m53297601
/
Paddle
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

fix API.spec not add defaults. test=develop

Browse Source
revert-15164-speed/enhance_cudnn
dengkaipeng 6 years ago
parent 0d1a9996ac
commit af4ef80e5b
4 changed files with 66 additions and 13 deletions
Show Stats Download Patch File Download Diff File

2
paddle/fluid/API.spec
Unescape View File

@ -327,7 +327,7 @@ 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.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.yolov3_loss (ArgSpec(args=['x', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '991e934c3e09abf0edec7c9c978b4691'))
paddle.fluid.layers.yolov3_loss (ArgSpec(args=['x', 'gtbox', 'gtlabel', 'anchors', 'anchor_mask', 'class_num', 'ignore_thresh', 'downsample_ratio', 'name', 'gtscore', 'use_label_smooth'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', '991e934c3e09abf0edec7c9c978b4691'))
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.distribute_fpn_proposals (ArgSpec(args=['fpn_rois', 'min_level', 'max_level', 'refer_level', 'refer_scale', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '7bb011ec26bace2bc23235aa4a17647d'))

3
paddle/fluid/operators/detection/yolov3_loss_op.cc
Unescape View File

@ -128,7 +128,8 @@ class Yolov3LossOpMaker : public framework::OpProtoAndCheckerMaker {
"The score of GTLabel, This is a 2-D tensor in same shape "
"GTLabel, and score values should in range (0, 1). This "
"input is for GTLabel score can be not 1.0 in image mixup "
"augmentation.");
"augmentation.")
.AsDispensable();
AddOutput("Loss",
"The output yolov3 loss tensor, "
"This is a 1-D tensor with shape of [N]");

28
paddle/fluid/operators/detection/yolov3_loss_op.h
Unescape View File

@ -289,7 +289,6 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
const T* input_data = input->data<T>();
const T* gt_box_data = gt_box->data<T>();
const int* gt_label_data = gt_label->data<int>();
const T* gt_score_data = gt_score->data<T>();
T* loss_data = loss->mutable_data<T>({n}, ctx.GetPlace());
memset(loss_data, 0, loss->numel() * sizeof(T));
T* obj_mask_data =
@ -298,6 +297,19 @@ class Yolov3LossKernel : public framework::OpKernel<T> {
int* gt_match_mask_data =
gt_match_mask->mutable_data<int>({n, b}, ctx.GetPlace());
const T* gt_score_data;
if (!gt_score) {
Tensor _gt_score;
_gt_score.mutable_data<T>({n, b}, ctx.GetPlace());
math::SetConstant<platform::CPUDeviceContext, T>()(
ctx.template device_context<platform::CPUDeviceContext>(), &_gt_score,
static_cast<T>(1.0));
gt_score = &_gt_score;
gt_score_data = _gt_score.data<T>();
} else {
gt_score_data = gt_score->data<T>();
}
// calc valid gt box mask, avoid calc duplicately in following code
Tensor gt_valid_mask;
bool* gt_valid_mask_data =
@ -432,7 +444,6 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
const T* input_data = input->data<T>();
const T* gt_box_data = gt_box->data<T>();
const int* gt_label_data = gt_label->data<int>();
const T* gt_score_data = gt_score->data<T>();
const T* loss_grad_data = loss_grad->data<T>();
const T* obj_mask_data = objness_mask->data<T>();
const int* gt_match_mask_data = gt_match_mask->data<int>();
@ -440,6 +451,19 @@ class Yolov3LossGradKernel : public framework::OpKernel<T> {
input_grad->mutable_data<T>({n, c, h, w}, ctx.GetPlace());
memset(input_grad_data, 0, input_grad->numel() * sizeof(T));
const T* gt_score_data;
if (!gt_score) {
Tensor _gt_score;
_gt_score.mutable_data<T>({n, b}, ctx.GetPlace());
math::SetConstant<platform::CPUDeviceContext, T>()(
ctx.template device_context<platform::CPUDeviceContext>(), &_gt_score,
static_cast<T>(1.0));
gt_score = &_gt_score;
gt_score_data = _gt_score.data<T>();
} else {
gt_score_data = gt_score->data<T>();
}
for (int i = 0; i < n; i++) {
for (int t = 0; t < b; t++) {
int mask_idx = gt_match_mask_data[i * b + t];

46
python/paddle/fluid/tests/unittests/test_yolov3_loss_op.py
Unescape View File

@ -168,7 +168,6 @@ class TestYolov3LossOp(OpTest):
x = logit(np.random.uniform(0, 1, self.x_shape).astype('float32'))
gtbox = np.random.random(size=self.gtbox_shape).astype('float32')
gtlabel = np.random.randint(0, self.class_num, self.gtbox_shape[:2])
gtscore = np.random.random(self.gtbox_shape[:2]).astype('float32')
gtmask = np.random.randint(0, 2, self.gtbox_shape[:2])
gtbox = gtbox * gtmask[:, :, np.newaxis]
gtlabel = gtlabel * gtmask
@ -186,8 +185,13 @@ class TestYolov3LossOp(OpTest):
'X': x,
'GTBox': gtbox.astype('float32'),
'GTLabel': gtlabel.astype('int32'),
'GTScore': gtscore.astype('float32')
}
gtscore = np.ones(self.gtbox_shape[:2]).astype('float32')
if self.gtscore:
gtscore = np.random.random(self.gtbox_shape[:2]).astype('float32')
self.inputs['GTScore'] = gtscore
loss, objness, gt_matches = YOLOv3Loss(x, gtbox, gtlabel, gtscore,
self.attrs)
self.outputs = {
@ -202,11 +206,7 @@ class TestYolov3LossOp(OpTest):
def test_check_grad_ignore_gtbox(self):
place = core.CPUPlace()
self.check_grad_with_place(
place, ['X'],
'Loss',
no_grad_set=set(["GTBox", "GTLabel", "GTScore"]),
max_relative_error=0.2)
self.check_grad_with_place(place, ['X'], 'Loss', max_relative_error=0.2)
def initTestCase(self):
self.anchors = [
@ -215,17 +215,45 @@ class TestYolov3LossOp(OpTest):
]
self.anchor_mask = [0, 1, 2]
self.class_num = 5
self.ignore_thresh = 0.5
self.ignore_thresh = 0.7
self.downsample_ratio = 32
self.x_shape = (3, len(self.anchor_mask) * (5 + self.class_num), 5, 5)
self.gtbox_shape = (3, 5, 4)
self.gtscore = True
self.use_label_smooth = True
class TestYolov3LossWithoutLabelSmooth(TestYolov3LossOp):
def set_label_smooth(self):
def initTestCase(self):
self.anchors = [
10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198,
373, 326
]
self.anchor_mask = [0, 1, 2]
self.class_num = 5
self.ignore_thresh = 0.7
self.downsample_ratio = 32
self.x_shape = (3, len(self.anchor_mask) * (5 + self.class_num), 5, 5)
self.gtbox_shape = (3, 5, 4)
self.gtscore = True
self.use_label_smooth = False
class TestYolov3LossNoGTScore(TestYolov3LossOp):
def initTestCase(self):
self.anchors = [
10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198,
373, 326
]
self.anchor_mask = [0, 1, 2]
self.class_num = 5
self.ignore_thresh = 0.7
self.downsample_ratio = 32
self.x_shape = (3, len(self.anchor_mask) * (5 + self.class_num), 5, 5)
self.gtbox_shape = (3, 5, 4)
self.gtscore = False
self.use_label_smooth = True
if __name__ == "__main__":
unittest.main()

Write Preview
Loading…
Cancel
Save