class_docstr: Operation after combining input features during feature fusiong.
code: def __init__(
      self,
      conv_bn_act_pattern,
      separable_conv,
      fpn_num_filters,
      act_type,
      data_format,
      name="op_after_combine",
  ):
      super().__init__(name=name)
      self.conv_bn_act_pattern = conv_bn_act_pattern
      self.separable_conv = separable_conv
      self.fpn_num_filters = fpn_num_filters
      self.act_type = act_type
      self.data_format = data_format
      if self.separable_conv:
          conv2d_layer = functools.partial(
              tf.keras.layers.SeparableConv2D, depth_multiplier=1
          )
      else:
          conv2d_layer = tf.keras.layers.Conv2D
  
      self.conv_op = conv2d_layer(
          filters=fpn_num_filters,
          kernel_size=(3, 3),
          padding="same",
          use_bias=not self.conv_bn_act_pattern,
          data_format=self.data_format,
          name="conv",
      )
      self.bn = utils.build_batch_norm(
          data_format=self.data_format, name="bn"
      )
  
imports: import functools
  from absl import logging
  import numpy
  import tensorflow
  import utils
  from .None import fpn_configs
label_desc: Use image node_id 1 to create a new OpAfterCombine object from inherited base classes: tf.keras.layers with example: obj = OpAfterCombine(conv_bn_act_pattern, separable_conv, fpn_num_filters, act_type, data_format, name)