Files
axolotl/tests/test_validation_dataset.py
NanoCode012 bfc77b0f36 Feat: Add support for tokenizer’s or custom jinja chat_template (#1970)
* Allow using tokenizer's default chat template with fallbacks

Summary of changes:

1. Adds `tokenizer_default` as option for `chat_template` in
   `chat_template` prompt strategy that allows using the chat template
   from tokenizer's config.json
2. Allows falling back to chat templates available in axolotl if
   tokenizer does not have a chat template
3. Adds a mistral chat template which supports system message - taken
   from https://github.com/chujiezheng/chat_templates/blob/main/chat_templates/mistral-instruct.jinja

---

Why?

Many popular models are not trained with chatml format. As a result for
the model to correctly learn chatml we have to turn on train_on_inputs
which requires more compute and time. If we can use the model's already
learned chat template we can just learn the output tokens

---

Todo:

- Write tests

* Add tests

* Fix lint and bug post merge from main

* Add option `chat_template_jinja` to provide a jinja template

* remove custom mistral template

* Address review comments and add docs

* Update docs/dataset-formats/conversation.qmd

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>

* fix: set default to tokenizer template

* Merge branch 'main' into cj_tokenizer_default_prompt_template

* chore: remove redundant function

* fix: re-arrange enum declaration position

* fix: refactor artifact left from main merge

* feat(doc): updated config with chat template options and clarified examples

* chore: clarify doc

* chore: added example for non-default template

* chore: refactor

* fix: test

* fix: config being dropped and unittest to catch that

* chore: lint

* chore: skip duplicate

* fix: rename var after merge

* feat: add test for levy's dpo case

* fix: remove default setting on edge case where chat template overriden in dataset section

* feat: handle sharegpt deprecation better in docs

* feat: add example using fallback

* feat: handles chat_template requiring specific user/assistant order

* fix: update test based on new defaults

* fix: imported name incorrectly updated on merge

* chore: lint

* fix: update dummy message to prevent potential overlap with real content

* fix(doc): formatting

* fix: update bradleyterry to use new chat_template

---------

Co-authored-by: Chirag Jain <jain.chirag925@gmail.com>
2024-10-29 10:14:51 +07:00

239 lines
7.3 KiB
Python

"""Module for testing the validation module for the dataset config"""
import warnings
from typing import Optional
import pytest
from axolotl.utils.config import validate_config
from axolotl.utils.config.models.input.v0_4_1 import ChatTemplate
from axolotl.utils.dict import DictDefault
warnings.filterwarnings("error")
@pytest.fixture(name="minimal_cfg")
def fixture_cfg():
return DictDefault(
{
"base_model": "TinyLlama/TinyLlama-1.1B-Chat-v0.6",
"learning_rate": 0.000001,
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
}
)
# pylint: disable=too-many-public-methods (duplicate-code)
class BaseValidation:
"""
Base validation module to setup the log capture
"""
_caplog: Optional[pytest.LogCaptureFixture] = None
@pytest.fixture(autouse=True)
def inject_fixtures(self, caplog):
self._caplog = caplog
class TestValidationCheckDatasetConfig(BaseValidation):
"""
Test the validation for the dataset config to ensure no correct parameters are dropped
"""
def test_dataset_config_no_drop_param(self, minimal_cfg):
cfg = DictDefault(
minimal_cfg
| {
"datasets": [
{
"path": "LDJnr/Puffin",
"type": "sharegpt",
"conversation": "chatml",
"shards": 10,
}
]
}
)
checked_cfg = validate_config(cfg)
def _check_config():
assert checked_cfg.datasets[0].path == cfg.datasets[0].path
assert checked_cfg.datasets[0].type == cfg.datasets[0].type
assert checked_cfg.datasets[0].conversation == cfg.datasets[0].conversation
assert checked_cfg.datasets[0].shards == cfg.datasets[0].shards
_check_config()
checked_cfg = validate_config(
cfg,
capabilities={
"bf16": "false",
"n_gpu": 1,
"compute_capability": "8.0",
},
)
_check_config()
def test_dataset_default_chat_template_no_drop_param(self, minimal_cfg):
cfg = DictDefault(
minimal_cfg
| {
"datasets": [
{
"path": "LDJnr/Puffin",
"type": "chat_template",
"field_messages": "conversations",
"shards": 10,
"message_field_role": "from",
"message_field_content": "value",
}
],
}
)
checked_cfg = validate_config(cfg)
def _check_config():
assert checked_cfg.datasets[0].path == cfg.datasets[0].path
assert checked_cfg.datasets[0].type == cfg.datasets[0].type
assert checked_cfg.chat_template is None
assert (
checked_cfg.datasets[0].chat_template == ChatTemplate.tokenizer_default
)
assert (
checked_cfg.datasets[0].field_messages == cfg.datasets[0].field_messages
)
assert checked_cfg.datasets[0].shards == cfg.datasets[0].shards
assert (
checked_cfg.datasets[0].message_field_role
== cfg.datasets[0].message_field_role
)
assert (
checked_cfg.datasets[0].message_field_content
== cfg.datasets[0].message_field_content
)
_check_config()
checked_cfg = validate_config(
cfg,
capabilities={
"bf16": "false",
"n_gpu": 1,
"compute_capability": "8.0",
},
)
_check_config()
def test_dataset_partial_default_chat_template_no_drop_param(self, minimal_cfg):
cfg = DictDefault(
minimal_cfg
| {
"chat_template": "chatml",
"datasets": [
{
"path": "LDJnr/Puffin",
"type": "chat_template",
"field_messages": "conversations",
"shards": 10,
"message_field_role": "from",
"message_field_content": "value",
}
],
}
)
checked_cfg = validate_config(cfg)
def _check_config():
assert checked_cfg.datasets[0].path == cfg.datasets[0].path
assert checked_cfg.datasets[0].type == cfg.datasets[0].type
assert checked_cfg.chat_template == ChatTemplate.chatml
assert (
checked_cfg.datasets[0].chat_template == ChatTemplate.tokenizer_default
)
assert (
checked_cfg.datasets[0].field_messages == cfg.datasets[0].field_messages
)
assert checked_cfg.datasets[0].shards == cfg.datasets[0].shards
assert (
checked_cfg.datasets[0].message_field_role
== cfg.datasets[0].message_field_role
)
assert (
checked_cfg.datasets[0].message_field_content
== cfg.datasets[0].message_field_content
)
_check_config()
checked_cfg = validate_config(
cfg,
capabilities={
"bf16": "false",
"n_gpu": 1,
"compute_capability": "8.0",
},
)
_check_config()
def test_dataset_chatml_chat_template_no_drop_param(self, minimal_cfg):
cfg = DictDefault(
minimal_cfg
| {
"chat_template": "chatml",
"datasets": [
{
"path": "LDJnr/Puffin",
"type": "chat_template",
"chat_template": "gemma",
"field_messages": "conversations",
"shards": 10,
"message_field_role": "from",
"message_field_content": "value",
}
],
}
)
checked_cfg = validate_config(cfg)
def _check_config():
assert checked_cfg.datasets[0].path == cfg.datasets[0].path
assert checked_cfg.datasets[0].type == cfg.datasets[0].type
assert checked_cfg.chat_template == cfg.chat_template
assert (
checked_cfg.datasets[0].chat_template == cfg.datasets[0].chat_template
)
assert (
checked_cfg.datasets[0].field_messages == cfg.datasets[0].field_messages
)
assert checked_cfg.datasets[0].shards == cfg.datasets[0].shards
assert (
checked_cfg.datasets[0].message_field_role
== cfg.datasets[0].message_field_role
)
assert (
checked_cfg.datasets[0].message_field_content
== cfg.datasets[0].message_field_content
)
_check_config()
checked_cfg = validate_config(
cfg,
capabilities={
"bf16": "false",
"n_gpu": 1,
"compute_capability": "8.0",
},
)
_check_config()