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title: Title


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nb_path: "nbs/demo-Copy1.ipynb"
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">tree_sitter</span> <span class="kn">import</span> <span class="n">Language</span>

<span class="kn">from</span> <span class="nn">function_parser.language_data</span> <span class="kn">import</span> <span class="n">LANGUAGE_METADATA</span>
<span class="kn">from</span> <span class="nn">function_parser.process</span> <span class="kn">import</span> <span class="n">DataProcessor</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">Language</span><span class="o">.</span><span class="n">build_library</span><span class="p">(</span>
    <span class="c1"># Store the library in the directory</span>
    <span class="s1">&#39;/root/workspace/function_parser/py-tree-sitter-languages.so&#39;</span><span class="p">,</span>
    <span class="c1"># Include one or more languages</span>
    <span class="p">[</span><span class="s1">&#39;/root/workspace/function_parser/tree-sitter-python&#39;</span><span class="p">]</span>
<span class="p">)</span>
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<pre>True</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">language</span> <span class="o">=</span> <span class="s1">&#39;python&#39;</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">DataProcessor</span><span class="o">.</span><span class="n">PARSER</span><span class="o">.</span><span class="n">set_language</span><span class="p">(</span><span class="n">Language</span><span class="p">(</span><span class="s1">&#39;/root/workspace/function_parser/py-tree-sitter-languages.so&#39;</span><span class="p">,</span> <span class="n">language</span><span class="p">))</span>

<span class="n">processor</span> <span class="o">=</span> <span class="n">DataProcessor</span><span class="p">(</span><span class="n">language</span><span class="o">=</span><span class="n">language</span><span class="p">,</span>
                          <span class="n">language_parser</span><span class="o">=</span><span class="n">LANGUAGE_METADATA</span><span class="p">[</span><span class="n">language</span><span class="p">][</span><span class="s1">&#39;language_parser&#39;</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dependee</span> <span class="o">=</span> <span class="s1">&#39;keras-team/keras&#39;</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">definitions</span> <span class="o">=</span> <span class="n">processor</span><span class="o">.</span><span class="n">process_dee</span><span class="p">(</span><span class="n">dependee</span><span class="p">,</span> <span class="n">ext</span><span class="o">=</span><span class="n">LANGUAGE_METADATA</span><span class="p">[</span><span class="n">language</span><span class="p">][</span><span class="s1">&#39;ext&#39;</span><span class="p">])</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">definitions</span><span class="p">)</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>nwo</th>
      <th>sha</th>
      <th>path</th>
      <th>language</th>
      <th>identifier</th>
      <th>parameters</th>
      <th>argument_list</th>
      <th>return_statement</th>
      <th>docstring</th>
      <th>docstring_summary</th>
      <th>docstring_tokens</th>
      <th>function</th>
      <th>function_tokens</th>
      <th>url</th>
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    <tr>
      <th>0</th>
      <td>keras-team/keras</td>
      <td>e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b</td>
      <td>keras/optimizer_v1.py</td>
      <td>python</td>
      <td>Optimizer.__init__</td>
      <td>(self, **kwargs)</td>
      <td></td>
      <td></td>
      <td></td>
      <td></td>
      <td>[]</td>
      <td>def __init__(self, **kwargs):\n    allowed_kwa...</td>
      <td>[def, __init__, (, self, ,, *, *, kwargs, ), :...</td>
      <td>https://github.com/keras-team/keras/blob/e43af...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>keras-team/keras</td>
      <td>e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b</td>
      <td>keras/optimizer_v1.py</td>
      <td>python</td>
      <td>Optimizer._create_all_weights</td>
      <td>(self, params)</td>
      <td></td>
      <td></td>
      <td>Creates and sets all optimizer weights.\n\n   ...</td>
      <td>Creates and sets all optimizer weights.</td>
      <td>[Creates, and, sets, all, optimizer, weights, .]</td>
      <td>def _create_all_weights(self, params):\n    ""...</td>
      <td>[def, _create_all_weights, (, self, ,, params,...</td>
      <td>https://github.com/keras-team/keras/blob/e43af...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>keras-team/keras</td>
      <td>e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b</td>
      <td>keras/optimizer_v1.py</td>
      <td>python</td>
      <td>Optimizer.get_gradients</td>
      <td>(self, loss, params)</td>
      <td></td>
      <td>return grads</td>
      <td>Returns gradients of `loss` with respect to `p...</td>
      <td>Returns gradients of `loss` with respect to `p...</td>
      <td>[Returns, gradients, of, loss, with, respect, ...</td>
      <td>def get_gradients(self, loss, params):\n    ""...</td>
      <td>[def, get_gradients, (, self, ,, loss, ,, para...</td>
      <td>https://github.com/keras-team/keras/blob/e43af...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>keras-team/keras</td>
      <td>e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b</td>
      <td>keras/optimizer_v1.py</td>
      <td>python</td>
      <td>Optimizer.set_weights</td>
      <td>(self, weights)</td>
      <td></td>
      <td></td>
      <td>Sets the weights of the optimizer, from Numpy ...</td>
      <td>Sets the weights of the optimizer, from Numpy ...</td>
      <td>[Sets, the, weights, of, the, optimizer, from,...</td>
      <td>def set_weights(self, weights):\n    """Sets t...</td>
      <td>[def, set_weights, (, self, ,, weights, ), :, ...</td>
      <td>https://github.com/keras-team/keras/blob/e43af...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>keras-team/keras</td>
      <td>e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b</td>
      <td>keras/optimizer_v1.py</td>
      <td>python</td>
      <td>Optimizer.get_weights</td>
      <td>(self)</td>
      <td></td>
      <td>return K.batch_get_value(self.weights)</td>
      <td>Returns the current value of the weights of th...</td>
      <td>Returns the current value of the weights of th...</td>
      <td>[Returns, the, current, value, of, the, weight...</td>
      <td>def get_weights(self):\n    """Returns the cur...</td>
      <td>[def, get_weights, (, self, ), :, return, K, ....</td>
      <td>https://github.com/keras-team/keras/blob/e43af...</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">library_candidates</span> <span class="o">=</span> <span class="p">{}</span>
<span class="n">library_candidates</span><span class="p">[</span><span class="n">dependee</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="o">-</span><span class="mi">1</span><span class="p">]]</span> <span class="o">=</span> <span class="n">definitions</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dependent</span> <span class="o">=</span> <span class="n">dependee</span><span class="c1">#&#39;eriklindernoren/Keras-GAN&#39;</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">calls</span><span class="p">,</span> <span class="n">edges</span> <span class="o">=</span> <span class="n">processor</span><span class="o">.</span><span class="n">process_dent</span><span class="p">(</span><span class="n">dependent</span><span class="p">,</span> <span class="n">ext</span><span class="o">=</span><span class="n">LANGUAGE_METADATA</span><span class="p">[</span><span class="n">language</span><span class="p">][</span><span class="s1">&#39;ext&#39;</span><span class="p">],</span> <span class="n">library_candidates</span><span class="o">=</span><span class="n">library_candidates</span><span class="p">)</span>
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<pre>[(&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L166-L166&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L729-L736&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L168-L168&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L729-L736&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L182-L182&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1402-L1428&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L186-L186&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1402-L1428&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L189-L189&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend_config.py#L116-L126&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L193-L193&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1402-L1428&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L202-L202&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1402-L1428&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L242-L242&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/engine/training_utils_v1.py#L530-L653&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L258-L258&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1257-L1349&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L259-L259&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1257-L1349&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L433-L433&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L692-L718&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L448-L448&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L314-L340&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/callbacks_v1.py#L449-L449&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L314-L340&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L47-L47&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/utils/generic_utils.py#L236-L271&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L84-L84&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/utils/generic_utils.py#L340-L399&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L112-L112&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizer_v1.py#L743-L751&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L113-L113&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L1068-L1073&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L51-L88&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/regularizers.py#L360-L369&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/activations.py#L506-L544&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/metrics.py#L3494-L3509&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/constraints.py#L288-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/losses.py#L1845-L1860&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/initializers/__init__.py#L141-L148&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/optimizers.py#L116-L116&#39;,
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  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L266-L266&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L268-L268&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L268-L268&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L269-L269&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L269-L269&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L270-L270&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L270-L270&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L271-L271&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L271-L271&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L272-L272&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L272-L272&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L276-L276&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L276-L276&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L277-L277&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/backend.py#L3027-L3060&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L277-L277&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/layers/merge.py#L899-L930&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L282-L282&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L282-L282&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L283-L283&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L283-L283&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L285-L285&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L285-L285&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L286-L286&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L286-L286&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L287-L287&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_resnet_v2.py#L254-L293&#39;),
 (&#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L287-L287&#39;,
  &#39;https://github.com/keras-team/keras/blob/e43af6c89cd6c4adecc21ad5fc05b21e7fa9477b/keras/applications/inception_v3.py#L364-L406&#39;),
 ...]</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">calls</span><span class="p">)</span>
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<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
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        text-align: right;
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</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>argument_list</th>
      <th>identifier</th>
      <th>language</th>
      <th>nwo</th>
      <th>path</th>
      <th>sha</th>
      <th>url</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>(0.0002, 0.5)</td>
      <td>Adam</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>(layer_input)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>(filters, kernel_size=f_size, strides=2, paddi...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>(d)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>(alpha=0.2)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>5</th>
      <td>(layer_input)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>6</th>
      <td>(size=2)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>7</th>
      <td>(u)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>8</th>
      <td>(filters, kernel_size=f_size, strides=1, paddi...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>9</th>
      <td>(u)</td>
      <td>Dropout</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>10</th>
      <td>(dropout_rate)</td>
      <td>Dropout</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>11</th>
      <td>([u, skip_input])</td>
      <td>Concatenate</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>12</th>
      <td>()</td>
      <td>Concatenate</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>13</th>
      <td>(u6)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>14</th>
      <td>(size=2)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>15</th>
      <td>(u7)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>16</th>
      <td>(self.channels, kernel_size=4, strides=1,\n   ...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>17</th>
      <td>(layer_input)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>18</th>
      <td>(filters, kernel_size=f_size, strides=2, paddi...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>19</th>
      <td>(d)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>20</th>
      <td>(alpha=0.2)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>21</th>
      <td>(d4)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>22</th>
      <td>(1, kernel_size=4, strides=1, padding='same')</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>discogan/discogan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>23</th>
      <td>(0.0002, 0.5)</td>
      <td>Adam</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>24</th>
      <td>()</td>
      <td>Sequential</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>25</th>
      <td>(128 * 7 * 7, activation="relu", input_dim=sel...</td>
      <td>Dense</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>26</th>
      <td>((7, 7, 128))</td>
      <td>Reshape</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>27</th>
      <td>()</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>28</th>
      <td>(128, kernel_size=3, padding="same")</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>29</th>
      <td>(momentum=0.8)</td>
      <td>BatchNormalization</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>dcgan/dcgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>...</th>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
      <td>...</td>
    </tr>
    <tr>
      <th>621</th>
      <td>(alpha=0.2)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>622</th>
      <td>(d)</td>
      <td>BatchNormalization</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>623</th>
      <td>(momentum=0.8)</td>
      <td>BatchNormalization</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>624</th>
      <td>(layer_input)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>625</th>
      <td>(size=2)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>626</th>
      <td>(u)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>627</th>
      <td>(filters, kernel_size=f_size, strides=1, paddi...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>628</th>
      <td>(u)</td>
      <td>Dropout</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>629</th>
      <td>(dropout_rate)</td>
      <td>Dropout</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>630</th>
      <td>(u)</td>
      <td>BatchNormalization</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>631</th>
      <td>(momentum=0.8)</td>
      <td>BatchNormalization</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>632</th>
      <td>([u, skip_input])</td>
      <td>Concatenate</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>633</th>
      <td>()</td>
      <td>Concatenate</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>634</th>
      <td>(u3)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>635</th>
      <td>(size=2)</td>
      <td>UpSampling2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>636</th>
      <td>(u4)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>637</th>
      <td>(self.channels, kernel_size=4, strides=1, padd...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>638</th>
      <td>()</td>
      <td>Sequential</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>639</th>
      <td>(64, kernel_size=4, strides=2, padding='same',...</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>640</th>
      <td>(alpha=0.8)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>641</th>
      <td>(128, kernel_size=4, strides=2, padding='same')</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>642</th>
      <td>(alpha=0.2)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>643</th>
      <td>(256, kernel_size=4, strides=2, padding='same')</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>644</th>
      <td>(alpha=0.2)</td>
      <td>LeakyReLU</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>645</th>
      <td>(features)</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>646</th>
      <td>(1, kernel_size=4, strides=1, padding='same')</td>
      <td>Conv2D</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>647</th>
      <td>(features)</td>
      <td>Flatten</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>648</th>
      <td>()</td>
      <td>Flatten</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>649</th>
      <td>(label)</td>
      <td>Dense</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
    <tr>
      <th>650</th>
      <td>(self.num_classes+1, activation="softmax")</td>
      <td>Dense</td>
      <td>python</td>
      <td>eriklindernoren/Keras-GAN</td>
      <td>ccgan/ccgan.py</td>
      <td>44d3320e84ca00071de8a5c0fb4566d10486bb1d</td>
      <td>https://github.com/eriklindernoren/Keras-GAN/b...</td>
    </tr>
  </tbody>
</table>
<p>651 rows × 7 columns</p>
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  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/optimizers.py#L455-L468&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L99-L99&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L99-L99&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L100-L100&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/advanced_activations.py#L42-L45&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L100-L100&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/advanced_activations.py#L42-L45&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L107-L107&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L2014-L2021&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L107-L107&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L2014-L2021&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L108-L108&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L108-L108&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L110-L110&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/core.py#L103-L108&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L110-L110&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/core.py#L103-L108&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L112-L112&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/merge.py#L340-L344&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L112-L112&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/merge.py#L340-L344&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L135-L135&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L2014-L2021&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L135-L135&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L2014-L2021&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L136-L136&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L136-L136&#39;,
  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/convolutional.py#L451-L484&#39;),
 (&#39;https://github.com/eriklindernoren/Keras-GAN/blob/44d3320e84ca00071de8a5c0fb4566d10486bb1d/discogan/discogan.py#L145-L145&#39;,
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  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/core.py#L860-L885&#39;),
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  &#39;https://github.com/keras-team/keras/blob/0fc33feb5f4efe3bb823c57a8390f52932a966ab/keras/layers/core.py#L860-L885&#39;)]</pre>
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