uid stringlengths 24 24 | split stringclasses 1
value | category stringclasses 2
values | content stringlengths 5 482k | signature stringlengths 1 14k | suffix stringlengths 1 482k | prefix stringlengths 9 14k | prefix_token_count int64 3 5.01k | prefix_token_budget int64 64 256 | element_token_count int64 1 292k | signature_token_count int64 1 5.01k | prefix_context_token_count int64 0 255 | repo stringlengths 7 112 | path stringlengths 4 208 | language stringclasses 1
value | name stringlengths 1 218 | qualname stringlengths 1 218 | start_line int64 1 26.7k | end_line int64 1 26.7k | signature_start_line int64 1 26.7k | signature_end_line int64 1 26.7k | source_hash stringlengths 40 40 | source_dataset stringclasses 1
value | source_split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c7183a932a431416aa5d0df6 | train | class | class FakeDriver(log_driver_base.DriverBase):
@staticmethod
def create():
return FakeDriver(
name='fake_driver',
vif_types=[],
vnic_types=[],
supported_logging_types=['security_group'],
requires_rpc=True
)
| class FakeDriver(log_driver_base.DriverBase):
@staticmethod
| def create():
return FakeDriver(
name='fake_driver',
vif_types=[],
vnic_types=[],
supported_logging_types=['security_group'],
requires_rpc=True
)
| resources
from neutron.services.logapi.common import sg_callback
from neutron.services.logapi.drivers import base as log_driver_base
from neutron.services.logapi.drivers import manager as driver_mgr
from neutron.tests import base
FAKE_DRIVER = None
class FakeDriver(log_driver_base.DriverBase):
@staticmethod
| 64 | 64 | 54 | 13 | 50 | congnt95/neutron | neutron/tests/unit/services/logapi/common/test_sg_callback.py | Python | FakeDriver | FakeDriver | 30 | 40 | 30 | 32 | 449232f753acc54ea1c1fe619e4d36a2d99c7fa5 | bigcode/the-stack | train |
0cc48661c407ab0595bbb6f3 | train | class | class TestSecurityGroupRuleCallback(base.BaseTestCase):
def setUp(self):
super(TestSecurityGroupRuleCallback, self).setUp()
self.driver_manager = driver_mgr.LoggingServiceDriverManager()
@mock.patch.object(sg_callback.SecurityGroupRuleCallBack, 'handle_event')
def test_handle_event(self, m... | class TestSecurityGroupRuleCallback(base.BaseTestCase):
| def setUp(self):
super(TestSecurityGroupRuleCallback, self).setUp()
self.driver_manager = driver_mgr.LoggingServiceDriverManager()
@mock.patch.object(sg_callback.SecurityGroupRuleCallBack, 'handle_event')
def test_handle_event(self, mock_sg_cb):
fake_register()
self.driver_m... | '],
requires_rpc=True
)
def fake_register():
global FAKE_DRIVER
if not FAKE_DRIVER:
FAKE_DRIVER = FakeDriver.create()
driver_mgr.register(resources.SECURITY_GROUP_RULE,
sg_callback.SecurityGroupRuleCallBack)
class TestSecurityGroupRuleCallback(base.BaseT... | 64 | 64 | 210 | 11 | 53 | congnt95/neutron | neutron/tests/unit/services/logapi/common/test_sg_callback.py | Python | TestSecurityGroupRuleCallback | TestSecurityGroupRuleCallback | 51 | 72 | 51 | 52 | 9a81d52be4fe80290df7de4b8f7b243e66cea47a | bigcode/the-stack | train |
d4f4b62d3518c1e2cffd46d8 | train | function | def fake_register():
global FAKE_DRIVER
if not FAKE_DRIVER:
FAKE_DRIVER = FakeDriver.create()
driver_mgr.register(resources.SECURITY_GROUP_RULE,
sg_callback.SecurityGroupRuleCallBack)
| def fake_register():
| global FAKE_DRIVER
if not FAKE_DRIVER:
FAKE_DRIVER = FakeDriver.create()
driver_mgr.register(resources.SECURITY_GROUP_RULE,
sg_callback.SecurityGroupRuleCallBack)
| FAKE_DRIVER = None
class FakeDriver(log_driver_base.DriverBase):
@staticmethod
def create():
return FakeDriver(
name='fake_driver',
vif_types=[],
vnic_types=[],
supported_logging_types=['security_group'],
requires_rpc=True
)
def fake... | 64 | 64 | 45 | 4 | 60 | congnt95/neutron | neutron/tests/unit/services/logapi/common/test_sg_callback.py | Python | fake_register | fake_register | 43 | 48 | 43 | 43 | b92837861a4a6b7fad7ff59a63c71307ee45ad1a | bigcode/the-stack | train |
672a8b5362b9a1913107606c | train | class | class KoubeiMarketingCampaignItemMerchantactivityModifyRequest(object):
def __init__(self, biz_model=None):
self._biz_model = biz_model
self._biz_content = None
self._version = "1.0"
self._terminal_type = None
self._terminal_info = None
self._prod_code = None
... | class KoubeiMarketingCampaignItemMerchantactivityModifyRequest(object):
| def __init__(self, biz_model=None):
self._biz_model = biz_model
self._biz_content = None
self._version = "1.0"
self._terminal_type = None
self._terminal_info = None
self._prod_code = None
self._notify_url = None
self._return_url = None
self._ud... | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from alipay.aop.api.FileItem import FileItem
from alipay.aop.api.constant.ParamConstants import *
from alipay.aop.api.domain.KoubeiMarketingCampaignItemMerchantactivityModifyModel import KoubeiMarketingCampaignItemMerchantactivityModifyModel
class KoubeiMarket... | 80 | 255 | 851 | 12 | 67 | snowxmas/alipay-sdk-python-all | alipay/aop/api/request/KoubeiMarketingCampaignItemMerchantactivityModifyRequest.py | Python | KoubeiMarketingCampaignItemMerchantactivityModifyRequest | KoubeiMarketingCampaignItemMerchantactivityModifyRequest | 12 | 144 | 12 | 13 | d43177f1dded56ca909b1c7c85dcef1a963934a9 | bigcode/the-stack | train |
e15d9e07ffd3a0de225ef61a | train | class | class ZeroRobotFactory(JSConfigBase):
def __init__(self):
self.__jslocation__ = "j.servers.zrobot"
JSConfigBase.__init__(self, ZeroRobotServer)
| class ZeroRobotFactory(JSConfigBase):
| def __init__(self):
self.__jslocation__ = "j.servers.zrobot"
JSConfigBase.__init__(self, ZeroRobotServer)
| from js9 import j
from .ZeroRobotServer import ZeroRobotServer
JSConfigBase = j.tools.configmanager.base_class_configs
class ZeroRobotFactory(JSConfigBase):
| 36 | 64 | 42 | 8 | 27 | PeterNashaat/0-robot | JumpScale9Zrobot/servers/zerorobot/ZeroRobotFactory.py | Python | ZeroRobotFactory | ZeroRobotFactory | 8 | 12 | 8 | 9 | 4593d273f5427913deffdfae028ae48e6d737d06 | bigcode/the-stack | train |
e64038a76670ab66d4959619 | train | function | def edit_pipeline(full_dataset_path, laz_path, tif_path, output_epsg, bound, polygon_input):
fetch_json = open_json("./pipeline.json")
fetch_json['pipeline'][0]['filename'] = full_dataset_path
fetch_json['pipeline'][0]['bounds'] = bound
fetch_json['pipeline'][1]['polygon'] = polygon_input
fetch_json... | def edit_pipeline(full_dataset_path, laz_path, tif_path, output_epsg, bound, polygon_input):
| fetch_json = open_json("./pipeline.json")
fetch_json['pipeline'][0]['filename'] = full_dataset_path
fetch_json['pipeline'][0]['bounds'] = bound
fetch_json['pipeline'][1]['polygon'] = polygon_input
fetch_json['pipeline'][3]['out_srs'] = f'EPSG:{output_epsg}'
fetch_json['pipeline'][4]['filename'] ... | import json
def open_json(path):
with open(path, 'r')as json_file:
dict_ob = json.load(json_file)
return dict_ob
def edit_pipeline(full_dataset_path, laz_path, tif_path, output_epsg, bound, polygon_input):
| 56 | 64 | 137 | 22 | 33 | Bethelsis/AgriTech-USGS-LIDAR-Challenge | scripts/edit_pipeline.py | Python | edit_pipeline | edit_pipeline | 8 | 18 | 8 | 8 | 642efbc4ae6611ddf2cd8e45a49144b900c01568 | bigcode/the-stack | train |
f6d7ef29acda709b13ded2c1 | train | function | def open_json(path):
with open(path, 'r')as json_file:
dict_ob = json.load(json_file)
return dict_ob
| def open_json(path):
| with open(path, 'r')as json_file:
dict_ob = json.load(json_file)
return dict_ob
| import json
def open_json(path):
| 8 | 64 | 31 | 5 | 2 | Bethelsis/AgriTech-USGS-LIDAR-Challenge | scripts/edit_pipeline.py | Python | open_json | open_json | 3 | 6 | 3 | 3 | a10112c653964921fcf5c5c89cdeb808e98189bb | bigcode/the-stack | train |
906ed902324ba134fcb362af | train | function | def test_dynamic_sidecar_env_vars(monkeypatch: MonkeyPatch) -> None:
for key, value in MOCKED_BASE_REGISTRY_ENV_VARS.items():
monkeypatch.setenv(key, value)
registry_settings = RegistrySettings()
dynamic_sidecar_env_vars = get_dynamic_sidecar_env_vars(registry_settings)
print("dynamic_sidecar_... | def test_dynamic_sidecar_env_vars(monkeypatch: MonkeyPatch) -> None:
| for key, value in MOCKED_BASE_REGISTRY_ENV_VARS.items():
monkeypatch.setenv(key, value)
registry_settings = RegistrySettings()
dynamic_sidecar_env_vars = get_dynamic_sidecar_env_vars(registry_settings)
print("dynamic_sidecar_env_vars:", dynamic_sidecar_env_vars)
assert len(dynamic_sidecar... | _USER": "usr",
"REGISTRY_PW": MOCKED_PASSWORD,
"REGISTRY_SSL": "False",
}
EXPECTED_DYNAMIC_SIDECAR_ENV_VAR_NAMES = {
"REGISTRY_AUTH",
"REGISTRY_PATH",
"REGISTRY_URL",
"REGISTRY_USER",
"REGISTRY_PW",
"REGISTRY_SSL",
}
def test_dynamic_sidecar_env_vars(monkeypatch: MonkeyPatch) -> None:
| 92 | 92 | 307 | 17 | 75 | colinRawlings/osparc-simcore | services/director-v2/tests/unit/test_utils_registry.py | Python | test_dynamic_sidecar_env_vars | test_dynamic_sidecar_env_vars | 26 | 58 | 26 | 26 | d54cad9f6ea15bbff36abe9889a32a97515c3bc5 | bigcode/the-stack | train |
9f346370a32a905b62dacf3f | train | class | class clean_versions(AppCommand):
"""Delete old version directories.
Warning:
This command will result in the destruction of the following files:
1) Table data for previous versions of the app.
"""
async def run(self) -> None:
"""Execute command."""
self.remove_old... | class clean_versions(AppCommand):
| """Delete old version directories.
Warning:
This command will result in the destruction of the following files:
1) Table data for previous versions of the app.
"""
async def run(self) -> None:
"""Execute command."""
self.remove_old_versiondirs()
def remove_old... | """Program ``faust reset`` used to delete local table state."""
from shutil import rmtree
from .base import AppCommand
__all__ = ['clean_versions']
class clean_versions(AppCommand):
| 41 | 64 | 119 | 6 | 35 | spencerpomme/Public-Transit-Status-with-Apache-Kafka | consumers/venv/lib/python3.7/site-packages/faust/cli/clean_versions.py | Python | clean_versions | clean_versions | 8 | 25 | 8 | 8 | cf9c1eb8e8f128942889db4afb0ad149a7229e3e | bigcode/the-stack | train |
891606af602f3c400845a078 | train | class | class read_writeTest(unittest.TestCase):
filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "test_file.nc"
)
broken_bounds = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "broken_bounds.cdl"
)
string_filename = os.path.join(
os.path.dirname(os.... | class read_writeTest(unittest.TestCase):
| filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "test_file.nc"
)
broken_bounds = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "broken_bounds.cdl"
)
string_filename = os.path.join(
os.path.dirname(os.path.abspath(__file__)), "string_char.nc"... | import atexit
import datetime
import faulthandler
import inspect
import os
import shutil
import subprocess
import tempfile
import unittest
import numpy
faulthandler.enable() # to debug seg faults and timeouts
import cf
n_tmpfiles = 8
tmpfiles = [
tempfile.mkstemp("_test_read_write.nc", dir=os.getcwd())[1]
... | 197 | 256 | 7,239 | 8 | 189 | sadielbartholomew/cf-python | cf/test/test_read_write.py | Python | read_writeTest | read_writeTest | 46 | 880 | 46 | 46 | dd9b7bf0883c947cc34c7fc645af07eb94869e59 | bigcode/the-stack | train |
48b0359be12c2be18730f21e | train | function | def _remove_tmpfiles():
"""Try to remove defined temporary files by deleting their paths."""
for f in tmpfiles:
try:
os.remove(f)
except OSError:
pass
| def _remove_tmpfiles():
| """Try to remove defined temporary files by deleting their paths."""
for f in tmpfiles:
try:
os.remove(f)
except OSError:
pass
| ]
for i in range(n_tmpfiles)
]
(
tmpfile,
tmpfileh,
tmpfileh2,
tmpfilec,
tmpfilec2,
tmpfile0,
tmpfile1,
tmpfile2,
) = tmpfiles
def _remove_tmpfiles():
| 64 | 64 | 42 | 6 | 57 | sadielbartholomew/cf-python | cf/test/test_read_write.py | Python | _remove_tmpfiles | _remove_tmpfiles | 34 | 40 | 34 | 34 | 210576a2a02df2443b5751ef1c2d02f113b24e19 | bigcode/the-stack | train |
88d5845dfe7641ca5c8c189d | train | class | class Cert_9_2_19_PendingDatasetGet(thread_cert.TestCase):
SUPPORT_NCP = False
TOPOLOGY = {
COMMISSIONER: {
'name': 'COMMISSIONER',
'mode': 'rdn',
'allowlist': [LEADER]
},
LEADER: {
'name': 'LEADER',
'mode': 'rdn',
... | class Cert_9_2_19_PendingDatasetGet(thread_cert.TestCase):
| SUPPORT_NCP = False
TOPOLOGY = {
COMMISSIONER: {
'name': 'COMMISSIONER',
'mode': 'rdn',
'allowlist': [LEADER]
},
LEADER: {
'name': 'LEADER',
'mode': 'rdn',
'allowlist': [COMMISSIONER]
},
}
def test(... | USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
import unittest
import config
import mesh_cop
import thread_cert
from pktverify.consts import MGMT_PENDING_GET_URI, MGMT_PENDING_SET_URI, NM_CHANNEL_TLV, NM_PAN_ID_TLV, NM_NETWORK_NAME_TLV, NM_NETWORK_MESH_LOCAL_PREFIX_TLV, NM_PSKC_TLV, NM... | 256 | 256 | 2,201 | 17 | 238 | sarah-iot/openthread | tests/scripts/thread-cert/Cert_9_2_19_PendingDatasetGet.py | Python | Cert_9_2_19_PendingDatasetGet | Cert_9_2_19_PendingDatasetGet | 59 | 289 | 59 | 59 | eaf1fd414d21478dde6e31edd5ff9a489b211f51 | bigcode/the-stack | train |
203cdfc09a85c2a956e5ec19 | train | function | def smart_divide(func):
def inner(a, b):
print("I am going to divide", a, "and", b)
if b == 0:
print("Whoops! cannot divide")
return
return func(a, b)
return inner
| def smart_divide(func):
| def inner(a, b):
print("I am going to divide", a, "and", b)
if b == 0:
print("Whoops! cannot divide")
return
return func(a, b)
return inner
| decorator's arg func..!!****")
# print(num + 1)
# my_decorator(test_in)
@my_decorator # this is exactly similar to: my_decorator(test_in)
def test_in():
print("***I m decorator's arg func..!!****")
def smart_divide(func):
| 64 | 64 | 59 | 6 | 58 | PranaliRPatil/Python_OOP_Basics | decorators_test.py | Python | smart_divide | smart_divide | 17 | 25 | 17 | 17 | 4584ce0226f3227d821ba5f5941b10ea282b3488 | bigcode/the-stack | train |
a9011d59fc6f85e06b4af0e4 | train | function | def my_decorator(func):
print("Inside decorator")
func()
print("End decorator\n*******###*********")
| def my_decorator(func):
| print("Inside decorator")
func()
print("End decorator\n*******###*********")
| #https://www.programiz.com/python-programming/decorator
#https://realpython.com/primer-on-python-decorators/
def my_decorator(func):
| 33 | 64 | 26 | 6 | 27 | PranaliRPatil/Python_OOP_Basics | decorators_test.py | Python | my_decorator | my_decorator | 3 | 6 | 3 | 3 | c74833b8703fbbb5a38a20d7bf7b8c544f8b86df | bigcode/the-stack | train |
988999e8887e0129f9aeda8e | train | function | @my_decorator # this is exactly similar to: my_decorator(test_in)
def test_in():
print("***I m decorator's arg func..!!****")
| @my_decorator # this is exactly similar to: my_decorator(test_in)
def test_in():
| print("***I m decorator's arg func..!!****")
| print("End decorator\n*******###*********")
def test_in():
print("***I m decorator's arg func..!!****")
# print(num + 1)
# my_decorator(test_in)
@my_decorator # this is exactly similar to: my_decorator(test_in)
def test_in():
| 64 | 64 | 35 | 22 | 42 | PranaliRPatil/Python_OOP_Basics | decorators_test.py | Python | test_in | test_in | 13 | 15 | 13 | 14 | cf834679d00d7475b32019af94d3d809caa84296 | bigcode/the-stack | train |
bd28bac8f37b1fc1ceceaab5 | train | function | @smart_divide
def divide(a, b):
print(a/b)
| @smart_divide
def divide(a, b):
| print(a/b)
| def inner(a, b):
print("I am going to divide", a, "and", b)
if b == 0:
print("Whoops! cannot divide")
return
return func(a, b)
return inner
@smart_divide
def divide(a, b):
| 64 | 64 | 16 | 11 | 52 | PranaliRPatil/Python_OOP_Basics | decorators_test.py | Python | divide | divide | 27 | 29 | 27 | 28 | 4b06f8312c9a22bfc7446f3a3b3d8b38774022a8 | bigcode/the-stack | train |
85df27105305de8deead856d | train | function | def test_in():
print("***I m decorator's arg func..!!****")
| def test_in():
| print("***I m decorator's arg func..!!****")
| #https://www.programiz.com/python-programming/decorator
#https://realpython.com/primer-on-python-decorators/
def my_decorator(func):
print("Inside decorator")
func()
print("End decorator\n*******###*********")
def test_in():
| 57 | 64 | 17 | 4 | 53 | PranaliRPatil/Python_OOP_Basics | decorators_test.py | Python | test_in | test_in | 8 | 9 | 8 | 8 | ebb7f168ef587e1fbc6d7e49e4ce6a96f53ba193 | bigcode/the-stack | train |
92db5ecf77e50fd36452954c | train | class | class CustomObjectReference(Reference):
"Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectReferenceSchema`."
#: Optional :class:`commercetools.types.CustomObject`
obj: typing.Optional["CustomObject"]
def __init__(
self,
*,
type_id: typing.Optional["R... | class CustomObjectReference(Reference):
| "Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectReferenceSchema`."
#: Optional :class:`commercetools.types.CustomObject`
obj: typing.Optional["CustomObject"]
def __init__(
self,
*,
type_id: typing.Optional["ReferenceTypeId"] = None,
id: typ... | super().__init__()
def __repr__(self) -> str:
return (
"CustomObjectPagedQueryResponse(count=%r, total=%r, offset=%r, results=%r)"
% (self.count, self.total, self.offset, self.results)
)
class CustomObjectReference(Reference):
| 64 | 64 | 173 | 7 | 57 | mbarga/commercetools-python-sdk | src/commercetools/types/_custom_object.py | Python | CustomObjectReference | CustomObjectReference | 128 | 148 | 128 | 128 | 813d14344e928eb8510aacfd40770791f03d33bc | bigcode/the-stack | train |
38de8e39e987e4963b446536 | train | class | class CustomObjectPagedQueryResponse(_BaseType):
"Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectPagedQueryResponseSchema`."
#: :class:`int`
count: typing.Optional[int]
#: Optional :class:`int`
total: typing.Optional[int]
#: :class:`int`
offset: typing.Optional... | class CustomObjectPagedQueryResponse(_BaseType):
| "Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectPagedQueryResponseSchema`."
#: :class:`int`
count: typing.Optional[int]
#: Optional :class:`int`
total: typing.Optional[int]
#: :class:`int`
offset: typing.Optional[int]
#: List of :class:`commercetools.types.... |
self.version = version
super().__init__()
def __repr__(self) -> str:
return "CustomObjectDraft(container=%r, key=%r, value=%r, version=%r)" % (
self.container,
self.key,
self.value,
self.version,
)
class CustomObjectPagedQueryResponse... | 74 | 74 | 247 | 10 | 64 | mbarga/commercetools-python-sdk | src/commercetools/types/_custom_object.py | Python | CustomObjectPagedQueryResponse | CustomObjectPagedQueryResponse | 96 | 125 | 96 | 96 | dc335f00b3a13aa9078cc2e66f33a947cd40615f | bigcode/the-stack | train |
2fd2bc707b5f305238274e8d | train | class | class CustomObject(BaseResource):
"Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectSchema`."
#: :class:`str`
container: typing.Optional[str]
#: :class:`str`
key: typing.Optional[str]
#: :class:`typing.Any`
value: typing.Optional[typing.Any]
def __init__(
... | class CustomObject(BaseResource):
| "Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectSchema`."
#: :class:`str`
container: typing.Optional[str]
#: :class:`str`
key: typing.Optional[str]
#: :class:`typing.Any`
value: typing.Optional[typing.Any]
def __init__(
self,
*,
id:... | # DO NOT EDIT! This file is automatically generated
import datetime
import typing
from commercetools.types._abstract import _BaseType
from commercetools.types._common import BaseResource, Reference, ReferenceTypeId
__all__ = [
"CustomObject",
"CustomObjectDraft",
"CustomObjectPagedQueryResponse",
"Cu... | 83 | 90 | 302 | 6 | 77 | mbarga/commercetools-python-sdk | src/commercetools/types/_custom_object.py | Python | CustomObject | CustomObject | 17 | 59 | 17 | 17 | aed84af0826e5cece6e1ed81243e6ff42dc91c45 | bigcode/the-stack | train |
6237f3f1baa62866a70c392c | train | class | class CustomObjectDraft(_BaseType):
"Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectDraftSchema`."
#: :class:`str`
container: typing.Optional[str]
#: :class:`str`
key: typing.Optional[str]
#: :class:`typing.Any`
value: typing.Optional[typing.Any]
#: Optiona... | class CustomObjectDraft(_BaseType):
| "Corresponding marshmallow schema is :class:`commercetools.schemas.CustomObjectDraftSchema`."
#: :class:`str`
container: typing.Optional[str]
#: :class:`str`
key: typing.Optional[str]
#: :class:`typing.Any`
value: typing.Optional[typing.Any]
#: Optional :class:`int`
version: typing.O... | _at=%r, last_modified_at=%r, container=%r, key=%r, value=%r)"
% (
self.id,
self.version,
self.created_at,
self.last_modified_at,
self.container,
self.key,
self.value,
)
)
class... | 68 | 68 | 228 | 8 | 60 | mbarga/commercetools-python-sdk | src/commercetools/types/_custom_object.py | Python | CustomObjectDraft | CustomObjectDraft | 62 | 93 | 62 | 62 | 5518241639ba5d7934bf67a93a570e2238138aed | bigcode/the-stack | train |
713c277a58726b0028b71be0 | train | class | class MathguideConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'mathguide'
| class MathguideConfig(AppConfig):
| default_auto_field = 'django.db.models.BigAutoField'
name = 'mathguide'
| from django.apps import AppConfig
class MathguideConfig(AppConfig):
| 14 | 64 | 27 | 7 | 6 | LHY-42/matholympiadguide | mathguide/apps.py | Python | MathguideConfig | MathguideConfig | 4 | 6 | 4 | 4 | e570e7403525b68f466cf955d2ecd7b25e128f57 | bigcode/the-stack | train |
abcc56f695aa2c9784e172c4 | train | function | def requires_backends(obj, backends):
if not isinstance(backends, (list, tuple)):
backends = [backends]
name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
if not all(BACKENDS_MAPPING[backend][0]() for backend in backends):
raise ImportError("".join([BACKENDS_MAPPING... | def requires_backends(obj, backends):
| if not isinstance(backends, (list, tuple)):
backends = [backends]
name = obj.__name__ if hasattr(obj, "__name__") else obj.__class__.__name__
if not all(BACKENDS_MAPPING[backend][0]() for backend in backends):
raise ImportError("".join([BACKENDS_MAPPING[backend][1].format(name) for backend ... | ERS_IMPORT_ERROR)),
("torch", (is_torch_available, PYTORCH_IMPORT_ERROR)),
("vision", (is_vision_available, VISION_IMPORT_ERROR)),
("scipy", (is_scipy_available, SCIPY_IMPORT_ERROR)),
]
)
def requires_backends(obj, backends):
| 64 | 64 | 95 | 9 | 55 | MichalPitr/transformers | src/transformers/file_utils.py | Python | requires_backends | requires_backends | 606 | 612 | 606 | 606 | 88d69d1aa3b100daffa968f95914fc5d9933c3ac | bigcode/the-stack | train |
c0dc29117101bd5011b8ce72 | train | function | def is_py3nvml_available():
return importlib.util.find_spec("py3nvml") is not None
| def is_py3nvml_available():
| return importlib.util.find_spec("py3nvml") is not None
| return False
return importlib.util.find_spec("torch_xla.core.xla_model") is not None
def is_datasets_available():
return _datasets_available
def is_psutil_available():
return importlib.util.find_spec("psutil") is not None
def is_py3nvml_available():
| 64 | 64 | 25 | 8 | 55 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_py3nvml_available | is_py3nvml_available | 322 | 323 | 322 | 322 | 733e4e4957712a033378e6e79e3a4753555fd362 | bigcode/the-stack | train |
95553f892e5f558acb030445 | train | function | def is_vision_available():
return importlib.util.find_spec("PIL") is not None
| def is_vision_available():
| return importlib.util.find_spec("PIL") is not None
| is_protobuf_available():
if importlib.util.find_spec("google") is None:
return False
return importlib.util.find_spec("google.protobuf") is not None
def is_tokenizers_available():
return importlib.util.find_spec("tokenizers") is not None
def is_vision_available():
| 64 | 64 | 21 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_vision_available | is_vision_available | 358 | 359 | 358 | 358 | 0a480f980adf3eed65c4fa7d63937c44b12383ec | bigcode/the-stack | train |
354221589fb308c21d68e553 | train | function | def is_pandas_available():
return importlib.util.find_spec("pandas") is not None
| def is_pandas_available():
| return importlib.util.find_spec("pandas") is not None
| ODE_PID" in os.environ:
raise ImportError("vscode")
return importlib.util.find_spec("IPython") is not None
except (AttributeError, ImportError, KeyError):
return False
def is_scatter_available():
return _scatter_available
def is_pandas_available():
| 64 | 64 | 21 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_pandas_available | is_pandas_available | 380 | 381 | 380 | 380 | 9a4b7708f8a9a86d73b803805fbbd3df3624fd85 | bigcode/the-stack | train |
7131ea6b7951f9c68abed206 | train | function | def is_remote_url(url_or_filename):
parsed = urlparse(url_or_filename)
return parsed.scheme in ("http", "https")
| def is_remote_url(url_or_filename):
| parsed = urlparse(url_or_filename)
return parsed.scheme in ("http", "https")
| f"The function {fn} should have an empty 'Return:' or 'Returns:' in its docstring as placeholder, current docstring is:\n{docstrings}"
)
fn.__doc__ = docstrings
return fn
return docstring_decorator
def is_remote_url(url_or_filename):
| 64 | 64 | 28 | 8 | 55 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_remote_url | is_remote_url | 1,162 | 1,164 | 1,162 | 1,162 | f3d38666696ad6c7d2f2f7ee2862f92d0868be91 | bigcode/the-stack | train |
1909346ac296c20976e0627c | train | function | def is_offline_mode():
return _is_offline_mode
| def is_offline_mode():
| return _is_offline_mode
| This is the version of torch required to run torch.fx features.
TORCH_FX_REQUIRED_VERSION = version.parse("1.8")
_is_offline_mode = True if os.environ.get("TRANSFORMERS_OFFLINE", "0").upper() in ENV_VARS_TRUE_VALUES else False
def is_offline_mode():
| 64 | 64 | 14 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_offline_mode | is_offline_mode | 261 | 262 | 261 | 261 | ccae0a114ab4dd2827891bc2eb5fca9d5eac4877 | bigcode/the-stack | train |
4a6cfa1e4d02cef39d51bc09 | train | function | def is_scipy_available():
return importlib.util.find_spec("scipy") is not None
| def is_scipy_available():
| return importlib.util.find_spec("scipy") is not None
| 3nvml_available():
return importlib.util.find_spec("py3nvml") is not None
def is_apex_available():
return importlib.util.find_spec("apex") is not None
def is_faiss_available():
return _faiss_available
def is_scipy_available():
| 64 | 64 | 22 | 7 | 56 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_scipy_available | is_scipy_available | 334 | 335 | 334 | 334 | 1678d3a35d7f95019f92512779ed6f806d996ff7 | bigcode/the-stack | train |
031286ad73bff9f7b09cc568 | train | class | class PaddingStrategy(ExplicitEnum):
"""
Possible values for the ``padding`` argument in :meth:`PreTrainedTokenizerBase.__call__`. Useful for tab-completion
in an IDE.
"""
LONGEST = "longest"
MAX_LENGTH = "max_length"
DO_NOT_PAD = "do_not_pad"
| class PaddingStrategy(ExplicitEnum):
| """
Possible values for the ``padding`` argument in :meth:`PreTrainedTokenizerBase.__call__`. Useful for tab-completion
in an IDE.
"""
LONGEST = "longest"
MAX_LENGTH = "max_length"
DO_NOT_PAD = "do_not_pad"
| for missing values.
"""
@classmethod
def _missing_(cls, value):
raise ValueError(
f"{value} is not a valid {cls.__name__}, please select one of {list(cls._value2member_map_.keys())}"
)
class PaddingStrategy(ExplicitEnum):
| 64 | 64 | 70 | 7 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | PaddingStrategy | PaddingStrategy | 1,841 | 1,849 | 1,841 | 1,841 | 0571de3418fbc68866dfa7038d5f664080d7b80c | bigcode/the-stack | train |
77fdd81937ee922d78bd1fe9 | train | function | def torch_only_method(fn):
def wrapper(*args, **kwargs):
if not _torch_available:
raise ImportError(
"You need to install pytorch to use this method or class, "
"or activate it with environment variables USE_TORCH=1 and USE_TF=0."
)
else:
... | def torch_only_method(fn):
| def wrapper(*args, **kwargs):
if not _torch_available:
raise ImportError(
"You need to install pytorch to use this method or class, "
"or activate it with environment variables USE_TORCH=1 and USE_TF=0."
)
else:
return fn(*args, **k... | ():
return _timm_available
def is_torchaudio_available():
return _torchaudio_available
def is_speech_available():
# For now this depends on torchaudio but the exact dependency might evolve in the future.
return _torchaudio_available
def torch_only_method(fn):
| 64 | 64 | 82 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | torch_only_method | torch_only_method | 443 | 453 | 443 | 443 | 580dab927089513f2cea7476bd29b1c570244d39 | bigcode/the-stack | train |
50905e2d449fbff3c27dce72 | train | class | class TensorType(ExplicitEnum):
"""
Possible values for the ``return_tensors`` argument in :meth:`PreTrainedTokenizerBase.__call__`. Useful for
tab-completion in an IDE.
"""
PYTORCH = "pt"
TENSORFLOW = "tf"
NUMPY = "np"
JAX = "jax"
| class TensorType(ExplicitEnum):
| """
Possible values for the ``return_tensors`` argument in :meth:`PreTrainedTokenizerBase.__call__`. Useful for
tab-completion in an IDE.
"""
PYTORCH = "pt"
TENSORFLOW = "tf"
NUMPY = "np"
JAX = "jax"
| the ``padding`` argument in :meth:`PreTrainedTokenizerBase.__call__`. Useful for tab-completion
in an IDE.
"""
LONGEST = "longest"
MAX_LENGTH = "max_length"
DO_NOT_PAD = "do_not_pad"
class TensorType(ExplicitEnum):
| 64 | 64 | 76 | 7 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | TensorType | TensorType | 1,852 | 1,861 | 1,852 | 1,852 | 440fd0142ee6e97a41834a048921f5792191e8b5 | bigcode/the-stack | train |
ccebc3ba9765725823169245 | train | function | def is_torch_cuda_available():
if is_torch_available():
import torch
return torch.cuda.is_available()
else:
return False
| def is_torch_cuda_available():
| if is_torch_available():
import torch
return torch.cuda.is_available()
else:
return False
| _is_offline_mode = True if os.environ.get("TRANSFORMERS_OFFLINE", "0").upper() in ENV_VARS_TRUE_VALUES else False
def is_offline_mode():
return _is_offline_mode
def is_torch_available():
return _torch_available
def is_torch_cuda_available():
| 64 | 64 | 32 | 7 | 56 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_torch_cuda_available | is_torch_cuda_available | 269 | 275 | 269 | 269 | 8d8d803792bd336bd8570b4b79c7544ac5c4231d | bigcode/the-stack | train |
17b33f290e3402b90f4f8cc0 | train | function | def add_start_docstrings_to_model_forward(*docstr):
def docstring_decorator(fn):
class_name = f":class:`~transformers.{fn.__qualname__.split('.')[0]}`"
intro = f" The {class_name} forward method, overrides the :func:`__call__` special method."
note = r"""
.. note::
Although th... | def add_start_docstrings_to_model_forward(*docstr):
| def docstring_decorator(fn):
class_name = f":class:`~transformers.{fn.__qualname__.split('.')[0]}`"
intro = f" The {class_name} forward method, overrides the :func:`__call__` special method."
note = r"""
.. note::
Although the recipe for forward pass needs to be defined within... | _docstrings(*docstr):
def docstring_decorator(fn):
fn.__doc__ = "".join(docstr) + (fn.__doc__ if fn.__doc__ is not None else "")
return fn
return docstring_decorator
def add_start_docstrings_to_model_forward(*docstr):
| 64 | 64 | 175 | 12 | 51 | MichalPitr/transformers | src/transformers/file_utils.py | Python | add_start_docstrings_to_model_forward | add_start_docstrings_to_model_forward | 623 | 637 | 623 | 623 | 37029ffbb65332e71ad3d6f67df1f56ff56306cd | bigcode/the-stack | train |
130bf754440381a3e00a1778 | train | function | def is_training_run_on_sagemaker():
return "SAGEMAKER_JOB_NAME" in os.environ
| def is_training_run_on_sagemaker():
| return "SAGEMAKER_JOB_NAME" in os.environ
| _mpi_enabled", False):
return False
except json.JSONDecodeError:
return False
# Lastly, check if the `smdistributed` module is present.
return importlib.util.find_spec("smdistributed") is not None
def is_training_run_on_sagemaker():
| 64 | 64 | 22 | 9 | 54 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_training_run_on_sagemaker | is_training_run_on_sagemaker | 422 | 423 | 422 | 422 | 8746f77794007988a9cda868d1ecd680d29ef352 | bigcode/the-stack | train |
3d674ed696f538aece200322 | train | function | def is_local_clone(repo_path, repo_url):
"""
Checks if the folder in `repo_path` is a local clone of `repo_url`.
"""
# First double-check that `repo_path` is a git repo
if not os.path.exists(os.path.join(repo_path, ".git")):
return False
test_git = subprocess.run("git branch".split(), cw... | def is_local_clone(repo_path, repo_url):
| """
Checks if the folder in `repo_path` is a local clone of `repo_url`.
"""
# First double-check that `repo_path` is a git repo
if not os.path.exists(os.path.join(repo_path, ".git")):
return False
test_git = subprocess.run("git branch".split(), cwd=repo_path)
if test_git.returncode !... | = types.FunctionType(f.__code__, f.__globals__, name=f.__name__, argdefs=f.__defaults__, closure=f.__closure__)
g = functools.update_wrapper(g, f)
g.__kwdefaults__ = f.__kwdefaults__
return g
def is_local_clone(repo_path, repo_url):
| 64 | 64 | 164 | 10 | 53 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_local_clone | is_local_clone | 1,910 | 1,931 | 1,910 | 1,910 | 8210980e76df9c226f0dbb374c8d33a35e107088 | bigcode/the-stack | train |
e169eaab5624d010e0b2f5f8 | train | function | def url_to_filename(url: str, etag: Optional[str] = None) -> str:
"""
Convert `url` into a hashed filename in a repeatable way. If `etag` is specified, append its hash to the url's,
delimited by a period. If the url ends with .h5 (Keras HDF5 weights) adds '.h5' to the name so that TF 2.0 can
identify it... | def url_to_filename(url: str, etag: Optional[str] = None) -> str:
| """
Convert `url` into a hashed filename in a repeatable way. If `etag` is specified, append its hash to the url's,
delimited by a period. If the url ends with .h5 (Keras HDF5 weights) adds '.h5' to the name so that TF 2.0 can
identify it as a HDF5 file (see
https://github.com/tensorflow/tensorflow/... | else:
return f"{endpoint}/{model_id}/{filename}"
if revision is None:
revision = "main"
return HUGGINGFACE_CO_PREFIX.format(model_id=model_id, revision=revision, filename=filename)
def url_to_filename(url: str, etag: Optional[str] = None) -> str:
| 68 | 68 | 228 | 20 | 48 | MichalPitr/transformers | src/transformers/file_utils.py | Python | url_to_filename | url_to_filename | 1,202 | 1,219 | 1,202 | 1,202 | 7131a09d9632574cb72a52f510651ba31d0de858 | bigcode/the-stack | train |
3aebf2f4d53d8a4c7a995a03 | train | function | def hf_bucket_url(
model_id: str, filename: str, subfolder: Optional[str] = None, revision: Optional[str] = None, mirror=None
) -> str:
"""
Resolve a model identifier, a file name, and an optional revision id, to a huggingface.co-hosted url, redirecting
to Cloudfront (a Content Delivery Network, or CDN)... | def hf_bucket_url(
model_id: str, filename: str, subfolder: Optional[str] = None, revision: Optional[str] = None, mirror=None
) -> str:
| """
Resolve a model identifier, a file name, and an optional revision id, to a huggingface.co-hosted url, redirecting
to Cloudfront (a Content Delivery Network, or CDN) for large files.
Cloudfront is replicated over the globe so downloads are way faster for the end user (and it also lowers our
band... | fn} should have an empty 'Return:' or 'Returns:' in its docstring as placeholder, current docstring is:\n{docstrings}"
)
fn.__doc__ = docstrings
return fn
return docstring_decorator
def is_remote_url(url_or_filename):
parsed = urlparse(url_or_filename)
return parsed.scheme in ... | 119 | 119 | 398 | 39 | 80 | MichalPitr/transformers | src/transformers/file_utils.py | Python | hf_bucket_url | hf_bucket_url | 1,167 | 1,199 | 1,167 | 1,169 | 827271e1c7ae4159b8c569e5e2d2998c8312ec8e | bigcode/the-stack | train |
f53baf9aef8e89059fbb37cf | train | function | def replace_return_docstrings(output_type=None, config_class=None):
def docstring_decorator(fn):
docstrings = fn.__doc__
lines = docstrings.split("\n")
i = 0
while i < len(lines) and re.search(r"^\s*Returns?:\s*$", lines[i]) is None:
i += 1
if i < len(lines):
... | def replace_return_docstrings(output_type=None, config_class=None):
| def docstring_decorator(fn):
docstrings = fn.__doc__
lines = docstrings.split("\n")
i = 0
while i < len(lines) and re.search(r"^\s*Returns?:\s*$", lines[i]) is None:
i += 1
if i < len(lines):
lines[i] = _prepare_output_docstrings(output_type, config_cl... | None else ""
built_doc = code_sample.format(**doc_kwargs)
fn.__doc__ = (fn.__doc__ or "") + "".join(docstr) + output_doc + built_doc
return fn
return docstring_decorator
def replace_return_docstrings(output_type=None, config_class=None):
| 64 | 64 | 175 | 13 | 50 | MichalPitr/transformers | src/transformers/file_utils.py | Python | replace_return_docstrings | replace_return_docstrings | 1,142 | 1,159 | 1,142 | 1,142 | c2b64c48cd5623797a030ba3c6ca5e3316d0a5c2 | bigcode/the-stack | train |
d85b2b0bde97505bfb67e440 | train | function | def is_sentencepiece_available():
return importlib.util.find_spec("sentencepiece") is not None
| def is_sentencepiece_available():
| return importlib.util.find_spec("sentencepiece") is not None
| return importlib.util.find_spec("scipy") is not None
def is_sklearn_available():
if importlib.util.find_spec("sklearn") is None:
return False
return is_scipy_available() and importlib.util.find_spec("sklearn.metrics")
def is_sentencepiece_available():
| 64 | 64 | 21 | 6 | 58 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_sentencepiece_available | is_sentencepiece_available | 344 | 345 | 344 | 344 | 39d75ce2c2893fa209351b0e474035f05b935977 | bigcode/the-stack | train |
d9ad2c822d02b1309cf3ce3c | train | function | def is_tf_available():
return _tf_available
| def is_tf_available():
| return _tf_available
| lib_metadata.version("torch"))
_torch_fx_available = (torch_version.major, torch_version.minor) == (
TORCH_FX_REQUIRED_VERSION.major,
TORCH_FX_REQUIRED_VERSION.minor,
)
def is_torch_fx_available():
return _torch_fx_available
def is_tf_available():
| 64 | 64 | 11 | 5 | 58 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_tf_available | is_tf_available | 291 | 292 | 291 | 291 | b26f8e8e3187e91dfb6aebaf4b4bac49cb792332 | bigcode/the-stack | train |
2a1dcdae6c1462617be8d608 | train | function | def is_faiss_available():
return _faiss_available
| def is_faiss_available():
| return _faiss_available
| .util.find_spec("psutil") is not None
def is_py3nvml_available():
return importlib.util.find_spec("py3nvml") is not None
def is_apex_available():
return importlib.util.find_spec("apex") is not None
def is_faiss_available():
| 64 | 64 | 14 | 7 | 56 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_faiss_available | is_faiss_available | 330 | 331 | 330 | 330 | 39ac0eb3d413850a67aa53e601115725829b49b4 | bigcode/the-stack | train |
875d025d95a9b13baeeb634d | train | class | class PushToHubMixin:
"""
A Mixin containing the functionality to push a model or tokenizer to the hub.
"""
def push_to_hub(
self,
repo_path_or_name: Optional[str] = None,
repo_url: Optional[str] = None,
use_temp_dir: bool = False,
commit_message: Optional[str] =... | class PushToHubMixin:
| """
A Mixin containing the functionality to push a model or tokenizer to the hub.
"""
def push_to_hub(
self,
repo_path_or_name: Optional[str] = None,
repo_url: Optional[str] = None,
use_temp_dir: bool = False,
commit_message: Optional[str] = None,
organiz... | Returns a copy of a function f."""
# Based on http://stackoverflow.com/a/6528148/190597 (Glenn Maynard)
g = types.FunctionType(f.__code__, f.__globals__, name=f.__name__, argdefs=f.__defaults__, closure=f.__closure__)
g = functools.update_wrapper(g, f)
g.__kwdefaults__ = f.__kwdefaults__
return g
... | 256 | 256 | 1,710 | 6 | 250 | MichalPitr/transformers | src/transformers/file_utils.py | Python | PushToHubMixin | PushToHubMixin | 1,934 | 2,107 | 1,934 | 1,934 | 398445593a3cb822410223285f100309d7adcc0d | bigcode/the-stack | train |
0e39dfd11810ab12692f1fac | train | function | def is_in_notebook():
try:
# Test adapted from tqdm.autonotebook: https://github.com/tqdm/tqdm/blob/master/tqdm/autonotebook.py
get_ipython = sys.modules["IPython"].get_ipython
if "IPKernelApp" not in get_ipython().config:
raise ImportError("console")
if "VSCODE_PID" in o... | def is_in_notebook():
| try:
# Test adapted from tqdm.autonotebook: https://github.com/tqdm/tqdm/blob/master/tqdm/autonotebook.py
get_ipython = sys.modules["IPython"].get_ipython
if "IPKernelApp" not in get_ipython().config:
raise ImportError("console")
if "VSCODE_PID" in os.environ:
... |
return importlib.util.find_spec("google.protobuf") is not None
def is_tokenizers_available():
return importlib.util.find_spec("tokenizers") is not None
def is_vision_available():
return importlib.util.find_spec("PIL") is not None
def is_in_notebook():
| 64 | 64 | 129 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_in_notebook | is_in_notebook | 362 | 373 | 362 | 362 | 8bffd1a5f7c87c343973803c1d57b3d47f4ea148 | bigcode/the-stack | train |
a98c4c378ff033d45806d1a4 | train | function | def is_soundfile_availble():
return _soundfile_available
| def is_soundfile_availble():
| return _soundfile_available
| # Lastly, check if the `smdistributed` module is present.
return importlib.util.find_spec("smdistributed") is not None
def is_training_run_on_sagemaker():
return "SAGEMAKER_JOB_NAME" in os.environ
def is_soundfile_availble():
| 64 | 64 | 15 | 8 | 55 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_soundfile_availble | is_soundfile_availble | 426 | 427 | 426 | 426 | 2a9269df79dadda8e9c1ff4622a5d361d3bf218b | bigcode/the-stack | train |
5f58c1a6c56b5daf4fae0420 | train | function | def http_user_agent(user_agent: Union[Dict, str, None] = None) -> str:
"""
Formats a user-agent string with basic info about a request.
"""
ua = f"transformers/{__version__}; python/{sys.version.split()[0]}; session_id/{SESSION_ID}"
if is_torch_available():
ua += f"; torch/{_torch_version}"
... | def http_user_agent(user_agent: Union[Dict, str, None] = None) -> str:
| """
Formats a user-agent string with basic info about a request.
"""
ua = f"transformers/{__version__}; python/{sys.version.split()[0]}; session_id/{SESSION_ID}"
if is_torch_available():
ua += f"; torch/{_torch_version}"
if is_tf_available():
ua += f"; tensorflow/{_tf_version}"
... | sm_distributed_training": runs_distributed_training,
"sm_deep_learning_container": dlc_container_used,
"sm_deep_learning_container_tag": dlc_tag,
"sm_account_id": account_id,
}
return sagemaker_object
def http_user_agent(user_agent: Union[Dict, str, None] = None) -> str:
| 75 | 75 | 250 | 21 | 53 | MichalPitr/transformers | src/transformers/file_utils.py | Python | http_user_agent | http_user_agent | 1,409 | 1,429 | 1,409 | 1,409 | d54dd3a06aea76865f046203880dbd165e8c9749 | bigcode/the-stack | train |
eae3d4d3c5ff399270521e3c | train | function | def is_timm_available():
return _timm_available
| def is_timm_available():
| return _timm_available
| module is present.
return importlib.util.find_spec("smdistributed") is not None
def is_training_run_on_sagemaker():
return "SAGEMAKER_JOB_NAME" in os.environ
def is_soundfile_availble():
return _soundfile_available
def is_timm_available():
| 64 | 64 | 13 | 6 | 57 | MichalPitr/transformers | src/transformers/file_utils.py | Python | is_timm_available | is_timm_available | 430 | 431 | 430 | 430 | 1fb8d68e94d097a99f1d5d85739ca687387508d8 | bigcode/the-stack | train |
ce4d74c9b6bad4164ad19fc4 | train | function | def _get_indent(t):
"""Returns the indentation in the first line of t"""
search = re.search(r"^(\s*)\S", t)
return "" if search is None else search.groups()[0]
| def _get_indent(t):
| """Returns the indentation in the first line of t"""
search = re.search(r"^(\s*)\S", t)
return "" if search is None else search.groups()[0]
| full_output_type}` or a tuple of
:obj:`tf.Tensor` (if ``return_dict=False`` is passed or when ``config.return_dict=False``) comprising various
elements depending on the configuration (:class:`~transformers.{config_class}`) and inputs.
"""
def _get_indent(t):
| 64 | 64 | 47 | 6 | 58 | MichalPitr/transformers | src/transformers/file_utils.py | Python | _get_indent | _get_indent | 666 | 669 | 666 | 666 | 6dddb0600b5fad3f5a5d327c4be89fb717bc5b88 | bigcode/the-stack | train |
4616a685f4604b33500ff5cd | train | function | def define_sagemaker_information():
try:
instance_data = requests.get(os.environ["ECS_CONTAINER_METADATA_URI"]).json()
dlc_container_used = instance_data["Image"]
dlc_tag = instance_data["Image"].split(":")[1]
except Exception:
dlc_container_used = None
dlc_tag = None
... | def define_sagemaker_information():
| try:
instance_data = requests.get(os.environ["ECS_CONTAINER_METADATA_URI"]).json()
dlc_container_used = instance_data["Image"]
dlc_tag = instance_data["Image"].split(":")[1]
except Exception:
dlc_container_used = None
dlc_tag = None
sagemaker_params = json.loads(os.g... | tracted)
zip_file.close()
elif tarfile.is_tarfile(output_path):
tar_file = tarfile.open(output_path)
tar_file.extractall(output_path_extracted)
tar_file.close()
else:
raise EnvironmentError(f"Archive format of {o... | 82 | 82 | 274 | 7 | 74 | MichalPitr/transformers | src/transformers/file_utils.py | Python | define_sagemaker_information | define_sagemaker_information | 1,383 | 1,406 | 1,383 | 1,383 | 2f1bd4e925b907e024d25a05ac053067be394934 | bigcode/the-stack | train |
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