torch.full_like#
- torch.full_like(input,fill_value,\*,dtype=None,layout=torch.strided,device=None,requires_grad=False,memory_format=torch.preserve_format)→Tensor#
Returns a tensor with the same size as
inputfilled withfill_value.torch.full_like(input,fill_value)is equivalent totorch.full(input.size(),fill_value,dtype=input.dtype,layout=input.layout,device=input.device).- Parameters:
input (Tensor) – the size of
inputwill determine size of the output tensor.fill_value – the number to fill the output tensor with.
- Keyword Arguments:
dtype (
torch.dtype, optional) – the desired data type of returned Tensor.Default: ifNone, defaults to the dtype ofinput.layout (
torch.layout, optional) – the desired layout of returned tensor.Default: ifNone, defaults to the layout ofinput.device (
torch.device, optional) – the desired device of returned tensor.Default: ifNone, defaults to the device ofinput.requires_grad (bool,optional) – If autograd should record operations on thereturned tensor. Default:
False.memory_format (
torch.memory_format, optional) – the desired memory format ofreturned Tensor. Default:torch.preserve_format.
Example:
>>>x=torch.ones(2,3)>>>torch.full_like(x,3.141592)tensor([[ 3.1416, 3.1416, 3.1416], [ 3.1416, 3.1416, 3.1416]])>>>torch.full_like(x,7)tensor([[7., 7., 7.], [7., 7., 7.]])>>>torch.full_like(x,0.5,dtype=torch.int32)tensor([[0, 0, 0], [0, 0, 0]], dtype=torch.int32)>>>y=torch.randn(3,4,dtype=torch.float64)>>>torch.full_like(y,-1.0)tensor([[-1., -1., -1., -1.], [-1., -1., -1., -1.], [-1., -1., -1., -1.]], dtype=torch.float64)
