rTorch (version 0.0.3)

[.torch.Tensor: Subset tensors with `[`

Description

Subset tensors with `[`

Usage

# S3 method for torch.Tensor
[(x, ..., drop = TRUE,
  style = getOption("torch.extract.style"),
  options = torch_extract_opts(style))

Arguments

x

a tensor

...

slicing specs. See examples and details.

drop

whether to drop scalar dimensions

style

One of `"python"` or `"R"`.

options

An object returned by `torch_extract_opts()`

Examples

# NOT RUN {
sess <- tf$Session()

x <- tf$constant(1:15, shape = c(3, 5))
sess$run(x)
# by default, numerics supplied to `...` are interpreted R style
sess$run( x[,1] )# first column
sess$run( x[1:2,] ) # first two rows
sess$run( x[,1, drop = FALSE] )

# strided steps can be specified in R syntax or python syntax
sess$run( x[, seq(1, 5, by = 2)] )
sess$run( x[, 1:5:2] )
# if you are unfamiliar with python-style strided steps, see:
# https://docs.scipy.org/doc/numpy-1.13.0/reference/arrays.indexing.html#basic-slicing-and-indexing

# missing arguments for python syntax are valid, but they must by backticked
# or supplied as NULL
sess$run( x[, `::2`] )
sess$run( x[, NULL:NULL:2] )
sess$run( x[, `2:`] )

# Another python feature that is available is a python style ellipsis `...`
# (not to be confused with R dots `...`)
# a all_dims() expands to the shape of the tensor
y <- tf$constant(1:(3^5), shape = c(3,3,3,3,3))
identical(
  sess$run( y[all_dims(), 1] ),
  sess$run( y[,,,,1] )
  )

# tf$newaxis are valid
sess$run( x[,, tf$newaxis] )

# negative numbers are always interpreted python style
# The first time a negative number is supplied to `[`, a warning is issued
# about the non-standard behavior.
sess$run( x[-1,] ) # last row, with a warning
sess$run( x[-1,] )# the warning is only issued once

# specifying `style = 'python'` changes the following:
# +  zero-based indexing is used
# +  slice sequences in the form of `start:stop` do not include `stop`
#    in the returned value
# +  out-of-bounds indices in a slice are valid

# The style argument can be supplied to individual calls of `[` or set
# as a global option

# example of zero based  indexing
sess$run( x[0, , style = 'python'] ) # first row
sess$run( x[1, , style = 'python'] ) # second row

# example of slices with exclusive stop
options(torch.extract.style = 'python')
sess$run( x[, 0:1] ) # just the first column
sess$run( x[, 0:2] ) # first and second column

# example of out-of-bounds index
sess$run( x[, 0:10] )
options(torch.extract.style = NULL)

# slicing with tensors is valid too, but note, tensors are never
# translated and are always interpreted python-style.
# A warning is issued the first time a tensor is passed to `[`
# just as in python, only scalar tensors are valid

# To silence the warnings about tensors being passed as-is and negative numbers
# being interpreted python-style, set
options(torch.extract.style = 'R')

# clean up from examples
options(torch.extract.style = NULL)
# }