mirror of
https://github.com/open-compass/opencompass.git
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[Sync] Use finally to clean up temp files (#337)
This commit is contained in:
Tong Gao
GitHub
parent
2cd994c3d1
commit
ce65d3393b
@ -86,65 +86,70 @@ class DLCRunner(BaseRunner):
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# Dump task config to file
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mmengine.mkdir_or_exist('tmp/')
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param_file = f'tmp/{os.getpid()}_params.py'
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task_cfg.dump(param_file)
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try:
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task_cfg.dump(param_file)
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# Build up DLC command
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pwd = os.getcwd()
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shell_cmd = (f'source {self.aliyun_cfg["bashrc_path"]}; '
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f'conda activate {self.aliyun_cfg["conda_env_name"]}; '
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f'cd {pwd}; '
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'{task_cmd}')
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# Build up DLC command
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pwd = os.getcwd()
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shell_cmd = (
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f'source {self.aliyun_cfg["bashrc_path"]}; '
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f'conda activate {self.aliyun_cfg["conda_env_name"]}; '
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f'cd {pwd}; '
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'{task_cmd}')
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tmpl = ('dlc create job'
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f" --command '{shell_cmd}'"
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f' --name {task_name[:512]}'
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' --kind BatchJob'
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f" -c {self.aliyun_cfg['dlc_config_path']}"
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f" --workspace_id {self.aliyun_cfg['workspace_id']}"
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' --worker_count 1'
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f' --worker_cpu {max(num_gpus * 6, 8)}'
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f' --worker_gpu {num_gpus}'
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f' --worker_memory {max(num_gpus * 32, 48)}'
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f" --worker_image {self.aliyun_cfg['worker_image']}"
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' --interactive')
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get_cmd = partial(task.get_command, cfg_path=param_file, template=tmpl)
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cmd = get_cmd()
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tmpl = ('dlc create job'
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f" --command '{shell_cmd}'"
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f' --name {task_name[:512]}'
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' --kind BatchJob'
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f" -c {self.aliyun_cfg['dlc_config_path']}"
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f" --workspace_id {self.aliyun_cfg['workspace_id']}"
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' --worker_count 1'
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f' --worker_cpu {max(num_gpus * 6, 8)}'
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f' --worker_gpu {num_gpus}'
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f' --worker_memory {max(num_gpus * 32, 48)}'
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f" --worker_image {self.aliyun_cfg['worker_image']}"
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' --interactive')
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get_cmd = partial(task.get_command,
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cfg_path=param_file,
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template=tmpl)
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cmd = get_cmd()
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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# Run command with retry
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if self.debug:
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stdout = None
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else:
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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# Run command with retry
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if self.debug:
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stdout = None
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else:
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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if random_sleep:
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time.sleep(random.randint(0, 10))
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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retry = self.retry
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output_paths = task.get_output_paths()
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while self._job_failed(result.returncode, output_paths) and retry > 0:
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retry -= 1
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if random_sleep:
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time.sleep(random.randint(0, 10))
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# Re-generate command to refresh ports.
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cmd = get_cmd()
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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# Clean up
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os.remove(param_file)
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retry = self.retry
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output_paths = task.get_output_paths()
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while self._job_failed(result.returncode,
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output_paths) and retry > 0:
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retry -= 1
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if random_sleep:
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time.sleep(random.randint(0, 10))
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# Re-generate command to refresh ports.
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cmd = get_cmd()
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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finally:
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# Clean up
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os.remove(param_file)
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return task_name, result.returncode
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def _job_failed(self, return_code: int, output_paths: List[str]) -> bool:
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@ -62,15 +62,17 @@ class LocalRunner(BaseRunner):
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# get cmd
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mmengine.mkdir_or_exist('tmp/')
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param_file = f'tmp/{os.getpid()}_params.py'
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task.cfg.dump(param_file)
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cmd = task.get_command(cfg_path=param_file,
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template='{task_cmd}')
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# run in subprocess if starts with torchrun etc.
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if cmd.startswith('python'):
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task.run()
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else:
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subprocess.run(cmd, shell=True, text=True)
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os.remove(param_file)
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try:
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task.cfg.dump(param_file)
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cmd = task.get_command(cfg_path=param_file,
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template='{task_cmd}')
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# run in subprocess if starts with torchrun etc.
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if cmd.startswith('python'):
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task.run()
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else:
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subprocess.run(cmd, shell=True, text=True)
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finally:
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os.remove(param_file)
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status.append((task_name, 0))
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else:
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import torch
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@ -141,31 +143,34 @@ class LocalRunner(BaseRunner):
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# Dump task config to file
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mmengine.mkdir_or_exist('tmp/')
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param_file = f'tmp/{os.getpid()}_{index}_params.py'
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task.cfg.dump(param_file)
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try:
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task.cfg.dump(param_file)
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# Build up slurm command
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tmpl = 'CUDA_VISIBLE_DEVICES=' + ','.join(str(i) for i in gpu_ids)
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tmpl += ' {task_cmd}'
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get_cmd = partial(task.get_command, cfg_path=param_file, template=tmpl)
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cmd = get_cmd()
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# Build up slurm command
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tmpl = 'CUDA_VISIBLE_DEVICES=' + ','.join(str(i) for i in gpu_ids)
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tmpl += ' {task_cmd}'
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get_cmd = partial(task.get_command,
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cfg_path=param_file,
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template=tmpl)
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cmd = get_cmd()
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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# Run command
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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# Run command
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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if result.returncode != 0:
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logger.warning(f'task {task_name} fail, see\n{out_path}')
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# Clean up
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os.remove(param_file)
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if result.returncode != 0:
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logger.warning(f'task {task_name} fail, see\n{out_path}')
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finally:
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# Clean up
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os.remove(param_file)
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return task_name, result.returncode
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@ -91,60 +91,64 @@ class SlurmRunner(BaseRunner):
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# Dump task config to file
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mmengine.mkdir_or_exist('tmp/')
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param_file = f'tmp/{os.getpid()}_params.py'
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task_cfg.dump(param_file)
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try:
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task_cfg.dump(param_file)
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# Build up slurm command
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tmpl = 'srun'
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if self.partition:
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tmpl += f' -p {self.partition}'
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if self.quotatype:
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tmpl += f' --quotatype={self.quotatype}'
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if self.qos:
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tmpl += f' --qos={self.qos}'
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if num_gpus > 0:
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tmpl += f' --gres=gpu:{num_gpus}'
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tmpl += f" -N1 -J '{task_name[:512]}'" + ' {task_cmd}'
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get_cmd = partial(task.get_command, cfg_path=param_file, template=tmpl)
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cmd = get_cmd()
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# Build up slurm command
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tmpl = 'srun'
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if self.partition:
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tmpl += f' -p {self.partition}'
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if self.quotatype:
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tmpl += f' --quotatype={self.quotatype}'
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if self.qos:
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tmpl += f' --qos={self.qos}'
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if num_gpus > 0:
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tmpl += f' --gres=gpu:{num_gpus}'
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tmpl += f" -N1 -J '{task_name[:512]}'" + ' {task_cmd}'
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get_cmd = partial(task.get_command,
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cfg_path=param_file,
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template=tmpl)
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cmd = get_cmd()
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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logger = get_logger()
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logger.debug(f'Running command: {cmd}')
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# Run command with retry
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if self.debug:
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stdout = None
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else:
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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# Run command with retry
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if self.debug:
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stdout = None
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else:
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out_path = task.get_log_path(file_extension='out')
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mmengine.mkdir_or_exist(osp.split(out_path)[0])
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stdout = open(out_path, 'w', encoding='utf-8')
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if random_sleep:
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time.sleep(random.randint(0, 10))
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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retry = self.retry
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output_paths = task.get_output_paths()
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while self._job_failed(result.returncode, output_paths) and retry > 0:
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retry -= 1
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if random_sleep:
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time.sleep(random.randint(0, 10))
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# Re-generate command to refresh ports.
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cmd = get_cmd()
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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if result.returncode != 0 and not self.debug:
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logger.warning(f'task {task_name} fail, see\n{out_path}')
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retry = self.retry
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output_paths = task.get_output_paths()
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while self._job_failed(result.returncode,
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output_paths) and retry > 0:
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retry -= 1
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if random_sleep:
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time.sleep(random.randint(0, 10))
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# Re-generate command to refresh ports.
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cmd = get_cmd()
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result = subprocess.run(cmd,
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shell=True,
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text=True,
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stdout=stdout,
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stderr=stdout)
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# Clean up
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os.remove(param_file)
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if result.returncode != 0 and not self.debug:
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logger.warning(f'task {task_name} fail, see\n{out_path}')
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finally:
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# Clean up
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os.remove(param_file)
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return task_name, result.returncode
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def _job_failed(self, return_code: int, output_paths: List[str]) -> bool:
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@ -3,7 +3,9 @@ from typing import List, Union
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import tabulate
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from mmengine.config import Config
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from opencompass.partitioners import NaivePartitioner, SizePartitioner
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from opencompass.runners import DLCRunner, LocalRunner, SlurmRunner
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from opencompass.tasks import OpenICLEvalTask, OpenICLInferTask
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from opencompass.utils import get_logger, match_files
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@ -118,54 +120,61 @@ def exec_mm_infer_runner(tasks, args, cfg):
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runner(tasks)
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def exec_infer_runner(tasks, args, cfg):
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"""execute infer runner according to args."""
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if args.slurm:
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runner = SlurmRunner(dict(type='OpenICLInferTask'),
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max_num_workers=args.max_num_workers,
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partition=args.partition,
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quotatype=args.quotatype,
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qos=args.qos,
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retry=args.retry,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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elif args.dlc:
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runner = DLCRunner(dict(type='OpenICLInferTask'),
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max_num_workers=args.max_num_workers,
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aliyun_cfg=Config.fromfile(args.aliyun_cfg),
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retry=args.retry,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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else:
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runner = LocalRunner(task=dict(type='OpenICLInferTask'),
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max_num_workers=args.max_num_workers,
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max_workers_per_gpu=args.max_workers_per_gpu,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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runner(tasks)
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def get_config_type(obj) -> str:
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return f'{obj.__module__}.{obj.__name__}'
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def exec_eval_runner(tasks, args, cfg):
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"""execute infer runner according to args."""
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def fill_infer_cfg(cfg, args):
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new_cfg = dict(infer=dict(
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partitioner=dict(type=get_config_type(SizePartitioner),
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max_task_size=args.max_partition_size,
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gen_task_coef=args.gen_task_coef),
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runner=dict(
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max_num_workers=args.max_num_workers,
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debug=args.debug,
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task=dict(type=get_config_type(OpenICLInferTask)),
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lark_bot_url=cfg['lark_bot_url'],
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)), )
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if args.slurm:
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runner = SlurmRunner(dict(type='OpenICLEvalTask'),
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max_num_workers=args.max_num_workers,
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partition=args.partition,
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quotatype=args.quotatype,
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qos=args.qos,
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retry=args.retry,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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new_cfg['infer']['runner']['type'] = get_config_type(SlurmRunner)
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new_cfg['infer']['runner']['partition'] = args.partition
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new_cfg['infer']['runner']['quotatype'] = args.quotatype
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new_cfg['infer']['runner']['qos'] = args.qos
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new_cfg['infer']['runner']['retry'] = args.retry
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elif args.dlc:
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runner = DLCRunner(dict(type='OpenICLEvalTask'),
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max_num_workers=args.max_num_workers,
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aliyun_cfg=Config.fromfile(args.aliyun_cfg),
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retry=args.retry,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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new_cfg['infer']['runner']['type'] = get_config_type(DLCRunner)
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new_cfg['infer']['runner']['aliyun_cfg'] = Config.fromfile(
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args.aliyun_cfg)
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new_cfg['infer']['runner']['retry'] = args.retry
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else:
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runner = LocalRunner(task=dict(type='OpenICLEvalTask'),
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max_num_workers=args.max_num_workers,
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debug=args.debug,
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lark_bot_url=cfg['lark_bot_url'])
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runner(tasks)
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new_cfg['infer']['runner']['type'] = get_config_type(LocalRunner)
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new_cfg['infer']['runner'][
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'max_workers_per_gpu'] = args.max_workers_per_gpu
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cfg.merge_from_dict(new_cfg)
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def fill_eval_cfg(cfg, args):
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new_cfg = dict(
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eval=dict(partitioner=dict(type=get_config_type(NaivePartitioner)),
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runner=dict(
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max_num_workers=args.max_num_workers,
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debug=args.debug,
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task=dict(type=get_config_type(OpenICLEvalTask)),
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lark_bot_url=cfg['lark_bot_url'],
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)))
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if args.slurm:
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new_cfg['eval']['runner']['type'] = get_config_type(SlurmRunner)
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new_cfg['eval']['runner']['partition'] = args.partition
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new_cfg['eval']['runner']['quotatype'] = args.quotatype
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new_cfg['eval']['runner']['qos'] = args.qos
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new_cfg['eval']['runner']['retry'] = args.retry
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elif args.dlc:
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new_cfg['eval']['runner']['type'] = get_config_type(DLCRunner)
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new_cfg['eval']['runner']['aliyun_cfg'] = Config.fromfile(
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args.aliyun_cfg)
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new_cfg['eval']['runner']['retry'] = args.retry
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else:
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new_cfg['eval']['runner']['type'] = get_config_type(LocalRunner)
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new_cfg['eval']['runner'][
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'max_workers_per_gpu'] = args.max_workers_per_gpu
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cfg.merge_from_dict(new_cfg)
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112
run.py
112
run.py
@ -6,13 +6,12 @@ from datetime import datetime
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from mmengine.config import Config, DictAction
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from opencompass.partitioners import (MultimodalNaivePartitioner,
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NaivePartitioner, SizePartitioner)
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from opencompass.partitioners import MultimodalNaivePartitioner
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from opencompass.registry import PARTITIONERS, RUNNERS
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from opencompass.runners import SlurmRunner
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from opencompass.utils import LarkReporter, Summarizer, get_logger
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from opencompass.utils.run import (exec_eval_runner, exec_infer_runner,
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exec_mm_infer_runner, get_config_from_arg)
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from opencompass.utils.run import (exec_mm_infer_runner, fill_eval_cfg,
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fill_infer_cfg, get_config_from_arg)
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def parse_args():
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@ -245,39 +244,29 @@ def main():
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tasks = partitioner(cfg)
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exec_mm_infer_runner(tasks, args, cfg)
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return
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elif args.dlc or args.slurm or cfg.get('infer', None) is None:
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# Use SizePartitioner to split into subtasks
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partitioner = SizePartitioner(
|
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osp.join(cfg['work_dir'], 'predictions/'),
|
||||
max_task_size=args.max_partition_size,
|
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gen_task_coef=args.gen_task_coef)
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tasks = partitioner(cfg)
|
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if args.dry_run:
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||||
return
|
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# execute the infer subtasks
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exec_infer_runner(tasks, args, cfg)
|
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# If they have specified "infer" in config and haven't used --slurm
|
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# or --dlc, just follow the config
|
||||
|
||||
if args.dlc or args.slurm or cfg.get('infer', None) is None:
|
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fill_infer_cfg(cfg, args)
|
||||
|
||||
if args.partition is not None:
|
||||
if RUNNERS.get(cfg.infer.runner.type) == SlurmRunner:
|
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cfg.infer.runner.partition = args.partition
|
||||
cfg.infer.runner.quotatype = args.quotatype
|
||||
else:
|
||||
if args.partition is not None:
|
||||
if RUNNERS.get(cfg.infer.runner.type) == SlurmRunner:
|
||||
cfg.infer.runner.partition = args.partition
|
||||
cfg.infer.runner.quotatype = args.quotatype
|
||||
else:
|
||||
logger.warning('SlurmRunner is not used, so the partition '
|
||||
'argument is ignored.')
|
||||
if args.debug:
|
||||
cfg.infer.runner.debug = True
|
||||
if args.lark:
|
||||
cfg.infer.runner.lark_bot_url = cfg['lark_bot_url']
|
||||
cfg.infer.partitioner['out_dir'] = osp.join(
|
||||
cfg['work_dir'], 'predictions/')
|
||||
partitioner = PARTITIONERS.build(cfg.infer.partitioner)
|
||||
tasks = partitioner(cfg)
|
||||
if args.dry_run:
|
||||
return
|
||||
runner = RUNNERS.build(cfg.infer.runner)
|
||||
runner(tasks)
|
||||
logger.warning('SlurmRunner is not used, so the partition '
|
||||
'argument is ignored.')
|
||||
if args.debug:
|
||||
cfg.infer.runner.debug = True
|
||||
if args.lark:
|
||||
cfg.infer.runner.lark_bot_url = cfg['lark_bot_url']
|
||||
cfg.infer.partitioner['out_dir'] = osp.join(cfg['work_dir'],
|
||||
'predictions/')
|
||||
partitioner = PARTITIONERS.build(cfg.infer.partitioner)
|
||||
tasks = partitioner(cfg)
|
||||
if args.dry_run:
|
||||
return
|
||||
runner = RUNNERS.build(cfg.infer.runner)
|
||||
runner(tasks)
|
||||
|
||||
# evaluate
|
||||
if args.mode in ['all', 'eval']:
|
||||
@ -289,37 +278,28 @@ def main():
|
||||
'also specified --slurm or --dlc. '
|
||||
'The "eval" configuration will be overridden by '
|
||||
'your runtime arguments.')
|
||||
|
||||
if args.dlc or args.slurm or cfg.get('eval', None) is None:
|
||||
# Use NaivePartitioner，not split
|
||||
partitioner = NaivePartitioner(
|
||||
osp.join(cfg['work_dir'], 'results/'))
|
||||
tasks = partitioner(cfg)
|
||||
if args.dry_run:
|
||||
return
|
||||
# execute the eval tasks
|
||||
exec_eval_runner(tasks, args, cfg)
|
||||
# If they have specified "eval" in config and haven't used --slurm
|
||||
# or --dlc, just follow the config
|
||||
else:
|
||||
if args.partition is not None:
|
||||
if RUNNERS.get(cfg.infer.runner.type) == SlurmRunner:
|
||||
cfg.eval.runner.partition = args.partition
|
||||
cfg.eval.runner.quotatype = args.quotatype
|
||||
else:
|
||||
logger.warning('SlurmRunner is not used, so the partition '
|
||||
'argument is ignored.')
|
||||
if args.debug:
|
||||
cfg.eval.runner.debug = True
|
||||
if args.lark:
|
||||
cfg.eval.runner.lark_bot_url = cfg['lark_bot_url']
|
||||
cfg.eval.partitioner['out_dir'] = osp.join(cfg['work_dir'],
|
||||
'results/')
|
||||
partitioner = PARTITIONERS.build(cfg.eval.partitioner)
|
||||
tasks = partitioner(cfg)
|
||||
if args.dry_run:
|
||||
return
|
||||
runner = RUNNERS.build(cfg.eval.runner)
|
||||
runner(tasks)
|
||||
fill_eval_cfg(cfg, args)
|
||||
|
||||
if args.partition is not None:
|
||||
if RUNNERS.get(cfg.infer.runner.type) == SlurmRunner:
|
||||
cfg.eval.runner.partition = args.partition
|
||||
cfg.eval.runner.quotatype = args.quotatype
|
||||
else:
|
||||
logger.warning('SlurmRunner is not used, so the partition '
|
||||
'argument is ignored.')
|
||||
if args.debug:
|
||||
cfg.eval.runner.debug = True
|
||||
if args.lark:
|
||||
cfg.eval.runner.lark_bot_url = cfg['lark_bot_url']
|
||||
cfg.eval.partitioner['out_dir'] = osp.join(cfg['work_dir'], 'results/')
|
||||
partitioner = PARTITIONERS.build(cfg.eval.partitioner)
|
||||
tasks = partitioner(cfg)
|
||||
if args.dry_run:
|
||||
return
|
||||
runner = RUNNERS.build(cfg.eval.runner)
|
||||
runner(tasks)
|
||||
|
||||
# visualize
|
||||
if args.mode in ['all', 'eval', 'viz']:
|
||||
|
||||
Loading…
Reference in New Issue
Block a user