PyTorch Notes
Tensor Operations clamp torch.clamp（或 Tensor 的实例方法 .clamp）是 PyTorch 中用于数值截断（clipping）的常用操作。它的主要作用是将输入张量（Tensor）中的所有元素限制在一个指定的范围内 $[min, max]$。 Example: import torch # Initialize a tensor with values ranging from -10 to 10 data = torch.tensor([-10.0, -5.0, 0.5, 5.0, 10.0]) print(f"Original: {data}") # 1. Clamp between a min and max range [-1, 1] # Values < -1 become -1; Values > 1 become 1 clamped_both = data.clamp(min=-1.0, max=1.0) print(f"Range [-1, 1]: {clamped_both}") # 2. Clamp with only a lower bound (min=-2) # Values < -2 become -2; No upper limit clamped_min = data.clamp(min=-2.0) print(f"Min -2 only: {clamped_min}") # 3. Clamp with only an upper bound (max=3) # Values > 3 become 3; No lower limit clamped_max = data.clamp(max=3.0) print(f"Max 3 only: {clamped_max}") Advanced Indexing x[y] 是 PyTorch（以及 NumPy）中非常强大且灵活的**高级索引（Advanced Indexing）**语法 ...