/*
 * Copyright (C) 2017 The Android Open Source Project
 *
 * 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.
 */

#include <gmock/gmock-matchers.h>
#include <gtest/gtest.h>

#include <vector>

#include "LSTM.h"
#include "NeuralNetworksWrapper.h"

namespace android {
namespace nn {
namespace wrapper {

using ::testing::Each;
using ::testing::FloatNear;
using ::testing::Matcher;

namespace {

std::vector<Matcher<float>> ArrayFloatNear(const std::vector<float>& values,
                                           float max_abs_error = 1.e-5) {
    std::vector<Matcher<float>> matchers;
    matchers.reserve(values.size());
    for (const float& v : values) {
        matchers.emplace_back(FloatNear(v, max_abs_error));
    }
    return matchers;
}

}  // anonymous namespace

#define FOR_ALL_INPUT_AND_WEIGHT_TENSORS(ACTION) \
    ACTION(Input)                                \
    ACTION(InputToInputWeights)                  \
    ACTION(InputToCellWeights)                   \
    ACTION(InputToForgetWeights)                 \
    ACTION(InputToOutputWeights)                 \
    ACTION(RecurrentToInputWeights)              \
    ACTION(RecurrentToCellWeights)               \
    ACTION(RecurrentToForgetWeights)             \
    ACTION(RecurrentToOutputWeights)             \
    ACTION(CellToInputWeights)                   \
    ACTION(CellToForgetWeights)                  \
    ACTION(CellToOutputWeights)                  \
    ACTION(InputGateBias)                        \
    ACTION(CellGateBias)                         \
    ACTION(ForgetGateBias)                       \
    ACTION(OutputGateBias)                       \
    ACTION(ProjectionWeights)                    \
    ACTION(ProjectionBias)                       \
    ACTION(OutputStateIn)                        \
    ACTION(CellStateIn)

// For all output and intermediate states
#define FOR_ALL_OUTPUT_TENSORS(ACTION) \
    ACTION(ScratchBuffer)              \
    ACTION(OutputStateOut)             \
    ACTION(CellStateOut)               \
    ACTION(Output)

class LSTMOpModel {
   public:
    LSTMOpModel(uint32_t n_batch, uint32_t n_input, uint32_t n_cell, uint32_t n_output,
                bool use_cifg, bool use_peephole, bool use_projection_weights,
                bool use_projection_bias, float cell_clip, float proj_clip,
                const std::vector<std::vector<uint32_t>>& input_shapes0)
        : n_input_(n_input),
          n_output_(n_output),
          use_cifg_(use_cifg),
          use_peephole_(use_peephole),
          use_projection_weights_(use_projection_weights),
          use_projection_bias_(use_projection_bias),
          activation_(ActivationFn::kActivationTanh),
          cell_clip_(cell_clip),
          proj_clip_(proj_clip) {
        std::vector<uint32_t> inputs;
        std::vector<std::vector<uint32_t>> input_shapes(input_shapes0);

        input_shapes.push_back({n_batch, n_output});
        input_shapes.push_back({n_batch, n_cell});
        auto it = input_shapes.begin();

        // Input and weights
#define AddInput(X)                                     \
    OperandType X##OpndTy(Type::TENSOR_FLOAT32, *it++); \
    inputs.push_back(model_.addOperand(&X##OpndTy));

        FOR_ALL_INPUT_AND_WEIGHT_TENSORS(AddInput);

#undef AddOperand

        // Parameters
        OperandType ActivationOpndTy(Type::INT32, {});
        inputs.push_back(model_.addOperand(&ActivationOpndTy));
        OperandType CellClipOpndTy(Type::FLOAT32, {});
        inputs.push_back(model_.addOperand(&CellClipOpndTy));
        OperandType ProjClipOpndTy(Type::FLOAT32, {});
        inputs.push_back(model_.addOperand(&ProjClipOpndTy));

        // Output and other intermediate state
        std::vector<std::vector<uint32_t>> output_shapes{
                {n_batch, n_cell * (use_cifg ? 3 : 4)},
                {n_batch, n_output},
                {n_batch, n_cell},
                {n_batch, n_output},
        };
        std::vector<uint32_t> outputs;

        auto it2 = output_shapes.begin();

#define AddOutput(X)                                     \
    OperandType X##OpndTy(Type::TENSOR_FLOAT32, *it2++); \
    outputs.push_back(model_.addOperand(&X##OpndTy));

        FOR_ALL_OUTPUT_TENSORS(AddOutput);

#undef AddOutput

        model_.addOperation(ANEURALNETWORKS_LSTM, inputs, outputs);
        model_.identifyInputsAndOutputs(inputs, outputs);

        Input_.insert(Input_.end(), n_batch * n_input, 0.f);
        OutputStateIn_.insert(OutputStateIn_.end(), n_batch * n_output, 0.f);
        CellStateIn_.insert(CellStateIn_.end(), n_batch * n_cell, 0.f);

        auto multiAll = [](const std::vector<uint32_t>& dims) -> uint32_t {
            uint32_t sz = 1;
            for (uint32_t d : dims) {
                sz *= d;
            }
            return sz;
        };

        it2 = output_shapes.begin();

#define ReserveOutput(X) X##_.insert(X##_.end(), multiAll(*it2++), 0.f);

        FOR_ALL_OUTPUT_TENSORS(ReserveOutput);

#undef ReserveOutput

        model_.finish();
    }

#define DefineSetter(X) \
    void Set##X(const std::vector<float>& f) { X##_.insert(X##_.end(), f.begin(), f.end()); }

    FOR_ALL_INPUT_AND_WEIGHT_TENSORS(DefineSetter);

#undef DefineSetter

    void ResetOutputState() {
        std::fill(OutputStateIn_.begin(), OutputStateIn_.end(), 0.f);
        std::fill(OutputStateOut_.begin(), OutputStateOut_.end(), 0.f);
    }

    void ResetCellState() {
        std::fill(CellStateIn_.begin(), CellStateIn_.end(), 0.f);
        std::fill(CellStateOut_.begin(), CellStateOut_.end(), 0.f);
    }

    void SetInput(int offset, float* begin, float* end) {
        for (; begin != end; begin++, offset++) {
            Input_[offset] = *begin;
        }
    }

    uint32_t num_inputs() const { return n_input_; }
    uint32_t num_outputs() const { return n_output_; }

    const std::vector<float>& GetOutput() const { return Output_; }

    void Invoke() {
        ASSERT_TRUE(model_.isValid());

        OutputStateIn_.swap(OutputStateOut_);
        CellStateIn_.swap(CellStateOut_);

        Compilation compilation(&model_);
        compilation.finish();
        Execution execution(&compilation);
#define SetInputOrWeight(X)                                                                       \
    ASSERT_EQ(                                                                                    \
            execution.setInput(LSTMCell::k##X##Tensor, X##_.data(), sizeof(float) * X##_.size()), \
            Result::NO_ERROR);

        FOR_ALL_INPUT_AND_WEIGHT_TENSORS(SetInputOrWeight);

#undef SetInputOrWeight

#define SetOutput(X)                                                                               \
    ASSERT_EQ(                                                                                     \
            execution.setOutput(LSTMCell::k##X##Tensor, X##_.data(), sizeof(float) * X##_.size()), \
            Result::NO_ERROR);

        FOR_ALL_OUTPUT_TENSORS(SetOutput);

#undef SetOutput

        if (use_cifg_) {
            execution.setInput(LSTMCell::kInputToInputWeightsTensor, nullptr, 0);
            execution.setInput(LSTMCell::kRecurrentToInputWeightsTensor, nullptr, 0);
        }

        if (use_peephole_) {
            if (use_cifg_) {
                execution.setInput(LSTMCell::kCellToInputWeightsTensor, nullptr, 0);
            }
        } else {
            execution.setInput(LSTMCell::kCellToInputWeightsTensor, nullptr, 0);
            execution.setInput(LSTMCell::kCellToForgetWeightsTensor, nullptr, 0);
            execution.setInput(LSTMCell::kCellToOutputWeightsTensor, nullptr, 0);
        }

        if (use_projection_weights_) {
            if (!use_projection_bias_) {
                execution.setInput(LSTMCell::kProjectionBiasTensor, nullptr, 0);
            }
        } else {
            execution.setInput(LSTMCell::kProjectionWeightsTensor, nullptr, 0);
            execution.setInput(LSTMCell::kProjectionBiasTensor, nullptr, 0);
        }

        ASSERT_EQ(execution.setInput(LSTMCell::kActivationParam, &activation_, sizeof(activation_)),
                  Result::NO_ERROR);
        ASSERT_EQ(execution.setInput(LSTMCell::kCellClipParam, &cell_clip_, sizeof(cell_clip_)),
                  Result::NO_ERROR);
        ASSERT_EQ(execution.setInput(LSTMCell::kProjClipParam, &proj_clip_, sizeof(proj_clip_)),
                  Result::NO_ERROR);

        ASSERT_EQ(execution.compute(), Result::NO_ERROR);
    }

   private:
    Model model_;
    // Execution execution_;
    const uint32_t n_input_;
    const uint32_t n_output_;

    const bool use_cifg_;
    const bool use_peephole_;
    const bool use_projection_weights_;
    const bool use_projection_bias_;

    const int activation_;
    const float cell_clip_;
    const float proj_clip_;

#define DefineTensor(X) std::vector<float> X##_;

    FOR_ALL_INPUT_AND_WEIGHT_TENSORS(DefineTensor);
    FOR_ALL_OUTPUT_TENSORS(DefineTensor);

#undef DefineTensor
};

TEST(LSTMOpTest, BlackBoxTestNoCifgNoPeepholeNoProjectionNoClipping) {
    const int n_batch = 1;
    const int n_input = 2;
    // n_cell and n_output have the same size when there is no projection.
    const int n_cell = 4;
    const int n_output = 4;

    LSTMOpModel lstm(n_batch, n_input, n_cell, n_output,
                     /*use_cifg=*/false, /*use_peephole=*/false,
                     /*use_projection_weights=*/false,
                     /*use_projection_bias=*/false,
                     /*cell_clip=*/0.0, /*proj_clip=*/0.0,
                     {
                             {n_batch, n_input},  // input tensor

                             {n_cell, n_input},  // input_to_input_weight tensor
                             {n_cell, n_input},  // input_to_forget_weight tensor
                             {n_cell, n_input},  // input_to_cell_weight tensor
                             {n_cell, n_input},  // input_to_output_weight tensor

                             {n_cell, n_output},  // recurrent_to_input_weight tensor
                             {n_cell, n_output},  // recurrent_to_forget_weight tensor
                             {n_cell, n_output},  // recurrent_to_cell_weight tensor
                             {n_cell, n_output},  // recurrent_to_output_weight tensor

                             {0},  // cell_to_input_weight tensor
                             {0},  // cell_to_forget_weight tensor
                             {0},  // cell_to_output_weight tensor

                             {n_cell},  // input_gate_bias tensor
                             {n_cell},  // forget_gate_bias tensor
                             {n_cell},  // cell_bias tensor
                             {n_cell},  // output_gate_bias tensor

                             {0, 0},  // projection_weight tensor
                             {0},     // projection_bias tensor
                     });

    lstm.SetInputToInputWeights({-0.45018822, -0.02338299, -0.0870589, -0.34550029, 0.04266912,
                                 -0.15680569, -0.34856534, 0.43890524});

    lstm.SetInputToCellWeights({-0.50013041, 0.1370284, 0.11810488, 0.2013163, -0.20583314,
                                0.44344562, 0.22077113, -0.29909778});

    lstm.SetInputToForgetWeights({0.09701663, 0.20334584, -0.50592935, -0.31343272, -0.40032279,
                                  0.44781327, 0.01387155, -0.35593212});

    lstm.SetInputToOutputWeights({-0.25065863, -0.28290087, 0.04613829, 0.40525138, 0.44272184,
                                  0.03897077, -0.1556896, 0.19487578});

    lstm.SetInputGateBias({0., 0., 0., 0.});

    lstm.SetCellGateBias({0., 0., 0., 0.});

    lstm.SetForgetGateBias({1., 1., 1., 1.});

    lstm.SetOutputGateBias({0., 0., 0., 0.});

    lstm.SetRecurrentToInputWeights({-0.0063535, -0.2042388, 0.31454784, -0.35746509, 0.28902304,
                                     0.08183324, -0.16555229, 0.02286911, -0.13566875, 0.03034258,
                                     0.48091322, -0.12528998, 0.24077177, -0.51332325, -0.33502164,
                                     0.10629296});

    lstm.SetRecurrentToCellWeights({-0.3407414, 0.24443203, -0.2078532, 0.26320225, 0.05695659,
                                    -0.00123841, -0.4744786, -0.35869038, -0.06418842, -0.13502428,
                                    -0.501764, 0.22830659, -0.46367589, 0.26016325, -0.03894562,
                                    -0.16368064});

    lstm.SetRecurrentToForgetWeights({-0.48684245, -0.06655136, 0.42224967, 0.2112639, 0.27654213,
                                      0.20864892, -0.07646349, 0.45877004, 0.00141793, -0.14609534,
                                      0.36447752, 0.09196436, 0.28053468, 0.01560611, -0.20127171,
                                      -0.01140004});

    lstm.SetRecurrentToOutputWeights({0.43385774, -0.17194885, 0.2718237, 0.09215671, 0.24107647,
                                      -0.39835793, 0.18212086, 0.01301402, 0.48572797, -0.50656658,
                                      0.20047462, -0.20607421, -0.51818722, -0.15390486, 0.0468148,
                                      0.39922136});

    static float lstm_input[] = {2., 3., 3., 4., 1., 1.};
    static float lstm_golden_output[] = {-0.02973187, 0.1229473,  0.20885126, -0.15358765,
                                         -0.03716109, 0.12507336, 0.41193449, -0.20860538,
                                         -0.15053082, 0.09120187, 0.24278517, -0.12222792};

    // Resetting cell_state and output_state
    lstm.ResetCellState();
    lstm.ResetOutputState();

    const int input_sequence_size = sizeof(lstm_input) / sizeof(float) / (lstm.num_inputs());
    for (int i = 0; i < input_sequence_size; i++) {
        float* batch0_start = lstm_input + i * lstm.num_inputs();
        float* batch0_end = batch0_start + lstm.num_inputs();

        lstm.SetInput(0, batch0_start, batch0_end);

        lstm.Invoke();

        float* golden_start = lstm_golden_output + i * lstm.num_outputs();
        float* golden_end = golden_start + lstm.num_outputs();
        std::vector<float> expected;
        expected.insert(expected.end(), golden_start, golden_end);
        EXPECT_THAT(lstm.GetOutput(), ElementsAreArray(ArrayFloatNear(expected)));
    }
}

TEST(LSTMOpTest, BlackBoxTestWithCifgWithPeepholeNoProjectionNoClipping) {
    const int n_batch = 1;
    const int n_input = 2;
    // n_cell and n_output have the same size when there is no projection.
    const int n_cell = 4;
    const int n_output = 4;

    LSTMOpModel lstm(n_batch, n_input, n_cell, n_output,
                     /*use_cifg=*/true, /*use_peephole=*/true,
                     /*use_projection_weights=*/false,
                     /*use_projection_bias=*/false,
                     /*cell_clip=*/0.0, /*proj_clip=*/0.0,
                     {
                             {n_batch, n_input},  // input tensor

                             {0, 0},             // input_to_input_weight tensor
                             {n_cell, n_input},  // input_to_forget_weight tensor
                             {n_cell, n_input},  // input_to_cell_weight tensor
                             {n_cell, n_input},  // input_to_output_weight tensor

                             {0, 0},              // recurrent_to_input_weight tensor
                             {n_cell, n_output},  // recurrent_to_forget_weight tensor
                             {n_cell, n_output},  // recurrent_to_cell_weight tensor
                             {n_cell, n_output},  // recurrent_to_output_weight tensor

                             {0},       // cell_to_input_weight tensor
                             {n_cell},  // cell_to_forget_weight tensor
                             {n_cell},  // cell_to_output_weight tensor

                             {n_cell},  // input_gate_bias tensor
                             {n_cell},  // forget_gate_bias tensor
                             {n_cell},  // cell_bias tensor
                             {n_cell},  // output_gate_bias tensor

                             {0, 0},  // projection_weight tensor
                             {0},     // projection_bias tensor
                     });

    lstm.SetInputToCellWeights({-0.49770179, -0.27711356, -0.09624726, 0.05100781, 0.04717243,
                                0.48944736, -0.38535351, -0.17212132});

    lstm.SetInputToForgetWeights({-0.55291498, -0.42866567, 0.13056988, -0.3633365, -0.22755712,
                                  0.28253698, 0.24407166, 0.33826375});

    lstm.SetInputToOutputWeights({0.10725588, -0.02335852, -0.55932593, -0.09426838, -0.44257352,
                                  0.54939759, 0.01533556, 0.42751634});

    lstm.SetCellGateBias({0., 0., 0., 0.});

    lstm.SetForgetGateBias({1., 1., 1., 1.});

    lstm.SetOutputGateBias({0., 0., 0., 0.});

    lstm.SetRecurrentToCellWeights({0.54066205, -0.32668582, -0.43562764, -0.56094903, 0.42957711,
                                    0.01841056, -0.32764608, -0.33027974, -0.10826075, 0.20675004,
                                    0.19069612, -0.03026325, -0.54532051, 0.33003211, 0.44901288,
                                    0.21193194});

    lstm.SetRecurrentToForgetWeights({-0.13832897, -0.0515101, -0.2359007, -0.16661474, -0.14340827,
                                      0.36986142, 0.23414481, 0.55899, 0.10798943, -0.41174671,
                                      0.17751795, -0.34484994, -0.35874045, -0.11352962, 0.27268326,
                                      0.54058349});

    lstm.SetRecurrentToOutputWeights({0.41613156, 0.42610586, -0.16495961, -0.5663873, 0.30579174,
                                      -0.05115908, -0.33941799, 0.23364776, 0.11178309, 0.09481031,
                                      -0.26424935, 0.46261835, 0.50248802, 0.26114327, -0.43736315,
                                      0.33149987});

    lstm.SetCellToForgetWeights({0.47485286, -0.51955009, -0.24458408, 0.31544167});
    lstm.SetCellToOutputWeights({-0.17135078, 0.82760304, 0.85573703, -0.77109635});

    static float lstm_input[] = {2., 3., 3., 4., 1., 1.};
    static float lstm_golden_output[] = {-0.36444446, -0.00352185, 0.12886585, -0.05163646,
                                         -0.42312205, -0.01218222, 0.24201041, -0.08124574,
                                         -0.358325,   -0.04621704, 0.21641694, -0.06471302};

    // Resetting cell_state and output_state
    lstm.ResetCellState();
    lstm.ResetOutputState();

    const int input_sequence_size = sizeof(lstm_input) / sizeof(float) / (lstm.num_inputs());
    for (int i = 0; i < input_sequence_size; i++) {
        float* batch0_start = lstm_input + i * lstm.num_inputs();
        float* batch0_end = batch0_start + lstm.num_inputs();

        lstm.SetInput(0, batch0_start, batch0_end);

        lstm.Invoke();

        float* golden_start = lstm_golden_output + i * lstm.num_outputs();
        float* golden_end = golden_start + lstm.num_outputs();
        std::vector<float> expected;
        expected.insert(expected.end(), golden_start, golden_end);
        EXPECT_THAT(lstm.GetOutput(), ElementsAreArray(ArrayFloatNear(expected)));
    }
}

TEST(LSTMOpTest, BlackBoxTestWithPeepholeWithProjectionNoClipping) {
    const int n_batch = 2;
    const int n_input = 5;
    const int n_cell = 20;
    const int n_output = 16;

    LSTMOpModel lstm(n_batch, n_input, n_cell, n_output,
                     /*use_cifg=*/false, /*use_peephole=*/true,
                     /*use_projection_weights=*/true,
                     /*use_projection_bias=*/false,
                     /*cell_clip=*/0.0, /*proj_clip=*/0.0,
                     {
                             {n_batch, n_input},  // input tensor

                             {n_cell, n_input},  // input_to_input_weight tensor
                             {n_cell, n_input},  // input_to_forget_weight tensor
                             {n_cell, n_input},  // input_to_cell_weight tensor
                             {n_cell, n_input},  // input_to_output_weight tensor

                             {n_cell, n_output},  // recurrent_to_input_weight tensor
                             {n_cell, n_output},  // recurrent_to_forget_weight tensor
                             {n_cell, n_output},  // recurrent_to_cell_weight tensor
                             {n_cell, n_output},  // recurrent_to_output_weight tensor

                             {n_cell},  // cell_to_input_weight tensor
                             {n_cell},  // cell_to_forget_weight tensor
                             {n_cell},  // cell_to_output_weight tensor

                             {n_cell},  // input_gate_bias tensor
                             {n_cell},  // forget_gate_bias tensor
                             {n_cell},  // cell_bias tensor
                             {n_cell},  // output_gate_bias tensor

                             {n_output, n_cell},  // projection_weight tensor
                             {0},                 // projection_bias tensor
                     });

    lstm.SetInputToInputWeights(
            {0.021393683,  0.06124551,   0.046905167,   -0.014657677, -0.03149463,   0.09171803,
             0.14647801,   0.10797193,   -0.0057968358, 0.0019193048, -0.2726754,    0.10154029,
             -0.018539885, 0.080349885,  -0.10262385,   -0.022599787, -0.09121155,   -0.008675967,
             -0.045206103, -0.0821282,   -0.008045952,  0.015478081,  0.055217247,   0.038719587,
             0.044153627,  -0.06453243,  0.05031825,    -0.046935108, -0.008164439,  0.014574226,
             -0.1671009,   -0.15519552,  -0.16819797,   -0.13971269,  -0.11953059,   0.25005487,
             -0.22790983,  0.009855087,  -0.028140958,  -0.11200698,  0.11295408,    -0.0035217577,
             0.054485075,  0.05184695,   0.064711206,   0.10989193,   0.11674786,    0.03490607,
             0.07727357,   0.11390585,   -0.1863375,    -0.1034451,   -0.13945189,   -0.049401227,
             -0.18767063,  0.042483903,  0.14233552,    0.13832581,   0.18350165,    0.14545603,
             -0.028545704, 0.024939531,  0.050929718,   0.0076203286, -0.0029723682, -0.042484224,
             -0.11827596,  -0.09171104,  -0.10808628,   -0.16327988,  -0.2273378,    -0.0993647,
             -0.017155107, 0.0023917493, 0.049272764,   0.0038534778, 0.054764505,   0.089753784,
             0.06947234,   0.08014476,   -0.04544234,   -0.0497073,   -0.07135631,   -0.048929106,
             -0.004042012, -0.009284026, 0.018042054,   0.0036860977, -0.07427302,   -0.11434604,
             -0.018995456, 0.031487543,  0.012834908,   0.019977754,  0.044256654,   -0.39292613,
             -0.18519334,  -0.11651281,  -0.06809892,   0.011373677});

    lstm.SetInputToForgetWeights(
            {-0.0018401089, -0.004852237, 0.03698424,   0.014181704,  0.028273236,   -0.016726194,
             -0.05249759,   -0.10204261,  0.00861066,   -0.040979505, -0.009899187,  0.01923892,
             -0.028177269,  -0.08535103,  -0.14585495,  0.10662567,   -0.01909731,   -0.017883534,
             -0.0047269356, -0.045103323, 0.0030784295, 0.076784775,  0.07463696,    0.094531395,
             0.0814421,     -0.12257899,  -0.033945758, -0.031303465, 0.045630626,   0.06843887,
             -0.13492945,   -0.012480007, -0.0811829,   -0.07224499,  -0.09628791,   0.045100946,
             0.0012300825,  0.013964662,  0.099372394,  0.02543059,   0.06958324,    0.034257296,
             0.0482646,     0.06267997,   0.052625068,  0.12784666,   0.07077897,    0.025725935,
             0.04165009,    0.07241905,   0.018668644,  -0.037377294, -0.06277783,   -0.08833636,
             -0.040120605,  -0.011405586, -0.007808335, -0.010301386, -0.005102167,  0.027717464,
             0.05483423,    0.11449111,   0.11289652,   0.10939839,   0.13396506,    -0.08402166,
             -0.01901462,   -0.044678304, -0.07720565,  0.014350063,  -0.11757958,   -0.0652038,
             -0.08185733,   -0.076754324, -0.092614375, 0.10405491,   0.052960336,   0.035755895,
             0.035839386,   -0.012540553, 0.036881298,  0.02913376,   0.03420159,    0.05448447,
             -0.054523353,  0.02582715,   0.02327355,   -0.011857179, -0.0011980024, -0.034641717,
             -0.026125094,  -0.17582615,  -0.15923657,  -0.27486774,  -0.0006143371, 0.0001771948,
             -8.470171e-05, 0.02651807,   0.045790765,  0.06956496});

    lstm.SetInputToCellWeights(
            {-0.04580283,   -0.09549462,  -0.032418985,  -0.06454633,  -0.043528453, 0.043018587,
             -0.049152344,  -0.12418144,  -0.078985475,  -0.07596889,  0.019484362,  -0.11434962,
             -0.0074034138, -0.06314844,  -0.092981495,  0.0062155537, -0.025034338, -0.0028890965,
             0.048929527,   0.06235075,   0.10665918,    -0.032036792, -0.08505916,  -0.10843358,
             -0.13002433,   -0.036816437, -0.02130134,   -0.016518239, 0.0047691227, -0.0025825808,
             0.066017866,   0.029991534,  -0.10652836,   -0.1037554,   -0.13056071,  -0.03266643,
             -0.033702414,  -0.006473424, -0.04611692,   0.014419339,  -0.025174323, 0.0396852,
             0.081777506,   0.06157468,   0.10210095,    -0.009658194, 0.046511717,  0.03603906,
             0.0069369148,  0.015960095,  -0.06507666,   0.09551598,   0.053568836,  0.06408714,
             0.12835667,    -0.008714329, -0.20211966,   -0.12093674,  0.029450472,  0.2849013,
             -0.029227901,  0.1164364,    -0.08560263,   0.09941786,   -0.036999565, -0.028842626,
             -0.0033637602, -0.017012902, -0.09720865,   -0.11193351,  -0.029155117, -0.017936034,
             -0.009768936,  -0.04223324,  -0.036159635,  0.06505112,   -0.021742892, -0.023377212,
             -0.07221364,   -0.06430552,  0.05453865,    0.091149814,  0.06387331,   0.007518393,
             0.055960953,   0.069779344,  0.046411168,   0.10509911,   0.07463894,   0.0075130584,
             0.012850982,   0.04555431,   0.056955688,   0.06555285,   0.050801456,  -0.009862683,
             0.00826772,    -0.026555609, -0.0073611983, -0.0014897042});

    lstm.SetInputToOutputWeights(
            {-0.0998932,   -0.07201956,  -0.052803773, -0.15629593,   -0.15001918,  -0.07650751,
             0.02359855,   -0.075155355, -0.08037709,  -0.15093534,   0.029517552,  -0.04751393,
             0.010350531,  -0.02664851,  -0.016839722, -0.023121163,  0.0077019283, 0.012851257,
             -0.05040649,  -0.0129761,   -0.021737747, -0.038305793,  -0.06870586,  -0.01481247,
             -0.001285394, 0.10124236,   0.083122835,  0.053313006,   -0.062235646, -0.075637154,
             -0.027833903, 0.029774971,  0.1130802,    0.09218906,    0.09506135,   -0.086665764,
             -0.037162706, -0.038880914, -0.035832845, -0.014481564,  -0.09825003,  -0.12048569,
             -0.097665586, -0.05287633,  -0.0964047,   -0.11366429,   0.035777505,  0.13568819,
             0.052451383,  0.050649304,  0.05798951,   -0.021852335,  -0.099848844, 0.014740475,
             -0.078897946, 0.04974699,   0.014160473,  0.06973932,    0.04964942,   0.033364646,
             0.08190124,   0.025535367,  0.050893165,  0.048514254,   0.06945813,   -0.078907564,
             -0.06707616,  -0.11844508,  -0.09986688,  -0.07509403,   0.06263226,   0.14925587,
             0.20188436,   0.12098451,   0.14639415,   0.0015017595,  -0.014267382, -0.03417257,
             0.012711468,  0.0028300495, -0.024758482, -0.05098548,   -0.0821182,   0.014225672,
             0.021544158,  0.08949725,   0.07505268,   -0.0020780868, 0.04908258,   0.06476295,
             -0.022907063, 0.027562456,  0.040185735,  0.019567577,   -0.015598739, -0.049097303,
             -0.017121866, -0.083368234, -0.02332002,  -0.0840956});

    lstm.SetInputGateBias({0.02234832,  0.14757581,   0.18176508,  0.10380666,  0.053110216,
                           -0.06928846, -0.13942584,  -0.11816189, 0.19483899,  0.03652339,
                           -0.10250295, 0.036714908,  -0.18426876, 0.036065217, 0.21810818,
                           0.02383196,  -0.043370757, 0.08690144,  -0.04444982, 0.00030581196});

    lstm.SetForgetGateBias({0.035185695, -0.042891346, -0.03032477, 0.23027696,  0.11098921,
                            0.15378423,  0.09263801,   0.09790885,  0.09508917,  0.061199076,
                            0.07665568,  -0.015443159, -0.03499149, 0.046190713, 0.08895977,
                            0.10899629,  0.40694186,   0.06030037,  0.012413437, -0.06108739});

    lstm.SetCellGateBias({-0.024379363, 0.0055531194, 0.23377132,  0.033463873, -0.1483596,
                          -0.10639995,  -0.091433935, 0.058573797, -0.06809782, -0.07889636,
                          -0.043246906, -0.09829136,  -0.4279842,  0.034901652, 0.18797937,
                          0.0075234566, 0.016178843,  0.1749513,   0.13975595,  0.92058027});

    lstm.SetOutputGateBias({0.046159424,  -0.0012809046, 0.03563469,   0.12648113, 0.027195795,
                            0.35373217,   -0.018957434,  0.008907322,  -0.0762701, 0.12018895,
                            0.04216877,   0.0022856654,  0.040952638,  0.3147856,  0.08225149,
                            -0.057416286, -0.14995944,   -0.008040261, 0.13208859, 0.029760877});

    lstm.SetRecurrentToInputWeights(
            {-0.001374326,   -0.078856036,  0.10672688,    0.029162422,  -0.11585556,
             0.02557986,     -0.13446963,   -0.035785314,  -0.01244275,  0.025961924,
             -0.02337298,    -0.044228926,  -0.055839065,  -0.046598054, -0.010546039,
             -0.06900766,    0.027239809,   0.022582639,   -0.013296484, -0.05459212,
             0.08981,        -0.045407712,  0.08682226,    -0.06867011,  -0.14390695,
             -0.02916037,    0.000996957,   0.091420636,   0.14283475,   -0.07390571,
             -0.06402044,    0.062524505,   -0.093129106,  0.04860203,   -0.08364217,
             -0.08119002,    0.009352075,   0.22920375,    0.0016303885, 0.11583097,
             -0.13732095,    0.012405723,   -0.07551853,   0.06343048,   0.12162708,
             -0.031923793,   -0.014335606,  0.01790974,    -0.10650317,  -0.0724401,
             0.08554849,     -0.05727212,   0.06556731,    -0.042729504, -0.043227166,
             0.011683251,    -0.013082158,  -0.029302018,  -0.010899579, -0.062036745,
             -0.022509435,   -0.00964907,   -0.01567329,   0.04260106,   -0.07787477,
             -0.11576462,    0.017356863,   0.048673786,   -0.017577527, -0.05527947,
             -0.082487635,   -0.040137455,  -0.10820036,   -0.04666372,  0.022746278,
             -0.07851417,    0.01068115,    0.032956902,   0.022433773,  0.0026891115,
             0.08944216,     -0.0685835,    0.010513544,   0.07228705,   0.02032331,
             -0.059686817,   -0.0005566496, -0.086984694,  0.040414046,  -0.1380399,
             0.094208956,    -0.05722982,   0.012092817,   -0.04989123,  -0.086576,
             -0.003399834,   -0.04696032,   -0.045747425,  0.10091314,   0.048676282,
             -0.029037097,   0.031399418,   -0.0040285117, 0.047237843,  0.09504992,
             0.041799378,    -0.049185462,  -0.031518843,  -0.10516937,  0.026374253,
             0.10058866,     -0.0033195973, -0.041975245,  0.0073591834, 0.0033782164,
             -0.004325073,   -0.10167381,   0.042500053,   -0.01447153,  0.06464186,
             -0.017142897,   0.03312627,    0.009205989,   0.024138335,  -0.011337001,
             0.035530265,    -0.010912711,  0.0706555,     -0.005894094, 0.051841937,
             -0.1401738,     -0.02351249,   0.0365468,     0.07590991,   0.08838724,
             0.021681072,    -0.10086113,   0.019608743,   -0.06195883,  0.077335775,
             0.023646897,    -0.095322326,  0.02233014,    0.09756986,   -0.048691444,
             -0.009579111,   0.07595467,    0.11480546,    -0.09801813,  0.019894179,
             0.08502348,     0.004032281,   0.037211012,   0.068537936,  -0.048005626,
             -0.091520436,   -0.028379958,  -0.01556313,   0.06554592,   -0.045599163,
             -0.01672207,    -0.020169014,  -0.011877351,  -0.20212261,  0.010889619,
             0.0047078193,   0.038385306,   0.08540671,    -0.017140968, -0.0035865551,
             0.016678626,    0.005633034,   0.015963363,   0.00871737,   0.060130805,
             0.028611384,    0.10109069,    -0.015060172,  -0.07894427,  0.06401885,
             0.011584063,    -0.024466386,  0.0047652307,  -0.09041358,  0.030737216,
             -0.0046374933,  0.14215417,    -0.11823516,   0.019899689,  0.006106124,
             -0.027092824,   0.0786356,     0.05052217,    -0.058925,    -0.011402121,
             -0.024987547,   -0.0013661642, -0.06832946,   -0.015667673, -0.1083353,
             -0.00096863037, -0.06988685,   -0.053350925,  -0.027275559, -0.033664223,
             -0.07978348,    -0.025200296,  -0.017207067,  -0.058403496, -0.055697463,
             0.005798788,    0.12965427,    -0.062582195,  0.0013350133, -0.10482091,
             0.0379771,      0.072521195,   -0.0029455067, -0.13797039,  -0.03628521,
             0.013806405,    -0.017858358,  -0.01008298,   -0.07700066,  -0.017081132,
             0.019358726,    0.0027079724,  0.004635139,   0.062634714,  -0.02338735,
             -0.039547626,   -0.02050681,   0.03385117,    -0.083611414, 0.002862572,
             -0.09421313,    0.058618143,   -0.08598433,   0.00972939,   0.023867095,
             -0.053934585,   -0.023203006,  0.07452513,    -0.048767887, -0.07314807,
             -0.056307215,   -0.10433547,   -0.06440842,   0.04328182,   0.04389765,
             -0.020006588,   -0.09076438,   -0.11652589,   -0.021705797, 0.03345259,
             -0.010329105,   -0.025767034,  0.013057034,   -0.07316461,  -0.10145612,
             0.06358255,     0.18531723,    0.07759293,    0.12006465,   0.1305557,
             0.058638252,    -0.03393652,   0.09622831,    -0.16253184,  -2.4580743e-06,
             0.079869635,    -0.070196845,  -0.005644518,  0.06857898,   -0.12598175,
             -0.035084512,   0.03156317,    -0.12794146,   -0.031963028, 0.04692781,
             0.030070418,    0.0071660685,  -0.095516115,  -0.004643372, 0.040170413,
             -0.062104587,   -0.0037324072, 0.0554317,     0.08184801,   -0.019164372,
             0.06791302,     0.034257166,   -0.10307039,   0.021943003,  0.046745934,
             0.0790918,      -0.0265588,    -0.007824208,  0.042546265,  -0.00977924,
             -0.0002440307,  -0.017384544,  -0.017990116,  0.12252321,   -0.014512694,
             -0.08251313,    0.08861942,    0.13589665,    0.026351685,  0.012641483,
             0.07466548,     0.044301085,   -0.045414884,  -0.051112458, 0.03444247,
             -0.08502782,    -0.04106223,   -0.028126027,  0.028473156,  0.10467447});

    lstm.SetRecurrentToForgetWeights(
            {-0.057784554,  -0.026057621,   -0.068447545,  -0.022581743,  0.14811787,
             0.10826372,    0.09471067,     0.03987225,    -0.0039523416, 0.00030638507,
             0.053185795,   0.10572994,     0.08414449,    -0.022036452,  -0.00066928595,
             -0.09203576,   0.032950465,    -0.10985798,   -0.023809856,  0.0021431844,
             -0.02196096,   -0.00326074,    0.00058621005, -0.074678116,  -0.06193199,
             0.055729095,   0.03736828,     0.020123724,   0.061878487,   -0.04729229,
             0.034919553,   -0.07585433,    -0.04421272,   -0.044019096,  0.085488975,
             0.04058006,    -0.06890133,    -0.030951202,  -0.024628663,  -0.07672815,
             0.034293607,   0.08556707,     -0.05293577,   -0.033561368,  -0.04899627,
             0.0241671,     0.015736353,    -0.095442444,  -0.029564252,  0.016493602,
             -0.035026584,  0.022337519,    -0.026871363,  0.004780428,   0.0077918363,
             -0.03601621,   0.016435321,    -0.03263031,   -0.09543275,   -0.047392778,
             0.013454138,   0.028934088,    0.01685226,    -0.086110644,  -0.046250615,
             -0.01847454,   0.047608484,    0.07339695,    0.034546845,   -0.04881143,
             0.009128804,   -0.08802852,    0.03761666,    0.008096139,   -0.014454086,
             0.014361001,   -0.023502491,   -0.0011840804, -0.07607001,   0.001856849,
             -0.06509276,   -0.006021153,   -0.08570962,   -0.1451793,    0.060212336,
             0.055259194,   0.06974018,     0.049454916,   -0.027794661,  -0.08077226,
             -0.016179763,  0.1169753,      0.17213494,    -0.0056326236, -0.053934924,
             -0.0124349,    -0.11520337,    0.05409887,    0.088759385,   0.0019655675,
             0.0042065294,  0.03881498,     0.019844765,   0.041858196,   -0.05695512,
             0.047233116,   0.038937137,    -0.06542224,   0.014429736,   -0.09719407,
             0.13908425,    -0.05379757,    0.012321099,   0.082840554,   -0.029899208,
             0.044217527,   0.059855383,    0.07711018,    -0.045319796,  0.0948846,
             -0.011724666,  -0.0033288454,  -0.033542685,  -0.04764985,   -0.13873616,
             0.040668588,   0.034832682,    -0.015319203,  -0.018715994,  0.046002675,
             0.0599172,     -0.043107376,   0.0294216,     -0.002314414,  -0.022424703,
             0.0030315618,  0.0014641669,   0.0029166266,  -0.11878115,   0.013738511,
             0.12375372,    -0.0006038222,  0.029104086,   0.087442465,   0.052958444,
             0.07558703,    0.04817258,     0.044462286,   -0.015213451,  -0.08783778,
             -0.0561384,    -0.003008196,   0.047060397,   -0.002058388,  0.03429439,
             -0.018839769,  0.024734668,    0.024614193,   -0.042046934,  0.09597743,
             -0.0043254104, 0.04320769,     0.0064070094,  -0.0019131786, -0.02558259,
             -0.022822596,  -0.023273505,   -0.02464396,   -0.10991725,   -0.006240552,
             0.0074488563,  0.024044557,    0.04383914,    -0.046476185,  0.028658995,
             0.060410924,   0.050786525,    0.009452605,   -0.0073054377, -0.024810238,
             0.0052906186,  0.0066939713,   -0.0020913032, 0.014515517,   0.015898481,
             0.021362653,   -0.030262267,   0.016587038,   -0.011442813,  0.041154444,
             -0.007631438,  -0.03423484,    -0.010977775,  0.036152758,   0.0066366293,
             0.11915515,    0.02318443,     -0.041350313,  0.021485701,   -0.10906167,
             -0.028218046,  -0.00954771,    0.020531068,   -0.11995105,   -0.03672871,
             0.024019798,   0.014255957,    -0.05221243,   -0.00661567,   -0.04630967,
             0.033188973,   0.10107534,     -0.014027541,  0.030796422,   -0.10270911,
             -0.035999842,  0.15443139,     0.07684145,    0.036571592,   -0.035900835,
             -0.0034699554, 0.06209149,     0.015920248,   -0.031122351,  -0.03858649,
             0.01849943,    0.13872518,     0.01503974,    0.069941424,   -0.06948533,
             -0.0088794185, 0.061282158,    -0.047401894,  0.03100163,    -0.041533746,
             -0.10430945,   0.044574402,    -0.01425562,   -0.024290353,  0.034563623,
             0.05866852,    0.023947537,    -0.09445152,   0.035450947,   0.02247216,
             -0.0042998926, 0.061146557,    -0.10250651,   0.020881841,   -0.06747029,
             0.10062043,    -0.0023941975,  0.03532124,    -0.016341697,  0.09685456,
             -0.016764693,  0.051808182,    0.05875331,    -0.04536488,   0.001626336,
             -0.028892258,  -0.01048663,    -0.009793449,  -0.017093895,  0.010987891,
             0.02357273,    -0.00010856845, 0.0099760275,  -0.001845119,  -0.03551521,
             0.0018358806,  0.05763657,     -0.01769146,   0.040995963,   0.02235177,
             -0.060430344,  0.11475477,     -0.023854522,  0.10071741,    0.0686208,
             -0.014250481,  0.034261297,    0.047418304,   0.08562733,    -0.030519066,
             0.0060542435,  0.014653856,    -0.038836084,  0.04096551,    0.032249358,
             -0.08355519,   -0.026823482,   0.056386515,   -0.010401743,  -0.028396193,
             0.08507674,    0.014410365,    0.020995233,   0.17040324,    0.11511526,
             0.02459721,    0.0066619175,   0.025853224,   -0.023133837,  -0.081302024,
             0.017264642,   -0.009585969,   0.09491168,    -0.051313367,  0.054532815,
             -0.014298593,  0.10657464,     0.007076659,   0.10964551,    0.0409152,
             0.008275321,   -0.07283536,    0.07937492,    0.04192024,    -0.1075027});

    lstm.SetRecurrentToCellWeights(
            {-0.037322544,  0.018592842,   0.0056175636,  -0.06253426,   0.055647098,
             -0.05713207,   -0.05626563,   0.005559383,   0.03375411,    -0.025757805,
             -0.088049285,  0.06017052,    -0.06570978,   0.007384076,   0.035123326,
             -0.07920549,   0.053676967,   0.044480428,   -0.07663568,   0.0071805613,
             0.08089997,    0.05143358,    0.038261272,   0.03339287,    -0.027673481,
             0.044746667,   0.028349208,   0.020090483,   -0.019443132,  -0.030755889,
             -0.0040000007, 0.04465846,    -0.021585021,  0.0031670958,  0.0053199246,
             -0.056117613,  -0.10893326,   0.076739706,   -0.08509834,   -0.027997585,
             0.037871376,   0.01449768,    -0.09002357,   -0.06111149,   -0.046195522,
             0.0422062,     -0.005683705,  -0.1253618,    -0.012925729,  -0.04890792,
             0.06985068,    0.037654128,   0.03398274,    -0.004781977,  0.007032333,
             -0.031787455,  0.010868644,   -0.031489216,  0.09525667,    0.013939797,
             0.0058680447,  0.0167067,     0.02668468,    -0.04797466,   -0.048885044,
             -0.12722108,   0.035304096,   0.06554885,    0.00972396,    -0.039238118,
             -0.05159735,   -0.11329045,   0.1613692,     -0.03750952,   0.06529313,
             -0.071974665,  -0.11769596,   0.015524369,   -0.0013754242, -0.12446318,
             0.02786344,    -0.014179351,  0.005264273,   0.14376344,    0.015983658,
             0.03406988,    -0.06939408,   0.040699873,   0.02111075,    0.09669095,
             0.041345075,   -0.08316494,   -0.07684199,   -0.045768797,  0.032298047,
             -0.041805092,  0.0119405,     0.0061010392,  0.12652606,    0.0064572375,
             -0.024950314,  0.11574242,    0.04508852,    -0.04335324,   0.06760663,
             -0.027437469,  0.07216407,    0.06977076,    -0.05438599,   0.034033038,
             -0.028602652,  0.05346137,    0.043184172,   -0.037189785,  0.10420091,
             0.00882477,    -0.054019816,  -0.074273005,  -0.030617684,  -0.0028467078,
             0.024302477,   -0.0038869337, 0.005332455,   0.0013399826,  0.04361412,
             -0.007001822,  0.09631092,    -0.06702025,   -0.042049985,  -0.035070654,
             -0.04103342,   -0.10273396,   0.0544271,     0.037184782,   -0.13150354,
             -0.0058036847, -0.008264958,  0.042035464,   0.05891794,    0.029673764,
             0.0063542654,  0.044788733,   0.054816857,   0.062257513,   -0.00093483756,
             0.048938446,   -0.004952862,  -0.007730018,  -0.04043371,   -0.017094059,
             0.07229206,    -0.023670016,  -0.052195564,  -0.025616996,  -0.01520939,
             0.045104615,   -0.007376126,  0.003533447,   0.006570588,   0.056037236,
             0.12436656,    0.051817212,   0.028532185,   -0.08686856,   0.11868599,
             0.07663395,    -0.07323171,   0.03463402,    -0.050708205,  -0.04458982,
             -0.11590894,   0.021273347,   0.1251325,     -0.15313013,   -0.12224372,
             0.17228661,    0.023029093,   0.086124025,   0.006445803,   -0.03496501,
             0.028332196,   0.04449512,    -0.042436164,  -0.026587414,  -0.006041347,
             -0.09292539,   -0.05678812,   0.03897832,    0.09465633,    0.008115513,
             -0.02171956,   0.08304309,    0.071401566,   0.019622514,   0.032163795,
             -0.004167056,  0.02295182,    0.030739572,   0.056506045,   0.004612461,
             0.06524936,    0.059999723,   0.046395954,   -0.0045512207, -0.1335546,
             -0.030136576,  0.11584653,    -0.014678886,  0.0020118146,  -0.09688814,
             -0.0790206,    0.039770417,   -0.0329582,    0.07922767,    0.029322514,
             0.026405897,   0.04207835,    -0.07073373,   0.063781224,   0.0859677,
             -0.10925287,   -0.07011058,   0.048005477,   0.03438226,    -0.09606514,
             -0.006669445,  -0.043381985,  0.04240257,    -0.06955775,   -0.06769346,
             0.043903265,   -0.026784198,  -0.017840602,  0.024307009,   -0.040079936,
             -0.019946516,  0.045318738,   -0.12233574,   0.026170589,   0.0074471775,
             0.15978073,    0.10185836,    0.10298046,    -0.015476589,  -0.039390966,
             -0.072174534,  0.0739445,     -0.1211869,    -0.0347889,    -0.07943156,
             0.014809798,   -0.12412325,   -0.0030663363, 0.039695457,   0.0647603,
             -0.08291318,   -0.018529687,  -0.004423833,  0.0037507233,  0.084633216,
             -0.01514876,   -0.056505352,  -0.012800942,  -0.06994386,   0.012962922,
             -0.031234352,  0.07029052,    0.016418684,   0.03618972,    0.055686004,
             -0.08663945,   -0.017404709,  -0.054761406,  0.029065743,   0.052404847,
             0.020238016,   0.0048197987,  -0.0214882,    0.07078733,    0.013016777,
             0.06262858,    0.009184685,   0.020785125,   -0.043904778,  -0.0270329,
             -0.03299152,   -0.060088247,  -0.015162964,  -0.001828936,  0.12642565,
             -0.056757294,  0.013586685,   0.09232601,    -0.035886683,  0.06000002,
             0.05229691,    -0.052580316,  -0.082029596,  -0.010794592,  0.012947712,
             -0.036429964,  -0.085508935,  -0.13127148,   -0.017744139,  0.031502828,
             0.036232427,   -0.031581745,  0.023051167,   -0.05325106,   -0.03421577,
             0.028793324,   -0.034633752,  -0.009881397,  -0.043551125,  -0.018609839,
             0.0019097115,  -0.008799762,  0.056595087,   0.0022273948,  0.055752404});

    lstm.SetRecurrentToOutputWeights({
            0.025825322,   -0.05813119,  0.09495884,   -0.045984812,   -0.01255415,
            -0.0026479573, -0.08196161,  -0.054914974, -0.0046604523,  -0.029587349,
            -0.044576716,  -0.07480124,  -0.082868785, 0.023254942,    0.027502948,
            -0.0039728214, -0.08683098,  -0.08116779,  -0.014675607,   -0.037924774,
            -0.023314456,  -0.007401714, -0.09255757,  0.029460307,    -0.08829125,
            -0.005139627,  -0.08989442,  -0.0555066,   0.13596267,     -0.025062224,
            -0.048351806,  -0.03850004,  0.07266485,   -0.022414139,   0.05940088,
            0.075114764,   0.09597592,   -0.010211725, -0.0049794707,  -0.011523867,
            -0.025980417,  0.072999895,  0.11091378,   -0.081685916,   0.014416728,
            0.043229222,   0.034178585,  -0.07530371,  0.035837382,    -0.085607,
            -0.007721233,  -0.03287832,  -0.043848954, -0.06404588,    -0.06632928,
            -0.073643476,  0.008214239,  -0.045984086, 0.039764922,    0.03474462,
            0.060612556,   -0.080590084, 0.049127717,  0.04151091,     -0.030063879,
            0.008801774,   -0.023021035, -0.019558564, 0.05158114,     -0.010947698,
            -0.011825728,  0.0075720972, 0.0699727,    -0.0039981045,  0.069350146,
            0.08799282,    0.016156472,  0.035502106,  0.11695009,     0.006217345,
            0.13392477,    -0.037875112, 0.025745004,  0.08940699,     -0.00924166,
            0.0046702605,  -0.036598757, -0.08811812,  0.10522024,     -0.032441203,
            0.008176899,   -0.04454919,  0.07058152,   0.0067963637,   0.039206743,
            0.03259838,    0.03725492,   -0.09515802,  0.013326398,    -0.052055415,
            -0.025676316,  0.03198509,   -0.015951829, -0.058556724,   0.036879618,
            0.043357447,   0.028362012,  -0.05908629,  0.0059240665,   -0.04995891,
            -0.019187413,  0.0276265,    -0.01628143,  0.0025863599,   0.08800015,
            0.035250366,   -0.022165963, -0.07328642,  -0.009415526,   -0.07455109,
            0.11690406,    0.0363299,    0.07411125,   0.042103454,    -0.009660886,
            0.019076364,   0.018299393,  -0.046004917, 0.08891175,     0.0431396,
            -0.026327137,  -0.051502608, 0.08979574,   -0.051670972,   0.04940282,
            -0.07491107,   -0.021240504, 0.022596184,  -0.034280192,   0.060163025,
            -0.058211457,  -0.051837247, -0.01349775,  -0.04639988,    -0.035936575,
            -0.011681591,  0.064818054,  0.0073146066, -0.021745546,   -0.043124277,
            -0.06471268,   -0.07053354,  -0.029321948, -0.05330136,    0.016933719,
            -0.053782392,  0.13747959,   -0.1361751,   -0.11569455,    0.0033329215,
            0.05693899,    -0.053219706, 0.063698,     0.07977434,     -0.07924483,
            0.06936997,    0.0034815092, -0.007305279, -0.037325785,   -0.07251102,
            -0.033633437,  -0.08677009,  0.091591336,  -0.14165086,    0.021752775,
            0.019683983,   0.0011612234, -0.058154266, 0.049996935,    0.0288841,
            -0.0024567875, -0.14345716,  0.010955264,  -0.10234828,    0.1183656,
            -0.0010731248, -0.023590032, -0.072285876, -0.0724771,     -0.026382286,
            -0.0014920527, 0.042667855,  0.0018776858, 0.02986552,     0.009814309,
            0.0733756,     0.12289186,   0.018043943,  -0.0458958,     0.049412545,
            0.033632483,   0.05495232,   0.036686596,  -0.013781798,   -0.010036754,
            0.02576849,    -0.08307328,  0.010112348,  0.042521734,    -0.05869831,
            -0.071689695,  0.03876447,   -0.13275425,  -0.0352966,     -0.023077697,
            0.10285965,    0.084736146,  0.15568255,   -0.00040734606, 0.027835453,
            -0.10292561,   -0.032401145, 0.10053256,   -0.026142767,   -0.08271222,
            -0.0030240538, -0.016368777, 0.1070414,    0.042672627,    0.013456989,
            -0.0437609,    -0.022309763, 0.11576483,   0.04108048,     0.061026827,
            -0.0190714,    -0.0869359,   0.037901703,  0.0610107,      0.07202949,
            0.01675338,    0.086139716,  -0.08795751,  -0.014898893,   -0.023771819,
            -0.01965048,   0.007955471,  -0.043740474, 0.03346837,     -0.10549954,
            0.090567775,   0.042013682,  -0.03176985,  0.12569028,     -0.02421228,
            -0.029526481,  0.023851605,  0.031539805,  0.05292009,     -0.02344001,
            -0.07811758,   -0.08834428,  0.10094801,   0.16594367,     -0.06861939,
            -0.021256343,  -0.041093912, -0.06669611,  0.035498552,    0.021757556,
            -0.09302526,   -0.015403468, -0.06614931,  -0.051798206,   -0.013874718,
            0.03630673,    0.010412845,  -0.08077351,  0.046185967,    0.0035662893,
            0.03541868,    -0.094149634, -0.034814864, 0.003128424,    -0.020674974,
            -0.03944324,   -0.008110165, -0.11113267,  0.08484226,     0.043586485,
            0.040582247,   0.0968012,    -0.065249965, -0.028036479,   0.0050708856,
            0.0017462453,  0.0326779,    0.041296225,  0.09164146,     -0.047743853,
            -0.015952192,  -0.034451712, 0.084197424,  -0.05347844,    -0.11768019,
            0.085926116,   -0.08251791,  -0.045081906, 0.0948852,      0.068401024,
            0.024856757,   0.06978981,   -0.057309967, -0.012775832,   -0.0032452994,
            0.01977615,    -0.041040014, -0.024264973, 0.063464895,    0.05431621,
    });

    lstm.SetCellToInputWeights({0.040369894, 0.030746894,  0.24704495,  0.018586371,  -0.037586458,
                                -0.15312155, -0.11812848,  -0.11465643, 0.20259799,   0.11418174,
                                -0.10116027, -0.011334949, 0.12411352,  -0.076769054, -0.052169047,
                                0.21198851,  -0.38871562,  -0.09061183, -0.09683246,  -0.21929175});

    lstm.SetCellToForgetWeights({-0.01998659,  -0.15568835,  -0.24248174,  -0.012770197,
                                 0.041331276,  -0.072311886, -0.052123554, -0.0066330447,
                                 -0.043891653, 0.036225766,  -0.047248036, 0.021479502,
                                 0.033189066,  0.11952997,   -0.020432774, 0.64658105,
                                 -0.06650122,  -0.03467612,  0.095340036,  0.23647355});

    lstm.SetCellToOutputWeights({0.08286371,  -0.08261836, -0.51210177, 0.002913762, 0.17764764,
                                 -0.5495371,  -0.08460716, -0.24552552, 0.030037103, 0.04123544,
                                 -0.11940523, 0.007358328, 0.1890978,   0.4833202,   -0.34441817,
                                 0.36312827,  -0.26375428, 0.1457655,   -0.19724406, 0.15548733});

    lstm.SetProjectionWeights(
            {-0.009802181,  0.09401916,   0.0717386,     -0.13895074,   0.09641832,    0.060420845,
             0.08539281,    0.054285463,  0.061395317,   0.034448683,   -0.042991187,  0.019801661,
             -0.16840284,   -0.015726732, -0.23041931,   -0.024478018,  -0.10959692,   -0.013875541,
             0.18600968,    -0.061274476, 0.0138165,     -0.08160894,   -0.07661644,   0.032372914,
             0.16169067,    0.22465782,   -0.03993472,   -0.004017731,  0.08633481,    -0.28869787,
             0.08682067,    0.17240396,   0.014975425,   0.056431185,   0.031037588,   0.16702051,
             0.0077946745,  0.15140012,   0.29405436,    0.120285,      -0.188994,     -0.027265169,
             0.043389652,   -0.022061434, 0.014777949,   -0.20203483,   0.094781205,   0.19100232,
             0.13987629,    -0.036132768, -0.06426278,   -0.05108664,   0.13221376,    0.009441198,
             -0.16715929,   0.15859416,   -0.040437475,  0.050779544,   -0.022187516,  0.012166504,
             0.027685808,   -0.07675938,  -0.0055694645, -0.09444123,   0.0046453946,  0.050794356,
             0.10770313,    -0.20790008,  -0.07149004,   -0.11425117,   0.008225835,   -0.035802525,
             0.14374903,    0.15262283,   0.048710253,   0.1847461,     -0.007487823,  0.11000021,
             -0.09542012,   0.22619456,   -0.029149994,  0.08527916,    0.009043713,   0.0042746216,
             0.016261552,   0.022461696,  0.12689082,    -0.043589946,  -0.12035478,   -0.08361797,
             -0.050666027,  -0.1248618,   -0.1275799,    -0.071875185,  0.07377272,    0.09944291,
             -0.18897448,   -0.1593054,   -0.06526116,   -0.040107165,  -0.004618631,  -0.067624845,
             -0.007576253,  0.10727444,   0.041546922,   -0.20424393,   0.06907816,    0.050412357,
             0.00724631,    0.039827548,  0.12449835,    0.10747581,    0.13708383,    0.09134148,
             -0.12617786,   -0.06428341,  0.09956831,    0.1208086,     -0.14676677,   -0.0727722,
             0.1126304,     0.010139365,  0.015571211,   -0.038128063,  0.022913318,   -0.042050496,
             0.16842307,    -0.060597885, 0.10531834,    -0.06411776,   -0.07451711,   -0.03410368,
             -0.13393489,   0.06534304,   0.003620307,   0.04490757,    0.05970546,    0.05197996,
             0.02839995,    0.10434969,   -0.013699693,  -0.028353551,  -0.07260381,   0.047201227,
             -0.024575593,  -0.036445823, 0.07155557,    0.009672501,   -0.02328883,   0.009533515,
             -0.03606021,   -0.07421458,  -0.028082801,  -0.2678904,    -0.13221288,   0.18419984,
             -0.13012612,   -0.014588381, -0.035059117,  -0.04824723,   0.07830115,    -0.056184657,
             0.03277091,    0.025466874,  0.14494097,    -0.12522776,   -0.098633975,  -0.10766018,
             -0.08317623,   0.08594209,   0.07749552,    0.039474737,   0.1776665,     -0.07409566,
             -0.0477268,    0.29323658,   0.10801441,    0.1154011,     0.013952499,   0.10739139,
             0.10708251,    -0.051456142, 0.0074137426,  -0.10430189,   0.10034707,    0.045594677,
             0.0635285,     -0.0715442,   -0.089667566,  -0.10811871,   0.00026344223, 0.08298446,
             -0.009525053,  0.006585689,  -0.24567553,   -0.09450807,   0.09648481,    0.026996298,
             -0.06419476,   -0.04752702,  -0.11063944,   -0.23441927,   -0.17608605,   -0.052156363,
             0.067035615,   0.19271925,   -0.0032889997, -0.043264326,  0.09663576,    -0.057112187,
             -0.10100678,   0.0628376,    0.04447668,    0.017961001,   -0.10094388,   -0.10190601,
             0.18335468,    0.10494553,   -0.052095775,  -0.0026118709, 0.10539724,    -0.04383912,
             -0.042349473,  0.08438151,   -0.1947263,    0.02251204,    0.11216432,    -0.10307853,
             0.17351969,    -0.039091777, 0.08066188,    -0.00561982,   0.12633002,    0.11335965,
             -0.0088127935, -0.019777594, 0.06864014,    -0.059751723,  0.016233567,   -0.06894641,
             -0.28651384,   -0.004228674, 0.019708522,   -0.16305895,   -0.07468996,   -0.0855457,
             0.099339016,   -0.07580735,  -0.13775392,   0.08434318,    0.08330512,    -0.12131499,
             0.031935584,   0.09180414,   -0.08876437,   -0.08049874,   0.008753825,   0.03498998,
             0.030215185,   0.03907079,   0.089751154,   0.029194152,   -0.03337423,   -0.019092513,
             0.04331237,    0.04299654,   -0.036394123,  -0.12915532,   0.09793732,    0.07512415,
             -0.11319543,   -0.032502122, 0.15661901,    0.07671967,    -0.005491124,  -0.19379048,
             -0.218606,     0.21448623,   0.017840758,   0.1416943,     -0.07051762,   0.19488361,
             0.02664691,    -0.18104725,  -0.09334311,   0.15026465,    -0.15493552,   -0.057762887,
             -0.11604192,   -0.262013,    -0.01391798,   0.012185008,   0.11156489,    -0.07483202,
             0.06693364,    -0.26151478,  0.046425626,   0.036540434,   -0.16435726,   0.17338543,
             -0.21401681,   -0.11385144,  -0.08283257,   -0.069031075,  0.030635102,   0.010969227,
             0.11109743,    0.010919218,  0.027526086,   0.13519906,    0.01891392,    -0.046839405,
             -0.040167913,  0.017953383,  -0.09700955,   0.0061885654,  -0.07000971,   0.026893595,
             -0.038844477,  0.14543656});

    static float lstm_input[][20] = {
            {// Batch0: 4 (input_sequence_size) * 5 (n_input)
             0.787926, 0.151646, 0.071352, 0.118426, 0.458058, 0.596268, 0.998386,
             0.568695, 0.864524, 0.571277, 0.073204, 0.296072, 0.743333, 0.069199,
             0.045348, 0.867394, 0.291279, 0.013714, 0.482521, 0.626339},

            {// Batch1: 4 (input_sequence_size) * 5 (n_input)
             0.295743, 0.544053, 0.690064, 0.858138, 0.497181, 0.642421, 0.524260,
             0.134799, 0.003639, 0.162482, 0.640394, 0.930399, 0.050782, 0.432485,
             0.988078, 0.082922, 0.563329, 0.865614, 0.333232, 0.259916}};

    static float lstm_golden_output[][64] = {
            {// Batch0: 4 (input_sequence_size) * 16 (n_output)
             -0.00396806, 0.029352,   -0.00279226,  0.0159977,  -0.00835576, -0.0211779,
             0.0283512,   -0.0114597, 0.00907307,   -0.0244004, -0.0152191,  -0.0259063,
             0.00914318,  0.00415118, 0.017147,     0.0134203,  -0.0166936,  0.0381209,
             0.000889694, 0.0143363,  -0.0328911,   -0.0234288, 0.0333051,   -0.012229,
             0.0110322,   -0.0457725, -0.000832209, -0.0202817, 0.0327257,   0.0121308,
             0.0155969,   0.0312091,  -0.0213783,   0.0350169,  0.000324794, 0.0276012,
             -0.0263374,  -0.0371449, 0.0446149,    -0.0205474, 0.0103729,   -0.0576349,
             -0.0150052,  -0.0292043, 0.0376827,    0.0136115,  0.0243435,   0.0354492,
             -0.0189322,  0.0464512,  -0.00251373,  0.0225745,  -0.0308346,  -0.0317124,
             0.0460407,   -0.0189395, 0.0149363,    -0.0530162, -0.0150767,  -0.0340193,
             0.0286833,   0.00824207, 0.0264887,    0.0305169},
            {// Batch1: 4 (input_sequence_size) * 16 (n_output)
             -0.013869,  0.0287268,  -0.00334693,  0.00733398, -0.0287926,  -0.0186926,
             0.0193662,  -0.0115437, 0.00422612,   -0.0345232, 0.00223253,  -0.00957321,
             0.0210624,  0.013331,   0.0150954,    0.02168,    -0.0141913,  0.0322082,
             0.00227024, 0.0260507,  -0.0188721,   -0.0296489, 0.0399134,   -0.0160509,
             0.0116039,  -0.0447318, -0.0150515,   -0.0277406, 0.0316596,   0.0118233,
             0.0214762,  0.0293641,  -0.0204549,   0.0450315,  -0.00117378, 0.0167673,
             -0.0375007, -0.0238314, 0.038784,     -0.0174034, 0.0131743,   -0.0506589,
             -0.0048447, -0.0240239, 0.0325789,    0.00790065, 0.0220157,   0.0333314,
             -0.0264787, 0.0387855,  -0.000764675, 0.0217599,  -0.037537,   -0.0335206,
             0.0431679,  -0.0211424, 0.010203,     -0.062785,  -0.00832363, -0.025181,
             0.0412031,  0.0118723,  0.0239643,    0.0394009}};

    // Resetting cell_state and output_state
    lstm.ResetCellState();
    lstm.ResetOutputState();

    const int input_sequence_size = sizeof(lstm_input[0]) / sizeof(float) / (lstm.num_inputs());
    for (int i = 0; i < input_sequence_size; i++) {
        float* batch0_start = lstm_input[0] + i * lstm.num_inputs();
        float* batch0_end = batch0_start + lstm.num_inputs();

        lstm.SetInput(0, batch0_start, batch0_end);

        float* batch1_start = lstm_input[1] + i * lstm.num_inputs();
        float* batch1_end = batch1_start + lstm.num_inputs();
        lstm.SetInput(lstm.num_inputs(), batch1_start, batch1_end);

        lstm.Invoke();

        float* golden_start_batch0 = lstm_golden_output[0] + i * lstm.num_outputs();
        float* golden_end_batch0 = golden_start_batch0 + lstm.num_outputs();
        float* golden_start_batch1 = lstm_golden_output[1] + i * lstm.num_outputs();
        float* golden_end_batch1 = golden_start_batch1 + lstm.num_outputs();
        std::vector<float> expected;
        expected.insert(expected.end(), golden_start_batch0, golden_end_batch0);
        expected.insert(expected.end(), golden_start_batch1, golden_end_batch1);
        EXPECT_THAT(lstm.GetOutput(), ElementsAreArray(ArrayFloatNear(expected)));
    }
}

}  // namespace wrapper
}  // namespace nn
}  // namespace android