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Resume SynthData0523 main/c13 batch 3

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  1. .gitattributes +49 -0
  2. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/X_cat_train.npy +3 -0
  3. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/X_num_test.npy +3 -0
  4. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/X_num_train.npy +3 -0
  5. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/info.json +3 -0
  6. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/test.csv +3 -0
  7. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/train.csv +3 -0
  8. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/y_test.npy +3 -0
  9. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/data/tabsyn_c13_tabsyn_c13_20260512_211521/y_train.npy +3 -0
  10. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/gen_20260513_042505.log +3 -0
  11. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/input_snapshot.json +3 -0
  12. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/public_gate/normalized_schema_snapshot.json +3 -0
  13. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/public_gate/public_gate_report.json +3 -0
  14. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/public_gate/staged_input_manifest.json +3 -0
  15. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/run_config.json +3 -0
  16. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/runtime_result.json +3 -0
  17. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/public/staged_features.json +3 -0
  18. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/public/test.csv +3 -0
  19. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/public/train.csv +3 -0
  20. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/public/val.csv +3 -0
  21. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/tabsyn/adapter_report.json +3 -0
  22. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/tabsyn/adapter_transforms_applied.json +3 -0
  23. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/staged/tabsyn/model_input_manifest.json +3 -0
  24. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/synthetic/tabsyn_c13_tabsyn_c13_20260512_211521/real.csv +3 -0
  25. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/synthetic/tabsyn_c13_tabsyn_c13_20260512_211521/test.csv +3 -0
  26. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn-c13-1966628-20260513_042505.csv +3 -0
  27. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/diffusion/tabsyn_c13_tabsyn_c13_20260512_211521/model.pt +3 -0
  28. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/diffusion/tabsyn_c13_tabsyn_c13_20260512_211521/model_0.pt +3 -0
  29. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/vae/tabsyn_c13_tabsyn_c13_20260512_211521/decoder.pt +3 -0
  30. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/vae/tabsyn_c13_tabsyn_c13_20260512_211521/encoder.pt +3 -0
  31. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/vae/tabsyn_c13_tabsyn_c13_20260512_211521/model.pt +3 -0
  32. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/tabsyn_ckpt/vae/tabsyn_c13_tabsyn_c13_20260512_211521/train_z.npy +3 -0
  33. SynthData0523/main/c13/tabsyn/tabsyn-c13-20260512_211521/train_20260512_211714.log +3 -0
  34. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/_tvae_generate.py +23 -0
  35. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/_tvae_train.py +30 -0
  36. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/gen_20260426_000517.log +3 -0
  37. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/input_snapshot.json +3 -0
  38. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/models_50epochs/train_20260425_212519.log +3 -0
  39. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/models_50epochs/tvae_50epochs.pt +3 -0
  40. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/public_gate/normalized_schema_snapshot.json +3 -0
  41. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/public_gate/public_gate_report.json +3 -0
  42. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/public_gate/staged_input_manifest.json +3 -0
  43. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/runtime_result.json +3 -0
  44. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/public/staged_features.json +3 -0
  45. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/public/test.csv +3 -0
  46. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/public/train.csv +3 -0
  47. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/public/val.csv +3 -0
  48. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/tvae/adapter_report.json +3 -0
  49. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/tvae/adapter_transforms_applied.json +3 -0
  50. SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/staged/tvae/model_input_manifest.json +3 -0
.gitattributes CHANGED
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+ import os, sys
2
+ sys.path.insert(0, "/work")
3
+ from src.SpecificModels.ctgan_joblib_parallel_cap import apply_parallel_cap_from_env
4
+ apply_parallel_cap_from_env()
5
+ from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix
6
+ apply_ctgan_inverse_fix()
7
+ import pandas as pd
8
+ from ctgan.synthesizers.tvae import TVAE
9
+ os.environ.setdefault("LOKY_MAX_CPU_COUNT", "8")
10
+ os.environ.setdefault("OPENBLAS_NUM_THREADS", "8")
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+ os.environ.setdefault("MKL_NUM_THREADS", "8")
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+ model = TVAE.load("/work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/models_50epochs/tvae_50epochs.pt")
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+ total = 1966628
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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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+ samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0]
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+ samples.to_csv("/work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/tvae-c13-1966628-20260426_000517.csv", index=False)
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+ print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/tvae-c13-1966628-20260426_000517.csv")
SynthData0523/main/c13/tvae/tvae-c13-20260425_212442/_tvae_train.py ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import json, os, sys
2
+ sys.path.insert(0, "/work")
3
+ from src.SpecificModels.ctgan_joblib_parallel_cap import apply_parallel_cap_from_env
4
+ apply_parallel_cap_from_env()
5
+ import pandas as pd
6
+ from ctgan.data import read_csv
7
+ from ctgan.synthesizers.tvae import TVAE
8
+
9
+ # Keep transform stage parallelism bounded for stability on shared host.
10
+ os.environ.setdefault("LOKY_MAX_CPU_COUNT", "8")
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+ os.environ.setdefault("OPENBLAS_NUM_THREADS", "8")
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+ os.environ.setdefault("MKL_NUM_THREADS", "8")
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+ _nj = (os.environ.get("TVAE_CTGAN_JOBTRANS_N_JOBS") or "").strip()
14
+ if _nj:
15
+ print("[TVAE] joblib Parallel cap ON, TVAE_CTGAN_JOBTRANS_N_JOBS=" + _nj)
16
+ else:
17
+ print("[TVAE] joblib Parallel cap OFF (unset TVAE_CTGAN_JOBTRANS_N_JOBS)")
18
+ print("[TVAE] LOKY_MAX_CPU_COUNT=" + str(os.environ.get("LOKY_MAX_CPU_COUNT", "")))
19
+
20
+ csv_path = "/work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/staged/public/train.csv"
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+ meta_path = "/work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/tvae_metadata.json"
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+ save_path = "/work/output-SpecializedModels/c13/tvae/tvae-c13-20260425_212442/models_50epochs/tvae_50epochs.pt"
23
+ epochs = 50
24
+
25
+ data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None)
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+ print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}")
27
+ model = TVAE(epochs=epochs, batch_size=500)
28
+ model.fit(data, discrete_columns)
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+ model.save(save_path)
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+ print(f"[TVAE] Model saved -> {save_path}")
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