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from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen:

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#!/bin/env python

import sys
import os
import shlex
import subprocess
import json
import configparser
import argparse

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with models.DAG() as dag:
    dataset = 'BREATHE'
    
    # create a task for each table in the BREATHE dataset
    for table_name in list_breathe_tables():  
      destination_uri = 'gs://' + '/'.join((dest_bucket,
                                  '{{ ds_nodash }}', # one day is enough for the full snapshot
                                  table_name,
                                  table_name + '-{{ ds_nodash }}-*.jsonl'))
      

Mistobaan

DECLARE SAMPLE_SIZE INT64 DEFAULT 5;

SELECT *
FROM 
    BREATHE.ncbi_xml 
WHERE
    RAND() < SAMPLE_SIZE/(SELECT COUNT(*) FROM `BREATHE.ncbi_xml`)