The 'fastai' <https://docs.fast.ai/index.html> library
simplifies training fast and accurate neural networks
using modern best practices. It is based on research
in to deep learning best practices undertaken
at 'fast.ai', including 'out of the box' support
for vision, text, tabular, audio, time series, and
collaborative filtering models.

Interface to 'fastai'

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7

resnet_generator(
  ch_in,
  ch_out,
  n_ftrs = 64,
  norm_layer = NULL,
  dropout = 0,
  n_blocks = 9,
  pad_mode = "reflection"
)

<table summary="R argblock">
<tr valign="top">
<td><code>ch_in</code></td>
<td>
input
</td>
</tr>
<tr valign="top">
<td><code>ch_out</code></td>
<td>
output
</td>
</tr>
<tr valign="top">
<td><code>n_ftrs</code></td>
<td>
filter
</td>
</tr>
<tr valign="top">
<td><code>norm_layer</code></td>
<td>
normalziation layer
</td>
</tr>
<tr valign="top">
<td><code>dropout</code></td>
<td>
dropout rate
</td>
</tr>
<tr valign="top">
<td><code>n_blocks</code></td>
<td>
number of blocks
</td>
</tr>
<tr valign="top">
<td><code>pad_mode</code></td>
<td>
paddoing mode
</td>
</tr>
</table>

package-ubuntu-20.04-r-4.0.5#cran#fastai-2.0.7#docs#resnet_generator

resnet_generator

Description

Usage

Arguments

Value

fastai

We don't support your browser anymore

`ch_in`	input
`ch_out`	output
`n_ftrs`	filter
`norm_layer`	normalziation layer
`dropout`	dropout rate
`n_blocks`	number of blocks
`pad_mode`	paddoing mode