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transformers/examples/pytorch/old_test_xla_examples.py

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+# Copyright 2018 HuggingFace Inc..
+#
+# 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 json
+import logging
+import os
+import sys
+from time import time
+from unittest.mock import patch
+
+from transformers.testing_utils import TestCasePlus, require_torch_xla
+
+
+logging.basicConfig(level=logging.DEBUG)
+
+logger = logging.getLogger()
+
+
+def get_results(output_dir):
+    results = {}
+    path = os.path.join(output_dir, "all_results.json")
+    if os.path.exists(path):
+        with open(path) as f:
+            results = json.load(f)
+    else:
+        raise ValueError(f"can't find {path}")
+    return results
+
+
+stream_handler = logging.StreamHandler(sys.stdout)
+logger.addHandler(stream_handler)
+
+
+@require_torch_xla
+class TorchXLAExamplesTests(TestCasePlus):
+    def test_run_glue(self):
+        import xla_spawn
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            ./examples/pytorch/text-classification/run_glue.py
+            --num_cores=8
+            ./examples/pytorch/text-classification/run_glue.py
+            --model_name_or_path distilbert/distilbert-base-uncased
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
+            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
+            --do_train
+            --do_eval
+            --debug tpu_metrics_debug
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+            --learning_rate=1e-4
+            --max_steps=10
+            --warmup_steps=2
+            --seed=42
+            --max_seq_length=128
+            """.split()
+
+        with patch.object(sys, "argv", testargs):
+            start = time()
+            xla_spawn.main()
+            end = time()
+
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_accuracy"], 0.75)
+
+            # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
+            self.assertLess(end - start, 500)
+
+    def test_trainer_tpu(self):
+        import xla_spawn
+
+        testargs = """
+            ./tests/test_trainer_tpu.py
+            --num_cores=8
+            ./tests/test_trainer_tpu.py
+            """.split()
+        with patch.object(sys, "argv", testargs):
+            xla_spawn.main()