/*
 *  ******************************************************************************
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 *  *
 *  * This program and the accompanying materials are made available under the
 *  * terms of the Apache License, Version 2.0 which is available at
 *  * https://www.apache.org/licenses/LICENSE-2.0.
 *  *
 *  *  See the NOTICE file distributed with this work for additional
 *  *  information regarding copyright ownership.
 *  * 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.
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 *  * SPDX-License-Identifier: Apache-2.0
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 */

package org.eclipse.deeplearning4j.frameworkimport.tensorflow;

import java.util.*;

public class TFGraphsSkipNodes {

    private static final Map<String, List<String>> SKIP_NODE_MAP = Collections.unmodifiableMap(
            new HashMap<String, List<String>>() {{
                //Note that we are testing equality with keep_prob of 1.0
                //The following are all dependent on rng seed and will fail. All other nodes pass.
                put("deep_mnist",
                        new ArrayList<>(Arrays.asList("dropout/dropout/random_uniform/RandomUniform",
                                "dropout/dropout/random_uniform/mul",
                                "dropout/dropout/random_uniform",
                                "dropout/dropout/add")));
            }});

    public static boolean skipNode(String modelName, String varName) {

        if (!SKIP_NODE_MAP.keySet().contains(modelName)) {
            return false;
        } else {
            for (String some_node : SKIP_NODE_MAP.get(modelName)) {
                if (some_node.equals(varName)) {
                    return true;
                }
            }
            return false;
        }

    }
}
