[.tensorflow.tensor | R Documentation |
[
Subset tensors with [
## S3 method for class 'tensorflow.tensor' x[ ..., drop = TRUE, style = getOption("tensorflow.extract.style"), options = tf_extract_opts(style) ]
x |
Tensorflow tensor |
... |
slicing specs. See examples and details. |
drop |
whether to drop scalar dimensions |
style |
One of |
options |
An object returned by |
## Not run: 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) ## End(Not run)
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