Organize test folders (#856)

Co-authored-by: Steven Palma <imstevenpmwork@ieee.org>

tests/utils/test_logging_utils.py

@@ -0,0 +1,120 @@
+# Copyright 2024 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.common.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