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Fix spurious liger token_accuracy CI warnings in SFT tests #6189

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Fix spurious liger token_accuracy CI warnings in SFT tests #6189

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10 changes: 8 additions & 2 deletions tests/test_sft_trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.

import collections
import copy
import gc
import json
Expand Down Expand Up @@ -950,7 +951,7 @@ def mock_super_compute_loss(model, inputs, return_outputs=False, num_items_in_ba
captured["skip_logits"] = inputs.get("skip_logits")
dummy_loss = torch.tensor(1.0, requires_grad=True)
dummy_outputs = MagicMock()
dummy_outputs.token_accuracy = None
dummy_outputs.token_accuracy = torch.tensor(0.5)
dummy_outputs.logits = torch.randn(1, 5, trainer.model.config.vocab_size)
return (dummy_loss, dummy_outputs)

Expand Down Expand Up @@ -994,7 +995,12 @@ def test_predict_does_not_skip_logits_with_liger(self):
def mock_super_compute_loss(model, inputs, return_outputs=False, num_items_in_batch=None):
captured["skip_logits"] = inputs.get("skip_logits")
dummy_loss = torch.tensor(1.0, requires_grad=True)
dummy_outputs = (dummy_loss, torch.randn(1, 5, trainer.model.config.vocab_size))
DummyOutput = collections.namedtuple("DummyOutput", ["loss", "logits", "token_accuracy"])
dummy_outputs = DummyOutput(
loss=dummy_loss,
logits=torch.randn(1, 5, trainer.model.config.vocab_size),
token_accuracy=torch.tensor(0.5),
)
return (dummy_loss, dummy_outputs)

with patch("transformers.Trainer.compute_loss", side_effect=mock_super_compute_loss):
Expand Down
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