Update API usage according to 1.8 recommendations (#666)

ppdet/ext_op/test/test_corner_pool.py

@@ -83,7 +83,7 @@ class TestRightPoolOp(unittest.TestCase):
         place = fluid.CUDAPlace(0)
 
         with fluid.program_guard(tp, sp):
-            x = fluid.layers.data(
+            x = fluid.data(
                 name=self.name,
                 shape=x_shape,
                 dtype=x_type,

ppdet/modeling/anchor_heads/fcos_head.py

@@ -283,22 +283,14 @@ class FCOSHead(object):
                 last dimension is [x1, y1, x2, y2]
         """
         act_shape_cls = self.__merge_hw(box_cls)
-        box_cls_ch_last = fluid.layers.reshape(
-            x=box_cls,
-            shape=[self.batch_size, self.num_classes, -1],
-            actual_shape=act_shape_cls)
+        box_cls_ch_last = fluid.layers.reshape(x=box_cls, shape=act_shape_cls)
         box_cls_ch_last = fluid.layers.sigmoid(box_cls_ch_last)
         act_shape_reg = self.__merge_hw(box_reg, "channel_last")
         box_reg_ch_last = fluid.layers.transpose(box_reg, perm=[0, 2, 3, 1])
         box_reg_ch_last = fluid.layers.reshape(
-            x=box_reg_ch_last,
-            shape=[self.batch_size, -1, 4],
-            actual_shape=act_shape_reg)
+            x=box_reg_ch_last, shape=act_shape_reg)
         act_shape_ctn = self.__merge_hw(box_ctn)
-        box_ctn_ch_last = fluid.layers.reshape(
-            x=box_ctn,
-            shape=[self.batch_size, 1, -1],
-            actual_shape=act_shape_ctn)
+        box_ctn_ch_last = fluid.layers.reshape(x=box_ctn, shape=act_shape_ctn)
         box_ctn_ch_last = fluid.layers.sigmoid(box_ctn_ch_last)
 
         box_reg_decoding = fluid.layers.stack(

ppdet/modeling/architectures/fcos.py

@@ -162,7 +162,7 @@ class FCOS(object):
             for i in range(len(self.fcos_head.fpn_stride)):
                 fields.extend(
                     ['labels%d' % i, 'reg_target%d' % i, 'centerness%d' % i])
-        feed_vars = OrderedDict([(key, fluid.layers.data(
+        feed_vars = OrderedDict([(key, fluid.data(
             name=key,
             shape=inputs_def[key]['shape'],
             dtype=inputs_def[key]['dtype'],

ppdet/modeling/backbones/bfp.py

@@ -152,5 +152,5 @@ class BFP(object):
         out_shape = fluid.layers.cast(out_shape_, dtype='int32')
         out_shape.stop_gradient = True
         body_output = fluid.layers.resize_nearest(
-            body_input, scale=scale, actual_shape=out_shape)
+            body_input, scale=scale, out_shape=out_shape)
         return body_output

ppdet/modeling/backbones/cb_resnet.py

@@ -401,8 +401,7 @@ class CBResNet(object):
         out_shape_ = shape_hw
         out_shape = fluid.layers.cast(out_shape_, dtype='int32')
         out_shape.stop_gradient = True
-        conv = fluid.layers.resize_nearest(
-            conv, scale=2., actual_shape=out_shape)
+        conv = fluid.layers.resize_nearest(conv, scale=2., out_shape=out_shape)
 
         output = fluid.layers.elementwise_add(x=right, y=conv)
         return output

ppdet/modeling/backbones/hrfpn.py

@@ -120,7 +120,7 @@ class HRFPN(object):
         out_shape = fluid.layers.cast(out_shape_, dtype='int32')
         out_shape.stop_gradient = True
         body_output = fluid.layers.resize_bilinear(
-            body_input, scale=scale, actual_shape=out_shape)
+            body_input, scale=scale, out_shape=out_shape)
         return body_output
 
     def pooling(self, input, size, stride, pooling_type):