100 lines
3 KiB
Python
100 lines
3 KiB
Python
import ast
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from pathlib import Path
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import logging
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import warnings as _warnings
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import torch
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def _find_vision():
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for p in [
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Path(__file__).resolve().parent / "unsloth" / "models" / "vision.py",
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Path(__file__).resolve().parents[1] / "unsloth" / "models" / "vision.py",
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Path(
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"/mnt/disks/unslothai/ubuntu/workspace_25/github_review/unsloth-pr-5053-staging-3/unsloth/models/vision.py"
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),
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]:
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if p.exists():
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return p
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raise FileNotFoundError("vision.py not found")
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def _load_fns():
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tree = ast.parse(_find_vision().read_text())
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ns = {"torch": torch, "warnings": _warnings, "logger": logging.getLogger("test")}
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for node in tree.body:
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if isinstance(node, ast.FunctionDef) and node.name in {
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"_infer_device_map_from_loaded_model",
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"_attach_bnb_multidevice_hooks",
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}:
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exec(
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compile(
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ast.Module(body = [node], type_ignores = []),
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str(_find_vision()),
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"exec",
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),
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ns,
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)
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return ns["_infer_device_map_from_loaded_model"], ns[
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"_attach_bnb_multidevice_hooks"
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]
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class _P:
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def __init__(self, dev):
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self.device = torch.device(dev) if isinstance(dev, str) else dev
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class _FakeMod:
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def __init__(self, params = None, buffers = None, children = None, hf_device_map = None):
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self._p = list(params or [])
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self._b = list(buffers or [])
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self._c = list(children or [])
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self.hf_device_map = hf_device_map
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def named_parameters(self, recurse = True, remove_duplicate = False):
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for n, d in self._p:
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yield n, _P(d)
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if recurse:
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for cn, cm in self._c:
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for pn, pp in cm.named_parameters(
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recurse = True, remove_duplicate = remove_duplicate
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):
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yield f"{cn}.{pn}", pp
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def parameters(self, recurse = True):
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for _, p in self.named_parameters(recurse = recurse):
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yield p
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def named_buffers(self, recurse = True):
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for n, d in self._b:
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yield n, _P(d)
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if recurse:
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for cn, cm in self._c:
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for bn, bb in cm.named_buffers(recurse = True):
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yield f"{cn}.{bn}", bb
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def named_children(self):
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yield from self._c
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def test_attach_load_in_4bit_bool_alone_activates(monkeypatch):
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"""Minimal contract: when only load_in_4bit=True is passed, the helper
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activates without requiring model.is_loaded_in_4bit to also be True."""
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import accelerate
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called = {"n": 0}
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monkeypatch.setattr(
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accelerate,
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"dispatch_model",
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lambda *a, **kw: called.__setitem__("n", called["n"] + 1),
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)
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_, attach = _load_fns()
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m = _FakeMod(params = [("w", "cuda:1")]) # no is_loaded_in_* attrs set
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attach(
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m,
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load_in_4bit = True,
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load_in_8bit = False,
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offload_embedding = False,
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fast_inference = False,
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)
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assert called["n"] == 1
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