attributeerror: 'sequential' object has no attribute "get_build_config"

[areflesh]

This issue appeared after switching from version 1.3.5 to 1.4.2. No code changes were done.

if args.auto_tune:
        print('AUTO TUNING ENABLED')
        def build_model(hp):

            model = Sequential()
            model.add(Dense(input_dims+1, input_dim=input_dims, activation='relu'))
            if args.normalize:
                model.add(tf.keras.layers.BatchNormalization())
            for i in range(hp.Int('num_layers', 1,5)):
                model.add(Dense(
                hp.Choice('units', [32, 64, 128, 256, 512, 1024]),
                activation='relu'))
                model.add(Dropout(args.dropout_rate))
            model.add(Dense(2, activation='softmax'))
            if args.gradient_clipping:
                optimizer = tf.keras.optimizers.Adam(clipnorm=args.gradient_clipping_value)
            else:
                optimizer = 'adam'
            model.compile(loss="kullback_leibler_divergence", optimizer=optimizer,
                    metrics=[
                        tf.keras.metrics.BinaryAccuracy(name='accuracy'),
                        tf.keras.metrics.Precision(name='precision'),
                        tf.keras.metrics.Recall(name='recall'),
                        tf.keras.metrics.AUC(name='auc'),
                        tf.keras.metrics.AUC(name='prc', curve='PR'),])
            return model
        if args.objective == 'prc':
            objective = keras_tuner.Objective("prc", direction="max")
        elif args.objective == 'loss':
            objective = keras_tuner.Objective("loss", direction="min")
        else:
            raise ValueError('objective must be either prc or loss')
        tuner = keras_tuner.BayesianOptimization(
            build_model,
            objective=objective,
            max_trials=args.max_trials,
            executions_per_trial=1,
            directory="s3://{}/{}/model/auto_tune".format(args.s3_bucket, args.s3_dir),
            overwrite=True)

        tuner.search_space_summary()
        tuner.search(dataset,
                epochs = args.max_epochs_tune,
                verbose = 2,
                class_weight = class_weights)
        print('TUNNING DONE. BEST HYPERPARAMETERS:')
        tuner.results_summary()

        model = tuner.get_best_models(num_models=1)[0]
        model.build()    

Issue appear after each trial and after third trial it says RuntimeError: Number of consecutive failures exceeded the limit of 3 and stops 

[haifeng-jin]

Hi @areflesh , it is probably because the TF version you use? We do model.get_build_config() under the hood. As I tested in colab, Sequential model class has this method.

[pacs27]

I have the same error when I use tensorflow version 2.10 which does not have this method

Tensorflow API v2.10 Layer

[haifeng-jin]

It has been fixed in master. Will be available in the next release. (1.4.3) It is much appreciated if anyone had the bug could test it on our master branch. Thanks!