f3cfaf9b01b5c4dd99b4412e1c63c59f839d6cdf,python/mxnet/ndarray/numpy/random.py,,rayleigh,#Any#Any#Any#Any#,365

Before Change

        Drawn samples from the parameterized Rayleigh distribution.
    
    from ...numpy import ndarray as np_ndarray
    tensor_type_name = np_ndarray
    if ctx is None:
        ctx = current_context()
    if size == ():
        size = None
    is_tensor = isinstance(scale, tensor_type_name)
    if is_tensor:
        return _npi.rayleigh(scale, scale=None, size=size, ctx=ctx, out=out)
    else:
        return _npi.rayleigh(scale=scale, size=size, ctx=ctx, out=out)


def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None):
    
    multivariate_normal(mean, cov, size=None, check_valid=None, tol=None)

After Change

        Drawn samples from the parameterized Rayleigh distribution.
    
    if ctx is None:
        ctx = str(current_context())
    else:
        ctx = str(ctx)
    if size == ():
        size = None
    return _api_internal.rayleigh(scale, size, ctx, out)


def multivariate_normal(mean, cov, size=None, check_valid=None, tol=None):
    

Instances