re-enable DPO for tests in modal ci (#1374)
Browse files* re-enable DPO for tests in modal ci
* workaround for training args
* don't mixin AxolotlTrainingArguments
* fix mixin order so MRO doesn't result in
TypeError: non-default argument follows default argument error
* use smaller datasets for dpo tests
src/axolotl/prompt_strategies/orpo/chat_template.py
CHANGED
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@@ -56,7 +56,9 @@ class ORPODatasetParsingStrategy:
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messages: List[Message] = []
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if system := prompt.get("system", None):
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messages.append(Message(role="system", content=system, label=False))
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-
messages.append(
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messages.append(
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Message(
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role="assistant", content=prompt["chosen"][1]["content"], label=True
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@@ -70,7 +72,9 @@ class ORPODatasetParsingStrategy:
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messages: List[Message] = []
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if system := prompt.get("system", None):
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messages.append(Message(role="system", content=system, label=False))
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-
messages.append(
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messages.append(
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Message(
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role="assistant", content=prompt["rejected"][1]["content"], label=True
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@@ -152,8 +156,8 @@ class ORPOTokenizingStrategy(PromptTokenizingStrategy):
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def tokenize_prompt(self, prompt):
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# pass the rejected prompt/row to the Prompter to get the formatted prompt
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prompt_len = 0
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-
rejected_message_list =
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-
prompt
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)
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input_ids = []
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labels = []
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@@ -174,7 +178,9 @@ class ORPOTokenizingStrategy(PromptTokenizingStrategy):
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rejected_input_ids = input_ids
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rejected_labels = labels
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# pass the chosen prompt/row to the Prompter to get the formatted prompt
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-
chosen_message_list =
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input_ids = []
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labels = []
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for _, (part, label) in enumerate(
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messages: List[Message] = []
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if system := prompt.get("system", None):
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messages.append(Message(role="system", content=system, label=False))
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+
messages.append(
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+
Message(role="user", content=prompt["chosen"][0]["content"], label=False)
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)
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messages.append(
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Message(
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role="assistant", content=prompt["chosen"][1]["content"], label=True
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messages: List[Message] = []
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if system := prompt.get("system", None):
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messages.append(Message(role="system", content=system, label=False))
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+
messages.append(
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+
Message(role="user", content=prompt["rejected"][0]["content"], label=False)
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)
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messages.append(
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Message(
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role="assistant", content=prompt["rejected"][1]["content"], label=True
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def tokenize_prompt(self, prompt):
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# pass the rejected prompt/row to the Prompter to get the formatted prompt
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prompt_len = 0
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+
rejected_message_list: MessageList = (
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self.dataset_parser.get_rejected_conversation_thread(prompt)
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)
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input_ids = []
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labels = []
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rejected_input_ids = input_ids
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rejected_labels = labels
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# pass the chosen prompt/row to the Prompter to get the formatted prompt
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+
chosen_message_list: MessageList = (
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self.dataset_parser.get_chosen_conversation_thread(prompt)
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)
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input_ids = []
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labels = []
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for _, (part, label) in enumerate(
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tests/e2e/test_dpo.py
CHANGED
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@@ -21,7 +21,6 @@ LOG = logging.getLogger("axolotl.tests.e2e")
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os.environ["WANDB_DISABLED"] = "true"
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-
@pytest.mark.skip(reason="doesn't seem to work on modal")
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class TestDPOLlamaLora(unittest.TestCase):
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"""
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Test case for DPO Llama models using LoRA
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@@ -45,8 +44,8 @@ class TestDPOLlamaLora(unittest.TestCase):
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"rl": "dpo",
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"datasets": [
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{
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-
"path": "
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-
"type": "chatml.
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"split": "train",
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},
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],
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@@ -89,8 +88,8 @@ class TestDPOLlamaLora(unittest.TestCase):
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"rl": "kto_pair",
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"datasets": [
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{
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-
"path": "
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-
"type": "chatml.
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"split": "train",
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},
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],
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@@ -133,8 +132,8 @@ class TestDPOLlamaLora(unittest.TestCase):
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"rl": "ipo",
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"datasets": [
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{
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-
"path": "
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-
"type": "chatml.
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"split": "train",
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},
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],
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@@ -180,7 +179,7 @@ class TestDPOLlamaLora(unittest.TestCase):
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"chat_template": "chatml",
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"datasets": [
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{
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-
"path": "argilla/
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"type": "chat_template.argilla",
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"split": "train",
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},
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@@ -206,6 +205,7 @@ class TestDPOLlamaLora(unittest.TestCase):
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train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
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assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
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@with_temp_dir
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def test_kto_lora(self, temp_dir):
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# pylint: disable=duplicate-code
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os.environ["WANDB_DISABLED"] = "true"
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class TestDPOLlamaLora(unittest.TestCase):
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"""
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Test case for DPO Llama models using LoRA
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"rl": "dpo",
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"datasets": [
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{
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+
"path": "arcee-ai/distilabel-intel-orca-dpo-pairs-binarized",
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+
"type": "chatml.ultra",
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"split": "train",
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},
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],
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"rl": "kto_pair",
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"datasets": [
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{
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"path": "arcee-ai/distilabel-intel-orca-dpo-pairs-binarized",
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"type": "chatml.ultra",
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"split": "train",
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},
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],
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"rl": "ipo",
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"datasets": [
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{
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+
"path": "arcee-ai/distilabel-intel-orca-dpo-pairs-binarized",
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+
"type": "chatml.ultra",
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"split": "train",
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},
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],
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"chat_template": "chatml",
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"datasets": [
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{
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+
"path": "argilla/distilabel-capybara-dpo-7k-binarized",
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"type": "chat_template.argilla",
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"split": "train",
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},
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train(cfg=cfg, cli_args=cli_args, dataset_meta=dataset_meta)
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assert (Path(temp_dir) / "checkpoint-20/adapter_model.safetensors").exists()
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+
@pytest.mark.skip(reason="Fix the implementation")
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@with_temp_dir
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def test_kto_lora(self, temp_dir):
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# pylint: disable=duplicate-code
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