Refactoring the generate() function (#6949)

* first draft

* show design proposition for new generate method

* up

* make better readable

* make first version

* gpt2 tests pass

* make beam search for gpt2 work

* add first encoder-decoder code

* delete typo

* make t5 work

* save indermediate

* make bart work with beam search

* finish beam search bart / t5

* add default kwargs

* make more tests pass

* fix no bad words sampler

* some fixes and tests for all distribution processors

* fix test

* fix rag slow tests

* merge to master

* add nograd to generate

* make all slow tests pass

* speed up generate

* fix edge case bug

* small fix

* correct typo

* add type hints and docstrings

* fix typos in tests

* add beam search tests

* add tests for beam scorer

* fix test rag

* finish beam search tests

* move generation tests in seperate file

* fix generation tests

* more tests

* add aggressive generation tests

* fix tests

* add gpt2 sample test

* add more docstring

* add more docs

* finish doc strings

* apply some more of sylvains and sams comments

* fix some typos

* make fix copies

* apply lysandres and sylvains comments

* final corrections on examples

* small fix for reformer

tests/test_modeling_gpt2.py

@@ -20,6 +20,7 @@ from transformers import is_torch_available
 from transformers.testing_utils import require_torch, slow, torch_device
 
 from .test_configuration_common import ConfigTester
+from .test_generation_utils import GenerationTesterMixin
 from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
 
 
@@ -377,7 +378,7 @@ class GPT2ModelTester:
 
 
 @require_torch
-class GPT2ModelTest(ModelTesterMixin, unittest.TestCase):
+class GPT2ModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
 
     all_model_classes = (
         (GPT2Model, GPT2LMHeadModel, GPT2DoubleHeadsModel, GPT2ForSequenceClassification)
@@ -510,32 +511,17 @@ class GPT2ModelLanguageGenerationTest(unittest.TestCase):
             self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
 
     @slow
-    def test_lm_generate_distilgpt2(self):
-        model = GPT2LMHeadModel.from_pretrained("distilgpt2")
+    def test_gpt2_sample(self):
+        tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+        model = GPT2LMHeadModel.from_pretrained("gpt2")
         model.to(torch_device)
-        input_ids = torch.tensor([[464, 1893]], dtype=torch.long, device=torch_device)  # The president
-        expected_output_ids = [
-            464,
-            1893,
-            286,
-            262,
-            1578,
-            1829,
-            11,
-            290,
-            262,
-            1893,
-            286,
-            262,
-            1578,
-            7526,
-            11,
-            423,
-            587,
-            287,
-            262,
-            2635,
-        ]  # The president of the United States, and the president of the United Kingdom, have been in the White
 
-        output_ids = model.generate(input_ids, do_sample=False)
-        self.assertListEqual(output_ids[0].tolist(), expected_output_ids)
+        torch.manual_seed(0)
+        input_ids = tokenizer("Today is a nice day and", return_tensors="pt").input_ids.to(torch_device)
+        output_ids = model.generate(input_ids, do_sample=True)
+        output_str = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+        EXPECTED_OUTPUT_STR = (
+            "Today is a nice day and if you don't know anything about the state of play during your holiday"
+        )
+        self.assertEqual(output_str, EXPECTED_OUTPUT_STR)