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python
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selection_command
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utils/preprocess_dataset.py
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logging.info(f" {fname}")\n
|
python
|
selection_command
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utils/preprocess_dataset.py
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for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
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selection_command
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1,521
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|
utils/preprocess_dataset.py
| 3,077
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logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,522
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|
utils/preprocess_dataset.py
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)\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,523
| 1,913,940
|
utils/preprocess_dataset.py
| 2,979
| 223
|
f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,524
| 1,913,974
|
utils/preprocess_dataset.py
| 2,957
| 245
|
logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,525
| 1,914,007
|
utils/preprocess_dataset.py
| 2,930
| 272
|
writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,526
| 1,914,041
|
utils/preprocess_dataset.py
| 2,899
| 303
|
for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,527
| 1,914,072
|
utils/preprocess_dataset.py
| 2,886
| 316
|
finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,528
| 1,914,105
|
utils/preprocess_dataset.py
| 2,814
| 388
|
logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,529
| 1,914,139
|
utils/preprocess_dataset.py
| 2,779
| 423
|
except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,530
| 1,914,172
|
utils/preprocess_dataset.py
| 2,778
| 424
|
\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,531
| 1,914,205
|
utils/preprocess_dataset.py
| 2,695
| 507
|
writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,532
| 1,914,239
|
utils/preprocess_dataset.py
| 2,694
| 508
|
\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,533
| 1,914,272
|
utils/preprocess_dataset.py
| 2,625
| 577
|
current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,534
| 1,914,305
|
utils/preprocess_dataset.py
| 2,560
| 642
|
current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,535
| 1,914,340
|
utils/preprocess_dataset.py
| 2,559
| 643
|
\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,536
| 1,914,372
|
utils/preprocess_dataset.py
| 2,492
| 710
|
tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,537
| 1,914,406
|
utils/preprocess_dataset.py
| 2,443
| 759
|
episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,538
| 1,914,440
|
utils/preprocess_dataset.py
| 2,426
| 776
|
try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,539
| 1,914,475
|
utils/preprocess_dataset.py
| 2,344
| 858
|
logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,540
| 1,914,518
|
utils/preprocess_dataset.py
| 2,305
| 897
|
if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,541
| 1,914,543
|
utils/preprocess_dataset.py
| 2,245
| 957
|
for i, npy_path in enumerate(episode_source_paths):\n if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,542
| 1,914,577
|
utils/preprocess_dataset.py
| 2,236
| 966
|
try:\n for i, npy_path in enumerate(episode_source_paths):\n if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,543
| 1,914,610
|
utils/preprocess_dataset.py
| 2,205
| 997
|
writer_idx_for_episode = 0\n try:\n for i, npy_path in enumerate(episode_source_paths):\n if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,544
| 1,915,038
|
utils/preprocess_dataset.py
| 2,236
| 966
|
try:\n for i, npy_path in enumerate(episode_source_paths):\n if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,545
| 1,916,014
|
utils/preprocess_dataset.py
| 2,236
| 966
|
try:\n for i, npy_path in enumerate(episode_source_paths):\n if i % 100 == 0 and i > 0:\n logging.info(f" Processed {i}/{num_total_episodes} episodes...")\n try:\n episode_data = np.load(npy_path)\n tf_example = create_tfrecord_example(episode_data)\n\n current_writer = writers[writer_idx_for_episode]\n current_writer.write(tf_example.SerializeToString())\n\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards\n\n except Exception as e:\n logging.error(f"Skipping {npy_path} due to error: {e}")\n finally:\n for writer in writers:\n writer.close()\n logging.info(\n f"TFRecord sharding complete. {num_shards} shards written to {output_dir}."\n )\n logging.info("Generated shard files:")\n for fname in output_filenames:\n logging.info(f" {fname}")\n
|
python
|
selection_command
|
1,546
| 1,936,597
|
utils/preprocess_dataset.py
| 2,245
| 180
|
for i, npy_path in tqdm(enumerate(episode_source_paths), total=num_total_episodes, desc="Processing episodes"):
|
python
|
content
|
1,547
| 1,936,598
|
utils/preprocess_dataset.py
| 130
| 0
|
from tqdm import tqdm\n
|
python
|
content
|
1,548
| 1,943,664
|
utils/preprocess_dataset.py
| 2,655
| 0
| null |
python
|
selection_mouse
|
1,549
| 1,943,666
|
utils/preprocess_dataset.py
| 2,655
| 83
|
\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards
|
python
|
selection_mouse
|
1,550
| 1,943,675
|
utils/preprocess_dataset.py
| 2,655
| 0
| null |
python
|
selection_command
|
1,551
| 1,943,676
|
utils/preprocess_dataset.py
| 2,655
| 83
|
\n writer_idx_for_episode = (writer_idx_for_episode + 1) % num_shards
|
python
|
selection_command
|
1,552
| 1,951,908
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 0
| 0
| null |
shellscript
|
tab
|
1,553
| 1,952,683
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 674
| 0
| null |
shellscript
|
selection_command
|
1,554
| 1,954,912
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 649
| 0
| null |
shellscript
|
selection_command
|
1,555
| 1,955,089
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 625
| 0
| null |
shellscript
|
selection_command
|
1,556
| 1,955,455
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 559
| 0
| null |
shellscript
|
selection_command
|
1,557
| 1,956,514
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 625
| 0
| null |
shellscript
|
selection_command
|
1,558
| 1,956,677
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 649
| 0
| null |
shellscript
|
selection_command
|
1,559
| 1,956,897
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 674
| 0
| null |
shellscript
|
selection_command
|
1,560
| 1,958,123
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 818
| 0
| null |
shellscript
|
selection_command
|
1,561
| 1,958,365
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 818
| 0
|
\n
|
shellscript
|
content
|
1,562
| 1,958,618
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 819
| 0
|
\n
|
shellscript
|
content
|
1,563
| 1,958,715
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 820
| 0
|
\n
|
shellscript
|
content
|
1,564
| 1,959,143
|
sbatch_scripts/preprocess/preprocess_video_to_npy.sbatch
| 821
| 0
|
\npython utils/preprocess_video_to_npy.py --input_path $input_path --output_path $output_path
|
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| 875
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shellscript
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1,586
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TERMINAL
| 0
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|
python utils/preprocess_video_to_npy.py --input_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft/6xx/10fps_160x90 --output_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft_npy/6xx/10fps_160x90
| null |
terminal_command
|
1,587
| 1,963,500
|
TERMINAL
| 0
| 0
|
]633;E;2025-06-25 10:49:56 python utils/preprocess_video_to_npy.py --input_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft/6xx/10fps_160x90 --output_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft_npy/6xx/10fps_160x90;a9a4de27-e0e0-4f7a-a81f-6ae3e98df676]633;C
| null |
terminal_output
|
1,588
| 1,968,028
|
TERMINAL
| 0
| 0
|
^CTraceback (most recent call last):\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/utils/preprocess_video_to_npy.py", line 4, in <module>\r\n import tyro\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/tyro/__init__.py", line 8, in <module>\r\n from . import extras as extras\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/tyro/extras/__init__.py", line 9, in <module>\r\n from .._argparse_formatter import set_accent_color as set_accent_color\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/tyro/_argparse_formatter.py", line 36, in <module>\r\n from rich.columns import Columns\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/rich/columns.py", line 7, in <module>\r\n from .console import Console, ConsoleOptions, RenderableType, RenderResult\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/rich/console.py", line 62, in <module>\r\n from .scope import render_scope\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/rich/scope.py", line 5, in <module>\r\n from .panel import Panel\r\n File "/hkfs/home/project/hk-project-pai00039/tum_ind3695/projects/jafar/.venv_jafar/lib/python3.10/site-packages/rich/panel.py", line 4, in <module>\r\n from .box import ROUNDED, Box\r\n File "<frozen importlib._bootstrap>", line 404, in parent\r\nKeyboardInterrupt\r\n
| null |
terminal_output
|
1,589
| 1,968,068
|
TERMINAL
| 0
| 0
|
\r\n]0;tum_ind3695@hkn1993:~/projects/jafar]633;D;130
| null |
terminal_output
|
1,590
| 1,978,978
|
TERMINAL
| 0
| 0
|
python utils/preprocess_video_to_npy.py --input_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft/6xx/10fps_160x90 --output_path /hkfs/work/workspace/scratch/tum_ind3695-jafa_ws_shared/data/open_ai_minecraft_npy/6xx/10^C
| null |
terminal_command
|
1,591
| 1,978,990
|
TERMINAL
| 0
| 0
|
^C[?2004l\r[?2004h[?2004l\r\r\n]633;E;;a9a4de27-e0e0-4f7a-a81f-6ae3e98df676]633;C]0;tum_ind3695@hkn1993:~/projects/jafar]633;D
| null |
terminal_output
|
1,592
| 1,980,334
|
utils/preprocess_dataset.py
| 0
| 0
| null |
python
|
tab
|
1,593
| 1,984,683
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 0
| 0
| null |
shellscript
|
tab
|
1,594
| 1,985,495
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 689
| 0
| null |
shellscript
|
selection_command
|
1,595
| 1,985,659
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 714
| 0
| null |
shellscript
|
selection_command
|
1,596
| 1,986,392
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 909
| 0
| null |
shellscript
|
selection_command
|
1,597
| 1,987,092
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 909
| 0
|
\npython utils/preprocess_dataset.py --source_data_dir $input_path --output_tfrecords_dir $output_path --num_shards 100
|
shellscript
|
content
|
1,598
| 1,987,100
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 910
| 0
| null |
shellscript
|
selection_command
|
1,599
| 1,988,007
|
sbatch_scripts/preprocess/npy_to_tfrecord_6xx.sbatch
| 917
| 0
| null |
shellscript
|
selection_command
|
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