module context.machine
¶
Short summary¶
module pymlbenchmark.context.machine
Helpers which returns more information about the system.
Functions¶
function |
truncated documentation |
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Retrieves information about numpy compilation. |
|
Returns information about the machine. |
Documentation¶
Helpers which returns more information about the system.
- pymlbenchmark.context.machine.get_numpy_info()¶
Retrieves information about numpy compilation.
- pymlbenchmark.context.machine.machine_information(pkgs=None)¶
Returns information about the machine.
- Parameters:
pkgs – if not None, adds version information for the listed packages
- Returns:
list of dictionaries
<<<
from pymlbenchmark.context import machine_information for row in machine_information(): print(row)
>>>
{'name': 'date', 'version': '2023-03-08'} {'name': 'python', 'value': '3.9.1 (default, Jan 18 2021, 16:35:58) \n[GCC 8.3.0]'} {'name': 'platform', 'value': 'linux'} {'name': 'OS', 'value': 'Linux-4.19.0-23-amd64-x86_64-with-glibc2.28'} {'name': 'machine', 'value': 'x86_64'} {'name': 'processor', 'value': ''} {'name': 'release', 'value': '4.19.0-23-amd64'} {'name': 'architecture', 'value': ('64bit', 'ELF')} {'name': 'arch', 'value': 'X86_64'} {'name': 'brand_raw', 'value': 'Intel(R) Atom(TM) CPU C2750 @ 2.40GHz'} {'name': 'count', 'value': 8} {'name': 'flags', 'value': '3dnowprefetch acpi aes aperfmperf apic arat arch_perfmon bts clflush cmov constant_tsc cpuid cpuid_fault cx16 cx8 de ds_cpl dtes64 dtherm dts epb ept erms est flexpriority fpu fxsr ht ibpb ibrs ida lahf_lm lm mca mce mmx monitor movbe msr mtrr nonstop_tsc nopl nx pae pat pbe pclmulqdq pdcm pebs pge pni popcnt pse pse36 pti rdrand rdrnd rdtscp rep_good sep smep ss sse sse2 sse4_1 sse4_2 ssse3 stibp syscall tm tm2 tpr_shadow tsc tsc_adjust tsc_deadline_timer tscdeadline vme vmx vnmi vpid xtopology xtpr'} {'name': 'hz_advertised', 'value': [2400000000, 0]} {'name': 'l1_data_cache_size', 'value': 24576} {'name': 'l1_instruction_cache_size', 'value': 32768} {'name': 'l2_cache_associativity', 'value': 8} {'name': 'l2_cache_line_size', 'value': 1024} {'name': 'l2_cache_size', 'value': 1048576} {'name': 'l3_cache_size', 'value': 1048576} {'name': 'stepping', 'value': 8}
<<<
from pymlbenchmark.context import machine_information import numpy import pandas print(pandas.DataFrame(machine_information(['numpy'])))
>>>
name ... value 0 date ... NaN 1 python ... 3.9.1 (default, Jan 18 2021, 16:35:58) \n[GCC ... 2 platform ... linux 3 OS ... Linux-4.19.0-23-amd64-x86_64-with-glibc2.28 4 machine ... x86_64 5 processor ... 6 release ... 4.19.0-23-amd64 7 architecture ... (64bit, ELF) 8 arch ... X86_64 9 brand_raw ... Intel(R) Atom(TM) CPU C2750 @ 2.40GHz 10 count ... 8 11 flags ... 3dnowprefetch acpi aes aperfmperf apic arat ar... 12 hz_advertised ... [2400000000, 0] 13 l1_data_cache_size ... 24576 14 l1_instruction_cache_size ... 32768 15 l2_cache_associativity ... 8 16 l2_cache_line_size ... 1024 17 l2_cache_size ... 1048576 18 l3_cache_size ... 1048576 19 stepping ... 8 20 numpy ... openblas, language=c [21 rows x 3 columns]