<jupyter_start><jupyter_text>Run Regression Tasks<jupyter_code>import nbloader
from nips_reg_config_2 import worker_class
if __name__ == "__main__": 
    print ("Packages loaded.")<jupyter_output>Packages loaded.<jupyter_text>Initiate Workers<jupyter_code>nWorker = 8
maxGPU  = 2
WORKERS = ['']*nWorker 
for i in range(nWorker):
    WORKERS[i] = worker_class(_idx=i,_maxProcessID=nWorker,_maxGPU=maxGPU
                              ,_name='Worker_%02d'%(i),_VERBOSE=False)
    print ("[%d/%d] worker initiated."%(i,nWorker))<jupyter_output>[0/8] worker initiated.
[1/8] worker initiated.
[2/8] worker initiated.
[3/8] worker initiated.
[4/8] worker initiated.
[5/8] worker initiated.
[6/8] worker initiated.
[7/8] worker initiated.<jupyter_text>Start Workers<jupyter_code>for i in range(nWorker):
    WORKERS[i].start(); # Start process<jupyter_output>Starting [Worker_00]
Starting [Worker_01]
Starting [Worker_02]
Starting [Worker_03]
Starting [Worker_04]
Starting [Worker_05]
Starting [Worker_06]
Starting [Worker_07]
processID:[0/8] GPU_ID:[0] #Config:[1]
===[0/1]===
processID:[1/8] GPU_ID:[1] #Config:[1]
===[0/1]===
processID:[2/8] GPU_ID:[0] #Config:[1]
===[0/1]===
processID:[3/8] GPU_ID:[1] #Config:[1]
===[0/1]===
processID:[4/8] GPU_ID:[0] #Config:[1]
===[0/1]===
processID:[5/8] GPU_ID:[1] #Config:[1]
===[0/1]===
processID:[6/8] GPU_ID:[0] #Config:[1]
===[0/1]===
processID:[7/8] GPU_ID:[1] #Config:[1]
===[0/1]===
WARNING:tensorflow:From <string>:131: calling softmax (from tensorflow.python.ops.nn_ops) with dim is deprecated and will be removed in a future version.
Instructions for updating:
dim is deprecated, use axis instead
WARNING:tensorflow:From <string>:131: calling softmax (from tensorflow.python.ops.nn_ops) with dim is deprecated and will be removed in a future version.
Instructions for updating:
dim is deprecated, use axi[...]
{'fraction_non_alphanumeric': 0.1759956942949408, 'fraction_numerical': 0.04897739504843918, 'mean_word_length': 6.0150943396226415, 'pattern_counts': {'":': 1, '<': 12, '<?xml version=': 0, '>': 12, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '240268', 'license': 'MIT', 'n_tokens_mistral': 760, 'n_tokens_neox': 698, 'n_words': 162, 'path': 'code/nips_reg_run_2.ipynb', 'repo_name': 'sjchoi86/choicenet', 'size': '1858'}