Update docs

docs/source/tutorial/advanced_optuna_configuration.rst

@@ -26,3 +26,92 @@ The example of `optuna.json <./config/optuna.json>`_ looks like:
       }
     }
   }
+
+
+Next, we have to add `optuna_pruner` to `epoch_callbacks`.
+
+- ``imdb_optuna_with_pruning.jsonnet``
+
+.. code-block:: text
+
+  local batch_size = 64;
+  local cuda_device = 0;
+  local num_epochs = 15;
+  local seed = 42;
+
+  local embedding_dim = std.parseInt(std.extVar('embedding_dim'));
+  local dropout = std.parseJson(std.extVar('dropout'));
+  local lr = std.parseJson(std.extVar('lr'));
+  local max_filter_size = std.parseInt(std.extVar('max_filter_size'));
+  local num_filters = std.parseInt(std.extVar('num_filters'));
+  local output_dim = std.parseInt(std.extVar('output_dim'));
+  local ngram_filter_sizes = std.range(2, max_filter_size);
+
+  {
+    numpy_seed: seed,
+    pytorch_seed: seed,
+    random_seed: seed,
+    dataset_reader: {
+      lazy: false,
+      type: 'text_classification_json',
+      tokenizer: {
+        type: 'spacy',
+      },
+      token_indexers: {
+        tokens: {
+          type: 'single_id',
+          lowercase_tokens: true,
+        },
+      },
+    },
+    train_data_path: 'https://s3-us-west-2.amazonaws.com/allennlp/datasets/imdb/train.jsonl',
+    validation_data_path: 'https://s3-us-west-2.amazonaws.com/allennlp/datasets/imdb/dev.jsonl',
+    model: {
+      type: 'basic_classifier',
+      text_field_embedder: {
+        token_embedders: {
+          tokens: {
+            embedding_dim: embedding_dim,
+          },
+        },
+      },
+      seq2vec_encoder: {
+        type: 'cnn',
+        embedding_dim: embedding_dim,
+        ngram_filter_sizes: ngram_filter_sizes,
+        num_filters: num_filters,
+        output_dim: output_dim,
+      },
+      dropout: dropout,
+    },
+    data_loader: {
+      shuffle: true,
+      batch_size: batch_size,
+    },
+    trainer: {
+      cuda_device: cuda_device,
+      epoch_callbacks: [
+        {
+          type: 'optuna_pruner',
+        }
+      ],
+      num_epochs: num_epochs,
+      optimizer: {
+        lr: lr,
+        type: 'sgd',
+      },
+      validation_metric: '+accuracy',
+    },
+  }
+
+
+Finally, you can run optimization with pruning:
+
+.. code-block:: bash
+
+    poetry run allennlp tune \
+        config/imdb_optuna_with_pruning.jsonnet \
+        config/hparams.json \
+        --optuna-param-path config/optuna.json \
+        --serialization-dir result/hpo \
+        --study-name test-with-pruning

docs/source/tutorial/index.rst

@@ -7,6 +7,6 @@ Tutorial
 
    allennlp_configuration
    optuna_search_space
-   advanced_optuna_configuration
    run_allennlp_optuna
+   advanced_optuna_configuration
    hyperparameter_optimization_at_scale

docs/source/tutorial/run_allennlp_optuna.rst

@@ -12,7 +12,6 @@ You can optimize hyperparameters by:
     poetry run allennlp tune \
         config/imdb_optuna.jsonnet \
         config/hparams.json \
-        --optuna-param-path config/optuna.json \
         --serialization-dir result \
         --study-name test