From 1c1616472367302e029350273a4c21c680cafd26 Mon Sep 17 00:00:00 2001
From: varisd <varis@ufal.mff.cuni.cz>
Date: Wed, 6 Feb 2019 19:08:32 +0100
Subject: [PATCH] fixing errors

---
 neuralmonkey/decoders/autoregressive.py      |  2 +-
 neuralmonkey/decoders/sequence_labeler.py    | 15 ++++++++-------
 neuralmonkey/readers/string_vector_reader.py |  2 +-
 tests/bert.ini                               |  1 -
 4 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/neuralmonkey/decoders/autoregressive.py b/neuralmonkey/decoders/autoregressive.py
index 5b39e4f43..3842e3eab 100644
--- a/neuralmonkey/decoders/autoregressive.py
+++ b/neuralmonkey/decoders/autoregressive.py
@@ -176,7 +176,7 @@ def embedding_size(self) -> int:
                      "size of the reused embeddings from the "
                      "`embeddings_source`.")
 
-        return self.embeddings_source.dimension
+        return self.embeddings_source.embedding_matrix.get_shape()[1].value
 
     @tensor
     def go_symbols(self) -> tf.Tensor:
diff --git a/neuralmonkey/decoders/sequence_labeler.py b/neuralmonkey/decoders/sequence_labeler.py
index 9d9931a1d..a5a11126a 100644
--- a/neuralmonkey/decoders/sequence_labeler.py
+++ b/neuralmonkey/decoders/sequence_labeler.py
@@ -23,7 +23,7 @@ def __init__(self,
                  name: str,
                  encoder: TemporalStateful,
                  data_id: str,
-                 vocabulary: Vocabulary,
+                 vocabulary: Vocabulary = None,
                  embeddings_source: EmbeddedSequence = None,
                  dropout_keep_prob: float = 1.0,
                  reuse: ModelPart = None,
@@ -34,19 +34,20 @@ def __init__(self,
         ModelPart.__init__(self, name, reuse, save_checkpoint, load_checkpoint,
                            initializers)
 
-        self.vocabulary = vocabulary
         self.embeddings_source = embeddings_source
         self.encoder = encoder
         self.data_id = data_id
         self.dropout_keep_prob = dropout_keep_prob
 
-        # We provide only embedding_source when we want to input and output
+        # We provide only embedding_source when we want to tie input and output
         # projections
-        if self.embeddings_source is not None and self.vocabulary is not None:
-            warn("Both `vocabulary` and `embedding_source` was provided. "
-                 "using `embedding_source.vocabulary` instead of provided "
-                 "`vocabulary`")
+        if (self.embeddings_source is None) == (vocabulary is None):
+            raise ValueError("You must specify either `vocabulary or` or "
+                             "`embeddings_source`, not both")
+        elif self.embeddings_source is not None:
             self.vocabulary = self.embeddings_source.vocabulary
+        elif vocabulary is not None:
+            self.vocabulary = vocabulary
     # pylint: enable=too-many-arguments
 
     @property
diff --git a/neuralmonkey/readers/string_vector_reader.py b/neuralmonkey/readers/string_vector_reader.py
index d6545b2a3..439a23838 100644
--- a/neuralmonkey/readers/string_vector_reader.py
+++ b/neuralmonkey/readers/string_vector_reader.py
@@ -13,7 +13,7 @@ def process_line(line: str, lineno: int, path: str) -> np.ndarray:
 
         return np.array(numbers, dtype=dtype)
 
-    def reader(files: List[str])-> Iterable[List[np.ndarray]]:
+    def reader(files: List[str]) -> Iterable[List[np.ndarray]]:
         for path in files:
             current_line = 0
 
diff --git a/tests/bert.ini b/tests/bert.ini
index 2b3e0b7cc..7c3a20c46 100644
--- a/tests/bert.ini
+++ b/tests/bert.ini
@@ -66,7 +66,6 @@ dropout_keep_prob=0.9
 class=decoders.sequence_labeler.SequenceLabeler
 name="labeler_bert"
 encoder=<encoder>
-vocabulary=<vocabulary>
 data_id="source_masked"
 dropout_keep_prob=0.5
 embeddings_source=<sequence>