# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# 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 typing import Dict, Optional
from nvflare.apis.analytix import AnalyticsDataType
from nvflare.app_common.tracking.log_writer import LogWriter
from nvflare.app_common.tracking.tracker_types import LogWriterName
from nvflare.app_common.widgets.streaming import ANALYTIC_EVENT_TYPE
[docs]class WandBWriter(LogWriter):
def __init__(self, event_type: str = ANALYTIC_EVENT_TYPE):
super().__init__(event_type)
[docs] def get_writer_name(self) -> LogWriterName:
"""Returns "WEIGHTS_AND_BIASES"."""
return LogWriterName.WANDB
[docs] def log(self, metrics: Dict[str, float], step: Optional[int] = None):
"""Log multiple metrics for the current run.
Args:
metrics (Dict[str, float]): Dictionary of metric_name of type String to Float values.
step (int, optional): A single integer step at which to log the specified Metrics.
"""
self.sender.add(tag="metrics", value=metrics, data_type=AnalyticsDataType.METRICS, global_step=step)