layer_input

Shape, not including the batch size. For instance,
<code>shape=c(32)</code> indicates that the expected input will be batches
of 32-dimensional vectors.

shape

Shape, including the batch size. For instance,
<code>shape = c(10,32)</code> indicates that the expected input will be batches
of 10 32-dimensional vectors. <code>batch_shape = list(NULL, 32)</code> indicates
batches of an arbitrary number of 32-dimensional vectors.

batch_shape

An optional name string for the layer. Should be unique in a
model (do not reuse the same name twice). It will be autogenerated if it
isn't provided.

name

The data type expected by the input, as a string (<code>float32</code>,
<code>float64</code>, <code>int32</code>...)

dtype

Boolean, whether the placeholder created is meant to be sparse.

sparse

Existing tensor to wrap into the <code>Input</code> layer. If set, the
layer will not create a placeholder tensor.

tensor

Layer to be used as an entry point into a graph.

Interface to 'Keras' <https://keras.io>, a high-level neural
networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation,
supports both convolution based networks and recurrent networks (as well as
combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.

JJ Allaire

keras

R Interface to 'Keras'

Fran<c3><a7>ois Chollet

 RStudio

 Google

Yuan Tang

Daniel Falbel

Wouter Van Der Bijl

Martin Studer

Sigrid Keydana

layer_input function

Input layer — layer_input

Input layer

Interface to 'Keras', a high-level neural networks API which
runs on top of TensorFlow. 'Keras' was developed with a focus on enabling
fast experimentation, supports both convolutional networks and recurrent
networks (as well as combinations of the two), and seamlessly on both CPUs
and GPUs.

layer_input: Input layer

Description

Usage

Arguments

Value

See Also