mirror of
https://github.com/MacRimi/ProxMenux.git
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MacRimi
1f9d2acef5
The installation record of an OCI application travels with its container: a copy inside the container and another in /etc/pve, written together with the one kept on the host. A container restored on a newly installed Proxmox, restored with another ID or moved to another node of a cluster is recognised and registered again, with its private network, hookscript, Rclone mount, host firewall rule and NVIDIA runtime. The Monitor offers the same recovery from the Updates tab. AMD GPUs are offered by generation. A GPU the ROCm image supports takes the profile as it is; one of a supported family (Radeon 680M, 780M) is an experimental option that asks for confirmation and is never proposed; an older one is not offered. The GPU is checked with a real inference before the installation accepts it. Recreate changes what runs recognition in an installed Immich, between the CPU and a GPU of the host. Updates: - A failed update that is restored and checked removes its temporary container and the disks of the failed attempt. - Every container volume is part of the backups, so Jellyfin, Plex and Hugo update with their default installation. - An image published with a Docker-format manifest is recognised by its layers and build time and updates. - The Proxmox notes of a multi-container application link to its LAN address.
82 lines
3.7 KiB
Python
82 lines
3.7 KiB
Python
#!/usr/bin/env python3
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"""A real inference on the AMD GPU of a container, through ROCm.
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That the MIGraphX provider is listed says nothing about the GPU of this host:
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an image carries kernels for some generations only, and on any other the
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first inference aborts. This runs a small convolution model on the GPU inside
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the container and fails when it does not come back with a result.
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"""
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from __future__ import annotations
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import argparse
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import re
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import subprocess
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import sys
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# A model of five operators (convolution, pooling and a dense layer), enough
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# to make ROCm compile and run on the GPU without downloading anything.
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MODEL = (
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'CAg65wUKPAoBeAoBdwoBYhIBYyIEQ29udioVCgxrZXJuZWxfc2hhcGVAA0ADoAEHKhEKBHBhZHNAAUABQAFAAaABBwoMCgFjEgFy'
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'IgRSZWx1ChkKAXISAWciEUdsb2JhbEF2ZXJhZ2VQb29sCg8KAWcSAWYiB0ZsYXR0ZW4KFAoBZgoCZncKAmZiEgF5IgRHZW1tEgVw'
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'cm9iZSrAAwgECAMIAwgDEAFCAXdKsAOu/QA5e7v0POCS4LyqZLa9sDs6vdcWy70cFMU78DwJPpibSb2CJX69qqNIPVEuEj3xtSw8'
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'U4++vWu0P7vqZY49x6UJvn5wO71qr0K+dgwEvvuXPL4vlsC8WskBvkI43jwWaYA8QyKZvKzbgL4Lply9i+2euzylOTyXrxy+ELBD'
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'vZVmyL1epqW9pUXZPRNipb1fIlW7gB+1PfIKb70yAze8Bfw0PAgA0Ts15Pq9D3/5O74kCz54bR6+ZwCwPbWMQzyGX4O9uNdMPl0c'
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'nD1HnfW9vyz0O0o2bD17ppq8K9yLPcf22bv9pog9Ak4TPipgir1BaaY8U8U9vT+EUDwwI/O9LUhtvUe5oLwdEbg9nYrqPX2HB74m'
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'vqK9X3yEPRcGTL7itj29GGUfvOW3AD6fMI090AYGvfz3Fr3I9cy8aQIcPqtRL71lxvi8pWsQPczeRbyAnaG8NSnkvaIDl7rdsDW9'
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'r9LuPabAhT1DOh67a+KIPeg1C726edc914sNuhP0bj3+LwS+CgAOPUPfLL7talC+b235vCBOuL1eZIY889xlPj9Wqr06kX+9VESo'
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'PDHwST0qGQgEEAFCAWJKEAAAAAAAAAAAAAAAAAAAAAAqLAgECAIQAUICZndKIAmDkLy5sqi8S92PPUX0VD1istO9DrsBvIJBZztd'
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'9de9KhIIAhABQgJmYkoIAAAAAAAAAABaGwoBeBIWChQIARIQCgIIAQoCCAMKAggICgIICGITCgF5Eg4KDAgBEggKAggBCgIIAkIE'
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'CgAQDQ=='
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)
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PROBE = """
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import base64, sys
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import numpy as np
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import onnxruntime as ort
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options = ort.SessionOptions()
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options.log_severity_level = 3
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session = ort.InferenceSession(base64.b64decode(sys.argv[1]), options, providers=['MIGraphXExecutionProvider'])
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assert session.get_providers()[0] == 'MIGraphXExecutionProvider', session.get_providers()
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result = session.run(None, {'x': np.ones((1, 3, 8, 8), np.float32)})[0]
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assert result.shape == (1, 2) and np.isfinite(result).all(), result
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print('ROCm inference on the GPU: ok')
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"""
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def variables(config):
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"""What the container tells ROCm about its GPU. A command run in the
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container does not receive the variables its application starts with."""
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found = re.findall(r'^lxc\.environment\.runtime: (.+)$', config, re.M)
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for line in re.findall(r'^env: (.+)$', config, re.M):
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found += line.split('\0')
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return [value for value in found if re.fullmatch(r'HSA_[A-Z_]+=[0-9A-Za-z.]+', value)]
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def check(vmid, timeout=300):
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"""Raises RuntimeError when the container cannot run the model on its GPU."""
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vmid = str(int(vmid))
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config = subprocess.run(['pct', 'config', vmid], capture_output=True, text=True, check=False).stdout
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try:
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result = subprocess.run(['pct', 'exec', vmid, '--', 'env', *variables(config), 'python', '-c', PROBE, MODEL],
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capture_output=True, text=True, timeout=timeout, check=False)
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except subprocess.TimeoutExpired as error:
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raise RuntimeError('the GPU did not answer in time') from error
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if result.returncode != 0:
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detail = (result.stderr or result.stdout).strip().splitlines()[-1:] or ['']
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raise RuntimeError(detail[0][:300])
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def main():
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('vmid', type=int)
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args = parser.parse_args()
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try:
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check(args.vmid)
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except RuntimeError as error:
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print(error, file=sys.stderr)
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return 1
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return 0
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if __name__ == '__main__':
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sys.exit(main())
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