Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

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

torch.fmod — PyTorch 2.7 documentation

torch.fmod(input, other, *, out=None) → Tensor¶

Applies C++’s std::fmod entrywise. The result has the same sign as the dividend input and its absolute value is less than that of other.

This function may be defined in terms of torch.div() as

torch.fmod(a, b) == a - a.div(b, rounding_mode="trunc") * b

Supports broadcasting to a common shape, type promotion, and integer and float inputs.

Note

When the divisor is zero, returns NaN for floating point dtypes on both CPU and GPU; raises RuntimeError for integer division by zero on CPU; Integer division by zero on GPU may return any value.

Note

Complex inputs are not supported. In some cases, it is not mathematically possible to satisfy the definition of a modulo operation with complex numbers.

See also

torch.remainder() which implements Python’s modulus operator. This one is defined using division rounding down the result.

Parameters

• input (Tensor) – the dividend

• other (Tensor or Scalar) – the divisor

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> torch.fmod(torch.tensor([-3., -2, -1, 1, 2, 3]), 2)
tensor([-1., -0., -1.,  1.,  0.,  1.])
>>> torch.fmod(torch.tensor([1, 2, 3, 4, 5]), -1.5)
tensor([1.0000, 0.5000, 0.0000, 1.0000, 0.5000])

Access comprehensive developer documentation for PyTorch

Get in-depth tutorials for beginners and advanced developers

Find development resources and get your questions answered

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4