Add examples telemetry (#17552)

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

examples/tensorflow/text-classification/run_glue.py

@@ -39,7 +39,7 @@ from transformers import (
     set_seed,
 )
 from transformers.trainer_utils import get_last_checkpoint, is_main_process
-from transformers.utils import check_min_version
+from transformers.utils import check_min_version, send_example_telemetry
 
 
 # region Helper functions
@@ -206,6 +206,10 @@ def main():
     else:
         model_args, data_args, training_args = parser.parse_args_into_dataclasses()
 
+    # Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
+    # information sent is the one passed as arguments along with your Python/PyTorch versions.
+    send_example_telemetry("run_glue", model_args, data_args, framework="tensorflow")
+
     if not (training_args.do_train or training_args.do_eval or training_args.do_predict):
         exit("Must specify at least one of --do_train, --do_eval or --do_predict!")
     # endregion

examples/tensorflow/text-classification/run_text_classification.py

@@ -37,7 +37,7 @@ from transformers import (
     TFTrainingArguments,
     set_seed,
 )
-from transformers.utils import CONFIG_NAME, TF2_WEIGHTS_NAME
+from transformers.utils import CONFIG_NAME, TF2_WEIGHTS_NAME, send_example_telemetry
 
 
 os.environ["TF_CPP_MIN_LOG_LEVEL"] = "1"  # Reduce the amount of console output from TF
@@ -196,6 +196,11 @@ def main():
         model_args, data_args, training_args = parser.parse_json_file(json_file=os.path.abspath(sys.argv[1]))
     else:
         model_args, data_args, training_args = parser.parse_args_into_dataclasses()
+
+    # Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
+    # information sent is the one passed as arguments along with your Python/PyTorch versions.
+    send_example_telemetry("run_text_classification", model_args, data_args, framework="tensorflow")
+
     output_dir = Path(training_args.output_dir)
     output_dir.mkdir(parents=True, exist_ok=True)
     # endregion