use fastchat conversations template (#578)

* use fastchat conversations template

* require fastchat (fschat) pip install

* handle roles dynamically from conversation

* tweak fastchat conversation with a monkeypatch to get individual turns

* fix up so it works with multiple conversation styles, and don't strip the turns

* fix sharegpt fixture now that we're using a more correct tokenization

* use a new prompter and support fastchat conversation type

* use sharegpt from prompt strategies now

* update docs, add chatml template

* add a newline after im_end token

* ensure we correctly set system message

* update per PR feedback to handle deprecated sharegpt types

* don't add duplicate wandb req

* make sharegpt fields configurable from yml

* llama2 fixes

* don't fail fatally when turns are improper

README.md

@@ -180,7 +180,7 @@ Have dataset(s) in one of the following format (JSONL recommended):
   ```json
   {"instruction": "...", "input": "...", "output": "..."}
   ```
-- `sharegpt:chat`: conversations where `from` is `human`/`gpt`
+- `sharegpt`: conversations where `from` is `human`/`gpt`
   ```json
   {"conversations": [{"from": "...", "value": "..."}]}
   ```
@@ -269,11 +269,11 @@ Have dataset(s) in one of the following format (JSONL recommended):
   ```json
   {"prompt": "...", "generation": "..."}
   ```
-- `sharegpt_simple.load_role`: conversations where `role` is used instead of `from`
+- `sharegpt.load_role`: conversations where `role` is used instead of `from`
   ```json
   {"conversations": [{"role": "...", "value": "..."}]}
   ```
-- `sharegpt_simple.load_guanaco`: conversations where `from` is `prompter`/`assistant` instead of default sharegpt
+- `sharegpt.load_guanaco`: conversations where `from` is `prompter`/`assistant` instead of default sharegpt
   ```json
   {"conversations": [{"from": "...", "value": "..."}]}
   ```
@@ -443,6 +443,7 @@ datasets:
     data_files: # Optional[str] path to source data files
     shards: # Optional[int] number of shards to split data into
     name: # Optional[str] name of dataset configuration to load
+    conversation:  # Optional[str] fastchat conversation type, only used with type: sharegpt
 
   # custom user prompt
   - path: repo

requirements.txt

@@ -31,3 +31,4 @@ scipy
 scikit-learn==1.2.2
 pynvml
 art
+fschat==0.2.29

src/axolotl/monkeypatch/fastchat_conversation_turns.py

@@ -0,0 +1,174 @@
+"""
+monkeypatch to add a get_turns method
+"""
+
+import logging
+from typing import Generator, Tuple
+
+from fastchat.conversation import SeparatorStyle
+
+LOG = logging.getLogger("axolotl.monkeypatch.fastchat_conversation_turns")
+
+
+def get_prompt(self) -> str:
+    ret = ""
+    for role, msg in self.get_turns():
+        ret += role + msg
+    return ret
+
+
+def get_turns(  # pylint: disable=too-many-return-statements
+    self,
+) -> Generator[Tuple[str, str], None, None]:
+    """Get the prompt for generation."""
+    system_prompt = self.system_template.format(system_message=self.system_message)
+    if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE:
+        yield "", system_prompt + self.sep
+        for role, message in self.messages:
+            if message:
+                yield role + ": ", message + self.sep
+            else:
+                yield role + ":", ""
+        return
+    if self.sep_style == SeparatorStyle.ADD_COLON_TWO:
+        seps = [self.sep, self.sep2]
+        yield "", system_prompt + seps[0]
+        for i, (role, message) in enumerate(self.messages):
+            if message:
+                yield role + ": ", message + seps[i % 2]
+            else:
+                yield role + ":", ""
+        return
+    if self.sep_style == SeparatorStyle.ADD_COLON_SPACE_SINGLE:
+        yield "", system_prompt + self.sep
+        for role, message in self.messages:
+            if message:
+                yield role + ": ", message + self.sep
+            else:
+                yield role + ": ", ""  # must be end with a space
+        return
+    if self.sep_style == SeparatorStyle.ADD_NEW_LINE_SINGLE:
+        yield "", "" if system_prompt == "" else system_prompt + self.sep
+        for role, message in self.messages:
+            if message:
+                yield role + "\n", message + self.sep
+            else:
+                yield role + "\n", ""
+        return
+    if self.sep_style == SeparatorStyle.NO_COLON_SINGLE:
+        yield "", system_prompt
+        for role, message in self.messages:
+            if message:
+                yield role, message + self.sep
+            else:
+                yield role, ""
+        return
+    if self.sep_style == SeparatorStyle.NO_COLON_TWO:
+        seps = [self.sep, self.sep2]
+        yield "", system_prompt
+        for i, (role, message) in enumerate(self.messages):
+            if message:
+                yield role, message + seps[i % 2]
+            else:
+                yield role, ""
+        return
+    if self.sep_style == SeparatorStyle.RWKV:
+        yield "", system_prompt
+        for i, (role, message) in enumerate(self.messages):
+            if message:
+                yield role + ": ", message.replace("\r\n", "\n").replace(
+                    "\n\n", "\n"
+                ) + "\n\n"
+            else:
+                yield role + ":", ""
+        return
+    if self.sep_style == SeparatorStyle.LLAMA2:
+        seps = [self.sep, self.sep2]
+        if self.system_message:
+            yield "", system_prompt
+        else:
+            yield "", "[INST] "
+        for i, (role, message) in enumerate(self.messages[1:]):
+            if message:
+                yield role + " ", message + seps[i % 2]
+            else:
+                yield role, ""
+        return
+    if self.sep_style == SeparatorStyle.CHATGLM:
+        # source: https://huggingface.co/THUDM/chatglm-6b/blob/1d240ba371910e9282298d4592532d7f0f3e9f3e/modeling_chatglm.py#L1302-L1308
+        # source2: https://huggingface.co/THUDM/chatglm2-6b/blob/e186c891cf64310ac66ef10a87e6635fa6c2a579/modeling_chatglm.py#L926
+        round_add_n = 1 if self.name == "chatglm2" else 0
+        if system_prompt:
+            yield "", system_prompt + self.sep
+
+        for i, (role, message) in enumerate(self.messages):
+            if i % 2 == 0:
+                yield "", f"[Round {i//2 + round_add_n}]{self.sep}"
+
+            if message:
+                yield f"{role}：", f"{message}{self.sep}"
+            else:
+                yield f"{role}：", ""
+        return
+    if self.sep_style == SeparatorStyle.CHATML:
+        yield "", "" if system_prompt == "" else system_prompt + self.sep + "\n"
+        for role, message in self.messages:
+            if message:
+                yield role + "\n", message + self.sep + "\n"
+            else:
+                yield role + "\n", ""
+        return
+    if self.sep_style == SeparatorStyle.CHATINTERN:
+        # source: https://huggingface.co/internlm/internlm-chat-7b-8k/blob/bd546fa984b4b0b86958f56bf37f94aa75ab8831/modeling_internlm.py#L771
+        seps = [self.sep, self.sep2]
+        yield "", system_prompt
+        for i, (role, message) in enumerate(self.messages):
+            prefix = "<s>" if i % 2 == 0 else ""
+            if message:
+                yield prefix + role + ":", message + seps[i % 2] + "\n"
+            else:
+                yield role + ":", ""
+        return
+    if self.sep_style == SeparatorStyle.DOLLY:
+        seps = [self.sep, self.sep2]
+        yield "", system_prompt
+        for i, (role, message) in enumerate(self.messages):
+            if message:
+                suffix = "\n\n" if i % 2 == 1 else ""
+                yield role + ":\n", message + seps[i % 2] + suffix
+            else:
+                yield role + ":\n", ""
+        return
+    if self.sep_style == SeparatorStyle.PHOENIX:
+        yield "", system_prompt
+        for role, message in self.messages:
+            if message:
+                yield role + ": ", "<s>" + message + "</s>"
+            else:
+                yield role + ": " + "<s>", ""
+        return
+    if self.sep_style == SeparatorStyle.ROBIN:
+        yield "", system_prompt + self.sep
+        for role, message in self.messages:
+            if message:
+                yield role + ":\n", message + self.sep
+            else:
+                yield role + ":\n", ""
+        return
+    if self.sep_style == SeparatorStyle.FALCON_CHAT:
+        if self.system_message:
+            yield "", system_prompt + self.sep
+        for role, message in self.messages:
+            if message:
+                yield role + ": ", message + self.sep
+            else:
+                yield role + ":", ""
+    else:
+        raise ValueError(f"Invalid style: {self.sep_style}")
+
+
+def add_get_turns_to_conversation():
+    import fastchat.conversation
+
+    fastchat.conversation.Conversation.get_turns = get_turns
+    fastchat.conversation.Conversation.get_prompt = get_prompt

src/axolotl/prompt_strategies/sharegpt.py

@@ -1,12 +1,35 @@
 """Module containing the SimpleShareGPTPromptTokenizingStrategy class"""
+from typing import Any, Dict, Optional
+
+from fastchat.conversation import Conversation, SeparatorStyle, register_conv_template
 
 from axolotl.prompt_tokenizers import ShareGPTPromptTokenizingStrategy
-from axolotl.prompters import PromptStyle, ShareGPTPrompter
+from axolotl.prompters import ShareGPTPrompterV2
+
+register_conv_template(
+    Conversation(
+        name="chatml",
+        system_template="<|im_start|>system\n{system_message}",
+        system_message="You are a helpful assistant.",
+        roles=["<|im_start|>user", "<|im_start|>assistant"],
+        sep_style=SeparatorStyle.CHATML,
+        sep="<|im_end|>\n",
+    )
+)
 
 
-def load(tokenizer, cfg):
+def load(tokenizer, cfg, ds_cfg: Optional[Dict[str, Any]] = None):
+    conversation = (
+        ds_cfg["conversation"] if ds_cfg and "conversation" in ds_cfg else None
+    )
+    field_human = ds_cfg["field_human"] if ds_cfg and "field_human" in ds_cfg else None
+    field_model = ds_cfg["field_model"] if ds_cfg and "field_model" in ds_cfg else None
     return SimpleShareGPTPromptTokenizingStrategy(
-        ShareGPTPrompter(PromptStyle.CHAT.value),
+        ShareGPTPrompterV2(
+            conversation=conversation,
+            role_key_model=field_model,
+            role_key_human=field_human,
+        ),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,
@@ -15,7 +38,7 @@ def load(tokenizer, cfg):
 
 def load_role(tokenizer, cfg):
     return SimpleRoleShareGPTPromptTokenizingStrategy(
-        ShareGPTPrompter(PromptStyle.CHAT.value),
+        ShareGPTPrompterV2(),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,
@@ -24,7 +47,7 @@ def load_role(tokenizer, cfg):
 
 def load_guanaco(tokenizer, cfg):
     return GuanacoShareGPTPromptTokenizingStrategy(
-        ShareGPTPrompter(PromptStyle.CHAT.value),
+        ShareGPTPrompterV2(),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,

src/axolotl/prompt_strategies/sharegpt_jokes.py

@@ -1,11 +1,11 @@
 """Module for Jokes prompts using sharegpt style """
 from axolotl.prompt_tokenizers import ShareGPTPromptTokenizingStrategy
-from axolotl.prompters import PromptStyle, ShareGPTPrompter
+from axolotl.prompters import ShareGPTPrompterV2
 
 
 def load(tokenizer, cfg):
     return SimpleJokesShareGPTPromptTokenizingStrategy(
-        ShareGPTPrompter(PromptStyle.CHAT.value),
+        ShareGPTPrompterV2(),
         tokenizer,
         cfg.train_on_inputs,
         cfg.sequence_len,

src/axolotl/prompt_tokenizers.py

@@ -6,8 +6,12 @@ import functools
 import logging
 from typing import Dict, List, Tuple, Union
 
+from fastchat.conversation import Conversation
 from transformers import BatchEncoding, PreTrainedTokenizer
 
+from axolotl.monkeypatch.fastchat_conversation_turns import (
+    add_get_turns_to_conversation,
+)
 from axolotl.prompters import IGNORE_TOKEN_ID
 
 LOG = logging.getLogger("axolotl")
@@ -18,6 +22,8 @@ LLAMA_DEFAULT_EOS_TOKEN = "</s>"  # nosec
 LLAMA_DEFAULT_BOS_TOKEN = "<s>"  # nosec
 LLAMA_DEFAULT_UNK_TOKEN = "<unk>"  # nosec
 
+add_get_turns_to_conversation()
+
 
 class InvalidDataException(Exception):
     """
@@ -352,18 +358,21 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
         result, current_len = tokenize_prompt_default()
         user_token = self._get_user_token()
         assistant_token = self._get_assistant_token()
+        conversation: Conversation = (
+            self.prompter._conversation  # pylint: disable=protected-access
+        )
         try:
             for _, part in enumerate(
                 self.prompter.build_prompt(self.get_conversation_thread(prompt))
             ):
                 if isinstance(part, tuple):
-                    if part[0] == "USER:":
+                    if conversation.roles[0] in part[0]:
                         turn = part[0] + part[1] if not user_token else part[1]
                         # this is still the user query, we should
                         if not part[1].strip():
                             LOG.warning(f"user turn has empty text: {prompt}")
                         res = self._tokenize(
-                            turn.strip(),
+                            turn,
                             add_eos_token=False,
                             strip_bos_token=True,
                         )
@@ -371,14 +380,14 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
                             res["input_ids"] = [user_token, *res["input_ids"]]
                         # everything from this is masked out from the labels
                         labels = [IGNORE_TOKEN_ID] * len(res["input_ids"])
-                    elif part[0] == "ASSISTANT:":
+                    elif conversation.roles[1] in part[0]:
                         # TODO label assistant token/tokens w/ IGNORE_TOKEN_ID
                         turn = part[0] + part[1] if not assistant_token else part[1]
                         # this should be the assistant response, should end with an eos token
                         if not part[1].strip():
                             LOG.warning(f"assistant turn has empty text: {prompt}")
                         res = self._tokenize(
-                            turn.strip(),
+                            turn,
                             add_eos_token=True,
                             strip_bos_token=True,
                         )
@@ -389,16 +398,17 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
                             ]
                         # not masked out from labels
                         labels = copy.deepcopy(res["input_ids"])
-                    elif part[0] == "SYSTEM:":
+                    elif part[0] == "":
-                        part = part[1]  # Ignore the system role from preamble
+                        turn = part[1]
                         # this is only ever the first part, should include the bos token and the user query
                         res = self._tokenize(
-                            part.strip(), add_eos_token=False, strip_bos_token=False
+                            turn, add_eos_token=False, strip_bos_token=False
                         )
                         # everything from this is masked out from the labels
                         labels = [IGNORE_TOKEN_ID] * len(res["input_ids"])
                     else:
                         LOG.warning(f"unhandled role: {part[0]}")
+                        continue
 
                 # pylint: disable=duplicate-code
                 result, current_len = parse_tokenized_to_result(

src/axolotl/prompters.py

@@ -1,9 +1,10 @@
 """Module containing prompters"""
 
-import dataclasses
 import logging
-from enum import Enum, auto
+from enum import Enum
-from typing import Generator, List, Optional, Tuple, Union
+from typing import Generator, Optional, Union
+
+from fastchat.conversation import Conversation, get_conv_template
 
 LOG = logging.getLogger("axolotl")
 IGNORE_TOKEN_ID = -100
@@ -214,53 +215,6 @@ class ReflectAlpacaPrompter:
         yield res
 
 
-class SeparatorStyle(Enum):
-    """Different separator style."""
-
-    SINGLE = auto()
-    TWO = auto()
-    DOLLY = auto()
-
-
-# TODO clean this 💩 up
-@dataclasses.dataclass
-class Conversation:
-    """A class that keeps all conversation history."""
-
-    system: str
-    roles: List[str]
-    messages: List[List[str]]
-    offset: int
-    sep_style: SeparatorStyle = SeparatorStyle.SINGLE
-    sep: str = "###"
-    sep2: Optional[str] = None
-
-    def get_prompt(self) -> Generator[Tuple[str, str], None, None]:
-        # seps = [self.sep, self.sep2]
-        preamble = self.system + self.sep
-        yield ("SYSTEM:", preamble)
-        for _, (role, message) in enumerate(self.messages):
-            if message:
-                yield (role + ":", " " + message)
-            else:
-                LOG.warning(f"role with empty message: {role}")
-                yield (role + ":", "")
-
-    def copy(self):
-        return Conversation(
-            system=self.system,
-            roles=self.roles,
-            messages=[[x, y] for x, y in self.messages],
-            offset=self.offset,
-            sep_style=self.sep_style,
-            sep=self.sep,
-            sep2=self.sep2,
-        )
-
-    def append_message(self, role, message):
-        self.messages.append([role, message])
-
-
 SHAREGPT_ASSERTION_FAILED_ROLE = (
     "Role did not alternate between turns (gpt and human). Please check your data."
 )
@@ -271,28 +225,27 @@ class ShareGPTPrompter:  # pylint: disable=too-few-public-methods
     A prompter that generates prompts for the ShareGPT
     """
 
-    def __init__(self, prompt_style=None, system_prompt: Optional[str] = None):
+    role_key_human = "human"
-        if prompt_style != PromptStyle.CHAT.value:
+    role_key_model = "gpt"
-            raise ValueError(
+
-                f"unsupported prompt_style for ShareGPTPrompter({prompt_style})"
+    def __init__(
-            )
+        self,
-        system: str = (
+        prompt_style=None,  # pylint: disable=unused-argument
-            system_prompt
+        conversation: Optional[Union[str, Conversation]] = None,
-            if system_prompt
+        role_key_human: Optional[str] = None,
-            else (
+        role_key_model: Optional[str] = None,
-                "A chat between a curious user and an artificial intelligence assistant. "
+    ):
-                "The assistant gives helpful, detailed, and polite answers to the user's questions."
+        if conversation:
-            )
+            if isinstance(conversation, Conversation):
-        )
+                self._conversation = conversation
-        self._conversation = Conversation(
+            else:
-            system=system,
+                self._conversation = get_conv_template(conversation)
-            roles=["USER", "ASSISTANT"],
+        else:
-            messages=[],
+            self._conversation = get_conv_template("vicuna_v1.1")
-            offset=0,
+        if role_key_human:
-            sep_style=SeparatorStyle.TWO,
+            self.role_key_human = role_key_human
-            sep=" ",
+        if role_key_model:
-            sep2=" ",
+            self.role_key_model = role_key_model
-        )
 
     def build_prompt(self, source) -> Generator[str, None, None]:
         if len(source) < 2:
@@ -306,17 +259,14 @@ class ShareGPTPrompter:  # pylint: disable=too-few-public-methods
 
         # Add the conversation system prompt if provided, otherwise use the default one
         if source[0]["from"] == "system":
-            conv.system = source[0]["value"]
+            conv.set_system_message(source[0]["value"])
             source.pop(0)
 
-        roles = {"human": conv.roles[0], "gpt": conv.roles[1]}
+        roles = {self.role_key_human: conv.roles[0], self.role_key_model: conv.roles[1]}
 
         try:
             # Apply prompt templates
-            if (
+            if source[0]["from"] not in roles:
-                source[0]["from"] not in roles
-                or roles[source[0]["from"]] != conv.roles[0]
-            ):
                 # Skip the first one if it is not from human
                 source = source[1:]
         except IndexError as err:
@@ -326,8 +276,29 @@ class ShareGPTPrompter:  # pylint: disable=too-few-public-methods
         conv.messages = []
         for j, sentence in enumerate(source):
             role = roles[sentence["from"]]
-            assert role == conv.roles[j % 2], SHAREGPT_ASSERTION_FAILED_ROLE
+            if role != conv.roles[j % 2]:
+                LOG.warning(f"{SHAREGPT_ASSERTION_FAILED_ROLE}: {sentence}")
             conv.append_message(role, sentence["value"])
 
-        for part in conv.get_prompt():
+        for part in conv.get_turns():
+            if part[0] and not part[1]:
+                LOG.warning(f"role with empty message: {part[0]}")
             yield part
+
+
+class ShareGPTPrompterV2(ShareGPTPrompter):
+    """
+    A V2 prompter that generates prompts for the ShareGPT
+    """
+
+    def __init__(
+        self,
+        conversation: Optional[Union[str, Conversation]] = None,
+        role_key_human: Optional[str] = None,
+        role_key_model: Optional[str] = None,
+    ):
+        super().__init__(
+            conversation=conversation,
+            role_key_human=role_key_human,
+            role_key_model=role_key_model,
+        )

src/axolotl/utils/config.py

@@ -278,6 +278,25 @@ def validate_config(cfg):
                     "`model_type: MixFormerSequentialForCausalLM` required for sample_packing"
                 )
 
+    if cfg.datasets:
+        for idx, ds_cfg in enumerate(cfg.datasets):
+            if ds_cfg.type == "sharegpt:chat":
+                LOG.warning(
+                    PendingDeprecationWarning(
+                        "`type: sharegpt:chat` will soon be deprecated. simply use `type: sharegpt` instead."
+                    )
+                )
+                cfg.datasets[idx].type = "sharegpt"
+            if "sharegpt_simple" in ds_cfg.type:
+                LOG.warning(
+                    PendingDeprecationWarning(
+                        "`type: sharegpt_simple` will soon be deprecated. simply use `type: sharegpt` instead."
+                    )
+                )
+                cfg.datasets[idx].type = cfg.datasets[idx].type.replace(
+                    "sharegpt_simple", "sharegpt"
+                )
+
     # TODO
     # MPT 7b
     # https://github.com/facebookresearch/bitsandbytes/issues/25

src/axolotl/utils/data.py

@@ -25,7 +25,6 @@ from axolotl.prompt_tokenizers import (
     GPTeacherPromptTokenizingStrategy,
     JeopardyPromptTokenizingStrategy,
     OpenAssistantPromptTokenizingStrategy,
-    ShareGPTPromptTokenizingStrategy,
     SummarizeTLDRPromptTokenizingStrategy,
 )
 from axolotl.prompters import (
@@ -35,7 +34,6 @@ from axolotl.prompters import (
     MultipleChoiceConcisePrompter,
     MultipleChoiceExplainPrompter,
     ReflectAlpacaPrompter,
-    ShareGPTPrompter,
     SummarizeTLDRPrompter,
 )
 from axolotl.utils.dict import DictDefault
@@ -320,15 +318,6 @@ def load_tokenized_prepared_datasets(
                 )
                 ds_wrapper = TokenizedPromptDataset(ds_strategy, ds)
                 datasets.append(ds_wrapper)
-            elif d_base_type == "sharegpt":
-                ds_strategy = ShareGPTPromptTokenizingStrategy(
-                    ShareGPTPrompter(d_prompt_style),
-                    tokenizer,
-                    cfg.train_on_inputs,
-                    cfg.sequence_len,
-                )
-                ds_wrapper = TokenizedPromptDataset(ds_strategy, ds)
-                datasets.append(ds_wrapper)
             else:
                 suffix = ""
                 if ":load_" in d.type:

src/axolotl/utils/tokenization.py

@@ -33,5 +33,6 @@ def check_example_labels(example, tokenizer, text_only=False):
 
     LOG.info(" ".join(colored_tokens))
     LOG.info("\n\n\n")
+    print(" ".join(colored_tokens))
 
     return " ".join(colored_tokens)

tests/test_prompt_tokenizers.py

@@ -21,7 +21,7 @@ from axolotl.prompt_tokenizers import (
     AlpacaPromptTokenizingStrategy,
     ShareGPTPromptTokenizingStrategy,
 )
-from axolotl.prompters import AlpacaPrompter, PromptStyle, ShareGPTPrompter
+from axolotl.prompters import AlpacaPrompter, PromptStyle, ShareGPTPrompterV2
 
 LOG = logging.getLogger("axolotl")
 
@@ -60,7 +60,7 @@ class TestPromptTokenizationStrategies(unittest.TestCase):
         ) as fin:
             data = fin.read()
             tokenized_conversation = json.loads(data)
-        prompter = ShareGPTPrompter("chat")
+        prompter = ShareGPTPrompterV2()
         strat = ShareGPTPromptTokenizingStrategy(
             prompter,
             self.tokenizer,
@@ -79,7 +79,7 @@ class TestPromptTokenizationStrategies(unittest.TestCase):
         ) as fin:
             data = fin.read()
             conversation = json.loads(data)
-        prompter = ShareGPTPrompter("chat")
+        prompter = ShareGPTPrompterV2()
         strat = ShareGPTPromptTokenizingStrategy(
             prompter,
             self.tokenizer,

tests/test_validation.py

@@ -374,3 +374,26 @@ class ValidationTest(unittest.TestCase):
         )
 
         validate_config(cfg)
+
+    def test_sharegpt_deprecation(self):
+        cfg = DictDefault(
+            {"datasets": [{"path": "lorem/ipsum", "type": "sharegpt:chat"}]}
+        )
+        with self._caplog.at_level(logging.WARNING):
+            validate_config(cfg)
+            assert any(
+                "`type: sharegpt:chat` will soon be deprecated." in record.message
+                for record in self._caplog.records
+            )
+        assert cfg.datasets[0].type == "sharegpt"
+
+        cfg = DictDefault(
+            {"datasets": [{"path": "lorem/ipsum", "type": "sharegpt_simple:load_role"}]}
+        )
+        with self._caplog.at_level(logging.WARNING):
+            validate_config(cfg)
+            assert any(
+                "`type: sharegpt_simple` will soon be deprecated." in record.message
+                for record in self._caplog.records
+            )
+        assert cfg.datasets[0].type == "sharegpt:load_role"