WIP: translation with prefix transforms

onmt/opts.py

@@ -1208,9 +1208,6 @@ def translate_opts(parser, dynamic=False):
         "Ex: {'feat_0': '../data.txt.feats0', 'feat_1': '../data.txt.feats1'}",
     )  # noqa: E501
     group.add('--tgt', '-tgt', help='True target sequence (optional)')
-    group.add(
-        '--tgt_prefix', '-tgt_prefix', action='store_true', help='Generate predictions using provided `-tgt` as prefix.'
-    )
     group.add(
         '--shard_size',
         '-shard_size',

onmt/transforms/misc.py

@@ -105,12 +105,17 @@ def apply(self, example, is_train=False, stats=None, **kwargs):
 
         Should provide `corpus_name` to get correspond prefix.
         """
-        corpus_name = kwargs.get('corpus_name', None)
-        if corpus_name is None:
-            raise ValueError('corpus_name is required.')
-        corpus_prefix = self.prefix_dict.get(corpus_name, None)
-        if corpus_prefix is None:
-            raise ValueError(f'prefix for {corpus_name} does not exist.')
+        if is_train:
+            corpus_name = kwargs.get('corpus_name', None)
+            if corpus_name is None:
+                raise ValueError('corpus_name is required.')
+            corpus_prefix = self.prefix_dict.get(corpus_name, None)
+            if corpus_prefix is None:
+                raise ValueError(f'prefix for {corpus_name} does not exist.')
+        else:
+            corpus_prefix = kwargs.get('corpus_prefix', None)
+            if corpus_name is None:
+                raise ValueError('corpus_prefix is required.')
         return self._prepend(example, corpus_prefix)
 
     def _repr_args(self):

onmt/translate/translator.py

@@ -350,8 +350,6 @@ def translate_dynamic(
         if batch_size is None:
             raise ValueError("batch_size must be set")
 
-        if self.tgt_prefix and tgt is None:
-            raise ValueError("Prefix should be feed to tgt if -tgt_prefix.")
         #
         # data_iter = InferenceDataIterator(src, tgt, src_feats, transform)
         #