tf.experimental.numpy.arange

TensorFlow variant of NumPy's arange.

tf.experimental.numpy.arange(
    start, stop=None, step=1, dtype=None
)

Returns step-separated values in the range [start, stop).

Args: start: Start of the interval. Included in the range. stop: End of the interval. If not specified, start is treated as 0 and start value is used as stop. If specified, it is not included in the range if step is integer. When step is floating point, it may or may not be included. step: The difference between 2 consecutive values in the output range. It is recommended to use linspace instead of using non-integer values for step. dtype: Optional. Type of the resulting ndarray. Could be a python type, a NumPy type or a TensorFlow DType. If not provided, the largest type of start, stop, step is used.

Raises: ValueError: If step is zero.

See the NumPy documentation for numpy.arange.