Generate uniformly sampled random barycentric coordinates.
tfg.geometry.representation.mesh.sampler.generate_random_barycentric_coordinates(
sample_shape: type_alias.TensorLike,
dtype: tf.DType = tf.dtypes.float32,
seed: Optional[type_alias.TensorLike] = None,
stateless: bool = False,
name: str = 'generate_random_barycentric_coordinates'
) -> type_alias.TensorLike
Note |
In the following, A1 to An are optional batch dimensions.
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Args |
sample_shape
|
An int tensor with shape [n+1,] and values (A1, ..., An,
num_samples) denoting total number of random samples drawn, where n is
number of batch dimensions, and num_samples is the number of samples
drawn for each mesh.
|
dtype
|
Optional type of generated barycentric coordinates, defaults to
float32.
|
seed
|
An optional random seed.
|
stateless
|
Optional flag to use stateless random sampler. If stateless=True,
then seed must be provided as shape [2] int tensor. Stateless random
sampling is useful for testing to generate the same reproducible sequence
across calls. If stateless=False, then a stateful random number generator
is used (default behavior).
|
name
|
Name for op. Defaults to "generate_random_barycentric_coordinates".
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Returns |
A dtype tensor of shape [A1, ..., An, num_samples, 3],
where the last dimension contains the sampled barycentric coordinates.
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