tf.range

TensorFlow 1 version

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Creates a sequence of numbers.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.range

tf.range(limit, delta=1, dtype=None, name='range')
tf.range(start, limit, delta=1, dtype=None, name='range')

Used in the notebooks

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Creates a sequence of numbers that begins at start and extends by increments of delta up to but not including limit.

The dtype of the resulting tensor is inferred from the inputs unless it is provided explicitly.

Like the Python builtin range, start defaults to 0, so that range(n) = range(0, n).

For example:

start = 3
limit = 18
delta = 3
tf.range(start, limit, delta)
<tf.Tensor: shape=(5,), dtype=int32,
numpy=array([ 3,  6,  9, 12, 15], dtype=int32)>

start = 3
limit = 1
delta = -0.5
tf.range(start, limit, delta)
<tf.Tensor: shape=(4,), dtype=float32,
numpy=array([3. , 2.5, 2. , 1.5], dtype=float32)>

limit = 5
tf.range(limit)
<tf.Tensor: shape=(5,), dtype=int32,
numpy=array([0, 1, 2, 3, 4], dtype=int32)>

Args
`start`	A 0-D `Tensor` (scalar). Acts as first entry in the range if `limit` is not None; otherwise, acts as range limit and first entry defaults to 0.
`limit`	A 0-D `Tensor` (scalar). Upper limit of sequence, exclusive. If None, defaults to the value of `start` while the first entry of the range defaults to 0.
`delta`	A 0-D `Tensor` (scalar). Number that increments `start`. Defaults to 1.
`dtype`	The type of the elements of the resulting tensor.
`name`	A name for the operation. Defaults to "range".

Returns
An 1-D `Tensor` of type `dtype`.

Numpy Compatibility

Equivalent to np.arange

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tf / range

View aliases

Used in the notebooks

For example:

Args

Returns

Numpy Compatibility