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[Benchmark] Add benchmarks for TF Training (#5594)

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* tf_train

* adapt timing for tpu

* fix timing

* fix timing

* fix timing

* fix timing

* update notebook

* add tests
This commit is contained in:
Patrick von Platen
2020-07-08 12:11:09 +02:00
committed by GitHub
parent cfbb982974
commit f82a2a5e8e
4 changed files with 103 additions and 15 deletions
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31
tests/test_benchmark_tf.py
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@@ -100,6 +100,37 @@ class TFBenchmarkTest(unittest.TestCase):
self.check_results_dict_not_empty(results.time_inference_result)
self.check_results_dict_not_empty(results.memory_inference_result)
def test_train_no_configs(self):
MODEL_ID = "sshleifer/tiny-gpt2"
benchmark_args = TensorFlowBenchmarkArguments(
models=[MODEL_ID],
training=True,
no_inference=True,
sequence_lengths=[8],
batch_sizes=[1],
no_multi_process=True,
)
benchmark = TensorFlowBenchmark(benchmark_args)
results = benchmark.run()
self.check_results_dict_not_empty(results.time_train_result)
self.check_results_dict_not_empty(results.memory_train_result)
def test_train_with_configs(self):
MODEL_ID = "sshleifer/tiny-gpt2"
config = AutoConfig.from_pretrained(MODEL_ID)
benchmark_args = TensorFlowBenchmarkArguments(
models=[MODEL_ID],
training=True,
no_inference=True,
sequence_lengths=[8],
batch_sizes=[1],
no_multi_process=True,
)
benchmark = TensorFlowBenchmark(benchmark_args, [config])
results = benchmark.run()
self.check_results_dict_not_empty(results.time_train_result)
self.check_results_dict_not_empty(results.memory_train_result)
def test_inference_encoder_decoder_with_configs(self):
MODEL_ID = "patrickvonplaten/t5-tiny-random"
config = AutoConfig.from_pretrained(MODEL_ID)