remote_exec.py

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import os
import subprocess

import numpy as np


def remote_exec(model, execution_context):
    """Executes the given model remotely on the pynq board. The metadata properties
    related to the pynq board have to be set. The execution context contains the
    input values."""
    # TODO fix for multi input-output
    pynq_ip = model.get_metadata_prop("pynq_ip")
    pynq_port = int(model.get_metadata_prop("pynq_port"))
    pynq_username = model.get_metadata_prop("pynq_username")
    pynq_password = model.get_metadata_prop("pynq_password")
    pynq_target_dir = model.get_metadata_prop("pynq_target_dir")
    deployment_dir = model.get_metadata_prop("pynq_deploy_dir")
    inp = execution_context[model.graph.input[0].name]
    # make copy of array before saving it
    inp = inp.copy()
    np.save(os.path.join(deployment_dir, "input.npy"), inp)
    # extracting last folder of absolute path (deployment_dir)
    deployment_folder = os.path.basename(os.path.normpath(deployment_dir))
    # copy input to PYNQ board
    cmd = "sshpass -p {} scp -P{} -r {}/input.npy {}@{}:{}/{}".format(
        pynq_password,
        pynq_port,
        deployment_dir,
        pynq_username,
        pynq_ip,
        pynq_target_dir,
        deployment_folder,
    )
    bash_command = ["/bin/bash", "-c", cmd]
    process_compile = subprocess.Popen(bash_command, stdout=subprocess.PIPE)
    process_compile.communicate()
    cmd = (
        "sshpass -p {} ssh {}@{} -p {} "
        '"cd {}/{}; echo "{}" | '
        'sudo -S python3.6 driver.py --exec_mode="remote_pynq" --batchsize=1"'
    ).format(
        pynq_password,
        pynq_username,
        pynq_ip,
        pynq_port,
        pynq_target_dir,
        deployment_folder,
        pynq_password,
    )
    bash_command = ["/bin/bash", "-c", cmd]
    process_compile = subprocess.Popen(bash_command, stdout=subprocess.PIPE)
    process_compile.communicate()
    cmd = "sshpass -p {} scp -P{} {}@{}:{}/{}/output.npy {}".format(
        pynq_password,
        pynq_port,
        pynq_username,
        pynq_ip,
        pynq_target_dir,
        deployment_folder,
        deployment_dir,
    )
    bash_command = ["/bin/bash", "-c", cmd]
    process_compile = subprocess.Popen(bash_command, stdout=subprocess.PIPE)
    process_compile.communicate()
    outp = np.load("{}/output.npy".format(deployment_dir))
    execution_context[model.graph.output[0].name] = outp