eazygrad.uniform¶

eazygrad.uniform(*shape: int, low: float = 0.0, high: float = 1.0, requires_grad: bool = False, dtype: Any = numpy.float32) → _Tensor[source]¶

Return a tensor filled with samples from a uniform distribution.

Parameters:

*shape (int) – Output shape.
low (float, default=0.0) – Lower bound of the distribution.
high (float, default=1.0) – Upper bound of the distribution.
requires_grad (bool, default=False) – Whether to track gradients for the returned tensor.
dtype (numpy.dtype or type, default=numpy.float32) – Output dtype.

Returns:

_Tensor – Randomly initialized tensor.