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#include "tim/vx/context.h"
#include "tim/vx/graph.h"
#include "tim/vx/ops/instancenormalization.h"
#include "test_utils.h"
#include "gtest/gtest.h"

TEST(InstanceNorm, shape_2_2_2_2_float) {
    auto ctx = tim::vx::Context::Create();
    auto graph = ctx->CreateGraph();

    tim::vx::ShapeType io_shape({2, 2, 2, 2}); //nchw
    tim::vx::ShapeType param_shape({2});
    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32,
                            param_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::OUTPUT);

    auto input_tensor = graph->CreateTensor(input_spec);
    auto gamma_tensor = graph->CreateTensor(param_spec);
    auto beta_tensor = graph->CreateTensor(param_spec);
    auto output_tensor = graph->CreateTensor(output_spec);

    std::vector<float> in_data = {
        0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 2.0f, 2.0f, 4.0f, 1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 2.0f, -2.0f, 4.0f
    };
    std::vector<float> gamma = {1.0f, 1.0f};
    std::vector<float> beta = {.0f, .0f};
    std::vector<float> golden = {
        0.0f, 0.0f, 0.0f, 0.0f, -1.1470304f, -0.22940612f, -0.22940612f, 1.6058424f, 0.99995005f,
        -0.99995005f, -0.99995005f, 0.99995005f, -0.7337929f, 0.52413774f, -1.1531031f, 1.3627582f
    };
    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
    EXPECT_TRUE(gamma_tensor->CopyDataToTensor(gamma.data(), gamma.size() * sizeof(float)));
    EXPECT_TRUE(beta_tensor->CopyDataToTensor(beta.data(), beta.size() * sizeof(float)));

    auto op = graph->CreateOperation<tim::vx::ops::InstanceNormalization>(1e-4f);
    (*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor});

    EXPECT_TRUE(graph->Compile());
    EXPECT_TRUE(graph->Run());

    std::vector<float> output(16);
    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
    EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}

TEST(InstanceNorm, shape_3_6_1_float) {
    auto ctx = tim::vx::Context::Create();
    auto graph = ctx->CreateGraph();

    tim::vx::ShapeType io_shape({3, 6, 1});
    tim::vx::ShapeType param_shape({6});
    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32,
                            param_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::OUTPUT);

    auto input_tensor = graph->CreateTensor(input_spec);
    auto gamma_tensor = graph->CreateTensor(param_spec);
    auto beta_tensor = graph->CreateTensor(param_spec);
    auto output_tensor = graph->CreateTensor(output_spec);

    std::vector<float> in_data = {
        -2, 0, 2,
        -3, 0, 3,
        -4, 0, 4,
        -5, 0, 5,
        -6, 0, 6,
        -7, 0, 7 };
    std::vector<float> gamma = {
        1.0f, 1.0f, 1.0f,
        1.0f, 1.0f, 1.0f
    };
    std::vector<float> beta = {
        .0f, .0f, .0f,
        .0f, .0f, .0f
    };
    std::vector<float> golden = {
        -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f,
    };

    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
    EXPECT_TRUE(gamma_tensor->CopyDataToTensor(gamma.data(), gamma.size() * sizeof(float)));
    EXPECT_TRUE(beta_tensor->CopyDataToTensor(beta.data(), beta.size() * sizeof(float)));

    auto op = graph->CreateOperation<tim::vx::ops::InstanceNormalization>(2e-5f);
    (*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor});

    EXPECT_TRUE(graph->Compile());
    EXPECT_TRUE(graph->Run());

    std::vector<float> output(18);
    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
    EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}

TEST(InstanceNorm, shape_3_3_6_1_float) {
    auto ctx = tim::vx::Context::Create();
    auto graph = ctx->CreateGraph();

    tim::vx::ShapeType io_shape({2, 3, 6, 1});
    tim::vx::ShapeType param_shape({6});
    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32,
                            param_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
                            io_shape, tim::vx::TensorAttribute::OUTPUT);

    auto input_tensor = graph->CreateTensor(input_spec);
    auto gamma_tensor = graph->CreateTensor(param_spec);
    auto beta_tensor = graph->CreateTensor(param_spec);
    auto output_tensor = graph->CreateTensor(output_spec);

    std::vector<float> in_data = {
        -2, 0, 2, -2, 0, 2,
        -3, 0, 3, -3, 0, 3,
        -4, 0, 4, -4, 0, 4,
        -5, 0, 5, -5, 0, 5,
        -6, 0, 6, -6, 0, 6,
        -7, 0, 7, -7, 0, 7,
        };
    std::vector<float> gamma = {
        1.0f, 1.0f, 1.0f,
        1.0f, 1.0f, 1.0f
    };
    std::vector<float> beta = {
        .0f, .0f, .0f,
        .0f, .0f, .0f
    };
    std::vector<float> golden = {
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
        -1.22474f, 0, 1.22474f, -1.22474f, 0, 1.22474f,
    };

    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * sizeof(float)));
    EXPECT_TRUE(gamma_tensor->CopyDataToTensor(gamma.data(), gamma.size() * sizeof(float)));
    EXPECT_TRUE(beta_tensor->CopyDataToTensor(beta.data(), beta.size() * sizeof(float)));

    auto op = graph->CreateOperation<tim::vx::ops::InstanceNormalization>(2e-5f);
    (*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor});

    EXPECT_TRUE(graph->Compile());
    EXPECT_TRUE(graph->Run());

    std::vector<float> output(36);
    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
    EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
}

#if 0
// Fail case
TEST(OP, instance_norm_shape_3_6_1_uint8) {
    auto ctx = tim::vx::Context::Create();
    auto graph = ctx->CreateGraph();

    tim::vx::ShapeType io_shape({3, 6, 1});
    tim::vx::ShapeType param_shape({6});
    tim::vx::Quantization input_quant(tim::vx::QuantType::ASYMMETRIC, 1, 7);
    tim::vx::Quantization output_quant(tim::vx::QuantType::ASYMMETRIC, 1.22474f, 1);
    tim::vx::TensorSpec input_spec(tim::vx::DataType::UINT8,
                            io_shape, tim::vx::TensorAttribute::INPUT, input_quant);
    tim::vx::TensorSpec param_spec(tim::vx::DataType::FLOAT32,
                            param_shape, tim::vx::TensorAttribute::INPUT);
    tim::vx::TensorSpec output_spec(tim::vx::DataType::UINT8,
                            io_shape, tim::vx::TensorAttribute::OUTPUT, output_quant);

    auto input_tensor = graph->CreateTensor(input_spec);
    auto gamma_tensor = graph->CreateTensor(param_spec);
    auto beta_tensor = graph->CreateTensor(param_spec);
    auto output_tensor = graph->CreateTensor(output_spec);

    std::vector<float> in_data = {
        5, 7, 9,
        4, 7, 10,
        3, 7, 11,
        2, 7, 12,
        1, 7, 13,
        0, 7, 14 };
    std::vector<float> gamma = {
        1.0f, 1.0f, 1.0f,
        1.0f, 1.0f, 1.0f
    };
    std::vector<float> beta = {
        .0f, .0f, .0f,
        .0f, .0f, .0f
    };
    std::vector<float> golden = {
        0, 1, 2,
        0, 1, 2,
        0, 1, 2,
        0, 1, 2,
        0, 1, 2,
        0, 1, 2,
    };

    EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
    EXPECT_TRUE(gamma_tensor->CopyDataToTensor(gamma.data(), gamma.size() * sizeof(float)));
    EXPECT_TRUE(beta_tensor->CopyDataToTensor(beta.data(), beta.size() * sizeof(float)));

    auto op = graph->CreateOperation<tim::vx::ops::InstanceNormalization>(2e-5f);
    (*op).BindInputs({input_tensor, beta_tensor, gamma_tensor}).BindOutputs({output_tensor});

    EXPECT_TRUE(graph->Compile());
    EXPECT_TRUE(graph->Run());

    std::vector<float> output(18);
    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
    EXPECT_EQ(golden, output);
}
#endif