LostTech.TensorFlow : API Documentation

Type training_utils

Namespace tensorflow.python.keras.engine.training_utils

Methods

Properties

Public static methods

object assert_not_batched(object dataset)

object assert_not_batched(Dataset dataset)

object assert_not_batched_dyn(object dataset)

object assert_not_shuffled(object dataset)

object assert_not_shuffled_dyn(object dataset)

object batch_shuffle(object index_array, Nullable<int> batch_size)

object batch_shuffle_dyn(object index_array, object batch_size)

object call_metric_function(PythonFunctionContainer metric_fn, object y_true, object y_pred, object weights, object mask)

object call_metric_function_dyn(object metric_fn, object y_true, object y_pred, object weights, object mask)

object cast_if_floating_dtype(IEnumerable<object> x)

object cast_if_floating_dtype(object x)

object cast_if_floating_dtype(PythonClassContainer x)

object cast_if_floating_dtype_and_mismatch(IEnumerable<object> targets, IEnumerable<IGraphNodeBase> outputs)

object cast_if_floating_dtype_and_mismatch(ValueTuple<IEnumerable<object>, object> targets, IEnumerable<IGraphNodeBase> outputs)

object cast_if_floating_dtype_and_mismatch(IDictionary<string, object> targets, IGraphNodeBase outputs)

object cast_if_floating_dtype_and_mismatch(ValueTuple<IEnumerable<object>, object> targets, IGraphNodeBase outputs)

object cast_if_floating_dtype_and_mismatch(object targets, IEnumerable<IGraphNodeBase> outputs)

object cast_if_floating_dtype_and_mismatch(IDictionary<string, object> targets, IEnumerable<IGraphNodeBase> outputs)

object cast_if_floating_dtype_and_mismatch(object targets, IGraphNodeBase outputs)

object cast_if_floating_dtype_and_mismatch(ndarray targets, IEnumerable<IGraphNodeBase> outputs)

object cast_if_floating_dtype_and_mismatch(IEnumerable<object> targets, IGraphNodeBase outputs)

object cast_if_floating_dtype_and_mismatch(ndarray targets, IGraphNodeBase outputs)

object cast_if_floating_dtype_and_mismatch_dyn(object targets, object outputs)

object cast_if_floating_dtype_dyn(object x)

object cast_single_tensor(object x, DType dtype)

object cast_single_tensor(ndarray x, DType dtype)

object cast_single_tensor(IDictionary<string, object> x, DType dtype)

object cast_single_tensor(ValueTuple<IEnumerable<object>, object> x, DType dtype)

object cast_single_tensor(IGraphNodeBase x, DType dtype)

object cast_single_tensor(IEnumerable<object> x, DType dtype)

object cast_single_tensor_dyn(object x, object dtype)

object cast_to_model_input_dtypes(object x, object model)

object cast_to_model_input_dtypes(object x, Model model)

object cast_to_model_input_dtypes(IGraphNodeBase x, object model)

object cast_to_model_input_dtypes(IGraphNodeBase x, Model model)

object cast_to_model_input_dtypes(IEnumerable<IGraphNodeBase> x, object model)

object cast_to_model_input_dtypes(IEnumerable<IGraphNodeBase> x, Model model)

object cast_to_model_input_dtypes(IDictionary<string, object> x, object model)

object cast_to_model_input_dtypes(IDictionary<string, object> x, Model model)

object cast_to_model_input_dtypes(ndarray x, object model)

object cast_to_model_input_dtypes(ndarray x, Model model)

object cast_to_model_input_dtypes_dyn(object x, object model)

void check_array_lengths(object inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(PythonFunctionContainer inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(IDictionary<object, object> inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(PythonFunctionContainer inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(ndarray inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(PythonFunctionContainer inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(ndarray inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(ndarray inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(object inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(ndarray inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(IDictionary<object, object> inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(ValueTuple<PythonClassContainer, PythonClassContainer> inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(object inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(PythonFunctionContainer inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(object inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(Trackable inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(ValueTuple<PythonClassContainer, PythonClassContainer> inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(IDictionary<object, object> inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(IEnumerable<IGraphNodeBase> inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(Trackable inputs, PythonFunctionContainer targets, IEnumerable<object> weights)

void check_array_lengths(Trackable inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(IEnumerable<IGraphNodeBase> inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(IEnumerable<IGraphNodeBase> inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(IDictionary<object, object> inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(IEnumerable<IGraphNodeBase> inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(ValueTuple<PythonClassContainer, PythonClassContainer> inputs, object targets, IEnumerable<object> weights)

void check_array_lengths(Trackable inputs, object targets, ValueTuple<IEnumerable<object>, object> weights)

void check_array_lengths(ValueTuple<PythonClassContainer, PythonClassContainer> inputs, PythonFunctionContainer targets, ValueTuple<IEnumerable<object>, object> weights)

object check_array_lengths_dyn(object inputs, object targets, object weights)

void check_generator_arguments(IDictionary<string, object> y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IDictionary<string, object> y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(int y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(HDF5Matrix y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IDictionary<string, object> y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(int y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IEnumerable<object> y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(ndarray y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(HDF5Matrix y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(HDF5Matrix y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IEnumerable<object> y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(ndarray y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IEnumerable<object> y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(ndarray y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(int y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IGraphNodeBase y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(object y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IGraphNodeBase y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(object y, IDictionary<string, object> sample_weight, Nullable<double> validation_split)

void check_generator_arguments(object y, ndarray sample_weight, Nullable<double> validation_split)

void check_generator_arguments(IGraphNodeBase y, IEnumerable<object> sample_weight, Nullable<double> validation_split)

object check_generator_arguments_dyn(object y, object sample_weight, object validation_split)

void check_loss_and_target_compatibility(IGraphNodeBase targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(object targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(PythonFunctionContainer targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(ValueTuple<IEnumerable<object>, object> targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(IEnumerable<object> targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(IDictionary<object, object> targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

void check_loss_and_target_compatibility(ndarray targets, IEnumerable<object> loss_fns, IEnumerable<Nullable<ValueTuple<object>>> output_shapes)

object check_loss_and_target_compatibility_dyn(object targets, object loss_fns, object output_shapes)

Nullable<int> check_num_samples(object ins, Nullable<int> batch_size, IEnumerable<object> steps, string steps_name)

Nullable<int> check_num_samples(IEnumerable<int> ins, Nullable<int> batch_size, IGraphNodeBase steps, string steps_name)

Nullable<int> check_num_samples(object ins, Nullable<int> batch_size, int steps, string steps_name)

Nullable<int> check_num_samples(IEnumerable<int> ins, Nullable<int> batch_size, IEnumerable<object> steps, string steps_name)

Nullable<int> check_num_samples(IEnumerable<int> ins, Nullable<int> batch_size, int steps, string steps_name)

Nullable<int> check_num_samples(object ins, Nullable<int> batch_size, object steps, string steps_name)

Nullable<int> check_num_samples(IEnumerable<int> ins, Nullable<int> batch_size, object steps, string steps_name)

Nullable<int> check_num_samples(object ins, Nullable<int> batch_size, IGraphNodeBase steps, string steps_name)

object check_num_samples_dyn(object ins, object batch_size, object steps, ImplicitContainer<T> steps_name)

bool check_steps_argument(object input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(PythonFunctionContainer input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(Iterator input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(ValueTuple<PythonClassContainer, PythonClassContainer> input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(IDictionary<object, object> input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(ndarray input_data, Nullable<int> steps, string steps_name)

bool check_steps_argument(IEnumerable<IGraphNodeBase> input_data, Nullable<int> steps, string steps_name)

object check_steps_argument_dyn(object input_data, object steps, object steps_name)

IList<IDictionary<object, object>> collect_per_output_metric_info(IDictionary<string, string> metrics, IEnumerable<object> output_names, IEnumerable<object> output_shapes, IEnumerable<object> loss_fns, bool is_weighted)

IList<IDictionary<object, object>> collect_per_output_metric_info(IEnumerable<object> metrics, IEnumerable<object> output_names, IEnumerable<object> output_shapes, IEnumerable<object> loss_fns, bool is_weighted)

object collect_per_output_metric_info_dyn(object metrics, object output_names, object output_shapes, object loss_fns, ImplicitContainer<T> is_weighted)

object convert_eager_tensors_to_numpy(ValueTuple<object, object, object> structure)

object convert_eager_tensors_to_numpy_dyn(object structure)

object extract_tensors_from_dataset(ValueTuple<PythonClassContainer, PythonClassContainer> dataset)

object extract_tensors_from_dataset_dyn(object dataset)

IList<string> generic_output_names(IGraphNodeBase outputs_list)

IList<string> generic_output_names(IEnumerable<IGraphNodeBase> outputs_list)

object generic_output_names_dyn(object outputs_list)

object get_copy_pool()

object get_copy_pool_dyn()

ValueTuple<object, object> get_input_shape_and_dtype(object layer)

ValueTuple<object, object> get_input_shape_and_dtype(Layer layer)

object get_input_shape_and_dtype_dyn(object layer)

object get_iterator(IEnumerable<PythonClassContainer> dataset)

object get_iterator(object dataset)

object get_iterator_dyn(object dataset)

object get_loss_function(IDictionary<object, object> loss)

object get_loss_function(PythonFunctionContainer loss)

object get_loss_function(object loss)

object get_loss_function_dyn(object loss)

object get_metric_function(string metric, object output_shape, IDictionary<object, object> loss_fn)

object get_metric_function(string metric, object output_shape, Loss loss_fn)

object get_metric_function(string metric, object output_shape, string loss_fn)

object get_metric_function_dyn(object metric, object output_shape, object loss_fn)

string get_metric_name(object metric, bool weighted)

string get_metric_name(string metric, bool weighted)

object get_metric_name_dyn(object metric, ImplicitContainer<T> weighted)

ProgbarLogger get_progbar(object model, string count_mode)

object get_progbar_dyn(object model, object count_mode)

Nullable<int> get_static_batch_size(Layer layer)

object get_static_batch_size_dyn(object layer)

bool has_symbolic_tensors(IEnumerable<IGraphNodeBase> ls)

bool has_symbolic_tensors(PythonFunctionContainer ls)

bool has_symbolic_tensors(object ls)

object has_symbolic_tensors_dyn(object ls)

bool has_tensors(IEnumerable<object> ls)

bool has_tensors(object ls)

bool has_tensors(PythonClassContainer ls)

object has_tensors_dyn(object ls)

object infer_steps_for_dataset(object model, object dataset, object steps, int epochs, string steps_name)

object infer_steps_for_dataset(object model, IEnumerable<IGraphNodeBase> dataset, object steps, int epochs, string steps_name)

object infer_steps_for_dataset_dyn(object model, object dataset, object steps, ImplicitContainer<T> epochs, ImplicitContainer<T> steps_name)

void initialize_iterator(Trackable iterator)

object initialize_iterator_dyn(object iterator)

bool is_dataset_or_iterator(object data)

object is_dataset_or_iterator_dyn(object data)

bool is_eager_dataset_or_iterator(object data)

bool is_eager_dataset_or_iterator(IEnumerable<PythonClassContainer> data)

object is_eager_dataset_or_iterator_dyn(object data)

bool is_feature_layer(Layer layer)

object is_feature_layer_dyn(object layer)

object list_to_tuple(ndarray maybe_list)

object list_to_tuple(object maybe_list)

object list_to_tuple(IDictionary<object, object> maybe_list)

object list_to_tuple(IEnumerable<object> maybe_list)

object list_to_tuple(PythonClassContainer maybe_list)

object list_to_tuple(IGraphNodeBase maybe_list)

object list_to_tuple(Dataset maybe_list)

object list_to_tuple_dyn(object maybe_list)

object prepare_loss_functions(PythonFunctionContainer loss, object output_names)

object prepare_loss_functions(object loss, object output_names)

object prepare_loss_functions(IDictionary<object, object> loss, object output_names)

object prepare_loss_functions_dyn(object loss, object output_names)

void prepare_loss_weights(IEnumerable<_TrainingEndpoint> training_endpoints, IDictionary<string, double> loss_weights)

void prepare_loss_weights(IEnumerable<_TrainingEndpoint> training_endpoints, IEnumerable<double> loss_weights)

object prepare_loss_weights_dyn(object training_endpoints, object loss_weights)

void prepare_sample_weight_modes(IEnumerable<_TrainingEndpoint> training_endpoints, IDictionary<string, object> sample_weight_mode)

void prepare_sample_weight_modes(IEnumerable<_TrainingEndpoint> training_endpoints, string sample_weight_mode)

void prepare_sample_weight_modes(IEnumerable<_TrainingEndpoint> training_endpoints, ValueTuple<IEnumerable<object>, object> sample_weight_mode)

void prepare_sample_weight_modes(IEnumerable<_TrainingEndpoint> training_endpoints, IEnumerable<object> sample_weight_mode)

object prepare_sample_weight_modes_dyn(object training_endpoints, object sample_weight_mode)

bool should_run_validation(int validation_freq, int epoch)

object should_run_validation_dyn(object validation_freq, object epoch)

object slice_arrays(object arrays, object indices, bool contiguous)

object slice_arrays_dyn(object arrays, object indices, ImplicitContainer<T> contiguous)

object split_training_and_validation_data(object x, IEnumerable<object> y, IDictionary<string, object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, ndarray y, IDictionary<string, object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, ndarray y, IEnumerable<object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, IDictionary<string, object> y, ndarray sample_weights, double validation_split)

object split_training_and_validation_data(object x, IDictionary<string, object> y, IDictionary<string, object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, IDictionary<string, object> y, IEnumerable<object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, IEnumerable<object> y, ndarray sample_weights, double validation_split)

object split_training_and_validation_data(object x, ndarray y, ndarray sample_weights, double validation_split)

object split_training_and_validation_data(object x, object y, ndarray sample_weights, double validation_split)

object split_training_and_validation_data(object x, object y, IDictionary<string, object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, object y, IEnumerable<object> sample_weights, double validation_split)

object split_training_and_validation_data(object x, IEnumerable<object> y, IEnumerable<object> sample_weights, double validation_split)

object split_training_and_validation_data_dyn(object x, object y, object sample_weights, object validation_split)

object standardize_class_weights(object class_weight, IEnumerable<object> output_names)

object standardize_class_weights_dyn(object class_weight, object output_names)

object standardize_input_data(IEnumerable<IGraphNodeBase> data, IEnumerable<object> names, IEnumerable<Nullable<ValueTuple<object>>> shapes, bool check_batch_axis, string exception_prefix)

object standardize_input_data(PythonFunctionContainer data, IEnumerable<object> names, IEnumerable<Nullable<ValueTuple<object>>> shapes, bool check_batch_axis, string exception_prefix)

object standardize_input_data(object data, IEnumerable<object> names, IEnumerable<Nullable<ValueTuple<object>>> shapes, bool check_batch_axis, string exception_prefix)

object standardize_input_data_dyn(object data, object names, object shapes, ImplicitContainer<T> check_batch_axis, ImplicitContainer<T> exception_prefix)

object standardize_sample_or_class_weights(IGraphNodeBase x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(IDictionary<object, object> x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(object x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(ValueTuple<IEnumerable<object>, object> x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(IEnumerable<object> x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(Dataset x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights(ndarray x_weight, IEnumerable<object> output_names, string weight_type)

object standardize_sample_or_class_weights_dyn(object x_weight, object output_names, object weight_type)

object standardize_sample_weights(IEnumerable<object> sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(object sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(IGraphNodeBase sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(ndarray sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(Dataset sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(IDictionary<string, object> sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights(ValueTuple<IEnumerable<object>, object> sample_weight, IEnumerable<object> output_names)

object standardize_sample_weights_dyn(object sample_weight, object output_names)

object standardize_single_array(object x, object expected_shape)

object standardize_single_array(IGraphNodeBase x, object expected_shape)

object standardize_single_array(PythonClassContainer x, object expected_shape)

object standardize_single_array(int x, object expected_shape)

object standardize_single_array(CompositeTensor x, object expected_shape)

object standardize_single_array(IEnumerable<object> x, object expected_shape)

object standardize_single_array_dyn(object x, object expected_shape)

object standardize_weights(ndarray y, object sample_weight, IDictionary<int, double> class_weight, object sample_weight_mode)

object standardize_weights(ndarray y, ndarray sample_weight, IDictionary<int, double> class_weight, object sample_weight_mode)

object standardize_weights_dyn(object y, object sample_weight, object class_weight, object sample_weight_mode)

object unpack_iterator_input(ValueTuple<IEnumerable<object>, object> iterator)

object unpack_iterator_input(IEnumerable<object> iterator)

object unpack_iterator_input(Trackable iterator)

object unpack_iterator_input_dyn(object iterator)

object unpack_validation_data(object validation_data)

object unpack_validation_data(Dataset validation_data)

object unpack_validation_data(Dataset validation_data)

object unpack_validation_data(ValueTuple<ndarray, object> validation_data)

object unpack_validation_data_dyn(object validation_data)

void validate_dataset_input(IEnumerable<object> x, PythonFunctionContainer y, IDictionary<string, object> sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, PythonFunctionContainer y, IEnumerable<object> sample_weight, object validation_split)

void validate_dataset_input(object x, object y, IDictionary<string, object> sample_weight, object validation_split)

void validate_dataset_input(object x, object y, ndarray sample_weight, object validation_split)

void validate_dataset_input(object x, object y, IEnumerable<object> sample_weight, object validation_split)

void validate_dataset_input(object x, PythonFunctionContainer y, object sample_weight, object validation_split)

void validate_dataset_input(object x, object y, Dataset sample_weight, object validation_split)

void validate_dataset_input(object x, object y, object sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, object y, Dataset sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, PythonFunctionContainer y, ndarray sample_weight, object validation_split)

void validate_dataset_input(object x, PythonFunctionContainer y, Dataset sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, object y, IDictionary<string, object> sample_weight, object validation_split)

void validate_dataset_input(object x, PythonFunctionContainer y, IDictionary<string, object> sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, PythonFunctionContainer y, Dataset sample_weight, object validation_split)

void validate_dataset_input(object x, PythonFunctionContainer y, IEnumerable<object> sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, object y, object sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, object y, ndarray sample_weight, object validation_split)

void validate_dataset_input(object x, PythonFunctionContainer y, ndarray sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, PythonFunctionContainer y, object sample_weight, object validation_split)

void validate_dataset_input(IEnumerable<object> x, object y, IEnumerable<object> sample_weight, object validation_split)

object validate_dataset_input_dyn(object x, object y, object sample_weight, object validation_split)

void validate_input_types(object inp, PythonClassContainer orig_inp, bool allow_dict, string field_name)

void validate_input_types(object inp, IEnumerable<object> orig_inp, bool allow_dict, string field_name)

void validate_input_types(PythonClassContainer inp, PythonClassContainer orig_inp, bool allow_dict, string field_name)

void validate_input_types(PythonClassContainer inp, IEnumerable<object> orig_inp, bool allow_dict, string field_name)

void validate_input_types(IEnumerable<object> inp, object orig_inp, bool allow_dict, string field_name)

void validate_input_types(object inp, object orig_inp, bool allow_dict, string field_name)

void validate_input_types(IEnumerable<object> inp, IEnumerable<object> orig_inp, bool allow_dict, string field_name)

void validate_input_types(IEnumerable<object> inp, PythonClassContainer orig_inp, bool allow_dict, string field_name)

void validate_input_types(PythonClassContainer inp, object orig_inp, bool allow_dict, string field_name)

object validate_input_types_dyn(object inp, object orig_inp, ImplicitContainer<T> allow_dict, ImplicitContainer<T> field_name)

void verify_dataset_shuffled(object x)

object verify_dataset_shuffled_dyn(object x)

Public properties

PythonFunctionContainer Aggregator_fn get;

PythonFunctionContainer assert_not_batched_fn get;

PythonFunctionContainer assert_not_shuffled_fn get;

PythonFunctionContainer batch_shuffle_fn get;

PythonFunctionContainer call_metric_function_fn get;

PythonFunctionContainer cast_if_floating_dtype_and_mismatch_fn get;

PythonFunctionContainer cast_if_floating_dtype_fn get;

PythonFunctionContainer cast_single_tensor_fn get;

PythonFunctionContainer cast_to_model_input_dtypes_fn get;

PythonFunctionContainer check_array_lengths_fn get;

PythonFunctionContainer check_generator_arguments_fn get;

PythonFunctionContainer check_loss_and_target_compatibility_fn get;

PythonFunctionContainer check_num_samples_fn get;

PythonFunctionContainer check_steps_argument_fn get;

PythonFunctionContainer collect_per_output_metric_info_fn get;

PythonFunctionContainer ConcatAggregator_fn get;

PythonFunctionContainer convert_eager_tensors_to_numpy_fn get;

PythonFunctionContainer extract_tensors_from_dataset_fn get;

PythonFunctionContainer generic_output_names_fn get;

PythonFunctionContainer get_copy_pool_fn get;

PythonFunctionContainer get_input_shape_and_dtype_fn get;

PythonFunctionContainer get_iterator_fn get;

PythonFunctionContainer get_loss_function_fn get;

PythonFunctionContainer get_metric_function_fn get;

PythonFunctionContainer get_metric_name_fn get;

PythonFunctionContainer get_progbar_fn get;

PythonFunctionContainer get_static_batch_size_fn get;

PythonFunctionContainer has_symbolic_tensors_fn get;

PythonFunctionContainer has_tensors_fn get;

PythonFunctionContainer infer_steps_for_dataset_fn get;

PythonFunctionContainer initialize_iterator_fn get;

PythonFunctionContainer is_dataset_or_iterator_fn get;

PythonFunctionContainer is_eager_dataset_or_iterator_fn get;

PythonFunctionContainer is_feature_layer_fn get;

PythonFunctionContainer list_to_tuple_fn get;

PythonFunctionContainer MetricsAggregator_fn get;

PythonFunctionContainer ModelInputs_fn get;

PythonFunctionContainer OutputsAggregator_fn get;

PythonFunctionContainer prepare_loss_functions_fn get;

PythonFunctionContainer prepare_loss_weights_fn get;

PythonFunctionContainer prepare_sample_weight_modes_fn get;

PythonFunctionContainer should_run_validation_fn get;

PythonFunctionContainer slice_arrays_fn get;

PythonFunctionContainer SliceAggregator_fn get;

PythonFunctionContainer split_training_and_validation_data_fn get;

PythonFunctionContainer standardize_class_weights_fn get;

PythonFunctionContainer standardize_input_data_fn get;

PythonFunctionContainer standardize_sample_or_class_weights_fn get;

PythonFunctionContainer standardize_sample_weights_fn get;

PythonFunctionContainer standardize_single_array_fn get;

PythonFunctionContainer standardize_weights_fn get;

PythonFunctionContainer TrainingLoop_fn get;

PythonFunctionContainer unpack_iterator_input_fn get;

PythonFunctionContainer unpack_validation_data_fn get;

PythonFunctionContainer validate_dataset_input_fn get;

PythonFunctionContainer validate_input_types_fn get;

PythonFunctionContainer verify_dataset_shuffled_fn get;