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remove unused

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This commit is contained in:
Dan Saunders
2025-08-22 00:37:43 +00:00
parent 42b38a718a
commit 49bd6ece4a
2 changed files with 0 additions and 93 deletions
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15
src/axolotl/utils/schemas/validation.py
View File

@@ -1456,21 +1456,6 @@ class StreamingValidationMixin:
return self return self
@model_validator(mode="after")
def check_streaming_skip_prepare_dataset(self):
"""Ensure skip_prepare_dataset is set for streaming datasets."""
# Check if streaming is enabled for training datasets
if self._is_streaming_enabled():
skip_prepare = getattr(self, "skip_prepare_dataset", None)
if skip_prepare is False:
LOG.warning(
"skip_prepare_dataset=False is not compatible with streaming "
"datasets. Setting skip_prepare_dataset=True."
)
self.skip_prepare_dataset = True
return self
@model_validator(mode="after") @model_validator(mode="after")
def check_dataset_mixing_weights(self): def check_dataset_mixing_weights(self):
"""Validate dataset mixing weights configuration.""" """Validate dataset mixing weights configuration."""

78
tests/e2e/test_streaming.py
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@@ -85,84 +85,6 @@ class TestStreamingDatasets:
"Train Loss (%s) is too high", "Train Loss (%s) is too high",
) )
def test_streaming_eval_specific_mixing(self, temp_dir):
"""Test eval-specific mixing strategy override"""
cfg = DictDefault(
{
"base_model": "HuggingFaceTB/SmolLM2-135M",
"flash_attention": True,
"sequence_len": 512,
"sample_packing": False,
"dataset_processes": 1,
"special_tokens": {
"pad_token": "<|endoftext|>",
},
"datasets": [
{
"path": "mhenrichsen/alpaca_2k_test",
"type": "alpaca",
},
{
"path": "tatsu-lab/alpaca",
"type": "alpaca",
},
],
"test_datasets": [
{
"path": "mhenrichsen/alpaca_2k_test",
"type": "alpaca",
"split": "train",
},
{
"path": "tatsu-lab/alpaca",
"type": "alpaca",
"split": "train",
},
],
# Streaming config
"streaming": True,
"eval_streaming": True,
"max_steps": 3,
# Different mixing for train vs eval
"dataset_mixing_strategy": "round_robin",
"eval_dataset_mixing_strategy": "weighted",
"eval_mixing_weights": [0.6, 0.4],
"micro_batch_size": 1,
"gradient_accumulation_steps": 1,
"output_dir": temp_dir,
"learning_rate": 0.00001,
"optimizer": "adamw_torch_fused",
"lr_scheduler": "cosine",
"save_safetensors": True,
"bf16": "auto",
"use_tensorboard": True,
"save_first_step": False,
"eval_steps": 3, # Eval at the end
}
)
cfg = validate_config(cfg)
normalize_config(cfg)
dataset_meta = load_datasets(cfg=cfg)
train(cfg=cfg, dataset_meta=dataset_meta)
check_model_output_exists(temp_dir, cfg)
# Check both train and eval losses
check_tensorboard(
temp_dir + "/runs",
"train/train_loss",
2.5,
"Train Loss (%s) is too high",
)
check_tensorboard(
temp_dir + "/runs",
"eval/eval_loss",
2.5,
"Eval Loss (%s) is too high",
)
def test_streaming_validation_error(self, temp_dir): def test_streaming_validation_error(self, temp_dir):
"""Test that pydantic validation catches invalid streaming configs""" """Test that pydantic validation catches invalid streaming configs"""