Commit Graph

13 Commits

Author SHA1 Message Date
Dan Saunders
10ba1622f7 checkpoint model on first step callback (#2906)
* checkpoint model on first step callback

* remove debug

* add test cases; update existing tests not to save on first step

* move test out of solo

* delete

* default to False

* typo
2025-07-15 15:00:48 -04:00
Dan Saunders
00cda8cc70 Data loader refactor (#2707)
* data loading refactor (wip)

* updates

* progress

* pytest

* pytest fix

* lint

* zero_first -> filelock, more simplifications

* small simplification

* import change

* nit

* lint

* simplify dedup

* couldnt resist

* review comments WIP

* continued wip

* minor changes

* fix; remove contrived test

* further refactor

* set default seed in pydantic config

* lint

* continued simplication

* lint

* renaming and nits

* filelock tests

* fix

* fix

* lint

* remove nullable arg

* remove unnecessary code

* moving dataset save fn to shared module

* remove debug print

* matching var naming

* fn name change

* coderabbit comments

* naming nit

* fix test
2025-06-10 19:53:07 -04:00
Dan Saunders
1d91d905c9 remove deprecated wandb env var (#2751)
* remove deprecated wandb env var

* remove os.environ wandb setting; unused loggers

* remove os.environ wandb setting; unused loggers
2025-06-03 14:04:15 -07:00
salman
65c5481120 Rank 0-only logging (#2608)
Co-authored-by: Wing Lian <wing@axolotl.ai>
2025-05-28 14:57:30 +01:00
Wing Lian
de8a625dd7 make e2e tests a bit faster by reducing test split size (#2522) [skip ci]
* [ci] make e2e tests a bit faster by reducing test split size

* use 10% split of alpaca dataset to speed up dataset loading/tokenization

* reduce gas 4->2 for most e2e tests

* increase val set size for packing
2025-04-12 07:24:43 -07:00
Wing Lian
ae66374156 Optimizer refactor and add Muon support (#2367)
* add muon optimizer

optimizer_cls_and_kwargs is on trainer_kwargs
only add adamw_kwargs if they're non-null
fix mocks
better handling of override and check the optimizer
unwrap optimizer

* fix import
2025-03-06 11:49:19 -05:00
NJordan72
b194e17c28 feat: add config for optional parameters in a chat message (#2260)
* feat: add config for optional parameters in a chat message

* chore: cleanup

* chore: fix nits and add light docs

* docs: update docs/dataset-formats/conversation.qmd

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

* feat: configurable message mappings, jinja template analyzer

* chore: handle bradley terry

* docs: update docs

* refactor: change order of mappings, improve message transform

* refactor: make chat awware of property mappings

* chore: remove .python-version

* chore: revert change

* chore: add dataset validation to tests where appropriate

* chore: add dataset validation to tests where appropriate

* chore: clean up handling of ds_cfg

* chore: recursively serialize config

* make sure to use the return value from validate_config

* DefaultDict pickle/unpickle fix

* fix super call for override

* refactor: message fields

* chore: empty commit

* tests: validate config before using

* chore: add config validation to all e2e tests

* chore: add unneeded logging

* chore: add missed config validation

* chore: pass field_messages to prompter

* test: fix borked test

* chore: remove uninteded file

* chore: add deprecation warning and update chat_datasets script

* chore: lint

* refactor: message fields

* feat: update axolotlinputconfig and test_models

- add configdict import in axolotl/utils/config/models/input/v0_4_1/__init__.py
- remove unnecessary line breaks in sftdataset, dpodataset, ktodataset, stepwisesuperviseddataset classes
- update model_dump method in axolotlinputconfig to exclude none values
- correct typo in test_models.py comment

* feat: simplify dpodataset and ktodataset classes in config models

removed several optional fields from dpodataset and ktodataset classes in axolotl/utils/config/models/input/v0_4_1. this simplifies the configuration subsets for these datasets.

* feat: improve readability and structure in dataset configuration models

this commit enhances the readability and structure of the dataset configuration models in the `axolotl/utils/config/models/input/v0_4_1` module. it removes unused `configdict` import and adds line breaks to separate class definitions for better clarity. additionally, a minor documentation fix is included to ensure a newline at the end of the `stepwise_supervised.qmd` file.

* feat: change log level from info to debug in chattemplatestrategy

* feat(prompt_strategies): refactor chattemplateprompter and chattemplatestrategy

- Make `chat_template` a required parameter in `ChatTemplatePrompter` constructor
- Add default value for `message_property_mappings` in `ChatTemplatePrompter` constructor
- Add `messages_array_name` property to `ChatTemplatePrompter`
- Change `processor` type to Optional in `ChatTemplatePrompter`
- Add TypeError check for `processor` in `ChatTemplatePrompter.build_prompt`
- Remove `_messages` property from `ChatTemplateStrategy`
- Make `prompter` a required parameter and add type hint in `ChatTemplateStrategy` constructor
- Remove `messages` getter and setter from `ChatTemplateStrategy`
- Use `prompter.messages_array_name` in `ChatTemplateStrategy.get_conversation_thread`
- Remove condition to set `messages` field in `load` function

* feat(tests/utils): ignore type check in load_model call in test_models.py

* feat: improve type handling and test structure in chat templates

- Add return type hint for `get_chat_template` function in `chat_templates.py`
- Remove unnecessary assignment of `strategy.messages` in several test cases
- Add `messages_array_name` parameter to various test configurations in `test_chat_templates.py` and `test_chat_templates_advanced.py`
- Remove redundant `strategy.messages` assignment in `test_chat_templates_advanced.py`

* feat(axolotl): enhance chat strategy with datasetconfig support

This commit introduces support for DatasetConfig in the ChatTemplateStrategy. It also refines the strategy loader to handle different types of ds_cfg inputs and improves the clarity of the code by formatting and reordering. The key changes include:

- Importing Union from typing and BaseModel from pydantic.
- Adding DatasetConfig as an optional type for ds_cfg in StrategyLoader.
- Adjusting the handling of ds_cfg in StrategyLoader to account for BaseModel instances.
- Refactoring the prompter_params and strategy_params for better readability.
- Changing the reference from prompt[self.messages] to prompt[self.prompter.messages_array_name] in the is_prompt_batched method.

* feat: update message handling in btchattemplatestrategy

* Replace `self.messages` with direct string references to "chosen_messages" and "rejected_messages"
* Append system, user, and assistant content directly to "chosen_messages" and "rejected_messages"
* Add a new attribute "messages_array_name" to the `load` function parameters
* Remove the conditional attribute assignment for "field_messages" in the `load` function

* feat: add config validation in test_kd.py

- Import `validate_config` from `axolotl.utils.config`
- Validate the configuration in `test_llama_kd` and another function in `TestKnowledgeDistillation` class

* feat: enhance config validation and capabilities handling

* Import `EnvCapabilities` and `GPUCapabilities` from `axolotl.utils.config.models.internals`
* Update `validate_config` function to create `KTODataset` and `SFTDataset` instances using `dict(ds_cfg)`
* Replace `capabilities` and `env_capabilities` with instances of `GPUCapabilities` and `EnvCapabilities` respectively in `AxolotlConfigWCapabilities` model dump

* feat: update config validation in axolotl utils

- Remove import of `EnvCapabilities` and `GPUCapabilities` from `axolotl.utils.config.models.internals`
- Update `validate_config` function to use `capabilities` and `env_capabilities` directly instead of creating new instances of `GPUCapabilities` and `EnvCapabilities`

* feat: refactor strategyloader in chat_template.py

- Extracted the creation of strategy parameters into a separate function, `_get_strategy_params(cfg, dataset_config)`
- Created a new function, `_get_strategy_cls()`, to obtain the strategy class
- Replaced `ChatTemplateStrategy` with `strategy_cls` for strategy instantiation

* trigger CI

* chore: revert dataset config changes for kto/dpo

* subject: refactor: rename 'messages_array_name' to 'field_messages'

Body:
- Renamed 'messages_array_name' to 'field_messages' in 'ChatTemplatePrompter' class and its usages in 'chat_template.py'
- Updated 'load' function in 'bradley_terry/chat_template.py' to reflect the change
- Adjusted 'get_chat_template_msg_variables' and 'get_message_vars' methods in 'jinja_template_analyzer.py' to use the new variable name
- Modified 'StrategyLoader' in 'chat_template.py' to use 'field_messages'
- Updated tests in 'test_chat_templates.py' and 'test_chat_templates_advanced.py' to use 'field_messages' instead of 'messages_array_name'

* feat: refactor prompt strategies and update config models

* Remove redundant 'return None' in `axolotl/prompt_strategies/__init__.py`
* Simplify message handling in `axolotl/prompt_strategies/bradley_terry/chat_template.py` by using a single 'messages' list instead of separate 'chosen_messages' and 'rejected_messages' lists
* Update default 'message_property_mappings' in `axolotl/prompt_strategies/bradley_terry/chat_template.py`
* Add 'field_messages' field to `axolotl/utils/config/models/input/v0_4_1/__init__.py` configuration model

* chore: remove unused input

* chore: remove redundant type ignore

* fix: remove old configs and update examples

* fix: type check

* fix: remove loading old config in ChatMessage

* fix: update faq with potential new undefinederror

* fix: add debug if property mapped is not found

* chore: improve explanation for unmapped properties

* fix: update docs with new config

* chore: add note for deprecation config and del old config from dict

---------

Co-authored-by: NanoCode012 <kevinvong@rocketmail.com>
Co-authored-by: Wing Lian <wing@axolotl.ai>
Co-authored-by: NanoCode012 <nano@axolotl.ai>
2025-02-18 09:59:27 +07:00
Dan Saunders
1ed4de73b6 CLI cleanup and documentation (#2244)
* CLI init refactor

* fix

* cleanup and (partial) docs

* Adding documentation and continuing cleanup (in progress)

* remove finetune.py script

* continued cleanup and documentation

* pytest fixes

* review comments

* fix

* Fix

* typing fixes

* make sure the batch dataset patcher for multipack is always loaded when handling datasets

* review comments

* fix

---------

Co-authored-by: Dan Saunders <dan@axolotl.ai>
Co-authored-by: Wing Lian <wing@axolotl.ai>
2025-01-13 17:55:29 +00:00
Wing Lian
dd26cc3c0f add helper to verify the correct model output file exists (#2245)
* add helper to verify the correct model output file exists

* more checks using helper

* chore: lint

* fix import and relora model check

* workaround for trl trainer saves

* remove stray print
2025-01-13 10:43:29 -05:00
Wing Lian
c10563c444 fix broken linting (#1541)
* chore: lint

* include examples in yaml check

* mistral decided to gate their models...

* more mistral models that were gated
2024-04-19 01:03:04 -04:00
Wing Lian
2a1589f6f6 strip out hacky qlora-fsdp workarounds now that qlora-fsdp fixes are upstreamed (#1428) 2024-03-21 11:56:13 -04:00
Wing Lian
da97285e63 keep gate in fp32 for 16 bit loras (#1105)
* keep gate in fp32 for loras

* add e2e check for lora w/o flash attention for mixtral to check gate

* add checks for gate in fp32 for mixtral, add typehints to train outputs

* mixtral doesn't support basic lora 🤦

add lora tests @ 16bit and fix gate layer check
fix the parameter name, was using the old disco name
don't lora over the gate so we can check that is in fp32
fix dtype check

* ensure we're using fp16/bf16 for 16bit and qlora is always going to be in uint8
2024-01-12 14:58:21 -05:00
Wing Lian
bcc78d8fa3 bump transformers and update attention class map name (#1023)
* bump transformers and update attention class map name

* also run the tests in docker

* add mixtral e2e smoke test

* fix base name for docker image in test

* mixtral lora doesn't seem to work, at least check qlora

* add testcase for mixtral w sample packing

* check monkeypatch for flash attn multipack

* also run the e2e tests in docker

* use all gpus to run tests in docker ci

* use privileged mode too for docker w gpus

* rename the docker e2e actions for gh ci

* set privileged mode for docker and update mixtral model self attn check

* use fp16/bf16 for mixtral w fa2

* skip e2e tests on docker w gpus for now

* tests to validate mistral and mixtral patches

* fix rel import
2024-01-03 12:11:04 -08:00