paddle复现pytorch踩坑(四）：Tensor

paddlepaddle从1.5版本以上采用动态图的思想&＃xff0c;本博客基于1.8.0以上版本。
关于Tensor的用法&＃xff1a;

• pytorch可以使用静态数组索引&＃xff1b;可以使用tensor索引
• paddlepaddle可以使用静态数组索引&＃xff1b;不可以使用tensor索引

示例1&＃xff1a;索引示例

# pytorch code
aa &＃61; cls[active, :]
# paddlepaddle code
aa &＃61; cls[active, :]


报错&＃xff1a;

SystemError: <built-in method __getitem__ of PyCapsule object at 0x0000023217C75F90> returned a result with an error set


• 其中
  activate &＃61; tensor [1,… 0, 1…0]
  clc &＃61; tenor.shape [300, 4]
• 原因&＃xff1a;在pytorch里可以这样写&＃xff0c;但是在paddle里不行
• 改为&＃xff1a;利用nonzero 和 gather函数

# paddlepaddle code
index &＃61; fluid.layers.nonzero(active)
aa &＃61; fluid.layers.gather(cls, index)


测试全代码

import paddle.fluid as fluid
from paddle.fluid.dygraph.base import to_variable
import numpy as npdata &＃61; np.ones([300, 4]).astype(&＃39;float32&＃39;)
index &＃61; np.zeros([300]).astype(&＃39;int&＃39;)
index[0] &＃61; 1
index[2] &＃61; 1
index[10] &＃61; 1with fluid.dygraph.guard():data &＃61; to_variable(data)index &＃61; to_variable(index)index &＃61; fluid.layers.nonzero(index)data &＃61; fluid.layers.gather(data, index)# data &＃61; data[index, :]print(data.shape)


示例2

# pytorch code
active &＃61; labels_weight > 0
y &＃61; bbox_x[active]# paddlepaddle code
active &＃61; labels_weight > 0
index &＃61; fluid.layers.nonzero(active)
y &＃61; fluid.layers.concat([fluid.layers.reshape(fluid.layers.gather(bbox_x[i, :], index[i, :]), [1, -1]) for i in range(index.shape[0])], axis&＃61;0)

示例3

# pytorch code
loss_bbox_y &＃61; fluid.layers.mean(loss_bbox_y * bbox_weights[active])# paddlepaddle code
loss_bbox_y &＃61; fluid.layers.mean(fluid.layers.cast(loss_bbox_y, &＃39;float64&＃39;)* fluid.layers.concat([fluid.layers.reshape(fluid.layers.gather(bbox_weights[i, :], index[i, :]), [1, -1]) for i in range(index.shape[0])], axis&＃61;0))

示例4

# pytorch code
bbox_x3d_dn_fg &＃61; bbox_x3d_dn[bind, fg_inds]# paddlepaddle code
bbox_x3d_dn_fg &＃61; fluid.layers.gather(bbox_x3d_dn[bind], fluid.dygraph.to_variable(fg_inds))


示例5&＃xff1a;不能维度直接赋值

报错&＃xff1a;

TypeError: &＃39;paddle.fluid.core_avx.VarBase&＃39; object does not support item assignment


# pytorch code
Pred_boxes[:, 0] &＃61; pred_ctr_x - 0.5 * pred_w
pred_boxes[:, 1] &＃61; pred_ctr_y - 0.5 * pred_h
pred_boxes[:, 2] &＃61; pred_ctr_x &＃43; 0.5 * pred_w
pred_boxes[:, 3] &＃61; pred_ctr_y &＃43; 0.5 * pred_h# paddlepaddle code
pred_boxes &＃61; fluid.layers.concat([pred_ctr_x - 0.5 * pred_w,pred_ctr_y - 0.5 * pred_h,pred_ctr_x &＃43; 0.5 * pred_w,pred_ctr_y &＃43; 0.5 * pred_h
])


示例6&＃xff1a;维度报错

报错&＃xff1a;

too many indices (3) for tensor of dimension 2


# pytorch code
bbox_x[bind, :, np.newaxis ]
# paddlepaddle code
fluid.layers.reshape(bbox_x[bind, :], [1, -1, 1])


示例7&＃xff1a;tensor的值不能直接利用

报错&＃xff1a;paddlepaddle中的value不能直接拿出来用。

TypeError: The type of &＃39;shape&＃39; in reshape must be list[int] or tuple(int) in Dygraph mode, but received <class &＃39;list&＃39;>, which contains Variable.


错误代码&＃xff1a;其中stack_size, feat_size 为 tensor。

# paddlepaddle code
shift_x1 &＃61; fluid.layers.reshape(fluid.dygraph.to_variable(shift_x1), [1, stack_size, feat_size[1]])


改进加入

# paddlepaddle code
stack_size &＃61; stack_size.numpy()
feat_size &＃61; feat_size.numpy()


Tensor数据类型判断

# pytorch code
if data_type &＃61;&＃61; torch.tensor:# paddlepaddle code
if data_type &＃61;&＃61; fluid.core_avx.VarBase:

其他用法

# pytorch code
b &＃61; q_lt[..., :N]# paddlepaddle code
b &＃61; q_lt[:, :, :, :N]

需要注意pytorch中.contiguous方法

.contiguous()方法&＃xff0c;使tensor的元素在内存空间中连续
通常

tensor.contiguous().view()
&＃61;&＃61;
tensor.reshape()