torch_is_floating_point

Provides functionality to define and train neural networks similar to
'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R
using the 'libtorch' library. Also supports low-level tensor operations and
'GPU' acceleration.

Daniel Falbel

torch

Tensors and Neural Networks with 'GPU' Acceleration

Javier Luraschi

Dmitriy Selivanov

Athos Damiani

Christophe Regouby

Krzysztof Joachimiak

Hamada S. Badr

Sebastian Fischer

Maximilian Pichler

 RStudio

torch_is_floating_point function

<dl><dt>self</dt>
<dd>(Tensor) the PyTorch tensor to test</dd></dl>

Arguments

Returns TRUE if the data type of <code>input</code> is a floating point data type i.e.,
one of <code>torch_float64</code>, <code>torch.float32</code> and <code>torch.float16</code>.

is_floating_point(input) -&gt; (bool) 

Is_floating_point — torch_is_floating_point

<dl>

<dt>self</dt>
<dd>(Tensor) the PyTorch tensor to test</dd>

</dl>

Returns TRUE if the data type of <code>input</code> is a floating point data type i.e.,
one of <code>torch_float64</code>, <code>torch.float32</code> and <code>torch.float16</code>.

torch_is_floating_point: Is_floating_point

Description

Usage

Arguments

is_floating_point(input) -> (bool)

Description

Usage

Arguments

is_floating_point(input) -&gt; (bool)

is_floating_point(input) -> (bool)