def solr_documents_from_paths(paths, classifications=None):
    CHUNK_SIZE = 20
    documents = []

    for i in xrange(0, len(paths), CHUNK_SIZE):
        paths_chunk = paths[i:i + CHUNK_SIZE]

        if classifications:
            q = ' OR '.join(['%s:[.7 TO *]' % key
                             for key in classifications])
        else:
            q = '*:*'

        r = requests.get(os.environ['IMAGE_SPACE_SOLR'] + '/select', params={
            'wt': 'json',
            'q': q,
            'fq': ['mainType:image',
                   'resourcename_t_md:(%s)' %
                   ' '.join('%s' % os.path.basename(p).upper() for p in paths_chunk)],
            'rows': str(CHUNK_SIZE)
        }, verify=False)

        documents += r.json()['response']['docs']

    return documents
Neural Network (RNN) Configuration Settings
dataset/ETHPy150Open memex-explorer/image_space/imagespace/server/__init__.py/solr_documents_from_paths--crossover with--dataset/ETHPy150Open dandxy89/rf_helicopter/Model/Q_Learning_Agent.py/Q_Neural_Network.config