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https://github.com/zebrajr/pytorch.git
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Add Intel GPU info collection to the collect env script (#157351)
https://github.com/pytorch/pytorch/pull/137846 was mistakenly closed. Reopen a PR to land the PR. Pull Request resolved: https://github.com/pytorch/pytorch/pull/157351 Approved by: https://github.com/guangyey, https://github.com/malfet
This commit is contained in:
Jing Xu
PyTorch MergeBot
parent
d6237721c0
commit
c515385b0a
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@ -10,6 +10,7 @@ import re
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import subprocess
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import sys
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import os
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from typing import cast as _cast
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from collections import namedtuple
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@ -37,6 +38,7 @@ SystemEnv = namedtuple('SystemEnv', [
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'nvidia_driver_version',
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'nvidia_gpu_models',
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'cudnn_version',
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'is_xpu_available',
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'pip_version', # 'pip' or 'pip3'
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'pip_packages',
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'conda_packages',
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@ -73,6 +75,30 @@ NVIDIA_PATTERNS = [
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"nvtx",
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]
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ONEAPI_PATTERNS = [
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"dpcpp-cpp-rt",
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"intel-cmplr-lib-rt",
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"intel-cmplr-lib-ur",
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"intel-cmplr-lic-rt",
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"intel-opencl-rt",
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"intel-sycl-rt",
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"mkl",
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"onemkl-sycl-blas",
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"onemkl-sycl-dft",
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"onemkl-sycl-lapack",
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"onemkl-sycl-rng",
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"onemkl-sycl-sparse",
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"intel-openmp",
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"tbb",
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"impi-rt",
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"impi-devel",
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"oneccl",
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"oneccl-devel",
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"intel-pti",
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"umf",
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"tcmlib",
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]
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CONDA_PATTERNS = [
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"cudatoolkit",
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"soumith",
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@ -131,7 +157,7 @@ def run_and_return_first_line(run_lambda, command):
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def get_conda_packages(run_lambda, patterns=None):
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if patterns is None:
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patterns = CONDA_PATTERNS + COMMON_PATTERNS + NVIDIA_PATTERNS
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patterns = CONDA_PATTERNS + COMMON_PATTERNS + NVIDIA_PATTERNS + ONEAPI_PATTERNS
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conda = os.environ.get('CONDA_EXE', 'conda')
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out = run_and_read_all(run_lambda, "{} list".format(conda))
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if out is None:
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@ -243,6 +269,152 @@ def get_nvidia_smi():
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return smi
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def _detect_linux_pkg_manager():
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if get_platform() != "linux":
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return "N/A"
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for mgr_name in ["dpkg", "dnf", "yum", "zypper"]:
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rc, _, _ = run(f"which {mgr_name}")
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if rc == 0:
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return mgr_name
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return "N/A"
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def get_linux_pkg_version(run_lambda, pkg_name):
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pkg_mgr = _detect_linux_pkg_manager()
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if pkg_mgr == "N/A":
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return "N/A"
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grep_version = {
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"dpkg": {
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"field_index": 2,
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"command": "dpkg -l | grep {}",
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},
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"dnf": {
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"field_index": 1,
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"command": "dnf list | grep {}",
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},
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"yum": {
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"field_index": 1,
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"command": "yum list | grep {}",
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},
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"zypper": {
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"field_index": 2,
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"command": "zypper info {} | grep Version",
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},
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}
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field_index: int = int(_cast(int, grep_version[pkg_mgr]["field_index"]))
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cmd: str = str(grep_version[pkg_mgr]["command"])
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cmd = cmd.format(pkg_name)
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ret = run_and_read_all(run_lambda, cmd)
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if ret is None or ret == "":
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return "N/A"
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lst = re.sub(" +", " ", ret).split(" ")
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if len(lst) <= field_index:
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return "N/A"
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return lst[field_index]
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def get_intel_gpu_driver_version(run_lambda):
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lst = []
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platform = get_platform()
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if platform == "linux":
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pkgs = { # type: ignore[var-annotated]
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"dpkg": {
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"intel-opencl-icd",
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"libze1",
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"level-zero",
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},
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"dnf": {
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"intel-opencl",
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"level-zero",
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},
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"yum": {
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"intel-opencl",
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"level-zero",
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},
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"zypper": {
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"intel-opencl",
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"level-zero",
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},
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}.get(_detect_linux_pkg_manager(), {})
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for pkg in pkgs:
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ver = get_linux_pkg_version(run_lambda, pkg)
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if ver != "N/A":
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lst.append(f"* {pkg}:\t{ver}")
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if platform in ["win32", "cygwin"]:
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txt = run_and_read_all(
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run_lambda,
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'powershell.exe "gwmi -Class Win32_PnpSignedDriver | where{$_.DeviceClass -eq \\"DISPLAY\\"\
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-and $_.Manufacturer -match \\"Intel\\"} | Select-Object -Property DeviceName,DriverVersion,DriverDate\
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| ConvertTo-Json"',
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)
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try:
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obj = json.loads(txt)
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if type(obj) is list:
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for o in obj:
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lst.append(
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f'* {o["DeviceName"]}: {o["DriverVersion"]} ({o["DriverDate"]})'
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)
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else:
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lst.append(f'* {obj["DriverVersion"]} ({obj["DriverDate"]})')
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except ValueError as e:
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lst.append(txt)
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lst.append(str(e))
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return "\n".join(lst)
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def get_intel_gpu_onboard(run_lambda):
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lst: list[str] = []
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platform = get_platform()
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if platform == "linux":
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txt = run_and_read_all(run_lambda, "xpu-smi discovery -j")
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if txt:
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try:
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obj = json.loads(txt)
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device_list = obj.get("device_list", [])
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if isinstance(device_list, list) and device_list:
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lst.extend(f'* {device["device_name"]}' for device in device_list)
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else:
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lst.append("N/A")
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except (ValueError, TypeError) as e:
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lst.append(txt)
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lst.append(str(e))
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else:
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lst.append("N/A")
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if platform in ["win32", "cygwin"]:
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txt = run_and_read_all(
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run_lambda,
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'powershell.exe "gwmi -Class Win32_PnpSignedDriver | where{$_.DeviceClass -eq \\"DISPLAY\\"\
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-and $_.Manufacturer -match \\"Intel\\"} | Select-Object -Property DeviceName | ConvertTo-Json"',
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)
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if txt:
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try:
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obj = json.loads(txt)
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if isinstance(obj, list) and obj:
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lst.extend(f'* {device["DeviceName"]}' for device in obj)
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else:
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lst.append(f'* {obj.get("DeviceName", "N/A")}')
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except ValueError as e:
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lst.append(txt)
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lst.append(str(e))
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else:
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lst.append("N/A")
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return "\n".join(lst)
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def get_intel_gpu_detected(run_lambda):
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if not TORCH_AVAILABLE or not hasattr(torch, "xpu"):
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return "N/A"
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device_count = torch.xpu.device_count()
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if device_count == 0:
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return "N/A"
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devices = [f"* [{i}] {torch.xpu.get_device_properties(i)}" for i in range(device_count)]
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return "\n".join(devices)
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# example outputs of CPU infos
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# * linux
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# Architecture: x86_64
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@ -396,7 +568,7 @@ def get_os(run_lambda):
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from platform import machine
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platform = get_platform()
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if platform == 'win32' or platform == 'cygwin':
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if platform in ["win32", "cygwin"]:
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return get_windows_version(run_lambda)
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if platform == 'darwin':
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@ -437,7 +609,7 @@ def get_libc_version():
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def get_pip_packages(run_lambda, patterns=None):
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"""Return `pip list` output. Note: will also find conda-installed pytorch and numpy packages."""
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if patterns is None:
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patterns = PIP_PATTERNS + COMMON_PATTERNS + NVIDIA_PATTERNS
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patterns = PIP_PATTERNS + COMMON_PATTERNS + NVIDIA_PATTERNS + ONEAPI_PATTERNS
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pip_version = 'pip3' if sys.version_info.major == 3 else 'pip'
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@ -504,6 +676,13 @@ def get_env_info():
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debug_mode_str = str(torch.version.debug)
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cuda_available_str = str(torch.cuda.is_available())
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cuda_version_str = torch.version.cuda
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xpu_available_str = str(torch.xpu.is_available())
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if torch.xpu.is_available():
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xpu_available_str = f'{xpu_available_str}\n' + \
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f'XPU used to build PyTorch: {torch.version.xpu}\n' + \
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f'Intel GPU driver version:\n{get_intel_gpu_driver_version(run_lambda)}\n' + \
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f'Intel GPU models onboard:\n{get_intel_gpu_onboard(run_lambda)}\n' + \
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f'Intel GPU models detected:\n{get_intel_gpu_detected(run_lambda)}'
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if not hasattr(torch.version, 'hip') or torch.version.hip is None: # cuda version
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hip_compiled_version = hip_runtime_version = miopen_runtime_version = 'N/A'
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else: # HIP version
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@ -517,7 +696,7 @@ def get_env_info():
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cuda_version_str = 'N/A'
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hip_compiled_version = torch.version.hip
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else:
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version_str = debug_mode_str = cuda_available_str = cuda_version_str = 'N/A'
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version_str = debug_mode_str = cuda_available_str = cuda_version_str = xpu_available_str = 'N/A'
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hip_compiled_version = hip_runtime_version = miopen_runtime_version = 'N/A'
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sys_version = sys.version.replace("\n", " ")
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@ -536,6 +715,7 @@ def get_env_info():
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nvidia_gpu_models=get_gpu_info(run_lambda),
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nvidia_driver_version=get_nvidia_driver_version(run_lambda),
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cudnn_version=get_cudnn_version(run_lambda),
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is_xpu_available=xpu_available_str,
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hip_compiled_version=hip_compiled_version,
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hip_runtime_version=hip_runtime_version,
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miopen_runtime_version=miopen_runtime_version,
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@ -572,6 +752,7 @@ CUDA_MODULE_LOADING set to: {cuda_module_loading}
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GPU models and configuration: {nvidia_gpu_models}
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Nvidia driver version: {nvidia_driver_version}
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cuDNN version: {cudnn_version}
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Is XPU available: {is_xpu_available}
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HIP runtime version: {hip_runtime_version}
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MIOpen runtime version: {miopen_runtime_version}
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Is XNNPACK available: {is_xnnpack_available}
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