Add Flax example tests (#14599)

* add test for glue

* add tests for clm

* fix clm test

* add summrization tests

* more tests

* fix few tests

* add test for t5 mlm

* fix t5 mlm test

* fix tests for multi device

* cleanup

* ci job

* fix metric file name

* make t5 more robust

examples/flax/test_examples.py

@@ -0,0 +1,270 @@
+# coding=utf-8
+# Copyright 2021 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 argparse
+import json
+import logging
+import os
+import sys
+from unittest.mock import patch
+
+from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
+
+
+SRC_DIRS = [
+    os.path.join(os.path.dirname(__file__), dirname)
+    for dirname in [
+        "text-classification",
+        "language-modeling",
+        "summarization",
+        "token-classification",
+        "question-answering",
+    ]
+]
+sys.path.extend(SRC_DIRS)
+
+
+if SRC_DIRS is not None:
+    import run_clm_flax
+    import run_flax_glue
+    import run_flax_ner
+    import run_mlm_flax
+    import run_qa
+    import run_summarization_flax
+    import run_t5_mlm_flax
+
+
+logging.basicConfig(level=logging.DEBUG)
+
+logger = logging.getLogger()
+
+
+def get_setup_file():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-f")
+    args = parser.parse_args()
+    return args.f
+
+
+def get_results(output_dir, split="eval"):
+    results = {}
+    path = os.path.join(output_dir, f"{split}_results.json")
+    if os.path.exists(path):
+        with open(path, "r") as f:
+            results = json.load(f)
+    else:
+        raise ValueError(f"can't find {path}")
+    return results
+
+
+class ExamplesTests(TestCasePlus):
+    def test_run_glue(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_glue.py
+            --model_name_or_path distilbert-base-uncased
+            --output_dir {tmp_dir}
+            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
+            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+            --learning_rate=1e-4
+            --max_train_steps=10
+            --num_warmup_steps=2
+            --seed=42
+            --max_length=128
+            """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_flax_glue.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_accuracy"], 0.75)
+
+    def test_run_clm(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_clm_flax.py
+            --model_name_or_path distilgpt2
+            --train_file ./tests/fixtures/sample_text.txt
+            --validation_file ./tests/fixtures/sample_text.txt
+            --do_train
+            --do_eval
+            --block_size 128
+            --per_device_train_batch_size 4
+            --per_device_eval_batch_size 4
+            --num_train_epochs 2
+            --logging_steps 2 --eval_steps 2
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_clm_flax.main()
+            result = get_results(tmp_dir)
+            self.assertLess(result["eval_perplexity"], 100)
+
+    @slow
+    def test_run_summarization(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_summarization.py
+            --model_name_or_path t5-small
+            --train_file tests/fixtures/tests_samples/xsum/sample.json
+            --validation_file tests/fixtures/tests_samples/xsum/sample.json
+            --test_file tests/fixtures/tests_samples/xsum/sample.json
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            --max_steps=50
+            --warmup_steps=8
+            --do_train
+            --do_eval
+            --do_predict
+            --learning_rate=2e-4
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+            --predict_with_generate
+        """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_summarization_flax.main()
+            result = get_results(tmp_dir, split="test")
+            self.assertGreaterEqual(result["test_rouge1"], 10)
+            self.assertGreaterEqual(result["test_rouge2"], 2)
+            self.assertGreaterEqual(result["test_rougeL"], 7)
+            self.assertGreaterEqual(result["test_rougeLsum"], 7)
+
+    def test_run_mlm(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_mlm.py
+            --model_name_or_path distilroberta-base
+            --train_file ./tests/fixtures/sample_text.txt
+            --validation_file ./tests/fixtures/sample_text.txt
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            --max_seq_length 128
+            --per_device_train_batch_size 4
+            --per_device_eval_batch_size 4
+            --logging_steps 2 --eval_steps 2
+            --do_train
+            --do_eval
+            --num_train_epochs=1
+        """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_mlm_flax.main()
+            result = get_results(tmp_dir)
+            self.assertLess(result["eval_perplexity"], 42)
+
+    @slow
+    def test_run_t5_mlm(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_t5_mlm_flax.py
+            --model_name_or_path t5-small
+            --train_file ./tests/fixtures/sample_text.txt
+            --validation_file ./tests/fixtures/sample_text.txt
+            --do_train
+            --do_eval
+            --max_seq_length 128
+            --per_device_train_batch_size 4
+            --per_device_eval_batch_size 4
+            --num_train_epochs 2
+            --logging_steps 2 --eval_steps 2
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_t5_mlm_flax.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_accuracy"], 0.42)
+
+    def test_run_ner(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
+        epochs = 7 if get_gpu_count() > 1 else 2
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_flax_ner.py
+            --model_name_or_path bert-base-uncased
+            --train_file tests/fixtures/tests_samples/conll/sample.json
+            --validation_file tests/fixtures/tests_samples/conll/sample.json
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            --do_train
+            --do_eval
+            --warmup_steps=2
+            --learning_rate=2e-4
+            --logging_steps 2 --eval_steps 2
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=2
+            --num_train_epochs={epochs}
+            --seed 7
+        """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_flax_ner.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_accuracy"], 0.75)
+            self.assertGreaterEqual(result["eval_f1"], 0.3)
+
+    def test_run_qa(self):
+        stream_handler = logging.StreamHandler(sys.stdout)
+        logger.addHandler(stream_handler)
+
+        tmp_dir = self.get_auto_remove_tmp_dir()
+        testargs = f"""
+            run_qa.py
+            --model_name_or_path bert-base-uncased
+            --version_2_with_negative
+            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
+            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
+            --output_dir {tmp_dir}
+            --overwrite_output_dir
+            --max_steps=10
+            --warmup_steps=2
+            --do_train
+            --do_eval
+            --logging_steps 2 --eval_steps 2
+            --learning_rate=2e-4
+            --per_device_train_batch_size=2
+            --per_device_eval_batch_size=1
+        """.split()
+
+        with patch.object(sys, "argv", testargs):
+            run_qa.main()
+            result = get_results(tmp_dir)
+            self.assertGreaterEqual(result["eval_f1"], 30)
+            self.assertGreaterEqual(result["eval_exact"], 30)