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How to use run_in_parallel method in lisa

Best Python code snippet using lisa_python

debugger.py

Source:debugger.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3"""Debugger to save results during training.4"""5from __future__ import annotations6import threading7from queue import Queue8from typing import Optional9from torch import Tensor10from torchkit.core.type import Callable11from torchkit.core.utils import console12__all__ = [13    "Debugger"14]15# MARK: - Debugger16class Debugger:17    """18    19    Attributes:20        every_n_epochs (int):21            Number of epochs between debugging. To disable, set22            `every_n_epochs=0`. Default: `1`.23        run_in_parallel (bool):24            If `True` runs debugging process in a separated thread.25            Default: `True`.26        queue_size (int):27            Debug queue size. It should equal the value of `save_max_n`.28            Default: `20`.29        save_max_n (int):30            Maximum debugging items to be kept. Default: `20`.31        save_to_subdir (bool):32            Save all debug images of the same epoch to a sub-directory naming33		    after the epoch number. Default: `True`.34        image_quality (int):35            Image quality to be saved. Default: `95`.36        verbose (bool):37            If `True` shows the results on the screen. Default: `False`.38        show_max_n (int):39            Maximum debugging items to be shown. Default: `8`.40        show_func (FunCls, optional):41            Function to visualize the debug results. Default: `None`.42        wait_time (float):43            Pause some times before showing the next image. Default: `0.001`.44    """45    46    # MARK: Magic Functions47    48    def __init__(49        self,50        every_n_epochs : int                = 1,51        run_in_parallel: bool               = True,52        queue_size     : Optional[int]      = 20,53        save_max_n     : int                = 20,54        save_to_subdir : bool               = True,55        image_quality  : int                = 95,56        verbose        : bool               = False,57        show_max_n     : int                = 8,58        show_func      : Optional[Callable] = None,59        wait_time      : float              = 0.001,60        *args, **kwargs61    ):62        super().__init__()63        self.every_n_epochs  = every_n_epochs64        self.run_in_parallel = run_in_parallel65        self.queue_size      = queue_size66        self.save_max_n      = save_max_n67        self.save_to_subdir  = save_to_subdir68        self.image_quality   = image_quality69        self.verbose         = verbose70        self.show_max_n      = show_max_n71        self.show_func       = show_func72        self.wait_time       = wait_time73        self.debug_queue     = None74        self.thread_debugger = None75        # self.init_thread()76        77    # MARK: Configure78    79    def init_thread(self):80        if self.run_in_parallel:81            self.debug_queue     = Queue(maxsize=self.queue_size)82            self.thread_debugger = threading.Thread(83                target=self.show_results_parallel84            )85            86    # MARK: Run87    88    def run(89        self,90        input   : Optional[Tensor] = None,91        target  : Optional[Tensor] = None,92        pred	: Optional[Tensor] = None,93        filepath: Optional[str]    = None,94    ):95        """Run the debugger process."""96        if self.show_func:97            if self.thread_debugger:98                self.debug_queue.put([input, target, pred, filepath])99            else:100                self.show_results(101                    input=input, target=target, pred=pred, filepath=filepath102                )103    def run_routine_start(self):104        """Perform operations when run routine starts."""105        self.init_thread()106        if self.thread_debugger and not self.thread_debugger.is_alive():107            self.thread_debugger.start()108    109    def run_routine_end(self):110        """Perform operations when run routine ends."""111        if self.thread_debugger and self.thread_debugger.is_alive():112            self.debug_queue.put([None, None, None, None])113    def is_alive(self) -> bool:114        """Return whether the thread is alive."""115        if self.thread_debugger:116            return self.thread_debugger.is_alive()117        return False118        119    # MARK: Visualize120    def show_results(121        self,122        input   : Optional[Tensor] = None,123        target  : Optional[Tensor] = None,124        pred	: Optional[Tensor] = None,125        filepath: Optional[str]    = None,126        *args, **kwargs127    ):128        self.show_func(129            input         = input,130            target        = target,131            pred          = pred,132            filepath      = filepath,133            image_quality = self.image_quality,134            verbose       = self.verbose,135            show_max_n    = self.show_max_n,136            wait_time     = self.wait_time,137            *args, **kwargs138        )139    def show_results_parallel(self):140        """Draw `result` in a separated thread."""141        while True:142            (input, target, pred, filepath) = self.debug_queue.get()143            if input is None:144                break145            self.show_results(146                input=input, target=target, pred=pred, filepath=filepath147            )148    149        # Stop debugger thread150        self.thread_debugger.join()151    152    # MARK: Utils153    154    def print(self):...

parallel_test.py

Source:parallel_test.py

...15from pyocd.core.helpers import ConnectHelper16from pyocd.probe.pydapaccess import DAPAccess17import threading18import multiprocessing19def run_in_parallel(function, args_list):20    """Create and run a thread in parallel for each element in args_list21    Wait until all threads finish executing. Throw an exception if an exception22    occurred on any of the threads.23    """24    def _thread_helper(idx, func, args):25        """Run the function and set result to True if there was not error"""26        func(*args)27        result_list[idx] = True28    result_list = [False] * len(args_list)29    thread_list = []30    for idx, args in enumerate(args_list):31        thread = threading.Thread(target=_thread_helper,32                                  args=(idx, function, args))33        thread.start()34        thread_list.append(thread)35    for thread in thread_list:36        thread.join()37    for result in result_list:38        if result is not True:39            raise Exception("Running in thread failed")40def run_in_processes(function, args_list):41    """Create and run a processes in parallel for each element in args_list42    Wait until all processes finish executing. Throw an exception if an43    exception occurred on any of the processes.44    """45    process_list = []46    for args in args_list:47        process = multiprocessing.Process(target=function, args=args)48        process.start()49        process_list.append(process)50    error_during_run = False51    for process in process_list:52        process.join()53        if process.exitcode != 0:54            error_during_run = True55    if error_during_run:56        raise Exception("Running in process failed")57def list_boards(id_list):58    """List all connected DAPLink boards repeatedly59    Assert that they are the same as the id list passed in.60    """61    for _ in range(0, 20):62        device_list = DAPAccess.get_connected_devices()63        found_id_list = [device.get_unique_id() for device in device_list]64        found_id_list.sort()65        assert id_list == found_id_list, "Expected %s, got %s" % \66            (id_list, found_id_list)67def search_and_lock(board_id):68    """Repeatedly lock a board with the given ID"""69    for _ in range(0, 20):70        device = DAPAccess.get_device(board_id)71        device.open()72        device.close()73        with ConnectHelper.session_with_chosen_probe(board_id=board_id):74            pass75def open_already_opened(board_id):76    """Open a device that is already open to verify it gives an error"""77    device = DAPAccess.get_device(board_id)78    try:79        device.open()80        assert False81    except DAPAccess.DeviceError:82        pass83def parallel_test():84    """Test that devices can be found and opened in parallel"""85    device_list = DAPAccess.get_connected_devices()86    id_list = [device.get_unique_id() for device in device_list]87    id_list.sort()88    if len(id_list) < 2:89        print("Need at least 2 boards to run the parallel test")90        exit(-1)91    # Goal of this file is to test that:92    # -The process of listing available boards does not interfere93    #  with other processes enumerating, opening, or using boards94    # -Opening and using a board does not interfere with another process95    #  processes which is enumerating, opening, or using boards as96    # long as that is not the current board97    print("Listing board from multiple threads at the same time")98    args_list = [(id_list,) for _ in range(5)]99    run_in_parallel(list_boards, args_list)100    print("Listing board from multiple processes at the same time")101    run_in_processes(list_boards, args_list)102    print("Opening same board from multiple threads at the same time")103    device = DAPAccess.get_device(id_list[0])104    device.open()105    open_already_opened(id_list[0])106    args_list = [(id_list[0],) for _ in range(5)]107    run_in_parallel(open_already_opened, args_list)108    device.close()109    print("Opening same board from multiple processes at the same time")110    device = DAPAccess.get_device(id_list[0])111    device.open()112    open_already_opened(id_list[0])113    args_list = [(id_list[0],) for _ in range(5)]114    run_in_processes(open_already_opened, args_list)115    device.close()116    print("Opening different boards from different threads")117    args_list = [(board_id,) for board_id in id_list]118    run_in_parallel(search_and_lock, args_list)119    print("Opening different boards from different processes")120    run_in_processes(search_and_lock, args_list)121    print("Test passed")122if __name__ == "__main__":123    multiprocessing.set_start_method('spawn')...

subsplit.py

Source:subsplit.py

1#!/bin/python32# Script to run cvat_vsm on a directory of Sentinel-2 products.3#4# Copyright 2021 KappaZeta Ltd.5#6# Licensed under the Apache License, Version 2.0 (the "License");7# you may not use this file except in compliance with the License.8# You may obtain a copy of the License at9#10#     http://www.apache.org/licenses/LICENSE-2.011#12# Unless required by applicable law or agreed to in writing, software13# distributed under the License is distributed on an "AS IS" BASIS,14# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.15# See the License for the specific language governing permissions and16# limitations under the License.17import os18import argparse19import subprocess20def subsplit(path_src):21    """22    Process a Sentinel-2 product.23    """24    subprocess.run(["cm_vsm", "-d", path_src])25def main():26    parser = argparse.ArgumentParser(description='Subsplit all S2 products in .SAFE directories')27    parser.add_argument('s2_path', type=str, help='Path to the directory with S2 products')28    parser.add_argument('-j', '--num-jobs', type=int, default=1, help='Number of jobs to process in parallel')29    args = parser.parse_args()30    # TODO:: Turn into command-line arguments.31    run_in_parallel = True32    paths = []33    # Map reduced product names to shapefile paths.34    for root, dirs, files in os.walk(args.s2_path):35        if root.endswith(".SAFE"):36            paths.append(root)37            print(root)38            if not run_in_parallel:39                subsplit(root)40    # Run all splittings in parallel.41    if run_in_parallel:42        commands = [["cm_vsm", "-d", p] for p in paths]43        for i in range(0, len(commands), args.num_jobs):44            cmds = commands[i:(i + args.num_jobs)]45            procs = [subprocess.Popen(p) for p in cmds]46            for p in procs:47                p.wait()48if __name__ == "__main__":...

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