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  1. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/_ctgan_generate.py +18 -0
  2. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/ctgan-n11-15215-20260501_000111.csv +3 -0
  3. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/ctgan_metadata.json +3 -0
  4. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/gen_20260501_000111.log +3 -0
  5. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/input_snapshot.json +3 -0
  6. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/models_300epochs/ctgan_300epochs.pt +3 -0
  7. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/models_300epochs/train_20260430_235732.log +3 -0
  8. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/public_gate/normalized_schema_snapshot.json +3 -0
  9. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/public_gate/public_gate_report.json +3 -0
  10. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/public_gate/staged_input_manifest.json +3 -0
  11. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/runtime_result.json +3 -0
  12. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/ctgan/adapter_report.json +3 -0
  13. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/ctgan/adapter_transforms_applied.json +3 -0
  14. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/ctgan/model_input_manifest.json +3 -0
  15. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/public/staged_features.json +3 -0
  16. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/public/test.csv +3 -0
  17. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/public/train.csv +3 -0
  18. syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/staged/public/val.csv +3 -0
syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/_ctgan_generate.py ADDED
@@ -0,0 +1,18 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import sys
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+ sys.path.insert(0, "/work")
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+ from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix
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+ apply_ctgan_inverse_fix()
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+ import pandas as pd
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+ from ctgan.synthesizers.ctgan import CTGAN
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+ model = CTGAN.load("/work/output-Benchmark-trainonly-v1/n11/ctgan/ctgan-n11-20260430_235732/models_300epochs/ctgan_300epochs.pt")
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+ total = 15215
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+ chunk = min(50000, total) if total > 50000 else total
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+ parts = []
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+ left = total
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+ while left > 0:
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+ take = min(chunk, left)
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+ parts.append(model.sample(take))
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+ left -= take
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+ sampled = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0]
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+ sampled.to_csv("/work/output-Benchmark-trainonly-v1/n11/ctgan/ctgan-n11-20260430_235732/ctgan-n11-15215-20260501_000111.csv", index=False)
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+ print("[CTGAN] Generated", total, "rows in", len(parts), "chunks ->", "/work/output-Benchmark-trainonly-v1/n11/ctgan/ctgan-n11-20260430_235732/ctgan-n11-15215-20260501_000111.csv")
syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/ctgan-n11-15215-20260501_000111.csv ADDED
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+ size 2885629
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syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/models_300epochs/ctgan_300epochs.pt ADDED
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syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/models_300epochs/train_20260430_235732.log ADDED
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syntheticSuccess/n11/ctgan/ctgan-n11-20260430_235732/runtime_result.json ADDED
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