deploy: 44946c2

_modules/dicee/evaluator.html

@@ -151,6 +151,16 @@ <h1>Source code for dicee.evaluator</h1><div class="highlight"><pre>
         <span class="k">else</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">ee_vocab</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">ee_vocab</span><span class="o">.</span><span class="n">result</span><span class="p">()</span>
 
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        if isinstance(dataset.constraints, tuple):</span>
+<span class="sd">            self.domain_constraints_per_rel, self.range_constraints_per_rel = dataset.constraints</span>
+<span class="sd">        else:</span>
+<span class="sd">            try:</span>
+<span class="sd">                self.domain_constraints_per_rel, self.range_constraints_per_rel = dataset.constraints.result()</span>
+<span class="sd">            except RuntimeError:</span>
+<span class="sd">                print(&#39;Domain constraint exception occurred&#39;)</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+
         <span class="bp">self</span><span class="o">.</span><span class="n">num_entities</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">num_entities</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">num_relations</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">num_relations</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">func_triple_to_bpe_representation</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">func_triple_to_bpe_representation</span>

_modules/dicee/static_funcs_training.html

@@ -102,13 +102,11 @@ <h1>Source code for dicee.static_funcs_training</h1><div class="highlight"><pre>
         <span class="k">return</span> <span class="n">iterable_object</span></div>
 
 
-
 <div class="viewcode-block" id="evaluate_lp">
 <a class="viewcode-back" href="../../autoapi/dicee/static_funcs_training/index.html#dicee.static_funcs_training.evaluate_lp">[docs]</a>
-<span class="k">def</span> <span class="nf">evaluate_lp</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">triple_idx</span><span class="p">,</span> <span class="n">num_entities</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span>
-                <span class="n">er_vocab</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Tuple</span><span class="p">,</span> <span class="n">List</span><span class="p">],</span>
-                <span class="n">re_vocab</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Tuple</span><span class="p">,</span> <span class="n">List</span><span class="p">],</span>
-                <span class="n">info</span><span class="o">=</span><span class="s1">&#39;Eval Starts&#39;</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">,</span> <span class="n">chunk_size</span><span class="o">=</span><span class="mi">1024</span><span class="p">):</span>
+<span class="nd">@torch</span><span class="o">.</span><span class="n">no_grad</span><span class="p">()</span>
+<span class="k">def</span> <span class="nf">evaluate_lp</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">triple_idx</span><span class="p">,</span> <span class="n">num_entities</span><span class="p">,</span> <span class="n">er_vocab</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Tuple</span><span class="p">,</span> <span class="n">List</span><span class="p">],</span> <span class="n">re_vocab</span><span class="p">:</span> <span class="n">Dict</span><span class="p">[</span><span class="n">Tuple</span><span class="p">,</span> <span class="n">List</span><span class="p">],</span>
+                <span class="n">info</span><span class="o">=</span><span class="s1">&#39;Eval Starts&#39;</span><span class="p">,</span> <span class="n">batch_size</span><span class="o">=</span><span class="mi">128</span><span class="p">,</span> <span class="n">chunk_size</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Evaluate model in a standard link prediction task</span>
 
@@ -117,9 +115,6 @@ <h1>Source code for dicee.static_funcs_training</h1><div class="highlight"><pre>
 <span class="sd">    the filtered missing tail entity rank</span>
 <span class="sd">    :param model:</span>
 <span class="sd">    :param triple_idx:</span>
-<span class="sd">    :param num_entities:</span>
-<span class="sd">    :param er_vocab:</span>
-<span class="sd">    :param re_vocab:</span>
 <span class="sd">    :param info:</span>
 <span class="sd">    :param batch_size:</span>
 <span class="sd">    :param chunk_size:</span>
@@ -227,7 +222,7 @@ <h1>Source code for dicee.static_funcs_training</h1><div class="highlight"><pre>
             <span class="p">),</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
 
             <span class="c1"># Predict scores for missing tails</span>
-            <span class="n">preds_tails</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">x_tails</span><span class="p">)</span>
+            <span class="n">preds_tails</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward_triples</span><span class="p">(</span><span class="n">x_tails</span><span class="p">)</span>
             <span class="n">preds_tails</span> <span class="o">=</span> <span class="n">preds_tails</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">batch_size_current</span><span class="p">,</span> <span class="n">chunk_size_current</span><span class="p">)</span>
             <span class="n">predictions_tails</span><span class="p">[:,</span> <span class="n">chunk_start</span><span class="p">:</span><span class="n">chunk_end</span><span class="p">]</span> <span class="o">=</span> <span class="n">preds_tails</span>
             <span class="k">del</span> <span class="n">x_tails</span>
@@ -240,7 +235,7 @@ <h1>Source code for dicee.static_funcs_training</h1><div class="highlight"><pre>
             <span class="p">),</span> <span class="n">dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
 
             <span class="c1"># Predict scores for missing heads</span>
-            <span class="n">preds_heads</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="n">x_heads</span><span class="p">)</span>
+            <span class="n">preds_heads</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forward_triples</span><span class="p">(</span><span class="n">x_heads</span><span class="p">)</span>
             <span class="n">preds_heads</span> <span class="o">=</span> <span class="n">preds_heads</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="n">batch_size_current</span><span class="p">,</span> <span class="n">chunk_size_current</span><span class="p">)</span>
             <span class="n">predictions_heads</span><span class="p">[:,</span> <span class="n">chunk_start</span><span class="p">:</span><span class="n">chunk_end</span><span class="p">]</span> <span class="o">=</span> <span class="n">preds_heads</span>
             <span class="k">del</span> <span class="n">x_heads</span>

_modules/dicee/trainer/model_parallelism.html

@@ -275,7 +275,7 @@ <h1>Source code for dicee.trainer.model_parallelism</h1><div class="highlight"><
                                                             <span class="n">persistent_workers</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
             <span class="k">if</span> <span class="n">batch_rt</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
                 <span class="n">expected_training_time</span><span class="o">=</span><span class="n">batch_rt</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_dataloader</span><span class="p">)</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">attributes</span><span class="o">.</span><span class="n">num_epochs</span>
-                <span class="c1"># print(f&quot;Exp.Training Runtime: {expected_training_time/60 :.3f} in mins\t|\tBatch Size:{batch_size}\t|\tBatch RT:{batch_rt:.3f}\t|\t # of batches:{len(train_dataloader)}\t|\t# of epochs:{self.attributes.num_epochs}&quot;)</span>
+                <span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;Exp.Training Runtime: </span><span class="si">{</span><span class="n">expected_training_time</span><span class="o">/</span><span class="mi">60</span><span class="w"> </span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> in mins</span><span class="se">\t</span><span class="s2">|</span><span class="se">\t</span><span class="s2">Batch Size:</span><span class="si">{</span><span class="n">batch_size</span><span class="si">}</span><span class="se">\t</span><span class="s2">|</span><span class="se">\t</span><span class="s2">Batch RT:</span><span class="si">{</span><span class="n">batch_rt</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="se">\t</span><span class="s2">|</span><span class="se">\t</span><span class="s2"> # of batches:</span><span class="si">{</span><span class="nb">len</span><span class="p">(</span><span class="n">train_dataloader</span><span class="p">)</span><span class="si">}</span><span class="se">\t</span><span class="s2">|</span><span class="se">\t</span><span class="s2"># of epochs:</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">attributes</span><span class="o">.</span><span class="n">num_epochs</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
 
         <span class="c1"># () Number of batches to reach a single epoch.</span>
         <span class="n">num_of_batches</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">train_dataloader</span><span class="p">)</span>

_sources/autoapi/dicee/abstracts/index.rst.txt

@@ -153,9 +153,13 @@ Module Contents
 
 
    .. py:attribute:: construct_ensemble
+      :value: False
+
 
 
    .. py:attribute:: apply_semantic_constraint
+      :value: False
+
 
 
    .. py:attribute:: configs

_sources/autoapi/dicee/callbacks/index.rst.txt

@@ -296,6 +296,8 @@ Module Contents
 
 
    .. py:attribute:: val_aswa
+      :value: -1
+
 
 
    .. py:method:: on_fit_end(trainer, model)
@@ -367,6 +369,8 @@ Module Contents
 
 
    .. py:attribute:: epoch_ratio
+      :value: None
+
 
 
    .. py:attribute:: epoch_counter
@@ -499,18 +503,28 @@ Module Contents
 
 
    .. py:attribute:: level
+      :value: 'input'
+
 
 
    .. py:attribute:: ratio
+      :value: 0.0
+
 
 
    .. py:attribute:: method
+      :value: None
+
 
 
    .. py:attribute:: scaler
+      :value: None
+
 
 
    .. py:attribute:: frequency
+      :value: None
+
 
 
    .. py:method:: on_train_batch_start(trainer, model, batch, batch_idx)

_sources/autoapi/dicee/dataset_classes/index.rst.txt

@@ -157,6 +157,8 @@ Module Contents
 
 
    .. py:attribute:: block_size
+      :value: 8
+
 
 
    .. py:attribute:: num_of_data_points
@@ -414,6 +416,8 @@ Module Contents
 
 
    .. py:attribute:: neg_sample_ratio
+      :value: None
+
 
 
    .. py:attribute:: label_smoothing_rate
@@ -494,6 +498,8 @@ Module Contents
 
 
    .. py:attribute:: neg_ratio
+      :value: None
+
 
 
    .. py:attribute:: num_entities

_sources/autoapi/dicee/evaluator/index.rst.txt

@@ -45,6 +45,8 @@ Module Contents
 
 
    .. py:attribute:: is_continual_training
+      :value: None
+
 
 
    .. py:attribute:: num_entities

_sources/autoapi/dicee/executer/index.rst.txt

@@ -29,6 +29,8 @@ Module Contents
 
 
    .. py:attribute:: is_continual_training
+      :value: False
+
 
 
    .. py:attribute:: trainer

_sources/autoapi/dicee/index.rst.txt

@@ -763,6 +763,8 @@ Package Contents
 
 
    .. py:attribute:: num_ent
+      :value: None
+
 
 
    .. py:method:: kvsall_score(e_1_h, e_2_h, e_3_h, e_4_h, e_5_h, e_6_h, e_7_h, e_8_h, e_1_t, e_2_t, e_3_t, e_4_t, e_5_t, e_6_t, e_7_t, e_8_t, r_1, r_2, r_3, r_4, r_5, r_6, r_7, r_8) -> torch.tensor
@@ -2226,6 +2228,8 @@ Package Contents
 
 
    .. py:attribute:: evaluator
+      :value: None
+
 
 
    .. py:attribute:: form_of_labelling
@@ -2593,6 +2597,8 @@ Package Contents
 
 
    .. py:attribute:: is_continual_training
+      :value: False
+
 
 
    .. py:attribute:: trainer
@@ -2822,6 +2828,8 @@ Package Contents
 
 
    .. py:attribute:: block_size
+      :value: 8
+
 
 
    .. py:attribute:: num_of_data_points
@@ -3079,6 +3087,8 @@ Package Contents
 
 
    .. py:attribute:: neg_sample_ratio
+      :value: None
+
 
 
    .. py:attribute:: label_smoothing_rate
@@ -3159,6 +3169,8 @@ Package Contents
 
 
    .. py:attribute:: neg_ratio
+      :value: None
+
 
 
    .. py:attribute:: num_entities
@@ -3501,12 +3513,18 @@ Package Contents
 
 
    .. py:attribute:: gen_valid
+      :value: False
+
 
 
    .. py:attribute:: gen_test
+      :value: True
+
 
 
    .. py:attribute:: seed
+      :value: 1
+
 
 
    .. py:attribute:: max_ans_num
@@ -3518,10 +3536,14 @@ Package Contents
 
 
    .. py:attribute:: ent2id
+      :value: None
+
 
 
    .. py:attribute:: rel2id
       :type:  Dict
+      :value: None
+
 
 
    .. py:attribute:: ent_in

_sources/autoapi/dicee/knowledge_graph/index.rst.txt

@@ -21,15 +21,23 @@ Module Contents
 
 
    .. py:attribute:: dataset_dir
+      :value: None
+
 
 
    .. py:attribute:: sparql_endpoint
+      :value: None
+
 
 
    .. py:attribute:: path_single_kg
+      :value: None
+
 
 
    .. py:attribute:: byte_pair_encoding
+      :value: False
+
 
 
    .. py:attribute:: ordered_shaped_bpe_tokens
@@ -38,6 +46,8 @@ Module Contents
 
 
    .. py:attribute:: add_noise_rate
+      :value: None
+
 
 
    .. py:attribute:: num_entities
@@ -51,33 +61,53 @@ Module Contents
 
 
    .. py:attribute:: path_for_deserialization
+      :value: None
+
 
 
    .. py:attribute:: add_reciprocal
+      :value: None
+
 
 
    .. py:attribute:: eval_model
+      :value: None
+
 
 
    .. py:attribute:: read_only_few
+      :value: None
+
 
 
    .. py:attribute:: sample_triples_ratio
+      :value: None
+
 
 
    .. py:attribute:: path_for_serialization
+      :value: None
+
 
 
    .. py:attribute:: entity_to_idx
+      :value: None
+
 
 
    .. py:attribute:: relation_to_idx
+      :value: None
+
 
 
    .. py:attribute:: backend
+      :value: 'pandas'
+
 
 
    .. py:attribute:: training_technique
+      :value: None
+
 
 
    .. py:attribute:: idx_entity_to_bpe_shaped
@@ -95,6 +125,8 @@ Module Contents
 
 
    .. py:attribute:: padding
+      :value: False
+
 
 
    .. py:attribute:: dummy_id
@@ -126,6 +158,8 @@ Module Contents
 
 
    .. py:attribute:: separator
+      :value: None
+
 
 
    .. py:attribute:: description_of_input

_sources/autoapi/dicee/models/base_model/index.rst.txt

@@ -631,6 +631,8 @@ Module Contents
 
 
    .. py:attribute:: args
+      :value: None
+
 
 
    .. py:method:: __call__(x)

_sources/autoapi/dicee/models/dualE/index.rst.txt

@@ -35,6 +35,8 @@ Module Contents
 
 
    .. py:attribute:: num_ent
+      :value: None
+
 
 
    .. py:method:: kvsall_score(e_1_h, e_2_h, e_3_h, e_4_h, e_5_h, e_6_h, e_7_h, e_8_h, e_1_t, e_2_t, e_3_t, e_4_t, e_5_t, e_6_t, e_7_t, e_8_t, r_1, r_2, r_3, r_4, r_5, r_6, r_7, r_8) -> torch.tensor