deploy: 0e8c062

Author: liugangcode

_modules/index.html

@@ -267,6 +267,7 @@ <h1>All modules for which code is available</h1>
 <li><a href="torch_molecule/encoder/attrmask/modeling_attrmask.html">torch_molecule.encoder.attrmask.modeling_attrmask</a></li>
 <li><a href="torch_molecule/encoder/contextpred/modeling_contextpred.html">torch_molecule.encoder.contextpred.modeling_contextpred</a></li>
 <li><a href="torch_molecule/encoder/edgepred/modeling_edgepred.html">torch_molecule.encoder.edgepred.modeling_edgepred</a></li>
+<li><a href="torch_molecule/encoder/graphmae/modeling_graphmae.html">torch_molecule.encoder.graphmae.modeling_graphmae</a></li>
 <li><a href="torch_molecule/encoder/infograph/modeling_infograph.html">torch_molecule.encoder.infograph.modeling_infograph</a></li>
 <li><a href="torch_molecule/encoder/moama/modeling_moama.html">torch_molecule.encoder.moama.modeling_moama</a></li>
 <li><a href="torch_molecule/encoder/pretrained/modeling_pretrained.html">torch_molecule.encoder.pretrained.modeling_pretrained</a></li>

_modules/torch_molecule/encoder/graphmae/modeling_graphmae.html

@@ -383,14 +383,15 @@ <h1>Source code for torch_molecule.nn.gnn</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="GINConv">
 <a class="viewcode-back" href="../../../api/nn.html#torch_molecule.nn.gnn.GINConv">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">GINConv</span><span class="p">(</span><span class="n">MessagePassing</span><span class="p">):</span>
-    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">):</span>
+    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&#39;&#39;&#39;</span>
 <span class="sd">            hidden_size (int): node embedding dimensionality</span>
 <span class="sd">        &#39;&#39;&#39;</span>
-
         <span class="nb">super</span><span class="p">(</span><span class="n">GINConv</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">aggr</span> <span class="o">=</span> <span class="s2">&quot;add&quot;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">output_size</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">output_size</span> <span class="o">=</span> <span class="n">hidden_size</span>
 
-        <span class="bp">self</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Sequential</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">Linear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span> <span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</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">BatchNorm1d</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</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">ReLU</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">Linear</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">))</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">mlp</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Sequential</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">Linear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span> <span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</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">BatchNorm1d</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</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">ReLU</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">Linear</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">hidden_size</span><span class="p">,</span> <span class="n">output_size</span><span class="p">))</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">eps</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Parameter</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="mi">0</span><span class="p">]))</span>
 
         <span class="bp">self</span><span class="o">.</span><span class="n">bond_encoder</span> <span class="o">=</span> <span class="n">BondEncoder</span><span class="p">(</span><span class="n">hidden_size</span> <span class="o">=</span> <span class="n">hidden_size</span><span class="p">)</span>
@@ -420,12 +421,14 @@ <h1>Source code for torch_molecule.nn.gnn</h1><div class="highlight"><pre>
 <div class="viewcode-block" id="GCNConv">
 <a class="viewcode-back" href="../../../api/nn.html#torch_molecule.nn.gnn.GCNConv">[docs]</a>
 <span class="k">class</span><span class="w"> </span><span class="nc">GCNConv</span><span class="p">(</span><span class="n">MessagePassing</span><span class="p">):</span>
-    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">):</span>
+    <span class="k">def</span><span class="w"> </span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">,</span> <span class="n">output_size</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
         <span class="nb">super</span><span class="p">(</span><span class="n">GCNConv</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">aggr</span><span class="o">=</span><span class="s1">&#39;add&#39;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">output_size</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">output_size</span> <span class="o">=</span> <span class="n">hidden_size</span>
 
-        <span class="bp">self</span><span class="o">.</span><span class="n">linear</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">root_emb</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">hidden_size</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">bond_encoder</span> <span class="o">=</span> <span class="n">BondEncoder</span><span class="p">(</span><span class="n">hidden_size</span> <span class="o">=</span> <span class="n">hidden_size</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">linear</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">hidden_size</span><span class="p">,</span> <span class="n">output_size</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">root_emb</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Embedding</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">output_size</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">bond_encoder</span> <span class="o">=</span> <span class="n">BondEncoder</span><span class="p">(</span><span class="n">hidden_size</span> <span class="o">=</span> <span class="n">output_size</span><span class="p">)</span>
 
 <div class="viewcode-block" id="GCNConv.forward">
 <a class="viewcode-back" href="../../../api/nn.html#torch_molecule.nn.gnn.GCNConv.forward">[docs]</a>
@@ -434,15 +437,14 @@ <h1>Source code for torch_molecule.nn.gnn</h1><div class="highlight"><pre>
         <span class="n">edge_embedding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bond_encoder</span><span class="p">(</span><span class="n">edge_attr</span><span class="p">)</span>
 
         <span class="n">row</span><span class="p">,</span> <span class="n">col</span> <span class="o">=</span> <span class="n">edge_index</span>
-
         <span class="c1">#edge_weight = torch.ones((edge_index.size(1), ), device=edge_index.device)</span>
         <span class="n">deg</span> <span class="o">=</span> <span class="n">degree</span><span class="p">(</span><span class="n">row</span><span class="p">,</span> <span class="n">x</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">),</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span>
         <span class="n">deg_inv_sqrt</span> <span class="o">=</span> <span class="n">deg</span><span class="o">.</span><span class="n">pow</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="p">)</span>
         <span class="n">deg_inv_sqrt</span><span class="p">[</span><span class="n">deg_inv_sqrt</span> <span class="o">==</span> <span class="nb">float</span><span class="p">(</span><span class="s1">&#39;inf&#39;</span><span class="p">)]</span> <span class="o">=</span> <span class="mi">0</span>
 
         <span class="n">norm</span> <span class="o">=</span> <span class="n">deg_inv_sqrt</span><span class="p">[</span><span class="n">row</span><span class="p">]</span> <span class="o">*</span> <span class="n">deg_inv_sqrt</span><span class="p">[</span><span class="n">col</span><span class="p">]</span>
 
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">propagate</span><span class="p">(</span><span class="n">edge_index</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_attr</span> <span class="o">=</span> <span class="n">edge_embedding</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="n">norm</span><span class="p">)</span> <span class="o">+</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">x</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">root_emb</span><span class="o">.</span><span class="n">weight</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.</span><span class="o">/</span><span class="n">deg</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">propagate</span><span class="p">(</span><span class="n">edge_index</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">edge_attr</span><span class="o">=</span><span class="n">edge_embedding</span><span class="p">,</span> <span class="n">norm</span><span class="o">=</span><span class="n">norm</span><span class="p">)</span> <span class="o">+</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="n">x</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">root_emb</span><span class="o">.</span><span class="n">weight</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.</span><span class="o">/</span><span class="n">deg</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span></div>
 
 
 <div class="viewcode-block" id="GCNConv.message">

_modules/torch_molecule/nn/gnn.html

@@ -262,6 +262,8 @@
           <h1>Source code for torch_molecule.utils.graph.features</h1><div class="highlight"><pre>
 <span></span><span class="c1"># allowable multiple choice node and edge features </span>
 <span class="n">allowable_features</span> <span class="o">=</span> <span class="p">{</span>
+    <span class="c1"># atom types: 1-118, 119 is masked atom, 120 is misc (e.g. * for polymers)</span>
+    <span class="c1"># index: 0-117, 118, 119</span>
     <span class="s1">&#39;possible_atomic_num_list&#39;</span> <span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">120</span><span class="p">))</span> <span class="o">+</span> <span class="p">[</span><span class="s1">&#39;misc&#39;</span><span class="p">],</span>
     <span class="s1">&#39;possible_chirality_list&#39;</span> <span class="p">:</span> <span class="p">[</span>
         <span class="s1">&#39;CHI_UNSPECIFIED&#39;</span><span class="p">,</span>

_modules/torch_molecule/utils/graph/features.html

@@ -331,6 +331,7 @@ <h1>Source code for torch_molecule.utils.graph.graph_from_smiles</h1><div class=
     <span class="c1"># atoms</span>
     <span class="n">atom_features_list</span> <span class="o">=</span> <span class="p">[]</span>
     <span class="k">for</span> <span class="n">atom</span> <span class="ow">in</span> <span class="n">mol</span><span class="o">.</span><span class="n">GetAtoms</span><span class="p">():</span>
+        <span class="c1"># print(atom.GetSymbol(), atom_to_feature_vector(atom)[0])</span>
         <span class="n">atom_features_list</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">atom_to_feature_vector</span><span class="p">(</span><span class="n">atom</span><span class="p">))</span>
 
     <span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">atom_features_list</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">np</span><span class="o">.</span><span class="n">int64</span><span class="p">)</span>

_modules/torch_molecule/utils/graph/graph_from_smiles.html

@@ -42,23 +42,31 @@ Self-supervised Molecular Representation Learning
    :undoc-members:
    :show-inheritance:
 
-.. rubric:: Context Prediction for Molecular Representation Learning
+.. rubric:: Graph masked autoencoder
+
+.. autoclass:: torch_molecule.encoder.graphmae.modeling_graphmae.GraphMAEMolecularEncoder
+   :members: fit, encode
+   :exclude-members: fitting_epoch, fitting_loss, model_name, model_class
+   :undoc-members:
+   :show-inheritance:
+
+.. rubric:: Context Prediction
 
 .. autoclass:: torch_molecule.encoder.contextpred.modeling_contextpred.ContextPredMolecularEncoder
    :members: fit, encode
    :exclude-members: fitting_epoch, fitting_loss, model_name, model_class
    :undoc-members:
    :show-inheritance:
 
-.. rubric:: Edge Prediction for Molecular Representation Learning
+.. rubric:: Edge Prediction
 
 .. autoclass:: torch_molecule.encoder.edgepred.modeling_edgepred.EdgePredMolecularEncoder
    :members: fit, encode
    :exclude-members: fitting_epoch, fitting_loss, model_name, model_class
    :undoc-members:
    :show-inheritance:
 
-.. rubric:: InfoGraph for Molecular Representation Learning
+.. rubric:: InfoGraph
 
 .. autoclass:: torch_molecule.encoder.infograph.modeling_infograph.InfoGraphMolecularEncoder
    :members: fit, encode
@@ -69,7 +77,7 @@ Self-supervised Molecular Representation Learning
 Supervised Pretraining for Molecules
 ------------------------------------
 
-.. rubric:: Supervised/Pseudolabeled Pretraining for Molecules
+.. rubric:: Pretraining with Supervised/Pseudolabeled Data
 .. autoclass:: torch_molecule.encoder.supervised.modeling_supervised.SupervisedMolecularEncoder
    :members: fit, encode
    :exclude-members: fitting_epoch, fitting_loss, model_name, model_class