LostTech.TensorFlow : API Documentation

Type training

Namespace tensorflow.contrib.training

Methods

Properties

Public static methods

IList<Tensor> add_gradients_summaries(IEnumerable<object> grads_and_vars)

object add_gradients_summaries_dyn(object grads_and_vars)

NextQueuedSequenceBatch batch_sequences_with_states(IGraphNodeBase input_key, IDictionary<string, object> input_sequences, IDictionary<string, IEnumerable<int>> input_context, Nullable<int> input_length, IDictionary<string, object> initial_states, int num_unroll, int batch_size, int num_threads, int capacity, bool allow_small_batch, bool pad, bool make_keys_unique, Nullable<int> make_keys_unique_seed, string name)

NextQueuedSequenceBatch batch_sequences_with_states(string input_key, IDictionary<string, object> input_sequences, IDictionary<string, IEnumerable<int>> input_context, Nullable<int> input_length, IDictionary<string, object> initial_states, int num_unroll, int batch_size, int num_threads, int capacity, bool allow_small_batch, bool pad, bool make_keys_unique, Nullable<int> make_keys_unique_seed, string name)

object batch_sequences_with_states_dyn(object input_key, object input_sequences, object input_context, object input_length, object initial_states, object num_unroll, object batch_size, ImplicitContainer<T> num_threads, ImplicitContainer<T> capacity, ImplicitContainer<T> allow_small_batch, ImplicitContainer<T> pad, ImplicitContainer<T> make_keys_unique, object make_keys_unique_seed, object name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IGraphNodeBase which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, ValueTuple<IEnumerable<object>, object> which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IndexedSlices which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, ValueTuple<IEnumerable<object>, object> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, IGraphNodeBase keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, IEnumerable<int> batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket(IEnumerable<SparseTensor> tensors, IEnumerable<object> which_bucket, int batch_size, int num_buckets, int num_threads, int capacity, IEnumerable<int> bucket_capacities, IEnumerable<object> shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

ValueTuple<object, object> bucket_by_sequence_length(object input_length, IEnumerable<object> tensors, int batch_size, IEnumerable<int> bucket_boundaries, int num_threads, int capacity, IEnumerable<int> bucket_capacities, object shapes, bool dynamic_pad, bool allow_smaller_final_batch, bool keep_input, object shared_name, string name)

object bucket_by_sequence_length_dyn(object input_length, object tensors, object batch_size, object bucket_boundaries, ImplicitContainer<T> num_threads, ImplicitContainer<T> capacity, object bucket_capacities, object shapes, ImplicitContainer<T> dynamic_pad, ImplicitContainer<T> allow_smaller_final_batch, ImplicitContainer<T> keep_input, object shared_name, object name)

object bucket_dyn(object tensors, object which_bucket, object batch_size, object num_buckets, ImplicitContainer<T> num_threads, ImplicitContainer<T> capacity, object bucket_capacities, object shapes, ImplicitContainer<T> dynamic_pad, ImplicitContainer<T> allow_smaller_final_batch, ImplicitContainer<T> keep_input, object shared_name, object name)

PythonFunctionContainer byte_size_load_fn(object op)

object byte_size_load_fn_dyn(object op)

IEnumerator<object> checkpoints_iterator(string checkpoint_dir, int min_interval_secs, Nullable<double> timeout, PythonFunctionContainer timeout_fn)

Continuously yield new checkpoint files as they appear.

The iterator only checks for new checkpoints when control flow has been reverted to it. This means it can miss checkpoints if your code takes longer to run between iterations than `min_interval_secs` or the interval at which new checkpoints are written.

The `timeout` argument is the maximum number of seconds to block waiting for a new checkpoint. It is used in combination with the `timeout_fn` as follows:

* If the timeout expires and no `timeout_fn` was specified, the iterator stops yielding. * If a `timeout_fn` was specified, that function is called and if it returns a true boolean value the iterator stops yielding. * If the function returns a false boolean value then the iterator resumes the wait for new checkpoints. At this point the timeout logic applies again.

This behavior gives control to callers on what to do if checkpoints do not come fast enough or stop being generated. For example, if callers have a way to detect that the training has stopped and know that no new checkpoints will be generated, they can provide a `timeout_fn` that returns `True` when the training has stopped. If they know that the training is still going on they return `False` instead.
Parameters
string checkpoint_dir
The directory in which checkpoints are saved.
int min_interval_secs
The minimum number of seconds between yielding checkpoints.
Nullable<double> timeout
The maximum number of seconds to wait between checkpoints. If left as `None`, then the process will wait indefinitely.
PythonFunctionContainer timeout_fn
Optional function to call after a timeout. If the function returns True, then it means that no new checkpoints will be generated and the iterator will exit. The function is called with no arguments.

IEnumerator<object> checkpoints_iterator(string checkpoint_dir, int min_interval_secs, int timeout, PythonFunctionContainer timeout_fn)

object checkpoints_iterator_dyn(object checkpoint_dir, ImplicitContainer<T> min_interval_secs, object timeout, object timeout_fn)

Continuously yield new checkpoint files as they appear.

The iterator only checks for new checkpoints when control flow has been reverted to it. This means it can miss checkpoints if your code takes longer to run between iterations than `min_interval_secs` or the interval at which new checkpoints are written.

The `timeout` argument is the maximum number of seconds to block waiting for a new checkpoint. It is used in combination with the `timeout_fn` as follows:

* If the timeout expires and no `timeout_fn` was specified, the iterator stops yielding. * If a `timeout_fn` was specified, that function is called and if it returns a true boolean value the iterator stops yielding. * If the function returns a false boolean value then the iterator resumes the wait for new checkpoints. At this point the timeout logic applies again.

This behavior gives control to callers on what to do if checkpoints do not come fast enough or stop being generated. For example, if callers have a way to detect that the training has stopped and know that no new checkpoints will be generated, they can provide a `timeout_fn` that returns `True` when the training has stopped. If they know that the training is still going on they return `False` instead.
Parameters
object checkpoint_dir
The directory in which checkpoints are saved.
ImplicitContainer<T> min_interval_secs
The minimum number of seconds between yielding checkpoints.
object timeout
The maximum number of seconds to wait between checkpoints. If left as `None`, then the process will wait indefinitely.
object timeout_fn
Optional function to call after a timeout. If the function returns True, then it means that no new checkpoints will be generated and the iterator will exit. The function is called with no arguments.

IList<ValueTuple<object, object>> clip_gradient_norms(IEnumerable<object> gradients_to_variables, double max_norm)

object clip_gradient_norms_dyn(object gradients_to_variables, object max_norm)

object clip_gradient_norms_fn(double max_norm)

object clip_gradient_norms_fn_dyn(object max_norm)

Tensor create_train_op(IGraphNodeBase total_loss, Optimizer optimizer, ImplicitContainer<T> global_step, IEnumerable<object> update_ops, IEnumerable<object> variables_to_train, PythonFunctionContainer transform_grads_fn, bool summarize_gradients, ImplicitContainer<T> gate_gradients, object aggregation_method, bool colocate_gradients_with_ops, bool check_numerics)

object create_train_op_dyn(object total_loss, object optimizer, ImplicitContainer<T> global_step, object update_ops, object variables_to_train, object transform_grads_fn, ImplicitContainer<T> summarize_gradients, ImplicitContainer<T> gate_gradients, object aggregation_method, ImplicitContainer<T> colocate_gradients_with_ops, ImplicitContainer<T> check_numerics)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, IDictionary<object, object> eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, double timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, IDictionary<object, object> eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, Nullable<int> timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, ValueTuple<object, IEnumerable<object>> eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, double timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, ValueTuple<object, IEnumerable<object>> eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, Nullable<int> timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, IGraphNodeBase eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, double timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly(string checkpoint_dir, string master, Scaffold scaffold, IGraphNodeBase eval_ops, IDictionary<object, object> feed_dict, IDictionary<string, object> final_ops, object final_ops_feed_dict, int eval_interval_secs, IEnumerable<object> hooks, object config, Nullable<int> max_number_of_evaluations, Nullable<int> timeout, PythonFunctionContainer timeout_fn)

object evaluate_repeatedly_dyn(object checkpoint_dir, ImplicitContainer<T> master, object scaffold, object eval_ops, object feed_dict, object final_ops, object final_ops_feed_dict, ImplicitContainer<T> eval_interval_secs, object hooks, object config, object max_number_of_evaluations, object timeout, object timeout_fn)

IList<ValueTuple<object, object>> multiply_gradients(object grads_and_vars, IDictionary<object, object> gradient_multipliers)

object multiply_gradients_dyn(object grads_and_vars, object gradient_multipliers)

IDictionary<object, object> parse_values(IEnumerable<string> values, IDictionary<object, PythonClassContainer> type_map, bool ignore_unknown)

IDictionary<object, object> parse_values(string values, IDictionary<object, PythonClassContainer> type_map, bool ignore_unknown)

object parse_values_dyn(object values, object type_map, ImplicitContainer<T> ignore_unknown)

object rejection_sample(IEnumerable<IGraphNodeBase> tensors, PythonFunctionContainer accept_prob_fn, int batch_size, int queue_threads, bool enqueue_many, int prebatch_capacity, int prebatch_threads, bool runtime_checks, string name)

object rejection_sample_dyn(object tensors, object accept_prob_fn, object batch_size, ImplicitContainer<T> queue_threads, ImplicitContainer<T> enqueue_many, ImplicitContainer<T> prebatch_capacity, ImplicitContainer<T> prebatch_threads, ImplicitContainer<T> runtime_checks, object name)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IEnumerable<object> rates, string scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> rates, object scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> rates, string scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IndexedSlices rates, object scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IndexedSlices rates, string scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase rates, object scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase rates, string scope, Nullable<int> seed, bool back_prop)

IList<Tensor> resample_at_rate(IEnumerable<IGraphNodeBase> inputs, IEnumerable<object> rates, object scope, Nullable<int> seed, bool back_prop)

object resample_at_rate_dyn(object inputs, object rates, object scope, object seed, ImplicitContainer<T> back_prop)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IEnumerable<object> labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IGraphNodeBase labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IEnumerable<object> labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IGraphNodeBase labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IEnumerable<object> labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IEnumerable<object> labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IGraphNodeBase labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IGraphNodeBase labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IEnumerable<object> labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IGraphNodeBase labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IGraphNodeBase labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IEnumerable<object> labels, object target_probs, int batch_size, ndarray init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IEnumerable<object> labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IEnumerable<IGraphNodeBase> tensors, IEnumerable<object> labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, object init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IGraphNodeBase labels, object target_probs, int batch_size, IEnumerable<object> init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, IGraphNodeBase labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

ValueTuple<object, object> stratified_sample(IGraphNodeBase tensors, ValueTuple<IEnumerable<object>, object> labels, object target_probs, int batch_size, IGraphNodeBase init_probs, bool enqueue_many, int queue_capacity, int threads_per_queue, string name)

object stratified_sample_dyn(object tensors, object labels, object target_probs, object batch_size, object init_probs, ImplicitContainer<T> enqueue_many, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> threads_per_queue, object name)

object train(IGraphNodeBase train_op, object logdir, string master, bool is_chief, Scaffold scaffold, IEnumerable<StopAtStepHook> hooks, object chief_only_hooks, Nullable<int> save_checkpoint_secs, Nullable<int> save_summaries_steps, object config, int max_wait_secs, object run_metadata)

object train_dyn(object train_op, object logdir, ImplicitContainer<T> master, ImplicitContainer<T> is_chief, object scaffold, object hooks, object chief_only_hooks, ImplicitContainer<T> save_checkpoint_secs, ImplicitContainer<T> save_summaries_steps, object config, ImplicitContainer<T> max_wait_secs, object run_metadata)

object wait_for_new_checkpoint(string checkpoint_dir, string last_checkpoint, int seconds_to_sleep, double timeout)

object wait_for_new_checkpoint(string checkpoint_dir, string last_checkpoint, int seconds_to_sleep, Nullable<int> timeout)

object wait_for_new_checkpoint(string checkpoint_dir, string last_checkpoint, double seconds_to_sleep, double timeout)

object wait_for_new_checkpoint(string checkpoint_dir, string last_checkpoint, double seconds_to_sleep, Nullable<int> timeout)

object wait_for_new_checkpoint_dyn(object checkpoint_dir, object last_checkpoint, ImplicitContainer<T> seconds_to_sleep, object timeout)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IEnumerable<object> weights, double overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IEnumerable<object> weights, ValueTuple<PythonClassContainer, PythonClassContainer> overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IEnumerable<object> weights, IndexedSlices overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IEnumerable<object> weights, IGraphNodeBase overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> weights, double overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> weights, IGraphNodeBase overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> weights, IndexedSlices overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IndexedSlices weights, double overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IndexedSlices weights, IndexedSlices overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IndexedSlices weights, IGraphNodeBase overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IGraphNodeBase weights, double overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IGraphNodeBase weights, ValueTuple<PythonClassContainer, PythonClassContainer> overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IGraphNodeBase weights, IndexedSlices overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IGraphNodeBase weights, IGraphNodeBase overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, ValueTuple<PythonClassContainer, PythonClassContainer> weights, ValueTuple<PythonClassContainer, PythonClassContainer> overall_rate, object scope, double mean_decay, Nullable<int> seed)

ValueTuple<IList<Tensor>, object> weighted_resample(IEnumerable<object> inputs, IndexedSlices weights, ValueTuple<PythonClassContainer, PythonClassContainer> overall_rate, object scope, double mean_decay, Nullable<int> seed)

object weighted_resample_dyn(object inputs, object weights, object overall_rate, object scope, ImplicitContainer<T> mean_decay, object seed)

Public properties

PythonFunctionContainer _SequenceInputWrapper_fn get;

PythonFunctionContainer add_gradients_summaries_fn get;

PythonFunctionContainer batch_sequences_with_states_fn get;

PythonFunctionContainer bucket_by_sequence_length_fn get;

PythonFunctionContainer bucket_fn get;

PythonFunctionContainer byte_size_load_fn_fn get;

PythonFunctionContainer checkpoints_iterator_fn get;

PythonFunctionContainer clip_gradient_norms_fn_ get;

PythonFunctionContainer clip_gradient_norms_fn_fn get;

PythonFunctionContainer create_train_op_fn get;

PythonFunctionContainer evaluate_repeatedly_fn get;

PythonFunctionContainer GreedyLoadBalancingStrategy_fn get;

PythonFunctionContainer HParams_fn get;

PythonFunctionContainer multiply_gradients_fn get;

PythonFunctionContainer NextQueuedSequenceBatch_fn get;

PythonClassContainer PARAM_RE get; set;

object PARAM_RE_dyn get; set;

PythonFunctionContainer parse_values_fn get;

PythonFunctionContainer RandomStrategy_fn get;

PythonFunctionContainer rejection_sample_fn get;

PythonFunctionContainer resample_at_rate_fn get;

PythonFunctionContainer SequenceQueueingStateSaver_fn get;

PythonFunctionContainer stratified_sample_fn get;

PythonFunctionContainer train_fn get;

PythonFunctionContainer wait_for_new_checkpoint_fn get;

PythonFunctionContainer weighted_resample_fn get;