code: def dropout2d(input, p=0.5, training=True, inplace=False):
      if input.ndim < 2:
          raise ValueError(
              "Feature dropout requires at least 2 dimensions in the input"
          )
  
      ret = ivy.dropout2d(
          input, p, training=training, data_format="NCHW"
      )
      if inplace:
          ivy.inplace_update(input, ret)
          return input
      return ret
  
file_path: ivy/ivy/functional/frontends/torch/nn/functional/dropout_functions.py
imports: import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
label_desc: Use image node_id 4 for calling a global function with example usage: dropout2d(input, p, training, inplace) and returns: ret, input