✨ Add PyTorch image classification example (#13134)

* ✨ add pytorch image classification example

* 🔥 remove utils.py

* 💄 fix flake8 style issues

* 🔥 remove unnecessary line

* ✨ limit dataset sizes

* 📌 update reqs

* 🎨 restructure - use datasets lib

* 🎨 import transforms directly

* 📝 add comments

* 💄 style

* 🔥 remove flag

* 📌 update requirement warning

* 📝 add vision README.md

* 📝 update README.md

* 📝 update README.md

* 🎨 add image-classification tag to model card

* 🚚 rename vision ➡️ image-classification

* 📝 update image-classification README.md

examples/pytorch/test_examples.py

@@ -38,6 +38,7 @@ SRC_DIRS = [
         "question-answering",
         "summarization",
         "translation",
+        "image-classification",
     ]
 ]
 sys.path.extend(SRC_DIRS)
@@ -47,6 +48,7 @@ if SRC_DIRS is not None:
     import run_clm
     import run_generation
     import run_glue
+    import run_image_classification
     import run_mlm
     import run_ner
     import run_qa as run_squad
@@ -340,3 +342,35 @@ class ExamplesTests(TestCasePlus):
             run_translation.main()
             result = get_results(tmp_dir)
             self.assertGreaterEqual(result["eval_bleu"], 30)
+
+    def test_run_image_classification(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_image_classification.py
+            --output_dir {tmp_dir}
+            --model_name_or_path google/vit-base-patch16-224-in21k
+            --train_dir tests/fixtures/tests_samples/cats_and_dogs/
+            --do_train
+            --do_eval
+            --learning_rate 2e-5
+            --per_device_train_batch_size 2
+            --per_device_eval_batch_size 1
+            --remove_unused_columns False
+            --overwrite_output_dir True
+            --dataloader_num_workers 16
+            --metric_for_best_model accuracy
+            --max_steps 30
+            --train_val_split 0.1
+            --seed 7
+        """.split()
+
+        if is_cuda_and_apex_available():
+            testargs.append("--fp16")
+
+        with patch.object(sys, "argv", testargs):
+            run_image_classification.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_accuracy"], 0.8)