def _default_event_space_bijector(self):
# TODO(b/145620027) Finalize choice of bijector.
cholesky_bijector = correlation_cholesky_bijector.CorrelationCholesky(
validate_args=self.validate_args)
if self.input_output_cholesky:
return cholesky_bijector
return chain_bijector.Chain([
cholesky_outer_product_bijector.CholeskyOuterProduct(
validate_args=self.validate_args), cholesky_bijector
],
validate_args=self.validate_args)
def _default_event_space_bijector(self):
# TODO(b/145620027) Finalize choice of bijector.
cholesky_bijector = correlation_cholesky_bijector.CorrelationCholesky(
validate_args=self.validate_args)
if self.input_output_cholesky:
return cholesky_bijector
return chain_bijector.Chain([
# We need to explictly clip the output of this bijector because the
# other two bijectors sometimes return values that exceed the bounds by
# an epsilon due to minute numerical errors. Even numerically stable
# algorithms (which the other two bijectors employ) allow for symmetric
# errors about the true value, which is inappropriate for a one-sided
# validity constraint associated with correlation matrices.
_ClipByValue(-1., tf.ones([], self.dtype)),
cholesky_outer_product_bijector.CholeskyOuterProduct(
validate_args=self.validate_args),
cholesky_bijector
], validate_args=self.validate_args)
def _default_event_space_bijector(self):
return correlation_cholesky_bijector.CorrelationCholesky(
validate_args=self.validate_args)
