σ VΎχXc@`s7dZddlmZddlmZddlmZddlmZddlmZddl m Z ddl m Z dd l mZdd l mZdd l mZdd l mZdd l mZddl mZd„Zded„Zded„Zdeed„Zdded„Zdddd„ZdS(sLSTM layers for sequences.i(tabsolute_import(tdivision(tprint_function(txrange(t variables(tcore_rnn_cell_impl(t constant_op(t array_ops(tmath_ops(tnn_ops(t random_ops(trnn(tvariable_scopecC`s|jƒjƒS(N(t get_shapetas_list(ttensor((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pyt_shape!scC`stj|d|gƒt|ƒ\}}}tj|dtƒ}tj||jgƒ}g} tj|ƒ} |r‹t t | ƒƒ} nxYt |ƒD]K} | dkr½tj ƒj ƒn|| | |ƒ\} }| | g7} q˜W|rt t | ƒƒ} ntj| ƒ} | SWdQXdS(sZRun an LSTM, either forward or backward. This is a 1D LSTM implementation using unrolling and the TensorFlow LSTM op. Args: inputs: input sequence (length, batch_size, ninput) noutput: depth of output scope: optional scope name reverse: run LSTM in reverse Returns: Output sequence (length, batch_size, noutput) tSeqLstmUnrolledtstate_is_tupleiN(R RRt BasicLSTMCelltFalseRtzerost state_sizetunstacktlisttreversedRtget_variable_scopetreuse_variableststack(tinputstnoutputtscopetreversetlengtht batch_sizet_t lstm_celltstatetoutput_utinputs_utitoutputtoutputs((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pytndlstm_base_unrolled%s" c C`sύtj|d|gƒίt|ƒ\}}}tj|dtƒ}tj||jgƒ}t|j ƒdƒ}t j tj |g|ƒƒ} |r­tj |dgƒ}ntj||| |dtƒ\} }|rοtj | dgƒ} n| SWdQXdS(s[Run an LSTM, either forward or backward. This is a 1D LSTM implementation using dynamic_rnn and the TensorFlow LSTM op. Args: inputs: input sequence (length, batch_size, ninput) noutput: depth of output scope: optional scope name reverse: run LSTM in reverse Returns: Output sequence (length, batch_size, noutput) tSeqLstmRit time_majorN(R RRRRRRRtintR Rtto_int64tfillt reverse_v2R t dynamic_rnntTrue( RRRR R#R"R$R%tsequence_lengthtsequence_lengthsR*((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pytndlstm_base_dynamicHscC`s<|rt||d|d|ƒSt||d|d|ƒSdS(s9Implements a 1D LSTM, either forward or backward. This is a base case for multidimensional LSTM implementations, which tend to be used differently from sequence-to-sequence implementations. For general 1D sequence to sequence transformations, you may want to consider another implementation from TF slim. Args: inputs: input sequence (length, batch_size, ninput) noutput: depth of output scope: optional scope name reverse: run LSTM in reverse dynamic: use dynamic_rnn Returns: Output sequence (length, batch_size, noutput) RR N(R6R+(RRRR tdynamic((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pyt ndlstm_baseisc C`stj|d|gƒβt|ƒ\}}}tj|dtƒ}tj||jgƒ} tj|ƒ} |r…t t | ƒƒ} nxLt |ƒD]>} | dkr·tj ƒj ƒn|| | | ƒ\} } q’Wtj| ||gd|ƒ} | SWdQXdS(s6Run an LSTM across all steps and returns only the final state. Args: inputs: (length, batch_size, depth) tensor noutput: size of output vector scope: optional scope name name: optional name for output tensor reverse: run in reverse Returns: Batch of size (batch_size, noutput). tSequenceToFinalRitnameN(R RRRRRRRRRRRRRtreshape(RRRR:R R!R"R#tlstmR%R'R(R)R*((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pytsequence_to_final…s  cC`s8t|ƒ\}}}tj|ƒ}g} tj|d|gƒπtjd||gddƒ} tjdd|gƒ} tj dd| ƒ} tj dd| ƒ} xrt |ƒD]d}tj|d ||gƒ@t j ||| | d |ƒ}t j |ƒ}| |g7} Wd QXq±Wtj| d |ƒ}Wd QX|S( sVRun a softmax layer over all the time steps of an input sequence. Args: inputs: (length, batch_size, depth) tensor noutput: output depth scope: optional scope name name: optional name for output tensor linear_name: name for linear (pre-softmax) output Returns: A tensor of size (length, batch_size, noutput). tSequenceSoftmaxitstddevgš™™™™™Ή?tshapetweightst initializertbiasestSequenceSoftmaxStepR:N(RRRR R ttruncated_normalRtconstantRtmodel_variableRR t xw_plus_btsoftmaxR(RRRR:t linear_nameR!R#tninputsR'R&t initial_wt initial_btwtbR(tlinearR)R*((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pytsequence_softmax‘s  N(t__doc__t __future__RRRt six.movesRt'tensorflow.contrib.framework.python.opsRt!tensorflow.contrib.rnn.python.opsRttensorflow.python.frameworkRttensorflow.python.opsRRR R R R RtNoneRR+R6R3R8R=RQ(((si/tmp/pip-build-h1VYrz/tensorflow/tensorflow-1.0.1.data/purelib/tensorflow/contrib/ndlstm/python/lstm1d.pyts& #!