'Connection': 'close'
}
DETECT_TABLE = ("fate_flow_detect_table_namespace", "fate_flow_detect_table_name", 16)
# fate-serving
SERVINGS_ZK_PATH = '/FATE-SERVICES/serving/online/publishLoad/providers'
FATE_FLOW_ZK_PATH = '/FATE-SERVICES/flow/online/transfer/providers'
FATE_FLOW_MODEL_TRANSFER_PATH = '/v1/model/transfer'
# fate-manager
FATE_MANAGER_GET_NODE_INFO = '/node/info'
FATE_MANAGER_NODE_CHECK = '/node/management/check'
# logger
log_utils.LoggerFactory.LEVEL = 10
# {CRITICAL: 50, FATAL:50, ERROR:40, WARNING:30, WARN:30, INFO:20, DEBUG:10, NOTSET:0}
log_utils.LoggerFactory.set_directory(os.path.join(file_utils.get_project_base_directory(), 'logs', 'fate_flow'))
stat_logger = log_utils.getLogger("fate_flow_stat")
detect_logger = log_utils.getLogger("fate_flow_detect")
access_logger = log_utils.getLogger("fate_flow_access")
audit_logger = log_utils.audit_logger()
"""
Services
"""
IP = get_base_config("fate_flow", {}).get("host", "0.0.0.0")
HTTP_PORT = get_base_config("fate_flow", {}).get("http_port")
GRPC_PORT = get_base_config("fate_flow", {}).get("grpc_port")
# standalone job will be send to the standalone job server when FATE-Flow work on cluster deploy mode,
# but not the port for FATE-Flow on standalone deploy mode.
CLUSTER_STANDALONE_JOB_SERVER_PORT = 9381
from fate_flow.entity.metric import Metric
from fate_flow.entity.metric import MetricMeta
from federatedml.feature.instance import Instance
from federatedml.feature.sparse_vector import SparseVector
from federatedml.util import consts
from federatedml.util import abnormal_detection
from federatedml.statistic import data_overview
from federatedml.model_base import ModelBase
from federatedml.protobuf.generated.data_io_meta_pb2 import DataIOMeta
from federatedml.protobuf.generated.data_io_param_pb2 import DataIOParam
from federatedml.protobuf.generated.data_io_meta_pb2 import ImputerMeta
from federatedml.protobuf.generated.data_io_param_pb2 import ImputerParam
from federatedml.protobuf.generated.data_io_meta_pb2 import OutlierMeta
from federatedml.protobuf.generated.data_io_param_pb2 import OutlierParam
LOGGER = log_utils.getLogger()
# =============================================================================
# DenseFeatureReader
# =============================================================================
class DenseFeatureReader(object):
def __init__(self, data_io_param):
self.delimitor = data_io_param.delimitor
self.data_type = data_io_param.data_type
self.missing_fill = data_io_param.missing_fill
self.default_value = data_io_param.default_value
self.missing_fill_method = data_io_param.missing_fill_method
self.missing_impute = data_io_param.missing_impute
self.outlier_replace = data_io_param.outlier_replace
self.outlier_replace_method = data_io_param.outlier_replace_method
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import deque
from arch.api.utils.log_utils import getLogger
LOGGER = getLogger()
class Rubbish(object):
"""
a collection collects all tables / objects in federation tagged by `tag`.
"""
def __init__(self, name, tag):
self._name = name
self._tag = tag
self._tables = []
self._kv = {}
@property
def tag(self):
return self._tag
