Check a prototype of 2nd version of this platform
being developed by cKnowledge.org in collaboration with
MLCommons.
time_to_solution vqe
ck-action:time_to_solution vqe (v1.0.0)
License: BSD 3-clause (code) and CC BY-SA 4.0 (data)
Creation date: 2018-07-17
Source: GitHub
cID: 081173242a88bc94:2e99d5fdad439087
Don't hesitate to get in touch if you encounter any issues or would like to discuss this community project!
Creation date: 2018-07-17
Source: GitHub
cID: 081173242a88bc94:2e99d5fdad439087
Description
- Automation framework: CK
- Workflow: VQE quantum competition pipeline
- Development repository: ck-quantum
- Source: GitHub
- How to get the stable version via the CK client:
pip install cbench
cb download module:vqe --version=1.0.0 --all
ck time_to_solution vqe --help - How to get the development version:
pip install ck
ck pull repo:ck-quantum
ck time_to_solution vqe --help
- How to run from Python:
import ck.kernel as ck
r=ck.access({'action':'',
'module_uoa':'',
... See JSON API below ...
})
if r['return']>0: return r
...
- Module description: simplify running the vqe pipeline and recording the results
- API Python code: Link
- JSON API:
" Input: { (cids[]) - CIDs of entries to compute the TTS metric for (interactive by default) OR (repo_uoa) - experiment repository name (defaults to 'local', but can be overridden by '*') (extra_tags) - extra tags to filter (delta) - delta parameter of TTS metric (prob) - probability parameter of TTS metric (which_fun) - 'fun_exact', 'fun_validated' or 'fun' (which_time) - 'total_q_shots' or 'total_q_seconds' (show_more) - more verbose if 'yes' } Output: { return - return code = 0, if successful > 0, if error (error) - error text if return > 0 } "