Deprecate old data/metrics functions (#8420)

src/transformers/data/datasets/glue.py

@@ -1,5 +1,6 @@
 import os
 import time
+import warnings
 from dataclasses import dataclass, field
 from enum import Enum
 from typing import List, Optional, Union
@@ -69,6 +70,12 @@ class GlueDataset(Dataset):
         mode: Union[str, Split] = Split.train,
         cache_dir: Optional[str] = None,
     ):
+        warnings.warn(
+            "This dataset will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets "
+            "library. You can have a look at this example script for pointers: "
+            "https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue.py",
+            FutureWarning,
+        )
         self.args = args
         self.processor = glue_processors[args.task_name]()
         self.output_mode = glue_output_modes[args.task_name]

src/transformers/data/datasets/language_modeling.py

@@ -19,7 +19,8 @@ logger = logging.get_logger(__name__)
 
 
 DEPRECATION_WARNING = (
-    "This dataset will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets library."
+    "This dataset will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets "
+    "library. You can have a look at this example script for pointers: {0}"
 )
 
 
@@ -36,7 +37,12 @@ class TextDataset(Dataset):
         overwrite_cache=False,
         cache_dir: Optional[str] = None,
     ):
-        warnings.warn(DEPRECATION_WARNING, FutureWarning)
+        warnings.warn(
+            DEPRECATION_WARNING.format(
+                "https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py"
+            ),
+            FutureWarning,
+        )
         assert os.path.isfile(file_path), f"Input file path {file_path} not found"
 
         block_size = block_size - tokenizer.num_special_tokens_to_add(pair=False)
@@ -101,7 +107,12 @@ class LineByLineTextDataset(Dataset):
     """
 
     def __init__(self, tokenizer: PreTrainedTokenizer, file_path: str, block_size: int):
-        warnings.warn(DEPRECATION_WARNING, FutureWarning)
+        warnings.warn(
+            DEPRECATION_WARNING.format(
+                "https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py"
+            ),
+            FutureWarning,
+        )
         assert os.path.isfile(file_path), f"Input file path {file_path} not found"
         # Here, we do not cache the features, operating under the assumption
         # that we will soon use fast multithreaded tokenizers from the
@@ -128,7 +139,12 @@ class LineByLineWithRefDataset(Dataset):
     """
 
     def __init__(self, tokenizer: PreTrainedTokenizer, file_path: str, block_size: int, ref_path: str):
-        warnings.warn(DEPRECATION_WARNING, FutureWarning)
+        warnings.warn(
+            DEPRECATION_WARNING.format(
+                "https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py"
+            ),
+            FutureWarning,
+        )
         assert os.path.isfile(file_path), f"Input file path {file_path} not found"
         assert os.path.isfile(ref_path), f"Ref file path {file_path} not found"
         # Here, we do not cache the features, operating under the assumption
@@ -165,7 +181,12 @@ class LineByLineWithSOPTextDataset(Dataset):
     """
 
     def __init__(self, tokenizer: PreTrainedTokenizer, file_dir: str, block_size: int):
-        warnings.warn(DEPRECATION_WARNING, FutureWarning)
+        warnings.warn(
+            DEPRECATION_WARNING.format(
+                "https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py"
+            ),
+            FutureWarning,
+        )
         assert os.path.isdir(file_dir)
         logger.info(f"Creating features from dataset file folder at {file_dir}")
         self.examples = []
@@ -315,7 +336,12 @@ class TextDatasetForNextSentencePrediction(Dataset):
         short_seq_probability=0.1,
         nsp_probability=0.5,
     ):
-        warnings.warn(DEPRECATION_WARNING, FutureWarning)
+        warnings.warn(
+            DEPRECATION_WARNING.format(
+                "https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py"
+            ),
+            FutureWarning,
+        )
         assert os.path.isfile(file_path), f"Input file path {file_path} not found"
 
         self.block_size = block_size - tokenizer.num_special_tokens_to_add(pair=True)

src/transformers/data/metrics/__init__.py

@@ -14,6 +14,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import warnings
+
 from ...file_utils import is_sklearn_available, requires_sklearn
 
 
@@ -23,12 +25,21 @@ if is_sklearn_available():
     from scipy.stats import pearsonr, spearmanr
 
 
+DEPRECATION_WARNING = (
+    "This metric will be removed from the library soon, metrics should be handled with the 🤗 Datasets "
+    "library. You can have a look at this example script for pointers: "
+    "https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue.py",
+)
+
+
 def simple_accuracy(preds, labels):
+    warnings.warn(DEPRECATION_WARNING, FutureWarning)
     requires_sklearn(simple_accuracy)
     return (preds == labels).mean()
 
 
 def acc_and_f1(preds, labels):
+    warnings.warn(DEPRECATION_WARNING, FutureWarning)
     requires_sklearn(acc_and_f1)
     acc = simple_accuracy(preds, labels)
     f1 = f1_score(y_true=labels, y_pred=preds)
@@ -40,6 +51,7 @@ def acc_and_f1(preds, labels):
 
 
 def pearson_and_spearman(preds, labels):
+    warnings.warn(DEPRECATION_WARNING, FutureWarning)
     requires_sklearn(pearson_and_spearman)
     pearson_corr = pearsonr(preds, labels)[0]
     spearman_corr = spearmanr(preds, labels)[0]
@@ -51,6 +63,7 @@ def pearson_and_spearman(preds, labels):
 
 
 def glue_compute_metrics(task_name, preds, labels):
+    warnings.warn(DEPRECATION_WARNING, FutureWarning)
     requires_sklearn(glue_compute_metrics)
     assert len(preds) == len(labels), f"Predictions and labels have mismatched lengths {len(preds)} and {len(labels)}"
     if task_name == "cola":
@@ -80,6 +93,7 @@ def glue_compute_metrics(task_name, preds, labels):
 
 
 def xnli_compute_metrics(task_name, preds, labels):
+    warnings.warn(DEPRECATION_WARNING, FutureWarning)
     requires_sklearn(xnli_compute_metrics)
     assert len(preds) == len(labels), f"Predictions and labels have mismatched lengths {len(preds)} and {len(labels)}"
     if task_name == "xnli":

src/transformers/data/processors/glue.py

@@ -16,6 +16,7 @@
 """ GLUE processors and helpers """
 
 import os
+import warnings
 from dataclasses import asdict
 from enum import Enum
 from typing import List, Optional, Union
@@ -31,6 +32,12 @@ if is_tf_available():
 
 logger = logging.get_logger(__name__)
 
+DEPRECATION_WARNING = (
+    "This {0} will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets "
+    "library. You can have a look at this example script for pointers: "
+    "https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_glue.py"
+)
+
 
 def glue_convert_examples_to_features(
     examples: Union[List[InputExample], "tf.data.Dataset"],
@@ -57,6 +64,7 @@ def glue_convert_examples_to_features(
         ``InputFeatures`` which can be fed to the model.
 
     """
+    warnings.warn(DEPRECATION_WARNING.format("function"), FutureWarning)
     if is_tf_available() and isinstance(examples, tf.data.Dataset):
         if task is None:
             raise ValueError("When calling glue_convert_examples_to_features from TF, the task parameter is required.")
@@ -162,6 +170,10 @@ class OutputMode(Enum):
 class MrpcProcessor(DataProcessor):
     """Processor for the MRPC data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -205,6 +217,10 @@ class MrpcProcessor(DataProcessor):
 class MnliProcessor(DataProcessor):
     """Processor for the MultiNLI data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -247,6 +263,10 @@ class MnliProcessor(DataProcessor):
 class MnliMismatchedProcessor(MnliProcessor):
     """Processor for the MultiNLI Mismatched data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_dev_examples(self, data_dir):
         """See base class."""
         return self._create_examples(self._read_tsv(os.path.join(data_dir, "dev_mismatched.tsv")), "dev_mismatched")
@@ -259,6 +279,10 @@ class MnliMismatchedProcessor(MnliProcessor):
 class ColaProcessor(DataProcessor):
     """Processor for the CoLA data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -302,6 +326,10 @@ class ColaProcessor(DataProcessor):
 class Sst2Processor(DataProcessor):
     """Processor for the SST-2 data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -344,6 +372,10 @@ class Sst2Processor(DataProcessor):
 class StsbProcessor(DataProcessor):
     """Processor for the STS-B data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -386,6 +418,10 @@ class StsbProcessor(DataProcessor):
 class QqpProcessor(DataProcessor):
     """Processor for the QQP data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -434,6 +470,10 @@ class QqpProcessor(DataProcessor):
 class QnliProcessor(DataProcessor):
     """Processor for the QNLI data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -476,6 +516,10 @@ class QnliProcessor(DataProcessor):
 class RteProcessor(DataProcessor):
     """Processor for the RTE data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(
@@ -518,6 +562,10 @@ class RteProcessor(DataProcessor):
 class WnliProcessor(DataProcessor):
     """Processor for the WNLI data set (GLUE version)."""
 
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        warnings.warn(DEPRECATION_WARNING.format("processor"), FutureWarning)
+
     def get_example_from_tensor_dict(self, tensor_dict):
         """See base class."""
         return InputExample(