提交 b5560726 编写于 作者: D dengkaipeng

fix unittest and API.spec. test=release/1.4

上级 b1e7799b
...@@ -347,7 +347,7 @@ paddle.fluid.layers.generate_mask_labels (ArgSpec(args=['im_info', 'gt_classes', ...@@ -347,7 +347,7 @@ paddle.fluid.layers.generate_mask_labels (ArgSpec(args=['im_info', 'gt_classes',
paddle.fluid.layers.iou_similarity (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '587845f60c5d97ffdf2dfd21da52eca1')) paddle.fluid.layers.iou_similarity (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '587845f60c5d97ffdf2dfd21da52eca1'))
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', '032d0f4b7d8f6235ee5d91e473344f0e'))
paddle.fluid.layers.polygon_box_transform (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '0e5ac2507723a0b5adec473f9556799b')) 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', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'gtscore', 'use_label_smooth', 'name'], varargs=None, keywords=None, defaults=(None, True, None)), ('document', '57fa96922e42db8f064c3fb77f2255e8')) 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', '059021025283ad1ee6f4d32228cf3e4e'))
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.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', '397e9e02b451d99c56e20f268fa03f2e'))
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.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'))
......
...@@ -605,7 +605,7 @@ def yolov3_loss(x, ...@@ -605,7 +605,7 @@ def yolov3_loss(x,
"GTBox": gt_box, "GTBox": gt_box,
"GTLabel": gt_label, "GTLabel": gt_label,
} }
if gtscore: if gt_score:
inputs["GTScore"] = gt_score inputs["GTScore"] = gt_score
attrs = { attrs = {
......
...@@ -474,17 +474,17 @@ class TestYoloDetection(unittest.TestCase): ...@@ -474,17 +474,17 @@ class TestYoloDetection(unittest.TestCase):
program = Program() program = Program()
with program_guard(program): with program_guard(program):
x = layers.data(name='x', shape=[30, 7, 7], dtype='float32') x = layers.data(name='x', shape=[30, 7, 7], dtype='float32')
gtbox = layers.data(name='gtbox', shape=[10, 4], dtype='float32') gt_box = layers.data(name='gt_box', shape=[10, 4], dtype='float32')
gtlabel = layers.data(name='gtlabel', shape=[10], dtype='int32') gt_label = layers.data(name='gt_label', shape=[10], dtype='int32')
gtscore = layers.data(name='gtscore', shape=[10], dtype='float32') gt_score = layers.data(name='gt_score', shape=[10], dtype='float32')
loss = layers.yolov3_loss( loss = layers.yolov3_loss(
x, x,
gtbox, gt_box,
gtlabel, [10, 13, 30, 13], [0, 1], gt_label, [10, 13, 30, 13], [0, 1],
10, 10,
0.7, 0.7,
32, 32,
gtscore=gtscore, gt_score=gt_score,
use_label_smooth=False) use_label_smooth=False)
self.assertIsNotNone(loss) self.assertIsNotNone(loss)
......
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