arange¶

paddle. arange ( start=0, end=None, step=1, dtype=None, name=None ) [source]

This OP returns a 1-D Tensor with spaced values within a given interval.

Values are generated into the half-open interval [start, end) with the step. (the interval including start but excluding end).

If dtype is float32 or float64, we advise adding a small epsilon to end to avoid floating point rounding errors when comparing against end.

Parameters

start (float|int|Tensor) – Start of interval. The interval includes this value. If end is None, the half-open interval is [0, start). If start is a Tensor, it is a 1-D Tensor with shape [1], with data type int32, int64, float32, float64. Default is 0.
end (float|int|Tensor, optional) – End of interval. The interval does not include this value. If end is a Tensor, it is a 1-D Tensor with shape [1], with data type int32, int64, float32, float64. If end is None, the half-open interval is [0, start). Default is None.
step (float|int|Tensor, optional) – Spacing between values. For any out, it is the istance between two adjacent values, out[i+1] - out[i]. If step is a Tensor, it is a 1-D Tensor with shape [1], with data type int32, int64, float32, float64. Default is 1.
dtype (str|np.dtype|core.VarDesc.VarType, optional) – The data type of the output tensor. Supported data types: int32, int64, float32, float64. If dytpe is None, the data type is float32. Default is None.
name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name.

Returns

A 1-D Tensor with values from the interval [start, end) taken with common difference step beginning from start. Its data type is set by dtype.

Return type

Tensor

Raises

TypeError – If dtype is not int32, int64, float32, float64.

Examples

           import paddle

out1 = paddle.arange(5)
# [0, 1, 2, 3, 4]

out2 = paddle.arange(3, 9, 2.0)
# [3, 5, 7]

# use 4.999 instead of 5.0 to avoid floating point rounding errors
out3 = paddle.arange(4.999, dtype='float32')
# [0., 1., 2., 3., 4.]

start_var = paddle.to_tensor([3])
out4 = paddle.arange(start_var, 7)
# [3, 4, 5, 6]

          