[xdoctest][task 165] reformat example code with google style in python/paddle/vision/ops.py #57108
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你的PR提交成功，感谢你对开源项目的贡献! |
megemini
reviewed
Sep 8, 2023
python/paddle/vision/ops.py
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| @@ -1888,7 +1879,7 @@ def nms( | |||
| Args: | |||
| boxes(Tensor): The input boxes data to be computed, it's a 2D-Tensor with | |||
| the shape of [num_boxes, 4]. The data type is float32 or float64. | |||
| Given as [[x1, y1, x2, y2], …], (x1, y1) is the top left coordinates, | |||
| Given as [[x1, y1, x2, y2], ��], (x1, y1) is the top left coordinates, | |||
megemini
reviewed
Sep 9, 2023
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| >>> print(rois, roi_probs, roi_nums) | ||
| Tensor(shape=[2, 4], dtype=float32, place=Place(cpu), stop_gradient=True, | ||
| [[0., 0., 0., 0.], | ||
| [0., 0., 0., 0.]]) | ||
| Tensor(shape=[2, 1], dtype=float32, place=Place(cpu), stop_gradient=True, | ||
| [[0.], | ||
| [0.]]) | ||
| Tensor(shape=[2], dtype=int32, place=Place(cpu), stop_gradient=True, | ||
| [1, 1]) |
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加个 seed 吧（好像也不管用 ... ...）～ 不然有一定概率会不是 0 ～
SigureMo
reviewed
Sep 9, 2023
python/paddle/vision/ops.py
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| >>> import paddle | ||
| >>> x = paddle.rand([2, 14, 8, 8]).astype('float32') | ||
| >>> gt_box = paddle.rand([2, 10, 4]).astype('float32') | ||
| >>> gt_label = paddle.rand([2, 10]).astype('int32') | ||
| >>> loss = paddle.vision.ops.yolo_loss(x, | ||
| ... gt_box=gt_box, | ||
| ... gt_label=gt_label, | ||
| ... anchors=[10, 13, 16, 30], | ||
| ... anchor_mask=[0, 1], | ||
| ... class_num=2, | ||
| ... ignore_thresh=0.7, | ||
| ... downsample_ratio=8, | ||
| ... use_label_smooth=True, | ||
| ... scale_x_y=1.) |
python/paddle/vision/ops.py
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| @@ -356,19 +353,19 @@ def yolo_box( | |||
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| .. code-block:: python | |||
megemini
reviewed
Sep 10, 2023
python/paddle/vision/ops.py
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| >>> print(rois, roi_probs, roi_nums) | ||
| Tensor(shape=[2, 4], dtype=float32, place=Place(cpu), stop_gradient=True, | ||
| [[0., 0., 0., 0.], | ||
| [0., 0., 0., 0.]]) | ||
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|
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| >>> # doctest: +SKIP('random sample') | ||
| >>> print(roi_probs, roi_nums) | ||
| Tensor(shape=[2, 1], dtype=float32, place=Place(cpu), stop_gradient=True, | ||
| [[0.], | ||
| [0.]]) | ||
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| >>> # doctest: -SKIP | ||
| >>> print(roi_nums) | ||
| Tensor(shape=[2], dtype=int32, place=Place(cpu), stop_gradient=True, | ||
| [1, 1]) |
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这里整体跳过就行 ～
另外，每次 print 一个就行 ～ 这每次少 print 一个 ... ... 忒抽象了 ～ 🤣🤣🤣
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Description
修改如下文件的示例代码，使其通过
xdoctest检查：Related links
@sunzhongkai588 @SigureMo @megemini