remove duplicate model definition of tok2vec layer

examples/experiments/onto-joint/pretrain.cfg

@@ -53,17 +53,7 @@ n_save_every = null
 batch_size = 3000
 seed = ${training:seed}
 use_pytorch_for_gpu_memory = ${training:use_pytorch_for_gpu_memory}
-
+tok2vec_model = "nlp.pipeline.tok2vec.model"
-[pretraining.model]
-@architectures = "spacy.HashEmbedCNN.v1"
-pretrained_vectors = ${nlp:vectors}
-width = 256
-depth = 6
-window_size = 1
-embed_size = 2000
-maxout_pieces = 3
-subword_features = true
-dropout = null
 
 [pretraining.optimizer]
 @optimizers = "Adam.v1"

spacy/cli/pretrain.py

@@ -109,7 +109,10 @@ def pretrain(
     with msg.loading(f"Loading model '{vectors_model}'..."):
         nlp = util.load_model(vectors_model)
     msg.good(f"Loaded model '{vectors_model}'")
-    tok2vec = pretrain_config["model"]
+    tok2vec_path = pretrain_config["tok2vec_model"]
+    tok2vec = config
+    for subpath in tok2vec_path.split("."):
+        tok2vec = tok2vec.get(subpath)
     model = create_pretraining_model(nlp, tok2vec)
     optimizer = pretrain_config["optimizer"]
 

spacy/ml/models/multi_task.py

@@ -102,4 +102,4 @@ def _replace_word(word, random_words, mask="[MASK]"):
     elif roll < 0.9:
         return random_words.next()
     else:
-        return word
+        return word