Open Wopple opened 1 month ago
Running the causal impact algorithm appears to leak memory.
Reproduction code:
import gc import pandas as pd from causalimpact import CausalImpact data = pd.read_csv('https://raw.githubusercontent.com/WillianFuks/tfcausalimpact/master/tests/fixtures/arma_data.csv')[['y', 'X']] data.iloc[70:, 0] += 5 pre_period = [0, 69] post_period = [70, 99] def run_causal_impact(): ci = CausalImpact(data, pre_period, post_period) print(ci.summary()) print(ci.summary(output='report')) for _ in range(10): run_causal_impact() gc.collect()
Dependencies:
[tool.poetry.dependencies] python = "=3.11.4" pandas = "=2.2" tensorflow = "=2.16.1" tfcausalimpact = "=0.0.15" pyarrow = "=15.0.2"
I run the program and watch the activity monitor, and each iteration leaks ~80mb or so.
Running the causal impact algorithm appears to leak memory.
Reproduction code:
Dependencies:
I run the program and watch the activity monitor, and each iteration leaks ~80mb or so.