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Resume SynthData0523 main/c14 batch 3

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Files changed (36) hide show
  1. .gitattributes +33 -0
  2. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/input_snapshot.json +3 -0
  3. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/public_gate/normalized_schema_snapshot.json +3 -0
  4. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/public_gate/public_gate_report.json +3 -0
  5. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/public_gate/staged_input_manifest.json +3 -0
  6. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/runtime_result.json +3 -0
  7. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/public/staged_features.json +3 -0
  8. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/public/test.csv +3 -0
  9. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/public/train.csv +3 -0
  10. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/public/val.csv +3 -0
  11. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/tabsyn/adapter_report.json +3 -0
  12. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/tabsyn/adapter_transforms_applied.json +3 -0
  13. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/staged/tabsyn/model_input_manifest.json +3 -0
  14. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/synthetic/tabsyn_c14/real.csv +3 -0
  15. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/synthetic/tabsyn_c14/test.csv +3 -0
  16. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/tabsyn-c14-240000-20260504_051538.csv +3 -0
  17. SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/train_20260504_042709.log +3 -0
  18. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/_tvae_generate.py +23 -0
  19. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/_tvae_train.py +30 -0
  20. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/gen_20260503_201638.log +3 -0
  21. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/input_snapshot.json +3 -0
  22. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/models_300epochs/train_20260503_194912.log +3 -0
  23. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/models_300epochs/tvae_300epochs.pt +3 -0
  24. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/public_gate/normalized_schema_snapshot.json +3 -0
  25. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/public_gate/public_gate_report.json +3 -0
  26. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/public_gate/staged_input_manifest.json +3 -0
  27. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/runtime_result.json +3 -0
  28. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/public/staged_features.json +3 -0
  29. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/public/test.csv +3 -0
  30. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/public/train.csv +3 -0
  31. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/public/val.csv +3 -0
  32. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/tvae/adapter_report.json +3 -0
  33. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/tvae/adapter_transforms_applied.json +3 -0
  34. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/staged/tvae/model_input_manifest.json +3 -0
  35. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/tvae-c14-240000-20260503_201638.csv +3 -0
  36. SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/tvae_metadata.json +3 -0
.gitattributes CHANGED
@@ -1472,3 +1472,36 @@ SynthData0523/main/c14/tabsyn/tabsyn-c14-20260504_042655/data/tabsyn_c14/train.c
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@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ 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")
11
+ os.environ.setdefault("MKL_NUM_THREADS", "8")
12
+ model = TVAE.load("/work/output-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/models_300epochs/tvae_300epochs.pt")
13
+ total = 240000
14
+ chunk = min(50000, total) if total > 50000 else total
15
+ parts = []
16
+ left = total
17
+ while left > 0:
18
+ take = min(chunk, left)
19
+ parts.append(model.sample(take))
20
+ left -= take
21
+ samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0]
22
+ samples.to_csv("/work/output-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/tvae-c14-240000-20260503_201638.csv", index=False)
23
+ print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/tvae-c14-240000-20260503_201638.csv")
SynthData0523/main/c14/tvae/tvae-c14-20260503_194908/_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")
11
+ os.environ.setdefault("OPENBLAS_NUM_THREADS", "8")
12
+ os.environ.setdefault("MKL_NUM_THREADS", "8")
13
+ _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-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/staged/public/train.csv"
21
+ meta_path = "/work/output-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/tvae_metadata.json"
22
+ save_path = "/work/output-Benchmark-trainonly-v1/c14/tvae/tvae-c14-20260503_194908/models_300epochs/tvae_300epochs.pt"
23
+ epochs = 300
24
+
25
+ data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None)
26
+ 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)
29
+ model.save(save_path)
30
+ print(f"[TVAE] Model saved -> {save_path}")
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