Merge pull request #2164 from huggingface/cleanup-configs

[SMALL BREAKING CHANGE] Cleaning up configuration classes - Adding Model Cards

transformers/tests/modeling_roberta_test.py

@@ -106,7 +106,7 @@ class RobertaModelTest(CommonTestCases.CommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = RobertaConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 hidden_size=self.hidden_size,
                 num_hidden_layers=self.num_hidden_layers,
                 num_attention_heads=self.num_attention_heads,

transformers/tests/modeling_t5_test.py

@@ -93,7 +93,7 @@ class T5ModelTest(CommonTestCases.CommonModelTester):
                 decoder_lm_labels = ids_tensor([self.batch_size, self.decoder_seq_length], self.vocab_size)
 
             config = T5Config(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 n_positions=self.n_positions,
                 d_model=self.hidden_size,
                 d_ff=self.d_ff,

transformers/tests/modeling_tf_albert_test.py

@@ -118,7 +118,7 @@ class TFAlbertModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = AlbertConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 hidden_size=self.hidden_size,
                 num_hidden_layers=self.num_hidden_layers,
                 num_attention_heads=self.num_attention_heads,

transformers/tests/modeling_tf_bert_test.py

@@ -114,7 +114,7 @@ class TFBertModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = BertConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 hidden_size=self.hidden_size,
                 num_hidden_layers=self.num_hidden_layers,
                 num_attention_heads=self.num_attention_heads,

transformers/tests/modeling_tf_ctrl_test.py

@@ -112,7 +112,7 @@ class TFCTRLModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = CTRLConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 n_embd=self.hidden_size,
                 n_layer=self.num_hidden_layers,
                 n_head=self.num_attention_heads,

transformers/tests/modeling_tf_distilbert_test.py

@@ -107,7 +107,7 @@ class TFDistilBertModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = DistilBertConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 dim=self.hidden_size,
                 n_layers=self.num_hidden_layers,
                 n_heads=self.num_attention_heads,

transformers/tests/modeling_tf_gpt2_test.py

@@ -115,7 +115,7 @@ class TFGPT2ModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = GPT2Config(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 n_embd=self.hidden_size,
                 n_layer=self.num_hidden_layers,
                 n_head=self.num_attention_heads,

transformers/tests/modeling_tf_openai_gpt_test.py

@@ -114,7 +114,7 @@ class TFOpenAIGPTModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = OpenAIGPTConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 n_embd=self.hidden_size,
                 n_layer=self.num_hidden_layers,
                 n_head=self.num_attention_heads,

transformers/tests/modeling_tf_roberta_test.py

@@ -109,7 +109,7 @@ class TFRobertaModelTest(TFCommonTestCases.TFCommonModelTester):
                 choice_labels = ids_tensor([self.batch_size], self.num_choices)
 
             config = RobertaConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 hidden_size=self.hidden_size,
                 num_hidden_layers=self.num_hidden_layers,
                 num_attention_heads=self.num_attention_heads,

transformers/tests/modeling_tf_t5_test.py

@@ -87,7 +87,7 @@ class TFT5ModelTest(TFCommonTestCases.TFCommonModelTester):
                 token_labels = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
 
             config = T5Config(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 n_positions=self.n_positions,
                 d_model=self.hidden_size,
                 d_ff=self.d_ff,

transformers/tests/modeling_tf_transfo_xl_test.py

@@ -92,7 +92,7 @@ class TFTransfoXLModelTest(TFCommonTestCases.TFCommonModelTester):
                 lm_labels = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
 
             config = TransfoXLConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 mem_len=self.mem_len,
                 clamp_len=self.clamp_len,
                 cutoffs=self.cutoffs,

transformers/tests/modeling_tf_xlm_test.py

@@ -125,7 +125,7 @@ class TFXLMModelTest(TFCommonTestCases.TFCommonModelTester):
                 is_impossible_labels = ids_tensor([self.batch_size], 2, dtype=tf.float32)
 
             config = XLMConfig(
-                 vocab_size_or_config_json_file=self.vocab_size,
+                 vocab_size=self.vocab_size,
                  n_special=self.n_special,
                  emb_dim=self.hidden_size,
                  n_layers=self.num_hidden_layers,

transformers/tests/modeling_tf_xlnet_test.py

@@ -64,7 +64,6 @@ class TFXLNetModelTest(TFCommonTestCases.TFCommonModelTester):
                      num_attention_heads=4,
                      d_inner=128,
                      num_hidden_layers=5,
-                     max_position_embeddings=10,
                      type_sequence_label_size=2,
                      untie_r=True,
                      bi_data=False,
@@ -88,7 +87,6 @@ class TFXLNetModelTest(TFCommonTestCases.TFCommonModelTester):
             self.num_attention_heads = num_attention_heads
             self.d_inner = d_inner
             self.num_hidden_layers = num_hidden_layers
-            self.max_position_embeddings = max_position_embeddings
             self.bi_data = bi_data
             self.untie_r = untie_r
             self.same_length = same_length
@@ -122,13 +120,12 @@ class TFXLNetModelTest(TFCommonTestCases.TFCommonModelTester):
                 is_impossible_labels = ids_tensor([self.batch_size], 2, dtype=tf.float32)
 
             config = XLNetConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 d_model=self.hidden_size,
                 n_head=self.num_attention_heads,
                 d_inner=self.d_inner,
                 n_layer=self.num_hidden_layers,
                 untie_r=self.untie_r,
-                max_position_embeddings=self.max_position_embeddings,
                 mem_len=self.mem_len,
                 clamp_len=self.clamp_len,
                 same_length=self.same_length,

transformers/tests/modeling_transfo_xl_test.py

@@ -91,7 +91,7 @@ class TransfoXLModelTest(CommonTestCases.CommonModelTester):
                 lm_labels = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
 
             config = TransfoXLConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 mem_len=self.mem_len,
                 clamp_len=self.clamp_len,
                 cutoffs=self.cutoffs,

transformers/tests/modeling_xlm_test.py

@@ -121,7 +121,7 @@ class XLMModelTest(CommonTestCases.CommonModelTester):
                 is_impossible_labels = ids_tensor([self.batch_size], 2).float()
 
             config = XLMConfig(
-                 vocab_size_or_config_json_file=self.vocab_size,
+                 vocab_size=self.vocab_size,
                  n_special=self.n_special,
                  emb_dim=self.hidden_size,
                  n_layers=self.num_hidden_layers,

transformers/tests/modeling_xlnet_test.py

@@ -60,7 +60,6 @@ class XLNetModelTest(CommonTestCases.CommonModelTester):
                      num_attention_heads=4,
                      d_inner=128,
                      num_hidden_layers=5,
-                     max_position_embeddings=10,
                      type_sequence_label_size=2,
                      untie_r=True,
                      bi_data=False,
@@ -84,7 +83,6 @@ class XLNetModelTest(CommonTestCases.CommonModelTester):
             self.num_attention_heads = num_attention_heads
             self.d_inner = d_inner
             self.num_hidden_layers = num_hidden_layers
-            self.max_position_embeddings = max_position_embeddings
             self.bi_data = bi_data
             self.untie_r = untie_r
             self.same_length = same_length
@@ -116,13 +114,12 @@ class XLNetModelTest(CommonTestCases.CommonModelTester):
                 token_labels = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size)
 
             config = XLNetConfig(
-                vocab_size_or_config_json_file=self.vocab_size,
+                vocab_size=self.vocab_size,
                 d_model=self.hidden_size,
                 n_head=self.num_attention_heads,
                 d_inner=self.d_inner,
                 n_layer=self.num_hidden_layers,
                 untie_r=self.untie_r,
-                max_position_embeddings=self.max_position_embeddings,
                 mem_len=self.mem_len,
                 clamp_len=self.clamp_len,
                 same_length=self.same_length,