tocmo0nlord/axolotl
1
0
Fork 0
Code Issues Pull Requests Actions 3 Packages Projects Releases Wiki Activity

add output for train loss in assertian err

Browse Source
This commit is contained in:
Wing Lian
2025-04-18 08:11:11 -07:00
parent 08f287b57f
commit a0670abc94
12 changed files with 25 additions and 25 deletions
Download Patch File Download Diff File Expand all files Collapse all files

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

@@ -89,5 +89,5 @@ 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

@@ -96,5 +96,5 @@ 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"
)

20
tests/e2e/multigpu/test_llama.py
View File

@@ -94,7 +94,7 @@ 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(
@@ -159,7 +159,7 @@ 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):
@@ -385,7 +385,7 @@ 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(
@@ -457,7 +457,7 @@ 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
@@ -538,7 +538,7 @@ 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):
@@ -618,7 +618,7 @@ 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(
@@ -702,7 +702,7 @@ 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(
@@ -776,7 +776,7 @@ 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(
@@ -850,7 +850,7 @@ 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(
@@ -917,5 +917,5 @@ 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

@@ -80,7 +80,7 @@ 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
@@ -138,5 +138,5 @@ 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/multigpu/test_sp.py
View File

@@ -93,7 +93,7 @@ class TestSequenceParallelism:
)
check_tensorboard(
temp_dir + "/runs", "train/train_loss", 2.6, "Train Loss is too high"
temp_dir + "/runs", "train/train_loss", 2.6, "Train loss (%s) is too high"
)
@pytest.mark.parametrize(