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
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@@ -46,7 +46,7 @@ from transformers import (
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set_seed,
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)
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from transformers.trainer_utils import get_last_checkpoint
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from transformers.utils import check_min_version, is_offline_mode
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from transformers.utils import check_min_version, is_offline_mode, send_example_telemetry
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from transformers.utils.versions import require_version
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@@ -302,6 +302,10 @@ def main():
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else:
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model_args, data_args, training_args = parser.parse_args_into_dataclasses()
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# Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
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# information sent is the one passed as arguments along with your Python/PyTorch versions.
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send_example_telemetry("run_summarization", model_args, data_args)
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# Setup logging
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logging.basicConfig(
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format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
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@@ -50,7 +50,7 @@ from transformers import (
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SchedulerType,
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get_scheduler,
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)
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from transformers.utils import get_full_repo_name, is_offline_mode
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from transformers.utils import get_full_repo_name, is_offline_mode, send_example_telemetry
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from transformers.utils.versions import require_version
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@@ -319,6 +319,10 @@ def parse_args():
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def main():
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args = parse_args()
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# Sending telemetry. Tracking the example usage helps us better allocate resources to maintain them. The
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# information sent is the one passed as arguments along with your Python/PyTorch versions.
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send_example_telemetry("run_summarization_no_trainer", args)
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# Initialize the accelerator. We will let the accelerator handle device placement for us in this example.
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# If we're using tracking, we also need to initialize it here and it will by default pick up all supported trackers
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# in the environment
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