Fix imports in conversion scripts (#9674)

src/transformers/models/albert/convert_albert_original_tf_checkpoint_to_pytorch.py

@@ -19,8 +19,8 @@ import argparse
 
 import torch
 
-from ...utils import logging
-from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
+from transformers import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py

@@ -23,9 +23,15 @@ import fairseq
 import torch
 from packaging import version
 
-from ...utils import logging
-from . import BartConfig, BartForConditionalGeneration, BartForSequenceClassification, BartModel, BartTokenizer
-from .modeling_bart import _make_linear_from_emb
+from transformers import (
+    BartConfig,
+    BartForConditionalGeneration,
+    BartForSequenceClassification,
+    BartModel,
+    BartTokenizer,
+)
+from transformers.models.bart.modeling_bart import _make_linear_from_emb
+from transformers.utils import logging
 
 
 FAIRSEQ_MODELS = ["bart.large", "bart.large.mnli", "bart.large.cnn", "bart_xsum/model.pt"]

src/transformers/models/bert/convert_bert_original_tf2_checkpoint_to_pytorch.py

@@ -28,8 +28,8 @@ import re
 import tensorflow as tf
 import torch
 
-from ...utils import logging
-from . import BertConfig, BertModel
+from transformers import BertConfig, BertModel
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/bert/convert_bert_original_tf_checkpoint_to_pytorch.py

@@ -19,8 +19,8 @@ import argparse
 
 import torch
 
-from ...utils import logging
-from . import BertConfig, BertForPreTraining, load_tf_weights_in_bert
+from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/bert/convert_bert_pytorch_checkpoint_to_original_tf.py

@@ -22,7 +22,7 @@ import numpy as np
 import tensorflow as tf
 import torch
 
-from . import BertModel
+from transformers import BertModel
 
 
 def convert_pytorch_checkpoint_to_tf(model: BertModel, ckpt_dir: str, model_name: str):

src/transformers/models/blenderbot/convert_blenderbot_original_pytorch_checkpoint_to_pytorch.py

@@ -18,8 +18,8 @@ import argparse
 
 import torch
 
-from ...models.bart import BartConfig, BartForConditionalGeneration
-from ...utils import logging
+from transformers import BartConfig, BartForConditionalGeneration
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/dialogpt/convert_dialogpt_original_pytorch_checkpoint_to_pytorch.py

@@ -17,7 +17,7 @@ import os
 
 import torch
 
-from ...file_utils import WEIGHTS_NAME
+from transformers.file_utils import WEIGHTS_NAME
 
 
 DIALOGPT_MODELS = ["small", "medium", "large"]

src/transformers/models/dpr/convert_dpr_original_checkpoint_to_pytorch.py

@@ -19,8 +19,7 @@ from pathlib import Path
 import torch
 from torch.serialization import default_restore_location
 
-from ...models.bert import BertConfig
-from . import DPRConfig, DPRContextEncoder, DPRQuestionEncoder, DPRReader
+from .transformers import BertConfig, DPRConfig, DPRContextEncoder, DPRQuestionEncoder, DPRReader
 
 
 CheckpointState = collections.namedtuple(

src/transformers/models/electra/convert_electra_original_tf_checkpoint_to_pytorch.py

@@ -19,8 +19,8 @@ import argparse
 
 import torch
 
-from ...utils import logging
-from . import ElectraConfig, ElectraForMaskedLM, ElectraForPreTraining, load_tf_weights_in_electra
+from transformers import ElectraConfig, ElectraForMaskedLM, ElectraForPreTraining, load_tf_weights_in_electra
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/fsmt/convert_fsmt_original_pytorch_checkpoint_to_pytorch.py

@@ -31,10 +31,11 @@ import torch
 from fairseq import hub_utils
 from fairseq.data.dictionary import Dictionary
 
-from ...file_utils import WEIGHTS_NAME
-from ...tokenization_utils_base import TOKENIZER_CONFIG_FILE
-from ...utils import logging
-from . import VOCAB_FILES_NAMES, FSMTConfig, FSMTForConditionalGeneration
+from transfomers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
+from transformers import FSMTConfig, FSMTForConditionalGeneration
+from transformers.file_utils import WEIGHTS_NAME
+from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
+from transformers.utils import logging
 
 
 logging.set_verbosity_warning()

src/transformers/models/funnel/__init__.py

@@ -23,6 +23,7 @@ from ...file_utils import _BaseLazyModule, is_tf_available, is_tokenizers_availa
 
 _import_structure = {
     "configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
+    "convert_funnel_original_tf_checkpoint_to_pytorch": [],
     "tokenization_funnel": ["FunnelTokenizer"],
 }
 

src/transformers/models/funnel/convert_funnel_original_tf_checkpoint_to_pytorch.py

@@ -16,14 +16,14 @@
 
 
 import argparse
-import logging
 
 import torch
 
-from . import FunnelConfig, FunnelForPreTraining, load_tf_weights_in_funnel
+from transformers import FunnelConfig, FunnelForPreTraining, load_tf_weights_in_funnel
+from transformers.utils import logging
 
 
-logging.basicConfig(level=logging.INFO)
+logging.set_verbosity_info()
 
 
 def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, config_file, pytorch_dump_path):

src/transformers/models/gpt2/convert_gpt2_original_tf_checkpoint_to_pytorch.py

@@ -19,9 +19,9 @@ import argparse
 
 import torch
 
-from ...file_utils import CONFIG_NAME, WEIGHTS_NAME
-from ...utils import logging
-from . import GPT2Config, GPT2Model, load_tf_weights_in_gpt2
+from transformers import GPT2Config, GPT2Model, load_tf_weights_in_gpt2
+from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/longformer/convert_longformer_original_pytorch_lightning_to_pytorch.py

@@ -20,7 +20,7 @@ import argparse
 import pytorch_lightning as pl
 import torch
 
-from . import LongformerForQuestionAnswering, LongformerModel
+from transformers import LongformerForQuestionAnswering, LongformerModel
 
 
 class LightningModel(pl.LightningModule):

src/transformers/models/lxmert/convert_lxmert_original_tf_checkpoint_to_pytorch.py

@@ -16,14 +16,14 @@
 
 
 import argparse
-import logging
 
 import torch
 
-from . import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
+from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
+from transformers.utils import logging
 
 
-logging.basicConfig(level=logging.INFO)
+logging.set_verbosity_info()
 
 
 def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, config_file, pytorch_dump_path):

src/transformers/models/marian/convert_marian_tatoeba_to_pytorch.py

@@ -17,7 +17,7 @@ import os
 from pathlib import Path
 from typing import List, Tuple
 
-from .convert_marian_to_pytorch import (
+from transformers.models.marian.convert_marian_to_pytorch import (
     FRONT_MATTER_TEMPLATE,
     _parse_readme,
     convert_all_sentencepiece_models,

src/transformers/models/marian/convert_marian_to_pytorch.py

@@ -26,8 +26,8 @@ import numpy as np
 import torch
 from tqdm import tqdm
 
-from ...hf_api import HfApi
-from . import MarianConfig, MarianMTModel, MarianTokenizer
+from transformers import MarianConfig, MarianMTModel, MarianTokenizer
+from transformers.hf_api import HfApi
 
 
 def remove_suffix(text: str, suffix: str):

src/transformers/models/mbart/convert_mbart_original_checkpoint_to_pytorch.py

@@ -16,9 +16,8 @@ import argparse
 
 import torch
 
-from ..bart import BartForConditionalGeneration
-from ..bart.convert_bart_original_pytorch_checkpoint_to_pytorch import remove_ignore_keys_
-from . import MBartConfig
+from transformers import BartForConditionalGeneration, MBartConfig
+from transformers.models.bart.convert_bart_original_pytorch_checkpoint_to_pytorch import remove_ignore_keys_
 
 
 def convert_fairseq_mbart_checkpoint_from_disk(checkpoint_path, hf_config_path="facebook/mbart-large-en-ro"):

src/transformers/models/mobilebert/convert_mobilebert_original_tf_checkpoint_to_pytorch.py

@@ -16,8 +16,8 @@ import argparse
 
 import torch
 
-from ...utils import logging
-from . import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
+from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
+from transformers.utils import logging
 
 
 logging.set_verbosity_info()

src/transformers/models/pegasus/convert_pegasus_tf_to_pytorch.py

@@ -22,8 +22,8 @@ import tensorflow as tf
 import torch
 from tqdm import tqdm
 
-from . import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
-from .configuration_pegasus import DEFAULTS, task_specific_params
+from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
+from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_params
 
 
 PATTERNS = [

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 = {