From 7c2a32ff888da76b32db839711da2b128698a16c Mon Sep 17 00:00:00 2001 From: Julien Chaumond Date: Thu, 23 Apr 2020 10:43:22 -0400 Subject: [PATCH] [housekeeping] super() --- src/transformers/modeling_bert.py | 2 +- src/transformers/modeling_flaubert.py | 10 +++++----- src/transformers/modeling_tf_flaubert.py | 8 ++++---- 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/src/transformers/modeling_bert.py b/src/transformers/modeling_bert.py index 8c74ff7b59..0d800dd717 100644 --- a/src/transformers/modeling_bert.py +++ b/src/transformers/modeling_bert.py @@ -1347,7 +1347,7 @@ class BertForTokenClassification(BertPreTrainedModel): ) class BertForQuestionAnswering(BertPreTrainedModel): def __init__(self, config): - super(BertForQuestionAnswering, self).__init__(config) + super().__init__(config) self.num_labels = config.num_labels self.bert = BertModel(config) diff --git a/src/transformers/modeling_flaubert.py b/src/transformers/modeling_flaubert.py index 80da729521..481fff14e8 100644 --- a/src/transformers/modeling_flaubert.py +++ b/src/transformers/modeling_flaubert.py @@ -112,7 +112,7 @@ class FlaubertModel(XLMModel): pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config): # , dico, is_encoder, with_output): - super(FlaubertModel, self).__init__(config) + super().__init__(config) self.layerdrop = getattr(config, "layerdrop", 0.0) self.pre_norm = getattr(config, "pre_norm", False) @@ -307,7 +307,7 @@ class FlaubertWithLMHeadModel(XLMWithLMHeadModel): pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config): - super(FlaubertWithLMHeadModel, self).__init__(config) + super().__init__(config) self.transformer = FlaubertModel(config) self.init_weights() @@ -327,7 +327,7 @@ class FlaubertForSequenceClassification(XLMForSequenceClassification): pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config): - super(FlaubertForSequenceClassification, self).__init__(config) + super().__init__(config) self.transformer = FlaubertModel(config) self.init_weights() @@ -347,7 +347,7 @@ class FlaubertForQuestionAnsweringSimple(XLMForQuestionAnsweringSimple): pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config): - super(FlaubertForQuestionAnsweringSimple, self).__init__(config) + super().__init__(config) self.transformer = FlaubertModel(config) self.init_weights() @@ -367,6 +367,6 @@ class FlaubertForQuestionAnswering(XLMForQuestionAnswering): pretrained_model_archive_map = FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config): - super(FlaubertForQuestionAnswering, self).__init__(config) + super().__init__(config) self.transformer = FlaubertModel(config) self.init_weights() diff --git a/src/transformers/modeling_tf_flaubert.py b/src/transformers/modeling_tf_flaubert.py index 5e62e3d37b..8b0e263097 100644 --- a/src/transformers/modeling_tf_flaubert.py +++ b/src/transformers/modeling_tf_flaubert.py @@ -107,13 +107,13 @@ class TFFlaubertModel(TFXLMModel): pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config, *inputs, **kwargs): - super(TFFlaubertModel, self).__init__(config, *inputs, **kwargs) + super().__init__(config, *inputs, **kwargs) self.transformer = TFFlaubertMainLayer(config, name="transformer") class TFFlaubertMainLayer(TFXLMMainLayer): def __init__(self, config, *inputs, **kwargs): - super(TFFlaubertMainLayer, self).__init__(config, *inputs, **kwargs) + super().__init__(config, *inputs, **kwargs) self.layerdrop = getattr(config, "layerdrop", 0.0) self.pre_norm = getattr(config, "pre_norm", False) @@ -312,7 +312,7 @@ class TFFlaubertWithLMHeadModel(TFXLMWithLMHeadModel): pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config, *inputs, **kwargs): - super(TFFlaubertWithLMHeadModel, self).__init__(config, *inputs, **kwargs) + super().__init__(config, *inputs, **kwargs) self.transformer = TFFlaubertMainLayer(config, name="transformer") @@ -326,5 +326,5 @@ class TFFlaubertForSequenceClassification(TFXLMForSequenceClassification): pretrained_model_archive_map = TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_MAP def __init__(self, config, *inputs, **kwargs): - super(TFFlaubertForSequenceClassification, self).__init__(config, *inputs, **kwargs) + super().__init__(config, *inputs, **kwargs) self.transformer = TFFlaubertMainLayer(config, name="transformer")