code: def call(self, inputs, training=False):
      text = inputs
      pooled_outputs = []
      for conv, maxpool in zip(self.conv, self.maxpool):
          text_conv = conv(text)
          text_conv_maxpool = maxpool(text_conv)
          pooled_outputs.append(text_conv_maxpool)
      text_h = self.reshape(tf.concat(pooled_outputs, axis=-1))
      if training:
          text_h = self.dropout(text_h)
      return text_h
  
imports: import numpy
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras import layers, initializers, Input
  from tensorflow.python.keras.preprocessing.sequence import pad_sequences
  from ...utils import get_rng
  from ...utils.init_utils import uniform
label_desc: Use image node_id 2 for calling the TextProcessor obj's underlying member method code with example usage: obj.call(inputs, training) and returns: text_h