Fix imports in conversion scripts (#9674)

src/transformers/models/prophetnet/convert_prophetnet_original_pytorch_checkpoint_to_pytorch.py

@@ -19,6 +19,8 @@ import argparse
 
 import torch
 
+from transformers import ProphetNetForConditionalGeneration, XLMProphetNetForConditionalGeneration, logging
+
 # transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
 # original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
 from transformers_old.modeling_prophetnet import (
@@ -28,8 +30,6 @@ from transformers_old.modeling_xlm_prophetnet import (
     XLMProphetNetForConditionalGeneration as XLMProphetNetForConditionalGenerationOld,
 )
 
-from . import ProphetNetForConditionalGeneration, XLMProphetNetForConditionalGeneration, logging
-
 
 logger = logging.get_logger(__name__)
 logging.set_verbosity_info()

src/transformers/models/reformer/convert_reformer_trax_checkpoint_to_pytorch.py

@@ -21,8 +21,8 @@ import pickle
 import numpy as np
 import torch
 
-from ...utils import logging
-from . import ReformerConfig, ReformerModelWithLMHead
+from transformers import ReformerConfig, ReformerModelWithLMHead
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/roberta/convert_roberta_original_pytorch_checkpoint_to_pytorch.py

@@ -24,9 +24,15 @@ from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
 from fairseq.modules import TransformerSentenceEncoderLayer
 from packaging import version
 
-from ...models.bert.modeling_bert import BertIntermediate, BertLayer, BertOutput, BertSelfAttention, BertSelfOutput
-from ...utils import logging
-from .modeling_roberta import RobertaConfig, RobertaForMaskedLM, RobertaForSequenceClassification
+from transformers import RobertaConfig, RobertaForMaskedLM, RobertaForSequenceClassification
+from transformers.models.bert.modeling_bert import (
+    BertIntermediate,
+    BertLayer,
+    BertOutput,
+    BertSelfAttention,
+    BertSelfOutput,
+)
+from transformers.utils import logging
 
 
 if version.parse(fairseq.__version__) < version.parse("0.9.0"):

src/transformers/models/t5/convert_t5_original_tf_checkpoint_to_pytorch.py

@@ -17,8 +17,8 @@
 
 import argparse
 
-from ...utils import logging
-from . import T5Config, T5ForConditionalGeneration, load_tf_weights_in_t5
+from transformers import T5Config, T5ForConditionalGeneration, load_tf_weights_in_t5
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/tapas/convert_tapas_original_tf_checkpoint_to_pytorch.py

@@ -17,8 +17,7 @@
 
 import argparse
 
-from ...utils import logging
-from . import (
+from transformers import (
     TapasConfig,
     TapasForMaskedLM,
     TapasForQuestionAnswering,
@@ -27,6 +26,7 @@ from . import (
     TapasTokenizer,
     load_tf_weights_in_tapas,
 )
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/transfo_xl/convert_transfo_xl_original_tf_checkpoint_to_pytorch.py

@@ -22,11 +22,11 @@ import sys
 
 import torch
 
-from ...file_utils import CONFIG_NAME, WEIGHTS_NAME
-from ...utils import logging
-from . import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
-from . import tokenization_transfo_xl as data_utils
-from .tokenization_transfo_xl import CORPUS_NAME, VOCAB_FILES_NAMES
+from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
+from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
+from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
+from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS_NAME, VOCAB_FILES_NAMES
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/xlm/convert_xlm_original_pytorch_checkpoint_to_pytorch.py

@@ -21,9 +21,9 @@ import json
 import numpy
 import torch
 
-from ...file_utils import CONFIG_NAME, WEIGHTS_NAME
-from ...utils import logging
-from .tokenization_xlm import VOCAB_FILES_NAMES
+from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
+from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/xlnet/convert_xlnet_original_tf_checkpoint_to_pytorch.py

@@ -20,15 +20,15 @@ import os
 
 import torch
 
-from ...file_utils import CONFIG_NAME, WEIGHTS_NAME
-from ...utils import logging
-from . import (
+from transformers import (
     XLNetConfig,
     XLNetForQuestionAnswering,
     XLNetForSequenceClassification,
     XLNetLMHeadModel,
     load_tf_weights_in_xlnet,
 )
+from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
+from transformers.utils import logging
 
 
 GLUE_TASKS_NUM_LABELS = {