TensorFlow 1 version | View source on GitHub |
Creates a sequence of numbers.
tf.range(limit, delta=1, dtype=None, name='range')
tf.range(start, limit, delta=1, dtype=None, name='range')
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