Vignette Title"
In rTorch: R Bindings to 'PyTorch'

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(reticulate)

torch      <- import("torch")
Variable   <- import("torch.autograd")$Variable
np         <- import("numpy")
optim      <- import("torch.optim") 
py         <- import_builtins()

x = torch$rand(20L, 50L, 100L)
x_size <- x$size()
x_size
class(x_size)

it <- iterate(py$enumerate(x_size))  # [[3]][[2]]
# for (i in it) print(i)
sapply(it, identity)

Creating a tensor of a size

y <- torch$Size(c(1L, 2L, 3L, 4L))
class(y)
y$index
it <- iterate(py$enumerate(y))
sapply(it, identity)

Creating a tensor of size

p <- torch$Tensor(torch$Size(c(256L, 3L, 9L, 9L, 2L)))
class(p)
it <- iterate(py$enumerate(p$size()))
class(sapply(it, `[`))
# "matrix"
m <- sapply(it, `[`)
v <- m[2, ]
class(unlist(v))
unlist(v)
p

Get the maximum values of a tensor

https://groups.google.com/forum/#!topic/torch7/a1EAEwLn15g

torch$manual_seed(42L)
a <- torch$randn(4L, 4L)
a

# expected to be in range of [-2, 1]
val <- torch$max(a, 1L)[[1]]
idx <- torch$max(a, 1L)[[2]]

val
idx

Test dimensions of a tensor

https://github.com/pytorch/pytorch/issues/1310

library(rTorch)

dims <- as.integer(c(3, 4, 5, 6, 7, 8))
a <-  torch$randn(torch$Size(dims))
a$size()


for (dim in seq(1, length(dims))) {
    dim <- as.integer(dim - 1)
    for (i in seq(a$size(dim))) {
        i <- as.integer(i - 1)
        a$select(dim, i)$fill_(i)  # slice and fill with the dim number
    }
    val    <- a$max(dim)[[1]]
    argmax <- a$max(dim)[[2]]
    cat(argmax$min(), "\t")    # min and max should be the same since
    cat(argmax$max(), "\n")    # the tensor was filled with the same value
}
a$size()

import torch

dims = (3, 4, 5, 6, 7, 8)
a = torch.randn(*dims)
for dim in range(len(dims)):
    for i in range(a.size(dim)):
        # print(dim, i)
        a.select(dim,i).fill_(i)
    val, argmax = a.max(dim)
    print(argmax.max())