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add helper to verify the correct model output file exists (#2245)

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* 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
This commit is contained in:
Wing Lian
2025-01-13 10:43:29 -05:00
committed by GitHub
parent d8b4027200
commit dd26cc3c0f
29 changed files with 116 additions and 111 deletions
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9
tests/e2e/test_llama.py
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@@ -4,7 +4,8 @@ E2E tests for llama
import logging
import os
from pathlib import Path
from e2e.utils import check_model_output_exists
from axolotl.cli import load_datasets
from axolotl.common.cli import TrainerCliArgs
@@ -60,7 +61,7 @@ class TestLlama:
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
check_model_output_exists(temp_dir, cfg)
def test_fix_untrained_tokens(self, temp_dir):
# pylint: disable=duplicate-code
@@ -103,7 +104,7 @@ class TestLlama:
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
check_model_output_exists(temp_dir, cfg)
def test_batch_flattening(self, temp_dir):
# pylint: disable=duplicate-code
@@ -142,4 +143,4 @@ class TestLlama:
dataset_meta = load_datasets(cfg=cfg, cli_args=cli_args)
train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
assert (Path(temp_dir) / "model.safetensors").exists()
check_model_output_exists(temp_dir, cfg)