def random_uniform(shape, minval=0, maxval=None, dtype=dtypes.float32, seed=None, name=None): return ops.RandomUniform(shape, minval, maxval)
def random_uniform(shape, minval=0, maxval=None, dtype=dtypes.float32, name=None): """ Outputs random values from a uniform distribution. The generated values follow a uniform distribution in the range `[minval, maxval)`. The lower bound `minval` is included in the range, while the upper bound `maxval` is excluded. For floats, the default range is `[0, 1)`. For ints, at least `maxval` must be specified explicitly. In the integer case, the random integers are slightly biased unless `maxval - minval` is an exact power of two. The bias is small for values of `maxval - minval` significantly smaller than the range of the output (either `2**32` or `2**64`). Args: shape: A 1-D integer Python array. The shape of the output tensor. minval: A 0-D Python value of type `dtype`. The lower bound on the range of random values to generate. Defaults to 0. maxval: A 0-D Python value of type `dtype`. The upper bound on the range of random values to generate. Defaults to 1 if `dtype` is floating point. dtype: The type of the output: `float32`, `float64`, `int32`, or `int64`. name: A name for the operation (optional). Returns: A tensor of the specified shape filled with random uniform values. """ return ops.RandomUniform(shape, minval, maxval)
def __call__(self, shape, dtype=None, **kwargs): if dtype is None: dtype = self.dtype return _ops.RandomUniform( shape=shape, low=self.minval, high=self.maxval, dtype=dtype.name, )
def __call__(self, shape, dtype=None): if dtype is None: dtype = self.dtype return ops.RandomUniform(shape, self.minval, self.maxval)