fix double eos token for chatml (#1054) [skip ci]

* fix double eos token for chatml

* isolate fix to chatml conversation

* fix add special tokens to include rstrip

* add test for train_on_inputs for sharegpt

* don't use rstrip for chatml

src/axolotl/prompt_tokenizers.py

@@ -392,9 +392,13 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
                     # this should be the assistant response, should end with an eos token
                     if not content.strip():
                         LOG.warning(f"assistant turn has empty text: {prompt}")
+                    add_eos_token = not (
+                        conversation.name == "chatml"
+                        and conversation.sep == self.tokenizer.eos_token
+                    )
                     res = self._tokenize(
                         turn,
-                        add_eos_token=True,
+                        add_eos_token=add_eos_token,
                         strip_bos_token=True,
                     )
                     role_res = self._tokenize(

tests/prompt_strategies/test_sharegpt.py

@@ -0,0 +1,153 @@
+"""
+Test module for sharegpt integration w chatml
+"""
+import pytest
+from datasets import Dataset
+from tokenizers import AddedToken
+from transformers import AutoTokenizer
+
+from axolotl.datasets import TokenizedPromptDataset
+from axolotl.prompt_strategies.sharegpt import SimpleShareGPTPromptTokenizingStrategy
+from axolotl.prompters import ShareGPTPrompterV2
+
+
+@pytest.fixture(name="sharegpt_dataset")
+def fixture_sharegpt_dataset():
+    return Dataset.from_list(
+        [
+            {
+                "conversations": [
+                    {
+                        "from": "system",
+                        "value": "repeat",
+                    },
+                    {
+                        "from": "human",
+                        "value": "hello",
+                    },
+                    {
+                        "from": "gpt",
+                        "value": "hello",
+                    },
+                    {
+                        "from": "human",
+                        "value": "goodbye",
+                    },
+                    {
+                        "from": "gpt",
+                        "value": "goodbye",
+                    },
+                ]
+            }
+        ]
+    )
+
+
+@pytest.fixture(name="tokenizer")
+def fixture_tokenizer():
+    tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
+    tokenizer.add_special_tokens(
+        {
+            "eos_token": AddedToken(
+                "<|im_end|>", rstrip=False, lstrip=False, normalized=False
+            )
+        }
+    )
+    tokenizer.add_tokens(
+        [
+            AddedToken("<|im_start|>", rstrip=False, lstrip=False, normalized=False),
+        ]
+    )
+
+    return tokenizer
+
+
+class TestSharegpt:
+    """
+    Test class for sharegpt prompter
+    """
+
+    def test_no_double_im_end(self, sharegpt_dataset, tokenizer):
+        strategy = SimpleShareGPTPromptTokenizingStrategy(
+            ShareGPTPrompterV2(
+                conversation="chatml",
+                role_key_model=None,
+                role_key_human=None,
+            ),
+            tokenizer,
+            False,  # train_on_inputs
+            2048,  # sequence_len
+        )
+
+        dataset_wrapper = TokenizedPromptDataset(
+            strategy, sharegpt_dataset, process_count=1
+        )
+
+        input_ids = dataset_wrapper[0]["input_ids"]
+        # fmt: off
+        assert input_ids == [
+            #  28705, 13, is " \n"
+            1,   # bos
+            32001, 1587, 13, 25997, 32000, 28705, 13,  # system
+            32001, 2188, 13, 21558, 32000, 28705, 13,  # human
+            32001, 13892, 13, 21558, 32000, 28705, 13,  # gpt
+            32001, 2188, 13, 12684, 17664, 32000, 28705, 13,   # human
+            32001, 13892, 13, 12684, 17664, 32000, 28705, 13,  # gpt
+        ]
+        # fmt: on
+
+    def test_w_train_on_input(self, sharegpt_dataset, tokenizer):
+        strategy = SimpleShareGPTPromptTokenizingStrategy(
+            ShareGPTPrompterV2(
+                conversation="chatml",
+                role_key_model=None,
+                role_key_human=None,
+            ),
+            tokenizer,
+            True,  # train_on_inputs
+            2048,  # sequence_len
+        )
+
+        dataset_wrapper = TokenizedPromptDataset(
+            strategy, sharegpt_dataset, process_count=1
+        )
+
+        labels = dataset_wrapper[0]["labels"]
+        # fmt: off
+        assert labels == [
+            -100,   # bos
+            -100, -100, -100, -100, -100, -100, -100,  # system
+            -100, -100, -100, -100, -100, -100, -100,  # human
+            -100, -100, 13, 21558, 32000, 28705, 13,  # gpt
+            -100, -100, -100, -100, -100, -100, -100, -100,   # human
+            -100, -100, 13, 12684, 17664, 32000, 28705, 13,  # gpt
+        ]
+        # fmt: on
+
+    # def test_no_train_on_input(self, sharegpt_dataset, tokenizer):
+    #     strategy = SimpleShareGPTPromptTokenizingStrategy(
+    #         ShareGPTPrompterV2(
+    #             conversation="chatml",
+    #             role_key_model=None,
+    #             role_key_human=None,
+    #         ),
+    #         tokenizer,
+    #         False,  # train_on_inputs
+    #         2048,  # sequence_len
+    #     )
+    #
+    #     dataset_wrapper = TokenizedPromptDataset(
+    #         strategy, sharegpt_dataset, process_count=1
+    #     )
+    #
+    #     labels = dataset_wrapper[0]["labels"]
+    #     # fmt: off
+    #     assert labels == [
+    #         1,   # bos
+    #         32001, 1587, 13, 25997, 32000, 28705, 13,  # system
+    #         32001, 2188, 13, 21558, 32000, 28705, 13,  # human
+    #         32001, 13892, 13, 21558, 32000, 28705, 13,  # gpt
+    #         32001, 2188, 13, 12684, 17664, 32000, 28705, 13,   # human
+    #         32001, 13892, 13, 12684, 17664, 32000, 28705, 13,  # gpt
+    #     ]
+    #     # fmt: on