Start to extract shared config for DP and EDP.

combo/config.graph.template.jsonnet

@@ -392,31 +392,7 @@ assert pretrained_tokens == null || pretrained_transformer_name == null: "Can't
             ],
         },
     }),
-    trainer: std.prune({
-        checkpointer: {
-            type: "finishing_only_checkpointer",
-        },
-        type: "gradient_descent_validate_n",
-        cuda_device: cuda_device,
-        grad_clipping: 5.0,
-        num_epochs: num_epochs,
-        optimizer: {
-            type: "adam",
-            lr: learning_rate,
-            betas: [0.9, 0.9],
-        },
-        patience: 1, # it will  be overwriten by callback
-        callbacks: [
-            { type: "transfer_patience" }
-            { type: "track_epoch_callback" },
-            if use_tensorboard then
-            { type: "tensorboard", should_log_parameter_statistics: false},
-        ],
-        learning_rate_scheduler: {
-            type: "combo_scheduler",
-        },
-        validation_metric: "+EM",
-    }),
+    trainer: shared_config.Trainer(cuda_device, num_epochs, learning_rate, use_tensorboard),
     random_seed: 8787,
     pytorch_seed: 8787,
     numpy_seed: 8787,

combo/config.shared.libsonnet

+{
+    local trainer(cuda_device, num_epochs, learning_rate, use_tensorboard) =
+        std.prune({
+            checkpointer: {
+                type: "finishing_only_checkpointer",
+            },
+            type: "gradient_descent_validate_n",
+            cuda_device: cuda_device,
+            grad_clipping: 5.0,
+            num_epochs: num_epochs,
+            optimizer: {
+                type: "adam",
+                lr: learning_rate,
+                betas: [0.9, 0.9],
+            },
+            patience: 1, # it will  be overwriten by callback
+            callbacks: [
+                { type: "transfer_patience" }
+                { type: "track_epoch_callback" },
+                if use_tensorboard then
+                { type: "tensorboard", should_log_parameter_statistics: false},
+            ],
+            learning_rate_scheduler: {
+                type: "combo_scheduler",
+            },
+            validation_metric: "+EM",
+        }),
+    Trainer: trainer
+}
\ No newline at end of file

combo/config.template.jsonnet

+local shared_config = import "config.shared.libsonnet";
 ########################################################################################
 #                                 BASIC configuration                                  #
 ########################################################################################
@@ -359,31 +360,7 @@ assert pretrained_tokens == null || pretrained_transformer_name == null: "Can't
             ],
         },
     }),
-    trainer: std.prune({
-        checkpointer: {
-            type: "finishing_only_checkpointer",
-        },
-        type: "gradient_descent_validate_n",
-        cuda_device: cuda_device,
-        grad_clipping: 5.0,
-        num_epochs: num_epochs,
-        optimizer: {
-            type: "adam",
-            lr: learning_rate,
-            betas: [0.9, 0.9],
-        },
-        patience: 1, # it will  be overwriten by callback
-        callbacks: [
-            { type: "transfer_patience" }
-            { type: "track_epoch_callback" },
-            if use_tensorboard then
-            { type: "tensorboard", should_log_parameter_statistics: false},
-        ],
-        learning_rate_scheduler: {
-            type: "combo_scheduler",
-        },
-        validation_metric: "+EM",
-    }),
+    trainer: shared_config.Trainer(cuda_device, num_epochs, learning_rate, use_tensorboard),
     random_seed: 8787,
     pytorch_seed: 8787,
     numpy_seed: 8787,