text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>def printconvertedresults(kilometer1, kilometer2, kilometer3, kilometer4, kilometer5, kilometer6, kilometer7,kilometer8,kilometer9,kilometer10)
print("kilometers\tMiles")
print( str( Kilometer1)+ "\t"+calcMiles( kilometers1),
(str(Kilometer2) + "\t" + calcMiles(kilometers2),
(str(Kilometer3 + "... | code_fim | hard | {
"lang": "python",
"repo": "cblac105/Miles-convertor-",
"path": "/miles-convertor.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> n_samples, n_features = X.shape
is_sparse = issparse(X)
if is_sparse:
L = slinalg.norm(X, axis=0) ** 2 / n_samples
else:
L = norm(X, axis=0) ** 2 / n_samples
v_ = v.copy()
list_beta = np.asarray(list_beta)
jac_t_v = model._init_g_backward(None)
for k in (np.... | code_fim | hard | {
"lang": "python",
"repo": "mathurinm/sparse-ho",
"path": "/sparse_ho/backward.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mathurinm/sparse-ho path: /sparse_ho/backward.py
import numpy as np
from numpy.linalg import norm
from scipy.sparse import issparse
import scipy.sparse.linalg as slinalg
from sparse_ho.forward import get_beta_jac_iterdiff
class Backward():
"""Algorithm that will compute the (hyper)gradient,... | code_fim | medium | {
"lang": "python",
"repo": "mathurinm/sparse-ho",
"path": "/sparse_ho/backward.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>def get_only_jac_backward(X, alpha, list_beta, v, model, jac_v0=None):
n_samples, n_features = X.shape
is_sparse = issparse(X)
if is_sparse:
L = slinalg.norm(X, axis=0) ** 2 / n_samples
else:
L = norm(X, axis=0) ** 2 / n_samples
v_ = v.copy()
list_beta = np.asarray(... | code_fim | hard | {
"lang": "python",
"repo": "mathurinm/sparse-ho",
"path": "/sparse_ho/backward.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sanskruti01/Social-Book path: /Social Book App/dm.py
import csv
from getpass import getpass
def main():
with open("users.txt","r") as file:
fileReader=csv.reader(file)
user_find(fileReader)
file.close()
<|fim_suffix|> user=input("Username:")
for row in file:
... | code_fim | medium | {
"lang": "python",
"repo": "sanskruti01/Social-Book",
"path": "/Social Book App/dm.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
print("Password does not match")
main()<|fim_prefix|># repo: sanskruti01/Social-Book path: /Social Book App/dm.py
import csv
from getpass import getpass
def main():
with open("users.txt","r") as file:
fileReader=csv.reader(file)
user_find(fileReader)
f... | code_fim | hard | {
"lang": "python",
"repo": "sanskruti01/Social-Book",
"path": "/Social Book App/dm.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self, module_id: ModuleID, hps: AppoLearnerHyperparameters
) -> None:
"""Update the target policy of each module with the current policy.
Do that update via polyak averaging.
Args:
module_id: The module ID, whose target network(s) need to be updated.
... | code_fim | hard | {
"lang": "python",
"repo": "ray-project/ray",
"path": "/rllib/algorithms/appo/appo_learner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ray-project/ray path: /rllib/algorithms/appo/appo_learner.py
import abc
from dataclasses import dataclass
from typing import Any, Mapping
from ray.rllib.algorithms.impala.impala_learner import (
ImpalaLearner,
ImpalaLearnerHyperparameters,
)
from ray.rllib.core.rl_module.marl_module impo... | code_fim | hard | {
"lang": "python",
"repo": "ray-project/ray",
"path": "/rllib/algorithms/appo/appo_learner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: trillionmonster/TensorFlowASR path: /tensorflow_asr/datasets/keras/asr_dataset.py
# Copyright 2020 Huy Le Nguyen (@usimarit)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Licens... | code_fim | hard | {
"lang": "python",
"repo": "trillionmonster/TensorFlowASR",
"path": "/tensorflow_asr/datasets/keras/asr_dataset.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> features, input_length, label, label_length, \
prediction, prediction_length = tf.numpy_function(
self.preprocess,
inp=[example["audio"], example["transcript"]],
Tout=[tf.float32, tf.int32, tf.int32, tf.int32, tf.int32, tf.int32]
... | code_fim | hard | {
"lang": "python",
"repo": "trillionmonster/TensorFlowASR",
"path": "/tensorflow_asr/datasets/keras/asr_dataset.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> for D in D_list:
# First convert each reference so it points to the right Device
converted_references = []
for e in D.references:
ref_device = cell_to_device[e.ref_cell]
if isinstance(e, gdspy.CellReference):
d... | code_fim | hard | {
"lang": "python",
"repo": "aisichenko/gdsfactory",
"path": "/gdsfactory/read/import_gds.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
D_list = []
cell_to_device = {}
for c in gdsii_lib.cells.values():
D = Component(name=c.name)
D.paths = c.paths
D.polygons = c.polygons
D.references = c.references
D.name = c.name
for label in c.label... | code_fim | hard | {
"lang": "python",
"repo": "aisichenko/gdsfactory",
"path": "/gdsfactory/read/import_gds.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aisichenko/gdsfactory path: /gdsfactory/read/import_gds.py
from functools import lru_cache
from pathlib import Path
from typing import Callable, Optional, Union, cast
import gdspy
import numpy as np
from omegaconf import OmegaConf
from phidl.device_layout import CellArray, DeviceReference
from ... | code_fim | hard | {
"lang": "python",
"repo": "aisichenko/gdsfactory",
"path": "/gdsfactory/read/import_gds.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>timeseries_preparator = TimeseriesPreparator(dku_config)
input_df = input_dataset.get_dataframe(infer_with_pandas=False)
df_prepared = timeseries_preparator.prepare_timeseries_dataframe(input_df)
input_validator.check(df_prepared)
start = perf_counter()
logger.info("Decomposing time series...")
transform... | code_fim | hard | {
"lang": "python",
"repo": "dataiku/dss-plugin-timeseries-preparation",
"path": "/custom-recipes/timeseries-preparation-decomposition/recipe.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dataiku/dss-plugin-timeseries-preparation path: /custom-recipes/timeseries-preparation-decomposition/recipe.py
import sys
from dku_config.utils import PluginCodeEnvError
if sys.version_info.major == 2:
raise PluginCodeEnvError("This custom recipe requires a Python 3 code env. You are using ... | code_fim | hard | {
"lang": "python",
"repo": "dataiku/dss-plugin-timeseries-preparation",
"path": "/custom-recipes/timeseries-preparation-decomposition/recipe.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>from dataiku.customrecipe import get_recipe_config
from io_utils import get_input_output, set_column_description
from recipe_config_loading import get_decomposition_params
from safe_logger import SafeLogger
from timeseries_preparation.preparation import TimeseriesPreparator
logger = SafeLogger("Timeseri... | code_fim | medium | {
"lang": "python",
"repo": "dataiku/dss-plugin-timeseries-preparation",
"path": "/custom-recipes/timeseries-preparation-decomposition/recipe.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frey1186/Dsystem path: /blog/migrations/0008_auto_20170303_1200.py
# -*- coding: utf-8 -*-
# Generated by Django 1.9.5 on 2017-03-03 12:00
from __future__ import unicode_literals
from django.db import migrations, models
<|fim_suffix|> dependencies = [
('blog', '0007_auto_20170226_080... | code_fim | medium | {
"lang": "python",
"repo": "frey1186/Dsystem",
"path": "/blog/migrations/0008_auto_20170303_1200.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('blog', '0007_auto_20170226_0802'),
]
operations = [
migrations.AddField(
model_name='comments',
name='remote_host',
field=models.CharField(blank=True, max_length=16, null=True, verbose_name='客户端地址'),
),
mig... | code_fim | medium | {
"lang": "python",
"repo": "frey1186/Dsystem",
"path": "/blog/migrations/0008_auto_20170303_1200.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: carachancla/tfg path: /xpander_generation/python/jellyfishGen.py
import matlab.engine
import os
import sys
if len(sys.argv)!=3:
print("Usage: jellyFishGen (int)numV (int)degree")
exit(0)
<|fim_suffix|># add ToRs Links
path = os.path.dirname(os.path.abspath(__file__))
eng = matlab.engi... | code_fim | hard | {
"lang": "python",
"repo": "carachancla/tfg",
"path": "/xpander_generation/python/jellyfishGen.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># add ToRs Links
path = os.path.dirname(os.path.abspath(__file__))
eng = matlab.engine.start_matlab()
eng.addpath(path + '/../lib')
eng.addpath(path + '/../expansion_algs')
eng.addpath(path + '/../graph_generation')
tf = eng.jellyfish(numV, degree)
# add servers?
topoFile.write("# Links \n")
for x in r... | code_fim | hard | {
"lang": "python",
"repo": "carachancla/tfg",
"path": "/xpander_generation/python/jellyfishGen.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DrewDennison/dlint path: /dlint/linters/bad_hashlib_use.py
#!/usr/bin/env python
from __future__ import (
absolute_import,
division,
print_function,
unicode_literals,
)
from .helpers import bad_module_attribute_use
class BadHashlibUseLinter(bad_module_attribute_use.BadModuleAt... | code_fim | medium | {
"lang": "python",
"repo": "DrewDennison/dlint",
"path": "/dlint/linters/bad_hashlib_use.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """This linter looks for unsafe use of the Python "hashlib" module. Use of
md5|sha1 is known to have hash collision weaknesses.
"""
off_by_default = False
_code = 'DUO130'
_error_tmpl = 'DUO130 insecure use of "hashlib" module'
@property
def illegal_module_attributes(self... | code_fim | medium | {
"lang": "python",
"repo": "DrewDennison/dlint",
"path": "/dlint/linters/bad_hashlib_use.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> eprint, getc, getf, geti, gets
try:
from .standard import getlong
except Exception:
pass
finally:
sys.path = path<|fim_prefix|># repo: vivekgupta1mg/miniprojectapp path: /env/lib/python3.8/site-packages/standard/__init__.py
import os
import sys
try:
path = sys.path[:]
... | code_fim | medium | {
"lang": "python",
"repo": "vivekgupta1mg/miniprojectapp",
"path": "/env/lib/python3.8/site-packages/standard/__init__.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vivekgupta1mg/miniprojectapp path: /env/lib/python3.8/site-packages/standard/__init__.py
import os
import sys
try:
path = sys.path[:]
sys.path = [p for<|fim_suffix|>getlong
except Exception:
pass
finally:
sys.path = path<|fim_middle|> p in sys.path if p not in ("", os.ge... | code_fim | medium | {
"lang": "python",
"repo": "vivekgupta1mg/miniprojectapp",
"path": "/env/lib/python3.8/site-packages/standard/__init__.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nkbyrne/pyplus path: /class5/ex1.py
#!/usr/bin/env python
from jinja2 import Template
template = """router bgp {{ local_as }}
neighbor {{ peer1_ip }} remote-as {{ peer1_ip_as }}
update-source loopback99
ebgp-multihop 2
address-family ipv4 unicast
neighbor {{ peer2_ip }} remote-a... | code_fim | medium | {
"lang": "python",
"repo": "nkbyrne/pyplus",
"path": "/class5/ex1.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>j2_template = Template(template)
output = j2_template.render(**my_vars)
print(output)<|fim_prefix|># repo: nkbyrne/pyplus path: /class5/ex1.py
#!/usr/bin/env python
from jinja2 import Template
template = """router bgp {{ local_as }}
neighbor {{ peer1_ip }} remote-as {{ peer1_ip_as }}
update-sourc... | code_fim | medium | {
"lang": "python",
"repo": "nkbyrne/pyplus",
"path": "/class5/ex1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
("standardpages", "0010_image_block"),
("standardpages", "0010_button_block"),
]
operations = []<|fim_prefix|># repo: nimasmi/buckinghamshire-council path: /bc/standardpages/migrations/0011_merge_20200331_1633.py
# Generated by Django 2.2.10 on 2020-03-31 15... | code_fim | easy | {
"lang": "python",
"repo": "nimasmi/buckinghamshire-council",
"path": "/bc/standardpages/migrations/0011_merge_20200331_1633.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
("standardpages", "0010_image_block"),
("standardpages", "0010_button_block"),
]
operations = []<|fim_prefix|># repo: nimasmi/buckinghamshire-council path: /bc/standardpages/migrations/0011_merge_20200331_1633.py
# Gen... | code_fim | easy | {
"lang": "python",
"repo": "nimasmi/buckinghamshire-council",
"path": "/bc/standardpages/migrations/0011_merge_20200331_1633.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nimasmi/buckinghamshire-council path: /bc/standardpages/migrations/0011_merge_20200331_1633.py
# Generated by Django 2.2.10 on 2020-03-31 15:33
<|fim_suffix|>
class Migration(migrations.Migration):
dependencies = [
("standardpages", "0010_image_block"),
("standardpages", "00... | code_fim | easy | {
"lang": "python",
"repo": "nimasmi/buckinghamshire-council",
"path": "/bc/standardpages/migrations/0011_merge_20200331_1633.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: benjaminxscott/goldlist path: /db_seed.py
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from db_setup import Base, Listing, Location
engine = create_engine('postgres://catalog:supersecret@localhost/listings')
Base.metadata.bind = engine
DBSession = sessionmaker(b... | code_fim | medium | {
"lang": "python",
"repo": "benjaminxscott/goldlist",
"path": "/db_seed.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>listings.append( Listing (location = store, name = "Gold Glasses", description = "worn by the man himself", price = 92) )
listings.append( Listing (location = pawn, name = 'Lock of Hair', price = 18) )
listings.append( Listing (location = pawn, name = "Samuel L Jackson's arm", description = "An arm foun... | code_fim | medium | {
"lang": "python",
"repo": "benjaminxscott/goldlist",
"path": "/db_seed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># -----
listings = []
listings.append( Listing (location = store, name = "Gold Glasses", description = "worn by the man himself", price = 92) )
listings.append( Listing (location = pawn, name = 'Lock of Hair', price = 18) )
listings.append( Listing (location = pawn, name = "Samuel L Jackson's arm", des... | code_fim | medium | {
"lang": "python",
"repo": "benjaminxscott/goldlist",
"path": "/db_seed.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name='users',
name='token',
field=models.CharField(default=b'00000000', max_length=50, verbose_name=b'oauth_token'),
),
migrations.AddField(
model_name='users',
name='token_sec... | code_fim | hard | {
"lang": "python",
"repo": "claudiaw111/cs411project",
"path": "/levelup/app/migrations/0002_auto_20151125_1426.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: claudiaw111/cs411project path: /levelup/app/migrations/0002_auto_20151125_1426.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
<|fim_suffix|> operations = [
migrations.AddField(
... | code_fim | hard | {
"lang": "python",
"repo": "claudiaw111/cs411project",
"path": "/levelup/app/migrations/0002_auto_20151125_1426.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>if __name__ == '__main__':
main()<|fim_prefix|># repo: ClockworkNet/svyn path: /svyn_runner.py
#!/usr/bin/env python
"""Convenience wrapper for running svyn directly from source tree."""
<|fim_middle|>from svyn.svyn import main
| code_fim | easy | {
"lang": "python",
"repo": "ClockworkNet/svyn",
"path": "/svyn_runner.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ClockworkNet/svyn path: /svyn_runner.py
#!/usr/bin/env python
"""Convenience wrapper for running svyn directly from source tree."""
<|fim_suffix|>
if __name__ == '__main__':
main()<|fim_middle|>from svyn.svyn import main
| code_fim | easy | {
"lang": "python",
"repo": "ClockworkNet/svyn",
"path": "/svyn_runner.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aiida-vasp/aiida-vasp path: /aiida_vasp/utils/delegates.py
"""
Delegate types.
---------------
Module containing decorators and classes implementing delegate types.
"""
from functools import update_wrapper
def delegate_method_kwargs(prefix='_init_with_'):
"""
Get a kwargs delegating de... | code_fim | medium | {
"lang": "python",
"repo": "aiida-vasp/aiida-vasp",
"path": "/aiida_vasp/utils/delegates.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def decorator(meth):
"""Decorate a class method to delegate kwargs."""
def wrapper(*args, **kwargs):
for kwarg, value in kwargs.items():
getattr(args[0], prefix + kwarg)(value)
meth(*args, **kwargs)
update_wrapper(wrapper, meth)
... | code_fim | medium | {
"lang": "python",
"repo": "aiida-vasp/aiida-vasp",
"path": "/aiida_vasp/utils/delegates.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> update_wrapper(wrapper, meth)
return wrapper
return decorator<|fim_prefix|># repo: aiida-vasp/aiida-vasp path: /aiida_vasp/utils/delegates.py
"""
Delegate types.
---------------
Module containing decorators and classes implementing delegate types.
"""
from functools import update_wr... | code_fim | hard | {
"lang": "python",
"repo": "aiida-vasp/aiida-vasp",
"path": "/aiida_vasp/utils/delegates.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jay-johnson/redten-python path: /redten/shellprinting.py
GRAY_COLOR = '\x1b[37m'
BLUE_COLOR = '\x1b[36m'
PURPLE_COLOR = '\x1b[35m'
YELLOW_COLOR = '\x1b[33m'
GREEN_COLOR = '\x1b[32m'
FAIL_COLOR = '\x1b[31m'
END_COLOR = '\x1b[0m'
def blue... | code_fim | hard | {
"lang": "python",
"repo": "jay-johnson/redten-python",
"path": "/redten/shellprinting.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def lg(msg, color_num=6):
if color_num == 0:
red_print(msg)
elif color_num == 1:
blue_print(msg)
elif color_num == 2:
yellow_print(msg)
elif color_num == 3:
purple_print(msg)
elif color_num == 4:
gray_print(msg)
elif color_num == 5:
g... | code_fim | hard | {
"lang": "python",
"repo": "jay-johnson/redten-python",
"path": "/redten/shellprinting.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def anmt(msg):
yellow_print(msg)
# end of anmt
def info(msg):
lg(msg)
# end of info
def mark(msg):
lg("", 6)
anmt("------------------")
boom(msg)
anmt("------------------")
lg("", 6)
# end of mark
def lg(msg, color_num=6):
if color_num == 0:
red_print(msg)
... | code_fim | hard | {
"lang": "python",
"repo": "jay-johnson/redten-python",
"path": "/redten/shellprinting.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mrooney/django-supervisor path: /djsupervisor/templatetags/djtags.py
import os
from django import template
register = template.Library()
<|fim_suffix|> templated_path = full_path + '.templated'
open(templated_path, 'w').write(templated)
return templated_path<|fim_middle|>project_dir ... | code_fim | hard | {
"lang": "python",
"repo": "mrooney/django-supervisor",
"path": "/djsupervisor/templatetags/djtags.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> templated_path = full_path + '.templated'
open(templated_path, 'w').write(templated)
return templated_path<|fim_prefix|># repo: mrooney/django-supervisor path: /djsupervisor/templatetags/djtags.py
import os
from django import template
register = template.Library()
project_dir = None
ctx = N... | code_fim | medium | {
"lang": "python",
"repo": "mrooney/django-supervisor",
"path": "/djsupervisor/templatetags/djtags.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@register.filter
def templated(template_path):
full_path = os.path.join(project_dir, template_path)
t = template.Template(open(full_path).read())
templated = t.render(template.Context(ctx)).encode('ascii')
templated_path = full_path + '.templated'
open(templated_path, 'w').write(templ... | code_fim | easy | {
"lang": "python",
"repo": "mrooney/django-supervisor",
"path": "/djsupervisor/templatetags/djtags.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HamidL/AMMM_Project path: /GreedyGRASP/ValidateInputData.py
# Validate instance attributes read from a DAT file.
# It validates the structure of the parameters read from the DAT file.
# It does not validate that the instance is feasible or not.
# Use Problem.checkInstance() function to validate t... | code_fim | hard | {
"lang": "python",
"repo": "HamidL/AMMM_Project",
"path": "/GreedyGRASP/ValidateInputData.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for value in cap:
if (not isinstance(value, int) or (value < 0)):
raise Exception(
'Invalid parameter value(%s) in cap. Should be an integer greater or equal than zero.' % str(value))
# Validate eurosMin
eurosMin = data.eurosMin
... | code_fim | hard | {
"lang": "python",
"repo": "HamidL/AMMM_Project",
"path": "/GreedyGRASP/ValidateInputData.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: justanr/uchan path: /uchan/lib/service/board_service.py
import string
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import lazyload
from sqlalchemy.orm.exc import NoResultFound
from uchan import g
from uchan.lib import ArgumentError
from uchan.lib.configs import BoardConfig
from ... | code_fim | hard | {
"lang": "python",
"repo": "justanr/uchan",
"path": "/uchan/lib/service/board_service.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def add_board(self, board):
if not self.check_board_name_validity(board.name):
raise ArgumentError('Invalid board name')
db = get_db()
board_config = BoardConfig()
board.config_id = g.config_service.save_config(board_config, None).id
db.add(board)... | code_fim | hard | {
"lang": "python",
"repo": "justanr/uchan",
"path": "/uchan/lib/service/board_service.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LBL-EESA/TECA path: /doc/source/stats_callbacks.py
from teca import *
import numpy as np
import sys
def get_request_callback(rank, var_names):
def request(port, md_in, req_in):
sys.stderr.write('descriptive_stats::request MPI %d\n'%(rank))
req = teca_metadata(req_in)
... | code_fim | medium | {
"lang": "python",
"repo": "LBL-EESA/TECA",
"path": "/doc/source/stats_callbacks.py",
"mode": "psm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_suffix|> table = teca_table.New()
table.declare_columns(['step','time'], ['ul','d'])
table << mesh.get_time_step() << mesh.get_time()
for var_name in var_names:
table.declare_columns(['min '+var_name, 'avg '+var_name, \
'max '+var_name, 'std '+var_name,... | code_fim | hard | {
"lang": "python",
"repo": "LBL-EESA/TECA",
"path": "/doc/source/stats_callbacks.py",
"mode": "spm",
"license": "BSD-3-Clause-LBNL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EC-Earth/ece2cmor3 path: /test/cmor_source_test.py
import logging
import unittest
from testfixtures import LogCapture
from ece2cmor3.cmor_source import ifs_source, netcdf_source, grib_code
logging.basicConfig(level=logging.DEBUG)
class cmor_source_tests(unittest.TestCase):
@staticmethod
... | code_fim | hard | {
"lang": "python",
"repo": "EC-Earth/ece2cmor3",
"path": "/test/cmor_source_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> src = ifs_source.read("88", "(var144==0)*sqrt(sq(var131)+sq(var132))", mask_expr="var172>0.5")
assert src.get_grib_code() == grib_code(88, 128)
assert set(src.get_root_codes()) == {grib_code(144, 128), grib_code(131, 128), grib_code(132, 128),
... | code_fim | hard | {
"lang": "python",
"repo": "EC-Earth/ece2cmor3",
"path": "/test/cmor_source_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BigNianNGS/AI path: /python_base/write_file.py
filename = 'test_write.txt'
# a 追加 w 重写
with open(filename,'a') as file_o<|fim_suffix|>ht\n')
file_object.write('dierhang\n')<|fim_middle|>bject:
file_object.write('you are rig | code_fim | easy | {
"lang": "python",
"repo": "BigNianNGS/AI",
"path": "/python_base/write_file.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>bject:
file_object.write('you are right\n')
file_object.write('dierhang\n')<|fim_prefix|># repo: BigNianNGS/AI path: /python_base/write_file.py
filename = 'test_write.txt'
# a 追加 <|fim_middle|>w 重写
with open(filename,'a') as file_o | code_fim | easy | {
"lang": "python",
"repo": "BigNianNGS/AI",
"path": "/python_base/write_file.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ht\n')
file_object.write('dierhang\n')<|fim_prefix|># repo: BigNianNGS/AI path: /python_base/write_file.py
filename = 'test_write.txt'
# a 追加 w 重写
with open(filename,'a') as file_o<|fim_middle|>bject:
file_object.write('you are rig | code_fim | easy | {
"lang": "python",
"repo": "BigNianNGS/AI",
"path": "/python_base/write_file.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Raekon/pythonfiles path: /on-demand.py
from PIL import Image
import threading
import ftplib
import time
import os
import datetime
import guizero
width_text=""
def update_size(width):
picture_width=int(float(width))
picture_height=int(picture_width//1.33)
print(int(picture_height))
... | code_fim | medium | {
"lang": "python",
"repo": "Raekon/pythonfiles",
"path": "/on-demand.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def videoUpload():
pass
def videoNoUpload():
pass
app=guizero.App(title="Surveillance tools")
menu=guizero.MenuBar(app,toplevel=["Photo", "Video"],options=[[["With upload",photoUpload],["Without upload",photoNoUpload]],[["with upload",videoUpload],["Without upload",videoNoUpload]]])
picsize=gui... | code_fim | hard | {
"lang": "python",
"repo": "Raekon/pythonfiles",
"path": "/on-demand.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Seraphid/padchest path: /read_data.py
# Load the Pandas libraries with alias 'pd'
import math
import pandas as pd
import ast
import matplotlib.pyplot as plt
LABELS_COL=31 #Column number of the column with labels
# Read data from file 'filename.csv'
# (in the same directory that your python pr... | code_fim | medium | {
"lang": "python",
"repo": "Seraphid/padchest",
"path": "/read_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>plt.plot(range(1,len(freqs)+1), freqs)
plt.show()
plt.plot(range(10,len(freqs)+1), freqs[9:])
plt.show()
plt.plot(range(100,len(freqs)+1), freqs[99:])
plt.show()<|fim_prefix|># repo: Seraphid/padchest path: /read_data.py
# Load the Pandas libraries with alias 'pd'
import math
import pandas as pd
impo... | code_fim | hard | {
"lang": "python",
"repo": "Seraphid/padchest",
"path": "/read_data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kartikeyangupta/Python-photoshop path: /FaceDetection/face_detection_camera.py
import cv2
cascade_path = "./haarcascade_frontalface_alt.xml"
color = (255, 255, 255) # color of rectangle for face detection
cam = cv2.VideoCapture(0)
count=0
<|fim_suffix|> count=0
cv2.imshow('face d... | code_fim | hard | {
"lang": "python",
"repo": "kartikeyangupta/Python-photoshop",
"path": "/FaceDetection/face_detection_camera.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if len(facerect) > 0:
for rect in facerect:
cv2.rectangle(image, tuple(rect[0:2]),tuple(rect[0:2]+rect[2:4]), color, thickness=2)
count=0
cv2.imshow('face detector', image)
cam.release()
cv2.destroyAllWindows()<|fim_prefix|># repo: kartikeyangupta/Pyth... | code_fim | hard | {
"lang": "python",
"repo": "kartikeyangupta/Python-photoshop",
"path": "/FaceDetection/face_detection_camera.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kamronald/pymatgen path: /tests/entries/test_exp_entries.py
from __future__ import annotations
import json
import unittest
from monty.json import MontyDecoder
from pytest import approx
<|fim_suffix|> assert self.entry.energy == approx(-825.5)
def test_as_from_dict(self):
d ... | code_fim | hard | {
"lang": "python",
"repo": "kamronald/pymatgen",
"path": "/tests/entries/test_exp_entries.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_energy(self):
assert self.entry.energy == approx(-825.5)
def test_as_from_dict(self):
d = self.entry.as_dict()
e = ExpEntry.from_dict(d)
assert e.energy == approx(-825.5)
def test_str(self):
assert str(self.entry) is not None<|fim_prefix|># re... | code_fim | hard | {
"lang": "python",
"repo": "kamronald/pymatgen",
"path": "/tests/entries/test_exp_entries.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not (self.expr_list or self.expr_tensor):
self.expr_list = [self[i] for i in range(len(self))]
return super().__iter__()
def __getitem__(self, key):
if self.expr_list or self.expr_tensor:
return super().__getitem__(key)
else:
return torch.tensor(
np.array([se... | code_fim | hard | {
"lang": "python",
"repo": "LHWsleeve/xnmt",
"path": "/xnmt/expression_seqs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>class BaseReversedExpressionSequence(BaseExpressionSequence):
def __init__(self, base_expr_seq):
self.base_expr_seq = base_expr_seq
self.expr_tensor = None
self.expr_list = None
self.expr_transposed_tensor = None
if base_expr_seq.mask is None:
self.mask = None
else:
s... | code_fim | hard | {
"lang": "python",
"repo": "LHWsleeve/xnmt",
"path": "/xnmt/expression_seqs.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LHWsleeve/xnmt path: /xnmt/expression_seqs.py
[tt.Tensor]] = None,
expr_tensor: Optional[tt.Tensor] = None,
expr_transposed_tensor: Optional[tt.Tensor] = None,
mask: Optional['batchers.Mask'] = None,
tensor_type = None) -> None:
"""C... | code_fim | hard | {
"lang": "python",
"repo": "LHWsleeve/xnmt",
"path": "/xnmt/expression_seqs.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DerWeh/gftools path: /gftool/statistics.py
"""Functionality related or derived from the Fermi and Bose statistics.
Per default, the functions refer to Fermi statistics,
a tailing '_b' indicates Bose statistics instead.
"""
from warnings import catch_warnings, filterwarnings
import numpy as np
... | code_fim | hard | {
"lang": "python",
"repo": "DerWeh/gftools",
"path": "/gftool/statistics.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> References
----------
.. [ozaki2007] Ozaki, Taisuke. Continued Fraction Representation of the
Fermi-Dirac Function for Large-Scale Electronic Structure Calculations.
Physical Review B 75, no. 3 (January 23, 2007): 035123.
https://doi.org/10.1103/PhysRevB.75.035123.
..... | code_fim | hard | {
"lang": "python",
"repo": "DerWeh/gftools",
"path": "/gftool/statistics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> See Also
--------
fermi_fct_inv : The inverse of the Fermi function for real arguments.
Examples
--------
>>> eps = np.linspace(-15, 15, num=501)
>>> fermi = gt.fermi_fct(eps, beta=1.0)
>>> import matplotlib.pyplot as plt
>>> _ = plt.plot(eps, fermi)
>>> _ = plt.x... | code_fim | hard | {
"lang": "python",
"repo": "DerWeh/gftools",
"path": "/gftool/statistics.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Aadit-Bhojgi/Automated-Attendance-System path: /RowMarking.py
import cv2 as cv
class RowMarking:
def __init__(self, image, path):
self.path = path
self.image = image
<|fim_suffix|> img = cv.imread(self.image)
gray = cv.cvtColor(img, 6)
thresh = cv.thr... | code_fim | hard | {
"lang": "python",
"repo": "Aadit-Bhojgi/Automated-Attendance-System",
"path": "/RowMarking.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> img = cv.imread(self.image)
gray = cv.cvtColor(img, 6)
thresh = cv.threshold(gray, thresh=200, maxval=255, type=cv.THRESH_BINARY_INV)[1]
# Find contours on the threshold image
contours = cv.findContours(thresh, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)[1]
fo... | code_fim | hard | {
"lang": "python",
"repo": "Aadit-Bhojgi/Automated-Attendance-System",
"path": "/RowMarking.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
content = open('./docs/openapi.yaml', 'r')
return Response(content, mimetype="text/yaml")
except FileNotFoundError:
return Response(status=404)<|fim_prefix|># repo: suricats/surirobot-api-emotions path: /api/server.py
from flask import Flask, redirect, Response
from f... | code_fim | medium | {
"lang": "python",
"repo": "suricats/surirobot-api-emotions",
"path": "/api/server.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: suricats/surirobot-api-emotions path: /api/server.py
from flask import Flask, redirect, Response
from flask_swagger_ui import get_swaggerui_blueprint
from api.microsoft.views import emo_microsoft
<|fim_suffix|>
@app.route('/docs/openapi.yaml')
def swagger_file():
try:
content = open(... | code_fim | hard | {
"lang": "python",
"repo": "suricats/surirobot-api-emotions",
"path": "/api/server.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SupriyoDam/DS-450-python path: /Dynamic Programming/Cutting a Rod.py
class BottomUp:
def rod_cutting(self, price, n, N):
self.dp = [[0] * (N+1) for x in range(n+1)]
length = [x for x in range(1, n+1)]
return self.rod_cutting_util(price, length, n, N)
<|fim_suffix|>if ... | code_fim | hard | {
"lang": "python",
"repo": "SupriyoDam/DS-450-python",
"path": "/Dynamic Programming/Cutting a Rod.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return self.dp[n][N]
if __name__ == '__main__':
price = [1,5,8,9,10,17,17,20]
N = 8
t = BottomUp()
print(t.rod_cutting(price, len(price), N))<|fim_prefix|># repo: SupriyoDam/DS-450-python path: /Dynamic Programming/Cutting a Rod.py
class BottomUp:
def rod_cutting(self, price... | code_fim | hard | {
"lang": "python",
"repo": "SupriyoDam/DS-450-python",
"path": "/Dynamic Programming/Cutting a Rod.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> serialized = super().serialize()
serialized['frame_deltas'] = [(stamp, pose.serialize()) for stamp, pose in self.frame_deltas.items()]
serialized['ground_truth_trajectory'] = [(stamp, pose.serialize()) for stamp, pose
in self.ground_... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/trials/visual_odometry/visual_odometry_result.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_computed_camera_poses(self):
"""
Get the computed poses, as a map from timestamp to absolute pose
This assumes that the first frame is the origin, and builds
the trajectory from there, assuming
:return:
"""
pairs = sorted((timestamp, pose... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/trials/visual_odometry/visual_odometry_result.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jskinn/robot-vision-experiment-framework path: /trials/visual_odometry/visual_odometry_result.py
# Copyright (c) 2017, John Skinner
import core.trial_result
import util.transform as tf
class VisualOdometryResult(core.trial_result.TrialResult):
"""
The results of running visual odometry ... | code_fim | hard | {
"lang": "python",
"repo": "jskinn/robot-vision-experiment-framework",
"path": "/trials/visual_odometry/visual_odometry_result.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_reports(self) -> typing.Iterator[dict]:
response = API_AnalyticsReporting(self.config, self.auth).reports().batchGet(body=self.body).execute()
while response:
next_body = {
"reportRequests":[],
"useResourceQuotas":self.body["useResourceQuotas"]
}
for i... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/starthinker/util/ga.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: google/starthinker path: /starthinker/util/ga.py
###########################################################################
#
# Copyright 2021 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# Y... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/starthinker/util/ga.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def get_dates(self) -> list:
report_dates = []
for report in self.body['reportRequests']:
dates = []
for date_range in report['dateRanges']:
date_start = self.get_date(date_range['startDate'])
date_end = self.get_date(date_range['endDate'])
while date_start ... | code_fim | hard | {
"lang": "python",
"repo": "google/starthinker",
"path": "/starthinker/util/ga.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> df = pd.DataFrame({"id": data[:, 0], "text": data[:, 1]})
inOp1 = dataframeToOperator(df, schemaStr='id long, text string', op_type='batch')
op = RegexTokenizer().setSelectedCol("text").setGaps(False).setToLowerCase(True).setOutputCol(
"token").setPattern("\\w+")
... | code_fim | hard | {
"lang": "python",
"repo": "vacaly/Alink",
"path": "/python/src/main/python/pyalink/alink/tests/examples/pipeline/test_regex_tokenizer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vacaly/Alink path: /python/src/main/python/pyalink/alink/tests/examples/pipeline/test_regex_tokenizer.py
import unittest
from pyalink.alink import *
class TestPinjiu(unittest.TestCase):
def test_regex_tokenizer(self):
<|fim_suffix|> df = pd.DataFrame({"id": data[:, 0], "text": data... | code_fim | hard | {
"lang": "python",
"repo": "vacaly/Alink",
"path": "/python/src/main/python/pyalink/alink/tests/examples/pipeline/test_regex_tokenizer.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> import numpy as np
import pandas as pd
data = np.array([
[0, 'That is an English Book!'],
[1, 'Do you like math?'],
[2, 'Have a good day!']
])
df = pd.DataFrame({"id": data[:, 0], "text": data[:, 1]})
inOp1 = dataframeTo... | code_fim | medium | {
"lang": "python",
"repo": "vacaly/Alink",
"path": "/python/src/main/python/pyalink/alink/tests/examples/pipeline/test_regex_tokenizer.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: logicalclocks/hops-util-py path: /hops/experiment_impl/parallel/random_search.py
"""
Random Search implementation
"""
from hops.experiment_impl.util import experiment_utils
from hops import devices, tensorboard, hdfs
from hops.experiment import Direction
import threading
import six
import time
... | code_fim | hard | {
"lang": "python",
"repo": "logicalclocks/hops-util-py",
"path": "/hops/experiment_impl/parallel/random_search.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> tb_hdfs_path = ''
hdfs_exec_logdir = ''
t = threading.Thread(target=devices._print_periodic_gpu_utilization)
if devices.get_num_gpus() > 0:
t.start()
try:
#Arguments
if args_dict:
param_string, params, args = exp... | code_fim | hard | {
"lang": "python",
"repo": "logicalclocks/hops-util-py",
"path": "/hops/experiment_impl/parallel/random_search.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> hp_names = random_dict.keys()
concatenated_hp_combs_arr = []
for index in range(samples):
separated_hp_comb = ""
for hp in hp_names:
separated_hp_comb = separated_hp_comb + str(random_dict[hp][index]) + "&"
concatenated_hp_combs_arr.append(separated_hp_comb)... | code_fim | hard | {
"lang": "python",
"repo": "logicalclocks/hops-util-py",
"path": "/hops/experiment_impl/parallel/random_search.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert torch.all(
torch.isclose(
predictions,
torch.tensor(
[[-15.5485, -22.0652], [-21.3081, -18.0292]],
),
atol=1e-01,
)
)
@staticmethod
def test_prototypical_networks_rai... | code_fim | hard | {
"lang": "python",
"repo": "sicara/easy-few-shot-learning",
"path": "/easyfsl/tests/methods/prototypical_networks_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> query_images = torch.randn((4, 3, 224, 224))
model(query_images)
@staticmethod
@pytest.mark.parametrize(
(
"support_set_path",
"expected_prototypes",
),
[
(
"easyfsl/tests/datasets/resources/unbalanced_sup... | code_fim | hard | {
"lang": "python",
"repo": "sicara/easy-few-shot-learning",
"path": "/easyfsl/tests/methods/prototypical_networks_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sicara/easy-few-shot-learning path: /easyfsl/tests/methods/prototypical_networks_test.py
import pytest
import torch
from torch import nn
from easyfsl.datasets import SupportSetFolder
from easyfsl.methods import PrototypicalNetworks
class TestPrototypicalNetworksPipeline:
@staticmethod
... | code_fim | hard | {
"lang": "python",
"repo": "sicara/easy-few-shot-learning",
"path": "/easyfsl/tests/methods/prototypical_networks_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: astrofrog/glue path: /glue/core/data_exporters/qt/dialog.py
from __future__ import absolute_import, division, print_function
from qtpy import compat
from glue import config
<|fim_suffix|> exporters = {}
for e in config.data_exporter:
if e.extension == '':
fltr = "{0} ... | code_fim | medium | {
"lang": "python",
"repo": "astrofrog/glue",
"path": "/glue/core/data_exporters/qt/dialog.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> filename = str(filename)
if not filename:
return
exporters[fltr](data, filename)<|fim_prefix|># repo: astrofrog/glue path: /glue/core/data_exporters/qt/dialog.py
from __future__ import absolute_import, division, print_function
from qtpy import compat
from glue import config
def ex... | code_fim | hard | {
"lang": "python",
"repo": "astrofrog/glue",
"path": "/glue/core/data_exporters/qt/dialog.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> filters = ';;'.join(sorted(exporters))
filename, fltr = compat.getsavefilename(caption="Choose an output filename",
filters=filters)
filename = str(filename)
if not filename:
return
exporters[fltr](data, filename)<|fim_prefix|># re... | code_fim | hard | {
"lang": "python",
"repo": "astrofrog/glue",
"path": "/glue/core/data_exporters/qt/dialog.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: opencobra/optlang path: /src/optlang/tests/test_inspyred_interface.py
import unittest
try:
import inspyred
from inspyred import benchmarks
from optlang.inspyred_interface import Model, Objective, Variable
def make_individual(evaluator):
def _(candidate):
r... | code_fim | hard | {
"lang": "python",
"repo": "opencobra/optlang",
"path": "/src/optlang/tests/test_inspyred_interface.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def setUp(self):
self.model = Model(algorithm='PSO')
self.model.configuration.terminator = inspyred.ec.terminators.generation_termination
x = Variable('x', lb=0, ub=2)
y = Variable('y', lb=0, ub=2)
rosenbrock_obj = Objective((1 - x) ** 2... | code_fim | hard | {
"lang": "python",
"repo": "opencobra/optlang",
"path": "/src/optlang/tests/test_inspyred_interface.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> best = max(final_pop)
self.assertAlmostEqual(best.fitness, 0)
def test_pso(self):
self.model.algorithm = 'PSO'
self.model.configuration.max_generations = 100
final_pop = self.model.optimize()
best = max(final_pop)
... | code_fim | hard | {
"lang": "python",
"repo": "opencobra/optlang",
"path": "/src/optlang/tests/test_inspyred_interface.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cadia-lvl/LOBE path: /migrations/versions/9af187822adc_.py
"""empty message
Revision ID: 9af187822adc
Revises: 75287632e523
Create Date: 2020-07-07 18:10:14.818730
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '9af187822adc'
down_revisi... | code_fim | hard | {
"lang": "python",
"repo": "cadia-lvl/LOBE",
"path": "/migrations/versions/9af187822adc_.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # ### commands auto generated by Alembic - please adjust! ###
op.drop_table('progression_icon')
# ### end Alembic commands ###<|fim_prefix|># repo: cadia-lvl/LOBE path: /migrations/versions/9af187822adc_.py
"""empty message
Revision ID: 9af187822adc
Revises: 75287632e523
Create Date: 2020-07... | code_fim | hard | {
"lang": "python",
"repo": "cadia-lvl/LOBE",
"path": "/migrations/versions/9af187822adc_.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>en(h))
print(' '.join(str(e[1]) for e in sorted(h.values())))<|fim_prefix|># repo: cielavenir/procon path: /hackerrank/word-order.py
#!/usr/bin/python
import sys
if sys.version_info[0]>=3: raw_input=input
h={}
for i in range(int(raw_input())):
s=raw_inp<|fim_middle|>ut().rstrip()
if s not in h: h[s]=[i... | code_fim | medium | {
"lang": "python",
"repo": "cielavenir/procon",
"path": "/hackerrank/word-order.py",
"mode": "spm",
"license": "0BSD",
"source": "the-stack-v2"
} |
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