sub-.tensorflow.tensor.qmd

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execute:
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[R/extract.R](https://github.com/rstudio/tensorflow//blob/main/R/extract.R#L89) 

# [.tensorflow.tensor

## Subset tensors with `[`

## Description
 Subset tensors with `[` 


## Usage
```r
 
## S3 method for class 'tensorflow.tensor'
[( 
  x, 
  ..., 
  drop = TRUE, 
  style = getOption("tensorflow.extract.style"), 
  options = tf_extract_opts(style) 
) 
```

## Arguments
|Arguments|Description|
|---|---|
| x | Tensorflow tensor |
| ... | slicing specs. See examples and details. |
| drop | whether to drop scalar dimensions |
| style | One of `"python"` or `"R"`. |
| options | An object returned by `tf_extract_opts()` |





## Examples
```{r, eval=ecodown::examples_not_run()}
library(tensorflow)
 
 
x <- as_tensor(array(1:15, dim = c(3, 5))) 
x 
# by default, numerics supplied to [...] are interpreted R style 
x[,1]    # first column 
x[1:2,]  # first two rows 
x[,1, drop = FALSE] # 1 column matrix 
 
# strided steps can be specified in R syntax or python syntax 
x[, seq(1, 5, by = 2)] 
x[, 1:5:2] 
# if you are unfamiliar with python-style strided steps, see: 
# https://numpy.org/doc/stable/reference/arrays.indexing.html#basic-slicing-and-indexing 
 
# missing arguments for python syntax are valid, but they must by backticked 
# or supplied as NULL 
x[, `::2`] 
x[, NULL:NULL:2] 
x[, `2:`] 
 
 
# all_dims() expands to the shape of the tensor 
# (equivalent to a python ellipsis `...`) 
# (not to be confused with R dots `...`) 
y <- as_tensor(array(1:(3^5), dim = c(3,3,3,3,3))) 
all.equal(y[all_dims(), 1], 
          y[, , , , 1]) 
 
# tf$newaxis are valid (equivalent to a NULL) 
x[,, tf$newaxis] 
x[,, NULL] 
 
 
# 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. 
x[-1,]  # last row, with a warning 
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 
x[0, , style = 'python']  # first row 
x[1, , style = 'python']  # second row 
 
# example of slices with exclusive stop 
options(tensorflow.extract.style = 'python') 
x[, 0:1]  # just the first column 
x[, 0:2]  # first and second column 
 
# example of out-of-bounds index 
x[, 0:10] 
options(tensorflow.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 `[` 
x[, tf$constant(0L):tf$constant(2L)] 
# just as in python, only scalar tensors are valid 
# https://www.tensorflow.org/api_docs/python/tf/Tensor#__getitem__ 
 
# To silence the warnings about tensors being passed as-is and negative numbers 
# being interpreted python-style, set 
options(tensorflow.extract.style = 'R') 
 
# clean up from examples 
options(tensorflow.extract.style = NULL) 
 
```