diff --git a/doc/_sources/algorithm/rnn/rnn.txt b/doc/_sources/algorithm/rnn/rnn.txt index 4753db450b744d3860d69e3928147b0932a9630f..0ab75a130686f85d1e719125bc7445175047f2d5 100644 --- a/doc/_sources/algorithm/rnn/rnn.txt +++ b/doc/_sources/algorithm/rnn/rnn.txt @@ -202,14 +202,17 @@ After training the model, we can use it to generate sequences. A common practice * use :code:`GeneratedInput` for trg_embedding. :code:`GeneratedInput` computes the embedding of the generated token at the last time step for the input at the current time step. * use :code:`beam_search` function. This function needs to set: - - :code:`id_input`: the integer ID of the data, used to identify the corresponding output in the generated files. - - :code:`dict_file`: the dictionary file for converting word id to word. - :code:`bos_id`: the start token. Every sentence starts with the start token. - :code:`eos_id`: the end token. Every sentence ends with the end token. - :code:`beam_size`: the beam size used in beam search. - :code:`max_length`: the maximum length of the generated sentences. - - :code:`result_file`: the path of the generation result file. +* use :code:`seqtext_printer_evaluator` to print text according to index matrix and dictionary. This function needs to set: + + - :code:`id_input`: the integer ID of the data, used to identify the corresponding output in the generated files. + - :code:`dict_file`: the dictionary file for converting word id to word. + - :code:`result_file`: the path of the generation result file. + The code is listed below: .. code-block:: python @@ -230,14 +233,15 @@ The code is listed below: beam_gen = beam_search(name=decoder_group_name, step=gru_decoder_with_attention, input=group_inputs, - id_input=data_layer(name="sent_id", - size=1), - dict_file=trg_dict_path, bos_id=0, # Beginnning token. eos_id=1, # End of sentence token. beam_size=beam_size, - max_length=max_length, - result_file=gen_trans_file) + max_length=max_length) + + seqtext_printer_evaluator(input=beam_gen, + id_input=data_layer(name="sent_id", size=1), + dict_file=trg_dict_path, + result_file=gen_trans_file) outputs(beam_gen) diff --git a/doc/algorithm/rnn/rnn.html b/doc/algorithm/rnn/rnn.html index 9d14cdb2680d89dcc022cbb628b3713df23e589b..c974b2a6a1e118585342f9d2d494cfca7c71ab55 100644 --- a/doc/algorithm/rnn/rnn.html +++ b/doc/algorithm/rnn/rnn.html @@ -200,12 +200,15 @@ Its output function simply takes \(x_t\)
  • use GeneratedInput for trg_embedding. GeneratedInput computes the embedding of the generated token at the last time step for the input at the current time step.
  • use beam_search function. This function needs to set: +
  • +
  • use seqtext_printer_evaluator to print text according to index matrix and dictionary. This function needs to set:
  • @@ -227,14 +230,15 @@ Its output function simply takes \(x_t\)beam_gen = beam_search(name=decoder_group_name, step=gru_decoder_with_attention, input=group_inputs, - id_input=data_layer(name="sent_id", - size=1), - dict_file=trg_dict_path, bos_id=0, # Beginnning token. eos_id=1, # End of sentence token. beam_size=beam_size, - max_length=max_length, - result_file=gen_trans_file) + max_length=max_length) + +seqtext_printer_evaluator(input=beam_gen, + id_input=data_layer(name="sent_id", size=1), + dict_file=trg_dict_path, + result_file=gen_trans_file) outputs(beam_gen) diff --git a/doc/searchindex.js b/doc/searchindex.js index c7d095908c61f57f9053ada0c2646abfd430d9f9..66be096cb6724fd832d7a413f1b814fe1a93ef1d 100644 --- a/doc/searchindex.js +++ b/doc/searchindex.js @@ -1 +1 @@ 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\ No newline at end of file diff --git a/doc/ui/api/trainer_config_helpers/evaluators.html b/doc/ui/api/trainer_config_helpers/evaluators.html index 93a763829ddc64dda5a8a395678c5676d580cef2..703d0c98a6afe957ccfe73b3c18f644dcee74116 100644 --- a/doc/ui/api/trainer_config_helpers/evaluators.html +++ b/doc/ui/api/trainer_config_helpers/evaluators.html @@ -499,10 +499,11 @@ It contains one or more input layers.

    paddle.trainer_config_helpers.evaluators.seqtext_printer_evaluator(*args, **kwargs)

    Sequence text printer will print text according to index matrix and a dictionary. There can be multiple input to this layer:

    -

    1. If there is only one input, the input must be a matrix containing +

    1. If there is no id_input, the input must be a matrix containing the sequence of indices;

    -

    2. If there are more than one input, the first input should be ids, -and are interpreted as sample ids.

    +
      +
    1. If there is id_input, it should be ids, and interpreted as sample ids.
    2. +

    The output format will be:

    1. sequence without sub-sequence, and there is probability.
    2. @@ -527,7 +528,8 @@ and are interpreted as sample ids.

      Typically SequenceTextPrinter layer takes output of maxid or RecurrentGroup with maxid (when generating) as an input.

      The simple usage is:

      -
      eval = seqtext_printer_evaluator(input,
      +
      eval = seqtext_printer_evaluator(input=maxid_layer,
      +                                 id_input=sample_id,
                                        dict_file=dict_file,
                                        result_file=result_file)
       
      @@ -536,16 +538,29 @@ with maxid (when generating) as an input.

      -Parameters:
        +Parameters:
        • input (LayerOutput|list) – Input Layer name.
        • -
        • dict_file (basestring) – The input dictionary which contains a list of tokens.
        • -
        • result_file (basestring) – The file is to save the results.
        • +
        • result_file (basestring) – Path of the file to store the generated results.
        • +
        • id_input (LayerOutput) – Index of the input sequence, and the specified index will +be prited in the gereated results. This an optional +parameter.
        • +
        • dict_file (basestring) – Path of dictionary. This is an optional parameter. +Every line is a word in the dictionary with +(line number - 1) as the word index. +If this parameter is set to None, or to an empty string, +only word index are printed in the generated results.
        • delimited (bool) – Whether to use space to separate output tokens. Default is True. No space is added if set to False.
        • name (None|basestring) – Evaluator name.
        +Returns:

        The seq_text_printer that prints the generated sequence to a file.

        + + +Return type:

        evaluator

        + +
    diff --git a/doc/ui/api/trainer_config_helpers/layers.html b/doc/ui/api/trainer_config_helpers/layers.html index ab6faee35bd33c2e1714b68d6a228ff5ed18bd83..d46749ba31f305dbaf9adb435fdb521bcfe28682 100644 --- a/doc/ui/api/trainer_config_helpers/layers.html +++ b/doc/ui/api/trainer_config_helpers/layers.html @@ -978,8 +978,7 @@ to maintain tractability.

    input=[StaticInput(encoder_last)], bos_id=0, eos_id=1, - beam_size=5, - result_file="./generated_sequences.txt") + beam_size=5)

    Please see the following demo for more details:

    @@ -1015,25 +1014,16 @@ algorithm. To maintain tractability, every iteration only only stores a predetermined number, called the beam_size, of the most promising next words. The greater the beam size, the fewer candidate words are pruned. -
  • result_file (basestring) – Path of the file to store the generated results.
  • -
  • dict_file (basestring) – Path of dictionary. This is an optional parameter. -Every line is a word in the dictionary with -(line number - 1) as the word index. -If this parameter is set to None, or to an empty string, -only word index are printed in the generated results.
  • num_results_per_sample (int) – Number of the generated results per input sequence. This number must always be less than beam size.
  • -
  • id_input (LayerOutput) – Index of the input sequence, and the specified index will -be prited in the gereated results. This an optional -parameter.
  • -Returns:

    The seq_text_printer that prints the generated sequence to a file.

    +Returns:

    The generated word index.

    -Return type:

    evaluator

    +Return type:

    LayerOutput