From 8e91907214a06f2d3ef2d40e849a1280dee74af0 Mon Sep 17 00:00:00 2001
From: Oleh Prypin <oprypin@google.com>
Date: Wed, 7 Oct 2026 06:39:00 -0700
Subject: [PATCH] Replace `# pytype: disable` suppressions with `# pyrefly:
 ignore`

PiperOrigin-RevId: 995072436
---
 .../geometry/convolution/graph_convolution.py |  4 ++--
 .../geometry/convolution/graph_pooling.py     |  6 ++---
 .../geometry/convolution/utils.py             | 10 ++++-----
 .../geometry/representation/grid.py           |  2 +-
 .../geometry/representation/point.py          |  4 ++--
 .../geometry/representation/ray.py            | 10 ++++-----
 .../geometry/representation/triangle.py       |  4 ++--
 tensorflow_graphics/image/matting.py          | 10 ++++-----
 tensorflow_graphics/image/pyramid.py          |  8 +++----
 tensorflow_graphics/image/transformer.py      |  4 ++--
 .../math/interpolation/bspline.py             | 22 +++++++++----------
 .../math/interpolation/slerp.py               |  6 ++---
 .../math/interpolation/trilinear.py           |  2 +-
 .../math/interpolation/weighted.py            |  4 ++--
 tensorflow_graphics/nn/metric/fscore.py       |  2 +-
 .../nn/metric/intersection_over_union.py      |  2 +-
 tensorflow_graphics/nn/metric/precision.py    |  2 +-
 tensorflow_graphics/nn/metric/recall.py       |  2 +-
 .../rendering/camera/orthographic.py          |  6 ++---
 .../rendering/camera/perspective.py           | 18 +++++++--------
 .../camera/quadratic_radial_distortion.py     |  4 ++--
 .../rendering/reflectance/blinn_phong.py      |  2 +-
 .../rendering/reflectance/lambertian.py       |  2 +-
 .../rendering/reflectance/phong.py            |  2 +-
 tensorflow_graphics/util/asserts.py           | 16 +++++++-------
 tensorflow_graphics/util/safe_ops.py          | 16 +++++++-------
 26 files changed, 85 insertions(+), 85 deletions(-)

diff --git a/tensorflow_graphics/geometry/convolution/graph_convolution.py b/tensorflow_graphics/geometry/convolution/graph_convolution.py
index e54203884..720499549 100644
--- a/tensorflow_graphics/geometry/convolution/graph_convolution.py
+++ b/tensorflow_graphics/geometry/convolution/graph_convolution.py
@@ -96,7 +96,7 @@ def feature_steered_convolution(
     ValueError: if the input dimensions are invalid.
   """
   #  pyformat: enable
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     neighbors = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=neighbors)
     if sizes is not None:
@@ -239,7 +239,7 @@ def edge_convolution_template(
     ValueError: if the input dimensions are invalid.
   """
   #  pyformat: enable
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     neighbors = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=neighbors)
     if sizes is not None:
diff --git a/tensorflow_graphics/geometry/convolution/graph_pooling.py b/tensorflow_graphics/geometry/convolution/graph_pooling.py
index ace3dab23..d93a6f1d3 100644
--- a/tensorflow_graphics/geometry/convolution/graph_pooling.py
+++ b/tensorflow_graphics/geometry/convolution/graph_pooling.py
@@ -74,7 +74,7 @@ def pool(data: type_alias.TensorLike,
     ValueError: if `algorithm` is invalid.
   """
   #  pyformat: enable
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     pool_map = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=pool_map)
     if sizes is not None:
@@ -161,7 +161,7 @@ def unpool(data: type_alias.TensorLike,
     ValueError: if the input dimensions are invalid.
   """
   #  pyformat: enable
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     pool_map = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=pool_map)
     if sizes is not None:
@@ -253,7 +253,7 @@ def upsample_transposed_convolution(
     ValueError: if the input dimensions are invalid.
   """
   #  pyformat: enable
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     pool_map = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=pool_map)
     if sizes is not None:
diff --git a/tensorflow_graphics/geometry/convolution/utils.py b/tensorflow_graphics/geometry/convolution/utils.py
index 88616b194..25ec9f233 100644
--- a/tensorflow_graphics/geometry/convolution/utils.py
+++ b/tensorflow_graphics/geometry/convolution/utils.py
@@ -249,7 +249,7 @@ def flatten_batch_to_2d(data: type_alias.TensorLike,
   Raises:
     ValueError: if the input tensor dimensions are invalid.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     if sizes is not None:
       sizes = tf.convert_to_tensor(value=sizes)
@@ -272,7 +272,7 @@ def flatten_batch_to_2d(data: type_alias.TensorLike,
 
       def unflatten(flat, name="utils_unflatten"):
         """Invert flatten_batch_to_2d."""
-        with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+        with tf.name_scope(name):
           flat = tf.convert_to_tensor(value=flat)
           output_shape = tf.concat((data_shape[:-1], tf.shape(input=flat)[-1:]),
                                    axis=0)
@@ -288,7 +288,7 @@ def unflatten(flat, name="utils_unflatten"):
 
       def unflatten(flat, name="utils_unflatten"):
         """Invert flatten_batch_to_2d."""
-        with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+        with tf.name_scope(name):
           flat = tf.convert_to_tensor(value=flat)
           output_shape = tf.concat((data_shape[:-1], tf.shape(input=flat)[-1:]),
                                    axis=0)
@@ -362,7 +362,7 @@ def unflatten_2d_to_batch(data: type_alias.TensorLike,
   Returns:
     A tensor with shape `[A1, A2, ..., max_rows, D2]`.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.convert_to_tensor(value=data)
     sizes = tf.convert_to_tensor(value=sizes)
     if max_rows is None:
@@ -418,7 +418,7 @@ def convert_to_block_diag_2d(data: tf.sparse.SparseTensor,
     TypeError: if the input types are invalid.
     ValueError: if the input dimensions are invalid.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     data = tf.compat.v1.convert_to_tensor_or_sparse_tensor(value=data)
     if sizes is not None:
       sizes = tf.convert_to_tensor(value=sizes)
diff --git a/tensorflow_graphics/geometry/representation/grid.py b/tensorflow_graphics/geometry/representation/grid.py
index 9d6676724..182e2ed33 100644
--- a/tensorflow_graphics/geometry/representation/grid.py
+++ b/tensorflow_graphics/geometry/representation/grid.py
@@ -98,7 +98,7 @@ def generate(starts, stops, nums, name="grid_generate"):
     axis and from -2.0 to 2.0 with 5 subdivisions for the y axis. This lead to a
     tensor of shape (3, 5, 2).
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     starts = tf.convert_to_tensor(value=starts)
     stops = tf.convert_to_tensor(value=stops)
     nums = tf.convert_to_tensor(value=nums)
diff --git a/tensorflow_graphics/geometry/representation/point.py b/tensorflow_graphics/geometry/representation/point.py
index ad561b799..9fca99824 100644
--- a/tensorflow_graphics/geometry/representation/point.py
+++ b/tensorflow_graphics/geometry/representation/point.py
@@ -55,7 +55,7 @@ def distance_to_ray(point: type_alias.TensorLike,
     ValueError: If the shape of `point`, `origin`, or 'direction' is not
     supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point = tf.convert_to_tensor(value=point)
     origin = tf.convert_to_tensor(value=origin)
     direction = tf.convert_to_tensor(value=direction)
@@ -99,7 +99,7 @@ def project_to_ray(point: type_alias.TensorLike,
     ValueError: If the shape of `point`, `origin`, or 'direction' is not
     supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point = tf.convert_to_tensor(value=point)
     origin = tf.convert_to_tensor(value=origin)
     direction = tf.convert_to_tensor(value=direction)
diff --git a/tensorflow_graphics/geometry/representation/ray.py b/tensorflow_graphics/geometry/representation/ray.py
index bf9dd04e9..0a9cfb182 100644
--- a/tensorflow_graphics/geometry/representation/ray.py
+++ b/tensorflow_graphics/geometry/representation/ray.py
@@ -92,7 +92,7 @@ def sample_1d(
     A tensor of shape `[A1, ..., An, M, 3]` indicating the M points on the ray
       and a tensor of shape `[A1, ..., An, M]` for the Z values on the points.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ray_org = tf.convert_to_tensor(ray_org)
     ray_dir = tf.convert_to_tensor(ray_dir)
     near = tf.convert_to_tensor(near) * tf.ones((1,))
@@ -175,7 +175,7 @@ def sample_stratified_1d(
     A tensor of shape `[A1, ..., An, M, 3]` indicating the M points on the ray
       and a tensor of shape `[A1, ..., An, M]` for the Z values on the points.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ray_org = tf.convert_to_tensor(ray_org)
     ray_dir = tf.convert_to_tensor(ray_dir)
     near = tf.convert_to_tensor(near) * tf.ones((1,))
@@ -245,7 +245,7 @@ def sample_inverse_transform_stratified_1d(
     A tensor of shape `[A1, ..., An, M, 3]` indicating the M points on the ray
       and a tensor of shape `[A1, ..., An, M]` for the Z values on the points.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     shape.check_static(
         tensor=ray_org,
         tensor_name="ray_org",
@@ -312,7 +312,7 @@ def triangulate(startpoints, endpoints, weights, name="ray_triangulate"):
   Raises:
     ValueError: If the shape of the arguments is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     startpoints = tf.convert_to_tensor(value=startpoints)
     endpoints = tf.convert_to_tensor(value=endpoints)
     weights = tf.convert_to_tensor(value=weights)
@@ -403,7 +403,7 @@ def intersection_ray_sphere(sphere_center,
       `point_on_ray` is not supported.
     tf.errors.InvalidArgumentError: If `ray` is not normalized.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     sphere_center = tf.convert_to_tensor(value=sphere_center)
     sphere_radius = tf.convert_to_tensor(value=sphere_radius)
     ray = tf.convert_to_tensor(value=ray)
diff --git a/tensorflow_graphics/geometry/representation/triangle.py b/tensorflow_graphics/geometry/representation/triangle.py
index 27a732166..0c6dda5b3 100644
--- a/tensorflow_graphics/geometry/representation/triangle.py
+++ b/tensorflow_graphics/geometry/representation/triangle.py
@@ -57,7 +57,7 @@ def normal(v0: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `v0`, `v1`, or `v2` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     v0 = tf.convert_to_tensor(value=v0)
     v1 = tf.convert_to_tensor(value=v1)
     v2 = tf.convert_to_tensor(value=v2)
@@ -104,7 +104,7 @@ def area(v0: type_alias.TensorLike,
     A tensor of shape `[A1, ..., An, 1]`, where the last dimension represents
       a normalized vector.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     v0 = tf.convert_to_tensor(value=v0)
     v1 = tf.convert_to_tensor(value=v1)
     v2 = tf.convert_to_tensor(value=v2)
diff --git a/tensorflow_graphics/image/matting.py b/tensorflow_graphics/image/matting.py
index 0d98cda0f..1554b7cd9 100644
--- a/tensorflow_graphics/image/matting.py
+++ b/tensorflow_graphics/image/matting.py
@@ -131,7 +131,7 @@ def build_matrices(image: type_alias.TensorLike,
   Raises:
     ValueError: If `image` is not of rank 4.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image)
     eps = tf.constant(value=eps, dtype=image.dtype)
 
@@ -192,7 +192,7 @@ def linear_coefficients(matte: type_alias.TensorLike,
     of rank 4. If `pseudo_inverse` is not of rank 5. If `B` is different
     between `matte` and `pseudo_inverse`.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     matte = tf.convert_to_tensor(value=matte)
     pseudo_inverse = tf.convert_to_tensor(value=pseudo_inverse)
 
@@ -216,7 +216,7 @@ def linear_coefficients(matte: type_alias.TensorLike,
     width = tf.shape(input=matte)[2] + size - 1
     coeffs = tf.image.resize_with_crop_or_pad(coeffs, height, width)
     ones = tf.image.resize_with_crop_or_pad(ones, height, width)
-    coeffs = _image_average(coeffs, size) / _image_average(ones, size)  # pyrefly: ignore[unsupported-operation]
+    coeffs = _image_average(coeffs, size) / _image_average(ones, size)
     return tf.split(coeffs, (-1, 1), axis=-1)
 
 
@@ -246,7 +246,7 @@ def loss(matte: type_alias.TensorLike,
     same size. If `laplacian` is not of rank 5. If `B` is different
     between `matte` and `laplacian`.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     matte = tf.convert_to_tensor(value=matte)
     laplacian = tf.convert_to_tensor(value=laplacian)
 
@@ -287,7 +287,7 @@ def reconstruct(image: type_alias.TensorLike,
     the last dimension of `coeff_add` is not 1. If the batch dimensions of
     `image`, `coeff_mul`, and `coeff_add` do not match.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image)
     coeff_mul = tf.convert_to_tensor(value=coeff_mul)
     coeff_add = tf.convert_to_tensor(value=coeff_add)
diff --git a/tensorflow_graphics/image/pyramid.py b/tensorflow_graphics/image/pyramid.py
index cffc4da22..f596425ee 100644
--- a/tensorflow_graphics/image/pyramid.py
+++ b/tensorflow_graphics/image/pyramid.py
@@ -170,7 +170,7 @@ def downsample(image: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `image` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image)
 
     shape.check_static(tensor=image, tensor_name="image", has_rank=4)
@@ -196,7 +196,7 @@ def merge(levels: List[type_alias.TensorLike],
   Raises:
     ValueError: If the shape of the elements of `levels` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     levels = [tf.convert_to_tensor(value=level) for level in levels]
 
     for index, level in enumerate(levels):
@@ -229,7 +229,7 @@ def split(image: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `image` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image)
 
     shape.check_static(tensor=image, tensor_name="image", has_rank=4)
@@ -264,7 +264,7 @@ def upsample(image: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `image` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image)
 
     shape.check_static(tensor=image, tensor_name="image", has_rank=4)
diff --git a/tensorflow_graphics/image/transformer.py b/tensorflow_graphics/image/transformer.py
index d27f994a7..ff3ac5bc9 100644
--- a/tensorflow_graphics/image/transformer.py
+++ b/tensorflow_graphics/image/transformer.py
@@ -77,7 +77,7 @@ def sample(image: type_alias.TensorLike,
     ValueError: If `image` has rank != 4. If `warp` has rank < 2 or its last
     dimension is not 2. If `image` and `warp` batch dimension does not match.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image, name="image")
     warp = tf.convert_to_tensor(value=warp, name="warp")
 
@@ -154,7 +154,7 @@ def perspective_transform(
     its last two dimensions are not 3. If `image` and `transform_matrix` batch
     dimension does not match.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     image = tf.convert_to_tensor(value=image, name="image")
     transform_matrix = tf.convert_to_tensor(
         value=transform_matrix, name="transform_matrix")
diff --git a/tensorflow_graphics/math/interpolation/bspline.py b/tensorflow_graphics/math/interpolation/bspline.py
index 3fe6c4088..1c7efac3a 100644
--- a/tensorflow_graphics/math/interpolation/bspline.py
+++ b/tensorflow_graphics/math/interpolation/bspline.py
@@ -44,13 +44,13 @@ class Degree(enum.IntEnum):
 def _constant(position: tf.Tensor) -> tf.Tensor:
   """B-Spline basis function of degree 0 for positions in the range [0, 1]."""
   # A piecewise constant spline is discontinuous at the knots.
-  return tf.expand_dims(tf.clip_by_value(1.0 + position, 1.0, 1.0), axis=-1)  # pyrefly: ignore[unsupported-operation]
+  return tf.expand_dims(tf.clip_by_value(1.0 + position, 1.0, 1.0), axis=-1)
 
 
 def _linear(position: tf.Tensor) -> tf.Tensor:
   """B-Spline basis functions of degree 1 for positions in the range [0, 1]."""
   # Piecewise linear splines are C0 smooth.
-  return tf.stack((1.0 - position, position), axis=-1)  # pyrefly: ignore[unsupported-operation]
+  return tf.stack((1.0 - position, position), axis=-1)
 
 
 def _quadratic(position: tf.Tensor) -> tf.Tensor:
@@ -59,7 +59,7 @@ def _quadratic(position: tf.Tensor) -> tf.Tensor:
   pos_sq = tf.pow(position, 2.0)
 
   # Piecewise quadratic splines are C1 smooth.
-  return tf.stack((tf.pow(1.0 - position, 2.0) / 2.0, -pos_sq + position + 0.5,  # pyrefly: ignore[unsupported-operation]
+  return tf.stack((tf.pow(1.0 - position, 2.0) / 2.0, -pos_sq + position + 0.5,
                    pos_sq / 2.0),
                   axis=-1)
 
@@ -67,14 +67,14 @@ def _quadratic(position: tf.Tensor) -> tf.Tensor:
 def _cubic(position: tf.Tensor) -> tf.Tensor:
   """B-Spline basis functions of degree 3 for positions in the range [0, 1]."""
   # We pre-calculate the terms that are used multiple times.
-  neg_pos = 1.0 - position  # pyrefly: ignore[unsupported-operation]
+  neg_pos = 1.0 - position
   pos_sq = tf.pow(position, 2.0)
   pos_cb = tf.pow(position, 3.0)
 
   # Piecewise cubic splines are C2 smooth.
   return tf.stack(
       (tf.pow(neg_pos, 3.0) / 6.0, (3.0 * pos_cb - 6.0 * pos_sq + 4.0) / 6.0,
-       (-3.0 * pos_cb + 3.0 * pos_sq + 3.0 * position + 1.0) / 6.0,  # pyrefly: ignore[unsupported-operation]
+       (-3.0 * pos_cb + 3.0 * pos_sq + 3.0 * position + 1.0) / 6.0,
        pos_cb / 6.0),
       axis=-1)
 
@@ -82,7 +82,7 @@ def _cubic(position: tf.Tensor) -> tf.Tensor:
 def _quartic(position: tf.Tensor) -> tf.Tensor:
   """B-Spline basis functions of degree 4 for positions in the range [0, 1]."""
   # We pre-calculate the terms that are used multiple times.
-  neg_pos = 1.0 - position  # pyrefly: ignore[unsupported-operation]
+  neg_pos = 1.0 - position
   pos_sq = tf.pow(position, 2.0)
   pos_cb = tf.pow(position, 3.0)
   pos_qt = tf.pow(position, 4.0)
@@ -92,8 +92,8 @@ def _quartic(position: tf.Tensor) -> tf.Tensor:
       (tf.pow(neg_pos, 4.0) / 24.0,
        (-4.0 * tf.pow(neg_pos, 4.0) + 4.0 * tf.pow(neg_pos, 3.0) +
         6.0 * tf.pow(neg_pos, 2.0) + 4.0 * neg_pos + 1.0) / 24.0,
-       (pos_qt - 2.0 * pos_cb - pos_sq + 2.0 * position) / 4.0 + 11.0 / 24.0,  # pyrefly: ignore[unsupported-operation]
-       (-4.0 * pos_qt + 4.0 * pos_cb + 6.0 * pos_sq + 4.0 * position + 1.0) /  # pyrefly: ignore[unsupported-operation]
+       (pos_qt - 2.0 * pos_cb - pos_sq + 2.0 * position) / 4.0 + 11.0 / 24.0,
+       (-4.0 * pos_qt + 4.0 * pos_cb + 6.0 * pos_sq + 4.0 * position + 1.0) /
        24.0, pos_qt / 24.0),
       axis=-1)
 
@@ -137,7 +137,7 @@ def knot_weights(
     ValueError: If degree is greater than 4 or num_knots - 1, or less than 0.
     InvalidArgumentError: If positions are not in the right range.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     positions = tf.convert_to_tensor(value=positions)
 
     if degree > 4 or degree < 0:
@@ -236,7 +236,7 @@ def interpolate_with_weights(
   Raises:
     ValueError: If the last dimension of knots and weights is not equal.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     knots = tf.convert_to_tensor(value=knots)
     weights = tf.convert_to_tensor(value=weights)
 
@@ -271,7 +271,7 @@ def interpolate(knots: type_alias.TensorLike,
     A tensor of shape `[A1, ... An, B1, ..., Bk]`, which is the result of spline
     interpolation.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     knots = tf.convert_to_tensor(value=knots)
     positions = tf.convert_to_tensor(value=positions)
 
diff --git a/tensorflow_graphics/math/interpolation/slerp.py b/tensorflow_graphics/math/interpolation/slerp.py
index b333532cd..9fd20091c 100644
--- a/tensorflow_graphics/math/interpolation/slerp.py
+++ b/tensorflow_graphics/math/interpolation/slerp.py
@@ -142,7 +142,7 @@ def interpolate_with_weights(
     A tensor of shape `[A1, ... , An, M]` containing the result of the
     interpolation.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     return weight1 * vector1 + weight2 * vector2
 
 
@@ -185,7 +185,7 @@ def quaternion_weights(
     Two tensors of shape `[A1, ... , An, 1]` each, which are the two slerp
       weights for each quaternion.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     quaternion1 = tf.convert_to_tensor(value=quaternion1)
     quaternion2 = tf.convert_to_tensor(value=quaternion2)
     percent = tf.convert_to_tensor(value=percent, dtype=quaternion1.dtype)
@@ -253,7 +253,7 @@ def vector_weights(vector1: type_alias.TensorLike,
     Two tensors of shape `[A1, ... , An, 1]`, representing interpolation weights
     for each input vector.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector1 = tf.convert_to_tensor(value=vector1)
     vector2 = tf.convert_to_tensor(value=vector2)
     percent = tf.convert_to_tensor(value=percent, dtype=vector1.dtype)
diff --git a/tensorflow_graphics/math/interpolation/trilinear.py b/tensorflow_graphics/math/interpolation/trilinear.py
index d577aab10..35230aa9a 100644
--- a/tensorflow_graphics/math/interpolation/trilinear.py
+++ b/tensorflow_graphics/math/interpolation/trilinear.py
@@ -41,7 +41,7 @@ def interpolate(grid_3d: type_alias.TensorLike,
     A tensor of shape `[A1, ..., An, M, C]`
   """
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     grid_3d = tf.convert_to_tensor(value=grid_3d)
     sampling_points = tf.convert_to_tensor(value=sampling_points)
 
diff --git a/tensorflow_graphics/math/interpolation/weighted.py b/tensorflow_graphics/math/interpolation/weighted.py
index 86d0c53eb..3f1151341 100644
--- a/tensorflow_graphics/math/interpolation/weighted.py
+++ b/tensorflow_graphics/math/interpolation/weighted.py
@@ -61,7 +61,7 @@ def interpolate(points: type_alias.TensorLike,
     A tensor of shape `[A1, ..., An, M]` storing the interpolated M-D
     points. The first n dimensions will be the same as weights and indices.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     points = tf.convert_to_tensor(value=points)
     weights = tf.convert_to_tensor(value=weights)
     indices = tf.convert_to_tensor(value=indices)
@@ -128,7 +128,7 @@ def get_barycentric_coordinates(
     valid: A boolean tensor of shape `[A1, ..., An, N], which is `True` where
       pixels are inside the triangle, and `False` otherwise.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     triangle_vertices = tf.convert_to_tensor(value=triangle_vertices)
     pixels = tf.convert_to_tensor(value=pixels)
 
diff --git a/tensorflow_graphics/nn/metric/fscore.py b/tensorflow_graphics/nn/metric/fscore.py
index 31396da24..8bb696c39 100644
--- a/tensorflow_graphics/nn/metric/fscore.py
+++ b/tensorflow_graphics/nn/metric/fscore.py
@@ -66,7 +66,7 @@ def evaluate(ground_truth: type_alias.TensorLike,
     ValueError: if the shape of `ground_truth`, `prediction` is
     not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ground_truth = tf.convert_to_tensor(value=ground_truth)
     prediction = tf.convert_to_tensor(value=prediction)
 
diff --git a/tensorflow_graphics/nn/metric/intersection_over_union.py b/tensorflow_graphics/nn/metric/intersection_over_union.py
index 8daa9b550..bbfbca76d 100644
--- a/tensorflow_graphics/nn/metric/intersection_over_union.py
+++ b/tensorflow_graphics/nn/metric/intersection_over_union.py
@@ -54,7 +54,7 @@ def evaluate(ground_truth_labels: type_alias.TensorLike,
     ValueError: if the shape of `ground_truth_labels`, `predicted_labels` is
     not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ground_truth_labels = tf.convert_to_tensor(value=ground_truth_labels)
     predicted_labels = tf.convert_to_tensor(value=predicted_labels)
 
diff --git a/tensorflow_graphics/nn/metric/precision.py b/tensorflow_graphics/nn/metric/precision.py
index 58a2c6ff5..814a82fb1 100644
--- a/tensorflow_graphics/nn/metric/precision.py
+++ b/tensorflow_graphics/nn/metric/precision.py
@@ -66,7 +66,7 @@ class and return a single precision value. Defaults to true.
   Raises:
     ValueError: if the shape of `ground_truth`, `prediction` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ground_truth = tf.cast(
         x=tf.convert_to_tensor(value=ground_truth), dtype=tf.int32)
     prediction = tf.convert_to_tensor(value=prediction)
diff --git a/tensorflow_graphics/nn/metric/recall.py b/tensorflow_graphics/nn/metric/recall.py
index e068d0f5a..7e82be870 100644
--- a/tensorflow_graphics/nn/metric/recall.py
+++ b/tensorflow_graphics/nn/metric/recall.py
@@ -66,7 +66,7 @@ class and return a single recall value. Defaults to true.
   Raises:
     ValueError: if the shape of `ground_truth`, `prediction` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     ground_truth = tf.cast(
         x=tf.convert_to_tensor(value=ground_truth), dtype=tf.int32)
     prediction = tf.convert_to_tensor(value=prediction)
diff --git a/tensorflow_graphics/rendering/camera/orthographic.py b/tensorflow_graphics/rendering/camera/orthographic.py
index 05d17159f..44f6ab0a0 100644
--- a/tensorflow_graphics/rendering/camera/orthographic.py
+++ b/tensorflow_graphics/rendering/camera/orthographic.py
@@ -59,7 +59,7 @@ def project(point_3d: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `point_3d` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_3d = tf.convert_to_tensor(value=point_3d)
 
     shape.check_static(
@@ -97,7 +97,7 @@ def ray(point_2d: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `point_2d` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_2d = tf.convert_to_tensor(value=point_2d)
 
     shape.check_static(
@@ -139,7 +139,7 @@ def unproject(point_2d: type_alias.TensorLike,
   Raises:
     ValueError: If the shape of `point_2d`, `depth` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_2d = tf.convert_to_tensor(value=point_2d)
     depth = tf.convert_to_tensor(value=depth)
 
diff --git a/tensorflow_graphics/rendering/camera/perspective.py b/tensorflow_graphics/rendering/camera/perspective.py
index e7368beb7..0efc0648f 100644
--- a/tensorflow_graphics/rendering/camera/perspective.py
+++ b/tensorflow_graphics/rendering/camera/perspective.py
@@ -82,7 +82,7 @@ def parameters_from_right_handed(
     represent the near and far clipping planes used to construct
     `projection_matrix`.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     projection_matrix = tf.convert_to_tensor(value=projection_matrix)
 
     shape.check_static(
@@ -141,7 +141,7 @@ def right_handed(vertical_field_of_view: type_alias.TensorLike,
     A tensor of shape `[A1, ..., An, 4, 4]`, containing matrices of right
     handed perspective-view frustum.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vertical_field_of_view = tf.convert_to_tensor(value=vertical_field_of_view)
     aspect_ratio = tf.convert_to_tensor(value=aspect_ratio)
     near = tf.convert_to_tensor(value=near)
@@ -220,7 +220,7 @@ def intrinsics_from_matrix(
   Raises:
     ValueError: If the shape of `matrix` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     matrix = tf.convert_to_tensor(value=matrix)
 
     shape.check_static(
@@ -281,7 +281,7 @@ def matrix_from_intrinsics(
     ValueError: If the shape of `focal`, or `principal_point` is not
     supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     focal = tf.convert_to_tensor(value=focal)
     principal_point = tf.convert_to_tensor(value=principal_point)
     skew = tf.convert_to_tensor(value=skew)
@@ -363,7 +363,7 @@ def project(point_3d: type_alias.TensorLike,
     ValueError: If the shape of `point_3d`, `focal`, or `principal_point` is not
     supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_3d = tf.convert_to_tensor(value=point_3d)
     focal = tf.convert_to_tensor(value=focal)
     principal_point = tf.convert_to_tensor(value=principal_point)
@@ -427,7 +427,7 @@ def ray(point_2d: type_alias.TensorLike,
     ValueError: If the shape of `point_2d`, `focal`, or `principal_point` is not
     supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_2d = tf.convert_to_tensor(value=point_2d)
     focal = tf.convert_to_tensor(value=focal)
     principal_point = tf.convert_to_tensor(value=principal_point)
@@ -478,7 +478,7 @@ def random_rays(focal: tf.Tensor,
     A tensor of shape `[A1, ..., An, M, 3]` with the ray directions and
     a tensor of shape `[A1, ..., An, M, 2]` with the pixel x, y locations.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     focal = tf.convert_to_tensor(value=focal)
     principal_point = tf.convert_to_tensor(value=principal_point)
 
@@ -531,7 +531,7 @@ def random_patches(focal: tf.Tensor,
       ray directions in 3D passing from the M*N pixels of the patch and
     a tensor of shape `[A1, ..., An, M*N, 2]` with the pixel x, y locations.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     focal = tf.convert_to_tensor(value=focal)
     principal_point = tf.convert_to_tensor(value=principal_point)
 
@@ -619,7 +619,7 @@ def unproject(point_2d: type_alias.TensorLike,
     ValueError: If the shape of `point_2d`, `depth`, `focal`, or
     `principal_point` is not supported.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     point_2d = tf.convert_to_tensor(value=point_2d)
     depth = tf.convert_to_tensor(value=depth)
     focal = tf.convert_to_tensor(value=focal)
diff --git a/tensorflow_graphics/rendering/camera/quadratic_radial_distortion.py b/tensorflow_graphics/rendering/camera/quadratic_radial_distortion.py
index 9d3e9900e..fea19fce9 100644
--- a/tensorflow_graphics/rendering/camera/quadratic_radial_distortion.py
+++ b/tensorflow_graphics/rendering/camera/quadratic_radial_distortion.py
@@ -79,7 +79,7 @@ def distortion_factor(
       monotonically increasing. Wherever `overflow_mask` is True,
       `distortion_factor`'s value is meaningless.
   """
-  with tf.name_scope(name,):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name,):
     squared_radius = tf.convert_to_tensor(value=squared_radius)
     distortion_coefficient = tf.convert_to_tensor(value=distortion_coefficient)
 
@@ -154,7 +154,7 @@ def undistortion_factor(
       `undistortion_factor`'s value is meaningless.
 
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     distorted_squared_radius = tf.convert_to_tensor(
         value=distorted_squared_radius)
     distortion_coefficient = tf.convert_to_tensor(value=distortion_coefficient)
diff --git a/tensorflow_graphics/rendering/reflectance/blinn_phong.py b/tensorflow_graphics/rendering/reflectance/blinn_phong.py
index e013418fc..ec5f75012 100644
--- a/tensorflow_graphics/rendering/reflectance/blinn_phong.py
+++ b/tensorflow_graphics/rendering/reflectance/blinn_phong.py
@@ -89,7 +89,7 @@ def brdf(direction_incoming_light: type_alias.TensorLike,
     InvalidArgumentError: if not all of shininess values are non-negative, or if
     at least one element of `albedo` is outside of [0,1].
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     direction_incoming_light = tf.convert_to_tensor(
         value=direction_incoming_light)
     direction_outgoing_light = tf.convert_to_tensor(
diff --git a/tensorflow_graphics/rendering/reflectance/lambertian.py b/tensorflow_graphics/rendering/reflectance/lambertian.py
index c2046f4ed..4b38c86b7 100644
--- a/tensorflow_graphics/rendering/reflectance/lambertian.py
+++ b/tensorflow_graphics/rendering/reflectance/lambertian.py
@@ -65,7 +65,7 @@ def brdf(direction_incoming_light: type_alias.TensorLike,
     InvalidArgumentError: if at least one element of `albedo` is outside of
     [0,1].
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     direction_incoming_light = tf.convert_to_tensor(
         value=direction_incoming_light)
     direction_outgoing_light = tf.convert_to_tensor(
diff --git a/tensorflow_graphics/rendering/reflectance/phong.py b/tensorflow_graphics/rendering/reflectance/phong.py
index cd66269db..a0a584c86 100644
--- a/tensorflow_graphics/rendering/reflectance/phong.py
+++ b/tensorflow_graphics/rendering/reflectance/phong.py
@@ -85,7 +85,7 @@ def brdf(direction_incoming_light: type_alias.TensorLike,
     InvalidArgumentError: if not all of shininess values are non-negative, or if
     at least one element of `albedo` is outside of [0,1].
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     direction_incoming_light = tf.convert_to_tensor(
         value=direction_incoming_light)
     direction_outgoing_light = tf.convert_to_tensor(
diff --git a/tensorflow_graphics/util/asserts.py b/tensorflow_graphics/util/asserts.py
index 862dc6696..874cd5dc9 100644
--- a/tensorflow_graphics/util/asserts.py
+++ b/tensorflow_graphics/util/asserts.py
@@ -51,7 +51,7 @@ def assert_no_infs_or_nans(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return tensor
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     tensor = tf.convert_to_tensor(value=tensor)
 
     assert_ops = (tf.debugging.check_numerics(
@@ -87,7 +87,7 @@ def assert_all_above(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return vector
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     minval = tf.convert_to_tensor(value=minval, dtype=vector.dtype)
 
@@ -126,7 +126,7 @@ def assert_all_below(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return vector
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     maxval = tf.convert_to_tensor(value=maxval, dtype=vector.dtype)
 
@@ -172,7 +172,7 @@ def assert_all_in_range(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return vector
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     minval = tf.convert_to_tensor(value=minval, dtype=vector.dtype)
     maxval = tf.convert_to_tensor(value=maxval, dtype=vector.dtype)
@@ -218,7 +218,7 @@ def assert_nonzero_norm(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return vector
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     if eps is None:
       eps = select_eps_for_division(vector.dtype)
@@ -258,7 +258,7 @@ def assert_normalized(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return vector
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     if eps is None:
       eps = select_eps_for_division(vector.dtype)
@@ -298,7 +298,7 @@ def assert_at_least_k_non_zero_entries(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return tensor
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     tensor = tf.convert_to_tensor(value=tensor)
 
     indicator = tf.cast(tf.math.greater(tensor, 0.0), dtype=tensor.dtype)
@@ -329,7 +329,7 @@ def assert_binary(
   if not FLAGS[tfg_flags.TFG_ADD_ASSERTS_TO_GRAPH].value:
     return tensor
 
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     tensor = tf.convert_to_tensor(value=tensor)
     condition = tf.reduce_all(
         input_tensor=tf.logical_or(tf.equal(tensor, 0), tf.equal(tensor, 1)))
diff --git a/tensorflow_graphics/util/safe_ops.py b/tensorflow_graphics/util/safe_ops.py
index 7c2ce7b9c..7a174d265 100644
--- a/tensorflow_graphics/util/safe_ops.py
+++ b/tensorflow_graphics/util/safe_ops.py
@@ -38,7 +38,7 @@ def nonzero_sign(
     x: type_alias.TensorLike,
     name: str = 'nonzero_sign') -> tf.Tensor:
   """Returns the sign of x with sign(0) defined as 1 instead of 0."""
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     x = tf.convert_to_tensor(value=x)
 
     one = tf.ones_like(x)
@@ -76,7 +76,7 @@ def safe_cospx_div_cosx(
   Returns:
     A tensor of shape `[A1, ..., An]` containing the resulting values.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     theta = tf.convert_to_tensor(value=theta)
     factor = tf.convert_to_tensor(value=factor, dtype=theta.dtype)
     if eps is None:
@@ -88,7 +88,7 @@ def safe_cospx_div_cosx(
     # factors as small as 1e-10 correctly, while preventing a division by zero.
     eps *= tf.clip_by_value(1.0 / factor, 1.0, 1e10)
     sign = nonzero_sign(0.5 * np.pi - (theta - 0.5 * np.pi) % np.pi)
-    theta += sign * eps  # pyrefly: ignore[unsupported-operation]
+    theta += sign * eps
     div = tf.cos(factor * theta) / tf.cos(theta)
     return asserts.assert_no_infs_or_nans(div)
 
@@ -138,7 +138,7 @@ def safe_shrink(
   Returns:
     A tensor of shape `[A1, ..., An]` containing the shrinked values.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     vector = tf.convert_to_tensor(value=vector)
     if eps is None:
       eps = asserts.select_eps_for_addition(vector.dtype)
@@ -181,7 +181,7 @@ def safe_signed_div(
   Returns:
      A tensor of shape `[A1, ..., An]` containing the results of division.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     a = tf.convert_to_tensor(value=a)
     b = tf.convert_to_tensor(value=b)
     if eps is None:
@@ -222,7 +222,7 @@ def safe_sinpx_div_sinx(
   Returns:
     A tensor of shape `[A1, ..., An]` containing the resulting values.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     theta = tf.convert_to_tensor(value=theta)
     factor = tf.convert_to_tensor(value=factor, dtype=theta.dtype)
     if eps is None:
@@ -234,7 +234,7 @@ def safe_sinpx_div_sinx(
     # factors as small as 1e-10 correctly, while preventing a division by zero.
     eps *= tf.clip_by_value(1.0 / factor, 1.0, 1e10)
     sign = nonzero_sign(0.5 * np.pi - theta % np.pi)
-    theta += sign * eps  # pyrefly: ignore[unsupported-operation]
+    theta += sign * eps
     div = tf.sin(factor * theta) / tf.sin(theta)
     return asserts.assert_no_infs_or_nans(div)
 
@@ -264,7 +264,7 @@ def safe_unsigned_div(
   Returns:
      A tensor of shape `[A1, ..., An]` containing the results of division.
   """
-  with tf.name_scope(name):  # pyrefly: ignore[bad-instantiation]
+  with tf.name_scope(name):
     a = tf.convert_to_tensor(value=a)
     b = tf.convert_to_tensor(value=b)
     if eps is None: