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a/SynthData0523/main/n3/realtabformer/rtf-n3-20260505_024350/train_20260505_024350.log b/SynthData0523/main/n3/realtabformer/rtf-n3-20260505_024350/train_20260505_024350.log new file mode 100644 index 0000000000000000000000000000000000000000..4b085b9475585512716014eaa60a88cba7ad99fc --- /dev/null +++ b/SynthData0523/main/n3/realtabformer/rtf-n3-20260505_024350/train_20260505_024350.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cd8591eff961a4518cbb59a39068fe3c6aa4944852877626b0e6512cd9b71d2d +size 140582 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_gen.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..cc773dcad632b3cd990c6e78e582634fc419b797 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_gen.py @@ -0,0 +1,33 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabular_bundle/pipeline_n3" +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_n3/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabbyflow-n3-3918-20260501_005942.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..11c52de385c5406a71ac62f40888a03828ce3be8 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_train.py @@ -0,0 +1,22 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabular_bundle/pipeline_n3" +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/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/gen_20260501_005942.log b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/gen_20260501_005942.log new file mode 100644 index 0000000000000000000000000000000000000000..d618b5545214c9f0244bbc1a457a80ca94330377 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/gen_20260501_005942.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:06fd1176aa6aa493b82c7c6071c805ec456bbdc3f4480bcd635ee8a5b88f784d +size 3026 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/input_snapshot.json b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..3a0cbc32605f1212374c27c5a11c08064d5b6b53 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n3", + "model": "tabbyflow", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-train.csv", + "exists": true, + "size": 211519, + "sha256": "2160a06db2fea02adb0ebb79d8d853bd2544580be301e71f6e8deeb1489a9009" + }, + "val_csv": { + "path": 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b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/_tabbyflow_gen.py @@ -0,0 +1,34 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabular_bundle/pipeline_n3" +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", "") +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +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_n3/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabbyflow-n3-3918-20260505_010451.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..370484d2d9270254590da221c66ff534621af3b4 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/_tabbyflow_train.py @@ -0,0 +1,24 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabular_bundle/pipeline_n3" +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"] = "100" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + 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b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010529/_tabbyflow_gen.py @@ -0,0 +1,34 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010529/tabular_bundle/pipeline_n3" +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", "") +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +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_n3/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010529/tabbyflow-n3-3918-20260505_010913.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010529/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010529/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..aa7a34e96bd38a0f2ed5381a279cd4e71124c2c0 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010529/_tabbyflow_train.py @@ -0,0 +1,24 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010529/tabular_bundle/pipeline_n3" +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"] = "200" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + 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b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010953/_tabbyflow_gen.py @@ -0,0 +1,34 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010953/tabular_bundle/pipeline_n3" +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", "") +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +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_n3/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010953/tabbyflow-n3-3918-20260505_011500.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010953/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010953/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..531f7b0fd0b6b13283c747175d5e72a930b4436a --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010953/_tabbyflow_train.py @@ -0,0 +1,24 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010953/tabular_bundle/pipeline_n3" +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"] = "300" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + 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b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/_tabbyflow_gen.py @@ -0,0 +1,34 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_011539/tabular_bundle/pipeline_n3" +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", "") +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +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_n3/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_011539/tabbyflow-n3-3918-20260505_012459.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..d339202e43c54d57c5d75f24edb3ee87d3d61773 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/_tabbyflow_train.py @@ -0,0 +1,24 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_011539/tabular_bundle/pipeline_n3" +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" +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", +]) diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/gen_20260505_012459.log b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/gen_20260505_012459.log new file mode 100644 index 0000000000000000000000000000000000000000..a72ee686b3f7a180eae89af73e1a4dbbb5fe5a9b --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/gen_20260505_012459.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1cf39a59a5f71e31e1393a0734f603f732945f3e520bf6c0039dd5dd8e983e5b +size 3945 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/input_snapshot.json b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..dbd033f07e808ecf06679c79e8325e7d07ba230f --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/input_snapshot.json @@ -0,0 +1,3 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sha256:85ed37c52f0ea54dfd3a476dcfafff02d61e92783748e5ee9aadfad20578bcb1 +size 31472 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/train_20260505_011539.log b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/train_20260505_011539.log new file mode 100644 index 0000000000000000000000000000000000000000..450c450b77634e42833b718c3452fffdb244b7e4 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_011539/train_20260505_011539.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4f47184a76cf9f55735dffc81b2027701ae0068d673cbc7e1d548b19bc51d37f +size 290236 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_gen.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..c5ee7eba5fc2c39504fce599f74d80267f710f87 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_gen.py @@ -0,0 +1,34 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_012543/tabular_bundle/pipeline_n3" +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", "") +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +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_n3/adapter_efvfm/model_700.pt", + "--num_samples_to_generate", str(int(3918)), +]) +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-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_012543/tabbyflow-n3-3918-20260505_013725.csv") diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_train.py b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..d9444365122d511807df906a17149156fbffe776 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/_tabbyflow_train.py @@ -0,0 +1,24 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_012543/tabular_bundle/pipeline_n3" +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"] = "700" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128") +os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + 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sha256:85ed37c52f0ea54dfd3a476dcfafff02d61e92783748e5ee9aadfad20578bcb1 +size 31472 diff --git a/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/train_20260505_012543.log b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/train_20260505_012543.log new file mode 100644 index 0000000000000000000000000000000000000000..337704e99f50e60daa8b680782e4cea3766db810 --- /dev/null +++ b/SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_012543/train_20260505_012543.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:655d2ba9d46b8601a0ca8d709855e6e01fbb3780e0fbdd89d064ee387d169ac6 +size 405514 diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_sample_r0.py b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_sample_r0.py new file mode 100644 index 0000000000000000000000000000000000000000..3d5fd4e093bb54b433e51d58d71710d7e8411c31 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_sample_r0.py @@ -0,0 +1,66 @@ +import os, sys, subprocess, json +import numpy as np +import pandas as pd + +tabddpm_root = "/workspace/tabddpm/code" +assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}" +env = os.environ.copy() +env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", "")) + +# Reuse the compat wrapper (patches collections.Sequence for skorch) +wrapper = os.path.join(tabddpm_root, "_compat_run.py") +if not os.path.exists(wrapper): + with open(wrapper, "w") as f: + f.write( + "import collections, collections.abc\n" + "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping'," + "'MutableSet','Set','Callable','Iterable','Iterator'):\n" + " if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n" + "import sys, runpy\n" + "sys.argv = sys.argv[1:]\n" + "runpy.run_path(sys.argv[0], run_name='__main__')\n" + ) + +print(f"[TabDDPM] Sampling 3918 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/config_sample_20260501_002035_r0.toml", + "--sample"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) + +# 将 .npy 输出转为 CSV（npy 在 TabDDPM 的 parent_dir，即 npy_dir） +info_path = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/output" +col_names = info.get("column_names", []) + +parts = [] +x_num_path = os.path.join(output_dir, "X_num_train.npy") +x_cat_path = os.path.join(output_dir, "X_cat_train.npy") +y_path = os.path.join(output_dir, "y_train.npy") + +if os.path.exists(x_num_path): + parts.append(np.load(x_num_path, allow_pickle=True)) +if os.path.exists(x_cat_path): + parts.append(np.load(x_cat_path, allow_pickle=True).astype(float)) +if os.path.exists(y_path): + y = np.load(y_path, allow_pickle=True) + parts.append(y.reshape(-1, 1) if y.ndim == 1 else y) + +if parts: + combined = np.concatenate(parts, axis=1) + if col_names and len(col_names) == combined.shape[1]: + df = pd.DataFrame(combined, columns=col_names) + else: + df = pd.DataFrame(combined) + df.to_csv("/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/tabddpm-n3-3918-20260501_002035.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/tabddpm-n3-3918-20260501_002035.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_train.py b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..16db5d0522d0347df0ebb928d10a5cd3e3da9af9 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/_tabddpm_train.py @@ -0,0 +1,32 @@ +import os, sys, subprocess + +tabddpm_root = "/workspace/tabddpm/code" +assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}" +env = os.environ.copy() +env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", "")) + +# Write a wrapper that patches collections.Sequence (removed in Python 3.10+) +# before running pipeline.py - needed because skorch uses old API +wrapper = os.path.join(tabddpm_root, "_compat_run.py") +with open(wrapper, "w") as f: + f.write( + "import collections, collections.abc\n" + "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping'," + "'MutableSet','Set','Callable','Iterable','Iterator'):\n" + " if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n" + "import sys, runpy\n" + "sys.argv = sys.argv[1:]\n" + "runpy.run_path(sys.argv[0], run_name='__main__')\n" + ) + +print(f"[TabDDPM] Training, config=/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config.toml b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..c774736da1e2d6dd06bb2981c8d5d527a7059c43 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/output" +real_data_path = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/data" +model_type = "mlp" +num_numerical_features = 11 +device = "cuda:0" + +[model_params] +d_in = 11 +num_classes = 7 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 1000 +batch_size = 1000 +seed = 0 diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config_sample_20260501_002035_r0.toml b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config_sample_20260501_002035_r0.toml new file mode 100644 index 0000000000000000000000000000000000000000..00d8c1b8acc5120a9558843978768b9f459c23e0 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/config_sample_20260501_002035_r0.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/output" +real_data_path = "/work/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/data" +model_type = "mlp" +num_numerical_features = 11 +device = "cuda:0" + +[model_params] +d_in = 11 +num_classes = 7 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 3918 +batch_size = 1000 +seed = 0 diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/X_num_train.npy b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/X_num_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..94beb8413ef55592710518365965f4cb503523ee --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/X_num_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:093d8f405d764277d5a007953f25ab6466f0857f71f0d8f3c437463fb5bf240a +size 172520 diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/info.json b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/info.json new file mode 100644 index 0000000000000000000000000000000000000000..45d216717b2847b5a467946053f10b0f41c3148b --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/info.json @@ -0,0 +1,39 @@ +{ + "name": "benchmark_dataset", + "task_type": "multiclass", + "n_num_features": 11, + "n_cat_features": 0, + "train_size": 3918, + "num_col_idx": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10 + ], + "cat_col_idx": [], + "target_col_idx": [ + 11 + ], + "column_names": [ + "fixed acidity", + "volatile acidity", + "citric acid", + "residual sugar", + "chlorides", + "free sulfur dioxide", + "total sulfur dioxide", + "density", + "pH", + "sulphates", + "alcohol", + "quality" + ], + "num_classes": 7 +} \ No newline at end of file diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/y_train.npy b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/y_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..1f737a58cd26592130c3604aaa90044a451eb576 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/data/y_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n3", + "model": "tabddpm", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-train.csv", + "exists": true, + "size": 211519, + "sha256": "2160a06db2fea02adb0ebb79d8d853bd2544580be301e71f6e8deeb1489a9009" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-val.csv", + "exists": true, + "size": 26499, + "sha256": "d5ccfee07dfa9e7bdee5bb87642b43828e09f74c6cc0266a3d19d9feaa83106e" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-test.csv", + "exists": true, + "size": 26676, + "sha256": "6f83aacb0d1747b95e287352a7fff5d9d65a1c127b773852346c68485c4ede47" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n3/n3-dataset_profile.json", + "exists": true, + "size": 5235, + "sha256": 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{ + "feature_name": "total sulfur dioxide", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "density", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "pH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "sulphates", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "alcohol", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "quality", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/test.csv b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..db5cd50d3746410ea470625fa2ba2c8e9775cc0d --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/test.csv @@ -0,0 +1,3 @@ +version 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newline at end of file diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/adapter_transforms_applied.json b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/model_input_manifest.json b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a72e8cf5191c7120c3f172ba5d3c5352d63f6c14 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/staged/tabddpm/model_input_manifest.json @@ -0,0 +1,266 @@ +{ + 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"numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 120, + "unique_ratio": 0.030628, + "example_values": [ + "21", + "24", + "41", + "43", + "69" + ] + } + }, + { + "name": "total sulfur dioxide", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 244, + "unique_ratio": 0.062277, + "example_values": [ + "144", + "99", + "114", + "132", + "160" + ] + } + }, + { + "name": "density", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 839, + "unique_ratio": 0.21414, + "example_values": [ + "0.99304", + "0.9947", + "0.99155", + "0.98975", + "0.99705" + ] + } + }, + { + "name": "pH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 100, + "unique_ratio": 0.025523, + "example_values": [ + "3.13", + "3.18", + "3.37", + "3.21", + "3.16" + ] + } + }, + { + "name": "sulphates", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 78, + "unique_ratio": 0.019908, + "example_values": [ + "0.4", + "0.53", + "0.66", + "0.47", + "0.5" + ] + } + }, + { + "name": "alcohol", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 97, + "unique_ratio": 0.024758, + "example_values": [ + "9.6", + "9.7", + "11.7", + "13.4", + "8.8" + ] + } + }, + { + "name": "quality", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 7, + "unique_ratio": 0.001787, + "example_values": [ + "5", + "6", + "7", + "8", + "3" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabddpm/tabddpm-n3-20260501_002012/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/tabddpm-n3-3918-20260501_002035.csv b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/tabddpm-n3-3918-20260501_002035.csv new file mode 100644 index 0000000000000000000000000000000000000000..6584abe44f425549ad98bed078778bd142c6b925 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/tabddpm-n3-3918-20260501_002035.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b8018f08da517f7ed3f7d159a317375a756eb254e6adf63f6b6d7ce19dd3586 +size 753786 diff --git a/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/train_20260501_002012.log b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/train_20260501_002012.log new file mode 100644 index 0000000000000000000000000000000000000000..9be1c25892c24ae25207e9ee3383feac085086c7 --- /dev/null +++ b/SynthData0523/main/n3/tabddpm/tabddpm-n3-20260501_002012/train_20260501_002012.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e5ba05af1754eef93e2c519198aa9c11b3ded64badaf882b13abde890338e8da +size 1067 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_gen.py b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..9def070a662335ac19866533cb6759f328f2a7de --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_004446/tabular_bundle/pipeline_n3" +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_n3/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +# 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-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_004446/tabdiff-n3-3918-20260501_005103.csv") diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_train.py b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..8785d95501d301a66431bbf637bbae9ad95d3ff5 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_004446/tabular_bundle/pipeline_n3" +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/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/gen_20260501_005103.log b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/gen_20260501_005103.log new file mode 100644 index 0000000000000000000000000000000000000000..f7600d692ca0911218d74673978f40a4a59e0e09 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/gen_20260501_005103.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2bb6dc678842c114f1cf611551ea8e33b9c867cd1c303062c178c576a93266a3 +size 4533 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/input_snapshot.json b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..fa87c1e2fb455691eb1aa2a0058c8ad8fdeb448e --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/input_snapshot.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ad40991501777a59a3e8f48ad5dddcb04f9908559ea41a92cff296753d4ac77b +size 1346 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/models_tabdiff/trained.pt 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b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/train_20260501_004446.log new file mode 100644 index 0000000000000000000000000000000000000000..2b845bdab3501091d630a028f052c02dd4ce1b81 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_004446/train_20260501_004446.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cc36ffc16d3a5a3628708bc1337e4733f6eefc2d2eda647495b92de7f796b63e +size 291235 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_gen.py b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..76f2f6d01190680e15e6db23b7eb4d5923a7b8c4 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_175353/tabular_bundle/pipeline_n3" +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_n3/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(3918)), +]) +# 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-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_175353/tabdiff-n3-3918-20260501_175710.csv") diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_train.py b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..33f62823f0bbcc1bf529c511776922b9648c407f --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n3" +src = r"/work/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_175353/tabular_bundle/pipeline_n3" +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/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/gen_20260501_175710.log b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/gen_20260501_175710.log new file mode 100644 index 0000000000000000000000000000000000000000..f245c4a246c56e53c45acea4c78cd9188f904962 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/gen_20260501_175710.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3da9ef17a571d51a9b70d51526cf51996b7395611f280fe207f05ff9177a4626 +size 4621 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/input_snapshot.json b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..751cd5fa38e2fbd0a4680d9f58579382404e5586 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n3", + "model": "tabdiff", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-train.csv", + "exists": true, + "size": 211519, + "sha256": "2160a06db2fea02adb0ebb79d8d853bd2544580be301e71f6e8deeb1489a9009" + }, + "val_csv": { + "path": 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a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/models_tabdiff/trained.pt b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/models_tabdiff/trained.pt new file mode 100644 index 0000000000000000000000000000000000000000..bc319a55a9c7152a1137f968b6fa1c735125ad11 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/models_tabdiff/trained.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:306660b8aad4549267c68390b017e15ddb9bc06a02c80515eb72a97ae31a81eb +size 74 diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/public_gate/normalized_schema_snapshot.json b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..c41fe304503de23190a02e6cbfafa35b3bf134d3 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,259 @@ +{ + 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"public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "success", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_175353/tabdiff-n3-3918-20260501_175710.csv", + "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabdiff/tabdiff-n3-20260501_175353/models_tabdiff/trained.pt" + }, + "timings": { + "train": { + "started_at": "2026-05-01T17:53:53", + "ended_at": "2026-05-01T17:57:10", + "duration_sec": 196.646 + }, + "generate": { + "started_at": "2026-05-01T17:57:10", + "ended_at": "2026-05-01T17:57:20", + "duration_sec": 10.731 + } + } +} \ No newline at end of file diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/staged_features.json b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..08fe4d766d091d2f2ddba724a16b9509cbe4c390 --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/staged_features.json @@ -0,0 +1,62 @@ +[ + { + "feature_name": "fixed acidity", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "volatile acidity", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "citric acid", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "residual sugar", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "chlorides", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "free sulfur dioxide", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "total sulfur dioxide", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "density", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "pH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "sulphates", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "alcohol", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "quality", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/test.csv b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..db5cd50d3746410ea470625fa2ba2c8e9775cc0d --- /dev/null +++ b/SynthData0523/main/n3/tabdiff/tabdiff-n3-20260501_175353/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:19e107152a94432e2a37ff045c00cfe35e1be30208b1553080d7dd0ede256d3b +size 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