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  1. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/_tabbyflow_gen.py +34 -0
  2. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/_tabbyflow_train.py +24 -0
  3. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/gen_20260505_003434.log +3 -0
  4. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/input_snapshot.json +3 -0
  5. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/models_tabbyflow/trained.pt +3 -0
  6. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/public_gate/normalized_schema_snapshot.json +3 -0
  7. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/public_gate/public_gate_report.json +3 -0
  8. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/public_gate/staged_input_manifest.json +3 -0
  9. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/run_config.json +3 -0
  10. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/runtime_result.json +3 -0
  11. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/public/staged_features.json +3 -0
  12. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/public/test.csv +3 -0
  13. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/public/train.csv +3 -0
  14. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/public/val.csv +3 -0
  15. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/tabbyflow/adapter_report.json +3 -0
  16. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/tabbyflow/adapter_transforms_applied.json +3 -0
  17. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/staged/tabbyflow/model_input_manifest.json +3 -0
  18. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabbyflow-m4-2217-20260505_003434.csv +3 -0
  19. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabbyflow_train_meta.json +3 -0
  20. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_cat_test.npy +3 -0
  21. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_cat_train.npy +3 -0
  22. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_cat_val.npy +3 -0
  23. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_num_test.npy +3 -0
  24. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_num_train.npy +3 -0
  25. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/X_num_val.npy +3 -0
  26. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/info.json +3 -0
  27. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/real.csv +3 -0
  28. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/test.csv +3 -0
  29. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/val.csv +3 -0
  30. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/y_test.npy +3 -0
  31. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/y_train.npy +3 -0
  32. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4/y_val.npy +3 -0
  33. syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/train_20260505_003100.log +3 -0
syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/_tabbyflow_gen.py ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+
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+ import os, shutil, subprocess, sys
3
+ root = r"/workspace/ef-vfm"
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+ name = r"pipeline_m4"
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+ src = r"/work/output-Benchmark-trainonly-v1/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4"
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+ dst_data = os.path.join(root, "data", name)
7
+ shutil.rmtree(dst_data, ignore_errors=True)
8
+ shutil.copytree(src, dst_data)
9
+ dst_syn = os.path.join(root, "synthetic", name)
10
+ os.makedirs(dst_syn, exist_ok=True)
11
+ for fn in ("real.csv", "test.csv", "val.csv"):
12
+ shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
13
+ os.chdir(root)
14
+ os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
15
+ os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128")
16
+ subprocess.check_call([
17
+ sys.executable, "main.py",
18
+ "--dataname", name, "--mode", "test", "--gpu", "0",
19
+ "--no_wandb", "--exp_name", r"adapter_efvfm",
20
+ "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_m4/adapter_efvfm/model_200.pt",
21
+ "--num_samples_to_generate", str(int(2217)),
22
+ ])
23
+ base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm")
24
+ best = None
25
+ best_t = -1.0
26
+ for r, _, files in os.walk(base):
27
+ if "samples.csv" in files:
28
+ p = os.path.join(r, "samples.csv")
29
+ t = os.path.getmtime(p)
30
+ if t > best_t:
31
+ best_t, best = t, p
32
+ if not best:
33
+ raise SystemExit("tabbyflow: no samples.csv in " + base)
34
+ shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabbyflow-m4-2217-20260505_003434.csv")
syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/_tabbyflow_train.py ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+ import os, shutil, subprocess, sys
3
+ root = r"/workspace/ef-vfm"
4
+ name = r"pipeline_m4"
5
+ src = r"/work/output-Benchmark-trainonly-v1/m4/tabbyflow/tabbyflow-m4-20260505_003100/tabular_bundle/pipeline_m4"
6
+ os.makedirs(os.path.join(root, "data", name), exist_ok=True)
7
+ dst_data = os.path.join(root, "data", name)
8
+ dst_syn = os.path.join(root, "synthetic", name)
9
+ shutil.rmtree(dst_data, ignore_errors=True)
10
+ shutil.copytree(src, dst_data)
11
+ os.makedirs(dst_syn, exist_ok=True)
12
+ for fn in ("real.csv", "test.csv", "val.csv"):
13
+ shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
14
+ os.chdir(root)
15
+ os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
16
+ os.environ["EFVFM_SMOKE_STEPS"] = "200"
17
+ os.environ["EFVFM_ADAPTER_TRAIN"] = "1"
18
+ os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128")
19
+ os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512")
20
+ subprocess.check_call([
21
+ sys.executable, "main.py",
22
+ "--dataname", name, "--mode", "train", "--gpu", "0",
23
+ "--no_wandb", "--exp_name", r"adapter_efvfm",
24
+ ])
syntheticSuccess/m4/tabbyflow/tabbyflow-m4-20260505_003100/gen_20260505_003434.log ADDED
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