# Sequences

### tf.linspace(start, stop, num, name=None)

Generates values in an interval.

A sequence of num evenly-spaced values are generated beginning at start. If num > 1, the values in the sequence increase by stop - start / num - 1, so that the last one is exactly stop.

For example:

tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0  11.0  12.0]

##### Args:
• start: A Tensor. Must be one of the following types: float32, float64. First entry in the range.
• stop: A Tensor. Must have the same type as start. Last entry in the range.
• num: A Tensor of type int32. Number of values to generate.
• name: A name for the operation (optional).
##### Returns:

A Tensor. Has the same type as start. 1-D. The generated values.

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

Creates a sequence of integers.

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

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

For example:

# 'start' is 3
# 'limit' is 18
# 'delta' is 3
tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]

# 'limit' is 5
tf.range(limit) ==> [0, 1, 2, 3, 4]

##### Args:
• start: A 0-D (scalar) of type int32. First entry in sequence. Defaults to 0.
• limit: A 0-D (scalar) of type int32. Upper limit of sequence, exclusive.
• delta: A 0-D Tensor (scalar) of type int32. Optional. Default is 1. Number that increments start.
• name: A name for the operation (optional).
##### Returns:

An 1-D int32 Tensor.
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