Feature/Model Testing During Training
This merge request contains following changes,
- Metrics class for performing default evaluation metrics (fedbiomed/common/metrics.py)
- Testing routine for
TorchTrainingPlan
andSkLearnSGDModel
- Processing testing argument in the
Round
class, to make sure is everthing OK to perform testing. - Extending
add_scalar
message of HistoryMonitor, adding more information about real-time training/testing status -
json.py
encode/decodeMetricType
defined in the experiment - Changes in
fedbiomed/researcher/monitor.py
- MetricStore -> to store and categorize metric values received in real-time
- Logging training/testing metric values to console as fancy/readable as possbile
- Categorizing plots on the Tensorboard (with headers) based on metric name, metric for training/testing_global_updates/testing_localupdates
- Adding unittests for;
- metric.py ->
MetricTypes
,Metrics
- monitor.py ->
_MetricStore
- fedbiosklearn.py ->
testing_routine
- torchnn.py ->
testing_routine
- metric.py ->
Edited by CANSIZ Sergen