broadcast_all

Raises value_error: if any of the values is not a <code>numeric</code> instance,
a <code>torch.*Tensor</code> instance, or an instance implementing torch_function
TODO: add has_torch_function((v,))
See: https://github.com/pytorch/pytorch/blob/master/torch/distributions/utils.py

Provides functionality to define and train neural networks similar to
'PyTorch' by Paszke et al (2019) <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

 RStudio

broadcast_all function

<dl><dt>values</dt>
<dd>List of:<ul>
<li><code>torch.*Tensor</code> instances are broadcasted as per <code>_broadcasting-semantics</code>.</li>
<li><code>numeric</code> instances (scalars) are upcast to tensors having
the same size and type as the first tensor passed to <code>values</code>. If all the
values are scalars, then they are upcasted to scalar Tensors.
values (list of <code>numeric</code>, <code>torch.*Tensor</code> or objects implementing torch_function)</li>
</ul></dd></dl>

Arguments

Given a list of values (possibly containing numbers), returns a list where each
value is broadcasted based on the following rules: — broadcast_all

<dl>

<dt>values</dt>
<dd>List of:<ul>
<li><code>torch.*Tensor</code> instances are broadcasted as per <code>_broadcasting-semantics</code>.</li>
<li><code>numeric</code> instances (scalars) are upcast to tensors having
the same size and type as the first tensor passed to <code>values</code>. If all the
values are scalars, then they are upcasted to scalar Tensors.
values (list of <code>numeric</code>, <code>torch.*Tensor</code> or objects implementing torch_function)</li>
</ul></dd>

</dl>

broadcast_all: Given a list of values (possibly containing numbers), returns a list where each value is broadcasted based on the following rules:

Description

Usage

Arguments