code: def dummy_1_build_fn(input_shape=(1,)):
      model = Sequential(
          [
              Embedding(
                  input_dim=9999,
                  output_dim=200,
                  input_length=100,
                  trainable=True,
              ),
              SpatialDropout1D(rate=0.5),
              Flatten(),
              Dense(100, activation="relu"),
              Dense(1, activation="sigmoid"),
          ]
      )
      model.compile(
          optimizer=RMSprop(lr=0.02, decay=0.001),
          loss=mean_absolute_error,
          metrics=["mean_absolute_error"],
      )
      return model
  
imports: from hyperparameter_hunter.compat.keras_helper import get_concise_params_dict
  from hyperparameter_hunter.compat.keras_helper import get_keras_attr
  from hyperparameter_hunter.compat.keras_helper import keras_callback_to_key
  from hyperparameter_hunter.compat.keras_helper import keras_initializer_to_dict
  from hyperparameter_hunter.compat.keras_helper import parameterize_compiled_keras_model
  from hyperparameter_hunter.compat.keras_helper import parameters_by_signature
  from hyperparameter_hunter import Integer
  from pkg_resources import get_distribution
  import pytest
  from keras import initializers
  from keras import callbacks
  from keras.layers import Dense, Dropout, Embedding, Flatten, SpatialDropout1D
  from keras.losses import binary_crossentropy, mean_absolute_error
  from keras.models import Sequential
  from keras.optimizers import Adam, RMSprop
label_desc: Use image node_id 2 for calling a global function with example usage: dummy_1_build_fn(input_shape) and returns: model