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Deci-AI
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super-gradients
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#396 Trainer constructor cleanup

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Ghost merged 1 commits into Deci-AI:master from deci-ai:feature/SG-266_clean_trainer_ctor
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    87. 

  87.              
    88. 

  88.   <h1>Source code for super_gradients.training.utils.utils</h1><div class="highlight"><pre>
    89. 

  89. <span></span><span class="kn">import</span> <span class="nn">math</span>
    90. 

  90. <span class="kn">import</span> <span class="nn">time</span>
    91. 

  91. <span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">lru_cache</span>
    92. 

  92. <span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
    93. 

  93. <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Mapping</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Union</span><span class="p">,</span> <span class="n">List</span>
    94. 

  94. <span class="kn">from</span> <span class="nn">zipfile</span> <span class="kn">import</span> <span class="n">ZipFile</span>
    95. 

  95. <span class="kn">import</span> <span class="nn">os</span>
    96. 

  96. <span class="kn">from</span> <span class="nn">jsonschema</span> <span class="kn">import</span> <span class="n">validate</span>
    97. 

  97. <span class="kn">import</span> <span class="nn">tarfile</span>
    98. 

  98. <span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span><span class="p">,</span> <span class="n">ExifTags</span>
    99. 

  99. 

  100. <span class="kn">import</span> <span class="nn">torch</span>
    101. 

  101. <span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
    102. 

  102. 

  103. 

  104. <span class="c1"># These functions changed from torch 1.2 to torch 1.3</span>
    105. 

  105. 

  106. <span class="kn">import</span> <span class="nn">random</span>
    107. 

  107. <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
    108. 

  108. <span class="kn">from</span> <span class="nn">importlib</span> <span class="kn">import</span> <span class="n">import_module</span>
    109. 

  109. 

  110. <span class="kn">from</span> <span class="nn">super_gradients.common.abstractions.abstract_logger</span> <span class="kn">import</span> <span class="n">get_logger</span>
    111. 

  111. 

  112. <span class="n">logger</span> <span class="o">=</span> <span class="n">get_logger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
    113. 

  113. 

  114. 

  115. <div class="viewcode-block" id="convert_to_tensor"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.convert_to_tensor">[docs]</a><span class="k">def</span> <span class="nf">convert_to_tensor</span><span class="p">(</span><span class="n">array</span><span class="p">):</span>
    116. 

  116.     <span class="sd">&quot;&quot;&quot;Converts numpy arrays and lists to Torch tensors before calculation losses</span>
    117. 

  117. <span class="sd">    :param array: torch.tensor / Numpy array / List</span>
    118. 

  118. <span class="sd">    &quot;&quot;&quot;</span>
    119. 

  119.     <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">FloatTensor</span><span class="p">(</span><span class="n">array</span><span class="p">)</span> <span class="k">if</span> <span class="nb">type</span><span class="p">(</span><span class="n">array</span><span class="p">)</span> <span class="o">!=</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span> <span class="k">else</span> <span class="n">array</span></div>
    120. 

  120. 

  121. 

  122. <div class="viewcode-block" id="HpmStruct"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.HpmStruct">[docs]</a><span class="k">class</span> <span class="nc">HpmStruct</span><span class="p">:</span>
    123. 

  123.     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">entries</span><span class="p">):</span>
    124. 

  124.         <span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">entries</span><span class="p">)</span>
    125. 

  125.         <span class="bp">self</span><span class="o">.</span><span class="n">schema</span> <span class="o">=</span> <span class="kc">None</span>
    126. 

  126. 

  127. <div class="viewcode-block" id="HpmStruct.set_schema"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.HpmStruct.set_schema">[docs]</a>    <span class="k">def</span> <span class="nf">set_schema</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">schema</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
    128. 

  128.         <span class="bp">self</span><span class="o">.</span><span class="n">schema</span> <span class="o">=</span> <span class="n">schema</span></div>
    129. 

  129. 

  130. <div class="viewcode-block" id="HpmStruct.override"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.HpmStruct.override">[docs]</a>    <span class="k">def</span> <span class="nf">override</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">entries</span><span class="p">):</span>
    131. 

  131.         <span class="n">recursive_override</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">,</span> <span class="n">entries</span><span class="p">)</span></div>
    132. 

  132. 

  133. <div class="viewcode-block" id="HpmStruct.to_dict"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.HpmStruct.to_dict">[docs]</a>    <span class="k">def</span> <span class="nf">to_dict</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    134. 

  134.         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span></div>
    135. 

  135. 

  136. <div class="viewcode-block" id="HpmStruct.validate"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.HpmStruct.validate">[docs]</a>    <span class="k">def</span> <span class="nf">validate</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    137. 

  137.         <span class="sd">&quot;&quot;&quot;</span>
    138. 

  138. <span class="sd">        Validate the current dict values according to the provided schema</span>
    139. 

  139. <span class="sd">        :raises</span>
    140. 

  140. <span class="sd">            `AttributeError` if schema was not set</span>
    141. 

  141. <span class="sd">            `jsonschema.exceptions.ValidationError` if the instance is invalid</span>
    142. 

  142. <span class="sd">            `jsonschema.exceptions.SchemaError` if the schema itselfis invalid</span>
    143. 

  143. <span class="sd">        &quot;&quot;&quot;</span>
    144. 

  144.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">schema</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
    145. 

  145.             <span class="k">raise</span> <span class="ne">AttributeError</span><span class="p">(</span><span class="s1">&#39;schema was not set&#39;</span><span class="p">)</span>
    146. 

  146.         <span class="k">else</span><span class="p">:</span>
    147. 

  147.             <span class="n">validate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">schema</span><span class="p">)</span></div></div>
    148. 

  148. 

  149. 

  150. <div class="viewcode-block" id="WrappedModel"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.WrappedModel">[docs]</a><span class="k">class</span> <span class="nc">WrappedModel</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    151. 

  151.     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">module</span><span class="p">):</span>
    152. 

  152.         <span class="nb">super</span><span class="p">(</span><span class="n">WrappedModel</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>
    153. 

  153.         <span class="bp">self</span><span class="o">.</span><span class="n">module</span> <span class="o">=</span> <span class="n">module</span>  <span class="c1"># that I actually define.</span>
    154. 

  154. 

  155. <div class="viewcode-block" id="WrappedModel.forward"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.WrappedModel.forward">[docs]</a>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
    156. 

  156.         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">module</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></div></div>
    157. 

  157. 

  158. 

  159. <div class="viewcode-block" id="Timer"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.Timer">[docs]</a><span class="k">class</span> <span class="nc">Timer</span><span class="p">:</span>
    160. 

  160.     <span class="sd">&quot;&quot;&quot;A class to measure time handling both GPU &amp; CPU processes</span>
    161. 

  161. <span class="sd">    Returns time in milliseconds&quot;&quot;&quot;</span>
    162. 

  162. 

  163.     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">device</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
    164. 

  164.         <span class="sd">&quot;&quot;&quot;</span>
    165. 

  165. <span class="sd">        :param device: str</span>
    166. 

  166. <span class="sd">            &#39;cpu&#39;\&#39;cuda&#39;</span>
    167. 

  167. <span class="sd">        &quot;&quot;&quot;</span>
    168. 

  168.         <span class="bp">self</span><span class="o">.</span><span class="n">on_gpu</span> <span class="o">=</span> <span class="p">(</span><span class="n">device</span> <span class="o">==</span> <span class="s1">&#39;cuda&#39;</span><span class="p">)</span>
    169. 

  169.         <span class="c1"># On GPU time is measured using cuda.events</span>
    170. 

  170.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">on_gpu</span><span class="p">:</span>
    171. 

  171.             <span class="bp">self</span><span class="o">.</span><span class="n">starter</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Event</span><span class="p">(</span><span class="n">enable_timing</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    172. 

  172.             <span class="bp">self</span><span class="o">.</span><span class="n">ender</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">Event</span><span class="p">(</span><span class="n">enable_timing</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    173. 

  173.         <span class="c1"># On CPU time is measured using time</span>
    174. 

  174.         <span class="k">else</span><span class="p">:</span>
    175. 

  175.             <span class="bp">self</span><span class="o">.</span><span class="n">starter</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">ender</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span>
    176. 

  176. 

  177. <div class="viewcode-block" id="Timer.start"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.Timer.start">[docs]</a>    <span class="k">def</span> <span class="nf">start</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    178. 

  178.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">on_gpu</span><span class="p">:</span>
    179. 

  179.             <span class="bp">self</span><span class="o">.</span><span class="n">starter</span><span class="o">.</span><span class="n">record</span><span class="p">()</span>
    180. 

  180.         <span class="k">else</span><span class="p">:</span>
    181. 

  181.             <span class="bp">self</span><span class="o">.</span><span class="n">starter</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span></div>
    182. 

  182. 

  183. <div class="viewcode-block" id="Timer.stop"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.Timer.stop">[docs]</a>    <span class="k">def</span> <span class="nf">stop</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    184. 

  184.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">on_gpu</span><span class="p">:</span>
    185. 

  185.             <span class="bp">self</span><span class="o">.</span><span class="n">ender</span><span class="o">.</span><span class="n">record</span><span class="p">()</span>
    186. 

  186.             <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">synchronize</span><span class="p">()</span>
    187. 

  187.             <span class="n">timer</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">starter</span><span class="o">.</span><span class="n">elapsed_time</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ender</span><span class="p">)</span>
    188. 

  188.         <span class="k">else</span><span class="p">:</span>
    189. 

  189.             <span class="c1"># Time measures in seconds -&gt; convert to milliseconds</span>
    190. 

  190.             <span class="n">timer</span> <span class="o">=</span> <span class="p">(</span><span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">starter</span><span class="p">)</span> <span class="o">*</span> <span class="mi">1000</span>
    191. 

  191. 

  192.         <span class="c1"># Return time in milliseconds</span>
    193. 

  193.         <span class="k">return</span> <span class="n">timer</span></div></div>
    194. 

  194. 

  195. 

  196. <div class="viewcode-block" id="AverageMeter"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.AverageMeter">[docs]</a><span class="k">class</span> <span class="nc">AverageMeter</span><span class="p">:</span>
    197. 

  197.     <span class="sd">&quot;&quot;&quot;A class to calculate the average of a metric, for each batch</span>
    198. 

  198. <span class="sd">    during training/testing&quot;&quot;&quot;</span>
    199. 

  199. 

  200.     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    201. 

  201.         <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="o">=</span> <span class="kc">None</span>
    202. 

  202.         <span class="bp">self</span><span class="o">.</span><span class="n">_count</span> <span class="o">=</span> <span class="mi">0</span>
    203. 

  203. 

  204. <div class="viewcode-block" id="AverageMeter.update"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.AverageMeter.update">[docs]</a>    <span class="k">def</span> <span class="nf">update</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">,</span> <span class="nb">list</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">],</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span>
    205. 

  205. 

  206.         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">value</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span>
    207. 

  207.             <span class="n">value</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
    208. 

  208. 

  209.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
    210. 

  210.             <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="o">=</span> <span class="n">value</span> <span class="o">*</span> <span class="n">batch_size</span>
    211. 

  211.         <span class="k">else</span><span class="p">:</span>
    212. 

  212.             <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="o">+=</span> <span class="n">value</span> <span class="o">*</span> <span class="n">batch_size</span>
    213. 

  213. 

  214.         <span class="bp">self</span><span class="o">.</span><span class="n">_count</span> <span class="o">+=</span> <span class="n">batch_size</span></div>
    215. 

  215. 

  216.     <span class="nd">@property</span>
    217. 

  217.     <span class="k">def</span> <span class="nf">average</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
    218. 

  218.         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
    219. 

  219.             <span class="k">return</span> <span class="mi">0</span>
    220. 

  220.         <span class="k">return</span> <span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_count</span><span class="p">)</span><span class="o">.</span><span class="fm">__float__</span><span class="p">())</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_sum</span><span class="o">.</span><span class="n">dim</span><span class="p">()</span> <span class="o">&lt;</span> <span class="mi">1</span> <span class="k">else</span> <span class="nb">tuple</span><span class="p">(</span>
    221. 

  221.             <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_sum</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_count</span><span class="p">)</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">())</span></div>
    222. 

  222. 

  223.         <span class="c1"># return (self._sum / self._count).__float__() if self._sum.dim() &lt; 1 or len(self._sum) == 1 \</span>
    224. 

  224.         <span class="c1">#     else tuple((self._sum / self._count).cpu().numpy())</span>
    225. 

  225. 

  226. 

  227. <div class="viewcode-block" id="tensor_container_to_device"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.tensor_container_to_device">[docs]</a><span class="k">def</span> <span class="nf">tensor_container_to_device</span><span class="p">(</span><span class="n">obj</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">,</span> <span class="nb">list</span><span class="p">,</span> <span class="nb">dict</span><span class="p">],</span> <span class="n">device</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    228. 

  228.     <span class="sd">&quot;&quot;&quot;</span>
    229. 

  229. <span class="sd">    recursively send compounded objects to device (sending all tensors to device and maintaining structure)</span>
    230. 

  230. <span class="sd">        :param obj           the object to send to device (list / tuple / tensor / dict)</span>
    231. 

  231. <span class="sd">        :param device:       device to send the tensors to</span>
    232. 

  232. <span class="sd">        :param non_blocking: used for DistributedDataParallel</span>
    233. 

  233. <span class="sd">        :returns        an object with the same structure (tensors, lists, tuples) with the device pointers (like</span>
    234. 

  234. <span class="sd">                        the return value of Tensor.to(device)</span>
    235. 

  235. <span class="sd">    &quot;&quot;&quot;</span>
    236. 

  236.     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span>
    237. 

  237.         <span class="k">return</span> <span class="n">obj</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="n">non_blocking</span><span class="p">)</span>
    238. 

  238.     <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
    239. 

  239.         <span class="k">return</span> <span class="nb">tuple</span><span class="p">(</span><span class="n">tensor_container_to_device</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="n">non_blocking</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">obj</span><span class="p">)</span>
    240. 

  240.     <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
    241. 

  241.         <span class="k">return</span> <span class="p">[</span><span class="n">tensor_container_to_device</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="n">non_blocking</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">obj</span><span class="p">]</span>
    242. 

  242.     <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
    243. 

  243.         <span class="k">return</span> <span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">tensor_container_to_device</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">non_blocking</span><span class="o">=</span><span class="n">non_blocking</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">obj</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
    244. 

  244.     <span class="k">else</span><span class="p">:</span>
    245. 

  245.         <span class="k">return</span> <span class="n">obj</span></div>
    246. 

  246. 

  247. 

  248. <div class="viewcode-block" id="get_param"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.get_param">[docs]</a><span class="k">def</span> <span class="nf">get_param</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">default_val</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    249. 

  249.     <span class="sd">&quot;&quot;&quot;</span>
    250. 

  250. <span class="sd">    Retrieves a param from a parameter object/dict. If the parameter does not exist, will return default_val.</span>
    251. 

  251. <span class="sd">    In case the default_val is of type dictionary, and a value is found in the params - the function</span>
    252. 

  252. <span class="sd">    will return the default value dictionary with internal values overridden by the found value</span>
    253. 

  253. 

  254. <span class="sd">    i.e.</span>
    255. 

  255. <span class="sd">    default_opt_params = {&#39;lr&#39;:0.1, &#39;momentum&#39;:0.99, &#39;alpha&#39;:0.001}</span>
    256. 

  256. <span class="sd">    training_params = {&#39;optimizer_params&#39;: {&#39;lr&#39;:0.0001}, &#39;batch&#39;: 32 .... }</span>
    257. 

  257. <span class="sd">    get_param(training_params, name=&#39;optimizer_params&#39;, default_val=default_opt_params)</span>
    258. 

  258. <span class="sd">    will return {&#39;lr&#39;:0.0001, &#39;momentum&#39;:0.99, &#39;alpha&#39;:0.001}</span>
    259. 

  259. 

  260. <span class="sd">    :param params:      an object (typically HpmStruct) or a dict holding the params</span>
    261. 

  261. <span class="sd">    :param name:        name of the searched parameter</span>
    262. 

  262. <span class="sd">    :param default_val: assumed to be the same type as the value searched in the params</span>
    263. 

  263. <span class="sd">    :return:            the found value, or default if not found</span>
    264. 

  264. <span class="sd">    &quot;&quot;&quot;</span>
    265. 

  265.     <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
    266. 

  266.         <span class="k">if</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">params</span><span class="p">:</span>
    267. 

  267.             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">default_val</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
    268. 

  268.                 <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">default_val</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">[</span><span class="n">name</span><span class="p">]}</span>
    269. 

  269.             <span class="k">else</span><span class="p">:</span>
    270. 

  270.                 <span class="k">return</span> <span class="n">params</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
    271. 

  271.         <span class="k">else</span><span class="p">:</span>
    272. 

  272.             <span class="k">return</span> <span class="n">default_val</span>
    273. 

  273.     <span class="k">elif</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">name</span><span class="p">):</span>
    274. 

  274.         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">default_val</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
    275. 

  275.             <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">default_val</span><span class="p">,</span> <span class="o">**</span><span class="nb">getattr</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">name</span><span class="p">)}</span>
    276. 

  276.         <span class="k">else</span><span class="p">:</span>
    277. 

  277.             <span class="k">return</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">params</span><span class="p">,</span> <span class="n">name</span><span class="p">)</span>
    278. 

  278.     <span class="k">else</span><span class="p">:</span>
    279. 

  279.         <span class="k">return</span> <span class="n">default_val</span></div>
    280. 

  280. 

  281. 

  282. <div class="viewcode-block" id="static_vars"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.static_vars">[docs]</a><span class="k">def</span> <span class="nf">static_vars</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
    283. 

  283.     <span class="k">def</span> <span class="nf">decorate</span><span class="p">(</span><span class="n">func</span><span class="p">):</span>
    284. 

  284.         <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
    285. 

  285.             <span class="nb">setattr</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
    286. 

  286.         <span class="k">return</span> <span class="n">func</span>
    287. 

  287. 

  288.     <span class="k">return</span> <span class="n">decorate</span></div>
    289. 

  289. 

  290. 

  291. <div class="viewcode-block" id="print_once"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.print_once">[docs]</a><span class="nd">@static_vars</span><span class="p">(</span><span class="n">printed</span><span class="o">=</span><span class="nb">set</span><span class="p">())</span>
    292. 

  292. <span class="k">def</span> <span class="nf">print_once</span><span class="p">(</span><span class="n">s</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
    293. 

  293.     <span class="k">if</span> <span class="n">s</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">print_once</span><span class="o">.</span><span class="n">printed</span><span class="p">:</span>
    294. 

  294.         <span class="n">print_once</span><span class="o">.</span><span class="n">printed</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
    295. 

  295.         <span class="nb">print</span><span class="p">(</span><span class="n">s</span><span class="p">)</span></div>
    296. 

  296. 

  297. 

  298. <div class="viewcode-block" id="move_state_dict_to_device"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.move_state_dict_to_device">[docs]</a><span class="k">def</span> <span class="nf">move_state_dict_to_device</span><span class="p">(</span><span class="n">model_sd</span><span class="p">,</span> <span class="n">device</span><span class="p">):</span>
    299. 

  299.     <span class="sd">&quot;&quot;&quot;</span>
    300. 

  300. <span class="sd">    Moving model state dict tensors to target device (cuda or cpu)</span>
    301. 

  301. <span class="sd">    :param model_sd: model state dict</span>
    302. 

  302. <span class="sd">    :param device: either cuda or cpu</span>
    303. 

  303. <span class="sd">    &quot;&quot;&quot;</span>
    304. 

  304.     <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">model_sd</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    305. 

  305.         <span class="n">model_sd</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">v</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">device</span><span class="p">)</span>
    306. 

  306.     <span class="k">return</span> <span class="n">model_sd</span></div>
    307. 

  307. 

  308. 

  309. <div class="viewcode-block" id="random_seed"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.random_seed">[docs]</a><span class="k">def</span> <span class="nf">random_seed</span><span class="p">(</span><span class="n">is_ddp</span><span class="p">,</span> <span class="n">device</span><span class="p">,</span> <span class="n">seed</span><span class="p">):</span>
    310. 

  310.     <span class="sd">&quot;&quot;&quot;</span>
    311. 

  311. <span class="sd">    Sets random seed of numpy, torch and random.</span>
    312. 

  312. 

  313. <span class="sd">    When using ddp a seed will be set for each process according to its local rank derived from the device number.</span>
    314. 

  314. <span class="sd">    :param is_ddp: bool, will set different random seed for each process when using ddp.</span>
    315. 

  315. <span class="sd">    :param device: &#39;cuda&#39;,&#39;cpu&#39;, &#39;cuda:&lt;device_number&gt;&#39;</span>
    316. 

  316. <span class="sd">    :param seed: int, random seed to be set</span>
    317. 

  317. <span class="sd">    &quot;&quot;&quot;</span>
    318. 

  318.     <span class="n">rank</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">is_ddp</span> <span class="k">else</span> <span class="nb">int</span><span class="p">(</span><span class="n">device</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;:&#39;</span><span class="p">)[</span><span class="mi">1</span><span class="p">])</span>
    319. 

  319.     <span class="n">torch</span><span class="o">.</span><span class="n">manual_seed</span><span class="p">(</span><span class="n">seed</span> <span class="o">+</span> <span class="n">rank</span><span class="p">)</span>
    320. 

  320.     <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span> <span class="o">+</span> <span class="n">rank</span><span class="p">)</span>
    321. 

  321.     <span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="n">seed</span> <span class="o">+</span> <span class="n">rank</span><span class="p">)</span></div>
    322. 

  322. 

  323. 

  324. <div class="viewcode-block" id="load_func"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.load_func">[docs]</a><span class="k">def</span> <span class="nf">load_func</span><span class="p">(</span><span class="n">dotpath</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
    325. 

  325.     <span class="sd">&quot;&quot;&quot;</span>
    326. 

  326. <span class="sd">    load function in module.  function is right-most segment.</span>
    327. 

  327. 

  328. <span class="sd">    Used for passing functions (without calling them) in yaml files.</span>
    329. 

  329. 

  330. <span class="sd">    @param dotpath: path to module.</span>
    331. 

  331. <span class="sd">    @return: a python function</span>
    332. 

  332. <span class="sd">    &quot;&quot;&quot;</span>
    333. 

  333.     <span class="n">module_</span><span class="p">,</span> <span class="n">func</span> <span class="o">=</span> <span class="n">dotpath</span><span class="o">.</span><span class="n">rsplit</span><span class="p">(</span><span class="s2">&quot;.&quot;</span><span class="p">,</span> <span class="n">maxsplit</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
    334. 

  334.     <span class="n">m</span> <span class="o">=</span> <span class="n">import_module</span><span class="p">(</span><span class="n">module_</span><span class="p">)</span>
    335. 

  335.     <span class="k">return</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="n">func</span><span class="p">)</span></div>
    336. 

  336. 

  337. 

  338. <div class="viewcode-block" id="get_filename_suffix_by_framework"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.get_filename_suffix_by_framework">[docs]</a><span class="k">def</span> <span class="nf">get_filename_suffix_by_framework</span><span class="p">(</span><span class="n">framework</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
    339. 

  339.     <span class="sd">&quot;&quot;&quot;</span>
    340. 

  340. <span class="sd">    Return the file extension of framework.</span>
    341. 

  341. 

  342. <span class="sd">    @param framework: (str)</span>
    343. 

  343. <span class="sd">    @return: (str) the suffix for the specific framework</span>
    344. 

  344. <span class="sd">    &quot;&quot;&quot;</span>
    345. 

  345.     <span class="n">frameworks_dict</span> <span class="o">=</span> \
    346. 

  346.         <span class="p">{</span>
    347. 

  347.             <span class="s1">&#39;TENSORFLOW1&#39;</span><span class="p">:</span> <span class="s1">&#39;.pb&#39;</span><span class="p">,</span>
    348. 

  348.             <span class="s1">&#39;TENSORFLOW2&#39;</span><span class="p">:</span> <span class="s1">&#39;.zip&#39;</span><span class="p">,</span>
    349. 

  349.             <span class="s1">&#39;PYTORCH&#39;</span><span class="p">:</span> <span class="s1">&#39;.pth&#39;</span><span class="p">,</span>
    350. 

  350.             <span class="s1">&#39;ONNX&#39;</span><span class="p">:</span> <span class="s1">&#39;.onnx&#39;</span><span class="p">,</span>
    351. 

  351.             <span class="s1">&#39;TENSORRT&#39;</span><span class="p">:</span> <span class="s1">&#39;.pkl&#39;</span><span class="p">,</span>
    352. 

  352.             <span class="s1">&#39;OPENVINO&#39;</span><span class="p">:</span> <span class="s1">&#39;.pkl&#39;</span><span class="p">,</span>
    353. 

  353.             <span class="s1">&#39;TORCHSCRIPT&#39;</span><span class="p">:</span> <span class="s1">&#39;.pth&#39;</span><span class="p">,</span>
    354. 

  354.             <span class="s1">&#39;TVM&#39;</span><span class="p">:</span> <span class="s1">&#39;&#39;</span><span class="p">,</span>
    355. 

  355.             <span class="s1">&#39;KERAS&#39;</span><span class="p">:</span> <span class="s1">&#39;.h5&#39;</span><span class="p">,</span>
    356. 

  356.             <span class="s1">&#39;TFLITE&#39;</span><span class="p">:</span> <span class="s1">&#39;.tflite&#39;</span>
    357. 

  357.         <span class="p">}</span>
    358. 

  358. 

  359.     <span class="k">if</span> <span class="n">framework</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">frameworks_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
    360. 

  360.         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Unsupported framework: </span><span class="si">{</span><span class="n">framework</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>
    361. 

  361. 

  362.     <span class="k">return</span> <span class="n">frameworks_dict</span><span class="p">[</span><span class="n">framework</span><span class="o">.</span><span class="n">upper</span><span class="p">()]</span></div>
    363. 

  363. 

  364. 

  365. <div class="viewcode-block" id="check_models_have_same_weights"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.check_models_have_same_weights">[docs]</a><span class="k">def</span> <span class="nf">check_models_have_same_weights</span><span class="p">(</span><span class="n">model_1</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">,</span> <span class="n">model_2</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    366. 

  366.     <span class="sd">&quot;&quot;&quot;</span>
    367. 

  367. <span class="sd">    Checks whether two networks have the same weights</span>
    368. 

  368. 

  369. <span class="sd">    @param model_1: Net to be checked</span>
    370. 

  370. <span class="sd">    @param model_2: Net to be checked</span>
    371. 

  371. <span class="sd">    @return: True iff the two networks have the same weights</span>
    372. 

  372. <span class="sd">    &quot;&quot;&quot;</span>
    373. 

  373.     <span class="n">model_1</span><span class="p">,</span> <span class="n">model_2</span> <span class="o">=</span> <span class="n">model_1</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cpu&#39;</span><span class="p">),</span> <span class="n">model_2</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="s1">&#39;cpu&#39;</span><span class="p">)</span>
    374. 

  374.     <span class="n">models_differ</span> <span class="o">=</span> <span class="mi">0</span>
    375. 

  375.     <span class="k">for</span> <span class="n">key_item_1</span><span class="p">,</span> <span class="n">key_item_2</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">model_1</span><span class="o">.</span><span class="n">state_dict</span><span class="p">()</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="n">model_2</span><span class="o">.</span><span class="n">state_dict</span><span class="p">()</span><span class="o">.</span><span class="n">items</span><span class="p">()):</span>
    376. 

  376.         <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">equal</span><span class="p">(</span><span class="n">key_item_1</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">key_item_2</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
    377. 

  377.             <span class="k">pass</span>
    378. 

  378.         <span class="k">else</span><span class="p">:</span>
    379. 

  379.             <span class="n">models_differ</span> <span class="o">+=</span> <span class="mi">1</span>
    380. 

  380.             <span class="k">if</span> <span class="p">(</span><span class="n">key_item_1</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="n">key_item_2</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
    381. 

  381.                 <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Layer names match but layers have different weights for layers: </span><span class="si">{</span><span class="n">key_item_1</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>
    382. 

  382.     <span class="k">if</span> <span class="n">models_differ</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
    383. 

  383.         <span class="k">return</span> <span class="kc">True</span>
    384. 

  384.     <span class="k">else</span><span class="p">:</span>
    385. 

  385.         <span class="k">return</span> <span class="kc">False</span></div>
    386. 

  386. 

  387. 

  388. <div class="viewcode-block" id="recursive_override"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.recursive_override">[docs]</a><span class="k">def</span> <span class="nf">recursive_override</span><span class="p">(</span><span class="n">base</span><span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">extension</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span>
    389. 

  389.     <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">extension</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    390. 

  390.         <span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">base</span><span class="p">:</span>
    391. 

  391.             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">Mapping</span><span class="p">):</span>
    392. 

  392.                 <span class="n">recursive_override</span><span class="p">(</span><span class="n">base</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">extension</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
    393. 

  393.             <span class="k">else</span><span class="p">:</span>
    394. 

  394.                 <span class="n">base</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">extension</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
    395. 

  395.         <span class="k">else</span><span class="p">:</span>
    396. 

  396.             <span class="n">base</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">extension</span><span class="p">[</span><span class="n">k</span><span class="p">]</span></div>
    397. 

  397. 

  398. 

  399. <div class="viewcode-block" id="download_and_unzip_from_url"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.download_and_unzip_from_url">[docs]</a><span class="k">def</span> <span class="nf">download_and_unzip_from_url</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="nb">dir</span><span class="o">=</span><span class="s1">&#39;.&#39;</span><span class="p">,</span> <span class="n">unzip</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">delete</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    400. 

  400.     <span class="sd">&quot;&quot;&quot;</span>
    401. 

  401. <span class="sd">    Downloads a zip file from url to dir, and unzips it.</span>
    402. 

  402. 

  403. <span class="sd">    :param url: Url to download the file from.</span>
    404. 

  404. <span class="sd">    :param dir: Destination directory.</span>
    405. 

  405. <span class="sd">    :param unzip: Whether to unzip the downloaded file.</span>
    406. 

  406. <span class="sd">    :param delete: Whether to delete the zip file.</span>
    407. 

  407. 

  408. <span class="sd">    used to downlaod VOC.</span>
    409. 

  409. 

  410. <span class="sd">    Source:</span>
    411. 

  411. <span class="sd">    https://github.com/ultralytics/yolov5/blob/master/data/VOC.yaml</span>
    412. 

  412. <span class="sd">    &quot;&quot;&quot;</span>
    413. 

  413. 

  414.     <span class="k">def</span> <span class="nf">download_one</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="nb">dir</span><span class="p">):</span>
    415. 

  415.         <span class="c1"># Download 1 file</span>
    416. 

  416.         <span class="n">f</span> <span class="o">=</span> <span class="nb">dir</span> <span class="o">/</span> <span class="n">Path</span><span class="p">(</span><span class="n">url</span><span class="p">)</span><span class="o">.</span><span class="n">name</span>  <span class="c1"># filename</span>
    417. 

  417.         <span class="k">if</span> <span class="n">Path</span><span class="p">(</span><span class="n">url</span><span class="p">)</span><span class="o">.</span><span class="n">is_file</span><span class="p">():</span>  <span class="c1"># exists in current path</span>
    418. 

  418.             <span class="n">Path</span><span class="p">(</span><span class="n">url</span><span class="p">)</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>  <span class="c1"># move to dir</span>
    419. 

  419.         <span class="k">elif</span> <span class="ow">not</span> <span class="n">f</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
    420. 

  420.             <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Downloading </span><span class="si">{</span><span class="n">url</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="n">f</span><span class="si">}</span><span class="s1">...&#39;</span><span class="p">)</span>
    421. 

  421.             <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">download_url_to_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="n">progress</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>  <span class="c1"># torch download</span>
    422. 

  422.         <span class="k">if</span> <span class="n">unzip</span> <span class="ow">and</span> <span class="n">f</span><span class="o">.</span><span class="n">suffix</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">&#39;.zip&#39;</span><span class="p">,</span> <span class="s1">&#39;.gz&#39;</span><span class="p">):</span>
    423. 

  423.             <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Unzipping </span><span class="si">{</span><span class="n">f</span><span class="si">}</span><span class="s1">...&#39;</span><span class="p">)</span>
    424. 

  424.             <span class="k">if</span> <span class="n">f</span><span class="o">.</span><span class="n">suffix</span> <span class="o">==</span> <span class="s1">&#39;.zip&#39;</span><span class="p">:</span>
    425. 

  425.                 <span class="n">ZipFile</span><span class="p">(</span><span class="n">f</span><span class="p">)</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="n">path</span><span class="o">=</span><span class="nb">dir</span><span class="p">)</span>  <span class="c1"># unzip</span>
    426. 

  426.             <span class="k">elif</span> <span class="n">f</span><span class="o">.</span><span class="n">suffix</span> <span class="o">==</span> <span class="s1">&#39;.gz&#39;</span><span class="p">:</span>
    427. 

  427.                 <span class="n">os</span><span class="o">.</span><span class="n">system</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;tar xfz </span><span class="si">{</span><span class="n">f</span><span class="si">}</span><span class="s1"> --directory </span><span class="si">{</span><span class="n">f</span><span class="o">.</span><span class="n">parent</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>  <span class="c1"># unzip</span>
    428. 

  428.             <span class="k">if</span> <span class="n">delete</span><span class="p">:</span>
    429. 

  429.                 <span class="n">f</span><span class="o">.</span><span class="n">unlink</span><span class="p">()</span>  <span class="c1"># remove zip</span>
    430. 

  430. 

  431.     <span class="nb">dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="nb">dir</span><span class="p">)</span>
    432. 

  432.     <span class="nb">dir</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">parents</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>  <span class="c1"># make directory</span>
    433. 

  433.     <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="p">[</span><span class="n">url</span><span class="p">]</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">))</span> <span class="k">else</span> <span class="n">url</span><span class="p">:</span>
    434. 

  434.         <span class="n">download_one</span><span class="p">(</span><span class="n">u</span><span class="p">,</span> <span class="nb">dir</span><span class="p">)</span></div>
    435. 

  435. 

  436. 

  437. <div class="viewcode-block" id="download_and_untar_from_url"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.download_and_untar_from_url">[docs]</a><span class="k">def</span> <span class="nf">download_and_untar_from_url</span><span class="p">(</span><span class="n">urls</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> <span class="nb">dir</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Path</span><span class="p">]</span> <span class="o">=</span> <span class="s1">&#39;.&#39;</span><span class="p">):</span>
    438. 

  438.     <span class="sd">&quot;&quot;&quot;</span>
    439. 

  439. <span class="sd">    Download a file from url and untar.</span>
    440. 

  440. 

  441. <span class="sd">    :param urls:    Url to download the file from.</span>
    442. 

  442. <span class="sd">    :param dir:     Destination directory.</span>
    443. 

  443. <span class="sd">    &quot;&quot;&quot;</span>
    444. 

  444.     <span class="nb">dir</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="nb">dir</span><span class="p">)</span>
    445. 

  445.     <span class="nb">dir</span><span class="o">.</span><span class="n">mkdir</span><span class="p">(</span><span class="n">parents</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">exist_ok</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    446. 

  446. 

  447.     <span class="k">for</span> <span class="n">url</span> <span class="ow">in</span> <span class="n">urls</span><span class="p">:</span>
    448. 

  448.         <span class="n">url_path</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">url</span><span class="p">)</span>
    449. 

  449.         <span class="n">filepath</span> <span class="o">=</span> <span class="nb">dir</span> <span class="o">/</span> <span class="n">url_path</span><span class="o">.</span><span class="n">name</span>
    450. 

  450. 

  451.         <span class="k">if</span> <span class="n">url_path</span><span class="o">.</span><span class="n">is_file</span><span class="p">():</span>
    452. 

  452.             <span class="n">url_path</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">filepath</span><span class="p">)</span>
    453. 

  453.         <span class="k">elif</span> <span class="ow">not</span> <span class="n">filepath</span><span class="o">.</span><span class="n">exists</span><span class="p">():</span>
    454. 

  454.             <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Downloading </span><span class="si">{</span><span class="n">url</span><span class="si">}</span><span class="s1"> to </span><span class="si">{</span><span class="n">filepath</span><span class="si">}</span><span class="s1">...&#39;</span><span class="p">)</span>
    455. 

  455.             <span class="n">torch</span><span class="o">.</span><span class="n">hub</span><span class="o">.</span><span class="n">download_url_to_file</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">filepath</span><span class="p">),</span> <span class="n">progress</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    456. 

  456. 

  457.         <span class="n">modes</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;.tar.gz&quot;</span><span class="p">:</span> <span class="s2">&quot;r:gz&quot;</span><span class="p">,</span> <span class="s2">&quot;.tar&quot;</span><span class="p">:</span> <span class="s2">&quot;r:&quot;</span><span class="p">}</span>
    458. 

  458.         <span class="k">assert</span> <span class="n">filepath</span><span class="o">.</span><span class="n">suffix</span> <span class="ow">in</span> <span class="n">modes</span><span class="o">.</span><span class="n">keys</span><span class="p">(),</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">filepath</span><span class="si">}</span><span class="s2"> has </span><span class="si">{</span><span class="n">filepath</span><span class="o">.</span><span class="n">suffix</span><span class="si">}</span><span class="s2"> suffix which is not supported&quot;</span>
    459. 

  459. 

  460.         <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;Extracting to </span><span class="si">{</span><span class="nb">dir</span><span class="si">}</span><span class="s1">...&#39;</span><span class="p">)</span>
    461. 

  461.         <span class="k">with</span> <span class="n">tarfile</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">filepath</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="n">modes</span><span class="p">[</span><span class="n">filepath</span><span class="o">.</span><span class="n">suffix</span><span class="p">])</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    462. 

  462.             <span class="n">f</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="nb">dir</span><span class="p">)</span>
    463. 

  463.         <span class="n">filepath</span><span class="o">.</span><span class="n">unlink</span><span class="p">()</span></div>
    464. 

  464. 

  465. 

  466. <div class="viewcode-block" id="make_divisible"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.make_divisible">[docs]</a><span class="k">def</span> <span class="nf">make_divisible</span><span class="p">(</span><span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">divisor</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">ceil</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
    467. 

  467.     <span class="sd">&quot;&quot;&quot;</span>
    468. 

  468. <span class="sd">    Returns x evenly divisible by divisor.</span>
    469. 

  469. <span class="sd">    If ceil=True it will return the closest larger number to the original x, and ceil=False the closest smaller number.</span>
    470. 

  470. <span class="sd">    &quot;&quot;&quot;</span>
    471. 

  471.     <span class="k">if</span> <span class="n">ceil</span><span class="p">:</span>
    472. 

  472.         <span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">x</span> <span class="o">/</span> <span class="n">divisor</span><span class="p">)</span> <span class="o">*</span> <span class="n">divisor</span>
    473. 

  473.     <span class="k">else</span><span class="p">:</span>
    474. 

  474.         <span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">floor</span><span class="p">(</span><span class="n">x</span> <span class="o">/</span> <span class="n">divisor</span><span class="p">)</span> <span class="o">*</span> <span class="n">divisor</span></div>
    475. 

  475. 

  476. 

  477. <div class="viewcode-block" id="check_img_size_divisibility"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.check_img_size_divisibility">[docs]</a><span class="k">def</span> <span class="nf">check_img_size_divisibility</span><span class="p">(</span><span class="n">img_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">stride</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">32</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">bool</span><span class="p">,</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">int</span><span class="p">]]]:</span>
    478. 

  478.     <span class="sd">&quot;&quot;&quot;</span>
    479. 

  479. <span class="sd">    :param img_size: Int, the size of the image (H or W).</span>
    480. 

  480. <span class="sd">    :param stride: Int, the number to check if img_size is divisible by.</span>
    481. 

  481. <span class="sd">    :return: (True, None) if img_size is divisble by stride, (False, Suggestions) if it&#39;s not.</span>
    482. 

  482. <span class="sd">        Note: Suggestions are the two closest numbers to img_size that *are* divisible by stride.</span>
    483. 

  483. <span class="sd">        For example if img_size=321, stride=32, it will return (False,(352, 320)).</span>
    484. 

  484. <span class="sd">    &quot;&quot;&quot;</span>
    485. 

  485.     <span class="n">new_size</span> <span class="o">=</span> <span class="n">make_divisible</span><span class="p">(</span><span class="n">img_size</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="n">stride</span><span class="p">))</span>
    486. 

  486.     <span class="k">if</span> <span class="n">new_size</span> <span class="o">!=</span> <span class="n">img_size</span><span class="p">:</span>
    487. 

  487.         <span class="k">return</span> <span class="kc">False</span><span class="p">,</span> <span class="p">(</span><span class="n">new_size</span><span class="p">,</span> <span class="n">make_divisible</span><span class="p">(</span><span class="n">img_size</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="n">stride</span><span class="p">),</span> <span class="n">ceil</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
    488. 

  488.     <span class="k">else</span><span class="p">:</span>
    489. 

  489.         <span class="k">return</span> <span class="kc">True</span><span class="p">,</span> <span class="kc">None</span></div>
    490. 

  490. 

  491. 

  492. <div class="viewcode-block" id="get_orientation_key"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.get_orientation_key">[docs]</a><span class="nd">@lru_cache</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
    493. 

  493. <span class="k">def</span> <span class="nf">get_orientation_key</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
    494. 

  494.     <span class="sd">&quot;&quot;&quot;Get the orientation key according to PIL, which is useful to get the image size for instance</span>
    495. 

  495. <span class="sd">    :return: Orientation key according to PIL&quot;&quot;&quot;</span>
    496. 

  496.     <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">ExifTags</span><span class="o">.</span><span class="n">TAGS</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
    497. 

  497.         <span class="k">if</span> <span class="n">value</span> <span class="o">==</span> <span class="s1">&#39;Orientation&#39;</span><span class="p">:</span>
    498. 

  498.             <span class="k">return</span> <span class="n">key</span></div>
    499. 

  499. 

  500. 

  501. <div class="viewcode-block" id="exif_size"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.exif_size">[docs]</a><span class="k">def</span> <span class="nf">exif_size</span><span class="p">(</span><span class="n">image</span><span class="p">:</span> <span class="n">Image</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">int</span><span class="p">]:</span>
    502. 

  502.     <span class="sd">&quot;&quot;&quot;Get the size of image.</span>
    503. 

  503. <span class="sd">    :param image:   The image to get size from</span>
    504. 

  504. <span class="sd">    :return:        (width, height)</span>
    505. 

  505. <span class="sd">    &quot;&quot;&quot;</span>
    506. 

  506. 

  507.     <span class="n">orientation_key</span> <span class="o">=</span> <span class="n">get_orientation_key</span><span class="p">()</span>
    508. 

  508. 

  509.     <span class="n">image_size</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">size</span>
    510. 

  510.     <span class="k">try</span><span class="p">:</span>
    511. 

  511.         <span class="n">exif_data</span> <span class="o">=</span> <span class="n">image</span><span class="o">.</span><span class="n">_getexif</span><span class="p">()</span>
    512. 

  512.         <span class="k">if</span> <span class="n">exif_data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
    513. 

  513.             <span class="n">rotation</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">exif_data</span><span class="o">.</span><span class="n">items</span><span class="p">())[</span><span class="n">orientation_key</span><span class="p">]</span>
    514. 

  514.             <span class="c1"># ROTATION 270</span>
    515. 

  515.             <span class="k">if</span> <span class="n">rotation</span> <span class="o">==</span> <span class="mi">6</span><span class="p">:</span>
    516. 

  516.                 <span class="n">image_size</span> <span class="o">=</span> <span class="p">(</span><span class="n">image_size</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">image_size</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
    517. 

  517.             <span class="c1"># ROTATION 90</span>
    518. 

  518.             <span class="k">elif</span> <span class="n">rotation</span> <span class="o">==</span> <span class="mi">8</span><span class="p">:</span>
    519. 

  519.                 <span class="n">image_size</span> <span class="o">=</span> <span class="p">(</span><span class="n">image_size</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">image_size</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
    520. 

  520.     <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">ex</span><span class="p">:</span>
    521. 

  521.         <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Caught Exception trying to rotate: &#39;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">image</span><span class="p">)</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">ex</span><span class="p">))</span>
    522. 

  522.     <span class="n">height</span><span class="p">,</span> <span class="n">width</span> <span class="o">=</span> <span class="n">image_size</span>
    523. 

  523.     <span class="k">return</span> <span class="n">width</span><span class="p">,</span> <span class="n">height</span></div>
    524. 

  524. 

  525. 

  526. <div class="viewcode-block" id="get_image_size_from_path"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.get_image_size_from_path">[docs]</a><span class="k">def</span> <span class="nf">get_image_size_from_path</span><span class="p">(</span><span class="n">img_path</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="nb">int</span><span class="p">]:</span>
    527. 

  527.     <span class="sd">&quot;&quot;&quot;Get the image size of an image at a specific path&quot;&quot;&quot;</span>
    528. 

  528.     <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">img_path</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    529. 

  529.         <span class="k">return</span> <span class="n">exif_size</span><span class="p">(</span><span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">f</span><span class="p">))</span></div>
    530. 

  530. </pre></div>
    531. 

  531. 

  532.            </div>
    533. 

  533.           </div>
    534. 

  534.           <footer>
    535. 

  535. 

  536.   <hr/>
    537. 

  537. 

  538.   <div role="contentinfo">
    539. 

  539.     <p>&#169; Copyright 2021, SuperGradients team.</p>
    540. 

  540.   </div>
    541. 

  541. 

  542.   Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a
    543. 

  543.     <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a>
    544. 

  544.     provided by <a href="https://readthedocs.org">Read the Docs</a>.
    545. 

  545.    
    546. 

  546. 

  547. </footer>
    548. 

  548.         </div>
    549. 

  549.       </div>
    550. 

  550.     </section>
    551. 

  551.   </div>
    552. 

  552.   <script>
    553. 

  553.       jQuery(function () {
    554. 

  554.           SphinxRtdTheme.Navigation.enable(true);
    555. 

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  557. 

  558. </body>
    559. 

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