How to reshape a tensor in R

This recipe helps you reshape a tensor in R

Recipe Objective - How to reshape a tensor in R?

Tensor reshaping allows data to be re-interpreted using the row-major semantics (opposed to R default column-major semantics) which in turn compatible with the way the numerical libraries called by the Keras library(e.g. TensorFlow, etc.) interpret the array dimensions. Reshaping a tensor involves arranging its rows and columns to match the target shape. The reshaped tensor has same total number of coefficients as the initial the tensor.

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Steps for reshaping a tensor.

Step 1: Installing the keras package

install.packages("keras")

Step 2: Loading keras package in R environment

library(keras)

Step 3: Creating a 2D tensor

 a <- matrix(c(1, 3,
  5, 7,
  9, 12,
  14, 16),
  nrow = 4, ncol = 2, byrow = TRUE)

Step 4: Reshaping the tensor

a <- array_reshape(a, dim = c(8, 1))

The tensor reshaping is done using array_reshape() function. The tensor is reshaped successfully..

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