code: def _pad_before_conv(x, padding, dims, data_format):
      if isinstance(padding, str):
          return x, padding
      elif isinstance(padding, int):
          pad_list = [(padding, padding)] * dims
      else:
          pad_list = padding
      if data_format[-1] == "C":
          pad_list = [(0, 0), *pad_list, (0, 0)]
      else:
          pad_list = [(0, 0), (0, 0), *pad_list]
      return tf.pad(x, pad_list, "CONSTANT"), "VALID"
  
imports: from typing import Optional, Tuple, Union, Sequence
  import tensorflow
  from tensorflow.python.types.core import Tensor
  import ivy
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_dtypes
  from .None import backend_version
  from ivy.functional.ivy.layers import _deconv_length, _get_x_data_format
label_desc: Use image node_id 3 for calling a global function with example usage: _pad_before_conv(x, padding, dims, data_format) and returns: tf,  str, x,  padding