Convert .pyre_configuration.local to fast by default architecture] [b…

…atch:44/100] [shard:2/N] [A]

Reviewed By: MaggieMoss

Differential Revision: D63644535

fbshipit-source-id: f4118078d10c24b1fd5c400659c5f3c70ae2c781

opensfm/actions/export_colmap.py

@@ -185,11 +185,13 @@ def array_to_blob(array) -> bytes:
     if IS_PYTHON3:
         return array.tobytes()
     else:
+        # pyre-fixme[16]: Module `numpy` has no attribute `getbuffer`.
         return np.getbuffer(array)
 
 
 def blob_to_array(blob, dtype, shape: Tuple[int] = (-1,)):
     if IS_PYTHON3:
+        # pyre-fixme[20]: Argument `sep` expected.
         return np.fromstring(blob, dtype=dtype).reshape(*shape)
     else:
         return np.frombuffer(blob, dtype=dtype).reshape(*shape)

opensfm/actions/export_geocoords.py

@@ -146,7 +146,9 @@ def _transform_dense_point_cloud(
                     fout.write(line)
                 else:
                     x, y, z, nx, ny, nz, red, green, blue = line.split()
+                    # pyre-fixme[6]: For 2nd argument expected `Union[Sequence[Sequen...
                     x, y, z = np.dot(A, map(float, [x, y, z])) + b
+                    # pyre-fixme[6]: For 2nd argument expected `Union[Sequence[Sequen...
                     nx, ny, nz = np.dot(A, map(float, [nx, ny, nz]))
                     fout.write(
                         "{} {} {} {} {} {} {} {} {}\n".format(

opensfm/align.py

@@ -282,7 +282,11 @@ def compute_orientation_prior_similarity(
         max_scale = 1000
         current_scale = np.linalg.norm(b)
         if two_shots and current_scale > max_scale:
+            # pyre-fixme[58]: `/` is not supported for operand types `int` and
+            #  `floating[typing.Any]`.
             b = max_scale * b / current_scale
+            # pyre-fixme[58]: `/` is not supported for operand types `int` and
+            #  `floating[typing.Any]`.
             s = max_scale / current_scale
     else:
         try:

opensfm/dataset.py

@@ -334,6 +334,8 @@ def load_words(self, image: str) -> np.ndarray:
 
     def save_words(self, image: str, words: np.ndarray) -> None:
         with self.io_handler.open(self._words_file(image), "wb") as f:
+            # pyre-fixme[6]: For 1st argument expected `Union[_SupportsWrite[bytes],
+            #  PathLike[str], str]` but got `IO[typing.Any]`.
             np.savez_compressed(f, words=words.astype(np.uint16))
 
     def _matches_path(self) -> str:

opensfm/feature_loading.py

@@ -133,6 +133,7 @@ def _add_segmentation_in_descriptor(
             return features
 
         desc_augmented = np.concatenate(
+            # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[ty...
             (
                 features.descriptors,
                 (np.array([segmentation]).T).astype(np.float32),

opensfm/features_processing.py

@@ -219,6 +219,8 @@ def bake_segmentation(
             new_width=new_width,
             new_height=new_height,
         ).astype(int)
+        # pyre-fixme[6]: For 2nd argument expected `None` but got
+        #  `ndarray[typing.Any, typing.Any]`.
         panoptic_data[i] = p_data[ps[:, 1], ps[:, 0]]
     return tuple(panoptic_data)
 

opensfm/multiview.py

@@ -182,6 +182,9 @@ def ransac(kernel: Any, threshold: float) -> TRansacSolution:
                     max_iterations, ransac_max_iterations(kernel, best_inliers, 0.01)
                 )
         i += 1
+    # pyre-fixme[7]: Expected `Tuple[ndarray[typing.Any, typing.Any],
+    #  ndarray[typing.Any, typing.Any], float]` but got `Tuple[typing.Any,
+    #  Union[List[typing.Any], ndarray[typing.Any, dtype[typing.Any]]], typing.Any]`.
     return best_model, best_inliers, best_error
 
 
@@ -211,6 +214,8 @@ def num_samples(self) -> int:
     def fit(self, samples: np.ndarray) -> List[float]:
         x = self.x[samples[0]]
         y = self.y[samples[0]]
+        # pyre-fixme[7]: Expected `List[float]` but got `List[ndarray[typing.Any,
+        #  dtype[typing.Any]]]`.
         return [y / x]
 
     def evaluate(self, model: np.ndarray) -> np.ndarray:
@@ -416,6 +421,9 @@ def fit_similarity_transform(
         errors = np.sqrt(np.sum((p2h.T - np.dot(best_T, p1h.T)) ** 2, axis=0))
         best_inliers = np.argwhere(errors < threshold)[:, 0]
 
+    # pyre-fixme[7]: Expected `Tuple[ndarray[typing.Any, typing.Any],
+    #  ndarray[typing.Any, typing.Any]]` but got `Tuple[ndarray[typing.Any,
+    #  typing.Any], Union[List[typing.Any], ndarray[typing.Any, dtype[typing.Any]]]]`.
     return best_T, best_inliers
 
 
@@ -453,7 +461,9 @@ def focal_from_homography(H: np.ndarray) -> np.ndarray:
 def R_from_homography(
     H: np.ndarray, f1: np.ndarray, f2: np.ndarray
 ) -> Optional[np.ndarray]:
+    # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[typing.Any...
     K1 = np.diag([f1, f1, 1])
+    # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[typing.Any...
     K2 = np.diag([f2, f2, 1])
     K2inv = np.linalg.inv(K2)
     R = K2inv.dot(H).dot(K1)
@@ -464,7 +474,6 @@ def R_from_homography(
 def project_to_rotation_matrix(A: np.ndarray) -> Optional[np.ndarray]:
     try:
         u, d, vt = np.linalg.svd(A)
-    # pyre-fixme[16]: Module `linalg` has no attribute `LinAlgError`.
     except np.linalg.linalg.LinAlgError:
         return None
     return u.dot(vt)

opensfm/pairs_selection.py

@@ -472,6 +472,8 @@ def construct_pairs(
         order = np.argsort(distances)
         if enforce_other_cameras:
             pairs.update(
+                # pyre-fixme[6]: For 4th argument expected `List[int]` but got
+                #  `ndarray[typing.Any, dtype[typing.Any]]`.
                 pairs_from_neighbors(im, exifs, distances, order, other, max_neighbors)
             )
         else:

opensfm/reconstruction.py

@@ -284,6 +284,8 @@ def _two_view_reconstruction_inliers(
 ) -> List[int]:
     """Returns indices of matches that can be triangulated."""
     ok = matching.compute_inliers_bearings(b1, b2, R, t, threshold)
+    # pyre-fixme[7]: Expected `List[int]` but got `ndarray[typing.Any,
+    #  dtype[typing.Any]]`.
     return np.nonzero(ok)[0]
 
 
@@ -318,6 +320,7 @@ def two_view_reconstruction_plane_based(
         inliers = _two_view_reconstruction_inliers(b1, b2, R.T, -R.T.dot(t), threshold)
         motion_inliers.append(inliers)
 
+    # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[typing.Any...
     best = np.argmax(map(len, motion_inliers))
     R, t, n, d = motions[best]
     inliers = motion_inliers[best]
@@ -370,6 +373,8 @@ def _two_view_rotation_inliers(
 ) -> List[int]:
     br2 = R.dot(b2.T).T
     ok = np.linalg.norm(br2 - b1, axis=1) < threshold
+    # pyre-fixme[7]: Expected `List[int]` but got `ndarray[typing.Any,
+    #  dtype[typing.Any]]`.
     return np.nonzero(ok)[0]
 
 
@@ -1048,6 +1053,8 @@ def triangulate_dlt(
 
         if len(Rts) >= 2:
             e, X = pygeometry.triangulate_bearings_dlt(
+                # pyre-fixme[6]: For 1st argument expected `List[ndarray[typing.Any,
+                #  typing.Any]]` but got `ndarray[typing.Any, dtype[typing.Any]]`.
                 np.asarray(Rts),
                 np.asarray(bs),
                 reproj_threshold,

opensfm/synthetic_data/synthetic_generator.py

@@ -201,6 +201,8 @@ def _gps_dop(shot: pymap.Shot) -> float:
     ):
         pose = rig_instance.pose.get_origin()
         if previous_pose is not None:
+            # pyre-fixme[58]: `+` is not supported for operand types `int` and
+            #  `floating[typing.Any]`.
             previous_time += np.linalg.norm(pose - previous_pose) / speed_ms
         previous_pose = pose
         for shot_id in rig_instance.shots:

opensfm/synthetic_data/synthetic_scene.py

@@ -177,9 +177,11 @@ def __init__(
     def combine(self, other_scene: "SyntheticStreetScene") -> "SyntheticStreetScene":
         combined_scene = SyntheticStreetScene(None)
         combined_scene.wall_points = np.concatenate(
+            # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[ty...
             (self.wall_points, other_scene.wall_points)
         )
         combined_scene.floor_points = np.concatenate(
+            # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[ty...
             (self.floor_points, other_scene.floor_points)
         )
         combined_scene.cameras = self.cameras + other_scene.cameras
@@ -400,7 +402,11 @@ def get_reconstruction(self) -> types.Reconstruction:
         wall_color = [10, 90, 130]
 
         return sg.create_reconstruction(
+            # pyre-fixme[6]: For 1st argument expected `List[ndarray[typing.Any,
+            #  typing.Any]]` but got `ndarray[typing.Any, dtype[typing.Any]]`.
             points=np.asarray([self.floor_points, self.wall_points], dtype=object),
+            # pyre-fixme[6]: For 2nd argument expected `List[ndarray[typing.Any,
+            #  typing.Any]]` but got `ndarray[typing.Any, dtype[typing.Any]]`.
             colors=np.asarray([floor_color, wall_color]),
             cameras=self.cameras,
             shot_ids=self.shot_ids,

opensfm/test/test_bundle.py

@@ -108,18 +108,13 @@ def test_bundle_projection_fixed_internals(scene_synthetic) -> None:
                 color = g_obs["feature_color"]
                 pt = g_obs["feature"]
                 obs = pymap.Observation(
-                    # pyre-fixme[6]: For 1st argument expected `str` but got `int`.
                     pt[0],
-                    # pyre-fixme[6]: For 1st argument expected `str` but got `int`.
                     pt[1],
                     # pyre-fixme[6]: For 3rd argument expected `float` but got
                     #  `Dict[str, typing.Any]`.
                     g_obs["feature_scale"],
-                    # pyre-fixme[6]: For 1st argument expected `str` but got `int`.
                     color[0],
-                    # pyre-fixme[6]: For 1st argument expected `str` but got `int`.
                     color[1],
-                    # pyre-fixme[6]: For 1st argument expected `str` but got `int`.
                     color[2],
                     # pyre-fixme[6]: For 7th argument expected `int` but got
                     #  `Dict[str, typing.Any]`.

opensfm/test/test_dataset.py

@@ -26,6 +26,7 @@ def test_dataset_load_features_sift(tmpdir) -> None:
     after = data.load_features(image)
     assert after
     assert np.allclose(points, after.points)
+    # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[dtype[typing.Any...
     assert np.allclose(descriptors, after.descriptors)
     assert np.allclose(colors, after.colors)
     semantic = after.semantic
@@ -34,4 +35,5 @@ def test_dataset_load_features_sift(tmpdir) -> None:
         segmentations,
         semantic.segmentation,
     )
+    # pyre-fixme[6]: For 2nd argument expected `Union[_SupportsArray[dtype[typing.Any...
     assert np.allclose(instances, semantic.instances)

opensfm/test/test_multiview.py

@@ -21,7 +21,6 @@ def test_motion_from_plane_homography() -> None:
     scale = 2 * np.random.rand() - 1
     H = scale * (d * R - np.outer(t, n))
 
-    # pyre-fixme[6]: For 1st argument expected `ndarray` but got `int`.
     motions = multiview.motion_from_plane_homography(H)
     assert motions is not None
     goodness = []

opensfm/test/test_triangulation.py

@@ -50,6 +50,7 @@ def test_track_triangulator_spherical() -> None:
 
 
 def unit_vector(x: object) -> np.ndarray:
+    # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[typing.Any...
     return np.array(x) / np.linalg.norm(x)
 
 

opensfm/tracking.py

@@ -98,6 +98,10 @@ def create_tracks_manager(
                 instances[image][featureid] if image in instances else NO_VALUE,
             )
             obs = pymap.Observation(
+                # pyre-fixme[6]: For 8th argument expected `int` but got
+                #  `Union[ndarray[typing.Any, typing.Any], int]`.
+                # pyre-fixme[6]: For 9th argument expected `int` but got
+                #  `Union[ndarray[typing.Any, typing.Any], int]`.
                 x, y, s, int(r), int(g), int(b), featureid, segmentation, instance
             )
             tracks_manager.add_observation(image, str(track_id), obs)

opensfm/transformations.py

@@ -411,6 +411,7 @@ def scale_matrix(
     """
     if direction is None:
         # uniform scaling
+        # pyre-fixme[6]: For 1st argument expected `Union[_SupportsArray[dtype[typing...
         M = numpy.diag([factor, factor, factor, 1.0])
         if origin is not None:
             M[:3, 3] = origin[:3]
@@ -466,6 +467,10 @@ def scale_from_matrix(
         raise ValueError("no eigenvector corresponding to eigenvalue 1")
     origin = numpy.real(V[:, i[-1]]).squeeze()
     origin /= origin[3]
+    # pyre-fixme[7]: Expected `Tuple[ndarray[typing.Any, typing.Any],
+    #  ndarray[typing.Any, typing.Any], ndarray[typing.Any, typing.Any]]` but got
+    #  `Tuple[typing.Any, ndarray[typing.Any, dtype[typing.Any]],
+    #  Optional[ndarray[typing.Any, dtype[typing.Any]]]]`.
     return factor, origin, direction
 
 
@@ -1663,10 +1668,14 @@ def vector_norm(
         data *= data
         out = numpy.atleast_1d(numpy.sum(data, axis=axis))
         numpy.sqrt(out, out)
+        # pyre-fixme[7]: Expected `float` but got `ndarray[typing.Any,
+        #  dtype[typing.Any]]`.
         return out
     else:
         data *= data
         numpy.sum(data, axis=axis, out=out)
+        # pyre-fixme[7]: Expected `float` but got `ndarray[typing.Any,
+        #  dtype[typing.Any]]`.
         return numpy.sqrt(out, out)
 
 
@@ -1832,6 +1841,7 @@ def is_same_transform(matrix0: numpy.ndarray, matrix1: numpy.ndarray) -> numpy.n
     matrix0 /= matrix0[3, 3]
     matrix1 = numpy.array(matrix1, dtype=numpy.float64, copy=True)
     matrix1 /= matrix1[3, 3]
+    # pyre-fixme[7]: Expected `ndarray[typing.Any, typing.Any]` but got `bool`.
     return numpy.allclose(matrix0, matrix1)