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384 lines
52 KiB
384 lines
52 KiB
1 year ago
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<title>Coverage for LSTMPredictStock\core\model.py: 65%</title>
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<h1>Coverage for <b>LSTMPredictStock\core\model.py</b> :
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<span class="pc_cov">65%</span>
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86 statements
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<span class="run hide_run shortkey_r button_toggle_run">56 run</span>
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<span class="mis shortkey_m button_toggle_mis">30 missing</span>
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<span class="exc shortkey_x button_toggle_exc">0 excluded</span>
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<p id="t1" class="stm run hide_run"><span class="key">import</span> <span class="nam">os</span><span class="strut"> </span></p>
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<p id="t2" class="stm run hide_run"><span class="key">import</span> <span class="nam">math</span><span class="strut"> </span></p>
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<p id="t3" class="stm run hide_run"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span><span class="strut"> </span></p>
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<p id="t4" class="stm run hide_run"><span class="key">import</span> <span class="nam">datetime</span> <span class="key">as</span> <span class="nam">dt</span><span class="strut"> </span></p>
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<p id="t5" class="stm run hide_run"><span class="key">from</span> <span class="nam">numpy</span> <span class="key">import</span> <span class="nam">newaxis</span><span class="strut"> </span></p>
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<p id="t6" class="stm run hide_run"><span class="key">from</span> <span class="nam">LSTMPredictStock</span><span class="op">.</span><span class="nam">core</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">Timer</span><span class="strut"> </span></p>
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<p id="t7" class="stm run hide_run"><span class="key">from</span> <span class="nam">keras</span><span class="op">.</span><span class="nam">layers</span> <span class="key">import</span> <span class="nam">Dense</span><span class="op">,</span> <span class="nam">Activation</span><span class="op">,</span> <span class="nam">Dropout</span><span class="op">,</span> <span class="nam">LSTM</span><span class="strut"> </span></p>
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<p id="t8" class="stm run hide_run"><span class="key">from</span> <span class="nam">keras</span><span class="op">.</span><span class="nam">models</span> <span class="key">import</span> <span class="nam">Sequential</span><span class="op">,</span> <span class="nam">load_model</span><span class="strut"> </span></p>
|
||
|
|
<p id="t9" class="stm run hide_run"><span class="key">from</span> <span class="nam">keras</span><span class="op">.</span><span class="nam">callbacks</span> <span class="key">import</span> <span class="nam">EarlyStopping</span><span class="op">,</span> <span class="nam">ModelCheckpoint</span><span class="strut"> </span></p>
|
||
|
|
<p id="t10" class="pln"><span class="strut"> </span></p>
|
||
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<p id="t11" class="stm run hide_run"><span class="key">class</span> <span class="nam">Model</span><span class="op">(</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t12" class="pln"> <span class="str">"""A class for an building and inferencing an lstm model"""</span><span class="strut"> </span></p>
|
||
|
|
<p id="t13" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t14" class="stm run hide_run"> <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t15" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">Sequential</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t16" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t17" class="stm run hide_run"> <span class="key">def</span> <span class="nam">load_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">filepath</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t18" class="pln"> <span class="str">'''</span><span class="strut"> </span></p>
|
||
|
|
<p id="t19" class="pln"><span class="str"> 从本地保存的模型参数来加载模型</span><span class="strut"> </span></p>
|
||
|
|
<p id="t20" class="pln"><span class="str"> filepath: .h5 格式文件</span><span class="strut"> </span></p>
|
||
|
|
<p id="t21" class="pln"><span class="str"> '''</span><span class="strut"> </span></p>
|
||
|
|
<p id="t22" class="stm run hide_run"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Loading model from file %s'</span> <span class="op">%</span> <span class="nam">filepath</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t23" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">load_model</span><span class="op">(</span><span class="nam">filepath</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t24" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t25" class="stm run hide_run"> <span class="key">def</span> <span class="nam">build_model</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">configs</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t26" class="pln"> <span class="str">"""</span><span class="strut"> </span></p>
|
||
|
|
<p id="t27" class="pln"><span class="str"> 新建一个模型</span><span class="strut"> </span></p>
|
||
|
|
<p id="t28" class="pln"><span class="str"> configs:配置文件</span><span class="strut"> </span></p>
|
||
|
|
<p id="t29" class="pln"><span class="str"> """</span><span class="strut"> </span></p>
|
||
|
|
<p id="t30" class="stm run hide_run"> <span class="nam">timer</span> <span class="op">=</span> <span class="nam">Timer</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t31" class="stm run hide_run"> <span class="nam">timer</span><span class="op">.</span><span class="nam">start</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t32" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t33" class="stm run hide_run"> <span class="key">for</span> <span class="nam">layer</span> <span class="key">in</span> <span class="nam">configs</span><span class="op">[</span><span class="str">'model'</span><span class="op">]</span><span class="op">[</span><span class="str">'layers'</span><span class="op">]</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t34" class="stm run hide_run"> <span class="nam">neurons</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'neurons'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'neurons'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t35" class="stm run hide_run"> <span class="nam">dropout_rate</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'rate'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'rate'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t36" class="stm run hide_run"> <span class="nam">activation</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'activation'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'activation'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t37" class="stm run hide_run"> <span class="nam">return_seq</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'return_seq'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'return_seq'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t38" class="stm run hide_run"> <span class="nam">input_timesteps</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'input_timesteps'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'input_timesteps'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t39" class="stm run hide_run"> <span class="nam">input_dim</span> <span class="op">=</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'input_dim'</span><span class="op">]</span> <span class="key">if</span> <span class="str">'input_dim'</span> <span class="key">in</span> <span class="nam">layer</span> <span class="key">else</span> <span class="key">None</span><span class="strut"> </span></p>
|
||
|
|
<p id="t40" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t41" class="stm run hide_run"> <span class="key">if</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'type'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'dense'</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t42" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span><span class="nam">Dense</span><span class="op">(</span><span class="nam">neurons</span><span class="op">,</span> <span class="nam">activation</span><span class="op">=</span><span class="nam">activation</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t43" class="stm run hide_run"> <span class="key">if</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'type'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'lstm'</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t44" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span><span class="nam">LSTM</span><span class="op">(</span><span class="nam">neurons</span><span class="op">,</span> <span class="nam">input_shape</span><span class="op">=</span><span class="op">(</span><span class="nam">input_timesteps</span><span class="op">,</span> <span class="nam">input_dim</span><span class="op">)</span><span class="op">,</span> <span class="nam">return_sequences</span><span class="op">=</span><span class="nam">return_seq</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t45" class="stm run hide_run"> <span class="key">if</span> <span class="nam">layer</span><span class="op">[</span><span class="str">'type'</span><span class="op">]</span> <span class="op">==</span> <span class="str">'dropout'</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t46" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span><span class="nam">Dropout</span><span class="op">(</span><span class="nam">dropout_rate</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t47" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t48" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">compile</span><span class="op">(</span><span class="nam">loss</span><span class="op">=</span><span class="nam">configs</span><span class="op">[</span><span class="str">'model'</span><span class="op">]</span><span class="op">[</span><span class="str">'loss'</span><span class="op">]</span><span class="op">,</span> <span class="nam">optimizer</span><span class="op">=</span><span class="nam">configs</span><span class="op">[</span><span class="str">'model'</span><span class="op">]</span><span class="op">[</span><span class="str">'optimizer'</span><span class="op">]</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t49" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t50" class="stm run hide_run"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Model Compiled'</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t51" class="stm run hide_run"> <span class="nam">timer</span><span class="op">.</span><span class="nam">stop</span><span class="op">(</span><span class="op">)</span> <span class="com">#输出构建一个模型耗时</span><span class="strut"> </span></p>
|
||
|
|
<p id="t52" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t53" class="stm run hide_run"> <span class="key">def</span> <span class="nam">train</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">epochs</span><span class="op">,</span> <span class="nam">batch_size</span><span class="op">,</span> <span class="nam">save_dir</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t54" class="stm mis"> <span class="nam">timer</span> <span class="op">=</span> <span class="nam">Timer</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t55" class="stm mis"> <span class="nam">timer</span><span class="op">.</span><span class="nam">start</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t56" class="stm mis"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Training Started'</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t57" class="stm mis"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] %s epochs, %s batch size'</span> <span class="op">%</span> <span class="op">(</span><span class="nam">epochs</span><span class="op">,</span> <span class="nam">batch_size</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t58" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t59" class="stm mis"> <span class="nam">save_fname</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">save_dir</span><span class="op">,</span> <span class="str">'%s-e%s.h5'</span> <span class="op">%</span> <span class="op">(</span><span class="nam">dt</span><span class="op">.</span><span class="nam">datetime</span><span class="op">.</span><span class="nam">now</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">strftime</span><span class="op">(</span><span class="str">'%d%m%Y-%H%M%S'</span><span class="op">)</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">epochs</span><span class="op">)</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t60" class="stm mis"> <span class="nam">callbacks</span> <span class="op">=</span> <span class="op">[</span><span class="strut"> </span></p>
|
||
|
|
<p id="t61" class="pln"> <span class="nam">EarlyStopping</span><span class="op">(</span><span class="nam">monitor</span><span class="op">=</span><span class="str">'val_loss'</span><span class="op">,</span> <span class="nam">patience</span><span class="op">=</span><span class="num">2</span><span class="op">)</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t62" class="pln"> <span class="nam">ModelCheckpoint</span><span class="op">(</span><span class="nam">filepath</span><span class="op">=</span><span class="nam">save_fname</span><span class="op">,</span> <span class="nam">monitor</span><span class="op">=</span><span class="str">'val_loss'</span><span class="op">,</span> <span class="nam">save_best_only</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t63" class="pln"> <span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t64" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="strut"> </span></p>
|
||
|
|
<p id="t65" class="pln"> <span class="nam">x</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t66" class="pln"> <span class="nam">y</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t67" class="pln"> <span class="nam">epochs</span><span class="op">=</span><span class="nam">epochs</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t68" class="pln"> <span class="nam">batch_size</span><span class="op">=</span><span class="nam">batch_size</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t69" class="pln"> <span class="nam">callbacks</span><span class="op">=</span><span class="nam">callbacks</span><span class="strut"> </span></p>
|
||
|
|
<p id="t70" class="pln"> <span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t71" class="stm mis"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">save</span><span class="op">(</span><span class="nam">save_fname</span><span class="op">)</span> <span class="com">#保存训练好的模型</span><span class="strut"> </span></p>
|
||
|
|
<p id="t72" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t73" class="stm mis"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Training Completed. Model saved as %s'</span> <span class="op">%</span> <span class="nam">save_fname</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t74" class="stm mis"> <span class="nam">timer</span><span class="op">.</span><span class="nam">stop</span><span class="op">(</span><span class="op">)</span> <span class="com">#输出训练耗时</span><span class="strut"> </span></p>
|
||
|
|
<p id="t75" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t76" class="stm run hide_run"> <span class="key">def</span> <span class="nam">train_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data_gen</span><span class="op">,</span> <span class="nam">epochs</span><span class="op">,</span> <span class="nam">batch_size</span><span class="op">,</span> <span class="nam">steps_per_epoch</span><span class="op">,</span> <span class="nam">save_dir</span><span class="op">,</span><span class="nam">save_name</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t77" class="pln"> <span class="str">'''</span><span class="strut"> </span></p>
|
||
|
|
<p id="t78" class="pln"><span class="str"> 由data_gen数据产生器来，逐步产生训练数据，而不是一次性将数据读入到内存</span><span class="strut"> </span></p>
|
||
|
|
<p id="t79" class="pln"><span class="str"> '''</span><span class="strut"> </span></p>
|
||
|
|
<p id="t80" class="stm run hide_run"> <span class="nam">timer</span> <span class="op">=</span> <span class="nam">Timer</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t81" class="stm run hide_run"> <span class="nam">timer</span><span class="op">.</span><span class="nam">start</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t82" class="stm run hide_run"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Training Started'</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t83" class="stm run hide_run"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] %s epochs, %s batch size, %s batches per epoch'</span> <span class="op">%</span> <span class="op">(</span><span class="nam">epochs</span><span class="op">,</span> <span class="nam">batch_size</span><span class="op">,</span> <span class="nam">steps_per_epoch</span><span class="op">)</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t84" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t85" class="pln"> <span class="com"># save_fname = os.path.join(save_dir, '%s-e%s.h5' % (dt.datetime.now().strftime('%d%m%Y-%H%M%S'), str(epochs)))</span><span class="strut"> </span></p>
|
||
|
|
<p id="t86" class="stm run hide_run"> <span class="nam">save_fname</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">save_dir</span><span class="op">,</span> <span class="nam">save_name</span><span class="op">+</span><span class="str">'.h5'</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t87" class="stm run hide_run"> <span class="nam">callbacks</span> <span class="op">=</span> <span class="op">[</span><span class="strut"> </span></p>
|
||
|
|
<p id="t88" class="pln"> <span class="nam">ModelCheckpoint</span><span class="op">(</span><span class="nam">filepath</span><span class="op">=</span><span class="nam">save_fname</span><span class="op">,</span> <span class="nam">monitor</span><span class="op">=</span><span class="str">'loss'</span><span class="op">,</span> <span class="nam">save_best_only</span><span class="op">=</span><span class="key">True</span><span class="op">)</span><span class="strut"> </span></p>
|
||
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<p id="t89" class="pln"> <span class="op">]</span><span class="strut"> </span></p>
|
||
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|
<p id="t90" class="stm run hide_run"> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">fit_generator</span><span class="op">(</span><span class="strut"> </span></p>
|
||
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|
<p id="t91" class="pln"> <span class="nam">data_gen</span><span class="op">,</span><span class="strut"> </span></p>
|
||
|
|
<p id="t92" class="pln"> <span class="nam">steps_per_epoch</span><span class="op">=</span><span class="nam">steps_per_epoch</span><span class="op">,</span><span class="strut"> </span></p>
|
||
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<p id="t93" class="pln"> <span class="nam">epochs</span><span class="op">=</span><span class="nam">epochs</span><span class="op">,</span><span class="strut"> </span></p>
|
||
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|
<p id="t94" class="pln"> <span class="nam">callbacks</span><span class="op">=</span><span class="nam">callbacks</span><span class="op">,</span><span class="strut"> </span></p>
|
||
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<p id="t95" class="pln"> <span class="nam">workers</span><span class="op">=</span><span class="num">1</span><span class="strut"> </span></p>
|
||
|
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<p id="t96" class="pln"> <span class="op">)</span><span class="strut"> </span></p>
|
||
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<p id="t97" class="pln"><span class="strut"> </span></p>
|
||
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<p id="t98" class="stm run hide_run"> <span class="nam">print</span><span class="op">(</span><span class="str">'[Model] Training Completed. Model saved as %s'</span> <span class="op">%</span> <span class="nam">save_fname</span><span class="op">)</span><span class="strut"> </span></p>
|
||
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<p id="t99" class="stm run hide_run"> <span class="nam">timer</span><span class="op">.</span><span class="nam">stop</span><span class="op">(</span><span class="op">)</span><span class="strut"> </span></p>
|
||
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<p id="t100" class="pln"><span class="strut"> </span></p>
|
||
|
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<p id="t101" class="pln"> <span class="com">#　data必须是三维数据，即shape:(a,b,c)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t102" class="stm run hide_run"> <span class="key">def</span> <span class="nam">predict_point_by_point</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
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<p id="t103" class="pln"> <span class="com">#Predict each timestep given the last sequence of true data, in effect only predicting 1 step ahead each time</span><span class="strut"> </span></p>
|
||
|
|
<p id="t104" class="stm mis"> <span class="nam">predicted</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">data</span><span class="op">)</span> <span class="com"># data有多少行就输出多少个预测值,返回的预测值是一个2维数组:(a,1) a:为data的行数</span><span class="strut"> </span></p>
|
||
|
|
<p id="t105" class="stm mis"> <span class="nam">predicted</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">reshape</span><span class="op">(</span><span class="nam">predicted</span><span class="op">,</span> <span class="op">(</span><span class="nam">predicted</span><span class="op">.</span><span class="nam">size</span><span class="op">,</span><span class="op">)</span><span class="op">)</span> <span class="com"># 这里将二维数组，变成一维数组</span><span class="strut"> </span></p>
|
||
|
|
<p id="t106" class="stm mis"> <span class="key">return</span> <span class="nam">predicted</span> <span class="com"># 返回一维数组，元素个数与data的a相同</span><span class="strut"> </span></p>
|
||
|
|
<p id="t107" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t108" class="pln"> <span class="com"># 对data进行多段预测，每段预测基于一个窗口大小（window_size）的数据，然后输出prediction_len长的预测值（一维数组）</span><span class="strut"> </span></p>
|
||
|
|
<p id="t109" class="pln"> <span class="com"># 再从上一个窗口移动prediction_len的长度，得到下一个窗口的数据，并基于该数据再预测prediction_len长的预测值</span><span class="strut"> </span></p>
|
||
|
|
<p id="t110" class="pln"> <span class="com"># 所以prediction_len决定了窗口的移位步数，每次的窗口大小是一样的，所以最后预测的段数 = 窗口个数/预测长度</span><span class="strut"> </span></p>
|
||
|
|
<p id="t111" class="pln"> <span class="com"># 相当于多次调用predict_1_win_sequence方法</span><span class="strut"> </span></p>
|
||
|
|
<p id="t112" class="stm run hide_run"> <span class="key">def</span> <span class="nam">predict_sequences_multiple</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data</span><span class="op">,</span> <span class="nam">window_size</span><span class="op">,</span> <span class="nam">prediction_len</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t113" class="pln"> <span class="com">#Predict sequence of 50 steps before shifting prediction run forward by 50 steps</span><span class="strut"> </span></p>
|
||
|
|
<p id="t114" class="stm mis"> <span class="nam">prediction_seqs</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t115" class="stm mis"> <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">data</span><span class="op">)</span><span class="op">/</span><span class="nam">prediction_len</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t116" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">data</span><span class="op">[</span><span class="nam">i</span><span class="op">*</span><span class="nam">prediction_len</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t117" class="stm mis"> <span class="nam">predicted</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t118" class="stm mis"> <span class="key">for</span> <span class="nam">j</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">prediction_len</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t119" class="stm mis"> <span class="nam">predicted</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">[</span><span class="nam">newaxis</span><span class="op">,</span><span class="op">:</span><span class="op">,</span><span class="op">:</span><span class="op">]</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">,</span><span class="num">0</span><span class="op">]</span><span class="op">)</span> <span class="com"># newaxis：增加新轴，使得curr_frame变成(1,x,x)三维数据</span><span class="strut"> </span></p>
|
||
|
|
<p id="t120" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">curr_frame</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t121" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">insert</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">,</span> <span class="op">[</span><span class="nam">window_size</span><span class="op">-</span><span class="num">2</span><span class="op">]</span><span class="op">,</span> <span class="nam">predicted</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t122" class="stm mis"> <span class="nam">prediction_seqs</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">predicted</span><span class="op">)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t123" class="stm mis"> <span class="key">return</span> <span class="nam">prediction_seqs</span><span class="strut"> </span></p>
|
||
|
|
<p id="t124" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t125" class="pln"> <span class="com"># 输入一个窗口的数据，指定预测的长度，data:依旧是三维数组(1,win_len,fea_len)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t126" class="pln"> <span class="com"># 返回预测数组</span><span class="strut"> </span></p>
|
||
|
|
<p id="t127" class="stm run hide_run"> <span class="key">def</span> <span class="nam">predict_sequence_full</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data</span><span class="op">,</span> <span class="nam">window_size</span><span class="op">)</span><span class="op">:</span> <span class="com"># window_size：为输入数据的长度</span><span class="strut"> </span></p>
|
||
|
|
<p id="t128" class="pln"> <span class="com">#Shift the window by 1 new prediction each time, re-run predictions on new window</span><span class="strut"> </span></p>
|
||
|
|
<p id="t129" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">data</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="com"># 基于data[0]一个窗口的数据，来预测len(data)个输出</span><span class="strut"> </span></p>
|
||
|
|
<p id="t130" class="stm mis"> <span class="nam">predicted</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t131" class="stm mis"> <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">data</span><span class="op">)</span><span class="op">)</span><span class="op">:</span><span class="strut"> </span></p>
|
||
|
|
<p id="t132" class="stm mis"> <span class="nam">predicted</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">[</span><span class="nam">newaxis</span><span class="op">,</span><span class="op">:</span><span class="op">,</span><span class="op">:</span><span class="op">]</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">,</span><span class="num">0</span><span class="op">]</span><span class="op">)</span> <span class="com"># append了一个预测值（标量）</span><span class="strut"> </span></p>
|
||
|
|
<p id="t133" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">curr_frame</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t134" class="stm mis"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">insert</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">,</span> <span class="op">[</span><span class="nam">window_size</span><span class="op">-</span><span class="num">2</span><span class="op">]</span><span class="op">,</span> <span class="nam">predicted</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">)</span> <span class="com"># 插入位置[window_size-2]:curr_frame的末尾，predicted[-1]：插入值</span><span class="strut"> </span></p>
|
||
|
|
<p id="t135" class="stm mis"> <span class="key">return</span> <span class="nam">predicted</span><span class="strut"> </span></p>
|
||
|
|
<p id="t136" class="pln"><span class="strut"> </span></p>
|
||
|
|
<p id="t137" class="pln"> <span class="com"># 输入一个窗口的数据，指定预测的长度，data:依旧是三维数组(1,win_len,fea_len)</span><span class="strut"> </span></p>
|
||
|
|
<p id="t138" class="pln"> <span class="com"># 返回预测数组</span><span class="strut"> </span></p>
|
||
|
|
<p id="t139" class="stm run hide_run"> <span class="key">def</span> <span class="nam">predict_1_win_sequence</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data</span><span class="op">,</span> <span class="nam">window_size</span><span class="op">,</span><span class="nam">predict_length</span><span class="op">)</span><span class="op">:</span> <span class="com"># window_size：data的窗口大小</span><span class="strut"> </span></p>
|
||
|
|
<p id="t140" class="pln"> <span class="com">#Shift the window by 1 new prediction each time, re-run predictions on new window</span><span class="strut"> </span></p>
|
||
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|
<p id="t141" class="stm run hide_run"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">data</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
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<p id="t142" class="stm run hide_run"> <span class="nam">predicted</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span><span class="strut"> </span></p>
|
||
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<p id="t143" class="stm run hide_run"> <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predict_length</span><span class="op">)</span><span class="op">:</span> <span class="com"># range(len(data))</span><span class="strut"> </span></p>
|
||
|
|
<p id="t144" class="stm run hide_run"> <span class="nam">predicted</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">[</span><span class="nam">newaxis</span><span class="op">,</span><span class="op">:</span><span class="op">,</span><span class="op">:</span><span class="op">]</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">,</span><span class="num">0</span><span class="op">]</span><span class="op">)</span> <span class="com"># append了一个预测值（标量）</span><span class="strut"> </span></p>
|
||
|
|
<p id="t145" class="stm run hide_run"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">curr_frame</span><span class="op">[</span><span class="num">1</span><span class="op">:</span><span class="op">]</span><span class="strut"> </span></p>
|
||
|
|
<p id="t146" class="stm run hide_run"> <span class="nam">curr_frame</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">insert</span><span class="op">(</span><span class="nam">curr_frame</span><span class="op">,</span> <span class="op">[</span><span class="nam">window_size</span><span class="op">-</span><span class="num">2</span><span class="op">]</span><span class="op">,</span> <span class="nam">predicted</span><span class="op">[</span><span class="op">-</span><span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">0</span><span class="op">)</span> <span class="com"># 插入位置[window_size-2]:curr_frame的末尾，predicted[-1]：插入值</span><span class="strut"> </span></p>
|
||
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<p id="t147" class="stm run hide_run"> <span class="key">return</span> <span class="nam">predicted</span><span class="strut"> </span></p>
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</td>
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</tr>
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</table>
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</div>
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<div id="footer">
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<div class="content">
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<p>
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<a class="nav" href="index.html">« index</a> <a class="nav" href="https://coverage.readthedocs.io">coverage.py v4.5.2</a>,
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created at 2018-12-22 16:41
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</p>
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