tensor.py 文件源码

def view(self, *args):
        dst = self.new()
        if len(args) == 1 and isinstance(args[0], torch.Size):
            sizes = args[0]
        else:
            sizes = torch.Size(args)
        sizes = _infer_sizes(sizes, self.nelement())
        numel = reduce(lambda a, b: a * b, sizes) if len(sizes) > 0 else 0

        if numel != self.nelement():
            def format_size(size):
                return 'x'.join(str(v) for v in size) if len(size) > 0 else '0'
            raise ValueError(
                "view of size '{0}' is invalid for input of size '{1}'"
                .format(format_size(sizes), format_size(self.size())))
        if not self.is_contiguous():
            raise ValueError("input should be contiguous")
        if self.storage() is not None:
            dst.set_(self.storage(), self.storage_offset(), sizes)
        return dst