Index _ | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | R | S | T | U | V | X | Z _ __call__() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) A add_module() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) adjust_learning_rate() (in module cleanlab.experimental.coteaching) append_extra_datapoint() (in module cleanlab.internal.util) apply() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) assert_indexing_works() (in module cleanlab.internal.validation) assert_nonempty_input() (in module cleanlab.internal.validation) assert_valid_class_labels() (in module cleanlab.internal.validation) assert_valid_inputs() (in module cleanlab.internal.validation) assert_valid_inputs_multiannotator() (in module cleanlab.internal.validation) B batch_size (cleanlab.experimental.mnist_pytorch.CNN attribute) bfloat16() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) buffers() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) C calibrate_confident_joint() (in module cleanlab.count) call_bn() (in module cleanlab.experimental.cifar_cnn) children() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) cleanlab.benchmarking module cleanlab.benchmarking.noise_generation module cleanlab.classification module cleanlab.count module cleanlab.dataset module cleanlab.experimental module cleanlab.experimental.cifar_cnn module cleanlab.experimental.coteaching module cleanlab.experimental.fasttext module cleanlab.experimental.keras module cleanlab.experimental.mnist_pytorch module cleanlab.filter module cleanlab.internal module cleanlab.internal.label_quality_utils module cleanlab.internal.latent_algebra module cleanlab.internal.token_classification_utils module cleanlab.internal.util module cleanlab.internal.validation module cleanlab.multiannotator module cleanlab.outlier module cleanlab.rank module cleanlab.token_classification module cleanlab.token_classification.filter module cleanlab.token_classification.rank module cleanlab.token_classification.summary module CleanLearning (class in cleanlab.classification) clip_noise_rates() (in module cleanlab.internal.util) clip_values() (in module cleanlab.internal.util) CNN (class in cleanlab.experimental.cifar_cnn) (class in cleanlab.experimental.mnist_pytorch) color_sentence() (in module cleanlab.internal.token_classification_utils) common_label_issues() (in module cleanlab.token_classification.summary) compress_int_array() (in module cleanlab.internal.util) compute_confident_joint() (in module cleanlab.count) compute_inv_noise_matrix() (in module cleanlab.internal.latent_algebra) compute_noise_matrix_from_inverse() (in module cleanlab.internal.latent_algebra) compute_ps_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra) compute_py() (in module cleanlab.internal.latent_algebra) compute_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra) compute_pyx() (in module cleanlab.internal.latent_algebra) confusion_matrix() (in module cleanlab.internal.util) convert_long_to_wide_dataset() (in module cleanlab.multiannotator) cpu() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) csr_vstack() (in module cleanlab.internal.util) cuda() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) D data_loader() (in module cleanlab.experimental.fasttext) dataset (cleanlab.experimental.mnist_pytorch.CNN attribute) display_issues() (in module cleanlab.token_classification.summary) double() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) dump_patches (cleanlab.experimental.cifar_cnn.CNN attribute) (cleanlab.experimental.mnist_pytorch.SimpleNet attribute) E epochs (cleanlab.experimental.mnist_pytorch.CNN attribute) estimate_confident_joint_and_cv_pred_proba() (in module cleanlab.count) estimate_cv_predicted_probabilities() (in module cleanlab.count) estimate_joint() (in module cleanlab.count) estimate_latent() (in module cleanlab.count) estimate_noise_matrices() (in module cleanlab.count) estimate_pu_f1() (in module cleanlab.internal.util) estimate_py_and_noise_matrices_from_probabilities() (in module cleanlab.count) estimate_py_noise_matrices_and_cv_pred_proba() (in module cleanlab.count) eval() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) evaluate() (in module cleanlab.experimental.coteaching) extra_repr() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) extract_indices_tf() (in module cleanlab.internal.util) F FastTextClassifier (class in cleanlab.experimental.fasttext) filter_by_token() (in module cleanlab.token_classification.summary) filter_sentence() (in module cleanlab.internal.token_classification_utils) find_label_issues() (cleanlab.classification.CleanLearning method) (in module cleanlab.filter) (in module cleanlab.token_classification.filter) find_label_issues_using_argmax_confusion_matrix() (in module cleanlab.filter) find_overlapping_classes() (in module cleanlab.dataset) find_predicted_neq_given() (in module cleanlab.filter) find_top_issues() (in module cleanlab.rank) fit() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.experimental.keras.KerasWrapperModel method) (cleanlab.experimental.keras.KerasWrapperSequential method) (cleanlab.experimental.mnist_pytorch.CNN method), [1] (cleanlab.outlier.OutOfDistribution method) fit_score() (cleanlab.outlier.OutOfDistribution method) float() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) forget_rate_scheduler() (in module cleanlab.experimental.coteaching) forward() (cleanlab.experimental.cifar_cnn.CNN method), [1] (cleanlab.experimental.mnist_pytorch.SimpleNet method) G generate_n_rand_probabilities_that_sum_to_m() (in module cleanlab.benchmarking.noise_generation) generate_noise_matrix_from_trace() (in module cleanlab.benchmarking.noise_generation) generate_noisy_labels() (in module cleanlab.benchmarking.noise_generation) get_buffer() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) get_confidence_weighted_entropy_for_each_label() (in module cleanlab.rank) get_confident_thresholds() (in module cleanlab.count) get_extra_state() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) get_label_issues() (cleanlab.classification.CleanLearning method) get_label_quality_ensemble_scores() (in module cleanlab.rank) get_label_quality_multiannotator() (in module cleanlab.multiannotator) get_label_quality_scores() (in module cleanlab.rank) (in module cleanlab.token_classification.rank) get_majority_vote_label() (in module cleanlab.multiannotator) get_mnist_dataset() (in module cleanlab.experimental.mnist_pytorch) get_normalized_entropy() (in module cleanlab.internal.label_quality_utils) get_normalized_margin_for_each_label() (in module cleanlab.rank) get_num_classes() (in module cleanlab.internal.util) get_parameter() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) get_params() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.experimental.keras.KerasWrapperModel method) (cleanlab.experimental.keras.KerasWrapperSequential method) (cleanlab.experimental.mnist_pytorch.CNN method) get_self_confidence_for_each_label() (in module cleanlab.rank) get_sentence() (in module cleanlab.internal.token_classification_utils) get_sklearn_digits_dataset() (in module cleanlab.experimental.mnist_pytorch) get_submodule() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) H half() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) health_summary() (in module cleanlab.dataset) I initialize_lr_scheduler() (in module cleanlab.experimental.coteaching) int2onehot() (in module cleanlab.internal.util) is_tensorflow_dataset() (in module cleanlab.internal.util) is_torch_dataset() (in module cleanlab.internal.util) issues_from_scores() (in module cleanlab.token_classification.rank) K KerasWrapperModel (class in cleanlab.experimental.keras) KerasWrapperSequential (class in cleanlab.experimental.keras) L labels_to_array() (in module cleanlab.internal.validation) load_state_dict() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) loader (cleanlab.experimental.mnist_pytorch.CNN attribute) log_interval (cleanlab.experimental.mnist_pytorch.CNN attribute) loss_coteaching() (in module cleanlab.experimental.coteaching) lr (cleanlab.experimental.mnist_pytorch.CNN attribute) M mapping() (in module cleanlab.internal.token_classification_utils) merge_probs() (in module cleanlab.internal.token_classification_utils) module cleanlab.benchmarking cleanlab.benchmarking.noise_generation cleanlab.classification cleanlab.count cleanlab.dataset cleanlab.experimental cleanlab.experimental.cifar_cnn cleanlab.experimental.coteaching cleanlab.experimental.fasttext cleanlab.experimental.keras cleanlab.experimental.mnist_pytorch cleanlab.filter cleanlab.internal cleanlab.internal.label_quality_utils cleanlab.internal.latent_algebra cleanlab.internal.token_classification_utils cleanlab.internal.util cleanlab.internal.validation cleanlab.multiannotator cleanlab.outlier cleanlab.rank cleanlab.token_classification cleanlab.token_classification.filter cleanlab.token_classification.rank cleanlab.token_classification.summary modules() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) momentum (cleanlab.experimental.mnist_pytorch.CNN attribute) N named_buffers() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) named_children() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) named_modules() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) named_parameters() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) no_cuda (cleanlab.experimental.mnist_pytorch.CNN attribute) noise_matrix_is_valid() (in module cleanlab.benchmarking.noise_generation) num_label_issues() (in module cleanlab.count) num_unique_classes() (in module cleanlab.internal.util) O onehot2int() (in module cleanlab.internal.util) order_label_issues() (in module cleanlab.rank) OutOfDistribution (class in cleanlab.outlier) overall_label_health_score() (in module cleanlab.dataset) P parameters() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) predict() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.experimental.keras.KerasWrapperModel method) (cleanlab.experimental.keras.KerasWrapperSequential method) (cleanlab.experimental.mnist_pytorch.CNN method), [1] predict_proba() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.experimental.keras.KerasWrapperModel method) (cleanlab.experimental.keras.KerasWrapperSequential method) (cleanlab.experimental.mnist_pytorch.CNN method), [1] print_inverse_noise_matrix() (in module cleanlab.internal.util) print_joint_matrix() (in module cleanlab.internal.util) print_noise_matrix() (in module cleanlab.internal.util) print_square_matrix() (in module cleanlab.internal.util) process_token() (in module cleanlab.internal.token_classification_utils) R randomly_distribute_N_balls_into_K_bins() (in module cleanlab.benchmarking.noise_generation) rank_classes_by_label_quality() (in module cleanlab.dataset) register_backward_hook() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_buffer() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_forward_hook() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_forward_pre_hook() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_full_backward_hook() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_module() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) register_parameter() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) remove_noise_from_class() (in module cleanlab.internal.util) requires_grad_() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) round_preserving_row_totals() (in module cleanlab.internal.util) round_preserving_sum() (in module cleanlab.internal.util) S save_space() (cleanlab.classification.CleanLearning method) score() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.outlier.OutOfDistribution method) seed (cleanlab.experimental.mnist_pytorch.CNN attribute) set_extra_state() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) set_params() (cleanlab.classification.CleanLearning method) (cleanlab.experimental.fasttext.FastTextClassifier method) (cleanlab.experimental.mnist_pytorch.CNN method) share_memory() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) SimpleNet (class in cleanlab.experimental.mnist_pytorch) smart_display_dataframe() (in module cleanlab.internal.util) state_dict() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) subset_data() (in module cleanlab.internal.util) subset_labels() (in module cleanlab.internal.util) subset_X_y() (in module cleanlab.internal.util) summary() (cleanlab.experimental.keras.KerasWrapperModel method) (cleanlab.experimental.keras.KerasWrapperSequential method) T T_destination (cleanlab.experimental.cifar_cnn.CNN attribute) (cleanlab.experimental.mnist_pytorch.SimpleNet attribute) test_batch_size (cleanlab.experimental.mnist_pytorch.CNN attribute) to() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) to_empty() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) train() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) (in module cleanlab.experimental.coteaching) train_val_split() (in module cleanlab.internal.util) training (cleanlab.experimental.cifar_cnn.CNN attribute) (cleanlab.experimental.mnist_pytorch.SimpleNet attribute) type() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) U unshuffle_tensorflow_dataset() (in module cleanlab.internal.util) V value_counts() (in module cleanlab.internal.util) X xpu() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method) Z zero_grad() (cleanlab.experimental.cifar_cnn.CNN method) (cleanlab.experimental.mnist_pytorch.SimpleNet method)