TensorFlow 1 version
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View source on GitHub
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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 = 3limit = 18delta = 3tf.range(start, limit, delta)<tf.Tensor: shape=(5,), dtype=int32,numpy=array([ 3, 6, 9, 12, 15], dtype=int32)>
start = 3limit = 1delta = -0.5tf.range(start, limit, delta)<tf.Tensor: shape=(4,), dtype=float32,numpy=array([3. , 2.5, 2. , 1.5], dtype=float32)>
limit = 5tf.range(limit)<tf.Tensor: shape=(5,), dtype=int32,numpy=array([0, 1, 2, 3, 4], dtype=int32)>
Args | |
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start
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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.
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limit
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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.
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delta
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A 0-D Tensor (scalar). Number that increments start. Defaults to
1.
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dtype
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The type of the elements of the resulting tensor. |
name
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A name for the operation. Defaults to "range". |
Returns | |
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An 1-D Tensor of type dtype.
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numpy compatibility
Equivalent to np.arange
TensorFlow 1 version
View source on GitHub