_SUM_OF_SIZE_ZERO_TENSORS_TEST = dict(
testcase_name='SumOfSizeZeroTensors',
combiner=analyzers.NumPyCombiner(fn=np.sum,
default_accumulator_value=0,
output_dtypes=[np.int64],
output_shapes=[None]),
batches=[
(np.array([]), ),
(np.array([]), ),
],
expected_outputs=[np.array([], np.int64) * 2],
)
_COVARIANCE_SIZE_ZERO_TENSORS_TEST = dict(
testcase_name='CovarianceSizeZeroTensors',
combiner=analyzers.CovarianceCombiner(output_shape=(0, 0),
numpy_dtype=np.float64),
batches=[
(np.empty((1, 0)), ),
(np.empty((2, 0)), ),
],
expected_outputs=[np.empty((0, 0), dtype=np.float64)],
)
_COVARIANCE_WITH_DEGENERATE_COVARIANCE_MATRIX_TEST = dict(
testcase_name='CovarianceWithDegenerateCovarianceMatrix',
combiner=analyzers.CovarianceCombiner(output_shape=(3, 3),
numpy_dtype=np.float64),
batches=[
(np.array([[0, 0, 1]]), ),
(np.array([[4, 0, 1], [2, -1, 1]]), ),
(np.array([[2, 1, 1]]), ),
expected_outputs=[np.array(3)],
)
_SUM_OF_SIZE_ZERO_TENSORS_TEST = dict(
testcase_name='SumOfSizeZeroTensors',
combiner=analyzers.NumPyCombiner(np.sum, output_dtypes=[np.int64]),
batches=[
(np.array([]), ),
(np.array([]), ),
],
expected_outputs=[np.array([], np.int64) * 2],
)
_COVARIANCE_SIZE_ZERO_TENSORS_TEST = dict(
testcase_name='CovarianceSizeZeroTensors',
combiner=analyzers.CovarianceCombiner(numpy_dtype=np.float64),
batches=[
(np.empty((1, 0)), ),
(np.empty((2, 0)), ),
],
expected_outputs=[np.empty((0, 0), dtype=np.float64)],
)
_COVARIANCE_WITH_DEGENERATE_COVARIANCE_MATRIX_TEST = dict(
testcase_name='CovarianceWithDegenerateCovarianceMatrix',
combiner=analyzers.CovarianceCombiner(numpy_dtype=np.float64),
batches=[
(np.array([[0, 0, 1]]), ),
(np.array([[4, 0, 1], [2, -1, 1]]), ),
(np.array([[2, 1, 1]]), ),
],