Tensor shape utility

This function can be used to create or get the shape of an object.

Usage

shape(...)

# S3 method for keras_shape
format(x, ..., prefix = TRUE)

# S3 method for keras_shape
print(x, ...)

# S3 method for keras_shape
[(x, ...)

# S3 method for keras_shape
as.integer(x, ...)

# S3 method for keras_shape
as.list(x, ...)

Arguments

...

A shape specification. Numerics, NULL and tensors are valid. NULL, NA, and -1L can be used to specify an unspecified dim size. Tensors are dispatched to op_shape() to extract the tensor shape. Values wrapped in I() are used asis (see examples). All other objects are coerced via as.integer().

x

A 'keras_shape' object

prefix

Whether to format the shape object with a prefix. Defaults to "shape".

Value

A list with a "keras_shape" class attribute. Each element of the list will be either a) NULL, b) an integer or c) a scalar integer tensor (e.g., when supplied a TF tensor with a unspecified dimension in a function being traced).

Examples

shape(1, 2, 3)

## shape(1, 2, 3)

3 ways to specify an unknown dimension

shape(NA,   2, 3)
shape(NULL, 2, 3)
shape(-1,   2, 3)

## shape(NA, 2, 3)
## shape(NA, 2, 3)
## shape(NA, 2, 3)

Most functions that take a 'shape' argument also coerce with shape()

layer_input(c(1, 2, 3))
layer_input(shape(1, 2, 3))

## <KerasTensor shape=(None, 1, 2, 3), dtype=float32, sparse=None, name=keras_tensor>
## <KerasTensor shape=(None, 1, 2, 3), dtype=float32, sparse=None, name=keras_tensor_1>

You can also use shape() to get the shape of a tensor (excepting scalar integer tensors).

symbolic_tensor <- layer_input(shape(1, 2, 3))
shape(symbolic_tensor)

## shape(NA, 1, 2, 3)

eager_tensor <- op_ones(c(1,2,3))
shape(eager_tensor)

## shape(1, 2, 3)

op_shape(eager_tensor)

## shape(1, 2, 3)

Combine or expand shapes

shape(symbolic_tensor, 4)

## shape(NA, 1, 2, 3, 4)

shape(5, symbolic_tensor, 4)

## shape(5, NA, 1, 2, 3, 4)

Scalar integer tensors are treated as axis values. These are most commonly encountered when tracing a function in graph mode, where an axis size might be unknown.

tfn <- tensorflow::tf_function(function(x) {
  print(op_shape(x))
  x
},
input_signature = list(tensorflow::tf$TensorSpec(shape(1, NA, 3))))
invisible(tfn(op_ones(shape(1, 2, 3))))

## shape(1, Tensor("strided_slice:0", shape=(), dtype=int32), 3)

A useful pattern is to unpack the shape() with %<-%, like this:

c(batch_size, seq_len, channels) %<-% shape(x)

echo_print <- function(x) {
  message("> ", deparse(substitute(x)));
  if(!is.null(x)) print(x)
}
tfn <- tensorflow::tf_function(function(x) {
  c(axis1, axis2, axis3) %<-% shape(x)
  echo_print(str(list(axis1 = axis1, axis2 = axis2, axis3 = axis3)))

  echo_print(shape(axis1))               # use axis1 tensor as axis value
  echo_print(shape(axis1, axis2, axis3)) # use axis1 tensor as axis value

  # use shape() to compose a new shape, e.g., in multihead attention
  n_heads <- 4
  echo_print(shape(axis1, axis2, n_heads, axis3/n_heads))

  x
},
input_signature = list(tensorflow::tf$TensorSpec(shape(NA, 4, 16))))
invisible(tfn(op_ones(shape(2, 4, 16))))

## > str(list(axis1 = axis1, axis2 = axis2, axis3 = axis3))

## List of 3
##  $ axis1:<tf.Tensor 'strided_slice:0' shape=() dtype=int32>
##  $ axis2: int 4
##  $ axis3: int 16

## > shape(axis1)

## shape(Tensor("strided_slice:0", shape=(), dtype=int32))

## > shape(axis1, axis2, axis3)

## shape(Tensor("strided_slice:0", shape=(), dtype=int32), 4, 16)

## > shape(axis1, axis2, n_heads, axis3/n_heads)

## shape(Tensor("strided_slice:0", shape=(), dtype=int32), 4, 4, 4)

If you want to resolve the shape of a tensor that can potentially be a scalar integer, you can wrap the tensor in I(), or use op_shape().

(x <- op_convert_to_tensor(2L))

## tf.Tensor(2, shape=(), dtype=int32)

# by default, shape() treats scalar integer tensors as axis values
shape(x)

## shape(tf.Tensor(2, shape=(), dtype=int32))

# to access the shape of a scalar integer,
# call `op_shape()`, or protect with `I()`
op_shape(x)

## shape()

shape(I(x))

## shape()

See also

op_shape()