/*******************************************************************************
 * 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.deeplearning4j.nn.modelimport.keras.layers.recurrent;

import org.deeplearning4j.nn.conf.dropout.Dropout;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.layers.LSTM;
import org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep;
import org.deeplearning4j.nn.conf.layers.util.MaskZeroLayer;
import org.deeplearning4j.nn.modelimport.keras.BaseDL4JTest;
import org.deeplearning4j.nn.modelimport.keras.KerasTestUtils;
import org.deeplearning4j.nn.modelimport.keras.config.Keras1LayerConfiguration;
import org.deeplearning4j.nn.modelimport.keras.config.Keras2LayerConfiguration;
import org.deeplearning4j.nn.modelimport.keras.config.KerasLayerConfiguration;
import org.deeplearning4j.nn.modelimport.keras.exceptions.InvalidKerasConfigurationException;
import org.deeplearning4j.nn.modelimport.keras.exceptions.UnsupportedKerasConfigurationException;
import org.deeplearning4j.nn.modelimport.keras.layers.embeddings.KerasEmbedding;
import org.deeplearning4j.nn.weights.IWeightInit;
import org.deeplearning4j.nn.weights.WeightInitXavier;
import org.junit.Assert;
import org.junit.Test;
import org.nd4j.linalg.learning.regularization.L1Regularization;
import org.nd4j.linalg.learning.regularization.L2Regularization;
import org.nd4j.linalg.learning.regularization.Regularization;

import java.util.*;

import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertNotNull;

/**
 * @author Max Pumperla
 */
public class KerasLSTMTest extends BaseDL4JTest {

    private final String ACTIVATION_KERAS = "linear";
    private final String ACTIVATION_DL4J = "identity";
    private final String LAYER_NAME = "lstm_layer";
    private final String INIT_KERAS = "glorot_normal";
    private final IWeightInit INIT_DL4J = new WeightInitXavier();
    private final double L1_REGULARIZATION = 0.01;
    private final double L2_REGULARIZATION = 0.02;
    private final double DROPOUT_KERAS = 0.3;
    private final double DROPOUT_DL4J = 1 - DROPOUT_KERAS;
    private final int N_OUT = 13;

    private Boolean[] returnSequences = new Boolean[]{true, false};
    private Boolean[] maskZero = new Boolean[]{true, false};
    private Integer keras1 = 1;
    private Integer keras2 = 2;
    private Keras1LayerConfiguration conf1 = new Keras1LayerConfiguration();
    private Keras2LayerConfiguration conf2 = new Keras2LayerConfiguration();

    @Test
    public void testLstmLayer() throws Exception {
        for (Boolean rs : returnSequences) {
            buildLstmLayer(conf1, keras1, rs);
            buildLstmLayer(conf2, keras2, rs);
        }
        for (Boolean mz : maskZero) {
            buildMaskZeroLstmLayer(conf1, keras1, mz);
            buildMaskZeroLstmLayer(conf2, keras2, mz);
        }
    }

    void buildLstmLayer(KerasLayerConfiguration conf, Integer kerasVersion, Boolean rs) throws Exception {
        String innerActivation = "hard_sigmoid";
        double lstmForgetBiasDouble = 1.0;
        String lstmForgetBiasString = "one";
        boolean lstmUnroll = true;

        Map<String, Object> layerConfig = new HashMap<>();
        layerConfig.put(conf.getLAYER_FIELD_CLASS_NAME(), conf.getLAYER_CLASS_NAME_LSTM());
        Map<String, Object> config = new HashMap<>();
        config.put(conf.getLAYER_FIELD_ACTIVATION(), ACTIVATION_KERAS);
        config.put(conf.getLAYER_FIELD_INNER_ACTIVATION(), innerActivation);
        config.put(conf.getLAYER_FIELD_NAME(), LAYER_NAME);
        if (kerasVersion == 1) {
            config.put(conf.getLAYER_FIELD_INNER_INIT(), INIT_KERAS);
            config.put(conf.getLAYER_FIELD_INIT(), INIT_KERAS);

        } else {
            Map<String, Object> init = new HashMap<>();
            init.put("class_name", conf.getINIT_GLOROT_NORMAL());
            config.put(conf.getLAYER_FIELD_INNER_INIT(), init);
            config.put(conf.getLAYER_FIELD_INIT(), init);
        }
        Map<String, Object> W_reg = new HashMap<>();
        W_reg.put(conf.getREGULARIZATION_TYPE_L1(), L1_REGULARIZATION);
        W_reg.put(conf.getREGULARIZATION_TYPE_L2(), L2_REGULARIZATION);
        config.put(conf.getLAYER_FIELD_W_REGULARIZER(), W_reg);
        config.put(conf.getLAYER_FIELD_RETURN_SEQUENCES(), rs);

        config.put(conf.getLAYER_FIELD_DROPOUT_W(), DROPOUT_KERAS);
        config.put(conf.getLAYER_FIELD_DROPOUT_U(), 0.0);
        config.put(conf.getLAYER_FIELD_FORGET_BIAS_INIT(), lstmForgetBiasString);
        config.put(conf.getLAYER_FIELD_OUTPUT_DIM(), N_OUT);
        config.put(conf.getLAYER_FIELD_UNROLL(), lstmUnroll);
        layerConfig.put(conf.getLAYER_FIELD_CONFIG(), config);
        layerConfig.put(conf.getLAYER_FIELD_KERAS_VERSION(), kerasVersion);

        LSTM layer;
        LastTimeStep lts;
        KerasLSTM kerasLstm = new KerasLSTM(layerConfig);
        if (rs) {
            InputType outputType = kerasLstm.getOutputType(InputType.recurrent(1337));
            assertEquals(outputType, InputType.recurrent(N_OUT));
            layer = (LSTM) kerasLstm.getLSTMLayer();
        } else {
            lts = (LastTimeStep) kerasLstm.getLSTMLayer();
            InputType outputType = kerasLstm.getOutputType(InputType.feedForward(1337));
            assertEquals(outputType, InputType.feedForward(N_OUT));
            layer = (LSTM) lts.getUnderlying();
        }
        assertEquals(ACTIVATION_DL4J, layer.getActivationFn().toString());
        assertEquals(LAYER_NAME, layer.getLayerName());
        assertEquals(INIT_DL4J, layer.getWeightInitFn());
        assertEquals(L1_REGULARIZATION, KerasTestUtils.getL1(layer), 0.0);
        assertEquals(L2_REGULARIZATION, KerasTestUtils.getL2(layer), 0.0);
        assertEquals(new Dropout(DROPOUT_DL4J), layer.getIDropout());
        assertEquals(lstmForgetBiasDouble, layer.getForgetGateBiasInit(), 0.0);
        assertEquals(N_OUT, layer.getNOut());

    }

    private void buildMaskZeroLstmLayer(KerasLayerConfiguration conf, Integer kerasVersion, Boolean maskZero)
            throws Exception {
        String innerActivation = "hard_sigmoid";
        String lstmForgetBiasString = "one";
        boolean lstmUnroll = true;

        Map<String, Object> layerConfig = new HashMap<>();
        layerConfig.put(conf.getLAYER_FIELD_CLASS_NAME(), conf.getLAYER_CLASS_NAME_LSTM());
        Map<String, Object> config = new HashMap<>();
        config.put(conf.getLAYER_FIELD_ACTIVATION(), ACTIVATION_KERAS);
        config.put(conf.getLAYER_FIELD_INNER_ACTIVATION(), innerActivation);
        config.put(conf.getLAYER_FIELD_NAME(), LAYER_NAME);
        if (kerasVersion == 1) {
            config.put(conf.getLAYER_FIELD_INNER_INIT(), INIT_KERAS);
            config.put(conf.getLAYER_FIELD_INIT(), INIT_KERAS);

        } else {
            Map<String, Object> init = new HashMap<>();
            init.put("class_name", conf.getINIT_GLOROT_NORMAL());
            config.put(conf.getLAYER_FIELD_INNER_INIT(), init);
            config.put(conf.getLAYER_FIELD_INIT(), init);
        }
        Map<String, Object> W_reg = new HashMap<>();
        W_reg.put(conf.getREGULARIZATION_TYPE_L1(), L1_REGULARIZATION);
        W_reg.put(conf.getREGULARIZATION_TYPE_L2(), L2_REGULARIZATION);
        config.put(conf.getLAYER_FIELD_W_REGULARIZER(), W_reg);

        config.put(conf.getLAYER_FIELD_DROPOUT_W(), DROPOUT_KERAS);
        config.put(conf.getLAYER_FIELD_DROPOUT_U(), 0.0);
        config.put(conf.getLAYER_FIELD_FORGET_BIAS_INIT(), lstmForgetBiasString);
        config.put(conf.getLAYER_FIELD_OUTPUT_DIM(), N_OUT);
        config.put(conf.getLAYER_FIELD_UNROLL(), lstmUnroll);
        config.put(conf.getLAYER_FIELD_RETURN_SEQUENCES(), true);

        layerConfig.put(conf.getLAYER_FIELD_CONFIG(), config);
        layerConfig.put(conf.getLAYER_FIELD_KERAS_VERSION(), kerasVersion);
        layerConfig.put(conf.getLAYER_FIELD_INBOUND_NODES(),
                Arrays.asList(Arrays.asList(
                        Arrays.asList("embedding"))));
        KerasEmbedding embedding = getEmbedding(maskZero);
        Map<String, KerasEmbedding> previousLayers = Collections.singletonMap("embedding", embedding);

        KerasLSTM kerasLstm = new KerasLSTM(layerConfig, previousLayers);
        Assert.assertEquals(kerasLstm.getLayer() instanceof MaskZeroLayer, maskZero);
    }

    private KerasEmbedding getEmbedding(boolean maskZero)
            throws InvalidKerasConfigurationException, UnsupportedKerasConfigurationException {
        KerasEmbedding embedding = new KerasEmbedding();
        embedding.setZeroMasking(maskZero);
        return embedding;
    }
}
