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#!/usr/bin/env python
# Copyright 2025 The HuggingFace Inc. team. 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.
import pytest
from lerobot.utils.logging_utils import AverageMeter, MetricsTracker
@pytest.fixture
def mock_metrics():
return {"loss": AverageMeter("loss", ":.3f"), "accuracy": AverageMeter("accuracy", ":.2f")}
def test_average_meter_initialization():
meter = AverageMeter("loss", ":.2f")
assert meter.name == "loss"
assert meter.fmt == ":.2f"
assert meter.val == 0.0
assert meter.avg == 0.0
assert meter.sum == 0.0
assert meter.count == 0.0
def test_average_meter_update():
meter = AverageMeter("accuracy")
meter.update(5, n=2)
assert meter.val == 5
assert meter.sum == 10
assert meter.count == 2
assert meter.avg == 5
def test_average_meter_reset():
meter = AverageMeter("loss")
meter.update(3, 4)
meter.reset()
assert meter.val == 0.0
assert meter.avg == 0.0
assert meter.sum == 0.0
assert meter.count == 0.0
def test_average_meter_str():
meter = AverageMeter("metric", ":.1f")
meter.update(4.567, 3)
assert str(meter) == "metric:4.6"
def test_metrics_tracker_initialization(mock_metrics):
tracker = MetricsTracker(
batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics, initial_step=10
)
assert tracker.steps == 10
assert tracker.samples == 10 * 32
assert tracker.episodes == tracker.samples / (1000 / 50)
assert tracker.epochs == tracker.samples / 1000
assert "loss" in tracker.metrics
assert "accuracy" in tracker.metrics
def test_metrics_tracker_step(mock_metrics):
tracker = MetricsTracker(
batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics, initial_step=5
)
tracker.step()
assert tracker.steps == 6
assert tracker.samples == 6 * 32
assert tracker.episodes == tracker.samples / (1000 / 50)
assert tracker.epochs == tracker.samples / 1000
def test_metrics_tracker_getattr(mock_metrics):
tracker = MetricsTracker(batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics)
assert tracker.loss == mock_metrics["loss"]
assert tracker.accuracy == mock_metrics["accuracy"]
with pytest.raises(AttributeError):
_ = tracker.non_existent_metric
def test_metrics_tracker_setattr(mock_metrics):
tracker = MetricsTracker(batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics)
tracker.loss = 2.0
assert tracker.loss.val == 2.0
def test_metrics_tracker_str(mock_metrics):
tracker = MetricsTracker(batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics)
tracker.loss.update(3.456, 1)
tracker.accuracy.update(0.876, 1)
output = str(tracker)
assert "loss:3.456" in output
assert "accuracy:0.88" in output
def test_metrics_tracker_to_dict(mock_metrics):
tracker = MetricsTracker(batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics)
tracker.loss.update(5, 2)
metrics_dict = tracker.to_dict()
assert isinstance(metrics_dict, dict)
assert metrics_dict["loss"] == 5 # average value
assert metrics_dict["steps"] == tracker.steps
def test_metrics_tracker_reset_averages(mock_metrics):
tracker = MetricsTracker(batch_size=32, num_frames=1000, num_episodes=50, metrics=mock_metrics)
tracker.loss.update(10, 3)
tracker.accuracy.update(0.95, 5)
tracker.reset_averages()
assert tracker.loss.avg == 0.0
assert tracker.accuracy.avg == 0.0
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