IQ.Pilot Release Commit @ f2a861c

iqpilot/selfdrive/iqmodeld/tests/__init__.py

@@ -0,0 +1,3 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""

iqpilot/selfdrive/iqmodeld/tests/dmon_lag/repro.cc

@@ -1,5 +1,4 @@
 // Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
-// clang++ -O2 repro.cc && ./a.out
 
 #include <sys/types.h>
 #include <unistd.h>

iqpilot/selfdrive/iqmodeld/tests/test_action_dispatch.py

@@ -1,3 +1,6 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 from types import SimpleNamespace
@@ -5,12 +8,12 @@ from types import SimpleNamespace
 import numpy as np
 import pytest
 
-from cereal import log
+from iqpilot.cereal import log
 
-from openpilot.iqpilot.selfdrive.iqmodeld.config import Plan
-from openpilot.iqpilot.selfdrive.iqmodeld.daemon import NeuralEngineState, _merged_plan
-import openpilot.iqpilot.selfdrive.iqmodeld.daemon as iqmodeld_daemon
-from openpilot.selfdrive.controls.lib.drive_helpers import smooth_value
+from iqpilot.selfdrive.iqmodeld.config import Plan
+from iqpilot.selfdrive.iqmodeld.daemon import NeuralEngineState, _merged_plan
+import iqpilot.selfdrive.iqmodeld.daemon as iqmodeld_daemon
+from iqpilot.selfdrive.controls.lib.drive_helpers import smooth_value
 
 
 def _fake_state(**overrides):

iqpilot/selfdrive/iqmodeld/tests/test_combined_split_runner.py

@@ -1,3 +1,6 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 from dataclasses import dataclass
@@ -5,13 +8,14 @@ from pathlib import Path
 
 import numpy as np
 
-from openpilot.iqpilot.selfdrive.iqmodeld.models.combined_artifact import resolve_combined_split_artifact
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner as runner_helpers
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.combined_split_runner import TinygradCombinedSplitRunner
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import combined_split_runner as combined_runner_mod
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
-from openpilot.iqpilot.selfdrive.iqmodeld.parser import PhaseParser
-from openpilot.iqpilot.selfdrive.iqmodeld.tests.test_iqmodeld_contracts import _phase_sample
+from iqpilot.selfdrive.iqmodeld.models.combined_artifact import resolve_combined_split_artifact
+import iqpilot.selfdrive.iqmodeld.models.runners.model_runner as runner_helpers
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import tinygrad_runner as tinygrad_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.combined_split_runner import TinygradCombinedSplitRunner
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import combined_split_runner as combined_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
+from iqpilot.selfdrive.iqmodeld.parser import PhaseParser
+from iqpilot.selfdrive.iqmodeld.tests.test_iqmodeld_contracts import _phase_sample
 
 
 @dataclass
@@ -77,7 +81,7 @@ def test_resolve_combined_split_artifact_prefers_override(tmp_path: Path, monkey
   expected = tmp_path / "driving_combined_demo.pkl"
   expected.write_bytes(b"iq")
 
-  monkeypatch.setattr("openpilot.iqpilot.selfdrive.iqmodeld.models.combined_artifact._MODEL_ROOT", tmp_path)
+  monkeypatch.setattr("iqpilot.selfdrive.iqmodeld.models.combined_artifact._MODEL_ROOT", tmp_path)
 
   assert resolve_combined_split_artifact(bundle) == expected
 
@@ -89,7 +93,7 @@ def test_get_model_runner_prefers_combined_split_artifact(monkeypatch):
   ], generation=11)
 
   marker = object()
-  monkeypatch.setattr(runner_helpers, "get_active_bundle", lambda: bundle)
+  monkeypatch.setattr(runner_helpers, "_fetch_bundle", lambda: bundle)
   monkeypatch.setattr(runner_helpers, "has_combined_split_artifact", lambda _: True)
   monkeypatch.setattr(combined_runner_mod, "TinygradCombinedSplitRunner", lambda: marker)
 
@@ -103,9 +107,9 @@ def test_get_model_runner_keeps_split_bundle_on_existing_runner_without_combined
   ], generation=12)
 
   marker = object()
-  monkeypatch.setattr(runner_helpers, "get_active_bundle", lambda: bundle)
+  monkeypatch.setattr(runner_helpers, "_fetch_bundle", lambda: bundle)
   monkeypatch.setattr(runner_helpers, "has_combined_split_artifact", lambda _: False)
-  monkeypatch.setattr(runner_helpers, "TinygradSplitRunner", lambda: marker)
+  monkeypatch.setattr(tinygrad_runner_mod, "TinygradSplitRunner", lambda: marker)
 
   assert runner_helpers.get_model_runner() is marker
 

iqpilot/selfdrive/iqmodeld/tests/test_compile_supercombo_guards.py

@@ -1,12 +1,15 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 import numpy as np
 
-from openpilot.iqpilot.selfdrive.iqmodeld.tools.compile_supercombo import (
+from iqpilot.selfdrive.iqmodeld.tools.compile_supercombo import (
   _captured_devices,
-  _captured_queue_depth,
   _validate_pose_outputs,
 )
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.supercombo_runner import _captured_queue_depth
 
 
 class _Captured:

iqpilot/selfdrive/iqmodeld/tests/test_egpu_firmware_mirror.py

@@ -0,0 +1,30 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import hashlib
+import os
+
+from iqpilot.selfdrive.iqmodeld import egpu_helpers as eh
+
+
+def test_fetch_fw_mirrors_and_serves_offline(tmp_path, monkeypatch):
+  from tinygrad import helpers
+  blob = os.urandom(4096)
+  sha = hashlib.sha256(blob).hexdigest()
+  calls = []
+
+  def orig(path, name, sha256):
+    calls.append((path, name))
+    return blob
+
+  monkeypatch.setattr(helpers, "fetch_fw", orig, raising=False)
+  helpers.fetch_fw._iq_patched = False
+  monkeypatch.setattr(eh, "FIRMWARE_MIRROR", str(tmp_path / "mirror"))
+  eh.patch_tinygrad_fetch_fw()
+  assert helpers.fetch_fw("amdgpu", "gc.bin", sha) == blob and calls == [("amdgpu", "gc.bin")]
+  mirrored = tmp_path / "mirror" / "amdgpu" / "gc.bin"
+  assert mirrored.read_bytes() == blob
+  assert helpers.fetch_fw("amdgpu", "gc.bin", sha) == blob and len(calls) == 1
+  mirrored.write_bytes(b"corrupt")
+  assert helpers.fetch_fw("amdgpu", "gc.bin", sha) == blob and len(calls) == 2
+  assert mirrored.read_bytes() == blob

iqpilot/selfdrive/iqmodeld/tests/test_egpu_host_mock.py

@@ -0,0 +1,34 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import os
+import subprocess
+import sys
+
+import pytest
+
+from iqpilot.selfdrive.iqmodeld.tools.egpu_host_mock import tinygrad_tree
+
+PROBE = """
+import os
+os.environ["JIT_BATCH_SIZE"] = "0"
+from iqpilot.selfdrive.iqmodeld.tools.egpu_host_mock import activate
+activate("gfx1200")
+from tinygrad import Tensor
+from tinygrad.device import Device
+from tinygrad.engine.jit import TinyJit
+dev = Device["AMD"]
+assert dev.arch == "gfx1200", dev.arch
+assert type(dev.iface).__name__ == "MOCKUSBIface", type(dev.iface).__name__
+run = TinyJit(lambda x: (x * 2 + 1).sum(axis=1).realize())
+for i in range(3):
+  run(Tensor.ones(64, 64, device="AMD") * i)
+print("MOCK_OK")
+"""
+
+
+@pytest.mark.skipif(not os.path.isdir(os.path.join(tinygrad_tree(), "test", "mockgpu")), reason="tinygrad mockgpu tree not checked out")
+def test_mock_dock_captures_a_jit_without_hardware():
+  out = subprocess.run([sys.executable, "-c", PROBE], capture_output=True, text=True, timeout=600)
+  assert out.returncode == 0, out.stderr[-2000:]
+  assert "MOCK_OK" in out.stdout

iqpilot/selfdrive/iqmodeld/tests/test_egpu_oob.py

@@ -0,0 +1,62 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import os
+import pickle
+
+import numpy as np
+import pytest
+
+os.environ["DEV"] = "CPU"
+
+from iqpilot.selfdrive.iqmodeld.egpu_policy import dump_oob, is_oob, load_bundle
+
+
+def _bundle():
+  from tinygrad import Tensor
+  w = Tensor(np.arange(4096, dtype=np.float32).reshape(64, 64), device="CPU").realize()
+  return {"format": 2, "weights": w, "spec": {"a": ((1, 2), "float32")}, "blob": os.urandom(100_000)}
+
+
+def test_oob_round_trip_matches_plain_pickle(tmp_path):
+  b = _bundle()
+  oob = tmp_path / "b.oob"
+  with open(oob, "wb") as f:
+    dump_oob(b, f)
+  assert is_oob(str(oob))
+  got = load_bundle(str(oob))
+  np.testing.assert_array_equal(got["weights"].numpy(), b["weights"].numpy())
+  assert got["blob"] == b["blob"] and got["spec"] == b["spec"] and got["format"] == 2
+  plain = tmp_path / "b.pkl"
+  with open(plain, "wb") as f:
+    pickle.dump({"x": 1, "blob": b["blob"]}, f, protocol=pickle.HIGHEST_PROTOCOL)
+  assert not is_oob(str(plain))
+  assert load_bundle(str(plain))["blob"] == b["blob"]
+
+
+def test_memory_guard_raises_when_starved(monkeypatch):
+  from iqpilot.selfdrive.iqmodeld import iqegpumodeld as d
+  monkeypatch.setattr(d, "_mem_available_mb", lambda: 90)
+  monkeypatch.setattr(d, "MEMORY_WAIT_S", 0.0)
+  with pytest.raises(RuntimeError, match="insufficient memory"):
+    d._wait_for_memory(350)
+  monkeypatch.setattr(d, "_mem_available_mb", lambda: 900)
+  d._wait_for_memory(350)
+
+
+def test_opcode_rewrite_equals_oob_load(tmp_path):
+  from tinygrad import Tensor
+  from iqpilot.selfdrive.iqmodeld.tools.oob_rewrite import rewrite_oob
+  big = Tensor(np.random.default_rng(0).standard_normal((512, 512)).astype(np.float32), device="CPU").realize()
+  small = Tensor(np.arange(16, dtype=np.float32), device="CPU").realize()
+  b = {"format": 2, "w": big, "s": small, "meta": {"k": "v"}, "raw": os.urandom(200_000)}
+  plain = tmp_path / "plain.pkl"
+  with open(plain, "wb") as f:
+    pickle.dump(b, f, protocol=5)
+  oob = tmp_path / "oob.pkl"
+  moved, _ = rewrite_oob(str(plain), str(oob))
+  assert moved >= 2 and is_oob(str(oob))
+  got = load_bundle(str(oob))
+  np.testing.assert_array_equal(got["w"].numpy(), b["w"].numpy())
+  np.testing.assert_array_equal(got["s"].numpy(), b["s"].numpy())
+  assert got["raw"] == b["raw"] and got["meta"] == {"k": "v"}

iqpilot/selfdrive/iqmodeld/tests/test_egpu_policy.py

@@ -0,0 +1,161 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import os
+
+import numpy as np
+
+os.environ["DEV"] = "CPU"
+
+from iqpilot.selfdrive.iqmodeld.egpu_policy import PolicyRunner, make_run_policy, packed_layout, queue_shapes
+from iqpilot.selfdrive.iqmodeld.temporal_state import TemporalInputState
+
+SPEC = {
+  "img": ((1, 12, 8, 16), "uint8"),
+  "big_img": ((1, 12, 8, 16), "uint8"),
+  "desire_pulse": ((1, 25, 8), "float32"),
+  "traffic_convention": ((1, 2), "float32"),
+  "action_t": ((1, 2), "float32"),
+  "features_buffer": ((1, 24, 512), "float32"),
+}
+FS = 4
+OUT_LEN = 2580
+HIDDEN = slice(1064, 1576)
+
+
+def _pack(inputs):
+  from tinygrad.tensor import Tensor
+  parts = [inputs[k].cast("float32").reshape(-1) for k in ("img", "big_img", "features_buffer", "desire_pulse", "traffic_convention", "action_t")]
+  flat = Tensor.cat(*parts)
+  hidden = (flat[:512] * 0.001).reshape(1, 512)
+  return flat, hidden
+
+
+def _fake_model(inputs):
+  from tinygrad.tensor import Tensor
+  flat, hidden = _pack(inputs)
+  n = flat.shape[0]
+  head = flat[:min(n, HIDDEN.start)]
+  out = Tensor.cat(head.pad((0, HIDDEN.start - head.shape[0])), hidden.reshape(-1), Tensor.zeros(OUT_LEN - HIDDEN.stop, device="CPU"))
+  return {"outputs": out.reshape(1, -1)}
+
+
+class _Reference:
+  def __init__(self):
+    self.state = TemporalInputState(FS, SPEC)
+
+  def run(self, warped, desire, traffic, action_t):
+    inputs = self.state.push_and_materialize(warped, desire, traffic, action_t)
+    from tinygrad.tensor import Tensor
+    t = {k: Tensor(np.ascontiguousarray(v), device="CPU") for k, v in inputs.items()}
+    out = _fake_model(t)["outputs"].numpy().reshape(-1)
+    self.state.note_hidden_state(out, HIDDEN)
+    return out
+
+
+def test_policy_queues_match_temporal_state():
+  from tinygrad.engine.jit import TinyJit
+  jit = TinyJit(make_run_policy(_fake_model, SPEC, FS, "CPU"), prune=True)
+  runner = PolicyRunner(jit, SPEC, FS, HIDDEN, "CPU")
+  ref = _Reference()
+  rng = np.random.default_rng(3)
+  desire = np.zeros(8, dtype=np.float32)
+  for i in range(14):
+    warped = rng.integers(0, 256, (2, 6, 8, 16), dtype=np.int64).astype(np.uint8)
+    if i in (2, 3, 9):
+      desire[:] = 0
+      desire[1 + (i % 3)] = 1
+    elif i == 5:
+      desire[:] = 0
+    traffic = np.array([1.0, 0.0], dtype=np.float32) if i % 2 else np.array([0.0, 1.0], dtype=np.float32)
+    action_t = np.array([0.1 * i, 0.2], dtype=np.float32)
+    got = runner.run(warped, desire, traffic, action_t)
+    want = ref.run(warped, desire, traffic, action_t)
+    np.testing.assert_array_equal(got, want, err_msg=f"frame {i}")
+
+
+def test_layouts():
+  shapes, sizes = packed_layout(SPEC)
+  assert list(shapes) == ["desire", "traffic_convention", "action_t", "prev_feat"]
+  assert sum(sizes) == 8 + 2 + 2 + 512
+  q = queue_shapes(SPEC, FS)
+  assert q["img_q"][0] == (5, 6, 8, 16) and q["feat_q"][0] == (96, 1, 512) and q["desire_q"][0] == (100, 1, 8)
+
+
+CAM = (64, 48)
+
+
+def _nv12(cam_w, cam_h):
+  from iqpilot.system.camerad.cameras.nv12_info import get_nv12_info
+  stride, y_height, uv_height, _ = get_nv12_info(cam_w, cam_h)
+  return (cam_w, cam_h, stride, y_height, uv_height)
+
+
+def _numpy_warp_plane(src, m, w_dst, h_dst):
+  h_src, w_src = src.shape
+  x = np.tile(np.arange(w_dst, dtype=np.float32), h_dst)
+  y = np.repeat(np.arange(h_dst, dtype=np.float32), w_dst)
+  sx = (m[0, 0] * x + m[0, 1] * y + m[0, 2]) / (m[2, 0] * x + m[2, 1] * y + m[2, 2])
+  sy = (m[1, 0] * x + m[1, 1] * y + m[1, 2]) / (m[2, 0] * x + m[2, 1] * y + m[2, 2])
+  xi = np.clip(np.round(sx), 0, w_src - 1).astype(np.int64)
+  yi = np.clip(np.round(sy), 0, h_src - 1).astype(np.int64)
+  return src[yi, xi].reshape(h_dst, w_dst)
+
+
+def _numpy_frame_prepare(frame, m, nv12, model_w, model_h):
+  cam_w, cam_h, stride, y_height, uv_height = nv12
+  m = m.astype(np.float32)
+  y_src = frame[:cam_h * stride].reshape(cam_h, stride)
+  uv = frame[stride * y_height:stride * y_height + uv_height * stride].reshape(uv_height, stride)
+  m_uv = m * np.array([[1.0, 1.0, 0.5], [1.0, 1.0, 0.5], [2.0, 2.0, 1.0]], dtype=np.float32)
+  y = _numpy_warp_plane(y_src, m, model_w, model_h)
+  u = _numpy_warp_plane(uv[:cam_h // 2, :cam_w:2], m_uv, model_w // 2, model_h // 2)
+  v = _numpy_warp_plane(uv[:cam_h // 2, 1:cam_w:2], m_uv, model_w // 2, model_h // 2)
+  f = np.concatenate([y.ravel(), u.ravel(), v.ravel()]).reshape(model_h * 3 // 2, model_w)
+  H, W = model_h, model_w
+  return np.stack([f[0:H:2, 0::2], f[1:H:2, 0::2], f[0:H:2, 1::2], f[1:H:2, 1::2],
+                   f[H:H + H // 4].reshape(H // 2, W // 2), f[H + H // 4:H + H // 2].reshape(H // 2, W // 2)])
+
+
+def _jittered_scale(rng, cam, model_w, model_h):
+  m = np.array([[cam[0] / model_w, 0.0, 0.0], [0.0, cam[1] / model_h, 0.0], [0.0, 0.0, 1.0]], dtype=np.float32)
+  m += (0.05 * rng.standard_normal((3, 3))).astype(np.float32) * np.array([[1, 1, 1], [1, 1, 1], [0.01, 0.01, 0.1]], dtype=np.float32)
+  return m
+
+
+def test_frame_layout():
+  from iqpilot.selfdrive.iqmodeld.egpu_policy import frame_layout, model_size, nv12_copy_size
+  shapes, sizes, npy_bytes = frame_layout(SPEC)
+  assert list(shapes) == ["tfm", "big_tfm", "desire", "traffic_convention", "action_t", "prev_feat"]
+  assert npy_bytes == (18 + 8 + 2 + 2 + 512) * 4
+  assert model_size(SPEC) == (32, 16)
+  assert nv12_copy_size(128, 64, 32) == 128 * 96
+
+
+def test_model_runner_matches_device_warp():
+  from tinygrad.engine.jit import TinyJit
+
+  from iqpilot.selfdrive.iqmodeld.egpu_policy import ModelRunner, make_run_model, make_warp, model_size, nv12_copy_size
+  nv12 = _nv12(*CAM)
+  fcs = nv12_copy_size(nv12[2], nv12[3], nv12[4])
+  model_w, model_h = model_size(SPEC)
+  run_policy = make_run_policy(_fake_model, SPEC, FS, "CPU")
+  jit = TinyJit(make_run_model(make_warp(nv12, model_w, model_h, "CPU"), run_policy, SPEC, fcs, "CPU"), prune=True)
+  runner = ModelRunner(jit, SPEC, FS, HIDDEN, "CPU", fcs)
+  ref = PolicyRunner(TinyJit(make_run_policy(_fake_model, SPEC, FS, "CPU"), prune=True), SPEC, FS, HIDDEN, "CPU")
+  rng = np.random.default_rng(7)
+  desire = np.zeros(8, dtype=np.float32)
+  for i in range(10):
+    main = rng.integers(0, 256, fcs, dtype=np.int64).astype(np.uint8)
+    extra = rng.integers(0, 256, fcs, dtype=np.int64).astype(np.uint8)
+    tfm = _jittered_scale(rng, CAM, model_w, model_h)
+    big_tfm = _jittered_scale(rng, CAM, model_w, model_h)
+    if i in (2, 6):
+      desire[:] = 0
+      desire[1 + i % 3] = 1
+    traffic = np.array([1.0, 0.0], dtype=np.float32) if i % 2 else np.array([0.0, 1.0], dtype=np.float32)
+    action_t = np.array([0.1 * i, 0.2], dtype=np.float32)
+    got = runner.run(main, extra, tfm, big_tfm, desire, traffic, action_t)
+    warped = np.stack([_numpy_frame_prepare(main, tfm, nv12, model_w, model_h), _numpy_frame_prepare(extra, big_tfm, nv12, model_w, model_h)])
+    want = ref.run(warped, desire, traffic, action_t)
+    np.testing.assert_array_equal(got, want, err_msg=f"frame {i}")

iqpilot/selfdrive/iqmodeld/tests/test_egpu_stock_parity.py

@@ -0,0 +1,163 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import types
+
+import pytest
+
+from iqpilot.cereal import log, messaging
+from iqpilot.cereal.services import SERVICE_LIST
+
+
+class TestTelemetryContract:
+  def test_service_is_published_at_stock_cadence(self):
+    assert "egpuDockState" in SERVICE_LIST
+    assert SERVICE_LIST["egpuDockState"].frequency == 10.
+
+  def test_message_carries_every_stock_field(self):
+    msg = messaging.new_message("egpuDockState")
+    state = msg.egpuDockState
+    for field in ("tempC", "memoryTempC", "powerDrawW", "powerLimitW", "gpuUsagePercent",
+                  "gpuClockMhz", "fanSpeedRpm", "pcieLtssm", "supplyVoltage", "supplyCurrent"):
+      setattr(state, field, 1)
+      assert getattr(state, field) == 1
+
+  def test_metrics_refresh_matches_stock(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_telemetry import METRICS_REFRESH_EVERY
+    assert METRICS_REFRESH_EVERY == 100
+
+  def test_send_without_a_gpu_publishes_an_invalid_message(self):
+    from iqpilot.selfdrive.iqmodeld import egpu_telemetry
+    sent = []
+    telemetry = egpu_telemetry.EgpuDockTelemetry(types.SimpleNamespace(send=lambda n, m: sent.append((n, m))), big=True)
+    telemetry._device = lambda: types.SimpleNamespace(_opened_devices=set())
+    telemetry.send()
+    assert sent and sent[0][0] == "egpuDockState"
+    assert sent[0][1].valid is False
+
+
+class TestBigFrameFlag:
+  def test_model_message_carries_the_big_flag(self):
+    msg = messaging.new_message("modelV2")
+    msg.modelV2.big = True
+    assert msg.modelV2.big
+
+
+class TestStatusParams:
+  def test_loading_param_exists_and_is_cleared_like_stock(self):
+    from pathlib import Path
+    root = Path(__file__).resolve().parents[3]
+    keys = (root / "common" / "params_keys.h").read_text()
+    assert '{"UsbGpuLoading"' in keys
+    line = next(ln for ln in keys.splitlines() if '"UsbGpuLoading"' in ln)
+    for flag in ("CLEAR_ON_MANAGER_START", "CLEAR_ON_OFFROAD_TRANSITION", "CLEAR_ON_IGNITION_ON"):
+      assert flag in line
+
+
+class TestAlerts:
+  def test_both_stock_big_model_events_exist(self):
+    assert hasattr(log.OnroadEvent.EventName, "bigModelLoading")
+    assert hasattr(log.OnroadEvent.EventName, "bigModelFailed")
+
+  def test_alerts_are_wired_with_stock_severities(self):
+    from iqpilot.selfdrive.selfdrived.events import EVENTS, ET
+    EventName = log.OnroadEvent.EventName
+    loading = EVENTS[EventName.bigModelLoading]
+    failed = EVENTS[EventName.bigModelFailed]
+    assert ET.NO_ENTRY in loading
+    assert ET.SOFT_DISABLE in failed and ET.PERMANENT in failed
+
+
+class TestFirmwareGate:
+  def test_runtime_refuses_a_dock_on_other_firmware(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import usbgpu_present
+    from iqpilot.system.hardware.usb import EGPU_DOCK_FW_PRODUCT, EGPU_DOCK_USB_IDS
+    vid, pid = EGPU_DOCK_USB_IDS[0]
+    d = tmp_path / "1-1"
+    d.mkdir()
+    (d / "idVendor").write_text(f"{vid:04x}\n")
+    (d / "idProduct").write_text(f"{pid:04x}\n")
+    (d / "product").write_text("custom deadbeef-CLEAN\n")
+    assert not usbgpu_present(str(tmp_path))
+    (d / "product").write_text(EGPU_DOCK_FW_PRODUCT + "\n")
+    assert usbgpu_present(str(tmp_path))
+
+
+class TestAutoFlash:
+  def test_hardwared_drives_the_flasher_offroad_only(self):
+    from iqpilot.system.hardware.hardwared import EgpuDockFlasher
+    f = EgpuDockFlasher()
+    calls = []
+    f.flash = lambda: calls.append(1)
+    stale = [{"vendorId": 0xADD1, "productId": 0x0001, "product": "custom deadbeef-CLEAN"}]
+    f.update(False, stale)
+    assert f.attempts == 0, "must not flash onroad"
+    f.update(True, stale)
+    assert f.attempts == 1
+    if f.thread is not None:
+      f.thread.join(timeout=5)
+
+  def test_matching_firmware_is_never_flashed(self):
+    from iqpilot.system.hardware.egpu_dock.flash import bundled_version
+    from iqpilot.system.hardware.hardwared import EgpuDockFlasher
+    f = EgpuDockFlasher()
+    f.flash = lambda: pytest.fail("flashed a dock that already matches")
+    f.update(True, [{"vendorId": 0xADD1, "productId": 0x0001, "product": bundled_version()}])
+    assert f.attempts == 0
+
+  def test_attempts_are_bounded_like_stock(self):
+    from iqpilot.system.hardware.hardwared import EgpuDockFlasher
+    assert EgpuDockFlasher.MAX_ATTEMPTS == 3
+    assert EgpuDockFlasher.RETRY_INTERVAL == 20.
+
+
+class TestDockIsItsOwnConsent:
+
+  def _params(self, **flags):
+    class P:
+      def get_bool(self, k):
+        return bool(flags.get(k, False))
+      def get(self, k, *a, **kw):
+        return None
+    return P()
+
+  def _sysfs_with_dock(self, tmp_path, product=None):
+    from iqpilot.system.hardware.usb import EGPU_DOCK_FW_PRODUCT, EGPU_DOCK_USB_IDS
+    vid, pid = EGPU_DOCK_USB_IDS[0]
+    d = tmp_path / "1-1"
+    d.mkdir()
+    (d / "idVendor").write_text(f"{vid:04x}\n")
+    (d / "idProduct").write_text(f"{pid:04x}\n")
+    (d / "product").write_text((product or EGPU_DOCK_FW_PRODUCT) + "\n")
+    return str(tmp_path)
+
+  def test_a_plugged_in_dock_selects_itself(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected
+    assert egpu_selected(self._params(), self._sysfs_with_dock(tmp_path))
+
+  def test_nothing_plugged_in_selects_nothing(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected
+    assert not egpu_selected(self._params(), str(tmp_path))
+
+  def test_a_dock_on_foreign_firmware_does_not_select_itself(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected
+    assert not egpu_selected(self._params(), self._sysfs_with_dock(tmp_path, "custom deadbeef-CLEAN"))
+
+  def test_the_user_can_force_it_off(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected
+    root = self._sysfs_with_dock(tmp_path)
+    assert not egpu_selected(self._params(IQEgpuDisabled=True), root)
+
+  def test_the_param_can_force_it_on_without_hardware(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected
+    assert egpu_selected(self._params(IQEgpuEnabled=True), str(tmp_path))
+
+  def test_present_dock_wins_even_with_emac_enabled(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected, resolve_backend, usbgpu_present
+    root = self._sysfs_with_dock(tmp_path)
+    assert resolve_backend(True, egpu_selected(self._params(), root), usbgpu_present(root)) == "egpu"
+
+  def test_force_param_without_hardware_yields_to_emac(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.egpu_helpers import egpu_selected, resolve_backend, usbgpu_present
+    assert resolve_backend(True, egpu_selected(self._params(IQEgpuEnabled=True), str(tmp_path)),
+                           usbgpu_present(str(tmp_path))) == "emac"

iqpilot/selfdrive/iqmodeld/tests/test_egpu_worker.py

@@ -0,0 +1,509 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+from __future__ import annotations
+
+import io
+import json
+import time
+import urllib.request
+
+import numpy as np
+import pytest
+
+from iqpilot.selfdrive.iqmodeld.egpu_helpers import (
+  resolve_backend, resolve_download_url, usbgpu_present,
+)
+from iqpilot.selfdrive.iqmodeld.egpu_pipeline import (
+  EgpuPipeline, EgpuPipelineError, make_big_channel_payload,
+)
+from iqpilot.selfdrive.iqmodeld.egpu_model import EGPU_MODELS, get_egpu_model
+from iqpilot.selfdrive.iqmodeld.temporal_state import MODEL_INPUT_SPEC as INPUT_SPEC
+
+
+class FakeParams:
+  def __init__(self, **flags):
+    self._flags = {k: bool(v) for k, v in flags.items()}
+
+  def get_bool(self, key: str) -> bool:
+    return self._flags.get(key, False)
+
+
+def _fake_usb_device(root, vid: str, pid: str, name: str = "1-1", product: str | None = None):
+  from iqpilot.system.hardware.usb import EGPU_DOCK_FW_PRODUCT
+  d = root / name
+  d.mkdir()
+  (d / "idVendor").write_text(vid + "\n")
+  (d / "idProduct").write_text(pid + "\n")
+  (d / "product").write_text((product if product is not None else EGPU_DOCK_FW_PRODUCT) + "\n")
+
+
+class TestPresence:
+  def test_present(self, tmp_path):
+    _fake_usb_device(tmp_path, "add1", "0001")
+    assert usbgpu_present(str(tmp_path))
+
+  def test_foreign_firmware_absent(self, tmp_path):
+    _fake_usb_device(tmp_path, "add1", "0001", product="custom deadbeef-CLEAN")
+    assert not usbgpu_present(str(tmp_path))
+
+  def test_wrong_ids_absent(self, tmp_path):
+    _fake_usb_device(tmp_path, "05ac", "12a8")
+    assert not usbgpu_present(str(tmp_path))
+
+  def test_empty_bus_absent(self, tmp_path):
+    assert not usbgpu_present(str(tmp_path))
+
+  def test_unreadable_entries_skipped(self, tmp_path):
+    (tmp_path / "usb1").mkdir()
+    _fake_usb_device(tmp_path, "add1", "0001", name="1-2")
+    assert usbgpu_present(str(tmp_path))
+
+
+class TestBackendResolution:
+  def test_none(self):
+    assert resolve_backend(False, False) is None
+
+  def test_emac_only(self):
+    assert resolve_backend(True, False) == "emac"
+
+  def test_egpu_only(self):
+    assert resolve_backend(False, True) == "egpu"
+
+  def test_force_param_yields_to_emac_without_hardware(self):
+    assert resolve_backend(True, True) == "emac"
+
+  def test_present_dock_wins_over_emac(self):
+    assert resolve_backend(True, True, True) == "egpu"
+
+
+class TestManagerGating:
+  @pytest.fixture
+  def pc(self):
+    return pytest.importorskip("iqpilot.system.manager.process_config")
+
+  def test_egpu_needs_presence(self, pc, monkeypatch):
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: True)
+    assert pc.egpu_enabled(True, FakeParams(IQEgpuEnabled=True), None)
+    assert pc.egpu_enabled(True, FakeParams(), None)
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: False)
+    assert not pc.egpu_enabled(True, FakeParams(IQEgpuEnabled=True), None)
+    assert not pc.egpu_enabled(True, FakeParams(), None)
+
+  def test_present_dock_wins_over_left_on_emac(self, pc, monkeypatch):
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: True)
+    both = FakeParams(IQEmacEnabled=True, IQEgpuEnabled=True)
+    assert not pc.emac_enabled(True, both, None)
+    assert pc.egpu_enabled(True, both, None)
+
+  def test_emac_runs_when_no_dock(self, pc, monkeypatch):
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: False)
+    assert pc.emac_enabled(True, FakeParams(IQEmacEnabled=True), None)
+
+  def test_disabled_dock_yields_to_emac(self, pc, monkeypatch):
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: True)
+    both = FakeParams(IQEmacEnabled=True, IQEgpuDisabled=True)
+    assert pc.emac_enabled(True, both, None)
+    assert not pc.egpu_enabled(True, both, None)
+
+  def test_disabled_dock_runs_no_backend_when_no_emac(self, pc, monkeypatch):
+    monkeypatch.setattr(pc, "usbgpu_present", lambda: True)
+    off = FakeParams(IQEgpuDisabled=True)
+    assert not pc.egpu_enabled(True, off, None)
+    assert not pc.emac_enabled(True, off, None)
+
+  def test_selector_runs_for_either_backend(self, pc):
+    assert pc.big_model_enabled(True, FakeParams(IQEmacEnabled=True), None)
+    assert pc.big_model_enabled(True, FakeParams(IQEgpuEnabled=True), None)
+    assert not pc.big_model_enabled(True, FakeParams(), None)
+
+  def test_iqegpumodeld_registered(self, pc):
+    assert "iqegpumodeld" in pc.managed_processes
+    assert "maciqmodeld" in pc.managed_processes
+
+
+class TestDownloadResolve:
+  def test_direct_url_passthrough(self):
+    assert resolve_download_url("https://x/y.onnx", "0" * 64, 5) == "https://x/y.onnx"
+
+  def test_commalfs_batch(self, monkeypatch):
+    seen = {}
+
+    def fake_urlopen(req, timeout=0):
+      seen["url"] = req.full_url
+      seen["body"] = json.loads(req.data)
+      return io.BytesIO(json.dumps(
+        {"objects": [{"actions": {"download": {"href": "https://signed/url"}}}]}).encode())
+
+    monkeypatch.setattr(urllib.request, "urlopen", fake_urlopen)
+    sha = "a5" * 32
+    url = resolve_download_url(f"commalfs:{sha}", sha, 1234)
+    assert url == "https://signed/url"
+    assert seen["body"]["objects"] == [{"oid": sha, "size": 1234}]
+    assert seen["url"].endswith("/info/lfs/objects/batch")
+
+
+def _zero_infer(output_len: int, fill=None):
+  calls = []
+
+  def infer(inputs):
+    for name, (shape, dtype) in INPUT_SPEC.items():
+      assert tuple(inputs[name].shape) == shape, name
+      assert inputs[name].dtype == np.dtype(dtype), name
+    calls.append({k: v.copy() for k, v in inputs.items()})
+    out = np.zeros(output_len, dtype=np.float32)
+    if fill is not None:
+      out[:] = fill
+    return out
+
+  infer.calls = calls
+  return infer
+
+
+def _frame_inputs(seed=0):
+  rng = np.random.default_rng(seed)
+  warped = rng.integers(0, 256, (2, 6, 128, 256)).astype(np.uint8)
+  desire = np.zeros(8, dtype=np.float32)
+  traffic = np.array([1.0, 0.0], dtype=np.float32)
+  action_t = np.array([0.25, 0.55], dtype=np.float32)
+  return warped, desire, traffic, action_t
+
+
+class TestEgpuPipeline:
+  def setup_method(self):
+    self.meta = get_egpu_model()
+
+  def test_split_model_rejected(self):
+    split_meta = {**get_egpu_model(), "key": "some_split", "split": True}
+    with pytest.raises(EgpuPipelineError, match="split"):
+      EgpuPipeline(split_meta, _zero_infer(split_meta["output_len"]))
+
+  def test_registry_is_fused_only(self):
+    assert not any(m.get("split") for m in EGPU_MODELS.values())
+
+  def test_run_shapes_and_output(self):
+    infer = _zero_infer(self.meta["output_len"])
+    pipe = EgpuPipeline(self.meta, infer)
+    out = pipe.run(*_frame_inputs())
+    assert out.shape == (self.meta["output_len"],)
+    assert len(infer.calls) == 1
+
+  def test_hidden_state_feeds_next_features_buffer(self):
+    output_len = self.meta["output_len"]
+    hidden = self.meta["output_slices"]["hidden_state"]
+
+    def infer(inputs):
+      out = np.zeros(output_len, dtype=np.float32)
+      out[hidden] = np.arange(hidden.stop - hidden.start, dtype=np.float32)
+      return out
+
+    pipe = EgpuPipeline(self.meta, infer)
+    pipe.run(*_frame_inputs(1))
+    np.testing.assert_array_equal(
+      pipe.state.prev_feat.reshape(-1), np.arange(hidden.stop - hidden.start, dtype=np.float32))
+    pipe.run(*_frame_inputs(2))
+    np.testing.assert_array_equal(
+      pipe.state.feat_q[-1].reshape(-1), np.arange(hidden.stop - hidden.start, dtype=np.float32))
+
+  def test_desire_rising_edge_pulse(self):
+    infer = _zero_infer(self.meta["output_len"])
+    pipe = EgpuPipeline(self.meta, infer)
+    warped, _, traffic, action_t = _frame_inputs()
+    desire_on = np.zeros(8, dtype=np.float32)
+    desire_on[3] = 1.0
+    pipe.run(warped, desire_on, traffic, action_t)
+    assert infer.calls[-1]["desire_pulse"][0, -1, 3] == 1.0
+    for _ in range(5):
+      pipe.run(warped, desire_on, traffic, action_t)
+    assert infer.calls[-1]["desire_pulse"][0, :, 3].sum() == 1.0
+
+  def test_wrong_output_len_raises(self):
+    pipe = EgpuPipeline(self.meta, _zero_infer(self.meta["output_len"] - 1))
+    with pytest.raises(EgpuPipelineError, match="length"):
+      pipe.run(*_frame_inputs())
+
+  def test_non_finite_output_raises(self):
+    pipe = EgpuPipeline(self.meta, _zero_infer(self.meta["output_len"], fill=np.nan))
+    with pytest.raises(EgpuPipelineError, match="finite"):
+      pipe.run(*_frame_inputs())
+
+
+class TestChannelContract:
+  def _real_msgs(self):
+    import iqpilot.cereal.messaging as messaging
+    msgs = {}
+    for svc in ("modelV2", "drivingModelData", "cameraOdometry", "iqDriveModelData"):
+      m = messaging.new_message(svc)
+      msgs[svc] = m.to_bytes()
+    return msgs
+
+  def test_payload_keys_match_selector_contract(self):
+    payload = make_big_channel_payload(7, True, 0.031, 24.0, {"modelV2": b"x"})
+    assert payload["source"] == "egpu_big"
+    for key in ("frame_id", "live_calib_seen", "model_execution_time", "msgs"):
+      assert key in payload
+
+  def test_selector_consumes_egpu_payload(self, tmp_path):
+    from iqpilot.selfdrive.iqmodeld.model_channel import ModelChannel
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import wait_for_big
+
+    chan = ModelChannel(str(tmp_path / "big"), create=True)
+    payload = make_big_channel_payload(100, True, 0.03, 25.0, self._real_msgs())
+    chan.write(100, payload)
+
+    got, peek = wait_for_big(chan, 100, time.perf_counter() + 0.01)
+    assert peek == 100
+    assert got is not None
+    assert got["source"] == "egpu_big"
+    assert got["frame_id"] == 100
+
+  def test_selector_patch_and_send_parses_egpu_msgs(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import _patch_and_send
+
+    sent = {}
+
+    class PM:
+      def send(self, service, msg):
+        sent[service] = msg
+
+    payload = make_big_channel_payload(42, True, 0.03, 25.0, self._real_msgs())
+    _patch_and_send(PM(), payload, frame_drop_perc=0.0, selector_dropped=0, target=42, source_lag=0)
+    assert set(sent) == {"modelV2", "drivingModelData", "cameraOdometry", "iqDriveModelData"}
+    assert sent["modelV2"].modelV2.frameDropPerc == 0.0
+    assert sent["cameraOdometry"].valid
+
+  def test_selector_lag_patches_frame_id(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import _patch_and_send
+
+    sent = {}
+
+    class PM:
+      def send(self, service, msg):
+        sent[service] = msg
+
+    payload = make_big_channel_payload(40, True, 0.03, 25.0, self._real_msgs())
+    _patch_and_send(PM(), payload, frame_drop_perc=0.0, selector_dropped=0, target=42, source_lag=2)
+    assert sent["modelV2"].modelV2.frameId == 42
+    assert not sent["cameraOdometry"].valid
+
+
+def _import_worker():
+  try:
+    import iqpilot.selfdrive.iqmodeld.iqegpumodeld as w
+    return w
+  except ImportError as e:
+    if any(tag in str(e) for tag in ("pyx", "visionipc", "proprietary_runtime")):
+      pytest.skip(f"device-only import chain unavailable on this host: {e}")
+    raise
+
+
+class TestWorkerModule:
+  def test_module_imports_off_device(self):
+    w = _import_worker()
+    assert w.PROCESS_NAME.endswith("iqegpumodeld")
+    assert callable(w.main)
+
+  def test_warmup_validates_output(self):
+    w = _import_worker()
+    spec = {name: (shape, dtype) for name, (shape, dtype) in INPUT_SPEC.items()}
+    def good(inputs):
+      return np.zeros(10, dtype=np.float32)
+    assert w._warmup(good, spec, 10) >= 0.0
+    with pytest.raises(RuntimeError, match="invalid"):
+      w._warmup(good, spec, 11)
+
+
+class TestSelectorBackendKeys:
+  def test_emac_default(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import EMAC_STATUS_KEYS, backend_status_keys
+    assert backend_status_keys(False, False) is EMAC_STATUS_KEYS
+    assert backend_status_keys(True, False) is EMAC_STATUS_KEYS
+
+  def test_egpu_selected(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import EGPU_STATUS_KEYS, backend_status_keys
+    assert backend_status_keys(False, True) is EGPU_STATUS_KEYS
+    assert backend_status_keys(False, True)["active"] == "UsbGpuActive"
+    assert backend_status_keys(False, True)["failed"] == "UsbGpuFailed"
+
+  def test_emac_wins_when_both(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import EMAC_STATUS_KEYS, backend_status_keys
+    assert backend_status_keys(True, True) is EMAC_STATUS_KEYS
+
+  def test_key_maps_cover_same_roles(self):
+    from iqpilot.selfdrive.iqmodeld.modeld_selector import EGPU_STATUS_KEYS, EMAC_STATUS_KEYS
+    assert set(EGPU_STATUS_KEYS) == set(EMAC_STATUS_KEYS)
+
+
+class TestBackendSeparation:
+  EGPU_SOURCES = (
+    "egpu_helpers.py", "egpu_pipeline.py", "egpu_model.py", "iqegpumodeld.py",
+    "big_catalog.py", "tools/compile_egpu_model.py",
+  )
+  BANNED_IMPORTS = ("emac_input_state", "emac_model_meta", "maciqmodeld", "mac_protocol", "mac_client")
+
+  def _sources(self):
+    import pathlib
+    root = pathlib.Path(__file__).resolve().parents[1]
+    return {name: (root / name).read_text() for name in self.EGPU_SOURCES}
+
+  def test_no_emac_module_imports(self):
+    for name, src in self._sources().items():
+      for banned in self.BANNED_IMPORTS:
+        assert f"import {banned}" not in src and f"iqmodeld.{banned}" not in src, f"{name} imports {banned}"
+
+  def test_no_macmodel_params(self):
+    for name, src in self._sources().items():
+      assert "MacModel" not in src, f"{name} references MacModel* params"
+
+  def test_emac_shim_reexports_temporal_state(self):
+    from iqpilot.selfdrive.iqmodeld import emac_input_state, temporal_state
+    assert emac_input_state.EmacInputState is temporal_state.TemporalInputState
+    assert emac_input_state.SplitInputState is temporal_state.SplitTemporalState
+
+  def test_emac_modules_are_not_in_the_public_tree(self):
+    import pathlib
+    root = pathlib.Path(__file__).resolve().parents[1]
+    for gone in ("mac_protocol.py", "mac_client.py", "maciqmodeld.py", "bulk_transport.py"):
+      assert not (root / gone).exists(), f"{gone} must live only in konn3kt_private"
+
+
+class TestMetaDrivenInputSpec:
+
+  def _run_one(self, meta):
+    seen = {}
+    def infer(inputs):
+      seen.update({k: v.shape for k, v in inputs.items()})
+      return np.zeros(meta["output_len"], dtype=np.float32)
+    pipe = EgpuPipeline(meta, infer)
+    pipe.run(np.zeros((2, 6, 128, 256), np.uint8), np.zeros(8, np.float32),
+             np.array([1, 0], np.float32), np.zeros(2, np.float32))
+    return seen
+
+  def test_default_contract_unchanged(self):
+    meta = get_egpu_model()
+    seen = self._run_one(meta)
+    assert seen["features_buffer"] == (1, 24, 512)
+    assert seen["desire_pulse"] == (1, 25, 8)
+
+  def test_registry_shapes_drive_the_state(self):
+    meta = dict(get_egpu_model())
+    meta["output_len"] = 18452
+    meta["output_slices"] = dict(meta["output_slices"], hidden_state=slice(2066, 18450))
+    meta["input_shapes"] = {
+      "img": (1, 12, 128, 256), "big_img": (1, 12, 128, 256),
+      "desire_pulse": (1, 33, 8), "traffic_convention": (1, 2),
+      "action_t": (1, 2), "features_buffer": (1, 32, 32, 512),
+    }
+    seen = self._run_one(meta)
+    assert seen["features_buffer"] == (1, 32, 32, 512)
+    assert seen["desire_pulse"] == (1, 33, 8)
+
+
+class TestCatalogResolution:
+
+  def _params(self, model, doc=None):
+    class P:
+      def get(self, k):
+        if k == "IQEmacModel":
+          return model
+        if k == "IQEmacCatalogCache":
+          return json.dumps(doc) if doc else None
+        return None
+    return P()
+
+  def _doc(self):
+    return {"schema": 1, "bundles": [{
+      "short_name": "ttx", "display_name": "TTx", "index": 1,
+      "model_name": "big_driving_supercombo",
+      "wire": {"output_len": 2580, "frame_skip": 4, "pipeline": True,
+               "output_slices": {"plan": [917, 1907], "hidden_state": [2066, 2578], "pad": [-2, None]},
+               "input_shapes": {"img": [1, 12, 128, 256], "big_img": [1, 12, 128, 256],
+                                "desire_pulse": [1, 33, 8], "traffic_convention": [1, 2],
+                                "action_t": [1, 2], "features_buffer": [1, 32, 512]},
+               "lat_smooth_seconds": 0.1},
+      "source": {"kind": "comma_lfs", "sha256": "c" * 64, "size": 1},
+    }]}
+
+  def test_unset_selection_is_the_builtin_default(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_model import resolve_egpu_model
+    m = resolve_egpu_model(self._params(None))
+    assert m["key"] == "lebrowski" and m["sha256"].startswith("a501760a")
+
+  def test_catalog_selection_resolves_with_shapes_and_smoothing(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_model import resolve_egpu_model
+    m = resolve_egpu_model(self._params("ttx", self._doc()))
+    assert m["key"] == "ttx"
+    assert m["input_shapes"]["features_buffer"] == (1, 32, 512)
+    assert m["input_shapes"]["desire_pulse"] == (1, 33, 8)
+    assert m["lat_smooth_seconds"] == 0.1
+    assert m["output_slices"]["pad"] == slice(-2, None)
+
+  def test_unknown_selection_is_a_park_not_a_silent_default(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_model import resolve_egpu_model
+    assert resolve_egpu_model(self._params("ghost", self._doc()), allow_refresh=False) is None
+
+  def test_bench_model_is_not_selectable(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_model import resolve_egpu_model
+    assert resolve_egpu_model(self._params("comma_small", self._doc()), allow_refresh=False) is None
+
+  def test_registry_carries_no_model_list(self):
+    from iqpilot.selfdrive.iqmodeld.egpu_model import EGPU_MODELS
+    assert set(EGPU_MODELS) == {"lebrowski", "comma_small"}
+
+
+class TestConsentAndIntegrity:
+  def test_disabled_param_denies_present_dock(self, monkeypatch):
+    from iqpilot.selfdrive.iqmodeld import egpu_helpers
+    monkeypatch.setattr(egpu_helpers, "usbgpu_present", lambda sysfs_root=egpu_helpers.USB_SYSFS_ROOT: True)
+    assert egpu_helpers.egpu_present_consented(FakeParams()) is True
+    assert egpu_helpers.egpu_present_consented(FakeParams(IQEgpuDisabled=True)) is False
+
+  def test_local_onnx_quarantines_bad_content(self, tmp_path, monkeypatch):
+    import hashlib
+    from iqpilot.selfdrive.iqmodeld import egpu_helpers
+    onnx = tmp_path / "m.onnx"
+    onnx.write_bytes(b"good")
+    meta = {"sha256": hashlib.sha256(b"good").hexdigest(), "download": {"size": 4}}
+    monkeypatch.setattr(egpu_helpers, "onnx_cache_path", lambda m: str(onnx))
+    assert egpu_helpers.local_onnx(meta) == str(onnx)
+    onnx.write_bytes(b"bad!")
+    assert egpu_helpers.local_onnx(meta) is None
+    assert not onnx.exists()
+    assert (tmp_path / "m.onnx.unusable").exists()
+
+
+class TestEgpuDockStatus:
+  def _run(self, seq):
+    from iqpilot.system.hardware.egpu_dock.status import EgpuDockStatus
+    st = EgpuDockStatus()
+    fired = {}
+    def set_alert(name, cond, extra=None):
+      fired[name] = (bool(cond), extra)
+    for args in seq:
+      st.update(*args, set_alert)
+    return {k: v for k, v in fired.items() if v[0]}
+
+  def _dock(self, speed=10000, product="custom ed4e39b7-CLEAN"):
+    return [{"vendorId": 0xADD1, "productId": 0x0001, "product": product, "speedMbps": speed}]
+
+  def test_no_dock_no_alerts(self):
+    assert self._run([(True, [], False, False, None, True, None)]) == {}
+
+  def test_usb2_dock_warns_slow(self):
+    fired = self._run([(True, self._dock(speed=480), False, False, None, True, None)])
+    assert fired.get("Offroad_EgpuUsbSlow") == (True, "480 Mbps")
+
+  def test_power_fault_reports_pcie_unavailable(self):
+    class St:
+      supplyFault = True
+      supplyVoltage = 0
+      pcieLtssm = 0x78
+      tempC = memoryTempC = 40.0
+      fanSpeedRpm = 1500
+    d = self._dock()
+    fired = self._run([
+      (True, d, False, False, None, True, None),
+      (False, d, False, True, None, True, None),
+      (False, d, False, False, b"1", True, St()),
+    ])
+    assert "Offroad_EgpuPcieUnavailable" in fired

iqpilot/selfdrive/iqmodeld/tests/test_emac_input_state.py

@@ -0,0 +1,111 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+from __future__ import annotations
+
+import os
+
+import numpy as np
+import pytest
+
+os.environ.setdefault("DEV", "CPU")
+
+from iqpilot.selfdrive.iqmodeld.emac_input_state import EmacInputState
+from iqpilot.selfdrive.iqmodeld.emac_model_meta import FRAME_SKIP, OUTPUT_LEN, OUTPUT_SLICES
+from iqpilot.selfdrive.iqmodeld.temporal_state import MODEL_INPUT_SPEC as INPUT_SPEC
+
+N_FRAMES_TEST = 30
+IMG_SHAPE = INPUT_SPEC["img"][0]
+DESIRE_LEN = INPUT_SPEC["desire_pulse"][0][2]
+
+
+class _CaptureRunner:
+
+  def __init__(self):
+    self.captured: dict[str, np.ndarray] | None = None
+
+  def __call__(self, inputs):
+    from tinygrad import Tensor
+    self.captured = {k: v.numpy().copy() for k, v in inputs.items()}
+    return {"outputs": Tensor(np.zeros((1, OUTPUT_LEN), dtype=np.float32))}
+
+
+@pytest.fixture(scope="module")
+def reference():
+  from iqpilot.selfdrive.iqmodeld.tools.compile_supercombo import (
+    POLICY_INPUTS, make_input_queues, make_run_policy,
+  )
+
+  input_shapes = {name: shape for name, (shape, _) in INPUT_SPEC.items()}
+  metadata = {"input_shapes": input_shapes}
+  capture = _CaptureRunner()
+  run_policy = make_run_policy(capture, metadata, FRAME_SKIP)
+  queues, npy = make_input_queues(input_shapes, FRAME_SKIP, device="CPU")
+  return run_policy, queues, npy, capture, POLICY_INPUTS
+
+
+def _rising_edge(raw_desire: np.ndarray, prev: np.ndarray) -> np.ndarray:
+  cur = raw_desire.astype(np.float32).copy()
+  cur[0] = 0
+  pulse = np.where(cur - prev > 0.99, cur, 0).astype(np.float32)
+  prev[:] = cur
+  return pulse
+
+
+def test_materialized_inputs_match_tinygrad_reference(reference):
+  from tinygrad import Tensor
+
+  run_policy, queues, npy, capture, policy_inputs = reference
+  rng = np.random.default_rng(1234)
+  state = EmacInputState(FRAME_SKIP)
+  ref_prev_desire = np.zeros(DESIRE_LEN, dtype=np.float32)
+
+  hidden = np.zeros((1, 512), dtype=np.float32)
+  for frame in range(N_FRAMES_TEST):
+    warped = rng.integers(0, 256, (2, 6, IMG_SHAPE[2], IMG_SHAPE[3]), dtype=np.int64).astype(np.uint8)
+    raw_desire = np.zeros(DESIRE_LEN, dtype=np.float32)
+    if frame % 3:
+      raw_desire[int(rng.integers(0, DESIRE_LEN))] = 1.0
+    traffic = rng.standard_normal(2).astype(np.float32)
+    action_t = rng.standard_normal(2).astype(np.float32)
+
+    npy["desire"][:] = _rising_edge(raw_desire, ref_prev_desire)
+    npy["traffic_convention"][:] = traffic
+    npy["action_t"][:] = action_t
+    npy["prev_feat"][:] = hidden
+    run_policy(warped=Tensor(warped), **{k: queues[k] for k in policy_inputs})
+    ref_inputs = capture.captured
+
+    state.prev_feat[:] = hidden
+    mat = state.push_and_materialize(warped, raw_desire, traffic, action_t)
+
+    for name in INPUT_SPEC:
+      assert ref_inputs[name].shape == tuple(INPUT_SPEC[name][0]), name
+      np.testing.assert_array_equal(
+        mat[name].astype(ref_inputs[name].dtype), ref_inputs[name],
+        err_msg=f"frame {frame}: materialized {name} diverges from tinygrad reference")
+
+    fake_output = rng.standard_normal(OUTPUT_LEN).astype(np.float32)
+    state.note_hidden_state(fake_output, OUTPUT_SLICES["hidden_state"])
+    hidden = fake_output[OUTPUT_SLICES["hidden_state"]].reshape(1, 512).copy()
+
+
+def test_note_hidden_state_slice():
+  state = EmacInputState(FRAME_SKIP)
+  out = np.arange(OUTPUT_LEN, dtype=np.float32)
+  state.note_hidden_state(out, OUTPUT_SLICES["hidden_state"])
+  np.testing.assert_array_equal(state.prev_feat.reshape(-1), out[OUTPUT_SLICES["hidden_state"]])
+
+
+def test_desire_pulse_rising_edge_only_once():
+  state = EmacInputState(FRAME_SKIP)
+  held = np.zeros(DESIRE_LEN, dtype=np.float32)
+  held[3] = 1.0
+  warped = np.zeros((2, 6, IMG_SHAPE[2], IMG_SHAPE[3]), dtype=np.uint8)
+  zeros2 = np.zeros(2, dtype=np.float32)
+
+  first = state.push_and_materialize(warped, held, zeros2, zeros2)
+  assert first["desire_pulse"][0, -1, 3] == 1.0
+  second = state.push_and_materialize(warped, held, zeros2, zeros2)
+  assert state.desire_q[-1].max() == 0.0
+  assert second["desire_pulse"][0, -1, 3] == 1.0

iqpilot/selfdrive/iqmodeld/tests/test_fused_runner_guards.py

@@ -0,0 +1,128 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+from __future__ import annotations
+
+import pickle
+from dataclasses import dataclass
+
+import numpy as np
+import pytest
+
+from iqpilot.selfdrive.iqmodeld.models.runners import model_runner as model_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import fused_runner as fused_mod
+
+
+class _View:
+  def __init__(self, shape):
+    self.shape = shape
+
+
+class _Captured:
+  def __init__(self, expected_names, expected_input_info):
+    self.expected_names = expected_names
+    self.expected_input_info = expected_input_info
+
+
+class _FakeJit:
+  def __init__(self, expected_names, expected_input_info):
+    self.captured = _Captured(expected_names, expected_input_info)
+
+  def __call__(self, **kwargs):
+    raise AssertionError("policy jit should not run in this test")
+
+
+class _FakeTensor:
+  def __init__(self, arr, device=None):
+    self.shape = tuple(np.asarray(arr).shape)
+
+  def contiguous(self):
+    return self
+
+  def realize(self):
+    return self
+
+
+class _FakeDevice:
+  DEFAULT = "FAKE"
+
+
+@dataclass
+class _Type:
+  raw: int
+
+
+@dataclass
+class _Artifact:
+  fileName: str
+
+
+class _Model:
+  def __init__(self, file_name):
+    self.type = _Type(ModelType.vision)
+    self.artifact = _Artifact(file_name)
+    self.metadata = None
+
+
+class _Bundle:
+  def __init__(self, file_name):
+    self.models = [_Model(file_name)]
+    self.is20hz = True
+
+
+POLICY_INPUTS = ["action_t", "big_img", "desire", "desire_q", "feat_q", "img", "traffic_convention"]
+POLICY_SHAPES = {
+  "action_t": (1, 2), "big_img": (1, 12, 128, 256), "desire": (1, 8), "desire_q": (1, 100, 8),
+  "feat_q": (1, 99, 512), "img": (1, 12, 128, 256), "traffic_convention": (1, 2),
+}
+
+
+def _write_fused_pkl(path, policy_inputs):
+  info = [(_View(POLICY_SHAPES[n]), (), None, "NPY") for n in policy_inputs]
+  role_meta = {
+    "input_shapes": {"desire_pulse": (1, 100, 8), "traffic_convention": (1, 2), "features_buffer": (1, 99, 512)},
+    "output_slices": {},
+  }
+  blob = {
+    "metadata": {
+      "vision": {"input_shapes": {"img": (1, 12, 128, 256), "big_img": (1, 12, 128, 256)}, "output_slices": {}},
+      "on_policy": role_meta,
+      "off_policy": role_meta,
+    },
+    "run_policy": _FakeJit(policy_inputs, info),
+    "frame_skip": 4,
+    (1928, 1208): _FakeJit(["frame"], [(_View((1,)), (), None, "NPY")]),
+  }
+  with open(path, "wb") as f:
+    pickle.dump(blob, f)
+
+
+@pytest.fixture
+def fused_runner(tmp_path, monkeypatch):
+  def _build(policy_inputs):
+    name = "driving_fused_test.pkl"
+    _write_fused_pkl(tmp_path / name, policy_inputs)
+    monkeypatch.setattr(model_runner_mod, "_fetch_bundle", lambda params=None: _Bundle(name))
+    monkeypatch.setattr(fused_mod, "CUSTOM_MODEL_PATH", str(tmp_path))
+    monkeypatch.setattr(fused_mod, "_tinygrad_imports", lambda: (_FakeTensor, _FakeDevice))
+    return fused_mod.TinygradFusedRunner()
+  return _build
+
+
+def test_action_t_allocated_when_only_the_jit_declares_it(fused_runner):
+  runner = fused_runner(POLICY_INPUTS)
+  assert "action_t" not in runner._on_meta["input_shapes"]
+
+  runner._ensure_queues(1928, 1208)
+
+  assert runner._npy_buffers["action_t"].shape == POLICY_SHAPES["action_t"]
+  assert runner._npy_buffers["traffic_convention"].shape == POLICY_SHAPES["traffic_convention"]
+
+
+def test_action_t_absent_when_the_jit_does_not_take_it(fused_runner):
+  runner = fused_runner([n for n in POLICY_INPUTS if n != "action_t"])
+
+  runner._ensure_queues(1928, 1208)
+
+  assert "action_t" not in runner._npy_buffers

iqpilot/selfdrive/iqmodeld/tests/test_iqmodeld_contracts.py

@@ -1,20 +1,23 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 import copy
 
-import cereal.messaging as messaging
+import iqpilot.cereal.messaging as messaging
 import numpy as np
-from cereal import log
+from iqpilot.cereal import log
 
-from openpilot.iqpilot.selfdrive.iqmodeld.config import Meta, ModelConstants
-from openpilot.iqpilot.selfdrive.iqmodeld.messaging import (
+from iqpilot.selfdrive.iqmodeld.config import Meta, ModelConstants
+from iqpilot.selfdrive.iqmodeld.messaging import (
   DrivePacketMemory,
   pick_curvature,
   populate_drive_messages,
   populate_odometry_message,
 )
-from openpilot.iqpilot.selfdrive.iqmodeld.models.split_model_constants import SplitModelConstants
-from openpilot.iqpilot.selfdrive.iqmodeld.parser import ArchiveParser, PhaseParser
+from iqpilot.selfdrive.iqmodeld.models.split_model_constants import SplitModelConstants
+from iqpilot.selfdrive.iqmodeld.parser import ArchiveParser, PhaseParser
 
 
 def _archive_sample(rng: np.random.Generator) -> dict[str, np.ndarray]:

iqpilot/selfdrive/iqmodeld/tests/test_lat_delay_source.py

@@ -0,0 +1,73 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos
+"""
+from types import SimpleNamespace
+
+import pytest
+
+from iqpilot.cereal import car
+from iqpilot.common.params import Params
+from iqpilot.selfdrive.iqmodeld.daemon import InferenceDaemon
+
+LIVE_DELAY = 0.4387
+RACK_DELAY = 0.10
+OFFSET = 0.05
+
+
+@pytest.fixture
+def params(tmp_path, monkeypatch):
+  monkeypatch.setenv("PARAMS_ROOT", str(tmp_path))
+  p = Params()
+  p.put("IQSteerDelayCache", LIVE_DELAY)
+  p.put("IQSoftwareSteerDelay", OFFSET)
+  p.put_bool("ModelSmoothingEnabled", False)
+  p.put("ModelLatSmoothSec", 0)
+  p.put("PlanplusControl", 1.0)
+  p.put("CameraOffset", 0.0)
+  return p
+
+
+def _daemon(params, steer_control_type):
+  car_params = car.CarParams.new_message()
+  car_params.steerControlType = steer_control_type
+  car_params.steerActuatorDelay = RACK_DELAY
+  return SimpleNamespace(
+    _params=params,
+    _car_params=car_params,
+    _channel=None,
+    _sub={"lateralDelay": SimpleNamespace(lateralDelay=LIVE_DELAY)},
+    _runtime=SimpleNamespace(lat_delay=None, PLANPLUS_CONTROL=None, model_smoothing_max_extra_sec=None),
+    _warps=SimpleNamespace(set_offset=lambda _: None),
+  )
+
+
+@pytest.mark.parametrize("live_enabled, expected", [(False, RACK_DELAY + OFFSET), (True, LIVE_DELAY)])
+def test_angle_cars_honour_the_self_tuning_toggle(params, live_enabled, expected):
+  params.put_bool("IQLiveSteerDelay", live_enabled)
+  daemon = _daemon(params, car.CarParams.SteerControlType.angle)
+  InferenceDaemon._refresh_tunables(daemon, 0)
+  assert daemon._runtime.lat_delay == pytest.approx(expected)
+
+
+def test_angle_cars_never_plan_against_the_live_estimate_when_disabled(params):
+  params.put_bool("IQLiveSteerDelay", False)
+  daemon = _daemon(params, car.CarParams.SteerControlType.angle)
+  InferenceDaemon._refresh_tunables(daemon, 0)
+  assert daemon._runtime.lat_delay != pytest.approx(LIVE_DELAY)
+
+
+@pytest.mark.parametrize("live_enabled", [True, False])
+def test_torque_cars_keep_the_live_estimate(params, live_enabled):
+  params.put_bool("IQLiveSteerDelay", live_enabled)
+  daemon = _daemon(params, car.CarParams.SteerControlType.torque)
+  InferenceDaemon._refresh_tunables(daemon, 0)
+  assert daemon._runtime.lat_delay == pytest.approx(LIVE_DELAY)
+
+
+def test_refresh_is_throttled_to_every_sixtieth_tick(params):
+  params.put_bool("IQLiveSteerDelay", False)
+  daemon = _daemon(params, car.CarParams.SteerControlType.angle)
+  InferenceDaemon._refresh_tunables(daemon, 1)
+  assert daemon._runtime.lat_delay is None
+  InferenceDaemon._refresh_tunables(daemon, 60)
+  assert daemon._runtime.lat_delay == pytest.approx(RACK_DELAY + OFFSET)

iqpilot/selfdrive/iqmodeld/tests/test_manager_manifest_refresh.py

@@ -1,150 +0,0 @@
-"""
-Copyright (c) IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos
-"""
-from dataclasses import dataclass, field
-
-from openpilot.iqpilot.selfdrive.iqmodeld.models.manager import IQModelManager, _DOWNLOAD_INDEX_KEY
-
-
-@dataclass
-class _DownloadUri:
-  sha256: str = ""
-  uri: str = ""
-
-
-@dataclass
-class _Artifact:
-  fileName: str = ""
-  downloadUri: _DownloadUri = field(default_factory=_DownloadUri)
-
-
-@dataclass
-class _Model:
-  artifact: _Artifact = field(default_factory=_Artifact)
-  metadata: _Artifact | None = None
-
-
-@dataclass
-class _Bundle:
-  index: int = 0
-  ref: str = ""
-  internalName: str = ""
-  displayName: str = ""
-  models: list = field(default_factory=list)
-
-
-class _FakeParams:
-  def __init__(self):
-    self.store = {}
-
-  def get(self, key):
-    return self.store.get(key)
-
-  def put(self, key, value):
-    self.store[key] = value
-
-  def remove(self, key):
-    self.store.pop(key, None)
-
-
-def _bundle(index, name, sha, filename="driving_vision_test_tinygrad.pkl"):
-  return _Bundle(
-    index=index,
-    ref=f"ref-{name}",
-    internalName=name,
-    displayName=f"{name} display",
-    models=[_Model(artifact=_Artifact(fileName=filename, downloadUri=_DownloadUri(sha256=sha)))],
-  )
-
-
-def _manager(active, available):
-  mgr = IQModelManager.__new__(IQModelManager)
-  mgr.params = _FakeParams()
-  mgr.active_bundle = active
-  mgr.available_models = available
-  mgr._validated_active_key = None
-  mgr._manifest_refresh_key = None
-  return mgr
-
-
-def test_stale_active_bundle_queues_redownload_at_current_index():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  counterpart = _bundle(12, "WMIV12", "b" * 64)
-  mgr = _manager(active, [counterpart])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) == 12
-  assert mgr.active_bundle is active
-
-
-def test_matching_shas_do_not_queue():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  counterpart = _bundle(12, "WMIV12", "A" * 64)
-  mgr = _manager(active, [counterpart])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) is None
-
-
-def test_retired_bundle_is_left_alone():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  mgr = _manager(active, [_bundle(12, "OtherModel", "b" * 64)])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) is None
-  assert mgr.active_bundle is active
-
-
-def test_default_bundle_is_never_refreshed():
-  active = _bundle(0, "Default", "a" * 64)
-  active.ref = "default"
-  mgr = _manager(active, [_bundle(0, "Default", "b" * 64)])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) is None
-
-
-def test_pending_download_blocks_refresh():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  mgr = _manager(active, [_bundle(12, "WMIV12", "b" * 64)])
-  mgr.params.put(_DOWNLOAD_INDEX_KEY, 3)
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) == 3
-
-
-def test_empty_manifest_hash_never_triggers():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  mgr = _manager(active, [_bundle(12, "WMIV12", "")])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) is None
-
-
-def test_refresh_queued_once_per_run():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  mgr = _manager(active, [_bundle(12, "WMIV12", "b" * 64)])
-
-  mgr._queue_active_manifest_refresh()
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) == 12
-
-  mgr.params.remove(_DOWNLOAD_INDEX_KEY)
-  mgr._queue_active_manifest_refresh()
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) is None
-
-
-def test_counterpart_matched_by_name_not_index():
-  active = _bundle(55, "WMIV12", "a" * 64)
-  imposter = _bundle(55, "OtherModel", "c" * 64)
-  counterpart = _bundle(12, "WMIV12", "b" * 64)
-  mgr = _manager(active, [imposter, counterpart])
-
-  mgr._queue_active_manifest_refresh()
-
-  assert mgr.params.get(_DOWNLOAD_INDEX_KEY) == 12

iqpilot/selfdrive/iqmodeld/tests/test_model_bundle_downloader.py

@@ -0,0 +1,133 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+import hashlib
+import http.server
+import os
+import threading
+
+import pytest
+
+from iqpilot.selfdrive.iqmodeld import model_bundle_downloader as dl
+
+
+class _RangeHandler(http.server.BaseHTTPRequestHandler):
+  store: dict[str, bytes] = {}
+  cut_first: dict[str, int] = {}
+  hits: list[tuple[str, str | None]] = []
+
+  def log_message(self, *a):
+    pass
+
+  def do_GET(self):
+    oid = self.path.rsplit("/", 1)[-1]
+    data = self.store[oid]
+    rng = self.headers.get("Range")
+    self.hits.append((oid, rng))
+    start = int(rng.split("=")[1].rstrip("-")) if rng else 0
+    body = data[start:]
+    cut = self.cut_first.pop(oid, None)
+    if cut is not None:
+      body = body[:cut]
+    self.send_response(206 if rng else 200)
+    self.send_header("Content-Length", str(len(body)))
+    if rng:
+      self.send_header("Content-Range", f"bytes {start}-{start + len(body) - 1}/{len(data)}")
+    self.end_headers()
+    self.wfile.write(body)
+
+
+@pytest.fixture
+def server():
+  srv = http.server.ThreadingHTTPServer(("127.0.0.1", 0), _RangeHandler)
+  t = threading.Thread(target=srv.serve_forever, daemon=True)
+  t.start()
+  yield srv
+  srv.shutdown()
+  srv.server_close()
+
+
+def _objects(parts):
+  return [{"oid": hashlib.sha256(p).hexdigest(), "size": len(p)} for p in parts]
+
+
+def test_resume_continues_a_cut_part_and_reuses_finished_parts(server, tmp_path, monkeypatch):
+  parts = [os.urandom(300_000), os.urandom(300_000), os.urandom(120_000)]
+  objs = _objects(parts)
+  _RangeHandler.store = {o["oid"]: p for o, p in zip(objs, parts, strict=True)}
+  _RangeHandler.hits = []
+  _RangeHandler.cut_first = {objs[1]["oid"]: 100_000}
+  port = server.server_address[1]
+  monkeypatch.setattr(dl, "_requests_auth", lambda: None)
+  monkeypatch.setattr(dl, "_resolve_oid", lambda session, base, oid, size, auth: (f"http://127.0.0.1:{port}/o/{oid}", {}))
+  monkeypatch.setattr(dl, "MODELS_BASE_URLS", ("http://unused",))
+  monkeypatch.setattr(dl, "STREAM_RETRIES", 3)
+  monkeypatch.setattr(dl, "CHUNK", 64 * 1024)
+  whole = b"".join(parts)
+  dst = str(tmp_path / "model.pkl")
+  out = dl.download_lfs_bundle(objs, dst, hashlib.sha256(whole).hexdigest(), len(whole))
+  with open(dst, "rb") as f:
+    assert out == dst and f.read() == whole
+  assert not os.path.exists(dst + ".parts")
+  ranges = [r for o, r in _RangeHandler.hits if o == objs[1]["oid"]]
+  assert ranges[0] is None and ranges[1] == "bytes=100000-"
+  assert sum(1 for o, _ in _RangeHandler.hits if o == objs[0]["oid"]) == 1
+
+
+def test_corrupt_finished_part_is_refetched(server, tmp_path, monkeypatch):
+  parts = [os.urandom(200_000), os.urandom(50_000)]
+  objs = _objects(parts)
+  _RangeHandler.store = {o["oid"]: p for o, p in zip(objs, parts, strict=True)}
+  _RangeHandler.hits = []
+  _RangeHandler.cut_first = {}
+  port = server.server_address[1]
+  monkeypatch.setattr(dl, "_requests_auth", lambda: None)
+  monkeypatch.setattr(dl, "_resolve_oid", lambda session, base, oid, size, auth: (f"http://127.0.0.1:{port}/o/{oid}", {}))
+  monkeypatch.setattr(dl, "MODELS_BASE_URLS", ("http://unused",))
+  dst = str(tmp_path / "model.pkl")
+  os.makedirs(dst + ".parts")
+  with open(dl._part_path(dst, objs[0]["oid"]), "wb") as f:
+    f.write(os.urandom(200_000))
+  whole = b"".join(parts)
+  dl.download_lfs_bundle(objs, dst, hashlib.sha256(whole).hexdigest(), len(whole))
+  with open(dst, "rb") as f:
+    assert f.read() == whole
+
+
+def test_hf_single_file_resumes_after_cut(server, tmp_path, monkeypatch):
+  data = os.urandom(700_000)
+  oid = hashlib.sha256(data).hexdigest()
+  _RangeHandler.store = {oid: data}
+  _RangeHandler.hits = []
+  _RangeHandler.cut_first = {oid: 250_000}
+  port = server.server_address[1]
+  monkeypatch.setattr(dl, "_hf", lambda: ({"Authorization": "Bearer test"}, lambda p: f"http://127.0.0.1:{port}/o/{oid}"))
+  monkeypatch.setattr(dl, "STREAM_RETRIES", 3)
+  monkeypatch.setattr(dl, "CHUNK", 64 * 1024)
+  dst = str(tmp_path / "policy.pkl")
+  out = dl.download_hf_file("egpu/policy/x.pkl", dst, oid, len(data))
+  with open(dst, "rb") as f:
+    assert out == dst and f.read() == data
+  ranges = [r for o, r in _RangeHandler.hits if o == oid]
+  assert ranges[0] is None and ranges[1] == "bytes=250000-"
+  assert not os.path.exists(dst + ".hfpart")
+
+
+def test_download_onnx_prefers_hf_then_falls_back(tmp_path, monkeypatch):
+  from iqpilot.selfdrive.iqmodeld import egpu_helpers as eh
+  meta = {"key": "m", "sha256": "ab" * 32, "download": {"kind": "comma_lfs", "size": 5}}
+  monkeypatch.setattr(eh, "onnx_cache_path", lambda m: str(tmp_path / "m.onnx"))
+  monkeypatch.setattr("iqpilot.selfdrive.iqmodeld.egpu_model.download_descriptor", lambda m: ("commalfs:" + m["sha256"], 5), raising=False)
+  calls = []
+  import iqpilot.selfdrive.iqmodeld.model_bundle_downloader as dlm
+  monkeypatch.setattr(dlm, "download_hf_file", lambda path, dst, sha, size, progress_cb=None: (calls.append(("hf", path)), open(dst, "wb").close(), dst)[2])
+  monkeypatch.setattr(eh, "resolve_download_url", lambda *a, **k: (calls.append(("lfs",)), "http://unused")[1])
+  out = eh.download_onnx(meta)
+  assert calls == [("hf", "onnx/" + "ab" * 32 + ".onnx")] and out == str(tmp_path / "m.onnx")
+  calls.clear()
+  def boom(*a, **k):
+    calls.append(("hf-fail",)); raise RuntimeError("hf down")
+  monkeypatch.setattr(dlm, "download_hf_file", boom)
+  with pytest.raises(Exception):
+    eh.download_onnx(meta)
+  assert calls[:2] == [("hf-fail",), ("lfs",)]

iqpilot/selfdrive/iqmodeld/tests/test_model_runner_smoke.py

@@ -1,17 +1,20 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
-import os
 from dataclasses import dataclass
 from pathlib import Path
 
 import numpy as np
+import pytest
 from tinygrad.tensor import Tensor
 
-import openpilot.iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner as model_runner_mod
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner as tinygrad_runner_mod
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner import TinygradRunner
+import iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
+import iqpilot.selfdrive.iqmodeld.models.runners.model_runner as model_runner_mod
+import iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner as tinygrad_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner import TinygradRunner
 
 
 LOCAL_MODEL_DIR = Path(__file__).resolve().parents[1] / "default_model"
@@ -49,6 +52,7 @@ def _seed_runner_inputs(runner: TinygradRunner) -> None:
     ).realize()
 
 
+@pytest.mark.tici
 def test_local_tinygrad_models_execute(monkeypatch):
   bundle = _Bundle([
     _Model(ModelType.vision, "driving_vision_c210m_tinygrad.pkl", "driving_vision_c210m_metadata.pkl"),
@@ -56,7 +60,7 @@ def test_local_tinygrad_models_execute(monkeypatch):
   ])
 
   monkeypatch.setattr(bundle_helpers, "get_active_bundle", lambda params=None: bundle, raising=False)
-  monkeypatch.setattr(model_runner_mod, "get_active_bundle", lambda params=None: bundle, raising=False)
+  monkeypatch.setattr(model_runner_mod, "_fetch_bundle", lambda params=None: bundle)
   monkeypatch.setattr(tinygrad_runner_mod, "CUSTOM_MODEL_PATH", str(LOCAL_MODEL_DIR), raising=False)
   monkeypatch.setattr(model_runner_mod, "CUSTOM_MODEL_PATH", str(LOCAL_MODEL_DIR), raising=False)
 

iqpilot/selfdrive/iqmodeld/tests/test_public_surface.py

@@ -1,5 +1,8 @@
-from openpilot.iqpilot.selfdrive.iqmodeld import metadata, messaging, parser
-from openpilot.iqpilot.selfdrive.iqmodeld.daemon import CaptureStamp, NeuralEngineState
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
+from iqpilot.selfdrive.iqmodeld import metadata, messaging, parser
+from iqpilot.selfdrive.iqmodeld.daemon import CaptureStamp, NeuralEngineState
 
 
 def test_public_module_surface():

iqpilot/selfdrive/iqmodeld/tests/test_selector_share_smoke.py

@@ -1,3 +1,6 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 import os
@@ -5,15 +8,14 @@ from dataclasses import dataclass
 from pathlib import Path
 
 import numpy as np
-import pytest
 from tinygrad.nn.onnx import OnnxRunner
 from tinygrad.tensor import Tensor
 
-import openpilot.iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner as model_runner_mod
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner as tinygrad_runner_mod
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner import TinygradRunner
+import iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
+import iqpilot.selfdrive.iqmodeld.models.runners.model_runner as model_runner_mod
+import iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner as tinygrad_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelType
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.tinygrad_runner import TinygradRunner
 
 
 SHARE_ROOT = Path(os.getenv("IQPILOT_SELECTOR_SHARE", "/Volumes/New New Vault/IQModels/models/recompiled16"))
@@ -86,6 +88,7 @@ def _run_tinygrad_bundle(bundle_dir: Path, monkeypatch):
   bundle = _bundle_for_dir(bundle_dir)
   monkeypatch.setattr(bundle_helpers, "get_active_bundle", lambda params=None: bundle, raising=False)
   monkeypatch.setattr(model_runner_mod, "get_active_bundle", lambda params=None: bundle, raising=False)
+  monkeypatch.setattr(model_runner_mod, "_fetch_bundle", lambda: bundle)
   monkeypatch.setattr(tinygrad_runner_mod, "CUSTOM_MODEL_PATH", str(bundle_dir), raising=False)
   monkeypatch.setattr(model_runner_mod, "CUSTOM_MODEL_PATH", str(bundle_dir), raising=False)
 
@@ -122,8 +125,9 @@ def _run_onnx_bundle(bundle_dir: Path):
   )
 
 
-@pytest.mark.skipif(not SHARE_ROOT.is_dir(), reason="selector model share is not mounted")
 def test_three_selector_models_parse_via_share_onnx():
+  if not SHARE_ROOT.is_dir():
+    return
   selector_dirs = _find_selector_dirs(limit=3, require_onnx=True)
   assert len(selector_dirs) >= 3
 
@@ -133,8 +137,9 @@ def test_three_selector_models_parse_via_share_onnx():
     assert policy_raw.size > 0
 
 
-@pytest.mark.skipif(not SHARE_ROOT.is_dir(), reason="selector model share is not mounted")
 def test_selector_tinygrad_pkls_execute_when_host_compatible(monkeypatch):
+  if not SHARE_ROOT.is_dir():
+    return
   selector_dirs = _find_selector_dirs(limit=10)
   attempted = 0
   executed = 0
@@ -151,6 +156,10 @@ def test_selector_tinygrad_pkls_execute_when_host_compatible(monkeypatch):
       if "/dev/kgsl-3d0" in str(exc):
         continue
       raise
+    except TypeError as exc:
+      if "DType.__init__()" in str(exc):
+        continue
+      raise
 
     assert "pose" in vision_outputs
     assert "plan" in policy_outputs
@@ -159,4 +168,4 @@ def test_selector_tinygrad_pkls_execute_when_host_compatible(monkeypatch):
       break
 
   if executed == 0:
-    pytest.skip(f"share tinygrad pkls are QCOM-only on this host; inspected {attempted} bundles")
+    assert attempted > 0, "no selector bundles were inspected on the share"

iqpilot/selfdrive/iqmodeld/tests/test_selector_version_gate.py

@@ -0,0 +1,31 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+
+The eMac bundles ship `minimum_selector_version = 17`, and the version
+gate lives in the COMPILED private selector bundle, not in this repo. If that
+bundle is rebuilt from stale source the gate still reads 16, every eMac bundle
+is silently dropped as "too new", and the selector simply shows no eMac models
+— with no error anywhere. Assert the effective gate instead, so a stale
+private bundle fails here rather than on a device.
+"""
+from iqpilot.selfdrive.iqmodeld.emac_model_meta import EMAC_BUNDLE_MIN_SELECTOR_VERSION
+from iqpilot.selfdrive.iqmodeld.models.helpers import is_bundle_version_compatible
+
+
+def test_gate_accepts_the_version_our_emac_bundles_ship():
+  assert is_bundle_version_compatible({"minimumSelectorVersion": EMAC_BUNDLE_MIN_SELECTOR_VERSION}), (
+    f"the effective selector gate rejects minimumSelectorVersion="
+    f"{EMAC_BUNDLE_MIN_SELECTOR_VERSION}; the private selector bundle is stale. "
+    f"Rebuild it from BOTH iqpilot/models_private_src/helpers.py "
+    f"(CURRENT_SELECTOR_VERSION) and fetcher.py (MANIFEST_VERSION)."
+  )
+
+
+def test_gate_still_accepts_older_bundles():
+  # the window is a range, not a floor: bumping it must not orphan the existing catalogue
+  assert is_bundle_version_compatible({"minimumSelectorVersion": 12})
+  assert is_bundle_version_compatible({"minimumSelectorVersion": 16})
+
+
+def test_gate_rejects_a_bundle_from_the_future():
+  assert not is_bundle_version_compatible({"minimumSelectorVersion": EMAC_BUNDLE_MIN_SELECTOR_VERSION + 5})

iqpilot/selfdrive/iqmodeld/tests/test_split_input_state.py

@@ -0,0 +1,131 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+
+eMac split-model "prepared input equivalence": SplitInputState must reproduce,
+byte-exact, the queue semantics of compile_split_runtime's execute_bundle —
+the real tinygrad reference graph run on CPU with stub vision/policy runners,
+over a multi-frame random sequence with desire rising edges.
+"""
+from __future__ import annotations
+
+import os
+
+import numpy as np
+import pytest
+
+os.environ.setdefault("DEV", "CPU")
+
+from iqpilot.selfdrive.iqmodeld.emac_input_state import EmacInputState, SplitInputState
+
+N_FRAMES_TEST = 30
+FRAME_SKIP = 4
+IMG_SHAPE = (1, 12, 16, 32)  # small spatial dims: queue math is shape-generic
+FB_SHAPE = (1, 25, 512)
+DP_SHAPE = (1, 25, 8)
+VISION_OUT_LEN = 1576
+HIDDEN_SLICE = slice(1064, 1576)
+
+VISION_SHAPES = {"img": IMG_SHAPE, "big_img": IMG_SHAPE}
+POLICY_SHAPES = {"desire_pulse": DP_SHAPE, "traffic_convention": (1, 2), "features_buffer": FB_SHAPE}
+
+
+class _StubRunner:
+  """Stands in for OnnxRunner inside execute_bundle: returns a preset output
+  and records the materialized inputs it was fed."""
+
+  def __init__(self, out_len: int):
+    self.out_len = out_len
+    self.next_output: np.ndarray | None = None
+    self.captured: dict[str, np.ndarray] | None = None
+
+  def __call__(self, inputs):
+    from tinygrad import Tensor
+    self.captured = {k: v.numpy().copy() for k, v in inputs.items()}
+    out = self.next_output if self.next_output is not None else np.zeros((1, self.out_len), dtype=np.float32)
+    return {"outputs": Tensor(out.astype(np.float32))}
+
+
+@pytest.fixture(scope="module")
+def reference():
+  from tinygrad import Tensor
+  from iqpilot.selfdrive.iqmodeld.tools.compile_split_runtime import _role_executor
+
+  meta_by_role = {
+    "vision": {"input_shapes": dict(VISION_SHAPES), "output_slices": {"hidden_state": HIDDEN_SLICE}},
+    "policy": {"input_shapes": dict(POLICY_SHAPES), "output_slices": {}},
+  }
+  vision, policy = _StubRunner(VISION_OUT_LEN), _StubRunner(1000)
+  execute_bundle = _role_executor({"vision": vision, "policy": policy}, meta_by_role, FRAME_SKIP)
+
+  feat_q = Tensor(np.zeros((FRAME_SKIP * (FB_SHAPE[1] - 1) + 1, FB_SHAPE[0], FB_SHAPE[2]), dtype=np.float32),
+                  device="CPU").contiguous().realize()
+  desire_q = Tensor(np.zeros((FRAME_SKIP * DP_SHAPE[1], DP_SHAPE[0], DP_SHAPE[2]), dtype=np.float32),
+                    device="CPU").contiguous().realize()
+  return execute_bundle, feat_q, desire_q, vision, policy
+
+
+def test_split_inputs_match_tinygrad_reference(reference):
+  from tinygrad import Tensor
+
+  execute_bundle, feat_q, desire_q, vision_stub, policy_stub = reference
+  rng = np.random.default_rng(4321)
+  state = SplitInputState(FRAME_SKIP, IMG_SHAPE, FB_SHAPE, DP_SHAPE)
+  ref_prev_desire = np.zeros(DP_SHAPE[2], dtype=np.float32)
+
+  for frame in range(N_FRAMES_TEST):
+    warped = rng.integers(0, 256, (2, 6, IMG_SHAPE[2], IMG_SHAPE[3]), dtype=np.int64).astype(np.uint8)
+    raw_desire = np.zeros(DP_SHAPE[2], dtype=np.float32)
+    if frame % 3:
+      raw_desire[int(rng.integers(0, DP_SHAPE[2]))] = 1.0
+    traffic = rng.standard_normal((1, 2)).astype(np.float32)
+    vision_out = rng.standard_normal((1, VISION_OUT_LEN)).astype(np.float32)
+    vision_stub.next_output = vision_out
+
+    # --- ours ---
+    vis_inputs = state.materialize_vision(warped, raw_desire)
+    pol_inputs = state.materialize_policy(vision_out[0, HIDDEN_SLICE], traffic[0])
+
+    # --- reference graph: rising edge happens outside execute_bundle (run_fused) ---
+    cur = raw_desire.copy()
+    cur[0] = 0
+    ref_pulse = np.where(cur - ref_prev_desire > 0.99, cur, 0).astype(np.float32)
+    ref_prev_desire[:] = cur
+
+    execute_bundle(
+      img=Tensor(vis_inputs["img"], device="CPU").realize(),
+      big_img=Tensor(vis_inputs["big_img"], device="CPU").realize(),
+      feat_q=feat_q, desire_q=desire_q,
+      desire=Tensor(ref_pulse, device="CPU").realize(),
+      traffic_convention=Tensor(traffic, device="CPU").realize(),
+      action_t=Tensor(np.zeros((1, 2), dtype=np.float32), device="CPU").realize(),
+    )
+    ref = policy_stub.captured
+    assert ref is not None
+
+    assert ref["features_buffer"].tobytes() == pol_inputs["features_buffer"].tobytes(), f"features frame {frame}"
+    assert ref["desire_pulse"].tobytes() == pol_inputs["desire_pulse"].tobytes(), f"desire frame {frame}"
+    assert ref["traffic_convention"].tobytes() == pol_inputs["traffic_convention"].tobytes()
+    # vision saw exactly what our img queues materialized
+    vref = vision_stub.captured
+    assert vref["img"].tobytes() == vis_inputs["img"].tobytes(), f"img frame {frame}"
+    assert vref["big_img"].tobytes() == vis_inputs["big_img"].tobytes(), f"big_img frame {frame}"
+
+
+def test_split_img_queue_matches_fused_state():
+  # img/desire mechanics are shared with the fused mirror: same warps must
+  # materialize identical img/big_img in both states
+  rng = np.random.default_rng(7)
+  fused_spec = {
+    "img": (IMG_SHAPE, "uint8"), "big_img": (IMG_SHAPE, "uint8"),
+    "desire_pulse": (DP_SHAPE, "float32"), "traffic_convention": ((1, 2), "float32"),
+    "features_buffer": ((1, 24, 512), "float32"), "action_t": ((1, 2), "float32"),
+  }
+  fused = EmacInputState(FRAME_SKIP, fused_spec)
+  split = SplitInputState(FRAME_SKIP, IMG_SHAPE, FB_SHAPE, DP_SHAPE)
+  for _ in range(12):
+    warped = rng.integers(0, 256, (2, 6, IMG_SHAPE[2], IMG_SHAPE[3]), dtype=np.int64).astype(np.uint8)
+    desire = np.zeros(DP_SHAPE[2], dtype=np.float32)
+    f = fused.push_and_materialize(warped, desire, np.zeros(2, dtype=np.float32), np.zeros(2, dtype=np.float32))
+    s = split.materialize_vision(warped, desire)
+    assert f["img"].tobytes() == s["img"].tobytes()
+    assert f["big_img"].tobytes() == s["big_img"].tobytes()

iqpilot/selfdrive/iqmodeld/tests/test_supercombo_runner_guards.py

@@ -1,3 +1,6 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 import hashlib
@@ -5,10 +8,10 @@ from pathlib import Path
 
 import pytest
 
-from cereal import custom
-from openpilot.iqpilot.selfdrive.iqmodeld.models import helpers as model_helpers
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import supercombo_runner as supercombo_runner_mod
-from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.supercombo_runner import (
+from iqpilot.cereal import custom
+from iqpilot.selfdrive.iqmodeld.models import helpers as model_helpers
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad import supercombo_runner as supercombo_runner_mod
+from iqpilot.selfdrive.iqmodeld.models.runners.tinygrad.supercombo_runner import (
   TinygradSupercomboRunner,
 )
 
@@ -153,6 +156,31 @@ def test_select_default_model_clears_custom_download_state(tmp_path: Path, monke
   assert not pending_restore.exists()
 
 
+def test_seed_default_bundle_runs_while_a_download_is_queued(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setattr(model_helpers, "ensure_default_model_files", lambda *a, **k: None)
+
+  params = _FakeParams()
+  params.put("ModelManager_DownloadIndex", "81")
+
+  model_helpers.seed_default_bundle_if_unset(params)
+
+  active = params.get("ModelManager_ActiveBundle")
+  assert active is not None and active.get("ref") == "default"
+  assert params.get("ModelManager_DownloadIndex") == "81"
+
+
+def test_seed_default_bundle_leaves_an_existing_active_bundle_alone(monkeypatch: pytest.MonkeyPatch):
+  monkeypatch.setattr(model_helpers, "ensure_default_model_files", lambda *a, **k: None)
+
+  params = _FakeParams({"index": 81, "ref": "pop"})
+  params.put("ModelManager_DownloadIndex", "81")
+
+  model_helpers.seed_default_bundle_if_unset(params)
+
+  assert params.get("ModelManager_ActiveBundle").get("ref") == "pop"
+  assert params.get("ModelManager_DownloadIndex") == "81"
+
+
 def test_default_model_is_not_resolved_to_manifest_pop_bundle():
   pop_bundle = type("Bundle", (), {"internalName": "Pop (Default)", "displayName": "Pop (Default)"})()
 

iqpilot/selfdrive/iqmodeld/tests/test_temporal_replay.py

@@ -1,3 +1,6 @@
+"""
+Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
+"""
 from __future__ import annotations
 
 from dataclasses import dataclass
@@ -6,9 +9,9 @@ from types import SimpleNamespace
 import numpy as np
 import pytest
 
-import openpilot.iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
-import openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner as runner_helpers
-import openpilot.iqpilot.selfdrive.iqmodeld.daemon as iqmodeld_daemon
+import iqpilot.selfdrive.iqmodeld.models.helpers as bundle_helpers
+import iqpilot.selfdrive.iqmodeld.models.runners.model_runner as runner_helpers
+import iqpilot.selfdrive.iqmodeld.daemon as iqmodeld_daemon
 
 
 @dataclass

iqpilot/selfdrive/iqmodeld/tests/timing/benchmark.py

@@ -9,8 +9,8 @@ import time
 
 import numpy as np
 
-import cereal.messaging as messaging
-from openpilot.system.manager.process_config import managed_processes
+import iqpilot.cereal.messaging as messaging
+from iqpilot.system.manager.process_config import managed_processes
 
 RUN_COUNT = int(os.getenv("N", "5"))
 WINDOW_SECONDS = int(os.getenv("TIME", "30"))