LostTech.TensorFlow : API Documentation

Type learn

Namespace tensorflow.contrib.learn

Methods

Properties

Fields

Public static methods

_BinarySvmHead binary_svm_head(string label_name, string weight_column_name, bool enable_centered_bias, object head_name, object thresholds)

object binary_svm_head_dyn(object label_name, object weight_column_name, ImplicitContainer<T> enable_centered_bias, object head_name, object thresholds)

object build_default_serving_input_fn(IDictionary<string, object> features, object default_batch_size)

object build_default_serving_input_fn_dyn(object features, object default_batch_size)

object build_parsing_serving_input_fn(IDictionary<object, object> feature_spec, object default_batch_size)

object build_parsing_serving_input_fn_dyn(object feature_spec, object default_batch_size)

ValueTuple<object, object> evaluate(object graph, Byte[] output_dir, object checkpoint_path, IDictionary<string, object> eval_dict, IGraphNodeBase update_op, object global_step_tensor, string supervisor_master, int log_every_steps, PythonFunctionContainer feed_fn, Nullable<int> max_steps)

ValueTuple<object, object> evaluate(object graph, string output_dir, object checkpoint_path, IDictionary<string, object> eval_dict, IGraphNodeBase update_op, object global_step_tensor, string supervisor_master, int log_every_steps, PythonFunctionContainer feed_fn, Nullable<int> max_steps)

object evaluate_dyn(object graph, object output_dir, object checkpoint_path, object eval_dict, object update_op, object global_step_tensor, ImplicitContainer<T> supervisor_master, ImplicitContainer<T> log_every_steps, object feed_fn, object max_steps)

void export_estimator(object estimator, object export_dir, PythonFunctionContainer signature_fn, ImplicitContainer<T> input_fn, int default_batch_size, object exports_to_keep)

object export_estimator_dyn(object estimator, object export_dir, object signature_fn, ImplicitContainer<T> input_fn, ImplicitContainer<T> default_batch_size, object exports_to_keep)

object extract_dask_data(IEnumerable<object> data)

object extract_dask_data(object data)

object extract_dask_data_dyn(object data)

Nullable<ValueTuple<object, object>> extract_dask_labels(Nullable<ValueTuple<object, object>> labels)

object extract_dask_labels_dyn(object labels)

object extract_pandas_data(object data)

object extract_pandas_data(IEnumerable<object> data)

object extract_pandas_data_dyn(object data)

Nullable<ValueTuple<object, object>> extract_pandas_labels(Nullable<ValueTuple<object, object>> labels)

object extract_pandas_labels_dyn(object labels)

IList<object> extract_pandas_matrix(IEnumerable<object> data)

object extract_pandas_matrix_dyn(object data)

object generator_input_fn(PythonFunctionContainer x, string target_key, int batch_size, int num_epochs, bool shuffle, int queue_capacity, int num_threads, object pad_value)

object generator_input_fn(PythonFunctionContainer x, IEnumerable<object> target_key, int batch_size, int num_epochs, bool shuffle, int queue_capacity, int num_threads, object pad_value)

object generator_input_fn_dyn(object x, object target_key, ImplicitContainer<T> batch_size, ImplicitContainer<T> num_epochs, ImplicitContainer<T> shuffle, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads, object pad_value)

object infer(object restore_checkpoint_path, IDictionary<string, object> output_dict, IDictionary<object, double> feed_dict)

object infer_dyn(object restore_checkpoint_path, object output_dict, object feed_dict)

object infer_real_valued_columns_from_input(IGraphNodeBase x)

object infer_real_valued_columns_from_input(ndarray x)

object infer_real_valued_columns_from_input_dyn(object x)

IList<_RealValuedColumn> infer_real_valued_columns_from_input_fn(PythonFunctionContainer input_fn)

object infer_real_valued_columns_from_input_fn_dyn(object input_fn)

Estimator LogisticRegressor(PythonFunctionContainer model_fn, object thresholds, object model_dir, object config, PythonFunctionContainer feature_engineering_fn)

object LogisticRegressor_dyn(object model_fn, object thresholds, object model_dir, object config, object feature_engineering_fn)

_LossOnlyHead loss_only_head(PythonFunctionContainer loss_fn, string head_name)

object loss_only_head_dyn(object loss_fn, object head_name)

ExportStrategy make_export_strategy(PythonFunctionContainer serving_input_fn, string default_output_alternative_key, IDictionary<string, string> assets_extra, bool as_text, Nullable<int> exports_to_keep, Nullable<bool> strip_default_attrs)

ExportStrategy make_export_strategy(Estimator serving_input_fn, string default_output_alternative_key, IDictionary<string, string> assets_extra, bool as_text, Nullable<int> exports_to_keep, Nullable<bool> strip_default_attrs)

ExportStrategy make_export_strategy(Evaluable serving_input_fn, string default_output_alternative_key, IDictionary<string, string> assets_extra, bool as_text, Nullable<int> exports_to_keep, Nullable<bool> strip_default_attrs)

object make_export_strategy_dyn(object serving_input_fn, object default_output_alternative_key, object assets_extra, ImplicitContainer<T> as_text, ImplicitContainer<T> exports_to_keep, object strip_default_attrs)

object multi_class_head(Nullable<int> n_classes, string label_name, string weight_column_name, bool enable_centered_bias, int head_name, object thresholds, IEnumerable<int> metric_class_ids, PythonFunctionContainer loss_fn, IEnumerable<Byte[]> label_keys)

object multi_class_head(Nullable<int> n_classes, string label_name, string weight_column_name, bool enable_centered_bias, int head_name, object thresholds, IEnumerable<int> metric_class_ids, PythonFunctionContainer loss_fn, ValueTuple<string, string, string> label_keys)

object multi_class_head(Nullable<int> n_classes, string label_name, string weight_column_name, bool enable_centered_bias, string head_name, object thresholds, IEnumerable<int> metric_class_ids, PythonFunctionContainer loss_fn, IEnumerable<Byte[]> label_keys)

object multi_class_head(Nullable<int> n_classes, string label_name, string weight_column_name, bool enable_centered_bias, string head_name, object thresholds, IEnumerable<int> metric_class_ids, PythonFunctionContainer loss_fn, ValueTuple<string, string, string> label_keys)

object multi_class_head_dyn(object n_classes, object label_name, object weight_column_name, ImplicitContainer<T> enable_centered_bias, object head_name, object thresholds, object metric_class_ids, object loss_fn, object label_keys)

_MultiHead multi_head(ValueTuple<object, object> heads, Nullable<ValueTuple<int, double>> loss_weights)

object multi_head_dyn(object heads, object loss_weights)

_MultiLabelHead multi_label_head(int n_classes, string label_name, string weight_column_name, bool enable_centered_bias, string head_name, object thresholds, IEnumerable<int> metric_class_ids, PythonFunctionContainer loss_fn)

object multi_label_head_dyn(object n_classes, object label_name, object weight_column_name, ImplicitContainer<T> enable_centered_bias, object head_name, object thresholds, object metric_class_ids, object loss_fn)

object no_op_train_fn(IEnumerable<object> loss)

object no_op_train_fn(ValueTuple<PythonClassContainer, PythonClassContainer> loss)

object no_op_train_fn(IGraphNodeBase loss)

object no_op_train_fn_dyn(object loss)

object numpy_input_fn(object x, object y, int batch_size, int num_epochs, bool shuffle, int queue_capacity, int num_threads)

object numpy_input_fn_dyn(object x, object y, ImplicitContainer<T> batch_size, ImplicitContainer<T> num_epochs, ImplicitContainer<T> shuffle, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads)

PythonFunctionContainer pandas_input_fn(object x, object y, int batch_size, int num_epochs, bool shuffle, Nullable<int> queue_capacity, int num_threads, string target_column)

object pandas_input_fn_dyn(object x, object y, ImplicitContainer<T> batch_size, ImplicitContainer<T> num_epochs, ImplicitContainer<T> shuffle, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads, ImplicitContainer<T> target_column)

_RegressionHead poisson_regression_head(object label_name, object weight_column_name, int label_dimension, bool enable_centered_bias, object head_name)

object poisson_regression_head_dyn(object label_name, object weight_column_name, ImplicitContainer<T> label_dimension, ImplicitContainer<T> enable_centered_bias, object head_name)

ValueTuple<object, object> queue_parsed_features(IDictionary<string, object> parsed_features, IEnumerable<SparseTensor> keys, int feature_queue_capacity, int num_enqueue_threads, string name)

ValueTuple<object, object> queue_parsed_features(IDictionary<string, object> parsed_features, PythonClassContainer keys, int feature_queue_capacity, int num_enqueue_threads, string name)

ValueTuple<object, object> queue_parsed_features(IDictionary<string, object> parsed_features, IDictionary<object, object> keys, int feature_queue_capacity, int num_enqueue_threads, string name)

ValueTuple<object, object> queue_parsed_features(IDictionary<string, object> parsed_features, SparseTensor keys, int feature_queue_capacity, int num_enqueue_threads, string name)

object queue_parsed_features_dyn(object parsed_features, object keys, ImplicitContainer<T> feature_queue_capacity, ImplicitContainer<T> num_enqueue_threads, object name)

object read_batch_examples(string file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_batch_examples(string file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_batch_examples(IEnumerable<string> file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_batch_examples(IEnumerable<string> file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_batch_examples_dyn(object file_pattern, object batch_size, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads, ImplicitContainer<T> read_batch_size, object parse_fn, object name, object seed)

IDictionary<object, object> read_batch_features(string file_pattern, int batch_size, IDictionary<string, object> features, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int feature_queue_capacity, int reader_num_threads, int num_enqueue_threads, PythonFunctionContainer parse_fn, string name, object read_batch_size)

IDictionary<object, object> read_batch_features(string file_pattern, int batch_size, IDictionary<string, object> features, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int feature_queue_capacity, int reader_num_threads, int num_enqueue_threads, PythonFunctionContainer parse_fn, string name, object read_batch_size)

object read_batch_features_dyn(object file_pattern, object batch_size, object features, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> feature_queue_capacity, ImplicitContainer<T> reader_num_threads, ImplicitContainer<T> num_enqueue_threads, object parse_fn, object name, object read_batch_size)

IDictionary<object, object> read_batch_record_features(string file_pattern, int batch_size, IDictionary<string, object> features, bool randomize_input, object num_epochs, int queue_capacity, int reader_num_threads, string name)

object read_batch_record_features_dyn(object file_pattern, object batch_size, object features, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> reader_num_threads, ImplicitContainer<T> name)

object read_keyed_batch_examples(string file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, Nullable<int> read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples(string file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, Nullable<int> read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples(IEnumerable<string> file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, Nullable<int> read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples(IEnumerable<string> file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, Nullable<int> read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples_dyn(object file_pattern, object batch_size, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads, ImplicitContainer<T> read_batch_size, object parse_fn, object name, object seed)

object read_keyed_batch_examples_shared_queue(string file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples_shared_queue(IEnumerable<object> file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples_shared_queue(string file_pattern, int batch_size, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples_shared_queue(IEnumerable<object> file_pattern, int batch_size, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int num_threads, int read_batch_size, PythonFunctionContainer parse_fn, string name, object seed)

object read_keyed_batch_examples_shared_queue_dyn(object file_pattern, object batch_size, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> num_threads, ImplicitContainer<T> read_batch_size, object parse_fn, object name, object seed)

ValueTuple<object, object> read_keyed_batch_features(string file_pattern, int batch_size, IDictionary<string, object> features, PythonClassContainer reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int reader_num_threads, int feature_queue_capacity, int num_enqueue_threads, PythonFunctionContainer parse_fn, string name, object read_batch_size)

ValueTuple<object, object> read_keyed_batch_features(string file_pattern, int batch_size, IDictionary<string, object> features, object reader, bool randomize_input, Nullable<int> num_epochs, int queue_capacity, int reader_num_threads, int feature_queue_capacity, int num_enqueue_threads, PythonFunctionContainer parse_fn, string name, object read_batch_size)

object read_keyed_batch_features_dyn(object file_pattern, object batch_size, object features, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> reader_num_threads, ImplicitContainer<T> feature_queue_capacity, ImplicitContainer<T> num_enqueue_threads, object parse_fn, object name, object read_batch_size)

ValueTuple<object, object> read_keyed_batch_features_shared_queue(string file_pattern, int batch_size, IDictionary<string, object> features, PythonClassContainer reader, bool randomize_input, object num_epochs, int queue_capacity, int reader_num_threads, int feature_queue_capacity, int num_queue_runners, PythonFunctionContainer parse_fn, string name)

ValueTuple<object, object> read_keyed_batch_features_shared_queue(string file_pattern, int batch_size, IDictionary<string, object> features, object reader, bool randomize_input, object num_epochs, int queue_capacity, int reader_num_threads, int feature_queue_capacity, int num_queue_runners, PythonFunctionContainer parse_fn, string name)

object read_keyed_batch_features_shared_queue_dyn(object file_pattern, object batch_size, object features, object reader, ImplicitContainer<T> randomize_input, object num_epochs, ImplicitContainer<T> queue_capacity, ImplicitContainer<T> reader_num_threads, ImplicitContainer<T> feature_queue_capacity, ImplicitContainer<T> num_queue_runners, object parse_fn, object name)

_RegressionHead regression_head(string label_name, string weight_column_name, int label_dimension, bool enable_centered_bias, Nullable<int> head_name, PythonFunctionContainer link_fn)

object regression_head_dyn(object label_name, object weight_column_name, ImplicitContainer<T> label_dimension, ImplicitContainer<T> enable_centered_bias, object head_name, object link_fn)

IList<object> run_feeds(Object[] args)

IList<object> run_feeds(IDictionary<string, object> kwargs, Object[] args)

object run_feeds_dyn(Object[] args)

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

IList<object> run_n(object output_dict, object feed_dict, object restore_checkpoint_path, int n)

object run_n_dyn(object output_dict, object feed_dict, object restore_checkpoint_path, ImplicitContainer<T> n)

object train(object graph, string output_dir, IGraphNodeBase train_op, IGraphNodeBase loss_op, object global_step_tensor, object init_op, object init_feed_dict, PythonFunctionContainer init_fn, int log_every_steps, bool supervisor_is_chief, string supervisor_master, int supervisor_save_model_secs, int keep_checkpoint_max, int supervisor_save_summaries_steps, PythonFunctionContainer feed_fn, Nullable<int> steps, bool fail_on_nan_loss, IEnumerable<BaseMonitor> monitors, Nullable<int> max_steps)

object train(object graph, Byte[] output_dir, IGraphNodeBase train_op, IGraphNodeBase loss_op, object global_step_tensor, object init_op, object init_feed_dict, PythonFunctionContainer init_fn, int log_every_steps, bool supervisor_is_chief, string supervisor_master, int supervisor_save_model_secs, int keep_checkpoint_max, int supervisor_save_summaries_steps, PythonFunctionContainer feed_fn, Nullable<int> steps, bool fail_on_nan_loss, IEnumerable<BaseMonitor> monitors, Nullable<int> max_steps)

object train_dyn(object graph, object output_dir, object train_op, object loss_op, object global_step_tensor, object init_op, object init_feed_dict, object init_fn, ImplicitContainer<T> log_every_steps, ImplicitContainer<T> supervisor_is_chief, ImplicitContainer<T> supervisor_master, ImplicitContainer<T> supervisor_save_model_secs, ImplicitContainer<T> keep_checkpoint_max, ImplicitContainer<T> supervisor_save_summaries_steps, object feed_fn, object steps, ImplicitContainer<T> fail_on_nan_loss, object monitors, object max_steps)

Public properties

PythonFunctionContainer binary_svm_head_fn get;

PythonFunctionContainer build_default_serving_input_fn_fn get;

PythonFunctionContainer build_parsing_serving_input_fn_fn get;

PythonFunctionContainer evaluate_fn get;

PythonFunctionContainer export_estimator_fn get;

PythonFunctionContainer extract_dask_data_fn get;

PythonFunctionContainer extract_dask_labels_fn get;

PythonFunctionContainer extract_pandas_data_fn get;

PythonFunctionContainer extract_pandas_labels_fn get;

PythonFunctionContainer extract_pandas_matrix_fn get;

PythonFunctionContainer generator_input_fn_fn get;

PythonFunctionContainer infer_fn get;

PythonFunctionContainer infer_real_valued_columns_from_input_fn_ get;

PythonFunctionContainer infer_real_valued_columns_from_input_fn_fn get;

PythonFunctionContainer LogisticRegressor_fn get;

PythonFunctionContainer loss_only_head_fn get;

PythonFunctionContainer make_export_strategy_fn get;

PythonFunctionContainer multi_class_head_fn get;

PythonFunctionContainer multi_head_fn get;

PythonFunctionContainer multi_label_head_fn get;

PythonFunctionContainer no_op_train_fn_fn get;

PythonFunctionContainer numpy_input_fn_fn get;

PythonFunctionContainer pandas_input_fn_fn get;

PythonFunctionContainer poisson_regression_head_fn get;

PythonFunctionContainer queue_parsed_features_fn get;

PythonFunctionContainer read_batch_examples_fn get;

PythonFunctionContainer read_batch_features_fn get;

PythonFunctionContainer read_batch_record_features_fn get;

PythonFunctionContainer read_keyed_batch_examples_fn get;

PythonFunctionContainer read_keyed_batch_examples_shared_queue_fn get;

PythonFunctionContainer read_keyed_batch_features_fn get;

PythonFunctionContainer read_keyed_batch_features_shared_queue_fn get;

PythonFunctionContainer regression_head_fn get;

PythonFunctionContainer run_feeds_fn get;

PythonFunctionContainer run_n_fn get;

PythonFunctionContainer train_fn get;

Public fields

bool HAS_DASK

return bool

bool HAS_PANDAS

return bool