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def test():
with plac.Interpreter(ishelve.main) as i:
i.check('.clear', 'cleared the shelve')
i.check('a=1', 'setting a=1')
i.check('a', '1')
i.check('.delete=a', 'deleted a')
i.check('a', 'a: not found')
def check_help(name):
sys.argv[0] = name + '.py' # avoid issue with pytest
plac_core._parser_registry.clear() # makes different imports independent
try:
try:
main = plac.import_main(name + '.py')
except SyntaxError:
if sys.version < '3': # expected for Python 2.X
return
else: # not expected for Python 3.X
raise
p = plac.parser_from(main)
expected = fix_today(open(name + '.help').read()).strip()
got = p.format_help().strip()
assert got == expected, got
finally:
sys.argv[0] = sys_argv0
def check_help(name):
sys.argv[0] = name + '.py' # avoid issue with pytest
plac_core._parser_registry.clear() # makes different imports independent
try:
try:
main = plac.import_main(name + '.py')
except SyntaxError:
if sys.version < '3': # expected for Python 2.X
return
else: # not expected for Python 3.X
raise
p = plac.parser_from(main)
expected = fix_today(open(name + '.help').read()).strip()
got = p.format_help().strip()
assert got == expected, got
finally:
sys.argv[0] = sys_argv0
def parser_from(f, **kw):
f.__annotations__ = kw
return plac.parser_from(f)
centroid = centroids[k]
plot_series(centroid, centroid_plot_foldpath, 'centroid', True)
members = X[y == k]
n_samples = members.shape[0]
sample_rows = np.arange(n_samples)
np.random.shuffle(sample_rows)
members_to_plot = members[sample_rows[:10]]
for i in xrange(members_to_plot.shape[0]):
print(k, i)
plot_series(members_to_plot[i], centroid_plot_foldpath, 'ex-%d' % i)
if __name__ == '__main__':
sys.exit(plac.call(main))
nr_row, nr_dim = header.split()
nlp.vocab.reset_vectors(width=int(nr_dim))
for line in file_:
line = line.rstrip().decode("utf8")
pieces = line.rsplit(" ", int(nr_dim))
word = pieces[0]
vector = numpy.asarray([float(v) for v in pieces[1:]], dtype="f")
nlp.vocab.set_vector(word, vector) # add the vectors to the vocab
# test the vectors and similarity
text = "class colspan"
doc = nlp(text)
print(text, doc[0].similarity(doc[1]))
if __name__ == "__main__":
plac.call(main)
i.interact(verbose=verbose)
elif multiline:
i.multiline(verbose=verbose)
elif serve:
i.start_server(serve)
elif batch:
run((fname,) + extra, 'execute', verbose)
elif test:
run((fname,) + extra, 'doctest', verbose)
print('run %s plac test(s)' % (len(extra) + 1))
else:
baseparser.print_usage()
main.add_help = False
if __name__ == '__main__':
plac.call(main)
max_ngram=plac.Annotation("Max N-gram length", 'option', 'm', int)
)
def main(input_file, alignment_file, output_file, max_ngram=10):
assert input_file and alignment_file and output_file, 'missing arguments'
with io.open(output_file, 'w', encoding='utf-8') as out, \
io.open(input_file, 'r', encoding='utf-8') as input_f, \
io.open(alignment_file, 'r', encoding='utf-8') as alignment_f:
for pair, alignment in izip(input_f, alignment_f):
source, target = pair.split(' ||| ')
for a, b in phrase_extraction(source, target, alignment):
a, b = whitespace_tokenizer(a), whitespace_tokenizer(b)
if 1 <= len(a) <= max_ngram and 1 <= len(b) <= max_ngram:
out.write('{0} ||| {1}\n'.format(' '.join(a), ' '.join(b)))
logging.info((output_file))
job_wd=Annotation("working dir for job", 'option'),
)
def runs(self, script, params=None, group=1, grid="mas", jobname="job", job_cwd=False, job_wd=None):
if not os.path.exists(params) and not os.path.isfile(script):
print("Parameter space file not found: {path}".format(path=params), file=sys.stderr)
sys.exit(1)
ps = ParamSpace(filename=params)
ps.write_grid_summary(jobname + '_params.csv')
grid_cfg = DEFAULT_CONFIGS[grid]
param_grid = ps.param_grid(include_id=True, id_param="id")
job_files = write_job_files(grid_cfg, script, jobname, param_grid, group, jobname, job_cwd, job_wd)
for job_file in job_files:
try:
def submit_tasks(self):
npoints = math.ceil(self.npoints / self.n_cpu)
self.i = plac.Interpreter(self).__enter__()
return [self.i.submit('calc_pi %d' % npoints)
for _ in range(self.n_cpu)]