Asserts that 'outputs' satisfiy constraints.
tfl.pwl_calibration_lib.assert_constraints(
outputs,
monotonicity,
output_min,
output_max,
clamp_min=False,
clamp_max=False,
debug_tensors=None,
eps=1e-06
)
Args |
outputs
|
Tensor of shape (num_output_values, units) which represents
outputs of pwl calibration layer which will be tested against the given
constraints. If monotonicity is specified these outputs must be for
consequtive inputs.
|
monotonicity
|
One of {-1, 0, 1}. -1 for decreasing, 1 for increasing 0 means
no monotonicity checks.
|
output_min
|
Lower bound or None.
|
output_max
|
Upper bound or None.
|
clamp_min
|
Whether one of outputs must match output_min.
|
clamp_max
|
Whther one of outputs must match output_max.
|
debug_tensors
|
None or list of anything convertible to tensor (for example
tensors or strings) which will be printed in case of constraints
violation.
|
eps
|
Allowed constraints violation.
|
Raises |
ValueError
|
If monotonicity is not one of {-1, 0, 1}
|
Returns |
List of assertion ops in graph mode or immideately asserts in eager mode.
|