690 lines
26 KiB
Python
690 lines
26 KiB
Python
import json
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import locale
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import multiprocessing
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import os
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import platform
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import textwrap
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import sys
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from contextlib import redirect_stdout
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from datetime import datetime
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from io import StringIO
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from subprocess import check_output, PIPE, CalledProcessError
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import numpy as np
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import llvmlite.binding as llvmbind
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from llvmlite import __version__ as llvmlite_version
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from numba import cuda as cu, __version__ as version_number
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from numba.cuda import cudadrv
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from numba.cuda.cudadrv.driver import driver as cudriver
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from numba.cuda.cudadrv.runtime import runtime as curuntime
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from numba.core import config
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_psutil_import = False
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try:
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import psutil
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except ImportError:
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pass
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else:
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_psutil_import = True
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__all__ = ['get_sysinfo', 'display_sysinfo']
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# Keys of a `sysinfo` dictionary
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# Time info
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_start, _start_utc, _runtime = 'Start', 'Start UTC', 'Runtime'
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_numba_version = 'Numba Version'
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# Hardware info
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_machine = 'Machine'
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_cpu_name, _cpu_count = 'CPU Name', 'CPU Count'
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_cpus_allowed, _cpus_list = 'CPUs Allowed', 'List CPUs Allowed'
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_cpu_features = 'CPU Features'
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_cfs_quota, _cfs_period = 'CFS Quota', 'CFS Period',
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_cfs_restrict = 'CFS Restriction'
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_mem_total, _mem_available = 'Mem Total', 'Mem Available'
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# OS info
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_platform_name, _platform_release = 'Platform Name', 'Platform Release'
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_os_name, _os_version = 'OS Name', 'OS Version'
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_os_spec_version = 'OS Specific Version'
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_libc_version = 'Libc Version'
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# Python info
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_python_comp = 'Python Compiler'
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_python_impl = 'Python Implementation'
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_python_version = 'Python Version'
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_python_locale = 'Python Locale'
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# LLVM info
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_llvmlite_version = 'llvmlite Version'
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_llvm_version = 'LLVM Version'
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# CUDA info
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_cu_dev_init = 'CUDA Device Init'
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_cu_drv_ver = 'CUDA Driver Version'
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_cu_rt_ver = 'CUDA Runtime Version'
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_cu_nvidia_bindings = 'NVIDIA CUDA Bindings'
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_cu_nvidia_bindings_used = 'NVIDIA CUDA Bindings In Use'
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_cu_detect_out, _cu_lib_test = 'CUDA Detect Output', 'CUDA Lib Test'
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_cu_mvc_available = 'NVIDIA CUDA Minor Version Compatibility Available'
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_cu_mvc_needed = 'NVIDIA CUDA Minor Version Compatibility Needed'
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_cu_mvc_in_use = 'NVIDIA CUDA Minor Version Compatibility In Use'
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# NumPy info
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_numpy_version = 'NumPy Version'
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_numpy_supported_simd_features = 'NumPy Supported SIMD features'
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_numpy_supported_simd_dispatch = 'NumPy Supported SIMD dispatch'
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_numpy_supported_simd_baseline = 'NumPy Supported SIMD baseline'
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_numpy_AVX512_SKX_detected = 'NumPy AVX512_SKX detected'
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# SVML info
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_svml_state, _svml_loaded = 'SVML State', 'SVML Lib Loaded'
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_llvm_svml_patched = 'LLVM SVML Patched'
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_svml_operational = 'SVML Operational'
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# Threading layer info
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_tbb_thread, _tbb_error = 'TBB Threading', 'TBB Threading Error'
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_openmp_thread, _openmp_error = 'OpenMP Threading', 'OpenMP Threading Error'
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_openmp_vendor = 'OpenMP vendor'
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_wkq_thread, _wkq_error = 'Workqueue Threading', 'Workqueue Threading Error'
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# Numba info
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_numba_env_vars = 'Numba Env Vars'
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# Conda info
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_conda_build_ver, _conda_env_ver = 'Conda Build', 'Conda Env'
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_conda_platform, _conda_python_ver = 'Conda Platform', 'Conda Python Version'
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_conda_root_writable = 'Conda Root Writable'
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# Packages info
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_inst_pkg = 'Installed Packages'
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# Psutil info
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_psutil = 'Psutil Available'
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# Errors and warnings
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_errors = 'Errors'
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_warnings = 'Warnings'
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# Error and warning log
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_error_log = []
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_warning_log = []
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def get_os_spec_info(os_name):
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# Linux man page for `/proc`:
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# http://man7.org/linux/man-pages/man5/proc.5.html
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# Windows documentation for `wmic OS`:
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# https://docs.microsoft.com/en-us/windows/win32/cimwin32prov/cim-operatingsystem
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# MacOS man page for `sysctl`:
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# https://www.unix.com/man-page/osx/3/sysctl/
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# MacOS man page for `vm_stat`:
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# https://www.unix.com/man-page/osx/1/vm_stat/
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class CmdBufferOut(tuple):
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buffer_output_flag = True
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class CmdReadFile(tuple):
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read_file_flag = True
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shell_params = {
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'Linux': {
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'cmd': (
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CmdReadFile(('/sys/fs/cgroup/cpuacct/cpu.cfs_quota_us',)),
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CmdReadFile(('/sys/fs/cgroup/cpuacct/cpu.cfs_period_us',)),
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),
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'cmd_optional': (
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CmdReadFile(('/proc/meminfo',)),
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CmdReadFile(('/proc/self/status',)),
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),
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'kwds': {
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# output string fragment -> result dict key
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'MemTotal:': _mem_total,
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'MemAvailable:': _mem_available,
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'Cpus_allowed:': _cpus_allowed,
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'Cpus_allowed_list:': _cpus_list,
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'/sys/fs/cgroup/cpuacct/cpu.cfs_quota_us': _cfs_quota,
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'/sys/fs/cgroup/cpuacct/cpu.cfs_period_us': _cfs_period,
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},
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},
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'Windows': {
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'cmd': (),
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'cmd_optional': (
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CmdBufferOut(('wmic', 'OS', 'get', 'TotalVirtualMemorySize')),
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CmdBufferOut(('wmic', 'OS', 'get', 'FreeVirtualMemory')),
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),
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'kwds': {
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# output string fragment -> result dict key
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'TotalVirtualMemorySize': _mem_total,
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'FreeVirtualMemory': _mem_available,
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},
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},
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'Darwin': {
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'cmd': (),
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'cmd_optional': (
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('sysctl', 'hw.memsize'),
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('vm_stat'),
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),
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'kwds': {
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# output string fragment -> result dict key
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'hw.memsize:': _mem_total,
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'free:': _mem_available,
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},
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'units': {
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_mem_total: 1, # Size is given in bytes.
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_mem_available: 4096, # Size is given in 4kB pages.
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},
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},
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}
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os_spec_info = {}
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params = shell_params.get(os_name, {})
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cmd_selected = params.get('cmd', ())
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if _psutil_import:
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vm = psutil.virtual_memory()
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os_spec_info.update({
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_mem_total: vm.total,
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_mem_available: vm.available,
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})
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p = psutil.Process()
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cpus_allowed = p.cpu_affinity() if hasattr(p, 'cpu_affinity') else []
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if cpus_allowed:
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os_spec_info[_cpus_allowed] = len(cpus_allowed)
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os_spec_info[_cpus_list] = ' '.join(str(n) for n in cpus_allowed)
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else:
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_warning_log.append(
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"Warning (psutil): psutil cannot be imported. "
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"For more accuracy, consider installing it.")
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# Fallback to internal heuristics
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cmd_selected += params.get('cmd_optional', ())
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# Assuming the shell cmd returns a unique (k, v) pair per line
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# or a unique (k, v) pair spread over several lines:
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# Gather output in a list of strings containing a keyword and some value.
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output = []
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for cmd in cmd_selected:
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if hasattr(cmd, 'read_file_flag'):
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# Open file within Python
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if os.path.exists(cmd[0]):
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try:
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with open(cmd[0], 'r') as f:
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out = f.readlines()
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if out:
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out[0] = ' '.join((cmd[0], out[0]))
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output.extend(out)
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except OSError as e:
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_error_log.append(f'Error (file read): {e}')
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continue
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else:
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_warning_log.append('Warning (no file): {}'.format(cmd[0]))
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continue
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else:
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# Spawn a subprocess
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try:
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out = check_output(cmd, stderr=PIPE)
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except (OSError, CalledProcessError) as e:
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_error_log.append(f'Error (subprocess): {e}')
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continue
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if hasattr(cmd, 'buffer_output_flag'):
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out = b' '.join(line for line in out.splitlines()) + b'\n'
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output.extend(out.decode().splitlines())
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# Extract (k, output) pairs by searching for keywords in output
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kwds = params.get('kwds', {})
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for line in output:
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match = kwds.keys() & line.split()
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if match and len(match) == 1:
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k = kwds[match.pop()]
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os_spec_info[k] = line
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elif len(match) > 1:
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print(f'Ambiguous output: {line}')
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# Try to extract something meaningful from output string
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def format():
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# CFS restrictions
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split = os_spec_info.get(_cfs_quota, '').split()
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if split:
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os_spec_info[_cfs_quota] = float(split[-1])
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split = os_spec_info.get(_cfs_period, '').split()
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if split:
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os_spec_info[_cfs_period] = float(split[-1])
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if os_spec_info.get(_cfs_quota, -1) != -1:
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cfs_quota = os_spec_info.get(_cfs_quota, '')
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cfs_period = os_spec_info.get(_cfs_period, '')
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runtime_amount = cfs_quota / cfs_period
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os_spec_info[_cfs_restrict] = runtime_amount
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def format_optional():
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# Memory
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units = {_mem_total: 1024, _mem_available: 1024}
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units.update(params.get('units', {}))
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for k in (_mem_total, _mem_available):
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digits = ''.join(d for d in os_spec_info.get(k, '') if d.isdigit())
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os_spec_info[k] = int(digits or 0) * units[k]
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# Accessible CPUs
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split = os_spec_info.get(_cpus_allowed, '').split()
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if split:
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n = split[-1]
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n = n.split(',')[-1]
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os_spec_info[_cpus_allowed] = str(bin(int(n or 0, 16))).count('1')
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split = os_spec_info.get(_cpus_list, '').split()
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if split:
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os_spec_info[_cpus_list] = split[-1]
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try:
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format()
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if not _psutil_import:
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format_optional()
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except Exception as e:
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_error_log.append(f'Error (format shell output): {e}')
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# Call OS specific functions
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os_specific_funcs = {
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'Linux': {
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_libc_version: lambda: ' '.join(platform.libc_ver())
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},
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'Windows': {
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_os_spec_version: lambda: ' '.join(
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s for s in platform.win32_ver()),
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},
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'Darwin': {
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_os_spec_version: lambda: ''.join(
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i or ' ' for s in tuple(platform.mac_ver()) for i in s),
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},
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}
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key_func = os_specific_funcs.get(os_name, {})
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os_spec_info.update({k: f() for k, f in key_func.items()})
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return os_spec_info
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def get_sysinfo():
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# Gather the information that shouldn't raise exceptions
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sys_info = {
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_start: datetime.now(),
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_start_utc: datetime.utcnow(),
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_machine: platform.machine(),
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_cpu_name: llvmbind.get_host_cpu_name(),
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_cpu_count: multiprocessing.cpu_count(),
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_platform_name: platform.platform(aliased=True),
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_platform_release: platform.release(),
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_os_name: platform.system(),
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_os_version: platform.version(),
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_python_comp: platform.python_compiler(),
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_python_impl: platform.python_implementation(),
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_python_version: platform.python_version(),
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_numba_env_vars: {k: v for (k, v) in os.environ.items()
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if k.startswith('NUMBA_')},
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_numba_version: version_number,
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_llvm_version: '.'.join(str(i) for i in llvmbind.llvm_version_info),
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_llvmlite_version: llvmlite_version,
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_psutil: _psutil_import,
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}
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# CPU features
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try:
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feature_map = llvmbind.get_host_cpu_features()
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except RuntimeError as e:
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_error_log.append(f'Error (CPU features): {e}')
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else:
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features = sorted([key for key, value in feature_map.items() if value])
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sys_info[_cpu_features] = ' '.join(features)
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# Python locale
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# On MacOSX, getdefaultlocale can raise. Check again if Py > 3.7.5
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try:
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# If $LANG is unset, getdefaultlocale() can return (None, None), make
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# sure we can encode this as strings by casting explicitly.
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sys_info[_python_locale] = '.'.join([str(i) for i in
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locale.getdefaultlocale()])
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except Exception as e:
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_error_log.append(f'Error (locale): {e}')
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# CUDA information
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try:
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cu.list_devices()[0] # will a device initialise?
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except Exception as e:
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sys_info[_cu_dev_init] = False
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msg_not_found = "CUDA driver library cannot be found"
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msg_disabled_by_user = "CUDA is disabled"
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msg_end = " or no CUDA enabled devices are present."
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msg_generic_problem = "CUDA device initialisation problem."
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msg = getattr(e, 'msg', None)
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if msg is not None:
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if msg_not_found in msg:
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err_msg = msg_not_found + msg_end
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elif msg_disabled_by_user in msg:
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err_msg = msg_disabled_by_user + msg_end
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else:
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err_msg = msg_generic_problem + " Message:" + msg
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else:
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err_msg = msg_generic_problem + " " + str(e)
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# Best effort error report
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_warning_log.append("Warning (cuda): %s\nException class: %s" %
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(err_msg, str(type(e))))
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else:
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try:
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sys_info[_cu_dev_init] = True
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output = StringIO()
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with redirect_stdout(output):
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cu.detect()
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sys_info[_cu_detect_out] = output.getvalue()
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output.close()
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cu_drv_ver = cudriver.get_version()
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cu_rt_ver = curuntime.get_version()
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sys_info[_cu_drv_ver] = '%s.%s' % cu_drv_ver
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sys_info[_cu_rt_ver] = '%s.%s' % cu_rt_ver
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output = StringIO()
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with redirect_stdout(output):
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cudadrv.libs.test()
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sys_info[_cu_lib_test] = output.getvalue()
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output.close()
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try:
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from cuda import cuda # noqa: F401
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nvidia_bindings_available = True
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except ImportError:
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nvidia_bindings_available = False
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sys_info[_cu_nvidia_bindings] = nvidia_bindings_available
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nv_binding_used = bool(cudadrv.driver.USE_NV_BINDING)
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sys_info[_cu_nvidia_bindings_used] = nv_binding_used
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try:
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from ptxcompiler import compile_ptx # noqa: F401
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from cubinlinker import CubinLinker # noqa: F401
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sys_info[_cu_mvc_available] = True
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except ImportError:
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sys_info[_cu_mvc_available] = False
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sys_info[_cu_mvc_needed] = cu_rt_ver > cu_drv_ver
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sys_info[_cu_mvc_in_use] = bool(
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config.CUDA_ENABLE_MINOR_VERSION_COMPATIBILITY)
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except Exception as e:
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_warning_log.append(
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"Warning (cuda): Probing CUDA failed "
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"(device and driver present, runtime problem?)\n"
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f"(cuda) {type(e)}: {e}")
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# NumPy information
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sys_info[_numpy_version] = np.version.full_version
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try:
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# NOTE: These consts were added in NumPy 1.20
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from numpy.core._multiarray_umath import (__cpu_features__,
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__cpu_dispatch__,
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__cpu_baseline__,)
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except ImportError:
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sys_info[_numpy_AVX512_SKX_detected] = False
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else:
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feat_filtered = [k for k, v in __cpu_features__.items() if v]
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sys_info[_numpy_supported_simd_features] = feat_filtered
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sys_info[_numpy_supported_simd_dispatch] = __cpu_dispatch__
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sys_info[_numpy_supported_simd_baseline] = __cpu_baseline__
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sys_info[_numpy_AVX512_SKX_detected] = \
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__cpu_features__.get("AVX512_SKX", False)
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|
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# SVML information
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# Replicate some SVML detection logic from numba.__init__ here.
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# If SVML load fails in numba.__init__ the splitting of the logic
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# here will help diagnosing the underlying issue.
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svml_lib_loaded = True
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try:
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if sys.platform.startswith('linux'):
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llvmbind.load_library_permanently("libsvml.so")
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elif sys.platform.startswith('darwin'):
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llvmbind.load_library_permanently("libsvml.dylib")
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elif sys.platform.startswith('win'):
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llvmbind.load_library_permanently("svml_dispmd")
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else:
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svml_lib_loaded = False
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except Exception:
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svml_lib_loaded = False
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func = getattr(llvmbind.targets, "has_svml", None)
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sys_info[_llvm_svml_patched] = func() if func else False
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sys_info[_svml_state] = config.USING_SVML
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sys_info[_svml_loaded] = svml_lib_loaded
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sys_info[_svml_operational] = all((
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sys_info[_svml_state],
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sys_info[_svml_loaded],
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sys_info[_llvm_svml_patched],
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))
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# Check which threading backends are available.
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def parse_error(e, backend):
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# parses a linux based error message, this is to provide feedback
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# and hide user paths etc
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try:
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path, problem, symbol = [x.strip() for x in e.msg.split(':')]
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extn_dso = os.path.split(path)[1]
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if backend in extn_dso:
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return "%s: %s" % (problem, symbol)
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except Exception:
|
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pass
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return "Unknown import problem."
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try:
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# check import is ok, this means the DSO linkage is working
|
|
from numba.np.ufunc import tbbpool # NOQA
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|
# check that the version is compatible, this is a check performed at
|
|
# runtime (well, compile time), it will also ImportError if there's
|
|
# a problem.
|
|
from numba.np.ufunc.parallel import _check_tbb_version_compatible
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|
_check_tbb_version_compatible()
|
|
sys_info[_tbb_thread] = True
|
|
except ImportError as e:
|
|
# might be a missing symbol due to e.g. tbb libraries missing
|
|
sys_info[_tbb_thread] = False
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|
sys_info[_tbb_error] = parse_error(e, 'tbbpool')
|
|
|
|
try:
|
|
from numba.np.ufunc import omppool
|
|
sys_info[_openmp_thread] = True
|
|
sys_info[_openmp_vendor] = omppool.openmp_vendor
|
|
except ImportError as e:
|
|
sys_info[_openmp_thread] = False
|
|
sys_info[_openmp_error] = parse_error(e, 'omppool')
|
|
|
|
try:
|
|
from numba.np.ufunc import workqueue # NOQA
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|
sys_info[_wkq_thread] = True
|
|
except ImportError as e:
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|
sys_info[_wkq_thread] = True
|
|
sys_info[_wkq_error] = parse_error(e, 'workqueue')
|
|
|
|
# Look for conda and installed packages information
|
|
cmd = ('conda', 'info', '--json')
|
|
try:
|
|
conda_out = check_output(cmd)
|
|
except Exception as e:
|
|
_warning_log.append(f'Warning: Conda not available.\n Error was {e}\n')
|
|
# Conda is not available, try pip list to list installed packages
|
|
cmd = (sys.executable, '-m', 'pip', 'list')
|
|
try:
|
|
reqs = check_output(cmd)
|
|
except Exception as e:
|
|
_error_log.append(f'Error (pip): {e}')
|
|
else:
|
|
sys_info[_inst_pkg] = reqs.decode().splitlines()
|
|
|
|
else:
|
|
jsond = json.loads(conda_out.decode())
|
|
keys = {
|
|
'conda_build_version': _conda_build_ver,
|
|
'conda_env_version': _conda_env_ver,
|
|
'platform': _conda_platform,
|
|
'python_version': _conda_python_ver,
|
|
'root_writable': _conda_root_writable,
|
|
}
|
|
for conda_k, sysinfo_k in keys.items():
|
|
sys_info[sysinfo_k] = jsond.get(conda_k, 'N/A')
|
|
|
|
# Get info about packages in current environment
|
|
cmd = ('conda', 'list')
|
|
try:
|
|
conda_out = check_output(cmd)
|
|
except CalledProcessError as e:
|
|
_error_log.append(f'Error (conda): {e}')
|
|
else:
|
|
data = conda_out.decode().splitlines()
|
|
sys_info[_inst_pkg] = [l for l in data if not l.startswith('#')]
|
|
|
|
sys_info.update(get_os_spec_info(sys_info[_os_name]))
|
|
sys_info[_errors] = _error_log
|
|
sys_info[_warnings] = _warning_log
|
|
sys_info[_runtime] = (datetime.now() - sys_info[_start]).total_seconds()
|
|
return sys_info
|
|
|
|
|
|
def display_sysinfo(info=None, sep_pos=45):
|
|
class DisplayMap(dict):
|
|
display_map_flag = True
|
|
|
|
class DisplaySeq(tuple):
|
|
display_seq_flag = True
|
|
|
|
class DisplaySeqMaps(tuple):
|
|
display_seqmaps_flag = True
|
|
|
|
if info is None:
|
|
info = get_sysinfo()
|
|
|
|
fmt = f'%-{sep_pos}s : %-s'
|
|
MB = 1024**2
|
|
template = (
|
|
("-" * 80,),
|
|
("__Time Stamp__",),
|
|
("Report started (local time)", info.get(_start, '?')),
|
|
("UTC start time", info.get(_start_utc, '?')),
|
|
("Running time (s)", info.get(_runtime, '?')),
|
|
("",),
|
|
("__Hardware Information__",),
|
|
("Machine", info.get(_machine, '?')),
|
|
("CPU Name", info.get(_cpu_name, '?')),
|
|
("CPU Count", info.get(_cpu_count, '?')),
|
|
("Number of accessible CPUs", info.get(_cpus_allowed, '?')),
|
|
("List of accessible CPUs cores", info.get(_cpus_list, '?')),
|
|
("CFS Restrictions (CPUs worth of runtime)",
|
|
info.get(_cfs_restrict, 'None')),
|
|
("",),
|
|
("CPU Features", '\n'.join(
|
|
' ' * (sep_pos + 3) + l if i else l
|
|
for i, l in enumerate(
|
|
textwrap.wrap(
|
|
info.get(_cpu_features, '?'),
|
|
width=79 - sep_pos
|
|
)
|
|
)
|
|
)),
|
|
("",),
|
|
("Memory Total (MB)", info.get(_mem_total, 0) // MB or '?'),
|
|
("Memory Available (MB)"
|
|
if info.get(_os_name, '') != 'Darwin' or info.get(_psutil, False)
|
|
else "Free Memory (MB)", info.get(_mem_available, 0) // MB or '?'),
|
|
("",),
|
|
("__OS Information__",),
|
|
("Platform Name", info.get(_platform_name, '?')),
|
|
("Platform Release", info.get(_platform_release, '?')),
|
|
("OS Name", info.get(_os_name, '?')),
|
|
("OS Version", info.get(_os_version, '?')),
|
|
("OS Specific Version", info.get(_os_spec_version, '?')),
|
|
("Libc Version", info.get(_libc_version, '?')),
|
|
("",),
|
|
("__Python Information__",),
|
|
DisplayMap({k: v for k, v in info.items() if k.startswith('Python')}),
|
|
("",),
|
|
("__Numba Toolchain Versions__",),
|
|
("Numba Version", info.get(_numba_version, '?')),
|
|
("llvmlite Version", info.get(_llvmlite_version, '?')),
|
|
("",),
|
|
("__LLVM Information__",),
|
|
("LLVM Version", info.get(_llvm_version, '?')),
|
|
("",),
|
|
("__CUDA Information__",),
|
|
("CUDA Device Initialized", info.get(_cu_dev_init, '?')),
|
|
("CUDA Driver Version", info.get(_cu_drv_ver, '?')),
|
|
("CUDA Runtime Version", info.get(_cu_rt_ver, '?')),
|
|
("CUDA NVIDIA Bindings Available", info.get(_cu_nvidia_bindings, '?')),
|
|
("CUDA NVIDIA Bindings In Use",
|
|
info.get(_cu_nvidia_bindings_used, '?')),
|
|
("CUDA Minor Version Compatibility Available",
|
|
info.get(_cu_mvc_available, '?')),
|
|
("CUDA Minor Version Compatibility Needed",
|
|
info.get(_cu_mvc_needed, '?')),
|
|
("CUDA Minor Version Compatibility In Use",
|
|
info.get(_cu_mvc_in_use, '?')),
|
|
("CUDA Detect Output:",),
|
|
(info.get(_cu_detect_out, "None"),),
|
|
("CUDA Libraries Test Output:",),
|
|
(info.get(_cu_lib_test, "None"),),
|
|
("",),
|
|
("__NumPy Information__",),
|
|
("NumPy Version", info.get(_numpy_version, '?')),
|
|
("NumPy Supported SIMD features",
|
|
DisplaySeq(info.get(_numpy_supported_simd_features, [])
|
|
or ('None found.',))),
|
|
("NumPy Supported SIMD dispatch",
|
|
DisplaySeq(info.get(_numpy_supported_simd_dispatch, [])
|
|
or ('None found.',))),
|
|
("NumPy Supported SIMD baseline",
|
|
DisplaySeq(info.get(_numpy_supported_simd_baseline, [])
|
|
or ('None found.',))),
|
|
("NumPy AVX512_SKX support detected",
|
|
info.get(_numpy_AVX512_SKX_detected, '?')),
|
|
("",),
|
|
("__SVML Information__",),
|
|
("SVML State, config.USING_SVML", info.get(_svml_state, '?')),
|
|
("SVML Library Loaded", info.get(_svml_loaded, '?')),
|
|
("llvmlite Using SVML Patched LLVM", info.get(_llvm_svml_patched, '?')),
|
|
("SVML Operational", info.get(_svml_operational, '?')),
|
|
("",),
|
|
("__Threading Layer Information__",),
|
|
("TBB Threading Layer Available", info.get(_tbb_thread, '?')),
|
|
("+-->TBB imported successfully." if info.get(_tbb_thread, '?')
|
|
else f"+--> Disabled due to {info.get(_tbb_error, '?')}",),
|
|
("OpenMP Threading Layer Available", info.get(_openmp_thread, '?')),
|
|
(f"+-->Vendor: {info.get(_openmp_vendor, '?')}"
|
|
if info.get(_openmp_thread, False)
|
|
else f"+--> Disabled due to {info.get(_openmp_error, '?')}",),
|
|
("Workqueue Threading Layer Available", info.get(_wkq_thread, '?')),
|
|
("+-->Workqueue imported successfully." if info.get(_wkq_thread, False)
|
|
else f"+--> Disabled due to {info.get(_wkq_error, '?')}",),
|
|
("",),
|
|
("__Numba Environment Variable Information__",),
|
|
(DisplayMap(info.get(_numba_env_vars, {})) or ('None found.',)),
|
|
("",),
|
|
("__Conda Information__",),
|
|
(DisplayMap({k: v for k, v in info.items()
|
|
if k.startswith('Conda')}) or ("Conda not available.",)),
|
|
("",),
|
|
("__Installed Packages__",),
|
|
DisplaySeq(info.get(_inst_pkg, ("Couldn't retrieve packages info.",))),
|
|
("",),
|
|
("__Error log__" if info.get(_errors, [])
|
|
else "No errors reported.",),
|
|
DisplaySeq(info.get(_errors, [])),
|
|
("",),
|
|
("__Warning log__" if info.get(_warnings, [])
|
|
else "No warnings reported.",),
|
|
DisplaySeq(info.get(_warnings, [])),
|
|
("-" * 80,),
|
|
("If requested, please copy and paste the information between\n"
|
|
"the dashed (----) lines, or from a given specific section as\n"
|
|
"appropriate.\n\n"
|
|
"=============================================================\n"
|
|
"IMPORTANT: Please ensure that you are happy with sharing the\n"
|
|
"contents of the information present, any information that you\n"
|
|
"wish to keep private you should remove before sharing.\n"
|
|
"=============================================================\n",),
|
|
)
|
|
for t in template:
|
|
if hasattr(t, 'display_seq_flag'):
|
|
print(*t, sep='\n')
|
|
elif hasattr(t, 'display_map_flag'):
|
|
print(*tuple(fmt % (k, v) for (k, v) in t.items()), sep='\n')
|
|
elif hasattr(t, 'display_seqmaps_flag'):
|
|
for d in t:
|
|
print(*tuple(fmt % ('\t' + k, v) for (k, v) in d.items()),
|
|
sep='\n', end='\n')
|
|
elif len(t) == 2:
|
|
print(fmt % t)
|
|
else:
|
|
print(*t)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
display_sysinfo()
|