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bump transformers==4.52.4 (#2800) [skip ci]

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* bump transformers==4.52.4

* don't use hf offline for qwen tokenizer

* increase timeout

* don't use methodtype

* increase timeout

* better assertion logging

* upgrade deepspeed version too
This commit is contained in:
Wing Lian
2025-06-18 15:46:14 -04:00
committed by GitHub
parent 06a648263b
commit a85efffbef
18 changed files with 34 additions and 35 deletions
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5
tests/e2e/multigpu/patched/test_sp.py
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@@ -91,7 +91,10 @@ class TestSequenceParallelism:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", threshold, "Train Loss is too high"
temp_dir + "/runs",
"train/train_loss",
threshold,
"Train Loss (%s) is too high",
)
@pytest.mark.parametrize(

2
tests/e2e/multigpu/solo/test_flex.py
View File

@@ -85,5 +85,5 @@ class TestPackedFlex:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)

2
tests/e2e/multigpu/test_gemma3.py
View File

@@ -91,5 +91,5 @@ class TestMultiGPUGemma3:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 1.8, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 1.8, "Train Loss (%s) is too high"
)

24
tests/e2e/multigpu/test_llama.py
View File

@@ -89,7 +89,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -154,7 +154,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
def test_dpo_lora_ddp(self, temp_dir):
@@ -232,7 +232,7 @@ class TestMultiGPULlama:
temp_dir + "/runs",
"train/train_loss",
loss_threshold,
"Train Loss is too high",
"Train Loss (%s) is too high",
)
def test_dpo_qlora_ddp(self, temp_dir):
@@ -310,7 +310,7 @@ class TestMultiGPULlama:
temp_dir + "/runs",
"train/train_loss",
loss_threshold,
"Train Loss is too high",
"Train Loss (%s) is too high",
)
@pytest.mark.parametrize(
@@ -380,7 +380,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -452,7 +452,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@require_torch_2_6_0
@@ -533,7 +533,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.1, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.1, "Train Loss (%s) is too high"
)
def test_fsdp_qlora_prequant_packed(self, temp_dir):
@@ -613,7 +613,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -697,7 +697,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.4, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -771,7 +771,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -845,7 +845,7 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@pytest.mark.skip(
@@ -912,5 +912,5 @@ class TestMultiGPULlama:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 4.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 4.0, "Train Loss (%s) is too high"
)

4
tests/e2e/multigpu/test_ray.py
View File

@@ -75,7 +75,7 @@ class TestMultiGPURay:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)
@require_torch_lt_2_6_0
@@ -133,5 +133,5 @@ class TestMultiGPURay:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.3, "Train Loss (%s) is too high"
)

2
tests/e2e/patched/test_fa_xentropy.py
View File

@@ -78,5 +78,5 @@ class TestFAXentropyLlama:
check_model_output_exists(temp_dir, cfg)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 1.5, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 1.5, "Train Loss (%s) is too high"
)

6
tests/e2e/patched/test_unsloth_qlora.py
View File

@@ -73,7 +73,7 @@ class TestUnslothQLoRA:
check_model_output_exists(temp_dir, cfg)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)
def test_unsloth_llama_qlora_unpacked(self, temp_dir):
@@ -123,7 +123,7 @@ class TestUnslothQLoRA:
check_model_output_exists(temp_dir, cfg)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)
@pytest.mark.parametrize(
@@ -178,5 +178,5 @@ class TestUnslothQLoRA:
check_model_output_exists(temp_dir, cfg)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)

2
tests/e2e/solo/test_flex.py
View File

@@ -63,5 +63,5 @@ class TestPackedFlex(unittest.TestCase):
train(cfg=cfg, dataset_meta=dataset_meta)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)

2
tests/e2e/test_llama_pretrain.py
View File

@@ -69,5 +69,5 @@ class TestPretrainLlama:
temp_dir + "/runs",
"train/train_loss",
loss_threshold,
"Train Loss is too high",
"Train Loss (%s) is too high",
)

2
tests/e2e/test_packing_loss.py
View File

@@ -62,5 +62,5 @@ class TestPackedLlama(unittest.TestCase):
train(cfg=cfg, dataset_meta=dataset_meta)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.0, "Train Loss (%s) is too high"
)

2
tests/e2e/test_qat.py
View File

@@ -129,5 +129,5 @@ class TestQATLlama:
temp_dir + "/runs",
"train/train_loss",
loss_threshold,
"Train Loss is too high",
"Train Loss (%s) is too high",
)

2
tests/e2e/test_reward_model_smollm2.py
View File

@@ -66,6 +66,6 @@ class TestRewardModelLoraSmolLM2(unittest.TestCase):
train(cfg=cfg, dataset_meta=dataset_meta)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.5, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.5, "Train Loss (%s) is too high"
)
check_model_output_exists(temp_dir, cfg)

3
tests/prompt_strategies/test_chat_templates_thinking.py
View File

@@ -11,8 +11,6 @@ from axolotl.prompt_strategies.chat_template import (
)
from axolotl.utils.dict import DictDefault
from tests.hf_offline_utils import enable_hf_offline
@pytest.fixture(name="messages_w_reasoning")
def messages_w_reasoning_fixture():
@@ -59,7 +57,6 @@ def messages_w_reasoning_fixture():
@pytest.fixture(name="qwen3_tokenizer")
@enable_hf_offline
def qwen3_tokenizer_fixture(
download_qwen3_half_billion_model,
): # pylint: disable=unused-argument