sunnypilot v2026.002.000

version: sunnypilot v2026.002.000 (staging)
date: 2026-07-21T07:44:02
master commit: 2c334ede443d7391d27575af8c854a095ba702a8

openpilot/sunnypilot/modeld_v2/tests/test_compile_modeld.py

@@ -0,0 +1,161 @@
+"""
+Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
+
+This file is part of sunnypilot and is licensed under the MIT License.
+See the LICENSE.md file in the root directory for more details.
+"""
+
+import numpy as np
+import pytest
+
+from openpilot.sunnypilot.modeld_v2.compile_modeld import derive_frame_skip, _detect_desire_key
+
+
+class TestDeriveFrameSkip:
+  def test_non20hz_supercombo(self):
+    vision = {}
+    policy = {'features_buffer': (1, 99, 512), 'desire': (1, 100, 8)}
+    assert derive_frame_skip(vision, policy) == 1
+
+  def test_20hz_supercombo(self):
+    vision = {}
+    policy = {'features_buffer': (1, 24, 512), 'desire': (1, 25, 8)}
+    assert derive_frame_skip(vision, policy) == 4
+
+  def test_split_vision_policy(self):
+    vision = {'img': (1, 12, 128, 256)}
+    policy = {'features_buffer': (1, 25, 512), 'desire_pulse': (1, 25, 8)}
+    assert derive_frame_skip(vision, policy) == 4
+
+  def test_no_features_buffer(self):
+    assert derive_frame_skip({}, {}) == 1
+
+
+class TestFrameSkipBufferLengthEquivalence:
+  @pytest.mark.parametrize("frame_skip,expected_buffer_length", [
+    (1, 2),
+    (4, 5),
+  ])
+  def test_img_buffer_size_matches_warp_buffer_length(self, frame_skip, expected_buffer_length):
+    n_frames = 2
+    img_buf_dim0 = frame_skip * (n_frames - 1) + 1
+    assert img_buf_dim0 == expected_buffer_length, \
+      f"frame_skip={frame_skip}: img_buf[0]={img_buf_dim0}, expected {expected_buffer_length}"
+
+  @pytest.mark.parametrize("is_20hz,expected_frame_skip,expected_buffer_length", [
+    (False, 1, 2),
+    (True, 4, 5),
+  ])
+  def test_is_20hz_to_frame_skip_to_buffer_length(self, is_20hz, expected_frame_skip, expected_buffer_length):
+    if is_20hz:
+      policy_shapes = {'features_buffer': (1, 24, 512)}
+    else:
+      policy_shapes = {'features_buffer': (1, 99, 512)}
+    frame_skip = derive_frame_skip({}, policy_shapes)
+    assert frame_skip == expected_frame_skip
+
+    n_frames = 2
+    img_buf_dim0 = frame_skip * (n_frames - 1) + 1
+    assert img_buf_dim0 == expected_buffer_length
+
+
+class TestTemporalSamplingEquivalence:
+  def test_non20hz_desire_sampling_identity(self):
+    buf = np.random.randn(100, 1, 8).astype(np.float32)
+    frame_skip = 1
+    sampled = buf[::frame_skip].reshape(-1, 8)
+    assert sampled.shape == (100, 8)
+    np.testing.assert_array_equal(sampled, buf[:, 0, :])
+
+  def test_20hz_desire_sampling_max(self):
+    buf = np.zeros((100, 1, 8), dtype=np.float32)
+    buf[99, 0, 3] = 1.0
+    frame_skip = 4
+    reshaped = buf.reshape(-1, frame_skip, 1, 8).max(axis=1)
+    sampled = reshaped.reshape(-1, 8)
+    assert sampled.shape == (25, 8)
+    assert sampled[24, 3] == 1.0
+    assert sampled[23, 3] == 0.0
+
+  def test_split_features_buffer_sampling_skip(self):
+    buf = np.arange(100 * 512, dtype=np.float32).reshape(100, 1, 512)
+    frame_skip = 4
+    sampled = buf[::frame_skip].reshape(-1, 512)
+    assert sampled.shape == (25, 512)
+    np.testing.assert_array_equal(sampled[0], buf[0, 0])
+    np.testing.assert_array_equal(sampled[1], buf[4, 0])
+    np.testing.assert_array_equal(sampled[24], buf[96, 0])
+
+  def test_non20hz_features_buffer_sampling_identity(self):
+    buf = np.arange(99 * 512, dtype=np.float32).reshape(99, 1, 512)
+    frame_skip = 1
+    sampled = buf[::frame_skip].reshape(-1, 512)
+    assert sampled.shape == (99, 512)
+    np.testing.assert_array_equal(sampled, buf[:, 0, :])
+
+
+class TestTemporalIdxEquivalence:
+  @pytest.mark.parametrize("mode,desire_shape,fb_shape,frame_skip", [
+    ('non20hz', (1, 100, 8), (1, 99, 512), 1),
+    ('20hz', (1, 25, 8), (1, 24, 512), 4),
+    ('split', (1, 25, 8), (1, 25, 512), 4),
+  ])
+  def test_features_buffer_idx_equivalence(self, mode, desire_shape, fb_shape, frame_skip):
+    history = fb_shape[1]
+
+    if mode == 'non20hz':
+      modelstate_idxs = np.arange(history)
+      buf_len = history
+    elif mode == '20hz':
+      buf_len = (history + 1) * 4
+      step = int(-buf_len / history)
+      modelstate_idxs = np.arange(step, step * (history + 1), step)[::-1]
+    elif mode == 'split':
+      buf_len = history * 4
+      skip = buf_len // history
+      modelstate_idxs = np.arange(buf_len)[-1 - (skip * (history - 1))::skip]
+
+    assert len(modelstate_idxs) == fb_shape[1], \
+      f"{mode}: ModelState idx count {len(modelstate_idxs)} != input shape {fb_shape[1]}"
+
+  @pytest.mark.parametrize("mode,desire_shape,fb_shape,frame_skip", [
+    ('non20hz', (1, 100, 8), (1, 99, 512), 1),
+    ('20hz', (1, 25, 8), (1, 24, 512), 4),
+    ('split', (1, 25, 8), (1, 25, 512), 4),
+  ])
+  def test_desire_idx_equivalence(self, mode, desire_shape, fb_shape, frame_skip):
+    history = desire_shape[1]
+
+    compile_desire_buf_len = frame_skip * history if mode != 'non20hz' else history
+    compile_sampled_count = compile_desire_buf_len // frame_skip if frame_skip > 1 else compile_desire_buf_len
+    assert compile_sampled_count == history, \
+      f"{mode}: compile desire samples {compile_sampled_count} != model input {history}"
+
+
+class TestDetectDesireKey:
+  def test_finds_desire(self):
+    shapes = {'features_buffer': (1, 99, 512), 'desire': (1, 100, 8), 'traffic_convention': (1, 2)}
+    assert _detect_desire_key(shapes) == 'desire'
+
+  def test_finds_desire_pulse(self):
+    shapes = {'features_buffer': (1, 25, 512), 'desire_pulse': (1, 25, 8), 'traffic_convention': (1, 2)}
+    assert _detect_desire_key(shapes) == 'desire_pulse'
+
+  def test_returns_none_when_no_desire(self):
+    shapes = {'features_buffer': (1, 99, 512), 'traffic_convention': (1, 2)}
+    assert _detect_desire_key(shapes) is None
+
+
+class TestOutputSlicePreservation:
+  def test_vision_hidden_state_slice_used_for_features(self):
+    mock_slices = {'hidden_state': slice(0, 512), 'plan': slice(512, 1024)}
+    features_slice = mock_slices['hidden_state']
+    fake_output = np.random.randn(1, 1024).astype(np.float32)
+    features = fake_output[:, features_slice]
+    assert features.shape == (1, 512)
+
+  def test_policy_output_slices_independent(self):
+    vision_slices = {'hidden_state': slice(0, 512)}
+    policy_slices = {'plan': slice(0, 495), 'meta': slice(495, 550)}
+    assert set(vision_slices.keys()) & set(policy_slices.keys()) == set(), \
+      "vision and policy slices should not overlap in keys"