code: def __init__(self, seq_length=30, widths=[3, 4, 5], filters=100):
      super().__init__()
      self.conv1s = [
          Conv1D(filters=filters, kernel_size=w, padding="same")
          for w in widths
      ]
      self.pools = [MaxPooling1D(pool_size=seq_length) for w in widths]
  
file_path: textflint/textflint/input/model/test_model/textcnn_tf_model.py
imports: import tensorflow
  from tensorflow.keras.layers import Embedding, Conv1D, Dense, MaxPooling1D, Dropout
  from tensorflow.keras import Model
  from .glove_embedding import GloveEmbedding
label_desc: Use image node_id 1 to create a new CNNTextLayer object from inherited base classes: Model with example: obj = CNNTextLayer(seq_length, widths, filters)