deploy: 25fc111

Author: liugangcode

_modules/index.html

@@ -272,6 +272,7 @@ <h1>All modules for which code is available</h1>
 <li><a href="torch_molecule/encoder/pretrained/modeling_pretrained.html">torch_molecule.encoder.pretrained.modeling_pretrained</a></li>
 <li><a href="torch_molecule/encoder/supervised/modeling_supervised.html">torch_molecule.encoder.supervised.modeling_supervised</a></li>
 <li><a href="torch_molecule/generator/digress/modeling_digress.html">torch_molecule.generator.digress.modeling_digress</a></li>
+<li><a href="torch_molecule/generator/gdss/modeling_gdss.html">torch_molecule.generator.gdss.modeling_gdss</a></li>
 <li><a href="torch_molecule/generator/graph_dit/modeling_graph_dit.html">torch_molecule.generator.graph_dit.modeling_graph_dit</a></li>
 <li><a href="torch_molecule/generator/graph_ga/modeling_graph_ga.html">torch_molecule.generator.graph_ga.modeling_graph_ga</a></li>
 <li><a href="torch_molecule/generator/graph_ga/oracle.html">torch_molecule.generator.graph_ga.oracle</a></li>

_modules/torch_molecule/generator/digress/modeling_digress.html

@@ -540,9 +540,9 @@ <h1>Source code for torch_molecule.generator.digress.modeling_digress</h1><div c
         <span class="bp">self</span><span class="o">.</span><span class="n">fitting_epoch</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">epochs</span><span class="p">):</span>
             <span class="n">train_losses</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_epoch</span><span class="p">(</span><span class="n">train_loader</span><span class="p">,</span> <span class="n">optimizer</span><span class="p">,</span> <span class="n">epoch</span><span class="p">)</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">fitting_loss</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">))</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">fitting_loss</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>
             <span class="k">if</span> <span class="n">scheduler</span><span class="p">:</span>
-                <span class="n">scheduler</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">))</span>
+                <span class="n">scheduler</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>
 
         <span class="bp">self</span><span class="o">.</span><span class="n">fitting_epoch</span> <span class="o">=</span> <span class="n">epoch</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">is_fitted_</span> <span class="o">=</span> <span class="kc">True</span>

_modules/torch_molecule/generator/gdss/modeling_gdss.html

@@ -286,8 +286,7 @@ <h1>Source code for torch_molecule.generator.graph_dit.modeling_graph_dit</h1><d
 
 <span class="sd">    References</span>
 <span class="sd">    ----------</span>
-<span class="sd">    - Graph Diffusion Transformers for Multi-Conditional Molecular Generation.</span>
-<span class="sd">      International Conference on Learning Representations (ICLR) 2024.</span>
+<span class="sd">    - Graph Diffusion Transformers for Multi-Conditional Molecular Generation. NeurIPS 2024.</span>
 <span class="sd">      https://openreview.net/forum?id=cfrDLD1wfO</span>
 <span class="sd">    - Implementation: https://github.com/liugangcode/Graph-DiT</span>
 
@@ -569,9 +568,9 @@ <h1>Source code for torch_molecule.generator.graph_dit.modeling_graph_dit</h1><d
         <span class="bp">self</span><span class="o">.</span><span class="n">fitting_epoch</span> <span class="o">=</span> <span class="mi">0</span>
         <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">epochs</span><span class="p">):</span>
             <span class="n">train_losses</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_train_epoch</span><span class="p">(</span><span class="n">train_loader</span><span class="p">,</span> <span class="n">optimizer</span><span class="p">,</span> <span class="n">epoch</span><span class="p">)</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">fitting_loss</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">))</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">fitting_loss</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>
             <span class="k">if</span> <span class="n">scheduler</span><span class="p">:</span>
-                <span class="n">scheduler</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">))</span>
+                <span class="n">scheduler</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">train_losses</span><span class="p">)</span><span class="o">.</span><span class="n">item</span><span class="p">())</span>
 
         <span class="bp">self</span><span class="o">.</span><span class="n">fitting_epoch</span> <span class="o">=</span> <span class="n">epoch</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">is_fitted_</span> <span class="o">=</span> <span class="kc">True</span>

_modules/torch_molecule/generator/graph_dit/modeling_graph_dit.html

@@ -44,12 +44,19 @@ Modeling Molecules as Graphs with GNN / Transformer-based Generators
    :undoc-members:
    :show-inheritance:
 
+.. rubric:: GDSS for score-based molecular generation
+.. autoclass:: torch_molecule.generator.gdss.modeling_gdss.GDSSMolecularGenerator
+   :exclude-members: fitting_epoch, fitting_loss, save_to_hf, load_from_hf
+   :members: fit, generate
+   :undoc-members:
+   :show-inheritance:
+
 Modeling Molecules as Graphs with Heuristic-based Generators
 ------------------------------------------------------------
 
 .. rubric:: Graph Genetic Algorithm for Un/Multi-conditional Molecular Generation
 .. autoclass:: torch_molecule.generator.graph_ga.modeling_graph_ga.GraphGAMolecularGenerator
-   :exclude-members: fitting_epoch, fitting_loss, push_to_huggingface, load_from_huggingface
+   :exclude-members: fitting_epoch, fitting_loss, save_to_hf, load_from_hf
    :members: fit, generate
    :undoc-members:
    :show-inheritance:

_sources/api/generator.rst.txt

@@ -7,8 +7,8 @@ Model Persistence
 ^^^^^^^^^^^^^^^^^
 - ``load_from_local``: Load a saved model from a local file
 - ``save_to_local``: Save the current model to a local file
-- ``load_from_huggingface``: Load a model from a Hugging Face repository
-- ``push_to_huggingface``: Push the current model to a Hugging Face repository
+- ``load_from_hf``: Load a model from a Hugging Face repository
+- ``save_to_hf``: Push the current model to a Hugging Face repository
 - ``load``: Load a model from either local storage or Hugging Face
 - ``save``: Save the model to either local storage or Hugging Face