Refactor duplicate code between Prompter and Pygmalion

src/axolotl/prompt_strategies/pygmalion.py

@@ -5,7 +5,11 @@ import logging
 from collections import defaultdict
 from typing import Generator
 
-from axolotl.prompt_tokenizers import PromptTokenizingStrategy
+from axolotl.prompt_tokenizers import (
+    PromptTokenizingStrategy,
+    parse_tokenized_to_result,
+    tokenize_prompt_default,
+)
 
 IGNORE_TOKEN_ID = -100
 
@@ -23,12 +27,7 @@ class PygmalionPromptTokenizingStrategy(PromptTokenizingStrategy):
         self.bot_prefix_token_ids = res["input_ids"]
 
     def tokenize_prompt(self, prompt):
-        result = {
+        result, current_len = tokenize_prompt_default()
-            "input_ids": [],
-            "attention_mask": [],
-            "labels": [],
-        }
-        current_len = 0
         for _, part in enumerate(self.prompter.build_prompt(prompt["conversations"])):
             role, message = part
             if role == "system":
@@ -67,37 +66,15 @@ class PygmalionPromptTokenizingStrategy(PromptTokenizingStrategy):
             else:
                 logging.warning(f"unknown role in conversation: {role}")
                 res = defaultdict(lambda: [])
-            input_ids = res["input_ids"]
-            input_len = len(input_ids)
-            result["input_ids"][current_len : current_len + input_len] = input_ids
-            result["attention_mask"][current_len : current_len + input_len] = [
-                1 if x != self.tokenizer.pad_token_id else 0 for x in input_ids
-            ]
-            result["labels"][current_len : current_len + input_len] = labels
-            current_len += input_len
-        return result
 
-    def _tokenize(self, prompt, add_eos_token=True, strip_bos_token=False):
+            # pylint: disable=duplicate-code
-        result = self.tokenizer(
+            result, current_len = parse_tokenized_to_result(
-            prompt,
+                result,
-            truncation=True,
+                current_len,
-            max_length=self.sequence_len,
+                res,
-            padding=False,
+                labels,
-            return_tensors=None,
+                pad_token_id=self.tokenizer.pad_token_id,
-        )
+            )
-        if (
-            result["input_ids"][-1] != self.tokenizer.eos_token_id
-            and len(result["input_ids"]) < self.sequence_len
-            and add_eos_token
-        ):
-            result["input_ids"].append(self.tokenizer.eos_token_id)
-            result["attention_mask"].append(1)
-
-        if result["input_ids"][0] == self.tokenizer.bos_token_id and strip_bos_token:
-            result["input_ids"] = result["input_ids"][1:]
-            result["attention_mask"] = result["attention_mask"][1:]
-
-        result["labels"] = result["input_ids"].copy()
         return result
 
 

src/axolotl/prompt_tokenizers.py

@@ -4,7 +4,7 @@ import abc
 import copy
 import functools
 import logging
-from typing import Tuple
+from typing import Dict, List, Tuple
 
 from transformers import PreTrainedTokenizer
 
@@ -58,6 +58,29 @@ class PromptTokenizingStrategy(abc.ABC):
             return id_or_ids
         return False
 
+    def _tokenize(self, prompt: str, add_eos_token=True, strip_bos_token=False):
+        result = self.tokenizer(
+            prompt,
+            truncation=True,
+            max_length=self.sequence_len,
+            padding=False,
+            return_tensors=None,
+        )
+        if (
+            result["input_ids"][-1] != self.tokenizer.eos_token_id
+            and len(result["input_ids"]) < self.sequence_len
+            and add_eos_token
+        ):
+            result["input_ids"].append(self.tokenizer.eos_token_id)
+            result["attention_mask"].append(1)
+
+        if result["input_ids"][0] == self.tokenizer.bos_token_id and strip_bos_token:
+            result["input_ids"] = result["input_ids"][1:]
+            result["attention_mask"] = result["attention_mask"][1:]
+
+        result["labels"] = result["input_ids"].copy()
+        return result
+
 
 class InstructionPromptTokenizingStrategy(PromptTokenizingStrategy):
     """
@@ -106,29 +129,6 @@ class InstructionPromptTokenizingStrategy(PromptTokenizingStrategy):
             )
         )
 
-    def _tokenize(self, prompt, add_eos_token=True, strip_bos_token=False):
-        result = self.tokenizer(
-            prompt,
-            truncation=True,
-            max_length=self.sequence_len,
-            padding=False,
-            return_tensors=None,
-        )
-        if (
-            result["input_ids"][-1] != self.tokenizer.eos_token_id
-            and len(result["input_ids"]) < self.sequence_len
-            and add_eos_token
-        ):
-            result["input_ids"].append(self.tokenizer.eos_token_id)
-            result["attention_mask"].append(1)
-
-        if result["input_ids"][0] == self.tokenizer.bos_token_id and strip_bos_token:
-            result["input_ids"] = result["input_ids"][1:]
-            result["attention_mask"] = result["attention_mask"][1:]
-
-        result["labels"] = result["input_ids"].copy()
-        return result
-
 
 class AlpacaPromptTokenizingStrategy(InstructionPromptTokenizingStrategy):
     """
@@ -295,7 +295,7 @@ class ReflectionPromptTokenizingStrategy(PromptTokenizingStrategy):
             )
         )
 
-    def _tokenize(self, prompt, add_eos_token=True):
+    def _tokenize(self, prompt, add_eos_token=True, strip_bos_token=False):
         result = self.tokenizer(
             prompt,
             truncation=True,
@@ -339,12 +339,7 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
         return prompt["conversations"]
 
     def tokenize_prompt(self, prompt):
-        result = {
+        result, current_len = tokenize_prompt_default()
-            "input_ids": [],
-            "attention_mask": [],
-            "labels": [],
-        }
-        current_len = 0
         user_token = self._get_user_token()
         assistant_token = self._get_assistant_token()
         try:
@@ -382,14 +377,15 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
                     )
                     # everything from this is masked out from the labels
                     labels = [IGNORE_TOKEN_ID] * len(res["input_ids"])
-                input_ids = res["input_ids"]
+
-                input_len = len(input_ids)
+                # pylint: disable=duplicate-code
-                result["input_ids"][current_len : current_len + input_len] = input_ids
+                result, current_len = parse_tokenized_to_result(
-                result["attention_mask"][current_len : current_len + input_len] = [
+                    result,
-                    1 if x != self.tokenizer.pad_token_id else 0 for x in input_ids
+                    current_len,
-                ]
+                    res,
-                result["labels"][current_len : current_len + input_len] = labels
+                    labels,
-                current_len += input_len
+                    pad_token_id=self.tokenizer.pad_token_id,
+                )
             return result
         except (KeyError, AssertionError, IndexError) as err:
             raise InvalidDataException(str(err)) from err
@@ -416,3 +412,40 @@ class ShareGPTPromptTokenizingStrategy(PromptTokenizingStrategy):
 
         result["labels"] = result["input_ids"].copy()
         return result
+
+
+def tokenize_prompt_default() -> Tuple[Dict[str, List[int]], int]:
+    """
+    Returns the default values for the tokenize prompt function
+    """
+
+    result = {
+        "input_ids": [],
+        "attention_mask": [],
+        "labels": [],
+    }
+    current_len = 0
+    return result, current_len
+
+
+def parse_tokenized_to_result(
+    result: Dict[str, List[int]],
+    current_len: int,
+    res: Dict[str, List[int]],
+    labels: list[int],
+    pad_token_id: int | None = None,
+) -> Tuple[Dict[str, List[int]], int]:
+    """
+    Parses the tokenized prompt and append the tokenized input_ids, attention_mask and labels to the result
+    """
+
+    input_ids = res["input_ids"]
+    input_len = len(input_ids)
+    result["input_ids"][current_len : current_len + input_len] = input_ids
+    result["attention_mask"][current_len : current_len + input_len] = [
+        1 if x != pad_token_id else 0 for x in input_ids
+    ]
+    result["labels"][current_len : current_len + input_len] = labels
+    current_len += input_len
+
+    return result, current_len