LostTech.TensorFlow : API Documentation

Type distributed_training_utils

Namespace tensorflow.python.keras.distribute.distributed_training_utils

Methods

Properties

Public static methods

PythonFunctionContainer call_replica_local_fn(object fn, IDictionary<string, object> kwargs, IGraphNodeBase[] args)

PythonFunctionContainer call_replica_local_fn(object fn, IDictionary<string, object> kwargs, Object[] args)

PythonFunctionContainer call_replica_local_fn(object fn, Object[] args)

PythonFunctionContainer call_replica_local_fn(object fn, IGraphNodeBase[] args)

object call_replica_local_fn_dyn(object fn, Object[] args)

object call_replica_local_fn_dyn(object fn, IDictionary<string, object> kwargs, Object[] args)

void clone_model_on_replicas(Model model, object strategy, string mode, ValueTuple<object, IEnumerable<object>> inputs, IEnumerable<object> targets)

void clone_model_on_replicas(Model model, object strategy, string mode, object inputs, IEnumerable<object> targets)

void clone_model_on_replicas(Model model, object strategy, string mode, IDictionary<object, object> inputs, IEnumerable<object> targets)

void clone_model_on_replicas(Model model, object strategy, string mode, IEnumerable<object> inputs, IEnumerable<object> targets)

object clone_model_on_replicas_dyn(object model, object strategy, object mode, object inputs, object targets)

object concat_along_batch_dimension(object outputs)

object concat_along_batch_dimension_dyn(object outputs)

IContextManager<T> distributed_scope(object strategy, int learning_phase)

object distributed_scope_dyn(object strategy, object learning_phase)

IList<object> filter_distributed_callbacks(IEnumerable<object> callbacks_list, object model)

object filter_distributed_callbacks_dyn(object callbacks_list, object model)

IList<object> flatten_per_replica_values(object distribution_strategy, IDictionary<object, object> per_replica_values)

IList<object> flatten_per_replica_values(object distribution_strategy, IEnumerable<object> per_replica_values)

IList<object> flatten_per_replica_values(object distribution_strategy, ValueTuple<PythonClassContainer, PythonClassContainer> per_replica_values)

object flatten_per_replica_values_dyn(object distribution_strategy, object per_replica_values)

object get_batch_dimension(object iterator)

object get_batch_dimension_dyn(object iterator)

object get_distributed_function(object model, object mode)

object get_distributed_function(object model, ValueTuple<object, string> mode)

object get_distributed_function(Model model, object mode)

object get_distributed_function(Model model, ValueTuple<object, string> mode)

object get_distributed_function_dyn(object model, object mode)

object get_distributed_model(object model, string mode)

object get_distributed_model(Model model, string mode)

object get_distributed_model_dyn(object model, object mode)

object get_input_params(object distribution_strategy, int num_samples, Nullable<int> steps, Nullable<int> batch_size, object mode)

object get_input_params_dyn(object distribution_strategy, object num_samples, object steps, object batch_size, object mode)

object get_iterator(object dataset, object distribution_strategy)

object get_iterator(IEnumerable<IGraphNodeBase> dataset, object distribution_strategy)

object get_iterator_dyn(object dataset, object distribution_strategy)

object global_batch_size_supported(Nullable<ValueTuple<PythonClassContainer, PythonClassContainer, PythonClassContainer>> distribution_strategy)

object global_batch_size_supported_dyn(object distribution_strategy)

void init_restore_or_wait_for_variables()

object init_restore_or_wait_for_variables_dyn()

void initialize_iterator(object iterator, object distribution_strategy)

object initialize_iterator_dyn(object iterator, object distribution_strategy)

object is_current_worker_chief()

object is_current_worker_chief_dyn()

bool is_dataset_shape_fully_defined(Dataset dataset)

bool is_dataset_shape_fully_defined(IEnumerable<object> dataset)

bool is_dataset_shape_fully_defined(Dataset dataset)

bool is_dataset_shape_fully_defined(object dataset)

bool is_dataset_shape_fully_defined(IDictionary<string, object> dataset)

bool is_dataset_shape_fully_defined(ndarray dataset)

object is_dataset_shape_fully_defined_dyn(object dataset)

bool is_distributing_by_cloning(Model model)

bool is_distributing_by_cloning(object model)

object is_distributing_by_cloning_dyn(object model)

bool is_tpu_strategy(IGraphNodeBase strategy)

bool is_tpu_strategy(IEnumerable<object> strategy)

bool is_tpu_strategy(int strategy)

bool is_tpu_strategy(double strategy)

object is_tpu_strategy_dyn(object strategy)

object process_batch_and_step_size(object strategy, object inputs, Nullable<int> batch_size, object steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, object inputs, Nullable<int> batch_size, IGraphNodeBase steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, object inputs, Nullable<int> batch_size, int steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, object inputs, Nullable<int> batch_size, IEnumerable<object> steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, IEnumerable<IGraphNodeBase> inputs, Nullable<int> batch_size, IEnumerable<object> steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, IEnumerable<IGraphNodeBase> inputs, Nullable<int> batch_size, int steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, IEnumerable<IGraphNodeBase> inputs, Nullable<int> batch_size, IGraphNodeBase steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size(object strategy, IEnumerable<IGraphNodeBase> inputs, Nullable<int> batch_size, object steps_per_epoch, string mode, double validation_split)

object process_batch_and_step_size_dyn(object strategy, object inputs, object batch_size, object steps_per_epoch, object mode, ImplicitContainer<T> validation_split)

void set_distributed_function(object model, object mode, object distributed_function)

void set_distributed_function(Model model, ValueTuple<object, string> mode, object distributed_function)

void set_distributed_function(Model model, object mode, object distributed_function)

void set_distributed_function(object model, ValueTuple<object, string> mode, object distributed_function)

object set_distributed_function_dyn(object model, object mode, object distributed_function)

void set_distributed_model(Model model, string mode, object distributed_model)

object set_distributed_model_dyn(object model, object mode, object distributed_model)

void set_weights(object distribution_strategy, Model dist_model, IEnumerable<object> weights)

void set_weights(object distribution_strategy, object dist_model, IEnumerable<object> weights)

object set_weights_dyn(object distribution_strategy, object dist_model, object weights)

object unwrap_output_dict(object strategy, object grouped_outputs, string mode)

object unwrap_output_dict_dyn(object strategy, object grouped_outputs, object mode)

IList<object> unwrap_outputs(object distribution_strategy, object grouped_outputs, bool with_loss_tensor)

object unwrap_outputs_dyn(object distribution_strategy, object grouped_outputs, ImplicitContainer<T> with_loss_tensor)

ValueTuple<IList<object>, object, object, IDictionary<string, object>> unwrap_values(object distribution_strategy, object grouped_inputs, object grouped_outputs, object grouped_updates, object grouped_session_args, bool with_loss_tensor)

object unwrap_values_dyn(object distribution_strategy, object grouped_inputs, object grouped_outputs, object grouped_updates, object grouped_session_args, ImplicitContainer<T> with_loss_tensor)

void validate_all_tensor_shapes(DistributedValues x, object x_values)

void validate_all_tensor_shapes(IEnumerable<object> x, object x_values)

object validate_all_tensor_shapes_dyn(object x, object x_values)

void validate_all_tensor_types(IEnumerable<object> x, object x_values)

void validate_all_tensor_types(DistributedValues x, object x_values)

object validate_all_tensor_types_dyn(object x, object x_values)

void validate_callbacks(CallbackList input_callbacks, IEnumerable<object> optimizer)

void validate_callbacks(IEnumerable<object> input_callbacks, ValueTuple<PythonClassContainer, PythonClassContainer> optimizer)

void validate_callbacks(IEnumerable<object> input_callbacks, IEnumerable<object> optimizer)

void validate_callbacks(CallbackList input_callbacks, ValueTuple<PythonClassContainer, PythonClassContainer> optimizer)

void validate_callbacks(CallbackList input_callbacks, Trackable optimizer)

void validate_callbacks(IEnumerable<object> input_callbacks, Trackable optimizer)

object validate_callbacks_dyn(object input_callbacks, object optimizer)

ValueTuple<IList<object>, object, object> validate_distributed_dataset_inputs(object distribution_strategy, DistributedValues x, DistributedValues y, object sample_weights)

ValueTuple<IList<object>, object, object> validate_distributed_dataset_inputs(object distribution_strategy, IEnumerable<object> x, DistributedValues y, object sample_weights)

object validate_distributed_dataset_inputs_dyn(object distribution_strategy, object x, object y, object sample_weights)

void validate_inputs(object x, ndarray y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, object y)

void validate_inputs(object x, IDictionary<object, object> y)

void validate_inputs(object x, IEnumerable<object> y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, int y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, IEnumerable<object> y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, HDF5Matrix y)

void validate_inputs(object x, HDF5Matrix y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, IDictionary<object, object> y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, ndarray y)

void validate_inputs(object x, IGraphNodeBase y)

void validate_inputs(object x, object y)

void validate_inputs(IEnumerable<IGraphNodeBase> x, IGraphNodeBase y)

void validate_inputs(object x, int y)

object validate_inputs_dyn(object x, object y)

IList<object> validate_per_replica_inputs(object distribution_strategy, DistributedValues x)

IList<object> validate_per_replica_inputs(object distribution_strategy, IEnumerable<object> x)

object validate_per_replica_inputs_dyn(object distribution_strategy, object x)

Public properties

PythonFunctionContainer call_replica_local_fn_fn get;

PythonFunctionContainer clone_model_on_replicas_fn get;

PythonFunctionContainer concat_along_batch_dimension_fn get;

PythonFunctionContainer distributed_scope_fn get;

PythonFunctionContainer filter_distributed_callbacks_fn get;

PythonFunctionContainer flatten_per_replica_values_fn get;

PythonFunctionContainer get_batch_dimension_fn get;

PythonFunctionContainer get_distributed_function_fn get;

PythonFunctionContainer get_distributed_model_fn get;

PythonFunctionContainer get_input_params_fn get;

PythonFunctionContainer get_iterator_fn get;

PythonFunctionContainer global_batch_size_supported_fn get;

PythonFunctionContainer init_restore_or_wait_for_variables_fn get;

PythonFunctionContainer initialize_iterator_fn get;

PythonFunctionContainer is_current_worker_chief_fn get;

PythonFunctionContainer is_dataset_shape_fully_defined_fn get;

PythonFunctionContainer is_distributing_by_cloning_fn get;

PythonFunctionContainer is_tpu_strategy_fn get;

PythonFunctionContainer process_batch_and_step_size_fn get;

PythonFunctionContainer set_distributed_function_fn get;

PythonFunctionContainer set_distributed_model_fn get;

PythonFunctionContainer set_weights_fn get;

PythonFunctionContainer unwrap_output_dict_fn get;

PythonFunctionContainer unwrap_outputs_fn get;

PythonFunctionContainer unwrap_values_fn get;

PythonFunctionContainer validate_all_tensor_shapes_fn get;

PythonFunctionContainer validate_all_tensor_types_fn get;

PythonFunctionContainer validate_callbacks_fn get;

PythonFunctionContainer validate_distributed_dataset_inputs_fn get;

PythonFunctionContainer validate_inputs_fn get;

PythonFunctionContainer validate_per_replica_inputs_fn get;