# 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. Must be one of the following types: int32, int64. 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. 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 (scalar) of type int32. 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) of type int32. Number that increments start. Defaults to 1.
• name: A name for the operation. Defaults to "range".
##### Returns:

An 1-D int32 Tensor.