/**

* @license

* Copyright 2018 Google LLC. All Rights Reserved.

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at

*

* http://www.apache.org/licenses/LICENSE-2.0

*

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

* =============================================================================

*/

import {dispose, InferenceModel, io, ModelPredictConfig, NamedTensorMap, Tensor, util} from '@tensorflow/tfjs-core';

import * as tensorflow from '../data/compiled_api';

import {NamedTensorsMap, TensorInfo} from '../data/types';

import {OperationMapper} from '../operations/operation_mapper';

import {GraphExecutor} from './graph_executor';

import {ResourceManager} from './resource_manager';

// tslint:disable-next-line: no-imports-from-dist

import {decodeWeightsStream} from '@tensorflow/tfjs-core/dist/io/io_utils';

export const TFHUB_SEARCH_PARAM = '?tfjs-format=file';

export const DEFAULT_MODEL_NAME = 'model.json';

type Url = string|io.IOHandler|io.IOHandlerSync;

type UrlIOHandler<T extends Url> = T extends string ? io.IOHandler : T;

/**

* A `tf.GraphModel` is a directed, acyclic graph built from a

* SavedModel GraphDef and allows inference execution.

*

* A `tf.GraphModel` can only be created by loading from a model converted from

* a [TensorFlow SavedModel](https://www.tensorflow.org/guide/saved_model) using

* the command line converter tool and loaded via `tf.loadGraphModel`.

*

* @doc {heading: 'Models', subheading: 'Classes'}

*/

export class GraphModel<ModelURL extends Url = string | io.IOHandler> implements

}

/**

* Load a graph model given a URL to the model definition.

*

* Example of loading MobileNetV2 from a URL and making a prediction with a

* zeros input:

*

* ```js

* const modelUrl =

* 'https://storage.googleapis.com/tfjs-models/savedmodel/mobilenet_v2_1.0_224/model.json';

* const model = await tf.loadGraphModel(modelUrl);

* const zeros = tf.zeros([1, 224, 224, 3]);

* model.predict(zeros).print();

* ```

*

* Example of loading MobileNetV2 from a TF Hub URL and making a prediction

* with a zeros input:

*

* ```js

* const modelUrl =

* 'https://tfhub.dev/google/imagenet/mobilenet_v2_140_224/classification/2';

* const model = await tf.loadGraphModel(modelUrl, {fromTFHub: true});

* const zeros = tf.zeros([1, 224, 224, 3]);

* model.predict(zeros).print();

* ```

* @param modelUrl The url or an `io.IOHandler` that loads the model.

* @param options Options for the HTTP request, which allows to send

* credentials

* and custom headers.

*

* @doc {heading: 'Models', subheading: 'Loading'}

*/

export async function loadGraphModel(

}

/**

* Load a graph model given a synchronous IO handler with a 'load' method.

*

* @param modelSource The `io.IOHandlerSync` that loads the model, or the

* `io.ModelArtifacts` that encode the model, or a tuple of

* `[io.ModelJSON, ArrayBuffer]` of which the first element encodes the

* model and the second contains the weights.

*

* @doc {heading: 'Models', subheading: 'Loading'}

*/

export function loadGraphModelSync(

}

function getTFHubUrl(modelUrl: string): string {

}