#include "common/inner_common.h"
#include "framework/channel.h"
#include "common/constant.h"
#include "framework/service.h"
#include <base/time.h> // base::Timer
#include "framework/server.h"
#include "framework/dag_view.h"
#include "framework/manager.h"
#include "framework/resource.h"
#include "framework/predictor_metric.h" // PredictorMetric

namespace baidu {
namespace paddle_serving {
namespace predictor {

int InferService::init(const comcfg::ConfigUnit& conf) {
    _infer_service_format = conf["name"].to_cstr();
    char merger[256];
    conf["merger"].get_cstr(merger, sizeof(merger), "default");
    if (!MergerManager::instance().get(merger, _merger)) {
        LOG(ERROR) << "Failed get merger: " << merger;
        return ERR_INTERNAL_FAILURE;
    } else {
        LOG(WARNING) << "Succ get merger: " << merger << 
            " for service: " << _infer_service_format;
    }
    ServerManager& svr_mgr = ServerManager::instance();
    if (svr_mgr.add_service_by_format(_infer_service_format) != 0) {
        LOG(FATAL) 
            << "Not found service by format name:"
            << _infer_service_format << "!";
        return ERR_INTERNAL_FAILURE;
    }
    
    uint32_t default_value = 0;
    conf["enable_map_request_to_workflow"].get_uint32(&default_value, 0);
    _enable_map_request_to_workflow = (default_value != 0);
    LOG(INFO) << "service[" << _infer_service_format
            << "], enable_map_request_to_workflow["
            << _enable_map_request_to_workflow << "].";

    uint32_t flow_size = conf["workflow"].size();
    if (_enable_map_request_to_workflow) {
        if (_request_to_workflow_map.init(
                MAX_WORKFLOW_NUM_IN_ONE_SERVICE/*load_factor=80*/) != 0) {
            LOG(FATAL) 
                << "init request to workflow map failed, bucket_count["
                << MAX_WORKFLOW_NUM_IN_ONE_SERVICE << "].";
            return ERR_INTERNAL_FAILURE;
        }
        int err = 0;
        const char* pchar = conf["request_field_key"].to_cstr(&err);
        if (err != 0) {
            LOG(FATAL) 
                << "read request_field_key failed, err_code[" 
                << err << "].";
            return ERR_INTERNAL_FAILURE;
        }
        _request_field_key = std::string(pchar); 
        LOG(INFO) 
            << "service[" << _infer_service_format
            << "], request_field_key[" 
            << _request_field_key << "].";
        uint32_t request_field_value_size = conf["request_field_value"].size();
        if (request_field_value_size != flow_size) {
            LOG(FATAL) 
                << "flow_size[" << flow_size 
                << "] not equal request_field_value_size[" 
                << request_field_value_size << "].";
            return ERR_INTERNAL_FAILURE;
        }

        for (uint32_t fi = 0; fi < flow_size; fi++) {
            std::vector<std::string> tokens;
            std::vector<Workflow*> workflows;
            std::string list = conf["workflow"][fi].to_cstr();
            boost::split(tokens, list, boost::is_any_of(","));
            uint32_t tsize = tokens.size();
            for (uint32_t ti = 0; ti < tsize; ++ti) {
                boost::trim_if(tokens[ti], boost::is_any_of(" "));
                Workflow* workflow = 
                    WorkflowManager::instance().item(tokens[ti]);
                if (workflow == NULL) {
                    LOG(FATAL) 
                        << "Failed get workflow by name:" 
                        << tokens[ti] << ", ti: " << ti;
                    return ERR_INTERNAL_FAILURE;
                }
                workflow->regist_metric(full_name());
                workflows.push_back(workflow);
            }
            const std::string& request_field_value = conf["request_field_value"][fi].to_cstr();
            if (_request_to_workflow_map.insert(request_field_value, workflows) == NULL) {
                LOG(FATAL) 
                    << "insert [" << request_field_value << "," 
                    << list << "] to _request_to_workflow_map failed.";
                return ERR_INTERNAL_FAILURE;
            }
            LOG(INFO) << "workflow[" << list
                << "], request_field_value[" << request_field_value << "].";
        }
    } else {
        for (uint32_t fi = 0; fi < flow_size; fi++) {
            const std::string& workflow_name = 
                conf["workflow"][fi].to_cstr();
            Workflow* workflow = 
                WorkflowManager::instance().item(workflow_name);
            if (workflow == NULL) {
                LOG(FATAL) 
                    << "Failed get workflow by name:" 
                    << workflow_name;
                return ERR_INTERNAL_FAILURE;
            }
            workflow->regist_metric(full_name());
            _flows.push_back(workflow);
        } 
    }

    LOG(TRACE) 
        << "Succ load infer_service: " 
        << _infer_service_format << "!";

    return ERR_OK;
} 

int InferService::reload() {
    return ERR_OK;
}

const std::string& InferService::name() const {
    return _infer_service_format;
}

// ´®ÐÐÖ´ÐÐÿ¸öworkflow
int InferService::inference(
        const google::protobuf::Message* request,
        google::protobuf::Message* response,
        base::IOBufBuilder* debug_os) {

    TRACEPRINTF("start to inference");
    // when funtion call begins, framework will reset
    // thread local variables&resources automatically.
    if (Resource::instance().thread_clear() != 0) {
        LOG(ERROR) << "Failed thread clear whole resource";
        return ERR_INTERNAL_FAILURE;
    }

    TRACEPRINTF("finish to thread clear");

    if (_enable_map_request_to_workflow) {
        std::vector<Workflow*>* workflows = _map_request_to_workflow(request);
        if (!workflows || workflows->size() == 0) {
            LOG(ERROR) << "Failed to map request to workflow";
            return ERR_INTERNAL_FAILURE;
        }
        size_t fsize = workflows->size();
        for (size_t fi = 0; fi < fsize; ++fi) {
            Workflow* workflow = (*workflows)[fi];
            if (workflow == NULL) {
                LOG(ERROR) << "Failed to get valid workflow at: " << fi;
                return ERR_INTERNAL_FAILURE;
            }
            TRACEPRINTF("start to execute workflow[%s]", workflow->name().c_str());
            int errcode = _execute_workflow(workflow, request, response, debug_os);
            TRACEPRINTF("finish to execute workflow[%s]", workflow->name().c_str());
            if (errcode < 0) {
                LOG(FATAL) << "Failed execute workflow[" << workflow->name()
                        << "] in:" << name();
                return errcode;
            }
        }
    } else {
        TRACEPRINTF("start to execute one workflow");
        size_t fsize = _flows.size();
        for (size_t fi = 0; fi < fsize; ++fi) {
            TRACEPRINTF("start to execute one workflow-%lu", fi);
            int errcode = execute_one_workflow(fi, request, response, debug_os);
            TRACEPRINTF("finish to execute one workflow-%lu", fi);
            if (errcode < 0) {
                LOG(FATAL) << "Failed execute 0-th workflow in:" << name();
                return errcode;
            }
        }
    }
    return ERR_OK;
}

int InferService::debug(
        const google::protobuf::Message* request,
        google::protobuf::Message* response,
        base::IOBufBuilder* debug_os) {
    return inference(request, response, debug_os);
}

int InferService::execute_one_workflow(
        uint32_t index, 
        const google::protobuf::Message* request, 
        google::protobuf::Message* response,
        base::IOBufBuilder* debug_os) {
    if (index >= _flows.size()) {
        LOG(FATAL) << "Faield execute workflow, index: "
            << index << " >= max:" << _flows.size();
        return ERR_OVERFLOW_FAILURE;
    } 
    Workflow* workflow = _flows[index];
    return _execute_workflow(workflow, request, response, debug_os);
}

int InferService::_execute_workflow(
        Workflow* workflow,
        const google::protobuf::Message* request, 
        google::protobuf::Message* response,
        base::IOBufBuilder* debug_os) {
    base::Timer workflow_time(base::Timer::STARTED);
    // create and submit beginer channel
    BuiltinChannel req_channel;
    req_channel.init(0, START_OP_NAME);
    req_channel = request;

    DagView* dv = workflow->fetch_dag_view(full_name());
    dv->set_request_channel(req_channel);

    // call actual inference interface
    int errcode = dv->execute(debug_os);
    if (errcode < 0) {
        LOG(FATAL) << "Failed execute dag for workflow:"
            << workflow->name();
        return errcode;
    }

    TRACEPRINTF("finish to dv execute");
    // create ender channel and copy
    const Channel* res_channel = dv->get_response_channel();
    if (!_merger || !_merger->merge(res_channel->message(), response)) {
        LOG(FATAL) << "Failed merge channel res to response"; 
        return ERR_INTERNAL_FAILURE;
    }
    TRACEPRINTF("finish to copy from");

    workflow_time.stop();
    PredictorMetric::GetInstance()->update_latency_metric(
            WORKFLOW_METRIC_PREFIX + dv->full_name(), workflow_time.u_elapsed());
    
    // return tls data to object pool
    workflow->return_dag_view(dv);
    TRACEPRINTF("finish to return dag view");
    return ERR_OK;
}

std::vector<Workflow*>* InferService::_map_request_to_workflow(
        const google::protobuf::Message* request) {
    const google::protobuf::Descriptor* desc = request->GetDescriptor();
    const google::protobuf::FieldDescriptor* field = desc->FindFieldByName(_request_field_key);
    if (field == NULL) {
        LOG(ERROR) << "No field[" << _request_field_key << "] in [" << desc->full_name() << "].";
        return NULL;
    }
    if (field->is_repeated()) {
        LOG(ERROR) << "field[" << desc->full_name() << "."
                << _request_field_key << "] is repeated.";
        return NULL;
    }
    if (field->cpp_type() != google::protobuf::FieldDescriptor::CPPTYPE_STRING) {
        LOG(ERROR) << "field[" << desc->full_name() << "."
                << _request_field_key << "] should be string";
        return NULL;
    }
    const std::string& field_value = request->GetReflection()->GetString(*request, field);
    std::vector<Workflow*>* p_workflow = _request_to_workflow_map.seek(field_value);
    if (p_workflow == NULL) {
        LOG(ERROR) << "cannot find key[" << field_value << "] in _request_to_workflow_map";
        return NULL;
    }
    return p_workflow;
}

} // predictor
} // paddle_serving
} // baidu