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| <h1>Source code for mxnet.rnn.io</h1><div class="highlight"><pre> |
| <span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span> |
| <span class="c1"># or more contributor license agreements. See the NOTICE file</span> |
| <span class="c1"># distributed with this work for additional information</span> |
| <span class="c1"># regarding copyright ownership. The ASF licenses this file</span> |
| <span class="c1"># to you under the Apache License, Version 2.0 (the</span> |
| <span class="c1"># "License"); you may not use this file except in compliance</span> |
| <span class="c1"># with the License. You may obtain a copy of the License at</span> |
| <span class="c1">#</span> |
| <span class="c1"># http://www.apache.org/licenses/LICENSE-2.0</span> |
| <span class="c1">#</span> |
| <span class="c1"># Unless required by applicable law or agreed to in writing,</span> |
| <span class="c1"># software distributed under the License is distributed on an</span> |
| <span class="c1"># "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span> |
| <span class="c1"># KIND, either express or implied. See the License for the</span> |
| <span class="c1"># specific language governing permissions and limitations</span> |
| <span class="c1"># under the License.</span> |
| |
| <span class="c1"># coding: utf-8</span> |
| <span class="c1"># pylint: disable=too-many-arguments, too-many-locals</span> |
| <span class="sd">"""Definition of various recurrent neural network cells."""</span> |
| <span class="kn">from</span> <span class="nn">__future__</span> <span class="k">import</span> <span class="n">print_function</span> |
| |
| <span class="kn">import</span> <span class="nn">bisect</span> |
| <span class="kn">import</span> <span class="nn">random</span> |
| <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span> |
| |
| <span class="kn">from</span> <span class="nn">..io</span> <span class="k">import</span> <span class="n">DataIter</span><span class="p">,</span> <span class="n">DataBatch</span><span class="p">,</span> <span class="n">DataDesc</span> |
| <span class="kn">from</span> <span class="nn">..</span> <span class="k">import</span> <span class="n">ndarray</span> |
| |
| <span class="k">def</span> <span class="nf">encode_sentences</span><span class="p">(</span><span class="n">sentences</span><span class="p">,</span> <span class="n">vocab</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">invalid_label</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> <span class="n">invalid_key</span><span class="o">=</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="p">,</span> |
| <span class="n">start_label</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">unknown_token</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> |
| <span class="sd">"""Encode sentences and (optionally) build a mapping</span> |
| <span class="sd"> from string tokens to integer indices. Unknown keys</span> |
| <span class="sd"> will be added to vocabulary.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> sentences : list of list of str</span> |
| <span class="sd"> A list of sentences to encode. Each sentence</span> |
| <span class="sd"> should be a list of string tokens.</span> |
| <span class="sd"> vocab : None or dict of str -> int</span> |
| <span class="sd"> Optional input Vocabulary</span> |
| <span class="sd"> invalid_label : int, default -1</span> |
| <span class="sd"> Index for invalid token, like <end-of-sentence></span> |
| <span class="sd"> invalid_key : str, default '\\n'</span> |
| <span class="sd"> Key for invalid token. Use '\\n' for end</span> |
| <span class="sd"> of sentence by default.</span> |
| <span class="sd"> start_label : int</span> |
| <span class="sd"> lowest index.</span> |
| <span class="sd"> unknown_token: str</span> |
| <span class="sd"> Symbol to represent unknown token.</span> |
| <span class="sd"> If not specified, unknown token will be skipped.</span> |
| |
| <span class="sd"> Returns</span> |
| <span class="sd"> -------</span> |
| <span class="sd"> result : list of list of int</span> |
| <span class="sd"> encoded sentences</span> |
| <span class="sd"> vocab : dict of str -> int</span> |
| <span class="sd"> result vocabulary</span> |
| <span class="sd"> """</span> |
| <span class="n">idx</span> <span class="o">=</span> <span class="n">start_label</span> |
| <span class="k">if</span> <span class="n">vocab</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> |
| <span class="n">vocab</span> <span class="o">=</span> <span class="p">{</span><span class="n">invalid_key</span><span class="p">:</span> <span class="n">invalid_label</span><span class="p">}</span> |
| <span class="n">new_vocab</span> <span class="o">=</span> <span class="kc">True</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">new_vocab</span> <span class="o">=</span> <span class="kc">False</span> |
| <span class="n">res</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">sent</span> <span class="ow">in</span> <span class="n">sentences</span><span class="p">:</span> |
| <span class="n">coded</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">word</span> <span class="ow">in</span> <span class="n">sent</span><span class="p">:</span> |
| <span class="k">if</span> <span class="n">word</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">vocab</span><span class="p">:</span> |
| <span class="k">assert</span> <span class="p">(</span><span class="n">new_vocab</span> <span class="ow">or</span> <span class="n">unknown_token</span><span class="p">),</span> <span class="s2">"Unknown token </span><span class="si">%s</span><span class="s2">"</span><span class="o">%</span><span class="n">word</span> |
| <span class="k">if</span> <span class="n">idx</span> <span class="o">==</span> <span class="n">invalid_label</span><span class="p">:</span> |
| <span class="n">idx</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="k">if</span> <span class="n">unknown_token</span><span class="p">:</span> |
| <span class="n">word</span> <span class="o">=</span> <span class="n">unknown_token</span> |
| <span class="n">vocab</span><span class="p">[</span><span class="n">word</span><span class="p">]</span> <span class="o">=</span> <span class="n">idx</span> |
| <span class="n">idx</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="n">coded</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">vocab</span><span class="p">[</span><span class="n">word</span><span class="p">])</span> |
| <span class="n">res</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">coded</span><span class="p">)</span> |
| |
| <span class="k">return</span> <span class="n">res</span><span class="p">,</span> <span class="n">vocab</span> |
| |
| <div class="viewcode-block" id="BucketSentenceIter"><a class="viewcode-back" href="../../../api/python/symbol/rnn.html#mxnet.rnn.BucketSentenceIter">[docs]</a><span class="k">class</span> <span class="nc">BucketSentenceIter</span><span class="p">(</span><span class="n">DataIter</span><span class="p">):</span> |
| <span class="sd">"""Simple bucketing iterator for language model.</span> |
| <span class="sd"> The label at each sequence step is the following token</span> |
| <span class="sd"> in the sequence.</span> |
| |
| <span class="sd"> Parameters</span> |
| <span class="sd"> ----------</span> |
| <span class="sd"> sentences : list of list of int</span> |
| <span class="sd"> Encoded sentences.</span> |
| <span class="sd"> batch_size : int</span> |
| <span class="sd"> Batch size of the data.</span> |
| <span class="sd"> invalid_label : int, optional</span> |
| <span class="sd"> Key for invalid label, e.g. <end-of-sentence>. The default is -1.</span> |
| <span class="sd"> dtype : str, optional</span> |
| <span class="sd"> Data type of the encoding. The default data type is 'float32'.</span> |
| <span class="sd"> buckets : list of int, optional</span> |
| <span class="sd"> Size of the data buckets. Automatically generated if None.</span> |
| <span class="sd"> data_name : str, optional</span> |
| <span class="sd"> Name of the data. The default name is 'data'.</span> |
| <span class="sd"> label_name : str, optional</span> |
| <span class="sd"> Name of the label. The default name is 'softmax_label'.</span> |
| <span class="sd"> layout : str, optional</span> |
| <span class="sd"> Format of data and label. 'NT' means (batch_size, length)</span> |
| <span class="sd"> and 'TN' means (length, batch_size).</span> |
| <span class="sd"> """</span> |
| <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sentences</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">buckets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">invalid_label</span><span class="o">=-</span><span class="mi">1</span><span class="p">,</span> |
| <span class="n">data_name</span><span class="o">=</span><span class="s1">'data'</span><span class="p">,</span> <span class="n">label_name</span><span class="o">=</span><span class="s1">'softmax_label'</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'float32'</span><span class="p">,</span> |
| <span class="n">layout</span><span class="o">=</span><span class="s1">'NT'</span><span class="p">):</span> |
| <span class="nb">super</span><span class="p">(</span><span class="n">BucketSentenceIter</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span> |
| <span class="k">if</span> <span class="ow">not</span> <span class="n">buckets</span><span class="p">:</span> |
| <span class="n">buckets</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">bincount</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">sentences</span><span class="p">]))</span> |
| <span class="k">if</span> <span class="n">j</span> <span class="o">>=</span> <span class="n">batch_size</span><span class="p">]</span> |
| <span class="n">buckets</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span> |
| |
| <span class="n">ndiscard</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="p">[[]</span> <span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="n">buckets</span><span class="p">]</span> |
| <span class="n">valid_buckets</span> <span class="o">=</span> <span class="p">{}</span> |
| <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">buckets</span><span class="p">)):</span> |
| <span class="n">valid_buckets</span><span class="p">[</span><span class="n">item</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span> |
| |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">sent</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sentences</span><span class="p">):</span> |
| <span class="n">buck</span> <span class="o">=</span> <span class="n">bisect</span><span class="o">.</span><span class="n">bisect_left</span><span class="p">(</span><span class="n">buckets</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">sent</span><span class="p">))</span> |
| <span class="n">valid_buckets</span><span class="p">[</span><span class="n">buck</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span> |
| <span class="k">if</span> <span class="n">buck</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">buckets</span><span class="p">):</span> |
| <span class="n">ndiscard</span> <span class="o">+=</span> <span class="mi">1</span> |
| <span class="k">continue</span> |
| <span class="n">buff</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">((</span><span class="n">buckets</span><span class="p">[</span><span class="n">buck</span><span class="p">],),</span> <span class="n">invalid_label</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span> |
| <span class="n">buff</span><span class="p">[:</span><span class="nb">len</span><span class="p">(</span><span class="n">sent</span><span class="p">)]</span> <span class="o">=</span> <span class="n">sent</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">buck</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">buff</span><span class="p">)</span> |
| <span class="n">buckets</span> <span class="o">=</span> <span class="p">[</span><span class="n">j</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">buckets</span><span class="p">)</span> <span class="k">if</span> <span class="n">valid_buckets</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">dtype</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="k">if</span> <span class="n">i</span><span class="p">]</span> |
| |
| <span class="nb">print</span><span class="p">(</span><span class="s2">"WARNING: discarded </span><span class="si">%d</span><span class="s2"> sentences longer than the largest bucket."</span><span class="o">%</span><span class="n">ndiscard</span><span class="p">)</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">=</span> <span class="n">batch_size</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">buckets</span> <span class="o">=</span> <span class="n">buckets</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">data_name</span> <span class="o">=</span> <span class="n">data_name</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">label_name</span> <span class="o">=</span> <span class="n">label_name</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">dtype</span> <span class="o">=</span> <span class="n">dtype</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">invalid_label</span> <span class="o">=</span> <span class="n">invalid_label</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">nddata</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">ndlabel</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">major_axis</span> <span class="o">=</span> <span class="n">layout</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">'N'</span><span class="p">)</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">layout</span> <span class="o">=</span> <span class="n">layout</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">default_bucket_key</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">buckets</span><span class="p">)</span> |
| |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">major_axis</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">provide_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">data_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">default_bucket_key</span><span class="p">),</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">provide_label</span> <span class="o">=</span> <span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">label_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">default_bucket_key</span><span class="p">),</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)]</span> |
| <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">major_axis</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">provide_data</span> <span class="o">=</span> <span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">data_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">default_bucket_key</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">),</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">provide_label</span> <span class="o">=</span> <span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">label_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">default_bucket_key</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">),</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)]</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Invalid layout </span><span class="si">%s</span><span class="s2">: Must by NT (batch major) or TN (time major)"</span><span class="p">)</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">idx</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">buck</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">):</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="o">.</span><span class="n">extend</span><span class="p">([(</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">)</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">buck</span><span class="p">)</span> <span class="o">-</span> <span class="n">batch_size</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)])</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">curr_idx</span> <span class="o">=</span> <span class="mi">0</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">reset</span><span class="p">()</span> |
| |
| <div class="viewcode-block" id="BucketSentenceIter.reset"><a class="viewcode-back" href="../../../api/python/symbol/rnn.html#mxnet.rnn.BucketSentenceIter.reset">[docs]</a> <span class="k">def</span> <span class="nf">reset</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Resets the iterator to the beginning of the data."""</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">curr_idx</span> <span class="o">=</span> <span class="mi">0</span> |
| <span class="n">random</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="p">)</span> |
| <span class="k">for</span> <span class="n">buck</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">:</span> |
| <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">shuffle</span><span class="p">(</span><span class="n">buck</span><span class="p">)</span> |
| |
| <span class="bp">self</span><span class="o">.</span><span class="n">nddata</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">ndlabel</span> <span class="o">=</span> <span class="p">[]</span> |
| <span class="k">for</span> <span class="n">buck</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">:</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty_like</span><span class="p">(</span><span class="n">buck</span><span class="p">)</span> |
| <span class="n">label</span><span class="p">[:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">buck</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">:]</span> |
| <span class="n">label</span><span class="p">[:,</span> <span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">invalid_label</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">nddata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ndarray</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">buck</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">ndlabel</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ndarray</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">label</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">dtype</span><span class="p">))</span></div> |
| |
| <div class="viewcode-block" id="BucketSentenceIter.next"><a class="viewcode-back" href="../../../api/python/symbol/rnn.html#mxnet.rnn.BucketSentenceIter.next">[docs]</a> <span class="k">def</span> <span class="nf">next</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> |
| <span class="sd">"""Returns the next batch of data."""</span> |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">curr_idx</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="p">):</span> |
| <span class="k">raise</span> <span class="ne">StopIteration</span> |
| <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">idx</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">curr_idx</span><span class="p">]</span> |
| <span class="bp">self</span><span class="o">.</span><span class="n">curr_idx</span> <span class="o">+=</span> <span class="mi">1</span> |
| |
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">major_axis</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">nddata</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">:</span><span class="n">j</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span><span class="p">]</span><span class="o">.</span><span class="n">T</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">ndlabel</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">:</span><span class="n">j</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span><span class="p">]</span><span class="o">.</span><span class="n">T</span> |
| <span class="k">else</span><span class="p">:</span> |
| <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">nddata</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">:</span><span class="n">j</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span><span class="p">]</span> |
| <span class="n">label</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">ndlabel</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">:</span><span class="n">j</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span><span class="p">]</span> |
| |
| <span class="k">return</span> <span class="n">DataBatch</span><span class="p">([</span><span class="n">data</span><span class="p">],</span> <span class="p">[</span><span class="n">label</span><span class="p">],</span> <span class="n">pad</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> |
| <span class="n">bucket_key</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">buckets</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> |
| <span class="n">provide_data</span><span class="o">=</span><span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">data_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)],</span> |
| <span class="n">provide_label</span><span class="o">=</span><span class="p">[</span><span class="n">DataDesc</span><span class="p">(</span> |
| <span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">label_name</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">label</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> |
| <span class="n">layout</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">layout</span><span class="p">)])</span></div></div> |
| </pre></div> |
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