36df317293
Comment-only pass over the Python this PR touches: drop what the code already says, collapse multi-line explanations that still read on one line, and keep the reasoning that is not recoverable from the code. No code, docstring semantics or behaviour changes; verified with an AST comparison against the previous revision, and the backend suite is unchanged (same 37 environment failures as before: the API integration tests that need a live keyed server, the flash-attn install hooks, and the GPU memory fields).
353 lines
12 KiB
Python
353 lines
12 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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"""Unit tests for the single-GPU arbiter.
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The real evictors (which tear down live backends) are replaced with recorders, so
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these verify only the ownership/eviction sequencing — no torch, GPU, or subprocess.
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"""
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from __future__ import annotations
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import pytest
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import core.inference.gpu_arbiter as arb
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@pytest.fixture
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def calls(monkeypatch):
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recorded: list[str] = []
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monkeypatch.setattr(arb, "_owner", None)
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monkeypatch.setitem(arb._EVICTORS, arb.CHAT, lambda: recorded.append("evict-chat"))
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monkeypatch.setitem(arb._EVICTORS, arb.DIFFUSION, lambda: recorded.append("evict-diffusion"))
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return recorded
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def test_first_acquire_evicts_nothing(calls):
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arb.acquire_for(arb.CHAT)
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assert calls == []
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assert arb.current_owner() == arb.CHAT
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def test_diffusion_load_evicts_chat(calls):
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arb.acquire_for(arb.CHAT)
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arb.acquire_for(arb.DIFFUSION)
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assert calls == ["evict-chat"]
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assert arb.current_owner() == arb.DIFFUSION
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def test_chat_load_evicts_diffusion(calls):
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arb.acquire_for(arb.DIFFUSION)
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arb.acquire_for(arb.CHAT)
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assert calls == ["evict-diffusion"]
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assert arb.current_owner() == arb.CHAT
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def test_reacquiring_same_owner_does_not_evict(calls):
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arb.acquire_for(arb.CHAT)
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arb.acquire_for(arb.CHAT)
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assert calls == []
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assert arb.current_owner() == arb.CHAT
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def test_release_clears_owner(calls):
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arb.acquire_for(arb.DIFFUSION)
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arb.release(arb.DIFFUSION)
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assert arb.current_owner() is None
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# A subsequent chat load then has nothing to evict.
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arb.acquire_for(arb.CHAT)
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assert calls == []
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def test_release_by_non_owner_is_noop(calls):
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arb.acquire_for(arb.CHAT)
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arb.release(arb.DIFFUSION)
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assert arb.current_owner() == arb.CHAT
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def test_unknown_owner_raises(calls):
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with pytest.raises(ValueError):
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arb.acquire_for("gpu")
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def test_evict_chat_unloads_a_still_loading_chat_backend(monkeypatch):
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# A chat model still starting up is is_active (process exists) but not yet is_loaded (healthy).
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# Eviction must still unload it, or the load keeps allocating VRAM after the GPU was handed over.
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import core.inference as core_inference
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import routes.inference as routes_inference
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unloaded: list[bool] = []
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class _FakeLlama:
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is_active = True
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is_loaded = False # still loading: skipped if eviction gates on is_loaded
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def unload_model(self):
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unloaded.append(True)
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def _wait_for_vram_settle(self, *, since_kill):
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pass
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class _FakeOrchestrator:
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active_model_name = None
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def unload_model(self, name):
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pass
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def _shutdown_subprocess(self, timeout = 5.0):
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pass
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monkeypatch.setattr(routes_inference, "get_llama_cpp_backend", lambda: _FakeLlama())
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monkeypatch.setattr(core_inference, "get_inference_backend", lambda: _FakeOrchestrator())
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arb._evict_chat()
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assert unloaded == [True] # still-loading chat backend was unloaded, not skipped
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def test_release_if_drops_only_when_predicate_true(calls):
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arb.acquire_for(arb.DIFFUSION)
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# Predicate false -> ownership kept.
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assert arb.release_if(arb.DIFFUSION, lambda: False) is False
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assert arb.current_owner() == arb.DIFFUSION
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# Predicate true -> ownership dropped.
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assert arb.release_if(arb.DIFFUSION, lambda: True) is True
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assert arb.current_owner() is None
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def test_release_if_by_non_owner_is_noop(calls):
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arb.acquire_for(arb.CHAT)
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# The predicate is never consulted for a non-owner; ownership is untouched.
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consulted: list[bool] = []
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assert arb.release_if(arb.DIFFUSION, lambda: consulted.append(True) or True) is False
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assert consulted == []
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assert arb.current_owner() == arb.CHAT
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def test_release_if_predicate_sees_a_reregistered_same_owner_load(calls):
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# The race release_if closes: a slow unload's predicate reports a load now in flight, so ownership
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# must stay with DIFFUSION.
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arb.acquire_for(arb.DIFFUSION)
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loading = {"in_flight": True}
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assert arb.release_if(arb.DIFFUSION, lambda: not loading["in_flight"]) is False
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assert arb.current_owner() == arb.DIFFUSION
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def test_register_runs_under_ownership_and_returns_result(calls):
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# A register callback runs after ownership transfers and its return value is forwarded; the route
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# uses this to register the in-flight load.
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seen_owner: list = []
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def register():
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seen_owner.append(arb.current_owner())
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return "status-dict"
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result = arb.acquire_for(arb.DIFFUSION, register)
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assert result == "status-dict"
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assert seen_owner == [arb.DIFFUSION]
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assert arb.current_owner() == arb.DIFFUSION
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def test_register_failure_leaves_ownership_in_place(calls):
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# A failing register (e.g. begin_load reporting a load already in progress) propagates but must not
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# drop ownership: the prior handoff stands.
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arb.acquire_for(arb.CHAT)
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def register():
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raise RuntimeError("A diffusion load is already in progress.")
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with pytest.raises(RuntimeError):
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arb.acquire_for(arb.DIFFUSION, register)
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assert calls == ["evict-chat"]
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assert arb.current_owner() == arb.DIFFUSION
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def test_competing_acquire_blocks_until_register_completes(monkeypatch):
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# While DIFFUSION registers its load, a competing VIDEO acquire must block (not evict) until the
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# load is in-flight; holding the lock across register makes eviction never race it.
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import threading
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import time
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monkeypatch.setattr(arb, "_owner", None)
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evicted: list = []
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monkeypatch.setitem(arb._EVICTORS, arb.DIFFUSION, lambda: evicted.append("evict-diffusion"))
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monkeypatch.setitem(arb._EVICTORS, arb.VIDEO, lambda: evicted.append("evict-video"))
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in_register = threading.Event()
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release_register = threading.Event()
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def register():
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in_register.set()
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# Hold the arbiter lock here; a competing acquire_for(VIDEO) must block until we return.
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assert release_register.wait(2.0)
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return "loading"
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loader = threading.Thread(target = lambda: arb.acquire_for(arb.DIFFUSION, register))
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loader.start()
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assert in_register.wait(2.0)
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competitor_done = threading.Event()
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threading.Thread(
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target = lambda: (arb.acquire_for(arb.VIDEO), competitor_done.set()),
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).start()
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# The competitor cannot evict DIFFUSION while register still holds the lock.
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time.sleep(0.1)
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assert evicted == []
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assert not competitor_done.is_set()
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# Let register finish; ownership is now safely registered, so the competitor proceeds.
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release_register.set()
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loader.join(2.0)
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assert competitor_done.wait(2.0)
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assert evicted == ["evict-diffusion"]
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assert arb.current_owner() == arb.VIDEO
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def test_evict_chat_cancels_a_chat_load_that_has_not_spawned_yet(monkeypatch):
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# An HF chat load has no llama-server process until its GGUF finished downloading, which is
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# minutes. Gating only on is_active let the evictor find nothing to cancel, grant the GPU to the
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# image/video load, and the chat load then spawned onto the same device. The in-flight marker is
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# what makes that load cancellable.
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import core.inference as core_inference
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import routes.inference as routes_inference
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from core.inference.llama_cpp import chat_load_in_flight
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unloaded: list[bool] = []
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class _FakeLlama:
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is_active = False # nothing spawned yet: the download is still running
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is_loaded = False
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def unload_model(self):
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unloaded.append(True)
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def _wait_for_vram_settle(self, *, since_kill):
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pass
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class _FakeOrchestrator:
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active_model_name = None
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def unload_model(self, name):
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pass
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def _shutdown_subprocess(self, timeout = 5.0):
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pass
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monkeypatch.setattr(routes_inference, "get_llama_cpp_backend", lambda: _FakeLlama())
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monkeypatch.setattr(core_inference, "get_inference_backend", lambda: _FakeOrchestrator())
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# No load in flight: nothing to cancel.
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arb._evict_chat()
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assert unloaded == []
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with chat_load_in_flight():
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arb._evict_chat()
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assert unloaded == [True]
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# The marker is released with the load, so a later eviction is a no-op again.
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arb._evict_chat()
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assert unloaded == [True]
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def test_evict_chat_cancels_an_in_flight_safetensors_load(monkeypatch):
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# The orchestrator publishes active_model_name only once its worker reports success, so an
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# in-flight safetensors load is visible ONLY in loading_models. Gating the cancellation on
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# active_model_name let that worker finish after ownership transferred and allocate alongside the
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# image/video pipeline.
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import core.inference as core_inference
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import routes.inference as routes_inference
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cancelled: list[str] = []
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class _FakeLlama:
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is_active = False
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is_loaded = False
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def unload_model(self):
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pass
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def _wait_for_vram_settle(self, *, since_kill):
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pass
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class _FakeOrchestrator:
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active_model_name = None # not published yet: the load is still running
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loading_models = {"unsloth/Qwen3-4B"}
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def unload_model(self, name):
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raise AssertionError("unload_model must not run for an unpublished load")
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def cancel_load(self, name):
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cancelled.append(name)
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return True
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def _shutdown_subprocess(self, timeout = 5.0):
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pass
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monkeypatch.setattr(routes_inference, "get_llama_cpp_backend", lambda: _FakeLlama())
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monkeypatch.setattr(core_inference, "get_inference_backend", lambda: _FakeOrchestrator())
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arb._evict_chat()
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assert cancelled == ["unsloth/Qwen3-4B"]
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def test_evict_chat_cancels_every_pending_load_over_a_live_snapshot(monkeypatch):
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# cancel_load discards the marker it cancels, so iterate a snapshot rather than the live set
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# (mutating during iteration raises).
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import core.inference as core_inference
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import routes.inference as routes_inference
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cancelled: list[str] = []
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class _FakeLlama:
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is_active = False
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is_loaded = False
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def unload_model(self):
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pass
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def _wait_for_vram_settle(self, *, since_kill):
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pass
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class _FakeOrchestrator:
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active_model_name = None
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def __init__(self):
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self.loading_models = {"a/one", "b/two"}
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def cancel_load(self, name):
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self.loading_models.discard(name)
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cancelled.append(name)
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return True
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def _shutdown_subprocess(self, timeout = 5.0):
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pass
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orchestrator = _FakeOrchestrator()
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monkeypatch.setattr(routes_inference, "get_llama_cpp_backend", lambda: _FakeLlama())
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monkeypatch.setattr(core_inference, "get_inference_backend", lambda: orchestrator)
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arb._evict_chat()
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assert sorted(cancelled) == ["a/one", "b/two"]
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assert orchestrator.loading_models == set()
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def test_the_safetensors_load_yields_a_gpu_it_lost_while_loading():
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# Mirror of the GGUF branch's guard: an Images/Video acquire can land in the gap between the
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# eviction and the load's publish, so the load has to undo itself instead of leaving two models
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# resident.
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from pathlib import Path
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route_src = (Path(__file__).resolve().parent.parent / "routes" / "inference.py").read_text(
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encoding = "utf-8"
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)
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load_impl = route_src[route_src.index("async def _load_model_impl") :]
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unsloth_load = load_impl.index(
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"success = await asyncio.to_thread(\n backend.load_model,"
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)
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tail = load_impl[unsloth_load:]
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guard = tail.index("if current_owner() != CHAT:")
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assert "await asyncio.to_thread(backend.unload_model, config.identifier)" in tail[guard:]
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assert tail.index("status_code = 409", guard) > guard
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