/*
 *  ******************************************************************************
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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.nd4j.linalg.api.ops.custom;

import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.api.shape.options.ArrayOptionsHelper;
import org.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;

import java.util.Collections;
import java.util.List;
import java.util.Map;

public class BitCast extends DynamicCustomOp {
    public BitCast() {}

    private DataType dtype;

    public BitCast(INDArray in, DataType dataType, INDArray out) {
        this(in, dataType.toInt(), out);
    }

    public BitCast(INDArray in, int dataType, INDArray out) {
        inputArguments.add(in);
        outputArguments.add(out);
        iArguments.add(Long.valueOf(dataType));

        dtype = DataType.fromInt(dataType);
    }

    public BitCast(INDArray in, DataType dataType) {
        this(in, dataType.toInt());
    }

    public BitCast(INDArray in, int dataType) {
        inputArguments.add(in);
        iArguments.add(Long.valueOf(dataType));
        dtype = DataType.fromInt(dataType);
    }

    public BitCast(SameDiff sameDiff, SDVariable in, SDVariable dataType) {
        super("", sameDiff, new SDVariable[]{in, dataType});
    }

    @Override
    public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
        throw new UnsupportedOperationException("Use the new Tensorflow Importer instead. This method is now removed.");

    }

    @Override
    public String opName() {
        return "bitcast";
    }

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

    @Override
    public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes){
        int n = args().length;
        Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
        if(dtype == null) {
            if(!iArguments.isEmpty()) {
                dtype = DataType.fromInt(iArguments.get(0).intValue());
            }
        }
        return Collections.singletonList(dtype);
    }
}