chore: import upstream snapshot with attribution

tests/training/test_trainer.py

@@ -0,0 +1,79 @@
+# ------------------------------------------------------------------------
+# RF-DETR
+# Copyright (c) 2025 Roboflow. All Rights Reserved.
+# Licensed under the Apache License, Version 2.0 [see LICENSE for details]
+# ------------------------------------------------------------------------
+"""Unit tests for build_trainer() — callback stack and config coercion."""
+
+import pytest
+from pytorch_lightning.callbacks import RichProgressBar, TQDMProgressBar
+
+from rfdetr.training import build_trainer
+
+# ---------------------------------------------------------------------------
+# TestProgressBarCallbacks — verifies the correct callback is installed
+# ---------------------------------------------------------------------------
+
+
+class TestProgressBarCallbacks:
+    """build_trainer() must install the right progress bar callback for each mode."""
+
+    def test_rich_progress_bar_installed_for_rich(self, base_model_config, base_train_config):
+        """progress_bar='rich' must add RichProgressBar and not TQDMProgressBar."""
+        mc = base_model_config()
+        tc = base_train_config(progress_bar="rich")
+        trainer = build_trainer(tc, mc, accelerator="cpu")
+        cb_types = [type(cb) for cb in trainer.callbacks]
+        assert RichProgressBar in cb_types
+        assert TQDMProgressBar not in cb_types
+
+    def test_tqdm_progress_bar_installed_for_tqdm(self, base_model_config, base_train_config):
+        """progress_bar='tqdm' must add TQDMProgressBar and not RichProgressBar."""
+        mc = base_model_config()
+        tc = base_train_config(progress_bar="tqdm")
+        trainer = build_trainer(tc, mc, accelerator="cpu")
+        cb_types = [type(cb) for cb in trainer.callbacks]
+        assert TQDMProgressBar in cb_types
+        assert RichProgressBar not in cb_types
+
+    def test_progress_bar_refresh_rate_is_five(self, base_model_config, base_train_config):
+        """The installed progress bar callback should refresh every five batches."""
+        mc = base_model_config()
+        tc = base_train_config(progress_bar="tqdm")
+        trainer = build_trainer(tc, mc, accelerator="cpu")
+        progress_bar = next(cb for cb in trainer.callbacks if isinstance(cb, TQDMProgressBar))
+
+        assert progress_bar.refresh_rate == 5
+
+    def test_no_progress_bar_callback_for_none(self, base_model_config, base_train_config):
+        """progress_bar=None must not add any progress bar callback."""
+        mc = base_model_config()
+        tc = base_train_config(progress_bar=None)
+        trainer = build_trainer(tc, mc, accelerator="cpu")
+        cb_types = [type(cb) for cb in trainer.callbacks]
+        assert RichProgressBar not in cb_types
+        assert TQDMProgressBar not in cb_types
+
+
+# ---------------------------------------------------------------------------
+# TestCoerceLegacyProgressBar — backward-compat validator on TrainConfig
+# ---------------------------------------------------------------------------
+
+
+class TestCoerceLegacyProgressBar:
+    """_coerce_legacy_progress_bar must normalise legacy bool values."""
+
+    @pytest.mark.parametrize(
+        "value, expected",
+        [
+            pytest.param(True, "tqdm", id="True->tqdm"),
+            pytest.param(False, None, id="False->None"),
+            pytest.param("rich", "rich", id="rich_passthrough"),
+            pytest.param("tqdm", "tqdm", id="tqdm_passthrough"),
+            pytest.param(None, None, id="None_passthrough"),
+        ],
+    )
+    def test_coerce(self, base_train_config, value, expected):
+        """progress_bar field normalises legacy bool and passes through string/None."""
+        tc = base_train_config(progress_bar=value)
+        assert tc.progress_bar == expected