code: def get_ignored_functions() -> Set[Callable]:
      """
      Return public functions that cannot be overridden by ``__torch_function__``.
  
      Returns
      -------
      Set[Callable]
          A tuple of functions that are publicly available in the torch API but cannot
          be overridden with ``__torch_function__``. Mostly this is because none of the
          arguments of these functions are tensors or tensor-likes.
  
      Examples
      --------
      >>> torch.Tensor.as_subclass in torch.overrides.get_ignored_functions()
      True
      >>> torch.add in torch.overrides.get_ignored_functions()
      False
      """
      Tensor = torch.Tensor
      return {
          torch.typename,
          torch.is_tensor,
          torch.is_storage,
          torch.set_default_tensor_type,
          torch.set_default_device,
          torch.get_default_device,
          torch.set_rng_state,
          torch.get_rng_state,
          torch.manual_seed,
          torch.initial_seed,
          torch.seed,
          torch.save,
          torch.load,
          torch.set_printoptions,
          torch.fork,
          torch.get_default_dtype,
          torch.get_num_interop_threads,
          torch.get_num_threads,
          torch.init_num_threads,
          torch.import_ir_module,
          torch.import_ir_module_from_buffer,
          torch.is_anomaly_enabled,
          torch.is_anomaly_check_nan_enabled,
          torch.is_grad_enabled,
          torch.merge_type_from_type_comment,
          torch.parse_ir,
          torch.parse_schema,
          torch.parse_type_comment,
          torch.set_anomaly_enabled,
          torch.set_flush_denormal,
          torch.set_num_interop_threads,
          torch.set_num_threads,
          torch.wait,
          torch.as_tensor,
          torch.from_numpy,
          torch.get_device,
          torch.tensor,
          torch.default_generator,
          torch.has_cuda,
          torch.has_cudnn,
          torch.has_lapack,
          torch.device,
          torch.dtype,
          torch.finfo,
          torch.has_mkl,
          torch.has_mps,
          torch.has_mkldnn,
          torch.has_openmp,
          torch.iinfo,
          torch.memory_format,
          torch.qscheme,
          torch.set_grad_enabled,
          torch.no_grad,
          torch.enable_grad,
          torch.inference_mode,
          torch.is_inference_mode_enabled,
          torch.layout,
          torch.align_tensors,
          torch.arange,
          torch.as_strided,
          torch.bartlett_window,
          torch.blackman_window,
          torch.broadcast_shapes,
          torch.can_cast,
          torch.compile,
          torch.cudnn_affine_grid_generator,
          torch.cudnn_batch_norm,
          torch.cudnn_convolution,
          torch.cudnn_convolution_transpose,
          torch.cudnn_convolution_relu,
          torch.cudnn_convolution_add_relu,
          torch.cudnn_grid_sampler,
          torch.cudnn_is_acceptable,
          torch.empty,
          torch.empty_permuted,
          torch.empty_strided,
          torch.empty_quantized,
          torch.export.dynamic_dim,
          torch.export.export,
          torch.export.load,
          torch.export.register_dataclass,
          torch.export.save,
          torch.eye,
          torch.fft.fftfreq,
          torch.fft.rfftfreq,
          torch.from_file,
          torch.full,
          torch.fill,
          torch.hamming_window,
          torch.hann_window,
          torch.kaiser_window,
          torch.linspace,
          torch.logspace,
          torch.mkldnn_adaptive_avg_pool2d,
          torch.mkldnn_convolution,
          torch.mkldnn_max_pool2d,
          torch.mkldnn_max_pool3d,
          torch.mkldnn_linear_backward_weights,
          torch.mkldnn_rnn_layer,
          torch.normal,
          torch.ones,
          torch.promote_types,
          torch.rand,
          torch.randn,
          torch.randint,
          torch.randperm,
          torch.range,
          torch.result_type,
          torch.scalar_tensor,
          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.sym_constrain_range,
          torch.sym_constrain_range_for_size,
          torch.tril_indices,
          torch.triu_indices,
          torch.vander,
          torch.zeros,
          torch._jit_internal.boolean_dispatch,
          torch.nn.functional.assert_int_or_pair,
          torch.nn.functional.upsample,
          torch.nn.functional.upsample_bilinear,
          torch.nn.functional.upsample_nearest,
          torch.nn.functional.has_torch_function,
          torch.nn.functional.has_torch_function_unary,
          torch.nn.functional.has_torch_function_variadic,
          torch.nn.functional.handle_torch_function,
          torch.nn.functional.sigmoid,
          torch.nn.functional.hardsigmoid,
          torch.nn.functional.tanh,
          torch.nn.functional._canonical_mask,
          torch.nn.functional._none_or_dtype,
          # Doesn't actually take or return tensor arguments
          torch.nn.init.calculate_gain,
          # These are deprecated; don't test them
          torch.nn.init.uniform,
          torch.nn.init.normal,
          torch.nn.init.constant,
          torch.nn.init.eye,
          torch.nn.init.dirac,
          torch.nn.init.xavier_uniform,
          torch.nn.init.xavier_normal,
          torch.nn.init.kaiming_uniform,
          torch.nn.init.kaiming_normal,
          torch.nn.init.orthogonal,
          torch.nn.init.sparse,
          torch.nested.to_padded_tensor,
          has_torch_function,
          handle_torch_function,
          torch.set_autocast_enabled,
          torch.is_autocast_enabled,
          torch.clear_autocast_cache,
          torch.set_autocast_cpu_enabled,
          torch.is_autocast_cpu_enabled,
          torch.set_autocast_xla_enabled,
          torch.is_autocast_xla_enabled,
          torch.set_autocast_ipu_enabled,
          torch.is_autocast_ipu_enabled,
          torch.set_autocast_cpu_dtype,
          torch.get_autocast_cpu_dtype,
          torch.set_autocast_ipu_dtype,
          torch.get_autocast_ipu_dtype,
          torch.get_autocast_gpu_dtype,
          torch.set_autocast_gpu_dtype,
          torch.get_autocast_xla_dtype,
          torch.set_autocast_xla_dtype,
          torch.autocast_increment_nesting,
          torch.autocast_decrement_nesting,
          torch.is_autocast_cache_enabled,
          torch.set_autocast_cache_enabled,
          torch.nn.functional.hardswish,
          torch.is_vulkan_available,
          torch.are_deterministic_algorithms_enabled,
          torch.use_deterministic_algorithms,
          torch.is_deterministic_algorithms_warn_only_enabled,
          torch.set_deterministic_debug_mode,
          torch.get_deterministic_debug_mode,
          torch.set_float32_matmul_precision,
          torch.get_float32_matmul_precision,
          torch.unify_type_list,
          torch.is_warn_always_enabled,
          torch.set_warn_always,
          torch.vitals_enabled,
          torch.set_vital,
          torch.read_vitals,
          torch.vmap,
          torch.cond,
          torch.frombuffer,
          torch.asarray,
          torch._functional_sym_constrain_range,
          torch._make_dep_token,
          Tensor.__delitem__,
          Tensor.__dir__,
          Tensor.__getattribute__,
          Tensor.__init__,
          Tensor.__iter__,
          Tensor.__init_subclass__,
          Tensor.__delattr__,
          Tensor.__setattr__,
          Tensor.__torch_function__,
          Tensor.__torch_dispatch__,
          Tensor.__new__,
          Tensor.__class__,
          Tensor.__subclasshook__,
          Tensor.__hash__,
          Tensor.as_subclass,
          Tensor.eig,
          Tensor.lstsq,
          Tensor.reinforce,
          Tensor.new,
          Tensor.new_tensor,
          Tensor.new_empty,
          Tensor.new_empty_strided,
          Tensor.new_zeros,
          Tensor.new_ones,
          Tensor.new_full,
          Tensor._make_subclass,
          Tensor.solve,
          Tensor.symeig,
          Tensor.stride,
          Tensor.unflatten,
          Tensor.to_sparse_coo,
          Tensor.to_sparse_csr,
          Tensor.to_sparse_csc,
          Tensor.to_sparse_bsr,
          Tensor.to_sparse_bsc,
          Tensor._to_sparse,
          Tensor._to_sparse_csr,
          Tensor._to_sparse_csc,
          Tensor._to_sparse_bsr,
          Tensor._to_sparse_bsc,
          Tensor._typed_storage,
          Tensor._reduce_ex_internal,
          Tensor._fix_weakref,
          Tensor._view_func,
          Tensor._view_func_unsafe,
          Tensor._rev_view_func_unsafe,
          Tensor._make_wrapper_subclass,
          Tensor._python_dispatch.__get__,
          Tensor._has_symbolic_sizes_strides.__get__,
          Tensor._conj,
          Tensor._conj_physical,
          Tensor._lazy_clone,
          Tensor._neg_view,
          Tensor._is_zerotensor,
          Tensor._is_all_true,
          Tensor._is_any_true,
          Tensor._addmm_activation,
          Tensor.to_padded_tensor,
      }
  
imports: import __future__
  import collections
  import functools
  import types
  import warnings
  from typing import Dict, Set, List, Any, Callable, Iterable, Type, Tuple
  from functools import wraps
  import contextlib
  import torch
  from torch._C import _has_torch_function, _has_torch_function_unary, _has_torch_function_variadic, _add_docstr, _push_on_torch_function_stack, _pop_torch_function_stack, _get_function_stack_at, _len_torch_function_stack, _is_torch_function_mode_enabled
label_desc: Use image node_id 2 for calling a global function with example usage: get_ignored_functions() and returns: unknown