create_simple_keras_model.py

from keras.models import Sequential
from keras.layers import Activation, Bidirectional, Conv1D, Dense
from keras.layers import Dropout, Embedding, LSTM, MaxPooling1D


def make_model(
    embedding_dim: int,
    dropout: float,
    filters: int,
    kernel_size: int,
    pool_size: int,
    lstm_output_size: int,
    metrics: list,
    vocab_size: int,
    maxlen: int,
):
    model = Sequential(
        [
            Embedding(vocab_size, embedding_dim, input_length=maxlen),
            Dropout(dropout),
            Conv1D(filters, kernel_size, padding="valid", activation="relu"),
            MaxPooling1D(pool_size=pool_size),
            Bidirectional(LSTM(lstm_output_size), merge_mode="ave"),
            Dense(1),
            Activation("sigmoid"),
        ]
    )

    model.compile(optimizer="adam", loss="binary_crossentropy", metrics=metrics)
    return model