code: def _device_constructors():
      return {
          # standard ones
          torch.empty,
          torch.empty_permuted,
          torch.empty_strided,
          torch.empty_quantized,
          torch.ones,
          torch.arange,
          torch.bartlett_window,
          torch.blackman_window,
          torch.eye,
          torch.fft.fftfreq,
          torch.fft.rfftfreq,
          torch.full,
          torch.fill,
          torch.hamming_window,
          torch.hann_window,
          torch.kaiser_window,
          torch.linspace,
          torch.logspace,
          torch.nested.nested_tensor,
          # This function doesn't actually take a device argument
          # torch.normal,
          torch.ones,
          torch.rand,
          torch.randn,
          torch.randint,
          torch.randperm,
          torch.range,
          torch.sparse_coo_tensor,
          torch.sparse_compressed_tensor,
          torch.sparse_csr_tensor,
          torch.sparse_csc_tensor,
          torch.sparse_bsr_tensor,
          torch.sparse_bsc_tensor,
          torch.tril_indices,
          torch.triu_indices,
          torch.vander,
          torch.zeros,
          torch.asarray,
          # weird ones
          torch.tensor,
          torch.as_tensor,
          torch.scalar_tensor,
          torch.asarray,
      }
  
file_path: pytorch/torch/utils/_device.py
imports: import torch
  from torch.overrides import TorchFunctionMode
  from torch.utils._contextlib import context_decorator
  import functools
label_desc: Use image node_id 1 for calling a global function with example usage: _device_constructors() and returns: unknown