Add semantic script no trainer, v2 (#16788)

* Add first draft from previous PR

* First draft

* Improve README and remove num_labels

* Make script more aligned with other scripts

* Improve README and apply suggestion from code review

examples/pytorch/test_accelerate_examples.py

@@ -43,6 +43,7 @@ SRC_DIRS = [
         "audio-classification",
         "speech-pretraining",
         "image-pretraining",
+        "semantic-segmentation",
     ]
 ]
 sys.path.extend(SRC_DIRS)
@@ -54,6 +55,7 @@ if SRC_DIRS is not None:
     import run_mlm_no_trainer
     import run_ner_no_trainer
     import run_qa_no_trainer as run_squad_no_trainer
+    import run_semantic_segmentation_no_trainer
     import run_summarization_no_trainer
     import run_swag_no_trainer
     import run_translation_no_trainer
@@ -296,3 +298,26 @@ class ExamplesTestsNoTrainer(TestCasePlus):
             self.assertGreaterEqual(result["eval_bleu"], 30)
             self.assertTrue(os.path.exists(os.path.join(tmp_dir, "epoch_0")))
             self.assertTrue(os.path.exists(os.path.join(tmp_dir, "translation_no_trainer")))
+
+    @slow
+    def test_run_semantic_segmentation_no_trainer(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_semantic_segmentation_no_trainer.py
+            --dataset_name huggingface/semantic-segmentation-test-sample
+            --output_dir {tmp_dir}
+            --max_train_steps=10
+            --num_warmup_steps=2
+            --learning_rate=2e-4
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+            --checkpointing_steps epoch
+        """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_semantic_segmentation_no_trainer.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_overall_accuracy"], 0.10)