--- title: Utils keywords: fastai sidebar: home_sidebar summary: "Basic utilities with few dependencies." ---
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%load_ext autoreload
%autoreload 2
%matplotlib inline

At training time, we will typically want to put the model and the current mini batch on the GPU. When developing on a CPU, a GPU isn't available, so we define a variable that will automatically find the right device. This goes in utils rather than core to avoid circular imports with the callbacks module.

DEVICE
device(type='cpu')

hasarg[source]

hasarg(func, arg)

Checks if a function has a given argument.
Works with args and kwargs as well if you exclude the
stars. See example below.

Parameters
----------
func: function
arg: str
    Name of argument to look for.

Returns
-------
bool

Example
-------
def foo(a, b=6, *args):
    return

>>> hasarg(foo, 'b')
True

>>> hasarg(foo, 'args')
True

>>> hasarg(foo, 'c')
False

quick_stats[source]

quick_stats(x, digits=3)

Quick wrapper to get mean and standard deviation of a tensor.

Parameters
----------
x: torch.Tensor
digits: int
    Number of digits to round mean and standard deviation to.

Returns
-------
tuple[float]
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