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Computational requirements check
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from os import listdir
from os.path import isfile, join
from pathlib import Path
# TODO: I have the option of maybe making a check for accuracy/metrics?
# Note, some of these are marked as FALSE instead of TRUE because the
# information is hidden somewhere non-standard, e.g. described in prose
# Intended Purpose, General Limitations, Computational Requirements
expected_check_results = {
"albert-base-v2": [True, True, False],
"bert-base-cased": [True, True, False],
"bert-base-multilingual-cased": [True, True, False],
"bert-base-uncased": [True, True, False],
"big-science___bloom": [True, True, True],
"cl-tohoku___bert-base-japanese-whole-word-masking": [False, False, False],
"distilbert-base-cased-distilled-squad": [True, True, True],
"distilbert-base-uncased": [True, True, False],
"distilbert-base-uncased-finetuned-sst-2-english": [True, True, False],
"distilroberta-base": [True, True, False],
"emilyalsentzer___Bio_ClinicalBERT": [False, False, False],
"facebook___bart-large-mnli": [False, False, False],
"google___electra-base-discriminator": [False, False, False],
"gpt2": [True, True, False],
"Helsinki-NLP___opus-mt-en-es": [False, False, False],
"jonatasgrosman___wav2vec2-large-xlsr-53-english": [False, False, False],
"microsoft___layoutlmv3-base": [False, False, False],
"openai___clip-vit-base-patch32": [True, True, False],
"openai___clip-vit-large-patch14": [True, True, False],
"philschmid___bart-large-cnn-samsum": [False, False, False],
"prajjwal1___bert-tiny": [False, False, False],
"roberta-base": [True, True, False],
"roberta-large": [True, True, False],
"runwayml___stable-diffusion-v1-5": [True, True, False],
"sentence-transformers___all-MiniLM-L6-v2": [True, False, False],
"StanfordAIMI___stanford-deidentifier-base": [False, False, False],
"t5-base": [True, False, False],
"t5-small": [True, False, False],
"xlm-roberta-base": [True, True, False],
"xlm-roberta-large": [True, True, False],
"yiyanghkust___finbert-tone": [False, False, False],
}
def pytest_generate_tests(metafunc):
if "real_model_card" in metafunc.fixturenames:
files = [f"cards/{f}" for f in listdir("cards") if isfile(join("cards", f))]
cards = [Path(f).read_text() for f in files]
model_ids = [f.replace("cards/", "").replace(".md", "") for f in files]
# TODO: IMPORTANT – remove the default [False, False, False]
expected_results = [expected_check_results.get(m, [False, False, False]) for m, c in zip(model_ids, cards)]
metafunc.parametrize(
["real_model_card", "expected_check_results"],
list(map(list, zip(cards, expected_results)))
)
# rows = read_csvrows()
# if 'row' in metafunc.fixturenames:
# metafunc.parametrize('row', rows)
# if 'col' in metafunc.fixturenames:
# metafunc.parametrize('col', list(itertools.chain(*rows)))