tensorflow:: מָנָה:: ServerCore:: אפשרויות #include <server_core.h>

אפשרויות עבור קינפוג ServerCore אובייקט.

סיכום
תכונות ציבוריות
allow_version_labels = true
bool
allow_version_labels_for_unavailable_models = false
bool
aspired_version_policy
std::unique_ptr< AspiredVersionPolicy >
custom_model_config_loader
fail_if_no_model_versions_found = false
bool
file_system_poll_wait_seconds = 30
int32
flush_filesystem_caches = false
bool
load_retry_interval_micros = 1LL * 60 * 1000 * 1000
int64
max_num_load_retries = 5
int32
model_config_list_root_dir
optional< string >
model_server_config
ModelServerConfig
num_initial_load_threads = 4.0 * port::NumSchedulableCPUs()
int32
num_load_threads = 0
int32
num_unload_threads = 0
int32
platform_config_map
PlatformConfigMap
pre_load_hook
PreLoadHook
predict_response_tensor_serialization_option = internal::PredictResponseTensorSerializationOption::kAsProtoField
internal::PredictResponseTensorSerializationOption
servable_state_monitor_creator
ServableStateMonitorCreator
servable_versions_always_present = false
bool
server_request_logger
std::unique_ptr< ServerRequestLogger >
server_request_logger_updater
storage_path_prefix
std::string
total_model_memory_limit_bytes = std::numeric_limits ::max() total_model_memory_limit_bytes = std::numeric_limits ::max()
uint64
תכונות ציבוריות
allow_version_labels 
bool tensorflow::serving::ServerCore::Options::allow_version_labels = true
allow_version_labels_for_unavailable_models 
bool tensorflow::serving::ServerCore::Options::allow_version_labels_for_unavailable_models = false
aspired_version_policy 
std::unique_ptr< AspiredVersionPolicy > tensorflow::serving::ServerCore::Options::aspired_version_policy
custom_model_config_loader 
CustomModelConfigLoader tensorflow::serving::ServerCore::Options::custom_model_config_loader
fail_if_no_model_versions_found 
bool tensorflow::serving::ServerCore::Options::fail_if_no_model_versions_found = false
file_system_poll_wait_seconds 
int32 tensorflow::serving::ServerCore::Options::file_system_poll_wait_seconds = 30
flush_filesystem_caches 
bool tensorflow::serving::ServerCore::Options::flush_filesystem_caches = false
load_retry_interval_micros 
int64 tensorflow::serving::ServerCore::Options::load_retry_interval_micros = 1LL * 60 * 1000 * 1000
max_num_load_resies 
int32 tensorflow::serving::ServerCore::Options::max_num_load_retries = 5
model_config_list_root_dir 
optional< string > tensorflow::serving::ServerCore::Options::model_config_list_root_dir
model_server_config 
ModelServerConfig tensorflow::serving::ServerCore::Options::model_server_config
num_initial_load_threads 
int32 tensorflow::serving::ServerCore::Options::num_initial_load_threads = 4.0 * port::NumSchedulableCPUs()
num_load_threads 
int32 tensorflow::serving::ServerCore::Options::num_load_threads = 0
num_unload_threads 
int32 tensorflow::serving::ServerCore::Options::num_unload_threads = 0
platform_config_map 
PlatformConfigMap tensorflow::serving::ServerCore::Options::platform_config_map
הוק_pre_load 
PreLoadHook tensorflow::serving::ServerCore::Options::pre_load_hook
predict_response_tensor_serialization_option 
internal::PredictResponseTensorSerializationOption tensorflow::serving::ServerCore::Options::predict_response_tensor_serialization_option =
            internal::PredictResponseTensorSerializationOption::kAsProtoField
שרת_state_monitor_creator 
ServableStateMonitorCreator tensorflow::serving::ServerCore::Options::servable_state_monitor_creator
servables_versions_always_present 
bool tensorflow::serving::ServerCore::Options::servable_versions_always_present = false
server_request_logger 
std::unique_ptr< ServerRequestLogger > tensorflow::serving::ServerCore::Options::server_request_logger
server_request_logger_updater 
ServerRequestLoggerUpdater tensorflow::serving::ServerCore::Options::server_request_logger_updater
storage_path_prefix 
std::string tensorflow::serving::ServerCore::Options::storage_path_prefix
total_model_memory_limit_bytes 
uint64 tensorflow::serving::ServerCore::Options::total_model_memory_limit_bytes = std::numeric_limits::max()