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unslothai--unsloth/tests/python/test_dpo_vision_processor_passthrough.py
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chore: import upstream snapshot with attribution
2026-07-13 12:59:56 +08:00

159 lines
4.0 KiB
Python

"""Verify dpo_trainer_vision_process_row forwards prompt and images verbatim."""
import ast
import os
import numpy as np
REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ".."))
RL_PATH = os.path.join(REPO_ROOT, "unsloth", "models", "rl_replacements.py")
def _load_helpers():
src = open(RL_PATH).read()
tree = ast.parse(src)
import torch as _torch
ns = {"torch": _torch}
for node in tree.body:
if isinstance(node, ast.Assign) and any(
isinstance(t, ast.Name) and t.id == "_DPO_VISION_KEYS" for t in node.targets
):
exec(ast.get_source_segment(src, node), ns)
for node in tree.body:
if isinstance(node, ast.FunctionDef) and node.name.startswith(
("dpo_trainer_", "_dpo_trainer_")
):
exec(ast.get_source_segment(src, node), ns)
return ns
class _Tok:
eos_token_id = 99
bos_token_id = None
def __call__(
self,
t,
add_special_tokens = False,
):
return {"input_ids": [10]}
class _Capture:
image_token = "<img>"
boi_token = "<boi>"
def __init__(self):
self.tokenizer = _Tok()
self.last_text = None
self.last_images = "__sentinel__"
def __call__(
self,
images = None,
text = None,
add_special_tokens = False,
):
self.last_text = text
self.last_images = images
out = {"input_ids": [[1, 2]]}
if images is not None:
out["pixel_values"] = [object()]
return out
def test_prompt_passes_through_without_image_token_synthesis():
ns = _load_helpers()
proc = _Capture()
ns["dpo_trainer_vision_process_row"](
{"prompt": "describe", "chosen": "c", "rejected": "r", "images": ["i"]},
proc,
)
assert proc.last_text == "describe"
def test_prompt_with_existing_image_token_unchanged():
ns = _load_helpers()
proc = _Capture()
ns["dpo_trainer_vision_process_row"](
{"prompt": "<img> describe", "chosen": "c", "rejected": "r", "images": ["i"]},
proc,
)
assert proc.last_text == "<img> describe"
def test_gemma3_style_boi_token_prompt_not_corrupted():
ns = _load_helpers()
proc = _Capture()
ns["dpo_trainer_vision_process_row"](
{"prompt": "<boi> describe", "chosen": "c", "rejected": "r", "images": ["i"]},
proc,
)
assert proc.last_text == "<boi> describe"
assert "<img>" not in proc.last_text
def test_multi_image_prompt_unchanged_no_extra_placeholders():
ns = _load_helpers()
proc = _Capture()
ns["dpo_trainer_vision_process_row"](
{
"prompt": "compare",
"chosen": "c",
"rejected": "r",
"images": ["a", "b", "c"],
},
proc,
)
assert proc.last_text == "compare"
def test_list_images_forwarded_verbatim():
ns = _load_helpers()
proc = _Capture()
payload = ["a", "b"]
ns["dpo_trainer_vision_process_row"](
{"prompt": "p", "chosen": "c", "rejected": "r", "images": payload},
proc,
)
assert proc.last_images is payload
def test_single_pil_like_image_forwarded_verbatim():
ns = _load_helpers()
class PIL:
def __bool__(self):
return True
proc = _Capture()
pil = PIL()
ns["dpo_trainer_vision_process_row"](
{"prompt": "p", "chosen": "c", "rejected": "r", "images": pil},
proc,
)
assert proc.last_images is pil
def test_numpy_ndarray_image_forwarded_verbatim():
ns = _load_helpers()
proc = _Capture()
arr = np.zeros((2, 3, 3), dtype = np.uint8)
ns["dpo_trainer_vision_process_row"](
{"prompt": "p", "chosen": "c", "rejected": "r", "images": arr},
proc,
)
assert proc.last_images is arr
def test_missing_images_key_passes_none_to_processor():
ns = _load_helpers()
proc = _Capture()
ns["dpo_trainer_vision_process_row"](
{"prompt": "p", "chosen": "c", "rejected": "r"},
proc,
)
assert proc.last_images is None