Initializes PWL calibration layer to represent linear function.
tfl.pwl_calibration_lib.linear_initializer(
shape, output_min, output_max, monotonicity, keypoints=None, dtype=None
)
PWL calibration layer weights have shape (num_keypoints, units)
. First row
represents bias. All remaining represent delta in y-value compare to previous
point. Aka heights of segments.
Args |
shape
|
Requested shape. Must be (num_keypoints, units) .
|
output_min
|
Minimum value of PWL calibration output after initialization.
|
output_max
|
Maximum value of PWL calibration output after initialization.
|
monotonicity
|
If one of {0, 1}, the returned function will go from
(input_min, output_min) to (input_max, output_max) . If set to -1, the
returned function will go from (input_min, output_max) to (input_max,
output_min) .
|
keypoints
|
If not provided (None or []), all pieces of returned function
will have equal heights (i.e. y[i+1] - y[i] is constant). If provided,
all pieces of returned function will have equal slopes (i.e. (y[i+1] -
y[i]) / (x[i+1] - x[i]) is constant).
|
dtype
|
dtype.
|
Returns |
PWLCalibration layer weights initialized according to params.
|
Raises |
ValueError
|
If given parameters are inconsistent.
|