#include <iostream>
#include <stdexcept>
#include <tuple>
#include <vector>

#include "data_type.hpp"
#include "element_wise_operation.hpp"
#include "conv_test_util.hpp"
#include "host_tensor.hpp"
#include "tensor_layout.hpp"
#include "test_util.hpp"

// Forward declarations for conv instances.

using DeviceConvFwdNoOpPtr =
    ck::tensor_operation::device::DeviceConvFwdPtr<ck::tensor_operation::element_wise::PassThrough,
                                                   ck::tensor_operation::element_wise::PassThrough,
                                                   ck::tensor_operation::element_wise::PassThrough>;

namespace ck {
namespace tensor_operation {
namespace device {
namespace device_conv1d_fwd_instance {

void add_device_conv1d_fwd_xdl_nwc_kxc_nwk_bf16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f16_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f32_instances(std::vector<DeviceConvFwdNoOpPtr>&);
void add_device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instances(std::vector<DeviceConvFwdNoOpPtr>&);

} // namespace device_conv1d_fwd_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

namespace {

bool TestConv1DNWC()
{
    bool res{true};
    ck::conv_util::ConvParams params;
    params.num_dim_spatial        = 1;
    params.N                      = 2;
    params.K                      = 16;
    params.C                      = 4;
    params.filter_spatial_lengths = std::vector<ck::index_t>{3};
    params.input_spatial_lengths  = std::vector<ck::index_t>{16};
    params.conv_filter_strides    = std::vector<ck::index_t>{1};
    params.conv_filter_dilations  = std::vector<ck::index_t>{1};
    params.input_left_pads        = std::vector<ck::index_t>{1};
    params.input_right_pads       = std::vector<ck::index_t>{1};

    auto host_tensors            = test::conv::GetHostTensors<float,
                                                   float,
                                                   float,
                                                   ck::tensor_layout::convolution::NWC,
                                                   ck::tensor_layout::convolution::KXC,
                                                   ck::tensor_layout::convolution::NWK>(params);
    const Tensor<float>& input   = std::get<0>(host_tensors);
    const Tensor<float>& weights = std::get<1>(host_tensors);
    Tensor<float>& host_output   = std::get<2>(host_tensors);
    Tensor<float>& device_output = std::get<3>(host_tensors);

    test::conv::RunReferenceConv<1>(params, input, weights, host_output);
    test::conv::RunConv<1>(params, input, weights, device_output);
    res = res &&
          test::check_err(
              device_output.mData, host_output.mData, "Error: incorrect results!", 1e-5f, 1e-4f);

    return res;
}

template <typename T>
bool TestConv1DNWCInstances(const std::vector<DeviceConvFwdNoOpPtr>& conv_ptrs)
{
    ck::conv_util::ConvParams params;
    params.num_dim_spatial        = 1;
    params.filter_spatial_lengths = std::vector<ck::index_t>{3};
    params.input_spatial_lengths  = std::vector<ck::index_t>{71};
    params.conv_filter_strides    = std::vector<ck::index_t>{2};
    params.conv_filter_dilations  = std::vector<ck::index_t>{1};
    params.input_left_pads        = std::vector<ck::index_t>{1};
    params.input_right_pads       = std::vector<ck::index_t>{1};

    auto host_tensors        = test::conv::GetHostTensors<T,
                                                   T,
                                                   T,
                                                   ck::tensor_layout::convolution::NWC,
                                                   ck::tensor_layout::convolution::KXC,
                                                   ck::tensor_layout::convolution::NWK>(params);
    const Tensor<T>& input   = std::get<0>(host_tensors);
    const Tensor<T>& weights = std::get<1>(host_tensors);
    Tensor<T>& host_output   = std::get<2>(host_tensors);
    Tensor<T>& device_output = std::get<3>(host_tensors);

    test::conv::RunReferenceConv<1>(params, input, weights, host_output);
    return test::conv::RunConvInstances<1>(
        params, conv_ptrs, input, weights, device_output, host_output);
}
bool TestConv1DNWCBF16Instances()
{
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_bf16_instances(conv_ptrs);
    return TestConv1DNWCInstances<ck::bhalf_t>(conv_ptrs);
}

bool TestConv1DNWCF16Instances()
{
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f16_instances(conv_ptrs);
    return TestConv1DNWCInstances<ck::half_t>(conv_ptrs);
}

bool TestConv1DNWCF32Instances()
{
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f32_instances(conv_ptrs);
    return TestConv1DNWCInstances<float>(conv_ptrs);
}

bool TestConv1DNWCInt8Instances()
{
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instances(conv_ptrs);
    return TestConv1DNWCInstances<int8_t>(conv_ptrs);
}

} // anonymous namespace

int main()
{
    bool res{true};
    res = TestConv1DNWC();
    std::cout << "TestConv1DNWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;

    res = TestConv1DNWCBF16Instances();
    std::cout << "\nTestConv1DNWCBF16Instances ..... " << (res ? "SUCCESS" : "FAILURE")
              << std::endl;
    res = TestConv1DNWCF16Instances();
    std::cout << "\nTestConv1DNWCF16Instances ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
    res = TestConv1DNWCF32Instances();
    std::cout << "\nTestConv1DNWCF32Instances ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
    res = TestConv1DNWCInt8Instances();
    std::cout << "\nTestConv1DNWCInt8Instances ..... " << (res ? "SUCCESS" : "FAILURE")
              << std::endl;
}