diff --git a/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_gen.py b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..8935a8344a540dca53070c799fcd1e548c1e439b --- /dev/null +++ b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_gen.py @@ -0,0 +1,33 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/c9/tabbyflow/tabbyflow-c9-20260420_074328/tabular_bundle/pipeline_ds" +dst_data = os.path.join(root, "data", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +dst_syn = os.path.join(root, "synthetic", name) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", + "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_ds/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(26215)), +]) +base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm") +best = None +best_t = -1.0 +for r, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(r, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t, best = t, p +if not best: + raise SystemExit("tabbyflow: no samples.csv in " + base) +shutil.copy(best, r"/work/output-SpecializedModels/c9/tabbyflow/tabbyflow-c9-20260420_074328/tabbyflow-c9-26215-20260420_075137.csv") diff --git a/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_train.py b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..1e28a6a9ac143f0b2f8027356924d7d45f6e63ee --- /dev/null +++ b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/_tabbyflow_train.py @@ -0,0 +1,22 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/c9/tabbyflow/tabbyflow-c9-20260420_074328/tabular_bundle/pipeline_ds" +os.makedirs(os.path.join(root, "data", name), exist_ok=True) +dst_data = os.path.join(root, "data", name) +dst_syn = os.path.join(root, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["EFVFM_SMOKE_STEPS"] = "500" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", +]) diff --git a/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/input_snapshot.json b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..0d2283727062ca949776ae7449052ad603429e8c --- /dev/null +++ b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/input_snapshot.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e9a8bc15a9e1d4052c750ed12cac437cdf0a2d846cd4f1e827aa1537f71757be +size 1351 diff --git a/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/models_tabbyflow/trained.pt b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/models_tabbyflow/trained.pt new file mode 100644 index 0000000000000000000000000000000000000000..f063a878c470d9d40f79db79881596e1e497dffd --- /dev/null +++ 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b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/train_20260420_074328.log new file mode 100644 index 0000000000000000000000000000000000000000..714101eae3e395d5adbc1a840dd50a8987b8e576 --- /dev/null +++ b/syntheticSuccess/c9/tabbyflow/tabbyflow-c9-20260420_074328/train_20260420_074328.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8376993418255e142b7736f2f03570ddfdae3421dcc60a59bf0966e70ddc5187 +size 816135 diff --git a/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_gen.py b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..c0a8ea7b8597b0719fe0b86f90f33cf89320dbfb --- /dev/null +++ b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/c9/tabdiff/tabdiff-c9-20260420_073501/tabular_bundle/pipeline_ds" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", + "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_ds/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(26215)), +]) +# test() 写入 tabdiff/result////samples.csv +import glob as g +base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable") +best = None +best_t = -1.0 +for root, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(root, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t = t + best = p +if not best: + raise SystemExit("tabdiff: no samples.csv under " + base) +shutil.copy(best, r"/work/output-SpecializedModels/c9/tabdiff/tabdiff-c9-20260420_073501/tabdiff-c9-26215-20260420_074317.csv") diff --git a/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_train.py b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..d72ce063587a1fd0c6b86c2a421f22ea6087eac9 --- /dev/null +++ b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/c9/tabdiff/tabdiff-c9-20260420_073501/tabular_bundle/pipeline_ds" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["TABDIFF_SMOKE_STEPS"] = "500" +os.environ["TABDIFF_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", +]) diff --git a/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/input_snapshot.json b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..4deadbc80148b841c48961a94c3466e3be9667f5 --- /dev/null +++ b/syntheticSuccess/c9/tabdiff/tabdiff-c9-20260420_073501/input_snapshot.json @@ -0,0 +1,3 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-0,0 +1,33 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/m1/tabbyflow/tabbyflow-m1-20260420_092230/tabular_bundle/pipeline_ds" +dst_data = os.path.join(root, "data", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +dst_syn = os.path.join(root, "synthetic", name) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", + "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_ds/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(1200)), +]) +base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm") +best = None +best_t = -1.0 +for r, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(r, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t, best = t, p +if not best: + raise SystemExit("tabbyflow: no samples.csv in " + base) +shutil.copy(best, r"/work/output-SpecializedModels/m1/tabbyflow/tabbyflow-m1-20260420_092230/tabbyflow-m1-1200-20260420_092929.csv") diff --git a/syntheticSuccess/m1/tabbyflow/tabbyflow-m1-20260420_092230/_tabbyflow_train.py b/syntheticSuccess/m1/tabbyflow/tabbyflow-m1-20260420_092230/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..fa82de04d7854e0ab6152ed8d96fc44db9b509df --- /dev/null +++ b/syntheticSuccess/m1/tabbyflow/tabbyflow-m1-20260420_092230/_tabbyflow_train.py @@ -0,0 +1,22 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/m1/tabbyflow/tabbyflow-m1-20260420_092230/tabular_bundle/pipeline_ds" +os.makedirs(os.path.join(root, "data", name), exist_ok=True) +dst_data = os.path.join(root, "data", name) +dst_syn = os.path.join(root, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["EFVFM_SMOKE_STEPS"] = "500" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", +]) diff --git a/syntheticSuccess/m1/tabbyflow/tabbyflow-m1-20260420_092230/input_snapshot.json b/syntheticSuccess/m1/tabbyflow/tabbyflow-m1-20260420_092230/input_snapshot.json new file mode 100644 index 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sha256:1aa396f1317b1e24c195c9f00a0a48d5511283735e1689bf7e307cbb9f3385f0 +size 288242 diff --git a/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_gen.py b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..dff629bf8c3a8956d77d7551120478b70f230e70 --- /dev/null +++ b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/m1/tabdiff/tabdiff-m1-20260420_091055/tabular_bundle/pipeline_ds" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", + "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_ds/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(1200)), +]) +# test() 写入 tabdiff/result////samples.csv +import glob as g +base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable") +best = None +best_t = -1.0 +for root, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(root, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t = t + best = p +if not best: + raise SystemExit("tabdiff: no samples.csv under " + base) +shutil.copy(best, r"/work/output-SpecializedModels/m1/tabdiff/tabdiff-m1-20260420_091055/tabdiff-m1-1200-20260420_092135.csv") diff --git a/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_train.py b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..78cbacf4a4f46cbf6a3ce1a24fa3cbec7eacfc4e --- /dev/null +++ b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_ds" +src = r"/work/output-SpecializedModels/m1/tabdiff/tabdiff-m1-20260420_091055/tabular_bundle/pipeline_ds" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["TABDIFF_SMOKE_STEPS"] = "500" +os.environ["TABDIFF_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", +]) diff --git a/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/input_snapshot.json b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..810c8952bca2d70b5d359516585b3265510c5806 --- /dev/null +++ b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/input_snapshot.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:79bb2d6029544eb608c702faa48d727af93ea1be583717a65dff83302f759e49 +size 1348 diff --git a/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/models_tabdiff/trained.pt b/syntheticSuccess/m1/tabdiff/tabdiff-m1-20260420_091055/models_tabdiff/trained.pt new file mode 100644 index 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0000000000000000000000000000000000000000..e8073d5f9d806d95c7518489a19d592ace16668d --- /dev/null +++ b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_gen.py @@ -0,0 +1,8 @@ + +import joblib, pandas as pd +m, meta = joblib.load(r'/work/output-SpecializedModels/m10/forestdiffusion/forest-m10-20260425_200135/forestdiffusion_model.joblib') +# generate：batch_size 为样本数 +arr = m.generate(batch_size=int(1600)) +df = pd.DataFrame(arr, columns=meta["column_names"]) +df.to_csv(r'/work/output-SpecializedModels/m10/forestdiffusion/forest-m10-20260425_200135/forest-m10-1600-20260426_101122.csv', index=False) +print("saved", len(df)) diff --git a/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_meta_host.json b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_meta_host.json new file mode 100644 index 0000000000000000000000000000000000000000..ea34eb7c3f0250aeca8614bef2a428e6e33468ed --- /dev/null +++ b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_meta_host.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d1d786109c8a271d69ddb91e5e7e99adf58472f8d1938924bd2fc5d3e7ad9e8c +size 288 diff --git a/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_train.py b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_train.py new file mode 100644 index 0000000000000000000000000000000000000000..e0ee934199cbad83e7da6d7242a2c81d09a15eb0 --- /dev/null +++ b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/_fd_train.py @@ -0,0 +1,20 @@ + +import shutil, json +shutil.copy(r'/work/output-SpecializedModels/m10/forestdiffusion/forest-m10-20260425_200135/_fd_X_host.npy', '/tmp/fd_X.npy') +with open(r'/work/output-SpecializedModels/m10/forestdiffusion/forest-m10-20260425_200135/_fd_meta_host.json') as f: + open('/tmp/fd_meta.json','w').write(f.read()) + +import numpy as np, joblib, json, os +from ForestDiffusion import ForestDiffusionModel +X = np.load("/tmp/fd_X.npy") +with open("/tmp/fd_meta.json") as f: + meta = json.load(f) +cat_indexes = meta["cat_indexes"] +m = ForestDiffusionModel( + X, n_t=20, n_estimators=100, duplicate_K=20, n_jobs=2, + model="xgboost", max_depth=6, tree_method="hist", cat_indexes=cat_indexes, +) +joblib.dump((m, meta), "/tmp/fd_model.joblib") +print("ForestDiffusion train OK") + +shutil.copy('/tmp/fd_model.joblib', r'/work/output-SpecializedModels/m10/forestdiffusion/forest-m10-20260425_200135/forestdiffusion_model.joblib') diff --git a/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/forest-m10-1600-20260426_101122.csv b/syntheticSuccess/m10/forestdiffusion/forest-m10-20260425_200135/forest-m10-1600-20260426_101122.csv new file mode 100644 index 0000000000000000000000000000000000000000..3183c6d25e877f1c2af0bb30555ac3b4072a20a1 --- /dev/null +++ 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