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a8eb6e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | #!/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")}
class MockAccelerator:
def __init__(self, num_processes: int):
self.num_processes = num_processes
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_initialization_with_accelerator(mock_metrics):
tracker = MetricsTracker(
batch_size=32,
num_frames=1000,
num_episodes=50,
metrics=mock_metrics,
initial_step=10,
accelerator=MockAccelerator(num_processes=2),
)
assert tracker.steps == 10
assert tracker.samples == 10 * 32 * 2
assert tracker.episodes == tracker.samples / (1000 / 50)
assert tracker.epochs == tracker.samples / 1000
def test_metrics_tracker_step_with_accelerator(mock_metrics):
tracker = MetricsTracker(
batch_size=32,
num_frames=1000,
num_episodes=50,
metrics=mock_metrics,
initial_step=5,
accelerator=MockAccelerator(num_processes=2),
)
tracker.step()
assert tracker.steps == 6
assert tracker.samples == (5 * 32 * 2) + (32 * 2)
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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