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Resume SynthData0523 main/c19 batch 2

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  1. .gitattributes +48 -0
  2. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/ctgan/adapter_transforms_applied.json +3 -0
  3. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/ctgan/model_input_manifest.json +3 -0
  4. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/public/staged_features.json +3 -0
  5. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/public/test.csv +3 -0
  6. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/public/train.csv +3 -0
  7. SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/staged/public/val.csv +3 -0
  8. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_X_host.npy +3 -0
  9. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_gen.py +8 -0
  10. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_meta_host.json +3 -0
  11. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_train.py +36 -0
  12. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/forest-c19-32759-20260511_190121.csv +3 -0
  13. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/forestdiffusion_model.joblib +3 -0
  14. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/gen_20260511_190121.log +3 -0
  15. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/input_snapshot.json +3 -0
  16. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/models_fd/model.joblib +3 -0
  17. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/public_gate/normalized_schema_snapshot.json +3 -0
  18. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/public_gate/public_gate_report.json +3 -0
  19. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/public_gate/staged_input_manifest.json +3 -0
  20. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/run_config.json +3 -0
  21. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/runtime_result.json +3 -0
  22. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/forestdiffusion/adapter_report.json +3 -0
  23. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/forestdiffusion/adapter_transforms_applied.json +3 -0
  24. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/forestdiffusion/model_input_manifest.json +3 -0
  25. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/public/staged_features.json +3 -0
  26. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/public/test.csv +3 -0
  27. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/public/train.csv +3 -0
  28. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/staged/public/val.csv +3 -0
  29. SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/train_20260511_185053.log +3 -0
  30. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/gen_20260513_070834.log +3 -0
  31. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/input_snapshot.json +3 -0
  32. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/models_20epochs/id000017786273118721425408/rtf_config.json +3 -0
  33. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/models_20epochs/id000017786273118721425408/rtf_model.pt +3 -0
  34. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/public_gate/normalized_schema_snapshot.json +3 -0
  35. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/public_gate/public_gate_report.json +3 -0
  36. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/public_gate/staged_input_manifest.json +3 -0
  37. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/realtabformer_features.json +3 -0
  38. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf-c19-32759-20260513_070834.csv +3 -0
  39. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/config.json +3 -0
  40. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/generation_config.json +3 -0
  41. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/model.safetensors +3 -0
  42. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/optimizer.pt +3 -0
  43. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/rng_state.pth +3 -0
  44. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/scaler.pt +3 -0
  45. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/scheduler.pt +3 -0
  46. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/trainer_state.json +3 -0
  47. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20000/training_args.bin +3 -0
  48. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20100/config.json +3 -0
  49. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20100/generation_config.json +3 -0
  50. SynthData0523/main/c19/realtabformer/rtf-c19-20260513_062753/rtf_checkpoints/checkpoint-20100/model.safetensors +3 -0
.gitattributes CHANGED
@@ -2692,3 +2692,51 @@ SynthData0523/main/c19/ctgan/ctgan-c19-20260422_031259/public_gate/public_gate_r
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+
2
+ import joblib, pandas as pd
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+ m, meta = joblib.load(r'/work/output-Benchmark-trainonly-v1/c19/forestdiffusion/forest-c19-20260511_185049/forestdiffusion_model.joblib')
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+ # generate:batch_size 为样本数
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+ arr = m.generate(batch_size=int(32759))
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+ df = pd.DataFrame(arr, columns=meta["column_names"])
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+ df.to_csv(r'/work/output-Benchmark-trainonly-v1/c19/forestdiffusion/forest-c19-20260511_185049/forest-c19-32759-20260511_190121.csv', index=False)
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+ print("saved", len(df))
SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_meta_host.json ADDED
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SynthData0523/main/c19/forestdiffusion/forest-c19-20260511_185049/_fd_train.py ADDED
@@ -0,0 +1,36 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+
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+ import os, shutil, json
3
+ with open('/tmp/pgrep', 'w') as _f:
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+ _f.write("#!/usr/bin/env python3\n")
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+ _f.write("import subprocess, sys\n")
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+ _f.write("ppid = sys.argv[-1]\n")
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+ _f.write("out = subprocess.check_output(['ps', '-o', 'pid=', '--ppid', str(ppid)], text=True)\n")
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+ _f.write("print(out, end='')\n")
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+ os.chmod('/tmp/pgrep', 0o755)
10
+ os.environ['PATH'] = '/tmp:' + os.environ.get('PATH', '')
11
+ shutil.copy(r'/work/output-Benchmark-trainonly-v1/c19/forestdiffusion/forest-c19-20260511_185049/_fd_X_host.npy', '/tmp/fd_X.npy')
12
+ with open(r'/work/output-Benchmark-trainonly-v1/c19/forestdiffusion/forest-c19-20260511_185049/_fd_meta_host.json') as f:
13
+ open('/tmp/fd_meta.json','w').write(f.read())
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+
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+ import numpy as np, joblib, json, os
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+ from ForestDiffusion import ForestDiffusionModel
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+ X = np.load("/tmp/fd_X.npy")
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+ with open("/tmp/fd_meta.json") as f:
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+ meta = json.load(f)
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+ cat_indexes = meta["cat_indexes"]
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+ print(
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+ "[ForestDiffusion] train config: "
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+ f"rows={X.shape[0]} cols={X.shape[1]} n_t=2 "
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+ f"n_estimators=1 duplicate_K=1 n_jobs=1 "
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+ f"max_depth=2 xgb_verbosity=0 xgb_nthread=1",
26
+ flush=True,
27
+ )
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+ m = ForestDiffusionModel(
29
+ X, n_t=2, n_estimators=1, duplicate_K=1, n_jobs=1,
30
+ model="xgboost", max_depth=2, tree_method="hist", cat_indexes=cat_indexes,
31
+ verbosity=0, nthread=1,
32
+ )
33
+ joblib.dump((m, meta), "/tmp/fd_model.joblib")
34
+ print("ForestDiffusion train OK")
35
+
36
+ shutil.copy('/tmp/fd_model.joblib', r'/work/output-Benchmark-trainonly-v1/c19/forestdiffusion/forest-c19-20260511_185049/forestdiffusion_model.joblib')
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