Add debug option for RL dataset preprocessing (#1404)

* adding debug option for RL dataset preprocessing

* Refine formatting of debugging code in RL dataset preprocessing

* Update __init__.py

* chore: fix lint

---------

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
This commit is contained in:
Abhinand
2024-04-30 21:06:04 +05:30
committed by GitHub
parent 1aeece6e24
commit cc5d31e0d9
2 changed files with 75 additions and 3 deletions

View File

@@ -433,6 +433,23 @@ def load_rl_datasets(
math.ceil(len(train_dataset) * cfg.num_epochs / cfg.batch_size)
)
if cli_args.debug or cfg.debug:
LOG.info("check_dataset_labels...")
tokenizer = load_tokenizer(cfg)
check_dataset_labels(
train_dataset.select(
[
random.randrange(0, len(train_dataset) - 1) # nosec
for _ in range(cli_args.debug_num_examples)
]
),
tokenizer,
num_examples=cli_args.debug_num_examples,
text_only=cli_args.debug_text_only,
rl_mode=True,
)
return TrainDatasetMeta(
train_dataset=train_dataset,
eval_dataset=eval_dataset,

View File

@@ -1,6 +1,5 @@
"""Module for tokenization utilities"""
import logging
import re
from typing import Dict, List
@@ -10,10 +9,19 @@ from termcolor import colored
LOG = logging.getLogger("axolotl")
def check_dataset_labels(dataset, tokenizer, num_examples=5, text_only=False):
def check_dataset_labels(
dataset,
tokenizer,
num_examples=5,
text_only=False,
rl_mode=False,
):
# the dataset is already shuffled, so let's just check the first 5 elements
for idx in range(num_examples):
check_example_labels(dataset[idx], tokenizer, text_only=text_only)
if not rl_mode:
check_example_labels(dataset[idx], tokenizer, text_only=text_only)
else:
check_rl_example_labels(dataset[idx], tokenizer, text_only=text_only)
def check_example_labels(example, tokenizer, text_only=False):
@@ -40,6 +48,53 @@ def check_example_labels(example, tokenizer, text_only=False):
return " ".join(colored_tokens)
def color_token_for_rl_debug(decoded_token, encoded_token, color, text_only):
"""Helper function to color tokens based on their type."""
colored_text = colored(decoded_token, color)
return (
colored_text
if text_only
else f"{colored_text}{colored(f'({encoded_token})', 'white')}"
)
def process_tokens_for_rl_debug(tokens, color, tokenizer, text_only):
"""Helper function to process and color tokens."""
colored_tokens = [
color_token_for_rl_debug(tokenizer.decode(token), token, color, text_only)
for token in tokenizer.encode(tokens)
]
return colored_tokens
def check_rl_example_labels(example, tokenizer, text_only=False):
field_prompt, field_chosen, field_rejected = "prompt", "chosen", "rejected"
input_tokens = example[field_prompt]
labels_chosen, labels_rejected = example[field_chosen], example[field_rejected]
# Process and color each type of token
colored_tokens = process_tokens_for_rl_debug(
input_tokens, "yellow", tokenizer, text_only
)
colored_chosens = process_tokens_for_rl_debug(
labels_chosen, "green", tokenizer, text_only
)
colored_rejecteds = process_tokens_for_rl_debug(
labels_rejected, "red", tokenizer, text_only
)
# Create a delimiter based on text_only flag
delimiter = "" if text_only else " "
# Logging information
LOG.info(f"INPUT PROMPT: {delimiter.join(colored_tokens)}\n\n")
LOG.info(f"CHOSEN RESPONSE: {delimiter.join(colored_chosens)}\n\n")
LOG.info(f"REJECTED RESPONSE: {delimiter.join(colored_rejecteds)}\n\n\n")
return delimiter.join(colored_tokens)
GLAIVE_ROLES = ["USER", "ASSISTANT", "FUNCTION RESPONSE"]
GLAIVE_TO_SHAREGPT_ROLE = {
"SYSTEM": "system",