Streaming SFT support (#3101)

* working

* fixes

* deprecate --iterable; cleanup

* pretrain_multipack_buffer_size -> streaming_multipack_buffer_size

* improvements

* tests

* remove unused

* docs, examples

* nit

* nit

* add val_set_size validation

* val

* nit

* min

* coderabbito

* cleanup

* nit

* add depr warning, cleanup

* nit

* fix test, fix quarto

* fix

* review comments

* review comments

* fix

tests/test_packed_dataset.py

@@ -1,16 +1,11 @@
 """Module for testing dataset sequence packing"""
 
 import unittest
-from pathlib import Path
 
-from datasets import Dataset, load_dataset
 from transformers import AutoTokenizer
 
 from axolotl.cli.args import TrainerCliArgs
 from axolotl.common.datasets import load_datasets
-from axolotl.datasets import ConstantLengthDataset, TokenizedPromptDataset
-from axolotl.prompt_tokenizers import AlpacaPromptTokenizingStrategy
-from axolotl.prompters import AlpacaPrompter
 from axolotl.train import setup_model_and_trainer
 from axolotl.utils.config import normalize_config, validate_config
 from axolotl.utils.dict import DictDefault
@@ -35,43 +30,6 @@ class TestPacking(unittest.TestCase):
             }
         )
 
-    def test_increments_attention(self):
-        prompter = AlpacaPrompter("chat")
-        strat = AlpacaPromptTokenizingStrategy(
-            prompter,
-            self.tokenizer,
-            False,
-            2048,
-        )
-        dateset = load_dataset(
-            "json",
-            data_files=str(Path(__file__).parent / "fixtures/alpaca/alpaca.json"),
-        )["train"]
-        dataset = Dataset.from_list(list(TokenizedPromptDataset(strat, dateset)))
-
-        constant_len_dataset = ConstantLengthDataset(
-            self.tokenizer,
-            [dataset],
-            seq_length=2048,
-        )
-        packed_dataset = Dataset.from_list(list(constant_len_dataset))
-        example = packed_dataset[0]
-        next_bos_index = (
-            example["input_ids"][1:].index(self.tokenizer.bos_token_id) + 1
-        )  # add one since we sliced
-
-        # first example doesn't have mask reset
-        assert example["input_ids"][0] == self.tokenizer.bos_token_id
-        assert example["attention_mask"][0] == 1
-        assert example["position_ids"][0] == 0
-        assert example["position_ids"][1] == 1
-
-        # but subsequent one does
-        assert example["input_ids"][next_bos_index] == self.tokenizer.bos_token_id
-        assert example["attention_mask"][next_bos_index] == 2
-        assert example["position_ids"][next_bos_index] == 0
-        assert example["position_ids"][next_bos_index + 1] == 1
-
     @with_temp_dir
     def test_lora_packing(self, temp_dir):
         cfg = DictDefault(