LostTech.TensorFlow : API Documentation

Type ops

Namespace tensorflow.contrib.learn.ops

Public static methods

Tensor categorical_variable(IGraphNodeBase tensor_in, int n_classes, int embedding_size, string name)

object categorical_variable_dyn(object tensor_in, object n_classes, object embedding_size, object name)

Tensor embedding_lookup(Variable params, IGraphNodeBase ids, string name)

Tensor embedding_lookup(PartitionedVariable params, IGraphNodeBase ids, string name)

object embedding_lookup_dyn(object params, object ids, ImplicitContainer<T> name)

ValueTuple<Tensor, object> mean_squared_error_regressor(IDictionary<object, object> tensor_in, IDictionary<object, object> labels, PartitionedVariable weights, Variable biases, string name)

ValueTuple<Tensor, object> mean_squared_error_regressor(IDictionary<object, object> tensor_in, IDictionary<object, object> labels, PartitionedVariable weights, PartitionedVariable biases, string name)

ValueTuple<Tensor, object> mean_squared_error_regressor(IDictionary<object, object> tensor_in, IDictionary<object, object> labels, Variable weights, Variable biases, string name)

ValueTuple<Tensor, object> mean_squared_error_regressor(IDictionary<object, object> tensor_in, IDictionary<object, object> labels, Variable weights, PartitionedVariable biases, string name)

object mean_squared_error_regressor_dyn(object tensor_in, object labels, object weights, object biases, object name)

ValueTuple<IList<object>, object, object, object> rnn_decoder(IEnumerable<IGraphNodeBase> decoder_inputs, AttentionWrapperState initial_state, GRUCell cell, object scope)

ValueTuple<IList<object>, object, object, object> rnn_decoder(IEnumerable<IGraphNodeBase> decoder_inputs, string initial_state, GRUCell cell, object scope)

ValueTuple<IList<object>, object, object, object> rnn_decoder(IEnumerable<IGraphNodeBase> decoder_inputs, object initial_state, GRUCell cell, object scope)

ValueTuple<IList<object>, object, object, object> rnn_decoder(IEnumerable<IGraphNodeBase> decoder_inputs, IGraphNodeBase initial_state, GRUCell cell, object scope)

ValueTuple<IList<object>, object, object, object> rnn_decoder(IEnumerable<IGraphNodeBase> decoder_inputs, IEnumerable<object> initial_state, GRUCell cell, object scope)

object rnn_decoder_dyn(object decoder_inputs, object initial_state, object cell, object scope)

IList<object> rnn_seq2seq(object encoder_inputs, object decoder_inputs, object encoder_cell, object decoder_cell, ImplicitContainer<T> dtype, object scope)

object rnn_seq2seq_dyn(object encoder_inputs, object decoder_inputs, object encoder_cell, object decoder_cell, ImplicitContainer<T> dtype, object scope)

ValueTuple<object, object, object> seq2seq_inputs(IGraphNodeBase x, IGraphNodeBase y, int input_length, int output_length, object sentinel, string name)

object seq2seq_inputs_dyn(object x, object y, object input_length, object output_length, object sentinel, object name)

ValueTuple<Tensor, object> sequence_classifier(IEnumerable<IGraphNodeBase> decoding, IEnumerable<IGraphNodeBase> labels, IEnumerable<IGraphNodeBase> sampling_decoding, string name)

object sequence_classifier_dyn(object decoding, object labels, object sampling_decoding, object name)

ValueTuple<Tensor, object> softmax_classifier(IGraphNodeBase tensor_in, IDictionary<object, object> labels, IGraphNodeBase weights, IGraphNodeBase biases, IGraphNodeBase class_weight, string name)

ValueTuple<Tensor, object> softmax_classifier(IDictionary<object, object> tensor_in, IGraphNodeBase labels, IGraphNodeBase weights, IGraphNodeBase biases, IGraphNodeBase class_weight, string name)

ValueTuple<Tensor, object> softmax_classifier(IDictionary<object, object> tensor_in, IDictionary<object, object> labels, IGraphNodeBase weights, IGraphNodeBase biases, IGraphNodeBase class_weight, string name)

ValueTuple<Tensor, object> softmax_classifier(IGraphNodeBase tensor_in, IGraphNodeBase labels, IGraphNodeBase weights, IGraphNodeBase biases, IGraphNodeBase class_weight, string name)

object softmax_classifier_dyn(object tensor_in, object labels, object weights, object biases, object class_weight, object name)

Public properties

PythonFunctionContainer categorical_variable_fn get;

PythonFunctionContainer embedding_lookup_fn get;

PythonFunctionContainer mean_squared_error_regressor_fn get;

PythonFunctionContainer rnn_decoder_fn get;

PythonFunctionContainer rnn_seq2seq_fn get;

PythonFunctionContainer seq2seq_inputs_fn get;

PythonFunctionContainer sequence_classifier_fn get;

PythonFunctionContainer softmax_classifier_fn get;