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Download and organise DLRM data automatically #93

Merged
merged 9 commits into from
Aug 7, 2024
Merged

Download and organise DLRM data automatically #93

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434ba23
incorporated model and dataset downloads
anandhu-eng Jul 19, 2024
19862dd
Updation for path not given scenario
anandhu-eng Jul 19, 2024
9412243
Merge branch 'mlperf-inference' into dlrm_data_org
arjunsuresh Jul 19, 2024
b23f749
Merge branch 'mlperf-inference' into dlrm_data_org
arjunsuresh Jul 19, 2024
f52ed25
Merge branch 'mlperf-inference' into dlrm_data_org
anandhu-eng Aug 5, 2024
f0bd463
fixed folder structure + generation of run cmd from customize.py
anandhu-eng Aug 7, 2024
ca8a6f8
Merge branch 'mlperf-inference' into dlrm_data_org
anandhu-eng Aug 7, 2024
2a8fb98
cleaned empty line
anandhu-eng Aug 7, 2024
1dec20a
DLRM - added manual input of raw data
anandhu-eng Aug 7, 2024
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14 changes: 14 additions & 0 deletions script/get-dlrm-data-mlperf-inference/_cm.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,20 @@ new_env_keys:
- DLRM_DATA_PATH
input_mapping:
dlrm_data_path: CM_DLRM_DATA_PATH

prehook_deps:
- tags: get,ml-model,dlrm,_pytorch
update_tags_from_env_with_prefix:
download_path: CM_DLRM_DATA_PATH
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_ missing? Also this uses a list right?

enable_if_env:
CM_DLRM_MODEL_DOWNLOAD:
- "on"
- tags: get,dataset,preprocessed,criteo,_mlc
update_tags_from_env_with_prefix:
output_dir: CM_DLRM_DATA_PATH
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Is output_dir a tag?

skip_if_env:
CM_DLRM_DATASET_DOWNLOAD:
- "on"
variations:
nvidia:
group: implementation
Expand Down
59 changes: 35 additions & 24 deletions script/get-dlrm-data-mlperf-inference/customize.py
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Expand Up @@ -9,7 +9,9 @@ def preprocess(i):

dlrm_data_path = env.get('CM_DLRM_DATA_PATH', env.get('DLRM_DATA_PATH', ''))
if dlrm_data_path == '' or not os.path.exists(dlrm_data_path):
return {'return': 1, 'error': f'Please input a valid path as --dlrm_data_path'}
print(f'Data path is not given as input through --dlrm_data_path. Using the cache directory:{os.getcwd()} as the data path'}
dlrm_data_path = os.getcwd()

meta = i['meta']

script_path=i['run_script_input']['path']
Expand All @@ -22,40 +24,46 @@ def preprocess(i):

if variation == "nvidia":
if not os.path.exists(os.path.join(dlrm_data_path, "model")):
return {'return': 1, 'error': f'model directory is missing inside {dlrm_data_path}'}
print(f'model directory is missing inside {dlrm_data_path}')
env['CM_DLRM_MODEL_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo")):
return {'return': 1, 'error': f'criteo directory is missing inside {dlrm_data_path}'}
print(f'criteo directory is missing inside {dlrm_data_path}')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "model", "model_weights")):
return {'return': 1, 'error': f'model_weights directory is missing inside {dlrm_data_path}/model'}
print(f'model_weights directory is missing inside {dlrm_data_path}/model')
env['CM_DLRM_MODEL_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23")):
return {'return': 1, 'error': f'day23 directory is missing inside {dlrm_data_path}/day23'}
print(f'day23 directory is missing inside {dlrm_data_path}/day23')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32")):
return {'return': 1, 'error': f'fp32 directory is missing inside {dlrm_data_path}/day23'}

print(f'fp32 directory is missing inside {dlrm_data_path}/criteo/day23')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot.npz")) and not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot_unpacked")):
return {'return': 1, 'error': f'day_23_sparse_multi_hot.npz is missing inside {dlrm_data_path}/criteo/day23/fp32'}
print(f'day_23_sparse_multi_hot.npz or day_23_sparse_multi_hot_unpacked is missing inside {dlrm_data_path}/criteo/day23/fp32')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_dense.npy")):
return {'return': 1, 'error': f'day_23_dense.npy is missing inside {dlrm_data_path}/criteo/day23/fp32'}
print(f'day_23_dense.npy is missing inside {dlrm_data_path}/criteo/day23/fp32')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_labels.npy")):
return {'return': 1, 'error': f'day_23_labels.npy is missing inside {dlrm_data_path}/criteo/day23/fp32'}
print(f'day_23_labels.npy is missing inside {dlrm_data_path}/criteo/day23/fp32')
env['CM_DLRM_DATASET_DOWNLOAD'] = True
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "raw_data")):
return {'return': 1, 'error': f'raw_data is missing inside {dlrm_data_path}/criteo/day23'}


if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot_unpacked")):
os.system(f"unzip {os.path.join(dlrm_data_path, 'criteo', 'day23', 'fp32', 'day_23_sparse_multi_hot.npz')} -d {os.path.join(dlrm_data_path, 'criteo', 'day23', 'fp32', 'day_23_sparse_multi_hot_unpacked')}")

xsep = ' && '
print(f'raw_data is missing inside {dlrm_data_path}/criteo/day23')
env['CM_DLRM_DATASET_DOWNLOAD'] = True

run_cmd = ''
if os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot.npz")):
file_path = os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot.npz")
run_cmd = ("echo {} {} | md5sum -c").format('c46b7e31ec6f2f8768fa60bdfc0f6e40', file_path)
xsep = ' && '

if run_cmd != '':
run_cmd += xsep
if env['CM_DLRM_DATASET_DOWNLOAD'] != True:
if not os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot_unpacked")):
os.system(f"unzip {os.path.join(dlrm_data_path, 'criteo', 'day23', 'fp32', 'day_23_sparse_multi_hot.npz')} -d {os.path.join(dlrm_data_path, 'criteo', 'day23', 'fp32', 'day_23_sparse_multi_hot_unpacked')}")

if os.path.exists(os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot.npz")) or env['CM_DLRM_DATASET_DOWNLOAD'] == True:
file_path = os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_sparse_multi_hot.npz")
run_cmd = xsep + ("echo {} {} | md5sum -c").format('c46b7e31ec6f2f8768fa60bdfc0f6e40', file_path)

file_path = os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_dense.npy")
run_cmd += ("echo {} {} | md5sum -c").format('cdf7af87cbc7e9b468c0be46b1767601', file_path)
run_cmd += xsep + ("echo {} {} | md5sum -c").format('cdf7af87cbc7e9b468c0be46b1767601', file_path)

file_path = os.path.join(dlrm_data_path, "criteo", "day23", "fp32", "day_23_labels.npy")
run_cmd += xsep + ("echo {} {} | md5sum -c").format('dd68f93301812026ed6f58dfb0757fa7', file_path)
Expand All @@ -74,6 +82,9 @@ def postprocess(i):

env = i['env']

env['CM_GET_DEPENDENT_CACHED_PATH'] = env.get('CM_DLRM_DATA_PATH', env['DLRM_DATA_PATH'])
if env.get('CM_DLRM_DATA_PATH', '') == '' and env.get('DLRM_DATA_PATH', '') == '':
env['CM_DLRM_DATA_PATH'] = os.getcwd()
else:
env['CM_GET_DEPENDENT_CACHED_PATH'] = env.get('CM_DLRM_DATA_PATH', env['DLRM_DATA_PATH'])

return {'return':0}
19 changes: 19 additions & 0 deletions script/get-dlrm-data-mlperf-inference/run.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -23,5 +23,24 @@ function run() {
fi
}

if [ "$CM_DLRM_DATASET_DOWNLOAD" = true ]; then
if [ -n "$CM_DLRM_DATA_PATH" ]; then
cp -r "$CM_CRITEO_PREPROCESSED_PATH" "$CM_DLRM_DATA_PATH/criteo/day23/fp32"
else
cp -r "$CM_CRITEO_PREPROCESSED_PATH" "$(pwd)/criteo/day23/fp32"
fi
exit_if_error
fi

if [ "$CM_DLRM_MODEL_DOWNLOAD" = true ]; then
if [ -n "$CM_DLRM_DATA_PATH" ]; then
cp -r "$CM_ML_MODEL_FILE_WITH_PATH" "$CM_DLRM_DATA_PATH/model"
else
cp -r "$CM_ML_MODEL_FILE_WITH_PATH" "$(pwd)/model"
fi
exit_if_error
fi


#Add your run commands here...
run "$CM_RUN_CMD"
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