code: def test_torch_numpy_to_torch_style_args(dim, keepdim, input, other):
      # PyTorch-style keyword arguments
      assert (dim, keepdim, input, other) == mocked_func(
          dim=dim, keepdim=keepdim, input=input, other=other
      )
  
      # NumPy-style keyword arguments
      assert (dim, keepdim, input, other) == mocked_func(
          axis=dim, keepdims=keepdim, x=input, x2=other
      )
  
      # Mixed-style keyword arguments
      assert (dim, keepdim, input, other) == mocked_func(
          axis=dim, keepdim=keepdim, input=input, x2=other
      )
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_torch/test_func_wrapper.py
imports: from hypothesis import given, strategies
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy.functional.frontends.torch.func_wrapper import inputs_to_ivy_arrays, outputs_to_frontend_arrays, to_ivy_arrays_and_back, numpy_to_torch_style_args
  from ivy.functional.frontends.torch.tensor import Tensor
  import ivy.functional.frontends.torch
label_desc: Use image node_id 4 for calling a global function with example usage: test_torch_numpy_to_torch_style_args(dim, keepdim, input, other) without return types