<jupyter_start><jupyter_text>Decentralized FlowA Flow does not have to be local-only, one can put any Pod to remote(s). In the example below, with the `host` keyword `gpu-pod` is put to a remote machine for parallelization, whereas other pods stay local. Extra file dependencies that need to be uploaded are specified via the `upload_files` keyword.<jupyter_code>#Run this command to install Jina in this notebook 
!pip install jina
import numpy as np
from jina import Flow, Document

f = (Flow()
     .add()
     .add(name='gpu_pod',
          uses='mwu_encoder.yml',
          host='cloud.jina.ai:8000',
          parallel=2,
          upload_files=['mwu_encoder.py'])
     .add())

with f:
    f.index(Document.from_ndarray(np.random.random([10, 100]), output=print))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10375, 'fraction_numerical': 0.0125, 'mean_word_length': 3.8545454545454545, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '465344', 'license': 'Apache-2.0', 'n_tokens_mistral': 260, 'n_tokens_neox': 246, 'n_words': 86, 'path': 'decentralized-flow.ipynb', 'repo_name': 'jina-ai/jupyter-notebooks', 'size': '800'}