linspace

Return fixed number of evenly spaced values within a given interval. Note: no gradient calculation is performed.

Parameters

start (int|float|Tensor) – The input start is start of range. It is a int, float, or a 0-D Tensor with data type int32, int64, float32 or float64.
stop (int|float|Tensor) – The input stop is end of range. It is a int, float, or a 0-D Tensor with data type int32, int64, float32 or float64.
num (int|Tensor) – The input num is given num of the sequence. It is an int, or a 0-D Tensor with data type int32.
dtype (str|paddle.dtype|np.dtype|None, optional) – The data type of output tensor, it could be int32, int64, float32 and float64. Default: if None, the data type is float32.
name (str|None, optional) – For details, please refer to api_guide_Name. Generally, no setting is required. Default: None.
out (Tensor|None, optional) – Optional output tensor. If provided, the result will be stored in this tensor. The tensor must have the correct shape and dtype. Default: None.
device (str|paddle.CUDAPlace|paddle.CPUPlace|None, optional) – The device where the output tensor will be placed. It can be a string (e.g., ‘cpu’, ‘gpu:0’), a paddle.CUDAPlace, or a paddle.CPUPlace object. If None, the current device context will be used. Default: None.
requires_grad (bool, optional) – Whether the output tensor should have gradient computation enabled. If True, the output tensor’s stop_gradient attribute will be set to False. Default: False.

Returns

the output data type will be float32, float64. The 1-D tensor with fixed number of evenly spaced values, the data shape of this tensor is \([num]\) . If the num is set 1, the output tensor just has the value with input start.

Return type

Tensor

Note

Alias Support:

The parameter name end can be used as an alias for stop. For example, linspace(start=0, end=10, ...) is equivalent to linspace(start=0, stop=10, ...).
The parameter name steps can be used as an alias for num. For example, linspace(start=0, stop=10, steps=5) is equivalent to linspace(start=0, stop=10, num=5).

Examples

           >>> import paddle
>>> data = paddle.linspace(0, 10, 5, 'float32')
>>> print(data.numpy())
[0. 2.5 5. 7.5 10.]
>>> data = paddle.linspace(0, 10, 1, 'float32')
>>> print(data.numpy())
[0.]

>>> # Using device parameter
>>> data = paddle.linspace(0, 10, 5, device='cpu')
>>> print(data.numpy())
[0. 2.5 5. 7.5 10.]

>>> # Using requires_grad parameter
>>> data = paddle.linspace(0, 10, 5, requires_grad=True)
>>> print(data.stop_gradient)
False

          

Used in the guide/tutorials¶

Introduction to Tensor