_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]]), ), ],