move xnli processor (and utils) to transformers/data/processors

examples/run_xnli.py

@@ -44,9 +44,9 @@ from transformers import (WEIGHTS_NAME,
 
 from transformers import AdamW, WarmupLinearSchedule
 
-from utils_xnli import xnli_compute_metrics as compute_metrics
-from utils_xnli import xnli_output_modes as output_modes
-from utils_xnli import xnli_processors as processors
+from transformers import xnli_compute_metrics as compute_metrics
+from transformers import xnli_output_modes as output_modes
+from transformers import xnli_processors as processors
 
 from transformers import glue_convert_examples_to_features as convert_examples_to_features
 

transformers/__init__.py

@@ -25,7 +25,8 @@ from .file_utils import (TRANSFORMERS_CACHE, PYTORCH_TRANSFORMERS_CACHE, PYTORCH
 from .data import (is_sklearn_available,
                    InputExample, InputFeatures, DataProcessor,
                    glue_output_modes, glue_convert_examples_to_features,
-                   glue_processors, glue_tasks_num_labels)
+                   glue_processors, glue_tasks_num_labels,
+                   xnli_output_modes, xnli_processors, xnli_tasks_num_labels)
 
 if is_sklearn_available():
     from .data import glue_compute_metrics

transformers/data/__init__.py

 from .processors import InputExample, InputFeatures, DataProcessor
 from .processors import glue_output_modes, glue_processors, glue_tasks_num_labels, glue_convert_examples_to_features
+from .processors import xnli_output_modes, xnli_processors, xnli_tasks_num_labels
 
 from .metrics import is_sklearn_available
 if is_sklearn_available():

transformers/data/processors/__init__.py

 from .utils import InputExample, InputFeatures, DataProcessor
 from .glue import glue_output_modes, glue_processors, glue_tasks_num_labels, glue_convert_examples_to_features
-
+from .xnli import xnli_output_modes, xnli_processors, xnli_tasks_num_labels

examples/utils_xnli.py → transformers/data/processors/xnli.py

@@ -20,7 +20,7 @@ from __future__ import absolute_import, division, print_function
 import logging
 import os
 
-from transformers.data.processors import DataProcessor, InputExample
+from .utils import DataProcessor, InputExample
 from transformers.data.metrics import simple_accuracy
 
 logger = logging.getLogger(__name__)