# Copyright 2022 Cerebras Systems.
#
# 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,
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"""This module contains the callback class that logs all metrics attached to the model."""
from cerebras.modelzoo.trainer.callbacks import Callback
from cerebras.pytorch.metrics.metric import Metric
[docs]class ModelEvalMetrics(Callback):
"""Callback class that logs all metrics attached to the model."""
[docs] def on_validate_end(self, trainer, model, loop):
if trainer.backend.is_e2e_execution:
# Print all metrics that are attached to the model
metrics = {}
for metric in model.modules():
if isinstance(metric, Metric):
if metric.num_updates == 0:
trainer.logger.warning(
f"Skipping logging unused metric `{metric.name}` "
f"To remove this warning, either remove it from "
f"the model or step the metric every step."
)
else:
metrics[metric.name] = float(metric)
metric.reset()
trainer.log_metrics(**metrics)