Migrate several files to TensorFlow 2 and Python 3.

PiperOrigin-RevId: 380159321

tensorflow_graphics/geometry/deformation_energy/as_conformal_as_possible.py

@@ -33,7 +33,7 @@ def energy(vertices_rest_pose,
            edge_weight=None,
            conformal_energy=True,
            aggregate_loss=True,
-           name=None):
+           name="as_conformal_as_possible_energy"):
   """Estimates an As Conformal As Possible (ACAP) fitting energy.
 
   For a given mesh in rest pose, this function evaluates a variant of the ACAP
@@ -92,10 +92,7 @@ def energy(vertices_rest_pose,
     ValueError: if the shape of `vertices_rest_pose`, `vertices_deformed_pose`,
     `quaternions`, `edges`, `vertex_weight`, or `edge_weight` is not supported.
   """
-  with tf.compat.v1.name_scope(name, "as_conformal_as_possible_energy", [
-      vertices_rest_pose, vertices_deformed_pose, quaternions, edges,
-      conformal_energy, vertex_weight, edge_weight
-  ]):
+  with tf.name_scope(name):
     vertices_rest_pose = tf.convert_to_tensor(value=vertices_rest_pose)
     vertices_deformed_pose = tf.convert_to_tensor(value=vertices_deformed_pose)
     quaternions = tf.convert_to_tensor(value=quaternions)
@@ -126,12 +123,12 @@ def energy(vertices_rest_pose,
         broadcast_compatible=False)
     shape.check_static(
         tensor=edges, tensor_name="edges", has_rank=2, has_dim_equals=(-1, 2))
-    tensors_with_vertices = [vertices_rest_pose,
-                             vertices_deformed_pose,
-                             quaternions]
-    names_with_vertices = ["vertices_rest_pose",
-                           "vertices_deformed_pose",
-                           "quaternions"]
+    tensors_with_vertices = [
+        vertices_rest_pose, vertices_deformed_pose, quaternions
+    ]
+    names_with_vertices = [
+        "vertices_rest_pose", "vertices_deformed_pose", "quaternions"
+    ]
     axes_with_vertices = [-2, -2, -2]
     if vertex_weight is not None:
       shape.check_static(
@@ -197,5 +194,6 @@ def energy(vertices_rest_pose,
       return (average_energy_ij + average_energy_ji) / 2.0
     return tf.concat((energy_ij_squared, energy_ji_squared), axis=-1)
 
+
 # API contains all public functions and classes.
 __all__ = export_api.get_functions_and_classes()

tensorflow_graphics/rendering/triangle_rasterizer.py

@@ -30,7 +30,7 @@
 
 
 def _dim_value(dim):
-  return 1 if dim is None else tf.compat.v1.dimension_value(dim)
+  return 1 if dim is None else tf.compat.dimension_value(dim)
 
 
 def _merge_batch_dims(tensor, last_axis):
@@ -50,7 +50,7 @@ def rasterize(vertices,
               image_size,
               enable_cull_face=True,
               backend=rasterization_backend.RasterizationBackends.OPENGL,
-              name=None):
+              name="triangle_rasterizer_rasterize"):
   """Rasterizes the scene.
 
   Note:
@@ -73,7 +73,7 @@ def rasterize(vertices,
       False.
     backend: A rasterization_backend.RasterizationBackends enum containing the
       backend method to use for rasterization.
-    name: A name for this op. Defaults to 'triangle_rasterizer_rasterize'.
+    name: A name for this op. Defaults to "triangle_rasterizer_rasterize".
 
   Returns:
     A dictionary. The key "mask" is of shape `[A1, ..., An, height, width, 1]`
@@ -83,9 +83,7 @@ def rasterize(vertices,
     the dictionary contains perspective correct interpolated attributes of shape
     `[A1, ..., An, height, width, K]` per entry in the `attributes` dictionary.
   """
-  with tf.compat.v1.name_scope(
-      name, "triangle_rasterizer_rasterize",
-      (vertices, triangles, attributes, view_projection_matrix)):
+  with tf.name_scope(name):
     vertices = tf.convert_to_tensor(value=vertices)
     triangles = tf.convert_to_tensor(value=triangles)
     view_projection_matrix = tf.convert_to_tensor(value=view_projection_matrix)