/**
 * @license
 * Copyright 2018 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/// <amd-module name="@tensorflow/tfjs-layers/dist/keras_format/model_serialization" />
import { LayerSerialization } from './layers/layer_serialization';
import { TensorKeyArray } from './node_config';
import { TrainingConfig } from './training_config';
import { BaseSerialization } from './types';
export type ModelConfig = {
    name: string;
    layers: LayerSerialization[];
    input_layers: TensorKeyArray[];
    output_layers: TensorKeyArray[];
};
/**
 * A standard Keras JSON 'Model' configuration.
 */
export interface ModelSerialization extends BaseSerialization<'Model', ModelConfig> {
    backend?: string;
    keras_version?: string;
}
export type SequentialConfig = {
    layers: LayerSerialization[];
};
/**
 * A standard Keras JSON 'Sequential' configuration.
 */
export interface SequentialSerialization extends BaseSerialization<'Sequential', SequentialConfig> {
    backend?: string;
    keras_version?: string;
}
/**
 * A legacy Keras JSON 'Sequential' configuration.
 *
 * It was a bug that Keras Sequential models were recorded with
 * model_config.config as an array of layers, instead of a dict containing a
 * 'layers' entry.  While the bug has been fixed, we still need to be able to
 * read this legacy format.
 */
export type LegacySequentialSerialization = {
    class_name: 'Sequential';
    config: LayerSerialization[];
    backend?: string;
    keras_version?: string;
};
/**
 * Contains the description of a KerasModel, as well as the configuration
 * necessary to train that model.
 */
export type KerasFileSerialization = {
    model_config: ModelSerialization | SequentialSerialization | LegacySequentialSerialization;
    training_config: TrainingConfig;
};