       dtype='float32')

doc/fluid/api_cn/layers_cn/sigmoid_focal_loss_cn.rst

@@ -3,7 +3,7 @@
 sigmoid_focal_loss
 -------------------------------
 
-.. py:function:: paddle.fluid.layers.sigmoid_focal_loss(x, label, fg_num, gamma=2, alpha=0.25)
+.. py:function:: paddle.fluid.layers.sigmoid_focal_loss(x, label, fg_num, gamma=2.0, alpha=0.25)
 
 `Focal Loss <https://arxiv.org/abs/1708.02002>`_ 被提出用于解决计算机视觉任务中前景-背景不平衡的问题。该OP先计算输入x中每个元素的sigmoid值，然后计算sigmoid值与类别目标值label之间的Focal Loss。
 
@@ -49,5 +49,5 @@ Focal Loss的计算过程如下：
     loss = fluid.layers.sigmoid_focal_loss(x=input,
                                            label=label,
                                            fg_num=fg_num,
-                                           gamma=2.,
+                                           gamma=2.0,
                                            alpha=0.25)