Fix Torch.hub + Integration test

.github/workflows/github-torch-hub.yml

+name: Torch hub integration
+
+on: 
+  push:
+    branches:
+      - "*"
+
+jobs:
+  torch_hub_integration:
+    runs-on: ubuntu-latest
+    steps:
+    # no checkout necessary here.
+    - name: Extract branch name
+      run: echo "::set-env name=BRANCH::${GITHUB_REF#refs/heads/}"
+    - name: Check branch name
+      run: echo $BRANCH
+    - name: Set up Python
+      uses: actions/setup-python@v1
+      with:
+        python-version: 3.7
+    - name: Install dependencies
+      run: |
+        pip install torch
+        pip install numpy tokenizers boto3 filelock requests tqdm regex sentencepiece sacremoses
+
+    - name: Torch hub list
+      run: |
+        python -c "import torch; print(torch.hub.list('huggingface/transformers:$BRANCH'))"
+
+    - name: Torch hub help
+      run: |
+        python -c "import torch; print(torch.hub.help('huggingface/transformers:$BRANCH', 'modelForSequenceClassification'))"

hubconf.py

-from transformers import (
+from src.transformers import (
     AutoConfig,
     AutoModel,
     AutoModelForQuestionAnswering,
@@ -6,10 +6,10 @@ from transformers import (
     AutoModelWithLMHead,
     AutoTokenizer,
 )
-from transformers.file_utils import add_start_docstrings
+from src.transformers.file_utils import add_start_docstrings
 
 
-dependencies = ["torch", "tqdm", "boto3", "requests", "regex", "sentencepiece", "sacremoses"]
+dependencies = ["torch", "numpy", "tokenizers", "boto3", "filelock", "requests", "tqdm", "regex", "sentencepiece", "sacremoses"]
 
 
 @add_start_docstrings(AutoConfig.__doc__)

src/transformers/modeling_albert.py

@@ -22,11 +22,10 @@ import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss, MSELoss
 
-from transformers.configuration_albert import AlbertConfig
-from transformers.modeling_bert import ACT2FN, BertEmbeddings, BertSelfAttention, prune_linear_layer
-from transformers.modeling_utils import PreTrainedModel
-
+from .configuration_albert import AlbertConfig
 from .file_utils import add_start_docstrings, add_start_docstrings_to_callable
+from .modeling_bert import ACT2FN, BertEmbeddings, BertSelfAttention, prune_linear_layer
+from .modeling_utils import PreTrainedModel
 
 
 logger = logging.getLogger(__name__)

src/transformers/modeling_electra.py

@@ -4,10 +4,9 @@ import os
 import torch
 import torch.nn as nn
 
-from transformers import ElectraConfig, add_start_docstrings
-from transformers.activations import get_activation
-
-from .file_utils import add_start_docstrings_to_callable
+from .activations import get_activation
+from .configuration_electra import ElectraConfig
+from .file_utils import add_start_docstrings, add_start_docstrings_to_callable
 from .modeling_bert import BertEmbeddings, BertEncoder, BertLayerNorm, BertPreTrainedModel
 
 

src/transformers/tokenization_camembert.py

@@ -22,8 +22,7 @@ from typing import List, Optional
 
 import sentencepiece as spm
 
-from transformers.tokenization_utils import PreTrainedTokenizer
-
+from .tokenization_utils import PreTrainedTokenizer
 from .tokenization_xlnet import SPIECE_UNDERLINE
 
 

src/transformers/tokenization_xlm_roberta.py

@@ -20,8 +20,7 @@ import os
 from shutil import copyfile
 from typing import List, Optional
 
-from transformers.tokenization_utils import PreTrainedTokenizer
-
+from .tokenization_utils import PreTrainedTokenizer
 from .tokenization_xlnet import SPIECE_UNDERLINE