#include <kernels.h>

static vx_status VX_CALLBACK validateTensorExp(vx_node node, const vx_reference *parameters, vx_uint32 num, vx_meta_format metas[]) 
{
    // check tensor dims    
    vx_enum type, out_type;
    vx_size num_dims;
    vx_size input_dims[4], output_dims[4];
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_NUMBER_OF_DIMS, &num_dims, sizeof(num_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_DATA_TYPE, &type, sizeof(type)));
    if (num_dims != 4) return VX_ERROR_INVALID_DIMENSION;
    if ((type != VX_TYPE_FLOAT32) && (type != VX_TYPE_FLOAT16)) return VX_ERROR_INVALID_TYPE;
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_DIMS, input_dims, sizeof(input_dims)));

    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_NUMBER_OF_DIMS, &num_dims, sizeof(num_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_DATA_TYPE, &out_type, sizeof(out_type)));
    if (num_dims != 4) return VX_ERROR_INVALID_DIMENSION;
    if ((out_type != VX_TYPE_FLOAT32) && (out_type != VX_TYPE_FLOAT16)) return VX_ERROR_INVALID_TYPE;
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_DIMS, output_dims, sizeof(output_dims)));

    if (output_dims[3] != input_dims[3] || output_dims[2] != input_dims[2] ||
        output_dims[1] != input_dims[1] || output_dims[0] != input_dims[0] ||
        type != out_type)
    {
        return ERRMSG(VX_ERROR_INVALID_DIMENSION, "validate: exp: dims input1[%ld,%ld,%ld,%ld] output[%ld,%ld,%ld,%ld]\n",
                    input_dims[0], input_dims[1], input_dims[2], input_dims[3],
                    output_dims[0], output_dims[1], output_dims[2], output_dims[3]);
    }

    // output tensor configuration
    out_type = type;
    num_dims = 4;    
    ERROR_CHECK_STATUS(vxSetMetaFormatAttribute(metas[1], VX_TENSOR_DATA_TYPE, &out_type, sizeof(out_type)));
    ERROR_CHECK_STATUS(vxSetMetaFormatAttribute(metas[1], VX_TENSOR_NUMBER_OF_DIMS, &num_dims, sizeof(num_dims)));
    ERROR_CHECK_STATUS(vxSetMetaFormatAttribute(metas[1], VX_TENSOR_DIMS, &output_dims, sizeof(output_dims)));
    return VX_SUCCESS;

}

static vx_status VX_CALLBACK query_target_support(vx_graph graph, vx_node node,
    vx_bool use_opencl_1_2,
    vx_uint32& supported_target_affinity
)
{
    supported_target_affinity = AGO_TARGET_AFFINITY_GPU;
    return VX_SUCCESS;
}

#if ENABLE_OPENCL
//! \brief The OpenCL code generator callback.
static vx_status VX_CALLBACK opencl_codegen(
    vx_node node,                                  // [input] node
    const vx_reference parameters[],               // [input] parameters
    vx_uint32 num,                                 // [input] number of parameters
    bool opencl_load_function,                     // [input]  false: normal OpenCL kernel; true: reserved
    char opencl_kernel_function_name[64],          // [output] kernel_name for clCreateKernel()
    std::string& opencl_kernel_code,               // [output] string for clCreateProgramWithSource()
    std::string& opencl_build_options,             // [output] options for clBuildProgram()
    vx_uint32& opencl_work_dim,                    // [output] work_dim for clEnqueueNDRangeKernel()
    vx_size opencl_global_work[],                  // [output] global_work[] for clEnqueueNDRangeKernel()
    vx_size opencl_local_work[],                   // [output] local_work[] for clEnqueueNDRangeKernel()
    vx_uint32& opencl_local_buffer_usage_mask,     // [output] reserved: must be ZERO
    vx_uint32& opencl_local_buffer_size_in_bytes   // [output] reserved: must be ZERO
)
{
    //get tensor dimensions
    vx_size input_dims[4], output_dims[4];
    vx_size num_of_dims;
    vx_enum type;

    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_NUMBER_OF_DIMS, &num_of_dims, sizeof(num_of_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_DIMS, input_dims, sizeof(input_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_DIMS, output_dims, sizeof(output_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_DATA_TYPE, &type, sizeof(type)));

    strcpy(opencl_kernel_function_name, "tensor_exp");

    vx_uint32 input_dim_size = input_dims[0] * input_dims[1] * input_dims[2] * input_dims[3];

    opencl_work_dim = 3;
    opencl_global_work[0] = input_dims[0];
    opencl_global_work[1] = input_dims[1];
    opencl_global_work[2] = input_dims[2] * input_dims[3];

    // Setting variables required by the interface
    opencl_local_buffer_usage_mask = 0;
    opencl_local_buffer_size_in_bytes = 0;

    if (num_of_dims == 4) {
        char item[8192];
        if (type == VX_TYPE_FLOAT32) {
        sprintf(item,
                "#pragma OPENCL EXTENSION cl_amd_media_ops : enable\n"
                "__kernel void %s(__global uchar * in, uint in_offset, uint4 in_stride, __global uchar * out, uint out_offset, uint4 out_stride) \n"
                "{ \n"
                "     uint x = get_global_id(0);\n"
                "     uint y = get_global_id(1);\n"
                "     uint c = get_global_id(2);\n"
                "     float value = *(__global float *)&in[in_offset + x * in_stride.s0 + y * in_stride.s1 + c * in_stride.s2];\n"
                "     out += out_offset + x  * out_stride.s0 + y * out_stride.s1 + c * out_stride.s2;\n"
                "     // read 1 value and calculate its exponential\n"
                "     *(__global float *)&out[0] = exp(value);\n"
                " }\n", opencl_kernel_function_name);
        } else {
            sprintf(item,
                "#pragma OPENCL EXTENSION cl_amd_media_ops : enable\n"
                "#pragma OPENCL EXTENSION cl_khr_fp16 : enable\n"
                "__kernel void %s(__global uchar * in, uint in_offset, uint4 in_stride, __global uchar * out, uint out_offset, uint4 out_stride) \n"
                "{ \n"
                "     uint x = get_global_id(0);\n"
                "     uint y = get_global_id(1);\n"
                "     uint c = get_global_id(2);\n"
                "     half value = *(__global half *)&in[in_offset + x * in_stride.s0 + y * in_stride.s1 + c * in_stride.s2];\n"
                "     out += out_offset + x  * out_stride.s0 + y * out_stride.s1 + c * out_stride.s2;\n"
                "     // read 1 value and calculate its exponential\n"
                "     *(__global half *)&out[0] = half_exp(value);\n"
                    " }\n", opencl_kernel_function_name);
        }
        opencl_kernel_code = item;
    }
    return VX_SUCCESS;
}
#endif

static vx_status VX_CALLBACK host_kernel(vx_node node, const vx_reference * parameters, vx_uint32 num) {
#if ENABLE_HIP
    vx_size input_dims[4];
    vx_size num_of_dims;
    vx_enum type;
    vx_size temp[4] = {0};
    vx_size input_offset, output_offset;
    uint4 input_stride, output_stride;
    unsigned char *input_mem = NULL;
    unsigned char *output_mem = NULL;
    hipStream_t hip_stream;

    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_NUMBER_OF_DIMS, &num_of_dims, sizeof(num_of_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_DIMS, input_dims, sizeof(input_dims)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_BUFFER_HIP, &input_mem, sizeof(input_mem)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_OFFSET_GPU, &input_offset, sizeof(input_offset)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[0], VX_TENSOR_STRIDE_GPU, &temp, sizeof(temp)));
    input_stride.x = temp[0];
    input_stride.y = temp[1];
    input_stride.z = temp[2];
    input_stride.w = temp[3];

    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_DATA_TYPE, &type, sizeof(type)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_BUFFER_HIP, &output_mem, sizeof(output_mem)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_OFFSET_GPU, &output_offset, sizeof(output_offset)));
    ERROR_CHECK_STATUS(vxQueryTensor((vx_tensor)parameters[1], VX_TENSOR_STRIDE_GPU, &temp, sizeof(temp)));
    output_stride.x = temp[0];
    output_stride.y = temp[1];
    output_stride.z = temp[2];
    output_stride.w = temp[3];

    ERROR_CHECK_STATUS(vxQueryNode(node, VX_NODE_ATTRIBUTE_AMD_HIP_STREAM, &hip_stream, sizeof(hip_stream)));

    dim3 globalThreads;
    globalThreads.x = (input_dims[0] + 3) >> 2;
    globalThreads.y = input_dims[1];
    globalThreads.z = input_dims[2] * input_dims[3];

    if (HipExec_tensor_exp_layer(hip_stream, globalThreads, dim3(1), type, input_mem, input_offset, input_stride, output_mem,
        output_offset, output_stride)) {
            return VX_FAILURE;
    }

    return VX_SUCCESS;

#elif ENABLE_OPENCL
    return VX_ERROR_NOT_IMPLEMENTED;
#endif
}

vx_status publishTensorExp(vx_context context)
{
    // add kernel to the context with callbacks
    vx_kernel kernel = vxAddUserKernel(context, "com.amd.nn_extension.tensor_exp", VX_KERNEL_TENSOR_EXP_AMD, host_kernel, 2, validateTensorExp, nullptr, nullptr);
    ERROR_CHECK_OBJECT(kernel);

    amd_kernel_query_target_support_f query_target_support_f = query_target_support;
    ERROR_CHECK_STATUS(vxSetKernelAttribute(kernel, VX_KERNEL_ATTRIBUTE_AMD_QUERY_TARGET_SUPPORT, &query_target_support_f, sizeof(query_target_support_f)));

#if ENABLE_OPENCL
    amd_kernel_opencl_codegen_callback_f opencl_codegen_callback_f = opencl_codegen;
    ERROR_CHECK_STATUS(vxSetKernelAttribute(kernel, VX_KERNEL_ATTRIBUTE_AMD_OPENCL_CODEGEN_CALLBACK, &opencl_codegen_callback_f, sizeof(opencl_codegen_callback_f)));
#endif

    //set kernel parameters.
    ERROR_CHECK_STATUS(vxAddParameterToKernel(kernel, 0, VX_INPUT, VX_TYPE_TENSOR, VX_PARAMETER_STATE_REQUIRED));
    ERROR_CHECK_STATUS(vxAddParameterToKernel(kernel, 1, VX_OUTPUT, VX_TYPE_TENSOR, VX_PARAMETER_STATE_REQUIRED));

    //finalize and release kernel object.
    ERROR_CHECK_STATUS(vxFinalizeKernel(kernel));
    ERROR_CHECK_STATUS(vxReleaseKernel(&kernel));

    return VX_SUCCESS;
}

VX_API_ENTRY vx_node VX_API_CALL vxTensorExpNode(vx_graph graph, vx_tensor input, vx_tensor output)
{
    vx_node node = NULL;
    vx_context context = vxGetContext((vx_reference)graph);
    if (vxGetStatus((vx_reference)context) == VX_SUCCESS) {
        vx_reference params[] = {
            (vx_reference)input,
            (vx_reference)output
        };
        node = createNode(graph, VX_KERNEL_TENSOR_EXP_AMD, params, sizeof(params) / sizeof(params[0]));
    }
    return node;
}