/*
 * Copyright 2018 Analytics Zoo Authors.
 *
 * 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.
 */

package com.intel.analytics.zoo.pipeline.inference;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;

public abstract class AbstractInferenceModel implements Serializable {
  private FloatInferenceModel model;
  private int supportedConcurrentNum = 1;

  public AbstractInferenceModel() {
  }

  public AbstractInferenceModel(int supportedConcurrentNum) {
    this.supportedConcurrentNum = supportedConcurrentNum;
  }

  public void load(String modelPath) {
    load(modelPath, null);
  }

  public void load(String modelPath, String weightPath) {
    this.model = InferenceModelFactory.loadFloatInferenceModel(modelPath, weightPath);
  }

  public void loadCaffe(String modelPath) {
    loadCaffe(modelPath, null);
  }

  public void loadCaffe(String modelPath, String weightPath) {
    this.model = InferenceModelFactory.loadFloatInferenceModelForCaffe(modelPath, weightPath);
  }

  public void loadTF(String modelPath) {
    this.model = InferenceModelFactory.loadFloatInferenceModelForTF(modelPath);
  }

  public void reload(String modelPath) {
    load(modelPath, null);
  }

  public void reload(String modelPath, String weightPath) {
    this.model = InferenceModelFactory.loadFloatInferenceModel(modelPath, weightPath);
  }

  @Deprecated
  public List<Float> predict(List<Float> input, int... shape) {
    List<Integer> inputShape = new ArrayList<Integer>();
    for (int s : shape) {
      inputShape.add(s);
    }
    return model.predict(input, inputShape);
  }

  public List<List<JTensor>> predict(List<JTensor> inputs) {
    return model.predict(inputs);
  }

}

@@ -653,16 +653,72 @@
 rence;%0A%0A
+import com.intel.analytics.zoo.pipeline.api.net.TFNet;%0A%0A
 import j
@@ -1686,24 +1686,417 @@
 TF(modelPath
+,%0A            1, 1, true);%0A  %7D%0A%0A  public void loadTF(String modelPath,%0A                     int intraOpParallelismThreads,%0A                     int interOpParallelismThreads,%0A                     boolean usePerSessionThreads) %7B%0A    this.model = InferenceModelFactory.loadFloatInferenceModelForTF(modelPath,%0A            intraOpParallelismThreads, interOpParallelismThreads, usePerSessionThreads
 );%0A  %7D%0A%0A  pu

support tfnet config (#463)