/*******************************************************************************
 * Copyright (c) 2015-2018 Skymind, Inc.
 *
 * 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.
 *
 * 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.
 *
 * SPDX-License-Identifier: Apache-2.0
 ******************************************************************************/

package org.nd4j.linalg.api.ops.impl.transforms.custom;

import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.descriptors.properties.AttributeAdapter;
import org.nd4j.imports.descriptors.properties.PropertyMapping;
import org.nd4j.imports.descriptors.properties.adapters.StringNotEqualsAdapter;
import org.nd4j.imports.graphmapper.tf.TFGraphMapper;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.*;

@Slf4j
public class ParallelConcat extends DynamicCustomOp {

    public ParallelConcat() {
        // we know that axis is always 0 for PC
        iArguments.add(0L);
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
        TFGraphMapper.getInstance().initFunctionFromProperties(nodeDef.getOp(), this, attributesForNode, nodeDef, graph);
        // We might want to import everything here? i.e. shape in advance?
    }

    @Override
    public String opName() {
        // :)
        return "ParallelConcat";
    }


    @Override
    public int getNumOutputs() {
        return 1;
    }

    @Override
    public String tensorflowName() {
        return "ParallelConcat";
    }

    @Override
    public Map<String, Map<String, AttributeAdapter>> attributeAdaptersForFunction() {
        Map<String, Map<String, AttributeAdapter>> ret = new HashMap<>();
        Map<String, AttributeAdapter> tfMappings = new LinkedHashMap<>();

        return ret;
    }

    @Override
    public Map<String, Map<String, PropertyMapping>> mappingsForFunction() {
        Map<String, Map<String, PropertyMapping>> ret = new HashMap<>();
        Map<String, PropertyMapping> map = new HashMap<>();

        return ret;
    }

    @Override
    public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
        DataType first = dataTypes.get(0);
        for(int i=1; i<dataTypes.size(); i++ ){
            DataType dt = dataTypes.get(i);
            Preconditions.checkState(first == dt, "Data types must all be equal: got %s", dataTypes);
        }
        return Collections.singletonList(first);
    }
}
