nvflare.apis.analytix module
- class AnalyticsData(key: str, value, data_type: AnalyticsDataType, sender: LogWriterName = LogWriterName.TORCH_TB, **kwargs)[source]
Bases:
objectThis class defines AnalyticsData format.
It is a wrapper to provide to/from DXO conversion.
- Parameters:
key (str) – tag name
value – value
data_type (AnalyticDataType) – type of the analytic data.
sender (LogWriterName) – Type of sender for syntax such as Tensorboard or MLflow
kwargs (optional, dict) – additional arguments to be passed.
- classmethod convert_data_type(sender_data_type: AnalyticsDataType, sender: LogWriterName, receiver: LogWriterName) AnalyticsDataType[source]
- classmethod from_dxo(dxo: DXO, receiver: LogWriterName = LogWriterName.TORCH_TB)[source]
Generates the AnalyticsData from DXO object.
- Parameters:
receiver – type of the experiment tacker, defaults to Tensorboard with LogWriterName.TORCH_TB.
dxo (DXO) – The DXO object to convert.
- Returns:
AnalyticsData object
- class AnalyticsDataType(value)[source]
Bases:
EnumAn enumeration.
- IMAGE = 'IMAGE'
- INIT_DATA = 'INIT_DATA'
- LOG_RECORD = 'LOG_RECORD'
- METRIC = 'METRIC'
- METRICS = 'METRICS'
- MODEL = 'MODEL'
- PARAMETER = 'PARAMETER'
- PARAMETERS = 'PARAMETERS'
- SCALAR = 'SCALAR'
- SCALARS = 'SCALARS'
- TAG = 'TAG'
- TAGS = 'TAGS'
- TEXT = 'TEXT'
- class LogWriterName(value)[source]
Bases:
EnumAn enumeration.
- MLFLOW = 'MLFLOW'
- TORCH_TB = 'TORCH_TENSORBOARD'
- WANDB = 'WEIGHTS_AND_BIASES'
- class TrackConst[source]
Bases:
object- DATA_TYPE_KEY = 'analytics_data_type'
- EXPERIMENT_NAME = 'experiment_name'
- EXPERIMENT_TAGS = 'experiment_tags'
- EXP_TAGS_KEY = 'tags_key'
- GLOBAL_STEP_KEY = 'global_step'
- INIT_CONFIG = 'init_config'
- JOB_ID_KEY = 'job_id'
- KWARGS_KEY = 'analytics_kwargs'
- PATH_KEY = 'path'
- PROJECT_NAME = 'project_name'
- PROJECT_TAGS = 'project_name'
- RUN_NAME = 'run_name'
- RUN_TAGS = 'run_tags'
- SITE_KEY = 'site'
- TAGS_KEY = 'tags_key'
- TAG_KEY = 'tag_key'
- TRACKER_KEY = 'tracker_key'
- TRACK_KEY = 'track_key'
- TRACK_VALUE = 'track_value'