A tuple length of 3, (normalized_tensor, mean, variance). # With `clear_session()` called at the beginning, # Keras starts with a blank state at each iteration. If you want to train multiple replicas of a same model on different GPUs, while sharing the same weights across the different replicas, you should first instantiate your model (or layers) under one device scope, then call the same model instance multiple times in different GPU device scopes, such as: You can trivially make use of TensorFlow distributed training by registering with Keras a TF session linked to a cluster: For more information about using TensorFlow in a distributed setting, see this tutorial. Theano's arange: if only one argument is provided, tf.keras.backend.constant abortion #46699 - GitHub To learn more, see our tips on writing great answers. If you want the Keras modules you write to be compatible with both Theano and TensorFlow, you have to write them via the abstract Keras backend API. pattern should be a tuple or list of Somewhat counter-intuitively, Keras seems faster most of the time, by 5-10%. output[i] is True if predictions[i, targets[i]] is within top-k k_batch_normalization() Applies batch normalization on x given mean, var, beta and gamma. Any Keras model can be exported with TensorFlow-serving (as long as it only has one input and one output, which is a limitation of TF-serving), whether or not it was training as part of a TensorFlow workflow. It does not handle itself low-level operations such as tensor products, convolutions and so on. https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/backend/constant, https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/backend/constant, tf.GPUOptions.Experimental.VirtualDevices, tf.contrib.bayesflow.monte_carlo.expectation, tf.contrib.bayesflow.monte_carlo.expectation_importance_sampler, tf.contrib.bayesflow.monte_carlo.expectation_importance_sampler_logspace, tf.contrib.checkpoint.CheckpointableObjectGraph, tf.contrib.checkpoint.CheckpointableObjectGraph.TrackableObject, tf.contrib.checkpoint.CheckpointableObjectGraph.TrackableObject.ObjectReference, tf.contrib.checkpoint.CheckpointableObjectGraph.TrackableObject.SerializedTensor, tf.contrib.checkpoint.CheckpointableObjectGraph.TrackableObject.SlotVariableReference, tf.contrib.checkpoint.capture_dependencies, tf.contrib.checkpoint.dot_graph_from_checkpoint, tf.contrib.constrained_optimization.AdditiveExternalRegretOptimizer, tf.contrib.constrained_optimization.AdditiveSwapRegretOptimizer, tf.contrib.constrained_optimization.ConstrainedMinimizationProblem, tf.contrib.constrained_optimization.ConstrainedOptimizer, tf.contrib.constrained_optimization.MultiplicativeSwapRegretOptimizer, tf.contrib.constrained_optimization.find_best_candidate_distribution, tf.contrib.constrained_optimization.find_best_candidate_index, tf.contrib.copy_graph.copy_variable_to_graph, tf.contrib.crf.crf_multitag_sequence_score, tf.contrib.cudnn_rnn.CudnnCompatibleGRUCell, tf.contrib.cudnn_rnn.CudnnCompatibleLSTMCell, tf.contrib.cudnn_rnn.CudnnParamsFormatConverterGRU, tf.contrib.cudnn_rnn.CudnnParamsFormatConverterLSTM, tf.contrib.cudnn_rnn.CudnnParamsFormatConverterRelu, tf.contrib.cudnn_rnn.CudnnParamsFormatConverterTanh, tf.contrib.cudnn_rnn.CudnnRNNReluSaveable, tf.contrib.cudnn_rnn.CudnnRNNTanhSaveable, tf.contrib.data.CheckpointInputPipelineHook, tf.contrib.data.bucket_by_sequence_length, tf.contrib.data.make_batched_features_dataset, tf.contrib.data.make_saveable_from_iterator, tf.contrib.data.padded_batch_and_drop_remainder, tf.contrib.deprecated.merge_all_summaries, tf.contrib.distribute.AllReduceCrossDeviceOps, tf.contrib.distribute.CollectiveAllReduceStrategy, tf.contrib.distribute.MultiWorkerAllReduce, tf.contrib.distribute.ParameterServerStrategy, tf.contrib.distribute.StandardSingleLossStep, tf.contrib.distribute.get_cross_replica_context, tf.contrib.distribute.require_replica_context, tf.contrib.distribute.run_standard_tensorflow_server, tf.contrib.distributions.BetaWithSoftplusConcentration, tf.contrib.distributions.ConditionalDistribution, tf.contrib.distributions.ConditionalTransformedDistribution, tf.contrib.distributions.ExpRelaxedOneHotCategorical, tf.contrib.distributions.ExponentialWithSoftplusRate, tf.contrib.distributions.GammaWithSoftplusConcentrationRate, tf.contrib.distributions.InverseGammaWithSoftplusConcentrationRate, tf.contrib.distributions.LaplaceWithSoftplusScale, tf.contrib.distributions.MixtureSameFamily, tf.contrib.distributions.MultivariateNormalDiag, tf.contrib.distributions.MultivariateNormalDiagPlusLowRank, tf.contrib.distributions.MultivariateNormalDiagWithSoftplusScale, tf.contrib.distributions.MultivariateNormalFullCovariance, tf.contrib.distributions.MultivariateNormalTriL, tf.contrib.distributions.NegativeBinomial, tf.contrib.distributions.NormalWithSoftplusScale, tf.contrib.distributions.OneHotCategorical, tf.contrib.distributions.PoissonLogNormalQuadratureCompound, tf.contrib.distributions.QuantizedDistribution, tf.contrib.distributions.RelaxedBernoulli, tf.contrib.distributions.RelaxedOneHotCategorical, tf.contrib.distributions.StudentTWithAbsDfSoftplusScale, tf.contrib.distributions.TransformedDistribution, tf.contrib.distributions.VectorDeterministic, tf.contrib.distributions.VectorDiffeomixture, tf.contrib.distributions.VectorExponentialDiag, tf.contrib.distributions.VectorLaplaceDiag, tf.contrib.distributions.VectorSinhArcsinhDiag, tf.contrib.distributions.assign_log_moving_mean_exp, tf.contrib.distributions.assign_moving_mean_variance, tf.contrib.distributions.auto_correlation, tf.contrib.distributions.bijectors.AbsoluteValue, tf.contrib.distributions.bijectors.Affine, tf.contrib.distributions.bijectors.AffineLinearOperator, tf.contrib.distributions.bijectors.AffineScalar, tf.contrib.distributions.bijectors.BatchNormalization, tf.contrib.distributions.bijectors.Bijector, tf.contrib.distributions.bijectors.CholeskyOuterProduct, tf.contrib.distributions.bijectors.ConditionalBijector, tf.contrib.distributions.bijectors.FillTriangular, tf.contrib.distributions.bijectors.Gumbel, tf.contrib.distributions.bijectors.Identity, tf.contrib.distributions.bijectors.Inline, tf.contrib.distributions.bijectors.Invert, tf.contrib.distributions.bijectors.Kumaraswamy, tf.contrib.distributions.bijectors.MaskedAutoregressiveFlow, tf.contrib.distributions.bijectors.MatrixInverseTriL, tf.contrib.distributions.bijectors.Ordered, tf.contrib.distributions.bijectors.Permute, tf.contrib.distributions.bijectors.PowerTransform, tf.contrib.distributions.bijectors.RealNVP, tf.contrib.distributions.bijectors.Reshape, tf.contrib.distributions.bijectors.ScaleTriL, tf.contrib.distributions.bijectors.Sigmoid, tf.contrib.distributions.bijectors.SinhArcsinh, tf.contrib.distributions.bijectors.SoftmaxCentered, tf.contrib.distributions.bijectors.Softplus, tf.contrib.distributions.bijectors.Softsign, tf.contrib.distributions.bijectors.Square, tf.contrib.distributions.bijectors.TransformDiagonal, tf.contrib.distributions.bijectors.masked_autoregressive_default_template, tf.contrib.distributions.bijectors.masked_dense, tf.contrib.distributions.bijectors.real_nvp_default_template, tf.contrib.distributions.estimator_head_distribution_regression, tf.contrib.distributions.fill_triangular_inverse, tf.contrib.distributions.matrix_diag_transform, tf.contrib.distributions.moving_mean_variance, tf.contrib.distributions.normal_conjugates_known_scale_posterior, tf.contrib.distributions.normal_conjugates_known_scale_predictive, tf.contrib.distributions.quadrature_scheme_lognormal_gauss_hermite, tf.contrib.distributions.quadrature_scheme_lognormal_quantiles, tf.contrib.distributions.quadrature_scheme_softmaxnormal_gauss_hermite, tf.contrib.distributions.quadrature_scheme_softmaxnormal_quantiles, tf.contrib.distributions.reduce_weighted_logsumexp, tf.contrib.distributions.softplus_inverse, tf.contrib.eager.clear_execution_callbacks, tf.contrib.eager.enable_remote_eager_execution, tf.contrib.eager.implicit_value_and_gradients, tf.contrib.eager.metrics.CategoricalAccuracy, tf.contrib.eager.restore_network_checkpoint, tf.contrib.eager.restore_variables_on_create, tf.contrib.eager.run_all_tests_in_graph_and_eager_modes, tf.contrib.eager.run_test_in_graph_and_eager_modes, tf.contrib.eager.value_and_gradients_function, tf.contrib.estimator.DNNClassifierWithLayerAnnotations, tf.contrib.estimator.DNNRegressorWithLayerAnnotations, tf.contrib.estimator.binary_classification_head, tf.contrib.estimator.boosted_trees_classifier_train_in_memory, tf.contrib.estimator.boosted_trees_regressor_train_in_memory, tf.contrib.estimator.build_raw_supervised_input_receiver_fn, tf.contrib.estimator.build_supervised_input_receiver_fn_from_input_fn, tf.contrib.estimator.clip_gradients_by_norm, tf.contrib.estimator.dnn_logit_fn_builder, tf.contrib.estimator.export_all_saved_models, tf.contrib.estimator.export_saved_model_for_mode, tf.contrib.estimator.linear_logit_fn_builder, tf.contrib.estimator.logistic_regression_head, tf.contrib.estimator.poisson_regression_head, tf.contrib.factorization.KMeansClustering, tf.contrib.factorization.WALSMatrixFactorization, tf.contrib.feature_column.sequence_categorical_column_with_hash_bucket, tf.contrib.feature_column.sequence_categorical_column_with_identity, tf.contrib.feature_column.sequence_categorical_column_with_vocabulary_file, tf.contrib.feature_column.sequence_categorical_column_with_vocabulary_list, tf.contrib.feature_column.sequence_input_layer, tf.contrib.feature_column.sequence_numeric_column, tf.contrib.framework.VariableDeviceChooser, tf.contrib.framework.arg_scoped_arguments, tf.contrib.framework.assert_or_get_global_step, tf.contrib.framework.assign_from_checkpoint, tf.contrib.framework.assign_from_checkpoint_fn, tf.contrib.framework.assign_from_values_fn, tf.contrib.framework.convolutional_delta_orthogonal, tf.contrib.framework.convolutional_orthogonal_1d, tf.contrib.framework.convolutional_orthogonal_2d, tf.contrib.framework.convolutional_orthogonal_3d, tf.contrib.framework.deprecated_arg_values, tf.contrib.framework.get_graph_from_inputs, tf.contrib.framework.get_or_create_global_step, tf.contrib.framework.get_trainable_variables, tf.contrib.framework.get_variable_full_name, tf.contrib.framework.get_variables_by_name, tf.contrib.framework.get_variables_by_suffix, tf.contrib.framework.get_variables_to_restore, tf.contrib.framework.init_from_checkpoint, tf.contrib.framework.load_and_remap_matrix_initializer, tf.contrib.framework.load_embedding_initializer, tf.contrib.framework.load_linear_multiclass_bias_initializer, tf.contrib.framework.load_variable_slot_initializer, tf.contrib.framework.nest.assert_shallow_structure, tf.contrib.framework.nest.flatten_dict_items, tf.contrib.framework.nest.flatten_with_joined_string_paths, tf.contrib.framework.nest.flatten_with_tuple_paths, tf.contrib.framework.nest.flatten_with_tuple_paths_up_to, tf.contrib.framework.nest.get_traverse_shallow_structure, tf.contrib.framework.nest.is_sequence_or_composite, tf.contrib.framework.nest.map_structure_up_to, tf.contrib.framework.nest.map_structure_with_paths, tf.contrib.framework.nest.map_structure_with_tuple_paths, tf.contrib.framework.nest.map_structure_with_tuple_paths_up_to, tf.contrib.framework.nest.yield_flat_paths, tf.contrib.framework.remove_squeezable_dimensions, tf.contrib.framework.smart_constant_value, tf.contrib.graph_editor.add_control_inputs, tf.contrib.graph_editor.assign_renamed_collections_handler, tf.contrib.graph_editor.compute_boundary_ts, tf.contrib.graph_editor.copy_with_input_replacements, tf.contrib.graph_editor.detach_control_inputs, tf.contrib.graph_editor.detach_control_outputs, tf.contrib.graph_editor.filter_ops_from_regex, tf.contrib.graph_editor.filter_ts_from_regex, tf.contrib.graph_editor.get_backward_walk_ops, tf.contrib.graph_editor.get_consuming_ops, tf.contrib.graph_editor.get_forward_walk_ops, tf.contrib.graph_editor.get_generating_ops, tf.contrib.graph_editor.get_name_scope_ops, tf.contrib.graph_editor.get_walks_intersection_ops, tf.contrib.graph_editor.get_walks_union_ops, tf.contrib.graph_editor.get_within_boundary_ops, tf.contrib.graph_editor.keep_t_if_possible_handler, tf.contrib.graph_editor.make_placeholder_from_dtype_and_shape, tf.contrib.graph_editor.make_placeholder_from_tensor, tf.contrib.graph_editor.make_view_from_scope, tf.contrib.graph_editor.remove_control_inputs, tf.contrib.graph_editor.replace_t_with_placeholder_handler, tf.contrib.graph_editor.select_ops_and_ts, tf.contrib.graph_editor.transform_op_if_inside_handler, tf.contrib.image.angles_to_projective_transforms, tf.contrib.image.flat_transforms_to_matrices, tf.contrib.image.matrices_to_flat_transforms, tf.contrib.image.single_image_random_dot_stereograms, tf.contrib.image.translations_to_projective_transforms, tf.contrib.kernel_methods.KernelLinearClassifier, tf.contrib.kernel_methods.RandomFourierFeatureMapper, tf.contrib.kernel_methods.sparse_multiclass_hinge_loss, tf.contrib.layers.create_feature_spec_for_parsing, tf.contrib.layers.embedding_lookup_unique, tf.contrib.layers.infer_real_valued_columns, tf.contrib.layers.input_from_feature_columns, tf.contrib.layers.joint_weighted_sum_from_feature_columns, tf.contrib.layers.make_place_holder_tensors_for_base_features, tf.contrib.layers.parse_feature_columns_from_examples, tf.contrib.layers.parse_feature_columns_from_sequence_examples, tf.contrib.layers.safe_embedding_lookup_sparse, tf.contrib.layers.scattered_embedding_column, tf.contrib.layers.sequence_input_from_feature_columns, tf.contrib.layers.shared_embedding_columns, tf.contrib.layers.sparse_column_with_hash_bucket, tf.contrib.layers.sparse_column_with_integerized_feature, tf.contrib.layers.sparse_column_with_keys, tf.contrib.layers.sparse_column_with_vocabulary_file, tf.contrib.layers.variance_scaling_initializer, tf.contrib.layers.weighted_sum_from_feature_columns, tf.contrib.learn.DNNLinearCombinedClassifier, tf.contrib.learn.DNNLinearCombinedEstimator, 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tf.contrib.legacy_seq2seq.tied_rnn_seq2seq, tf.contrib.linear_optimizer.SDCAOptimizer, tf.contrib.linear_optimizer.SparseFeatureColumn, tf.contrib.lookup.InitializableLookupTableBase, tf.contrib.lookup.TextFileIdTableInitializer, tf.contrib.lookup.TextFileStringTableInitializer, tf.contrib.lookup.index_table_from_tensor, tf.contrib.lookup.index_to_string_table_from_file, tf.contrib.lookup.index_to_string_table_from_tensor, tf.contrib.lookup.string_to_index_table_from_file, tf.contrib.lookup.string_to_index_table_from_tensor, tf.contrib.losses.get_regularization_losses, tf.contrib.losses.mean_pairwise_squared_error, tf.contrib.losses.metric_learning.cluster_loss, tf.contrib.losses.metric_learning.contrastive_loss, tf.contrib.losses.metric_learning.lifted_struct_loss, tf.contrib.losses.metric_learning.npairs_loss, tf.contrib.losses.metric_learning.npairs_loss_multilabel, tf.contrib.losses.metric_learning.triplet_semihard_loss, tf.contrib.losses.sparse_softmax_cross_entropy, tf.contrib.metrics.auc_with_confidence_intervals, tf.contrib.metrics.precision_recall_at_equal_thresholds, tf.contrib.metrics.sparse_recall_at_top_k, tf.contrib.metrics.streaming_curve_points, tf.contrib.metrics.streaming_false_negative_rate, tf.contrib.metrics.streaming_false_negative_rate_at_thresholds, tf.contrib.metrics.streaming_false_negatives, tf.contrib.metrics.streaming_false_negatives_at_thresholds, tf.contrib.metrics.streaming_false_positive_rate, tf.contrib.metrics.streaming_false_positive_rate_at_thresholds, tf.contrib.metrics.streaming_false_positives, tf.contrib.metrics.streaming_false_positives_at_thresholds, tf.contrib.metrics.streaming_mean_absolute_error, tf.contrib.metrics.streaming_mean_cosine_distance, tf.contrib.metrics.streaming_mean_relative_error, tf.contrib.metrics.streaming_mean_squared_error, tf.contrib.metrics.streaming_pearson_correlation, tf.contrib.metrics.streaming_percentage_less, tf.contrib.metrics.streaming_precision_at_thresholds, 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tf.contrib.model_pruning.get_masked_weights, tf.contrib.model_pruning.get_pruning_hparams, tf.contrib.model_pruning.get_weight_sparsity, tf.contrib.model_pruning.graph_def_from_checkpoint, tf.contrib.model_pruning.masked_fully_connected, tf.contrib.model_pruning.strip_pruning_vars_fn, tf.contrib.nn.deprecated_flipped_sigmoid_cross_entropy_with_logits, tf.contrib.nn.deprecated_flipped_softmax_cross_entropy_with_logits, tf.contrib.nn.deprecated_flipped_sparse_softmax_cross_entropy_with_logits, tf.contrib.nn.sampled_sparse_softmax_loss, tf.contrib.opt.DecoupledWeightDecayExtension, tf.contrib.opt.DropStaleGradientOptimizer, tf.contrib.opt.ElasticAverageCustomGetter, tf.contrib.opt.ExternalOptimizerInterface, tf.contrib.opt.clip_gradients_by_global_norm, tf.contrib.opt.extend_with_decoupled_weight_decay, tf.contrib.optimizer_v2.AdadeltaOptimizer, tf.contrib.optimizer_v2.GradientDescentOptimizer, tf.contrib.optimizer_v2.MomentumOptimizer, tf.contrib.periodic_resample.periodic_resample, 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tf.contrib.stat_summarizer.StatSummarizer, tf.contrib.summary.always_record_summaries, tf.contrib.summary.create_summary_file_writer, tf.contrib.summary.never_record_summaries, tf.contrib.summary.record_summaries_every_n_global_steps, tf.contrib.summary.should_record_summaries, tf.contrib.summary.summary_writer_initializer_op, tf.contrib.timeseries.OneShotPredictionHead, tf.contrib.timeseries.RandomWindowInputFn, tf.contrib.timeseries.StructuralEnsembleRegressor, tf.contrib.timeseries.TimeSeriesRegressor, tf.contrib.timeseries.WholeDatasetInputFn, tf.contrib.timeseries.predict_continuation_input_fn, tf.contrib.timeseries.saved_model_utils.cold_start_filter, tf.contrib.timeseries.saved_model_utils.filter_continuation, tf.contrib.timeseries.saved_model_utils.predict_continuation, tf.contrib.tpu.export_estimator_savedmodel, tf.contrib.tpu.profiler.Device.ResourcesEntry, tf.contrib.tpu.profiler.Trace.DevicesEntry, tf.contrib.tpu.profiler.TraceEvent.ArgsEntry, tf.contrib.training.GreedyLoadBalancingStrategy, tf.contrib.training.NextQueuedSequenceBatch, tf.contrib.training.SequenceQueueingStateSaver, tf.contrib.training.add_gradients_summaries, tf.contrib.training.batch_sequences_with_states, tf.contrib.training.bucket_by_sequence_length, tf.contrib.training.clip_gradient_norms_fn, tf.contrib.training.get_or_create_eval_step, tf.contrib.training.wait_for_new_checkpoint, tf.contrib.util.stripped_op_list_for_graph, tf.resource_loader.get_root_dir_with_all_resources, tf.compat.v1.saved_model.signature_constants, tf.compat.v1.saved_model.signature_def_utils, tf.compat.v2.data.FixedLengthRecordDataset, tf.compat.v2.data.experimental.CsvDataset, tf.compat.v2.data.experimental.RandomDataset, tf.compat.v2.data.experimental.SqlDataset, tf.compat.v2.data.experimental.StatsAggregator, tf.compat.v2.data.experimental.choose_from_datasets, tf.compat.v2.data.experimental.make_batched_features_dataset, tf.compat.v2.data.experimental.make_csv_dataset, 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tf.compat.v2.feature_column.make_parse_example_spec, tf.compat.v2.feature_column.shared_embeddings, tf.compat.v2.image.sample_distorted_bounding_box, tf.compat.v2.keras.applications.imagenet_utils, tf.compat.v2.keras.applications.inception_resnet_v2, tf.compat.v2.keras.applications.inception_v3, tf.compat.v2.keras.applications.mobilenet, tf.compat.v2.keras.applications.mobilenet_v2, tf.compat.v2.keras.applications.resnet_v2, tf.compat.v2.keras.datasets.boston_housing, tf.compat.v2.keras.datasets.fashion_mnist, tf.compat.v2.keras.estimator.model_to_estimator, tf.compat.v2.keras.initializers.GlorotNormal, tf.compat.v2.keras.initializers.GlorotUniform, tf.compat.v2.keras.initializers.Initializer, tf.compat.v2.keras.initializers.Orthogonal, tf.compat.v2.keras.initializers.RandomNormal, tf.compat.v2.keras.initializers.RandomUniform, tf.compat.v2.keras.initializers.TruncatedNormal, tf.compat.v2.keras.initializers.VarianceScaling, tf.compat.v2.keras.initializers.he_normal, tf.compat.v2.keras.initializers.he_uniform, tf.compat.v2.keras.initializers.lecun_normal, tf.compat.v2.keras.initializers.lecun_uniform, tf.compat.v2.keras.layers.BatchNormalization, tf.compat.v2.keras.mixed_precision.experimental, tf.compat.v2.keras.preprocessing.sequence, tf.compat.v2.lookup.StaticVocabularyTable, tf.compat.v2.nn.batch_norm_with_global_normalization, tf.compat.v2.nn.safe_embedding_lookup_sparse, tf.compat.v2.nn.sigmoid_cross_entropy_with_logits, tf.compat.v2.nn.softmax_cross_entropy_with_logits, tf.compat.v2.nn.sparse_softmax_cross_entropy_with_logits, tf.compat.v2.nn.weighted_cross_entropy_with_logits, tf.compat.v2.saved_model.contains_saved_model, tf.compat.v2.summary.experimental.get_step, tf.compat.v2.summary.experimental.set_step, tf.compat.v2.summary.experimental.summary_scope, tf.compat.v2.summary.experimental.write_raw_pb, tf.compat.v2.train.experimental.disable_mixed_precision_graph_rewrite, tf.compat.v2.train.experimental.enable_mixed_precision_graph_rewrite, tf.config.experimental.VirtualDeviceConfiguration, tf.config.experimental.get_synchronous_execution, tf.config.experimental.get_virtual_device_configuration, tf.config.experimental.get_visible_devices, tf.config.experimental.list_logical_devices, tf.config.experimental.list_physical_devices, tf.config.experimental.set_synchronous_execution, tf.config.experimental.set_virtual_device_configuration, tf.config.experimental.set_visible_devices, tf.config.experimental_connect_to_cluster, tf.config.experimental_run_functions_eagerly, tf.config.optimizer.get_experimental_options, tf.config.optimizer.set_experimental_options, tf.config.threading.get_inter_op_parallelism_threads, tf.config.threading.get_intra_op_parallelism_threads, tf.config.threading.set_inter_op_parallelism_threads, tf.config.threading.set_intra_op_parallelism_threads, tf.data.experimental.CheckpointInputPipelineHook, tf.data.experimental.MapVectorizationOptions, tf.data.experimental.RaggedTensorStructure, tf.data.experimental.SparseTensorStructure, tf.data.experimental.TensorArrayStructure, tf.data.experimental.bucket_by_sequence_length, tf.data.experimental.bytes_produced_stats, tf.data.experimental.choose_from_datasets, tf.data.experimental.dense_to_sparse_batch, tf.data.experimental.get_next_as_optional, tf.data.experimental.make_batched_features_dataset, tf.data.experimental.make_saveable_from_iterator, tf.data.experimental.map_and_batch_with_legacy_function, tf.data.experimental.parse_example_dataset, tf.data.experimental.sample_from_datasets, tf.distribute.cluster_resolver.ClusterResolver, tf.distribute.cluster_resolver.GCEClusterResolver, tf.distribute.cluster_resolver.KubernetesClusterResolver, tf.distribute.cluster_resolver.SimpleClusterResolver, tf.distribute.cluster_resolver.SlurmClusterResolver, tf.distribute.cluster_resolver.TFConfigClusterResolver, tf.distribute.cluster_resolver.TPUClusterResolver, tf.distribute.cluster_resolver.UnionResolver, tf.distribute.experimental.CentralStorageStrategy, tf.distribute.experimental.CollectiveCommunication, tf.distribute.experimental.MultiWorkerMirroredStrategy, tf.distribute.experimental.ParameterServerStrategy, tf.errors.raise_exception_on_not_ok_status, tf.estimator.classifier_parse_example_spec, tf.estimator.experimental.InMemoryEvaluatorHook, tf.estimator.experimental.make_early_stopping_hook, tf.estimator.experimental.make_stop_at_checkpoint_step_hook, tf.estimator.experimental.stop_if_higher_hook, tf.estimator.experimental.stop_if_lower_hook, tf.estimator.experimental.stop_if_no_decrease_hook, tf.estimator.experimental.stop_if_no_increase_hook, tf.estimator.export.TensorServingInputReceiver, tf.estimator.export.build_parsing_serving_input_receiver_fn, tf.estimator.export.build_raw_serving_input_receiver_fn, tf.estimator.regressor_parse_example_spec, tf.estimator.tpu.experimental.EmbeddingConfigSpec, tf.feature_column.categorical_column_with_hash_bucket, tf.feature_column.categorical_column_with_identity, tf.feature_column.categorical_column_with_vocabulary_file, tf.feature_column.categorical_column_with_vocabulary_list, tf.feature_column.make_parse_example_spec, tf.feature_column.sequence_categorical_column_with_hash_bucket, tf.feature_column.sequence_categorical_column_with_identity, tf.feature_column.sequence_categorical_column_with_vocabulary_file, tf.feature_column.sequence_categorical_column_with_vocabulary_list, tf.feature_column.sequence_numeric_column, tf.feature_column.shared_embedding_columns, tf.feature_column.weighted_categorical_column, tf.graph_util.convert_variables_to_constants, tf.graph_util.tensor_shape_from_node_def_name, tf.keras.applications.densenet.decode_predictions, tf.keras.applications.densenet.preprocess_input, tf.keras.applications.imagenet_utils.decode_predictions, tf.keras.applications.imagenet_utils.preprocess_input, tf.keras.applications.inception_resnet_v2, tf.keras.applications.inception_resnet_v2.decode_predictions, tf.keras.applications.inception_resnet_v2.preprocess_input, tf.keras.applications.inception_v3.decode_predictions, tf.keras.applications.inception_v3.preprocess_input, tf.keras.applications.mobilenet.decode_predictions, tf.keras.applications.mobilenet.preprocess_input, tf.keras.applications.mobilenet_v2.decode_predictions, tf.keras.applications.mobilenet_v2.preprocess_input, tf.keras.applications.nasnet.decode_predictions, tf.keras.applications.nasnet.preprocess_input, tf.keras.applications.resnet.decode_predictions, tf.keras.applications.resnet.preprocess_input, tf.keras.applications.resnet_v2.decode_predictions, tf.keras.applications.resnet_v2.preprocess_input, tf.keras.applications.vgg16.decode_predictions, tf.keras.applications.vgg16.preprocess_input, tf.keras.applications.vgg19.decode_predictions, tf.keras.applications.vgg19.preprocess_input, tf.keras.applications.xception.decode_predictions, tf.keras.applications.xception.preprocess_input, tf.keras.backend.categorical_crossentropy, tf.keras.backend.ctc_label_dense_to_sparse, tf.keras.backend.manual_variable_initialization, tf.keras.backend.normalize_batch_in_training, tf.keras.backend.sparse_categorical_crossentropy, tf.keras.datasets.boston_housing.load_data, tf.keras.datasets.fashion_mnist.load_data, tf.keras.experimental.CosineDecayRestarts, tf.keras.experimental.NoisyLinearCosineDecay, tf.keras.experimental.load_from_saved_model, tf.keras.experimental.terminate_keras_multiprocessing_pools, tf.keras.losses.MeanAbsolutePercentageError, tf.keras.losses.MeanSquaredLogarithmicError, tf.keras.losses.SparseCategoricalCrossentropy, tf.keras.losses.sparse_categorical_crossentropy, tf.keras.metrics.MeanAbsolutePercentageError, tf.keras.metrics.MeanSquaredLogarithmicError, tf.keras.metrics.SensitivityAtSpecificity, tf.keras.metrics.SparseCategoricalAccuracy, tf.keras.metrics.SparseCategoricalCrossentropy, tf.keras.metrics.SparseTopKCategoricalAccuracy, tf.keras.metrics.SpecificityAtSensitivity, tf.keras.metrics.sparse_categorical_accuracy, tf.keras.metrics.sparse_top_k_categorical_accuracy, tf.keras.metrics.top_k_categorical_accuracy, tf.keras.mixed_precision.experimental.LossScaleOptimizer, tf.keras.mixed_precision.experimental.Policy, tf.keras.mixed_precision.experimental.global_policy, tf.keras.mixed_precision.experimental.set_policy, tf.keras.optimizers.schedules.ExponentialDecay, tf.keras.optimizers.schedules.InverseTimeDecay, tf.keras.optimizers.schedules.LearningRateSchedule, tf.keras.optimizers.schedules.PiecewiseConstantDecay, tf.keras.optimizers.schedules.PolynomialDecay, tf.keras.optimizers.schedules.deserialize, tf.keras.preprocessing.image.DirectoryIterator, tf.keras.preprocessing.image.ImageDataGenerator, tf.keras.preprocessing.image.NumpyArrayIterator, tf.keras.preprocessing.image.apply_affine_transform, tf.keras.preprocessing.image.apply_brightness_shift, tf.keras.preprocessing.image.apply_channel_shift, tf.keras.preprocessing.image.array_to_img, tf.keras.preprocessing.image.img_to_array, tf.keras.preprocessing.image.random_brightness, tf.keras.preprocessing.image.random_channel_shift, tf.keras.preprocessing.image.random_rotation, tf.keras.preprocessing.image.random_shear, tf.keras.preprocessing.image.random_shift, tf.keras.preprocessing.sequence.TimeseriesGenerator, tf.keras.preprocessing.sequence.make_sampling_table, tf.keras.preprocessing.sequence.pad_sequences, tf.keras.preprocessing.sequence.skipgrams, tf.keras.preprocessing.text.hashing_trick, tf.keras.preprocessing.text.text_to_word_sequence, tf.keras.utils.convert_all_kernels_in_model, tf.keras.wrappers.scikit_learn.KerasClassifier, tf.keras.wrappers.scikit_learn.KerasRegressor, tf.lite.experimental.convert_op_hints_to_stubs, tf.lite.experimental.get_potentially_supported_ops, tf.nn.batch_norm_with_global_normalization, tf.nn.softmax_cross_entropy_with_logits_v2, tf.nn.sparse_softmax_cross_entropy_with_logits, tf.profiler.GraphNodeProto.InputShapesEntry, tf.quantization.fake_quant_with_min_max_args, tf.quantization.fake_quant_with_min_max_args_gradient, tf.quantization.fake_quant_with_min_max_vars, tf.quantization.fake_quant_with_min_max_vars_gradient, tf.quantization.fake_quant_with_min_max_vars_per_channel, tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient, tf.random.experimental.get_global_generator, tf.random.experimental.set_global_generator, tf.random.fixed_unigram_candidate_sampler, tf.random.learned_unigram_candidate_sampler, tf.saved_model.classification_signature_def, tf.saved_model.get_tensor_from_tensor_info, tf.signal.mfccs_from_log_mel_spectrograms, tf.tpu.experimental.StochasticGradientDescentParameters, tf.tpu.experimental.initialize_tpu_system, tf.tpu.experimental.shared_embedding_columns, tf.train.ProximalGradientDescentOptimizer, tf.train.do_quantize_training_on_graphdef, tf.train.experimental.MixedPrecisionLossScaleOptimizer, tf.train.experimental.disable_mixed_precision_graph_rewrite, tf.train.experimental.enable_mixed_precision_graph_rewrite, tf.train.queue_runner.start_queue_runners.
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