fix docs

src/transformers/configuration_reformer.py

@@ -64,11 +64,6 @@ class ReformerConfig(PretrainedConfig):
                 A chunk size of 0 means that the feed forward layer is not chunked.
                 A chunk size of n means that the feed forward layer processes n < sequence_length embeddings at a time.
                 For more information on feed forward chunking, see `How does Feed Forward Chunking work? <../glossary.html#feed-forward-chunking>`__ .
-            chunk_size_feed_forward (:obj:`int`, optional, defaults to 0):
-                The chunk size of all feed forward layers in the residual attention blocks.
-                A chunk size of 0 means that the feed forward layer is not chunked.
-                A chunk size of n means that the feed forward layer processes n < sequence_length embeddings at a time.
-                For more information on feed forward chunking, see `How does Feed Forward Chunking work? <../glossary.html#feed-forward-chunking>`__ .
             eos_token_id (:obj:`int`, optional, defaults to 2):
                 The token id for the <EOS> token.
             feed_forward_size (:obj:`int`, optional, defaults to 512):
@@ -147,7 +142,6 @@ def __init__(
         axial_pos_shape=[64, 64],
         axial_pos_embds_dim=[64, 192],
         chunk_size_lm_head=0,
-        chunk_size_feed_forward=0,
         eos_token_id=2,
         feed_forward_size=512,
         hash_seed=None,
@@ -202,5 +196,4 @@ def __init__(
         self.axial_pos_embds_dim = tuple(axial_pos_embds_dim)
         self.axial_norm_std = axial_norm_std
         self.chunk_size_lm_head = chunk_size_lm_head
-        self.chunk_size_feed_forward = chunk_size_feed_forward
         self.attn_layers = attn_layers

src/transformers/configuration_utils.py

@@ -64,6 +64,11 @@ class PretrainedConfig(object):
                 2.
             xla_device (:obj:`bool`, `optional`):
                 A flag to indicate if TPU are available or not.
+            chunk_size_feed_forward (:obj:`int`, `optional`, defaults to :obj:`0`):
+                The chunk size of all feed forward layers in the residual attention blocks.
+                A chunk size of :obj:`0` means that the feed forward layer is not chunked.
+                A chunk size of n means that the feed forward layer processes :obj:`n` < sequence_length embeddings at a time.
+                For more information on feed forward chunking, see `How does Feed Forward Chunking work? <../glossary.html#feed-forward-chunking>`__ .
 
         Parameters for sequence generation
             - **max_length** (:obj:`int`, `optional`, defaults to 20) -- Maximum length that will be used by

tests/test_modeling_common.py

@@ -530,19 +530,15 @@ def test_feed_forward_chunking(self):
             config = copy.deepcopy(original_config)
             model = model_class(config)
             model.to(torch_device)
-
-            if self.model_tester.is_training is False:
-                model.eval()
+            model.eval()
 
             hidden_states_no_chunk = model(**self._prepare_for_class(inputs_dict, model_class))[0]
 
             torch.manual_seed(0)
             config.chunk_size_feed_forward = 1
             model = model_class(config)
             model.to(torch_device)
-
-            if self.model_tester.is_training is False:
-                model.eval()
+            model.eval()
 
             hidden_states_with_chunk = model(**self._prepare_for_class(inputs_dict, model_class))[0]
             self.assertTrue(torch.allclose(hidden_states_no_chunk, hidden_states_with_chunk, atol=1e-3))