deploy: SimplexLab/TorchJD@1443dcd

Author: ValerianRey

latest/_sources/examples/monitoring.rst.txt

@@ -29,7 +29,7 @@ they have a negative inner product).
         """Prints the extracted weights."""
         print(f"Weights: {weights}")
 
-    def print_similarity_with_gd(_, inputs: torch.Tensor, aggregation: torch.Tensor) -> None:
+    def print_similarity_with_gd(_, inputs: tuple[torch.Tensor], aggregation: torch.Tensor) -> None:
         """Prints the cosine similarity between the aggregation and the average gradient."""
         matrix = inputs[0]
         gd_output = matrix.mean(dim=0)

latest/examples/monitoring/index.html

@@ -263,7 +263,7 @@ <h1>Monitoring aggregations<a class="headerlink" href="#monitoring-aggregations"
 </span><span class="hll"><span class="w">    </span><span class="sd">&quot;&quot;&quot;Prints the extracted weights.&quot;&quot;&quot;</span>
 </span><span class="hll">    <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Weights: </span><span class="si">{</span><span class="n">weights</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
 </span>
-<span class="hll"><span class="k">def</span><span class="w"> </span><span class="nf">print_similarity_with_gd</span><span class="p">(</span><span class="n">_</span><span class="p">,</span> <span class="n">inputs</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">aggregation</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="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
+<span class="hll"><span class="k">def</span><span class="w"> </span><span class="nf">print_similarity_with_gd</span><span class="p">(</span><span class="n">_</span><span class="p">,</span> <span class="n">inputs</span><span class="p">:</span> <span class="nb">tuple</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">aggregation</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="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
 </span><span class="hll"><span class="w">    </span><span class="sd">&quot;&quot;&quot;Prints the cosine similarity between the aggregation and the average gradient.&quot;&quot;&quot;</span>
 </span><span class="hll">    <span class="n">matrix</span> <span class="o">=</span> <span class="n">inputs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
 </span><span class="hll">    <span class="n">gd_output</span> <span class="o">=</span> <span class="n">matrix</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>