mirror of
https://github.com/hpcaitech/Open-Sora.git
synced 2026-04-11 05:13:31 +02:00
update notebook
This commit is contained in:
Zangwei Zheng
parent
8513ff8734
commit
e88185fb9f
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@ -1,555 +0,0 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Data Process Pipeline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First, you should add hosts in your ~/.ssh/config file"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import paramiko\n",
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"import time\n",
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"\n",
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"HOSTS = [\"h800-80\", \"h800-81\", \"h800-82\", \"h800-83\", \"h800-84\", \"h800-85\", \"h800-86\", \"h800-170\", \"h800-171\"]\n",
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"\n",
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"# load from ~/.ssh/config\n",
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"ssh_config = paramiko.SSHConfig()\n",
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"user_config_file = os.path.expanduser(\"~/.ssh/config\")\n",
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"if os.path.exists(user_config_file):\n",
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" with open(user_config_file) as f:\n",
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" ssh_config.parse(f)\n",
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"\n",
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"\n",
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"def get_ssh_config(hostname):\n",
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" # get the configuration for the host\n",
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" user_config = ssh_config.lookup(hostname)\n",
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" cfg = {\n",
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" \"hostname\": user_config[\"hostname\"],\n",
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" \"username\": user_config[\"user\"],\n",
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" \"port\": int(user_config[\"port\"]),\n",
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" \"key_filename\": user_config[\"identityfile\"],\n",
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" }\n",
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" return cfg\n",
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"\n",
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"\n",
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"def connect(hostname):\n",
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" cfg = get_ssh_config(hostname)\n",
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" # connect\n",
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" client = paramiko.SSHClient()\n",
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" client.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n",
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" client.connect(**cfg)\n",
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" return client\n",
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"\n",
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"\n",
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"def run_command(command, hostname, nohup=False, log_file=None):\n",
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" client = connect(hostname)\n",
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" print(\"HOST:\", hostname)\n",
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" command = f\"bash -ic '{command}'\"\n",
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" if log_file:\n",
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" command = f\"{command} >> {log_file} 2>&1\"\n",
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" if nohup:\n",
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" command = f\"nohup {command} &\"\n",
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" print(\"COMMAND:\", command)\n",
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" stdin, stdout, stderr = client.exec_command(command, get_pty=False)\n",
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"\n",
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" stdout_str = stdout.read().decode()\n",
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" stderr_str = stderr.read().decode()\n",
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" if stdout_str:\n",
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" print(\"==== STDOUT ====\\n\", stdout_str)\n",
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" if stderr_str:\n",
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" print(\"==== STDERR ====\\n\", stderr_str)\n",
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"\n",
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" client.close()\n",
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"\n",
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"\n",
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"def run_command_all_hosts(command, hosts=HOSTS):\n",
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" for hostname in hosts:\n",
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" run_command(command, hostname)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here are tools to examine machine's status."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"def nvidia_smi(host):\n",
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" if host:\n",
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" run_command(\"nvidia-smi\", host)\n",
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" else:\n",
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" run_command_all_hosts(\"nvidia-smi\")\n",
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"\n",
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"\n",
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"def nvitop(host=None):\n",
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" if host:\n",
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" run_command(f\"/home/zhaowangbo/.local/bin/nvitop -1\", host)\n",
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" else:\n",
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" run_command_all_hosts(\"/home/zhaowangbo/.local/bin/nvitop -1\")\n",
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"\n",
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"\n",
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"def ps(host=None, interest=\"python|sleep|torchrun|colossal\"):\n",
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" if host:\n",
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" if interest is None:\n",
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" run_command(\"ps ux | cat\", host)\n",
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" else:\n",
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" run_command(f'ps ux | cat | grep --color=never -E \"{interest}\"', host)\n",
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" else:\n",
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" if interest is None:\n",
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" run_command_all_hosts(\"ps ux | cat\")\n",
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" else:\n",
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" run_command_all_hosts(f'ps ux | cat | grep --color=never -E \"{interest}\"')\n",
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"\n",
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"\n",
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"def kill(pid, host):\n",
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" run_command(f\"kill -KILL {pid}\", host)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here we define different tasks."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"OPEN_SORA_HOME = \"/home/zhaowangbo/zangwei/opensora/\"\n",
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"\n",
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"\n",
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"def convert_dataset_cmd(input_dir, output_file, datatype=\"video\"):\n",
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" commands = []\n",
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" commands.append(f'echo \"Converting {input_dir} to {output_file}\"')\n",
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" output_dir = os.path.dirname(output_file)\n",
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"\n",
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" commands.append(f\"mkdir -p {output_dir}\")\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(f\"python -m tools.datasets.convert {datatype} {input_dir} --output {output_file}\")\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_video_info(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_info{ext}\"\n",
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" output_format = ext[1:]\n",
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"\n",
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" commands.append(f'echo \"Getting info of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(\n",
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" f\"python -m tools.datasets.datautil {input_file} --output {output_file} --format {output_format} --info --fmin 1\"\n",
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" )\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_caption_llava7b_video(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_info{ext}\"\n",
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" output_format = ext[1:]\n",
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"\n",
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" commands.append(f'echo \"Getting info of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(\n",
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" f\"torchrun --nproc_per_node 8 --standalone -m tools.caption.caption_llava {input_file} --dp-size 8 --tp-size 1 --model-path liuhaotian/llava-v1.6-mistral-7b --prompt video\"\n",
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" )\n",
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" commands.append(\n",
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" f\"python -m tools.datasets.datautil {base}_part*{ext} --output {output_file} --format {output_format} --intersection {input_file} --clean-caption --refine-llm-caption --remove-empty-caption\"\n",
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" )\n",
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"\n",
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"\n",
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"def get_caption_load(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_caption{ext}\"\n",
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" output_format = ext[1:]\n",
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"\n",
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" commands.append(f'echo \"Getting caption of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(\n",
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" f\"python -m tools.datasets.datautil {input_file} --output {output_file} --format {output_format} --load-caption json --remove-empty-caption --clean-caption\"\n",
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" )\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_aesthetic_score(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_aes{ext}\"\n",
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" output_format = ext[1:]\n",
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"\n",
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" commands.append(f'echo \"Getting aesthetic score of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(f\"torchrun --standalone --nproc_per_node 8 -m tools.scoring.aesthetic.inference {input_file}\")\n",
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" commands.append(\n",
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" f\"python -m tools.datasets.datautil {base}_part*{ext} --output {output_file} --format {output_format} --sort aes\"\n",
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" )\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_flow_score(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_flow{ext}\"\n",
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"\n",
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" commands.append(f'echo \"Getting flow score of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(f\"torchrun --standalone --nproc_per_node 8 -m tools.scoring.optical_flow.inference {input_file}\")\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_match_score(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_match{ext}\"\n",
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"\n",
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" commands.append(f'echo \"Getting match score of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(f\"torchrun --standalone --nproc_per_node 8 -m tools.scoring.matching.inference {input_file}\")\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_cmotion_score(input_file):\n",
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" commands = []\n",
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" base, ext = os.path.splitext(input_file)\n",
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" output_file = f\"{base}_cmotion{ext}\"\n",
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"\n",
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" commands.append(f'echo \"Getting cmotion score of {input_file} to {output_file}\"')\n",
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" commands.append(f\"cd {OPEN_SORA_HOME}\")\n",
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" commands.append(f\"python -m tools.caption.camera_motion_detect {input_file}\")\n",
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" return \" && \".join(commands), output_file\n",
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"\n",
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"\n",
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"def get_commands(job_list):\n",
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" commands = []\n",
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" output_file = None\n",
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" for job in job_list:\n",
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" cmd = job.pop(\"cmd\")\n",
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" if output_file is None:\n",
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" command, output_file = cmd(**job)\n",
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" commands.append(command)\n",
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" else:\n",
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" job[\"input_file\"] = output_file\n",
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" command, output_file = cmd(**job)\n",
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" commands.append(command)\n",
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" commands.append(f'echo \"All Done!\"')\n",
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" return \" && \".join(commands), output_file"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The following is the pipeline for panda."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"echo \"Getting flow score of /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv to /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption_flow.csv\" && cd /home/zhaowangbo/zangwei/opensora/ && torchrun --standalone --nproc_per_node 8 -m tools.scoring.optical_flow.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv && echo \"All Done!\"\n",
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"/mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption_flow.csv\n"
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]
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}
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],
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"source": [
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"host = \"h800-83\"\n",
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"log_file = os.path.join(OPEN_SORA_HOME, \"logs/data-panda-16-split.log\")\n",
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"input_dir = \"/mnt/disk1/data-panda/16\"\n",
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"output_file = \"/mnt/hdd/data/panda70m_by/raw/meta/split-16/meta.csv\"\n",
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"cmd, output_file = get_commands(\n",
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" [\n",
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" # {\n",
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" # \"cmd\": convert_dataset_cmd,\n",
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" # \"input_dir\": input_dir,\n",
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" # \"output_file\": output_file,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_video_info,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_caption_load,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_aesthetic_score,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_flow_score,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_match_score,\n",
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" # },\n",
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" # {\n",
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" # \"cmd\": get_cmotion_score,\n",
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" # },\n",
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" ]\n",
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")\n",
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"print(cmd)\n",
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"print(output_file)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"echo \"Getting info of /mnt/hdd/data/panda70m_by/raw/meta/split-8/meta_loadjson_noempty_clean.csv to /mnt/hdd/data/panda70m_by/raw/meta/split-8/meta_loadjson_noempty_clean_info.csv\" && cd /home/zhaowangbo/zangwei/opensora/ && python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-8/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-8/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1 && echo \"All Done!\"\n",
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"/mnt/hdd/data/panda70m_by/raw/meta/split-8/meta_loadjson_noempty_clean_info.csv\n"
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]
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}
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],
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"source": [
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"host = \"h800-81\"\n",
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"split = 8\n",
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"log_file = os.path.join(OPEN_SORA_HOME, f\"logs/data-panda-{split}-split.log\")\n",
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"cmd, output_file = get_commands(\n",
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" [\n",
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" {\n",
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" \"cmd\": get_video_info,\n",
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" \"input_file\": f\"/mnt/hdd/data/panda70m_by/raw/meta/split-{split}/meta_loadjson_noempty_clean.csv\",\n",
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" },\n",
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" ]\n",
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")\n",
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"print(cmd)\n",
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"print(output_file)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"HOST: h800-83\n",
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"COMMAND: nohup bash -ic 'echo \"Getting flow score of /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv to /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption_flow.csv\" && cd /home/zhaowangbo/zangwei/opensora/ && torchrun --standalone --nproc_per_node 8 -m tools.scoring.optical_flow.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv && echo \"All Done!\"' >> /home/zhaowangbo/zangwei/opensora/logs/data-panda-16-split.log 2>&1 &\n",
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"HOST: h800-83\n",
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"COMMAND: bash -ic 'ps ux | cat | grep --color=never -E \"python|sleep|torchrun|colossal\"'\n",
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"==== STDOUT ====\n",
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" zhaowan+ 891142 0.8 0.0 20886768 197296 pts/10 Sl+ 22:36 0:22 /home/zhaowangbo/.conda/envs/opensora/bin/python /home/zhaowangbo/.conda/envs/opensora/bin/torchrun --standalone --nproc_per_node 1 -m tools.scoring.aesthetic.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv --num_frames 2 --num_workers 0\n",
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"zhaowan+ 891294 3.0 0.0 74364928 1938304 ? Ssl 22:36 1:15 /home/zhaowangbo/.conda/envs/opensora/bin/python -u -m tools.scoring.aesthetic.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv --num_frames 2 --num_workers 0\n",
|
||||
"zhaowan+ 2100459 2.7 0.0 14180 5292 ? S 23:17 0:00 bash -ic echo \"Getting flow score of /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv to /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption_flow.csv\" && cd /home/zhaowangbo/zangwei/opensora/ && torchrun --standalone --nproc_per_node 8 -m tools.scoring.optical_flow.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv && echo \"All Done!\"\n",
|
||||
"zhaowan+ 2100656 13.0 0.0 2803920 18924 ? I 23:17 0:00 /home/zhaowangbo/.conda/envs/opensora/bin/python /home/zhaowangbo/.conda/envs/opensora/bin/torchrun --standalone --nproc_per_node 8 -m tools.scoring.optical_flow.inference /mnt/hdd/data/panda70m_by/raw/meta/split-16/meta_info_caption.csv\n",
|
||||
"zhaowan+ 2100724 10.0 0.0 14176 5104 ? Ss 23:17 0:00 bash -ic ps ux | cat | grep --color=never -E \"python|sleep|torchrun|colossal\"\n",
|
||||
"zhaowan+ 2100840 0.0 0.0 12124 728 ? S 23:17 0:00 grep --color=auto --color=never -E python|sleep|torchrun|colossal\n",
|
||||
"\n",
|
||||
"==== STDERR ====\n",
|
||||
" bash: cannot set terminal process group (-1): Inappropriate ioctl for device\n",
|
||||
"bash: no job control in this shell\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"run_command(cmd, host, log_file=log_file, nohup=True)\n",
|
||||
"ps(host)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Using following commands to monitor the status of the jobs."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"HOST: h800-80\n",
|
||||
"COMMAND: bash -ic 'ps ux | cat | grep --color=never -E \"python|sleep|torchrun|colossal\"'\n",
|
||||
"==== STDOUT ====\n",
|
||||
" zhaowan+ 3707972 0.1 0.0 8492 5240 ? S 21:07 0:00 bash -ic echo \"Getting info of /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv to /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv\" && cd /home/zhaowangbo/zangwei/opensora/ && python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1 && echo \"All Done!\"\n",
|
||||
"zhaowan+ 3708645 33.6 0.0 17792816 399760 ? Sl 21:07 0:21 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710337 0.4 0.0 18128668 386580 ? Sl 21:07 0:00 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710347 3.8 0.0 17590060 397448 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710349 4.2 0.0 17590060 397468 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710351 4.1 0.0 17590060 397460 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710353 4.8 0.0 17590060 397468 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710355 4.9 0.0 17590060 397456 ? R 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710358 4.6 0.0 17590060 397464 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710360 4.5 0.0 17590060 397456 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710362 5.4 0.0 17590060 397472 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710366 5.5 0.0 17590060 397500 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710368 5.3 0.0 17590060 397504 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710370 5.0 0.0 17590060 397496 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710377 3.6 0.0 17590060 397476 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710379 4.5 0.0 17590060 397472 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710381 4.5 0.0 17590060 397484 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710391 3.8 0.0 17590060 397468 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710401 5.2 0.0 17590060 397508 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710403 5.9 0.0 17590060 397500 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710409 4.6 0.0 17590060 397500 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710411 5.0 0.0 17590060 397472 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710425 4.0 0.0 17590060 397456 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710435 5.3 0.0 17590060 397500 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710448 5.2 0.0 17590060 397492 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710450 4.7 0.0 17590060 397512 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710459 5.1 0.0 17590060 397484 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710466 5.0 0.0 17590060 397516 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710468 4.5 0.0 17590060 397488 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710470 3.4 0.0 17590060 397492 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710472 4.6 0.0 17590060 397548 ? R 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710474 4.7 0.0 17590060 397520 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710476 4.5 0.0 17590060 397512 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710478 4.4 0.0 17590060 397524 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710480 5.1 0.0 17590060 397524 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710482 4.5 0.0 17590060 397524 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710483 5.6 0.0 17590060 397504 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710486 4.6 0.0 17590060 397532 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710489 3.5 0.0 17590060 397520 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710491 4.5 0.0 17590060 397528 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710493 5.5 0.0 17590060 397540 ? R 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710495 4.1 0.0 17590060 397532 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710497 4.1 0.0 17590060 397548 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710499 5.3 0.0 17590060 397536 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710501 4.1 0.0 17590060 397552 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710503 4.0 0.0 17590060 397540 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710505 4.9 0.0 17590060 397544 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710507 4.9 0.0 17590060 397544 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710509 4.6 0.0 17590060 397532 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710511 4.9 0.0 17590060 397588 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710513 4.4 0.0 17590060 397536 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710515 4.5 0.0 17590060 397536 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710517 5.5 0.0 17590060 397536 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710519 4.5 0.0 17590060 397552 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710521 5.3 0.0 17590060 397552 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710523 6.6 0.0 17590060 398028 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710525 5.7 0.0 17590060 397548 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710527 5.1 0.0 17590060 397544 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710529 6.8 0.0 17590060 397568 ? I 21:07 0:03 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710531 3.9 0.0 17590060 397560 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710533 4.5 0.0 17590060 397572 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710535 5.6 0.0 17590060 397548 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710537 6.1 0.0 17590060 398048 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710539 5.2 0.0 17590060 397552 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710541 4.4 0.0 17590060 397536 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710543 6.8 0.0 17590060 398020 ? R 21:07 0:03 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710545 4.4 0.0 17590060 397556 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710547 5.5 0.0 17590060 397552 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710549 4.3 0.0 17590060 397564 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710551 4.6 0.0 17590060 397564 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710553 5.1 0.0 17590060 397568 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710555 4.5 0.0 17590060 397564 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710556 5.9 0.0 17590060 397580 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710559 5.0 0.0 17590060 397568 ? D 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710561 6.4 0.0 17590060 397588 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710563 5.0 0.0 17590060 397644 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710565 5.1 0.0 17590060 397584 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710566 5.5 0.0 17590060 397584 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710568 5.1 0.0 17590060 397588 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710571 4.4 0.0 17590060 397600 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710573 5.1 0.0 17590060 397644 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710575 4.4 0.0 17590060 397652 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710577 4.6 0.0 17590060 397652 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710579 3.8 0.0 17590060 397596 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710581 5.0 0.0 17590060 397588 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710583 4.5 0.0 17590060 397596 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710585 4.4 0.0 17590060 397612 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710587 4.2 0.0 17590060 397596 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710589 5.7 0.0 17590060 397612 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710591 4.4 0.0 17590060 397596 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710593 5.3 0.0 17590060 397604 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710595 5.2 0.0 17590060 397604 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710597 4.5 0.0 17590060 397608 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710599 5.2 0.0 17590060 397608 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710601 5.2 0.0 17590060 397620 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710603 5.4 0.0 17590060 397600 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710605 3.5 0.0 17590060 397572 ? I 21:07 0:01 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710607 5.1 0.0 17590060 397612 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3710609 6.0 0.0 17590060 397628 ? I 21:07 0:02 python -m tools.datasets.datautil /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean.csv --output /mnt/hdd/data/panda70m_by/raw/meta/split-6/meta_loadjson_noempty_clean_info.csv --format csv --info --fmin 1\n",
|
||||
"zhaowan+ 3862481 5.0 0.0 8488 5328 ? Ss 21:08 0:00 bash -ic ps ux | cat | grep --color=never -E \"python|sleep|torchrun|colossal\"\n",
|
||||
"zhaowan+ 3868112 0.0 0.0 6412 724 ? S 21:08 0:00 grep --color=auto --color=never -E python|sleep|torchrun|colossal\n",
|
||||
"\n",
|
||||
"==== STDERR ====\n",
|
||||
" bash: cannot set terminal process group (-1): Inappropriate ioctl for device\n",
|
||||
"bash: no job control in this shell\n",
|
||||
"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"ps(host)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"nvitop(host)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"kill(, host)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
1353
notebooks/launch.ipynb
Normal file
1353
notebooks/launch.ipynb
Normal file
File diff suppressed because it is too large
Load diff
|
|
@ -304,6 +304,7 @@ def main():
|
|||
dataloader.sampler.set_start_index(0)
|
||||
if cfg.dataset.type == "VariableVideoTextDataset":
|
||||
dataloader.batch_sampler.set_epoch(epoch + 1)
|
||||
print("Epoch done, recomputing batch sampler")
|
||||
start_step = 0
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in a new issue