fix PR (#4810)
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@@ -3,7 +3,7 @@ import tempfile
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import unittest
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from pathlib import Path
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from transformers import GPT2Config, is_torch_available
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from transformers import AutoConfig, is_torch_available
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from .utils import require_torch
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@@ -45,7 +45,18 @@ class BenchmarkTest(unittest.TestCase):
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def test_inference_with_configs(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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config = GPT2Config.from_pretrained(MODEL_ID)
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = PyTorchBenchmarkArguments(
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models=[MODEL_ID], training=False, no_inference=False, sequence_lengths=[8], batch_sizes=[1]
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)
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benchmark = PyTorchBenchmark(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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def test_inference_encoder_decoder_with_configs(self):
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MODEL_ID = "sshleifer/tinier_bart"
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = PyTorchBenchmarkArguments(
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models=[MODEL_ID], training=False, no_inference=False, sequence_lengths=[8], batch_sizes=[1]
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)
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@@ -56,7 +67,18 @@ class BenchmarkTest(unittest.TestCase):
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def test_train_with_configs(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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config = GPT2Config.from_pretrained(MODEL_ID)
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = PyTorchBenchmarkArguments(
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models=[MODEL_ID], training=True, no_inference=True, sequence_lengths=[8], batch_sizes=[1]
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)
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benchmark = PyTorchBenchmark(benchmark_args, configs=[config])
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results = benchmark.run()
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self.check_results_dict_not_empty(results.time_train_result)
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self.check_results_dict_not_empty(results.memory_train_result)
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def test_train_encoder_decoder_with_configs(self):
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MODEL_ID = "sshleifer/tinier_bart"
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config = AutoConfig.from_pretrained(MODEL_ID)
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benchmark_args = PyTorchBenchmarkArguments(
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models=[MODEL_ID], training=True, no_inference=True, sequence_lengths=[8], batch_sizes=[1]
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)
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@@ -88,3 +110,29 @@ class BenchmarkTest(unittest.TestCase):
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self.assertTrue(Path(os.path.join(tmp_dir, "inf_mem.csv")).exists())
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self.assertTrue(Path(os.path.join(tmp_dir, "train_mem.csv")).exists())
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self.assertTrue(Path(os.path.join(tmp_dir, "env.csv")).exists())
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def test_trace_memory(self):
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MODEL_ID = "sshleifer/tiny-gpt2"
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def _check_summary_is_not_empty(summary):
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self.assertTrue(hasattr(summary, "sequential"))
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self.assertTrue(hasattr(summary, "cumulative"))
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self.assertTrue(hasattr(summary, "current"))
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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 = PyTorchBenchmarkArguments(
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models=[MODEL_ID],
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training=True,
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no_inference=False,
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sequence_lengths=[8],
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batch_sizes=[1],
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log_filename=os.path.join(tmp_dir, "log.txt"),
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log_print=True,
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trace_memory_line_by_line=True,
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)
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benchmark = PyTorchBenchmark(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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_check_summary_is_not_empty(result.train_summary)
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self.assertTrue(Path(os.path.join(tmp_dir, "log.txt")).exists())
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