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Improve log messages in text_entries and memory leak unit test
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2 changed files with 4 additions and 2 deletions
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@ -93,7 +93,7 @@ class TextToEntries(ABC):
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num_deleted_entries = 0
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num_deleted_entries = 0
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if regenerate:
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if regenerate:
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with timer("Prepared dataset for regeneration in", logger):
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with timer("Cleared existing dataset for regeneration in", logger):
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logger.debug(f"Deleting all entries for file type {file_type}")
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logger.debug(f"Deleting all entries for file type {file_type}")
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num_deleted_entries = EntryAdapters.delete_all_entries(user, file_type)
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num_deleted_entries = EntryAdapters.delete_all_entries(user, file_type)
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@ -64,6 +64,7 @@ def test_encode_docs_memory_leak():
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batch_size = 20
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batch_size = 20
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embeddings_model = EmbeddingsModel()
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embeddings_model = EmbeddingsModel()
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memory_usage_trend = []
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memory_usage_trend = []
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device = f"{helpers.get_device()}".upper()
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# Act
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# Act
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# Encode random strings repeatedly and record memory usage trend
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# Encode random strings repeatedly and record memory usage trend
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@ -76,8 +77,9 @@ def test_encode_docs_memory_leak():
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# Calculate slope of line fitting memory usage history
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# Calculate slope of line fitting memory usage history
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memory_usage_trend = np.array(memory_usage_trend)
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memory_usage_trend = np.array(memory_usage_trend)
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slope, _, _, _, _ = linregress(np.arange(len(memory_usage_trend)), memory_usage_trend)
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slope, _, _, _, _ = linregress(np.arange(len(memory_usage_trend)), memory_usage_trend)
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print(f"Memory usage increased at ~{slope:.2f} MB per iteration on {device}")
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# Assert
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# Assert
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# If slope is positive memory utilization is increasing
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# If slope is positive memory utilization is increasing
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# Positive threshold of 2, from observing memory usage trend on MPS vs CPU device
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# Positive threshold of 2, from observing memory usage trend on MPS vs CPU device
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assert slope < 2, f"Memory usage increasing at ~{slope:.2f} MB per iteration"
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assert slope < 2, f"Memory leak suspected on {device}. Memory usage increased at ~{slope:.2f} MB per iteration"
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