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).
441 lines
19 KiB
Python
441 lines
19 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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"""Hermetic CPU tests for attention-backend selection. No torch/diffusers needed:
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``_is_cuda_nvidia`` is monkeypatched for the policy tests, and the apply path uses a fake
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transformer that records / raises on ``set_attention_backend``.
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"""
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from __future__ import annotations
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import types
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import pytest
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import core.inference.diffusion_attention as att
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from core.inference.diffusion_attention import (
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ATTN_AUTO,
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apply_attention_backend,
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normalize_attention_backend,
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select_attention_backend,
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)
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def _target(device = "cuda"):
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return types.SimpleNamespace(device = device)
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# ── normalize ────────────────────────────────────────────────────────────────────
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def test_normalize_defaults_and_aliases():
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assert normalize_attention_backend(None) == ATTN_AUTO
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assert normalize_attention_backend("") == ATTN_AUTO
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assert normalize_attention_backend("auto") == ATTN_AUTO
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assert normalize_attention_backend("CuDNN") == "cudnn"
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assert normalize_attention_backend("FLASH3") == "flash3"
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assert normalize_attention_backend("sdpa") == "sdpa"
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def test_normalize_rejects_unknown():
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with pytest.raises(ValueError):
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normalize_attention_backend("bogus")
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# dashes are no longer silently rewritten to underscores, so a dashed alias is rejected.
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with pytest.raises(ValueError):
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normalize_attention_backend("flash-3")
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def test_sdpa_alias_maps_to_native():
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# sdpa is an alias for native, so nothing to set on the dispatcher.
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assert select_attention_backend(_target(), "sdpa", speed_active = True) is None
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# ── select policy ─────────────────────────────────────────────────────────────────
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def test_auto_upgrades_to_cudnn_on_nvidia_when_speed_active(monkeypatch):
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: True)
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monkeypatch.setattr(att, "_cuda_capability", lambda: (8, 0)) # Ampere+: cuDNN ok
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assert select_attention_backend(_target(), "auto", speed_active = True) == "_native_cudnn"
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def test_auto_does_not_pin_cudnn_below_sm80(monkeypatch):
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# cuDNN fused SDPA fails at run time on pre-SM80 (T4 / V100), so auto must stay native there
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# rather than pin a backend that crashes on first generation.
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: True)
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monkeypatch.setattr(att, "_cuda_capability", lambda: (7, 5)) # Turing T4
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assert select_attention_backend(_target(), "auto", speed_active = True) is None
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def test_auto_stays_native_when_speed_off(monkeypatch):
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# off must stay bit-identical, so no backend change even on NVIDIA.
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: True)
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assert select_attention_backend(_target(), "auto", speed_active = False) is None
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def test_auto_stays_native_off_nvidia(monkeypatch):
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: False)
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assert select_attention_backend(_target(device = "mps"), "auto", speed_active = True) is None
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def test_explicit_backend_honored_regardless_of_speed(monkeypatch):
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: True)
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# Pin a high capability so the arch-gated flash4 isn't dropped by the runtime check.
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monkeypatch.setattr(att, "_cuda_capability", lambda: (10, 0))
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assert select_attention_backend(_target(), "sage", speed_active = False) == "sage"
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assert select_attention_backend(_target(), "flash4", speed_active = False) == "flash_4_hub"
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assert select_attention_backend(_target(), "cudnn", speed_active = False) == "_native_cudnn"
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def test_explicit_backend_dropped_off_nvidia_cuda(monkeypatch):
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# Explicit cuDNN/flash/sage on ROCm / MPS / CPU passes diffusers' set-time check and crashes at
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# the first generation, so selection drops to the native default.
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: False)
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monkeypatch.setattr(att, "_cuda_capability", lambda: (10, 0))
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for alias in ("sage", "flash", "flash4", "cudnn"):
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assert select_attention_backend(_target(device = "mps"), alias, speed_active = True) is None
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def test_aiter_honored_on_rocm(monkeypatch):
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# AITER is the AMD ROCm kernel, so on a ROCm CUDA target it must be honored, not dropped by the
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# NVIDIA-only guard.
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: False) # hip build
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assert select_attention_backend(_target(), "aiter", speed_active = False) == "aiter"
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def test_aiter_dropped_off_rocm(monkeypatch):
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# aiter on NVIDIA CUDA (or MPS / CPU) is not usable, so it drops to the native default.
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: True) # NVIDIA
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assert select_attention_backend(_target(), "aiter", speed_active = False) is None
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monkeypatch.setattr(att, "_is_cuda_nvidia", lambda target: False)
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assert select_attention_backend(_target(device = "mps"), "aiter", speed_active = False) is None
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def test_explicit_native_returns_none():
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# native is the default, so nothing to set.
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assert select_attention_backend(_target(), "native", speed_active = True) is None
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# ── arch gating (flash3/flash4 need a specific CUDA capability) ─────────────────────
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def test_flash3_dropped_below_hopper(monkeypatch):
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monkeypatch.setattr(att, "_cuda_capability", lambda: (8, 9)) # Ada / consumer
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assert select_attention_backend(_target(), "flash3", speed_active = False) is None
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def test_flash4_dropped_below_blackwell(monkeypatch):
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monkeypatch.setattr(att, "_cuda_capability", lambda: (9, 0)) # Hopper, but FA4 needs SM100
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assert select_attention_backend(_target(), "flash4", speed_active = False) is None
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# flash3 still allowed on Hopper.
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assert select_attention_backend(_target(), "flash3", speed_active = False) == "_flash_3_hub"
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def test_arch_gate_does_not_block_when_capability_unknown(monkeypatch):
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# Unknown capability must not block; diffusers' set-time check still guards.
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monkeypatch.setattr(att, "_cuda_capability", lambda: None)
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assert select_attention_backend(_target(), "flash4", speed_active = False) == "flash_4_hub"
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def test_flash3_dropped_on_blackwell(monkeypatch):
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# FlashAttention 3 is a Hopper-SM90 rewrite with no Blackwell kernel, so an explicit flash3 on a
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# B200 must drop to native rather than set fine then crash.
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monkeypatch.setattr(att, "_cuda_capability", lambda: (10, 0))
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assert select_attention_backend(_target(), "flash3", speed_active = False) is None
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# FA4 is still honored on Blackwell.
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assert select_attention_backend(_target(), "flash4", speed_active = False) == "flash_4_hub"
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# flash3 is allowed exactly on Hopper SM90.
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monkeypatch.setattr(att, "_cuda_capability", lambda: (9, 0))
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assert select_attention_backend(_target(), "flash3", speed_active = False) == "_flash_3_hub"
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def test_explicit_cudnn_dropped_below_sm80(monkeypatch):
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# An explicit cuDNN request on pre-Ampere must drop to native, not set fine and crash at first
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# generation -- the same gate the auto path applies.
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monkeypatch.setattr(att, "_cuda_capability", lambda: (7, 5))
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assert select_attention_backend(_target(), "cudnn", speed_active = False) is None
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# Ampere+ still honors it.
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monkeypatch.setattr(att, "_cuda_capability", lambda: (8, 0))
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assert select_attention_backend(_target(), "cudnn", speed_active = False) == "_native_cudnn"
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# ── apply ─────────────────────────────────────────────────────────────────────────
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class _FakeTransformer:
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def __init__(self, *, fail = False):
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self.fail = fail
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self.set_to = None
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def set_attention_backend(self, name):
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if self.fail:
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raise RuntimeError(f"{name} kernel unavailable")
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self.set_to = name
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def _pipe(transformer):
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return types.SimpleNamespace(transformer = transformer)
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def test_apply_none_leaves_native_when_global_already_native(monkeypatch):
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# Global already native, so no redundant set call.
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monkeypatch.setattr(att, "_active_attention_backend", lambda: "native")
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t = _FakeTransformer()
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assert apply_attention_backend(_pipe(t), None) is None
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assert t.set_to is None
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def test_apply_none_restores_native_when_global_polluted(monkeypatch):
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# A previous load pinned cuDNN process-wide; a native load must reset it so it can't silently
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# inherit cuDNN (the bit-identical/off guarantee).
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monkeypatch.setattr(att, "_active_attention_backend", lambda: "_native_cudnn")
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t = _FakeTransformer()
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assert apply_attention_backend(_pipe(t), None) is None
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assert t.set_to == "native"
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def test_apply_sets_backend():
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t = _FakeTransformer()
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engaged = apply_attention_backend(_pipe(t), "_native_cudnn")
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assert engaged == "_native_cudnn" and t.set_to == "_native_cudnn"
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def test_apply_sets_backend_on_both_dits():
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# A dual-DiT family (Ideogram) runs both DiTs each step, so the backend must be set on BOTH, else
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# the second keeps native while status reports the requested kernel as engaged.
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t1, t2 = _FakeTransformer(), _FakeTransformer()
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pipe = types.SimpleNamespace(transformer = t1, unconditional_transformer = t2)
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engaged = apply_attention_backend(pipe, "_native_cudnn")
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assert engaged == "_native_cudnn"
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assert t1.set_to == "_native_cudnn" and t2.set_to == "_native_cudnn"
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def test_apply_falls_back_on_unavailable_kernel(monkeypatch):
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# An unavailable kernel must not fail the load: returns None (diffusers default).
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monkeypatch.setattr(att, "_active_attention_backend", lambda: "native")
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t = _FakeTransformer(fail = True)
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assert apply_attention_backend(_pipe(t), "sage") is None
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def test_apply_failed_kernel_restores_native_when_polluted(monkeypatch):
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# Requested kernel fails AND the global is polluted: restore native before returning.
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monkeypatch.setattr(att, "_active_attention_backend", lambda: "_native_cudnn")
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class _FailOnceTransformer:
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def __init__(self):
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self.calls = []
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def set_attention_backend(self, name):
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self.calls.append(name)
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if name != "native":
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raise RuntimeError(f"{name} kernel unavailable")
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t = _FailOnceTransformer()
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assert apply_attention_backend(_pipe(t), "sage") is None
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assert t.calls == ["sage", "native"]
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def test_apply_handles_missing_method():
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pipe = types.SimpleNamespace(transformer = types.SimpleNamespace())
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assert apply_attention_backend(pipe, "_native_cudnn") is None
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def test_apply_resets_global_registry_after_success(monkeypatch):
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# After a successful per-transformer set, the process-wide registry must be reset to native so a
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# later component can't inherit this kernel, while the transformer keeps the engaged one.
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called = {"reset": False}
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monkeypatch.setattr(
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att, "_reset_global_backend_to_native", lambda logger: called.__setitem__("reset", True)
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)
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t = _FakeTransformer()
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engaged = apply_attention_backend(_pipe(t), "_native_cudnn")
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assert engaged == "_native_cudnn" and t.set_to == "_native_cudnn"
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assert called["reset"] is True
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def test_active_attention_backend_reads_tuple_return():
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# get_active_backend() returns a (AttentionBackendName, fn) tuple; the helper must read the
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# name's .value, not stringify the tuple (which never compares equal to a name).
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pytest.importorskip("diffusers")
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from diffusers.models.attention_dispatch import (
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AttentionBackendName,
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_AttentionBackendRegistry,
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)
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_AttentionBackendRegistry.set_active_backend(AttentionBackendName.NATIVE)
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assert att._active_attention_backend() == "native"
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# ── on-demand wheel-only install of optional kernels ─────────────────────────────
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@pytest.fixture(autouse = True)
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def _no_real_installs(monkeypatch):
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# Unit tests must never shell out to pip: the apply path probes installable backends, so
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# hard-disable the gate; install tests re-enable it with a stubbed subprocess.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "0")
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# The install once-per-process memo is module state; clear it so each test starts fresh.
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att._INSTALL_ATTEMPTED.clear()
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class _Recorder:
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def __init__(self):
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self.calls = []
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def __call__(self, cmd, **kwargs):
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self.calls.append(list(cmd))
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return types.SimpleNamespace(returncode = 0)
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def _stub_subprocess(monkeypatch, run):
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import subprocess
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monkeypatch.setattr(subprocess, "run", run)
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def test_install_skipped_when_gate_disabled(monkeypatch):
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run = _Recorder()
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_stub_subprocess(monkeypatch, run)
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att._ensure_attention_backend_installed("sage")
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assert run.calls == []
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def test_install_skipped_when_module_present(monkeypatch):
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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monkeypatch.setattr(
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importlib.util, "find_spec", lambda name: object() if name == "sageattention" else None
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)
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run = _Recorder()
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_stub_subprocess(monkeypatch, run)
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att._ensure_attention_backend_installed("sage")
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assert run.calls == []
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def test_install_runs_wheel_only_for_missing_kernel(monkeypatch):
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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run = _Recorder()
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_stub_subprocess(monkeypatch, run)
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att._ensure_attention_backend_installed("sage")
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assert len(run.calls) == 1
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cmd = run.calls[0]
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assert "--only-binary" in cmd and ":all:" in cmd and "sageattention" in cmd
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def test_install_uses_no_deps_to_protect_core_deps(monkeypatch):
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# A kernel add-on pins an exact torch, so a normal install would replace the running torch/triton.
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# --no-deps installs only the kernel wheel; an ABI-incompatible one just fails to import.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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run = _Recorder()
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_stub_subprocess(monkeypatch, run)
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att._ensure_attention_backend_installed("xformers")
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assert len(run.calls) == 1
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assert "--no-deps" in run.calls[0]
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def test_failed_install_not_retried_in_same_process(monkeypatch):
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# The loader pre-installs the kernel OUTSIDE its locks and re-resolves under _generate_lock; if
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# the pre-install failed the in-lock apply must NOT re-run pip (a second 600s install would block
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# unload/cancel). The once-per-process memo makes the retry a no-op.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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import subprocess as sp
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None) # stays missing
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calls: list[list[str]] = []
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def _boom(cmd, **kwargs):
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calls.append(list(cmd))
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raise sp.CalledProcessError(returncode = 1, cmd = cmd)
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_stub_subprocess(monkeypatch, _boom)
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att._ensure_attention_backend_installed("sage") # pre-install attempt (outside lock)
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att._ensure_attention_backend_installed("sage") # in-lock retry -> must be skipped
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assert len(calls) == 1
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def test_install_invalidates_import_caches_on_success(monkeypatch):
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# A wheel written to site-packages after the finder cached that directory can be missed by the
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# very next import, so a successful install must invalidate the caches.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib
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import importlib.util
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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_stub_subprocess(monkeypatch, _Recorder())
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invalidated = []
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monkeypatch.setattr(importlib, "invalidate_caches", lambda: invalidated.append(True))
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att._ensure_attention_backend_installed("sage")
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assert invalidated == [True]
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def test_install_failure_skips_cache_invalidation(monkeypatch):
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# A failed install left nothing to import, so the finder caches must be left alone.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib
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import importlib.util
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import subprocess as sp
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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def _boom(cmd, **kwargs):
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raise sp.CalledProcessError(returncode = 1, cmd = cmd)
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_stub_subprocess(monkeypatch, _boom)
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invalidated = []
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monkeypatch.setattr(importlib, "invalidate_caches", lambda: invalidated.append(True))
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att._ensure_attention_backend_installed("sage")
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assert invalidated == []
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def test_install_never_attempted_for_builtin_backends(monkeypatch):
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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run = _Recorder()
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_stub_subprocess(monkeypatch, run)
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att._ensure_attention_backend_installed("_native_cudnn")
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att._ensure_attention_backend_installed("native")
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assert run.calls == []
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def test_install_failure_logs_pip_stderr(monkeypatch):
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# A CalledProcessError's str() hides the pip reason; the warning must surface the captured stderr
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# so a fallback to native is diagnosable.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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import subprocess as sp
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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def _boom(cmd, **kwargs):
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raise sp.CalledProcessError(
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returncode = 1, cmd = cmd, stderr = b"ERROR: No matching distribution found"
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)
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_stub_subprocess(monkeypatch, _boom)
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warnings: list[str] = []
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class _Logger:
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def info(self, *a, **k):
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pass
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def warning(self, msg, *args):
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warnings.append(msg % args if args else msg)
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att._ensure_attention_backend_installed("sage", _Logger())
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assert warnings and "No matching distribution found" in warnings[-1]
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def test_install_failure_falls_back_to_native(monkeypatch):
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# pip failing (no wheel for this platform) must not break the load: apply proceeds,
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# set_attention_backend raises on the missing package, and the dispatcher is restored to native.
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monkeypatch.setenv("UNSLOTH_DIFFUSION_ATTENTION_INSTALL", "auto")
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import importlib.util
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import subprocess as sp
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monkeypatch.setattr(importlib.util, "find_spec", lambda name: None)
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def _boom(cmd, **kwargs):
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raise sp.CalledProcessError(returncode = 1, cmd = cmd)
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_stub_subprocess(monkeypatch, _boom)
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monkeypatch.setattr(att, "_active_attention_backend", lambda: "native")
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t = _FakeTransformer(fail = True)
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assert apply_attention_backend(_pipe(t), "sage") is None
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