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Showing content from https://docs.pytorch.org/docs/stable/generated/torch.clamp.html below:

torch.clamp — PyTorch 2.8 documentation

Clamps all elements in input into the range [ min, max ]. Letting min_value and max_value be min and max, respectively, this returns:

y i = min ⁡ ( max ⁡ ( x i , min_value i ) , max_value i ) y_i = \min(\max(x_i, \text{min\_value}_i), \text{max\_value}_i) yi​=min(max(xi​,min_valuei​),max_valuei​)

If min is None, there is no lower bound. Or, if max is None there is no upper bound.

Parameters

• input (Tensor) – the input tensor.

• min (Number or Tensor, optional) – lower-bound of the range to be clamped to

• max (Number or Tensor, optional) – upper-bound of the range to be clamped to

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> a = torch.randn(4)
>>> a
tensor([-1.7120,  0.1734, -0.0478, -0.0922])
>>> torch.clamp(a, min=-0.5, max=0.5)
tensor([-0.5000,  0.1734, -0.0478, -0.0922])

>>> min = torch.linspace(-1, 1, steps=4)
>>> torch.clamp(a, min=min)
tensor([-1.0000,  0.1734,  0.3333,  1.0000])

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