[Docs] Benchmark docs (#5360)
* first doc version * add benchmark docs * fix typos * improve README * Update docs/source/benchmarks.rst Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * fix naming and docs Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
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Patrick von Platen
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@@ -10,7 +10,7 @@ from .utils import require_tf
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if is_tf_available():
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import tensorflow as tf
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from transformers import TensorflowBenchmark, TensorflowBenchmarkArguments
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from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
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@require_tf
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@@ -23,7 +23,7 @@ class TFBenchmarkTest(unittest.TestCase):
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def test_inference_no_configs_eager(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -32,14 +32,14 @@ class TFBenchmarkTest(unittest.TestCase):
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eager_mode=True,
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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def test_inference_no_configs_only_pretrain(self):
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MODEL_ID = "sshleifer/tiny-distilbert-base-uncased-finetuned-sst-2-english"
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -48,14 +48,14 @@ class TFBenchmarkTest(unittest.TestCase):
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no_multi_process=True,
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only_pretrain_model=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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def test_inference_no_configs_graph(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -63,7 +63,7 @@ class TFBenchmarkTest(unittest.TestCase):
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batch_sizes=[1],
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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@@ -71,7 +71,7 @@ class TFBenchmarkTest(unittest.TestCase):
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def test_inference_with_configs_eager(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -80,7 +80,7 @@ class TFBenchmarkTest(unittest.TestCase):
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eager_mode=True,
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args, [config])
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benchmark = TensorFlowBenchmark(benchmark_args, [config])
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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@@ -88,7 +88,7 @@ class TFBenchmarkTest(unittest.TestCase):
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def test_inference_with_configs_graph(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -96,7 +96,7 @@ class TFBenchmarkTest(unittest.TestCase):
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batch_sizes=[1],
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args, [config])
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benchmark = TensorFlowBenchmark(benchmark_args, [config])
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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@@ -104,7 +104,7 @@ class TFBenchmarkTest(unittest.TestCase):
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def test_inference_encoder_decoder_with_configs(self):
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MODEL_ID = "patrickvonplaten/t5-tiny-random"
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -112,7 +112,7 @@ class TFBenchmarkTest(unittest.TestCase):
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batch_sizes=[1],
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args, configs=[config])
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benchmark = TensorFlowBenchmark(benchmark_args, configs=[config])
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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@@ -120,7 +120,7 @@ class TFBenchmarkTest(unittest.TestCase):
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@unittest.skipIf(is_tf_available() and len(tf.config.list_physical_devices("GPU")) == 0, "Cannot do xla on CPU.")
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def test_inference_no_configs_xla(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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training=False,
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no_inference=False,
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@@ -129,7 +129,7 @@ class TFBenchmarkTest(unittest.TestCase):
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use_xla=True,
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_inference_result)
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self.check_results_dict_not_empty(results.memory_inference_result)
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@@ -137,7 +137,7 @@ class TFBenchmarkTest(unittest.TestCase):
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def test_save_csv_files(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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with tempfile.TemporaryDirectory() as tmp_dir:
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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no_inference=False,
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save_to_csv=True,
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@@ -148,7 +148,7 @@ class TFBenchmarkTest(unittest.TestCase):
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env_info_csv_file=os.path.join(tmp_dir, "env.csv"),
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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benchmark.run()
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self.assertTrue(Path(os.path.join(tmp_dir, "inf_time.csv")).exists())
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self.assertTrue(Path(os.path.join(tmp_dir, "inf_mem.csv")).exists())
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@@ -164,7 +164,7 @@ class TFBenchmarkTest(unittest.TestCase):
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self.assertTrue(hasattr(summary, "total"))
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with tempfile.TemporaryDirectory() as tmp_dir:
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benchmark_args = TensorflowBenchmarkArguments(
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benchmark_args = TensorFlowBenchmarkArguments(
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models=[MODEL_ID],
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no_inference=False,
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sequence_lengths=[8],
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@@ -175,7 +175,7 @@ class TFBenchmarkTest(unittest.TestCase):
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eager_mode=True,
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no_multi_process=True,
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)
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benchmark = TensorflowBenchmark(benchmark_args)
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benchmark = TensorFlowBenchmark(benchmark_args)
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result = benchmark.run()
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_check_summary_is_not_empty(result.inference_summary)
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self.assertTrue(Path(os.path.join(tmp_dir, "log.txt")).exists())
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