import tensorflow as tf

from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, Dropout, BatchNormalization
from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint

# Функциональный API
inputs = Input(shape=(100,))
x = Dense(128, activation='relu')(inputs)
x = BatchNormalization()(x)
x = Dropout(0.5)(x)
x = Dense(64, activation='relu')(x)
x = Dropout(0.3)(x)
outputs = Dense(10, activation='softmax')(x)

model = Model(inputs=inputs, outputs=outputs)

# Компиляция модели
model.compile(
    optimizer='adam',
    loss='categorical_crossentropy',
    metrics=['accuracy', tf.keras.metrics.Precision(), tf.keras.metrics.Recall()]
)

# Callbacks для обучения
callbacks = [
    EarlyStopping(patience=10, restore_best_weights=True),
    ModelCheckpoint('best_model.h5', save_best_only=True)
]

# Обучение модели
history = model.fit(
    X_train, y_train,
    validation_split=0.2,
    epochs=100,
    batch_size=32,
    callbacks=callbacks,
    verbose=1
)