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bed7e1f041189c058f434f8e
train
function
def hSAGetAccountInformation(dce, handle, pwszJobName, ccBufferSize = MAX_BUFFER_SIZE): request = SAGetAccountInformation() request['Handle'] = handle request['pwszJobName'] = checkNullString(pwszJobName) request['ccBufferSize'] = ccBufferSize for _ in range(ccBufferSize): request['wszBuffer...
def hSAGetAccountInformation(dce, handle, pwszJobName, ccBufferSize = MAX_BUFFER_SIZE):
request = SAGetAccountInformation() request['Handle'] = handle request['pwszJobName'] = checkNullString(pwszJobName) request['ccBufferSize'] = ccBufferSize for _ in range(ccBufferSize): request['wszBuffer'].append(0) return dce.request(request)
handle request['ccBufferSize'] = ccBufferSize for _ in range(ccBufferSize): request['wszBuffer'].append(0) return dce.request(request) def hSAGetAccountInformation(dce, handle, pwszJobName, ccBufferSize = MAX_BUFFER_SIZE):
64
64
95
24
40
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
hSAGetAccountInformation
hSAGetAccountInformation
168
175
168
168
23e88b77bdfea383b7c76beb279a67bf3ede66f5
bigcode/the-stack
train
b4c05bdee5ee2bc216e13d75
train
class
class SASetAccountInformationResponse(NDRCALL): structure = ( ('ErrorCode',ULONG), )
class SASetAccountInformationResponse(NDRCALL):
structure = ( ('ErrorCode',ULONG), )
0 structure = ( ('Handle', PSASEC_HANDLE), ('pwszJobName', WSTR), ('pwszAccount', WSTR), ('pwszPassword', LPWSTR), ('dwJobFlags', DWORD), ) class SASetAccountInformationResponse(NDRCALL):
64
64
23
10
54
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
SASetAccountInformationResponse
SASetAccountInformationResponse
73
76
73
73
b6f68f23c8528b0b8fdad5e5001d131f690b779b
bigcode/the-stack
train
8457fc01ea86c21724c05fb6
train
class
class SASetNSAccountInformationResponse(NDRCALL): structure = ( ('ErrorCode',ULONG), )
class SASetNSAccountInformationResponse(NDRCALL):
structure = ( ('ErrorCode',ULONG), )
1) class SASetNSAccountInformation(NDRCALL): opnum = 1 structure = ( ('Handle', PSASEC_HANDLE), ('pwszAccount', LPWSTR), ('pwszPassword', LPWSTR), ) class SASetNSAccountInformationResponse(NDRCALL):
64
64
24
11
53
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
SASetNSAccountInformationResponse
SASetNSAccountInformationResponse
87
90
87
87
73208fc491338255c4471295580cf8d4aa763d97
bigcode/the-stack
train
7d84bf95c92cb72219d3c4e6
train
class
class SASetNSAccountInformation(NDRCALL): opnum = 1 structure = ( ('Handle', PSASEC_HANDLE), ('pwszAccount', LPWSTR), ('pwszPassword', LPWSTR), )
class SASetNSAccountInformation(NDRCALL):
opnum = 1 structure = ( ('Handle', PSASEC_HANDLE), ('pwszAccount', LPWSTR), ('pwszPassword', LPWSTR), )
('dwJobFlags', DWORD), ) class SASetAccountInformationResponse(NDRCALL): structure = ( ('ErrorCode',ULONG), ) # 3.2.5.3.5 SASetNSAccountInformation (Opnum 1) class SASetNSAccountInformation(NDRCALL):
64
64
50
10
54
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
SASetNSAccountInformation
SASetNSAccountInformation
79
85
79
79
b1fe150cdcaa8e47a1e8baea226c746cc1155f5d
bigcode/the-stack
train
951557ab42f41b98cfba25be
train
class
class SASetAccountInformation(NDRCALL): opnum = 0 structure = ( ('Handle', PSASEC_HANDLE), ('pwszJobName', WSTR), ('pwszAccount', WSTR), ('pwszPassword', LPWSTR), ('dwJobFlags', DWORD), )
class SASetAccountInformation(NDRCALL):
opnum = 0 structure = ( ('Handle', PSASEC_HANDLE), ('pwszJobName', WSTR), ('pwszAccount', WSTR), ('pwszPassword', LPWSTR), ('dwJobFlags', DWORD), )
################################################################################ # STRUCTURES ################################################################################ class WORD_ARRAY(NDRUniConformantArray): item = '<H' ################################################################################ # RPC ...
64
64
67
9
55
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
SASetAccountInformation
SASetAccountInformation
63
71
63
63
68ed814c7df739ab27b682d9bd2ea8abda3c0e1b
bigcode/the-stack
train
a38035c0ae706167c954eb42
train
function
def hSASetAccountInformation(dce, handle, pwszJobName, pwszAccount, pwszPassword, dwJobFlags=0): request = SASetAccountInformation() request['Handle'] = handle request['pwszJobName'] = checkNullString(pwszJobName) request['pwszAccount'] = checkNullString(pwszAccount) request['pwszPassword'] = checkN...
def hSASetAccountInformation(dce, handle, pwszJobName, pwszAccount, pwszPassword, dwJobFlags=0):
request = SASetAccountInformation() request['Handle'] = handle request['pwszJobName'] = checkNullString(pwszJobName) request['pwszAccount'] = checkNullString(pwszAccount) request['pwszPassword'] = checkNullString(pwszPassword) request['dwJobFlags'] = dwJobFlags return dce.request(request)
string == NULL: return string if string[-1:] != '\x00': return string + '\x00' else: return string def hSASetAccountInformation(dce, handle, pwszJobName, pwszAccount, pwszPassword, dwJobFlags=0):
64
64
112
30
33
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
hSASetAccountInformation
hSASetAccountInformation
144
151
144
144
674b27141c5eadfb3071c3e6e5f7bc8ef8b5bfc7
bigcode/the-stack
train
fe8e4abdb7663d8869ce9ce2
train
function
def hSAGetNSAccountInformation(dce, handle, ccBufferSize = MAX_BUFFER_SIZE): request = SAGetNSAccountInformation() request['Handle'] = handle request['ccBufferSize'] = ccBufferSize for _ in range(ccBufferSize): request['wszBuffer'].append(0) return dce.request(request)
def hSAGetNSAccountInformation(dce, handle, ccBufferSize = MAX_BUFFER_SIZE):
request = SAGetNSAccountInformation() request['Handle'] = handle request['ccBufferSize'] = ccBufferSize for _ in range(ccBufferSize): request['wszBuffer'].append(0) return dce.request(request)
request['Handle'] = handle request['pwszAccount'] = checkNullString(pwszAccount) request['pwszPassword'] = checkNullString(pwszPassword) return dce.request(request) def hSAGetNSAccountInformation(dce, handle, ccBufferSize = MAX_BUFFER_SIZE):
64
64
75
20
44
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
hSAGetNSAccountInformation
hSAGetNSAccountInformation
160
166
160
160
35d4700553711fafadbab2087c6ec2b1125e359f
bigcode/the-stack
train
906ddfe7f46594f7bb3b33aa
train
class
class SAGetNSAccountInformationResponse(NDRCALL): structure = ( ('wszBuffer',WORD_ARRAY), ('ErrorCode',ULONG), )
class SAGetNSAccountInformationResponse(NDRCALL):
structure = ( ('wszBuffer',WORD_ARRAY), ('ErrorCode',ULONG), )
Opnum 2) class SAGetNSAccountInformation(NDRCALL): opnum = 2 structure = ( ('Handle', PSASEC_HANDLE), ('ccBufferSize', DWORD), ('wszBuffer', WORD_ARRAY), ) class SAGetNSAccountInformationResponse(NDRCALL):
64
64
32
11
53
addenial/impacket
impacket/dcerpc/v5/sasec.py
Python
SAGetNSAccountInformationResponse
SAGetNSAccountInformationResponse
101
105
101
101
ef11d1e4aba65be6329adf5c9c5f4c58b4b9c603
bigcode/the-stack
train
3e289dd878750033481093dc
train
function
def _mix_settings_with_env(settings): """Reads CONAN_ENV_XXXX variables from environment and if it's defined uses these value instead of the default from conf file. If you specify a compiler with ENV variable you need to specify all the subsettings, the file defaulted will be ignored""" def get...
def _mix_settings_with_env(settings):
"""Reads CONAN_ENV_XXXX variables from environment and if it's defined uses these value instead of the default from conf file. If you specify a compiler with ENV variable you need to specify all the subsettings, the file defaulted will be ignored""" def get_env_value(name_): env_name = ...
if os.path.exists(self.default_profile_path): remove(self.default_profile_path) self.initialize_default_profile() def initialize_settings(self): if not os.path.exists(self.settings_path): save(self.settings_path, normalize(get_default_settings_yml())) def reset_setting...
85
85
284
8
77
matthiasng/conan
conans/client/cache/cache.py
Python
_mix_settings_with_env
_mix_settings_with_env
283
311
283
283
ef29c308d16a025a2d8ee78d43acdce54a02776f
bigcode/the-stack
train
1e796eee655b3ab7c69f6513
train
class
class ClientCache(object): """ Class to represent/store/compute all the paths involved in the execution of conans commands. Accesses to real disk and reads/write things. (OLD client ConanPaths) """ def __init__(self, cache_folder, output): self.cache_folder = cache_folder self._output =...
class ClientCache(object):
""" Class to represent/store/compute all the paths involved in the execution of conans commands. Accesses to real disk and reads/write things. (OLD client ConanPaths) """ def __init__(self, cache_folder, output): self.cache_folder = cache_folder self._output = output # Caching ...
ocks import Lock CONAN_CONF = 'conan.conf' CONAN_SETTINGS = "settings.yml" LOCALDB = ".conan.db" REMOTES = "remotes.json" PROFILES_FOLDER = "profiles" HOOKS_FOLDER = "hooks" TEMPLATES_FOLDER = "templates" def is_case_insensitive_os(): system = platform.system() return system != "Linux" and system != "FreeBSD...
256
256
1,676
5
250
matthiasng/conan
conans/client/cache/cache.py
Python
ClientCache
ClientCache
64
280
64
64
adc216d2805292f1737cf3fad70cb21fa0557b6b
bigcode/the-stack
train
d5d278dc5a92db008618a7b0
train
function
def is_case_insensitive_os(): system = platform.system() return system != "Linux" and system != "FreeBSD" and system != "SunOS"
def is_case_insensitive_os():
system = platform.system() return system != "Linux" and system != "FreeBSD" and system != "SunOS"
Lock CONAN_CONF = 'conan.conf' CONAN_SETTINGS = "settings.yml" LOCALDB = ".conan.db" REMOTES = "remotes.json" PROFILES_FOLDER = "profiles" HOOKS_FOLDER = "hooks" TEMPLATES_FOLDER = "templates" def is_case_insensitive_os():
64
64
34
7
57
matthiasng/conan
conans/client/cache/cache.py
Python
is_case_insensitive_os
is_case_insensitive_os
37
39
37
37
04863dc143e86ce604c59f868958c917bf0b8ec9
bigcode/the-stack
train
d28bff7e1768023e45241bba
train
function
def process_gpu(cntr): # GPUs may not have been assigned to a pod gpu = 0 gpuvendor = 'nvidia' try: gpu = cntr["resources"]["limits"]["nvidia.com/gpu"] except KeyError: try: gpu = cntr["resources"]["limits"]["amd.com/gpu"] gpuvendor = 'amd' excep...
def process_gpu(cntr): # GPUs may not have been assigned to a pod
gpu = 0 gpuvendor = 'nvidia' try: gpu = cntr["resources"]["limits"]["nvidia.com/gpu"] except KeyError: try: gpu = cntr["resources"]["limits"]["amd.com/gpu"] gpuvendor = 'amd' except KeyError: gpu = 0 gpuvendor = '' return gpu, ...
.metadata.namespace, "size": rsrc.spec.resources.requests["storage"], "mode": rsrc.spec.access_modes[0], "class": rsrc.spec.storage_class_name, } return res def process_gpu(cntr): # GPUs may not have been assigned to a pod
64
64
106
20
43
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
process_gpu
process_gpu
262
277
262
264
872cd3b93993d56c1b91a1a83147e54259cd9635
bigcode/the-stack
train
114527e905d813b688f503c3
train
function
def get_data_vols(body, defaults): """ Checks the config and the form values and returns a list of Volume Dictionaries for the Notebook's Data Volumes. If the Data Volumes are readOnly, then the value from the config will be used instead. The Volume Dict has the same format as the Volume interface o...
def get_data_vols(body, defaults):
""" Checks the config and the form values and returns a list of Volume Dictionaries for the Notebook's Data Volumes. If the Data Volumes are readOnly, then the value from the config will be used instead. The Volume Dict has the same format as the Volume interface of the frontend. """ default...
(ws)) elif form_ws is not None: ws = form_ws logger.info("Using form's Workspace Volume: {}".format(ws)) else: ws = default_ws logger.info("Using the default Workspace Volume: {}".format(ws)) return ws def get_data_vols(body, defaults):
66
66
220
9
56
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
get_data_vols
get_data_vols
223
246
223
223
a67384e6b97fe7d0c2e10b5659627e6e5ec9c986
bigcode/the-stack
train
7e1bd64daf9636603761ed17
train
function
def process_resource(rsrc, rsrc_events): # VAR: change this function according to the main resource cntr = rsrc["spec"]["template"]["spec"]["containers"][0] status, reason = process_status(rsrc, rsrc_events) gpu, gpuvendor = process_gpu(cntr) res = { "name": rsrc["metadata"]["name"], ...
def process_resource(rsrc, rsrc_events): # VAR: change this function according to the main resource
cntr = rsrc["spec"]["template"]["spec"]["containers"][0] status, reason = process_status(rsrc, rsrc_events) gpu, gpuvendor = process_gpu(cntr) res = { "name": rsrc["metadata"]["name"], "namespace": rsrc["metadata"]["namespace"], "age": get_uptime(rsrc["metadata"]["creationTim...
tr["resources"]["limits"]["amd.com/gpu"] gpuvendor = 'amd' except KeyError: gpu = 0 gpuvendor = '' return gpu, gpuvendor def process_resource(rsrc, rsrc_events): # VAR: change this function according to the main resource
64
64
210
23
40
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
process_resource
process_resource
280
300
280
281
339c0f8cea7d332c23e1b522329b72f20f400e7a
bigcode/the-stack
train
7fbe126e86403e2f59366104
train
function
def set_notebook_shm(notebook, body, defaults): if defaults["shm"].get("readOnly", False): if not defaults["shm"]["value"]: return elif "shm" in body: if not body["shm"]: return else: if not defaults["shm"]["value"]: return notebook_spec = not...
def set_notebook_shm(notebook, body, defaults):
if defaults["shm"].get("readOnly", False): if not defaults["shm"]["value"]: return elif "shm" in body: if not body["shm"]: return else: if not defaults["shm"]["value"]: return notebook_spec = notebook["spec"]["template"]["spec"] notebook_c...
extra = json.loads(resources_str) except Exception as e: r["success"] = False r["log"] = api.parse_error(e) return r container["resources"]["limits"] = extra return r def set_notebook_shm(notebook, body, defaults):
64
64
175
13
50
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_shm
set_notebook_shm
514
531
514
514
7c73d6f60af03d47533f8d546b0befb8c81c4fc5
bigcode/the-stack
train
9407208d29d53b78026d4f33
train
function
def spawner_ui_config(): for config in CONFIGS: c = None try: with open(config, "r") as f: c = f.read() except IOError: logger.warning("Config file '{}' is not found".format(config)) continue try: if yaml.safe_load(c) i...
def spawner_ui_config():
for config in CONFIGS: c = None try: with open(config, "r") as f: c = f.read() except IOError: logger.warning("Config file '{}' is not found".format(config)) continue try: if yaml.safe_load(c) is None: #...
is None: # YAML exists but is empty return {} else: # YAML exists and is not empty return yaml.safe_load(c) except yaml.YAMLError as e: logger.warning("Couldn't load yaml: {}".format(e)) return None def spawner_ui_config():
64
64
182
6
57
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
spawner_ui_config
spawner_ui_config
88
115
88
88
6ce6870c9c319ec582b4ba9f1d14fee891d910d6
bigcode/the-stack
train
1ad2a153c2f66ef551a10181
train
function
def create_logger(name): handler = logging.StreamHandler(sys.stdout) handler.setFormatter( logging.Formatter( "%(asctime)s | %(name)s | %(levelname)s | %(message)s" ) ) logger = logging.getLogger(name) logger.setLevel(logging.INFO) logger.addHandler(handler) retur...
def create_logger(name):
handler = logging.StreamHandler(sys.stdout) handler.setFormatter( logging.Formatter( "%(asctime)s | %(name)s | %(levelname)s | %(message)s" ) ) logger = logging.getLogger(name) logger.setLevel(logging.INFO) logger.addHandler(handler) return logger
") USER_PREFIX = os.getenv("USERID_PREFIX", "accounts.google.com:") EVENT_TYPE_NORMAL = "Normal" EVENT_TYPE_WARNING = "Warning" STATUS_ERROR = "error" STATUS_WARNING = "warning" STATUS_RUNNING = "running" STATUS_WAITING = "waiting" # Logging def create_logger(name):
64
64
73
5
58
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
create_logger
create_logger
34
44
34
34
314972b5a96bcbf7e5228e1c01ea8708a446687f
bigcode/the-stack
train
65c66a802ac3e77d7e31596a
train
function
def set_notebook_image(notebook, body, defaults): """ If the image is set to readOnly, use only the value from the config """ if defaults["image"].get("readOnly", False): image = defaults["image"]["value"] logger.info("Using default Image: " + image) elif body.get("customImageCheck",...
def set_notebook_image(notebook, body, defaults):
""" If the image is set to readOnly, use only the value from the config """ if defaults["image"].get("readOnly", False): image = defaults["image"]["value"] logger.info("Using default Image: " + image) elif body.get("customImageCheck", False): image = body["customImage"] ...
event_timestamp, reverse=True): if e.type == EVENT_TYPE_WARNING: return STATUS_WAITING, e.message return None, None def event_timestamp(event): return event.metadata.creation_timestamp.replace(tzinfo=None) # Notebook YAML processing def set_notebook_image(notebook, body, defaults):
64
64
171
12
51
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_image
set_notebook_image
359
376
359
359
ec8dc16b4bc532336e875372c5a76a591314028f
bigcode/the-stack
train
47774b91417bdbfeff131972
train
function
def volume_from_config(config_vol, notebook): """ Create a Volume Dict from the config.yaml. This dict has the same fields as a Volume returned from the frontend """ vol_name = config_vol["name"]["value"].replace( "{notebook-name}", notebook["name"] ) vol_class = handle_storage_class...
def volume_from_config(config_vol, notebook):
""" Create a Volume Dict from the config.yaml. This dict has the same fields as a Volume returned from the frontend """ vol_name = config_vol["name"]["value"].replace( "{notebook-name}", notebook["name"] ) vol_class = handle_storage_class(config_vol["class"]["value"]) return { ...
"class" not in vol: return None if vol["class"] == "{empty}": return "" if vol["class"] == "{none}": return None else: return vol["class"] # Volume handling functions def volume_from_config(config_vol, notebook):
64
64
155
9
54
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
volume_from_config
volume_from_config
163
181
163
163
5d5102d53309db249acec71b20b84f4a1aec9619
bigcode/the-stack
train
d87fa911d12a6711ac7df635
train
function
def set_notebook_gpus(notebook, body, defaults): gpus = None gpuDefaults = defaults.get("gpus", {}) if gpuDefaults.get("readOnly", False): # The server should not allow the user to set the GPUs # if the config's value is readOnly. Use the config's value gpus = gpuDefaults["value"] ...
def set_notebook_gpus(notebook, body, defaults):
gpus = None gpuDefaults = defaults.get("gpus", {}) if gpuDefaults.get("readOnly", False): # The server should not allow the user to set the GPUs # if the config's value is readOnly. Use the config's value gpus = gpuDefaults["value"] logger.info(f"Using default GPU config: {gp...
body, defaults): container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["memory"].get("readOnly", False): memory = defaults["memory"]["value"] logger.info("Using default Memory: " + memory) elif body.get("memory", ""): memory = body["memory"] logger.i...
131
131
438
13
117
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_gpus
set_notebook_gpus
411
463
411
411
da5d3e57788364ab5f2529c485e2f2ac709bf617
bigcode/the-stack
train
d949d6f87caa6a5f4e993ad8
train
function
def set_notebook_configurations(notebook, body, defaults): notebook_labels = notebook["metadata"]["labels"] if defaults["configurations"].get("readOnly", False): labels = defaults["configurations"]["value"] logger.info("Using default Configurations: {}".format(labels)) elif body.get("config...
def set_notebook_configurations(notebook, body, defaults):
notebook_labels = notebook["metadata"]["labels"] if defaults["configurations"].get("readOnly", False): labels = defaults["configurations"]["value"] logger.info("Using default Configurations: {}".format(labels)) elif body.get("configurations", None) is not None: labels = body["config...
containers"][0] vendor = gpus["vendor"] num = int(gpus["num"]) limits = container["resources"].get("limits", {}) limits[vendor] = num container["resources"]["limits"] = limits def set_notebook_configurations(notebook, body, defaults):
64
64
168
13
50
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_configurations
set_notebook_configurations
466
486
466
466
046efad9e43f8008a0c05ae815fe443d70a0e79c
bigcode/the-stack
train
e160f3e05c580451001dc1d7
train
function
def set_notebook_memory(notebook, body, defaults): container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["memory"].get("readOnly", False): memory = defaults["memory"]["value"] logger.info("Using default Memory: " + memory) elif body.get("memory", ""): memory ...
def set_notebook_memory(notebook, body, defaults):
container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["memory"].get("readOnly", False): memory = defaults["memory"]["value"] logger.info("Using default Memory: " + memory) elif body.get("memory", ""): memory = body["memory"] logger.info("Using form's ...
["cpu"] logger.info("Using form's CPU: " + cpu) else: cpu = defaults["cpu"]["value"] logger.info("Using default CPU: " + cpu) container["resources"]["requests"]["cpu"] = cpu def set_notebook_memory(notebook, body, defaults):
64
64
126
12
51
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_memory
set_notebook_memory
395
408
395
395
a94b992f2619c5181f866ba51773fd22c8c503e1
bigcode/the-stack
train
fa6c72f5f54e633de7342f2d
train
function
def event_timestamp(event): return event.metadata.creation_timestamp.replace(tzinfo=None)
def event_timestamp(event):
return event.metadata.creation_timestamp.replace(tzinfo=None)
1 nodes are available: 1 Insufficient cpu (originated in pod) ''' for e in sorted(rsrc_events, key=event_timestamp, reverse=True): if e.type == EVENT_TYPE_WARNING: return STATUS_WAITING, e.message return None, None def event_timestamp(event):
64
64
17
5
58
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
event_timestamp
event_timestamp
354
355
354
354
b0acf31ebd2b218daee90660c9a12501680e10a6
bigcode/the-stack
train
b5b71905b8d58f3fd66546e8
train
function
def add_notebook_volume_secret(nb, secret, secret_name, mnt_path, mode): # Create the volume in the Pod spec = nb["spec"]["template"]["spec"] container = nb["spec"]["template"]["spec"]["containers"][0] volume = { "name": secret, "secret": {"defaultMode": mode, "secretName": secret_name,...
def add_notebook_volume_secret(nb, secret, secret_name, mnt_path, mode): # Create the volume in the Pod
spec = nb["spec"]["template"]["spec"] container = nb["spec"]["template"]["spec"]["containers"][0] volume = { "name": secret, "secret": {"defaultMode": mode, "secretName": secret_name, }, } spec["volumes"].append(volume) # Container volumeMounts mnt = { "mountPath": ...
) # Container Mounts mnt = {"mountPath": mnt_path, "name": vol_name} container["volumeMounts"].append(mnt) def add_notebook_volume_secret(nb, secret, secret_name, mnt_path, mode): # Create the volume in the Pod
64
64
133
28
36
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
add_notebook_volume_secret
add_notebook_volume_secret
546
562
546
547
d687693d55ddac7b4138276431396a8b0c1d10a1
bigcode/the-stack
train
099961842d54f4d90010683d
train
function
def get_username_from_request(): if USER_HEADER not in request.headers: logger.debug("User header not present!") username = None else: user = request.headers[USER_HEADER] username = user.replace(USER_PREFIX, "") logger.debug( "User: '{}' | Headers: '{}' '{}'"....
def get_username_from_request():
if USER_HEADER not in request.headers: logger.debug("User header not present!") username = None else: user = request.headers[USER_HEADER] username = user.replace(USER_PREFIX, "") logger.debug( "User: '{}' | Headers: '{}' '{}'".format( username,...
"%(asctime)s | %(name)s | %(levelname)s | %(message)s" ) ) logger = logging.getLogger(name) logger.setLevel(logging.INFO) logger.addHandler(handler) return logger logger = create_logger(__name__) # Utils def get_username_from_request():
64
64
84
6
57
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
get_username_from_request
get_username_from_request
51
64
51
51
9b383ecccb45445dfdd87b3c9e9b34e7e7240c00
bigcode/the-stack
train
12b820e36e5599d849ca8c72
train
function
def get_workspace_vol(body, defaults): """ Checks the config and the form values and returns a Volume Dict for the workspace. If the workspace is readOnly, then the value from the config will be used instead. The Volume Dict has the same format as the Volume interface of the frontend. """ de...
def get_workspace_vol(body, defaults):
""" Checks the config and the form values and returns a Volume Dict for the workspace. If the workspace is readOnly, then the value from the config will be used instead. The Volume Dict has the same format as the Volume interface of the frontend. """ default_ws = volume_from_config(defaults[...
=namespace,), spec=client.V1PersistentVolumeClaimSpec( access_modes=[vol["mode"]], storage_class_name=handle_storage_class(vol), resources=client.V1ResourceRequirements( requests={"storage": vol["size"]} ), ), ) def get_workspace_vol(bo...
64
64
185
8
56
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
get_workspace_vol
get_workspace_vol
200
220
200
200
28a03659a43c30b749bcfa7a6f62cd2057ce7157
bigcode/the-stack
train
67d4d5d588d036b5f392a181
train
function
def handle_storage_class(vol): # handle the StorageClass if "class" not in vol: return None if vol["class"] == "{empty}": return "" if vol["class"] == "{none}": return None else: return vol["class"]
def handle_storage_class(vol): # handle the StorageClass
if "class" not in vol: return None if vol["class"] == "{empty}": return "" if vol["class"] == "{none}": return None else: return vol["class"]
if mins == 0: return "just now" if mins == 1: age = str(mins) + " min" else: age = str(mins) + " mins" return age + " ago" def handle_storage_class(vol): # handle the StorageClass
64
64
64
13
51
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
handle_storage_class
handle_storage_class
150
159
150
151
202a87298a837b9555f9f612f64820f64ce1355e
bigcode/the-stack
train
9c19dfd84946a6dad5d5e886
train
function
def get_uptime(then): now = dt.datetime.now() then = dt.datetime.strptime(then, "%Y-%m-%dT%H:%M:%SZ") diff = now - then.replace(tzinfo=None) days = diff.days hours = int(diff.seconds / 3600) mins = int((diff.seconds % 3600) / 60) age = "" if days > 0: if days == 1: ...
def get_uptime(then):
now = dt.datetime.now() then = dt.datetime.strptime(then, "%Y-%m-%dT%H:%M:%SZ") diff = now - then.replace(tzinfo=None) days = diff.days hours = int(diff.seconds / 3600) mins = int((diff.seconds % 3600) / 60) age = "" if days > 0: if days == 1: age = str(days) + " da...
: logger.error("Notebook config is not a valid yaml") return {} except AttributeError as e: logger.error( "Can't load the config at {}: {}".format(config, str(e)) ) logger.warning("Couldn't load any config") return {} def get_uptime(then):...
64
65
218
7
57
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
get_uptime
get_uptime
118
147
118
118
525652d41cb44c823d207fca8828566e7a9d2874
bigcode/the-stack
train
8ad82f7b60ac71ed2ab0c9bd
train
function
def set_notebook_cpu(notebook, body, defaults): container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["cpu"].get("readOnly", False): cpu = defaults["cpu"]["value"] logger.info("Using default CPU: " + cpu) elif body.get("cpu", ""): cpu = body["cpu"] lo...
def set_notebook_cpu(notebook, body, defaults):
container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["cpu"].get("readOnly", False): cpu = defaults["cpu"]["value"] logger.info("Using default CPU: " + cpu) elif body.get("cpu", ""): cpu = body["cpu"] logger.info("Using form's CPU: " + cpu) else: ...
("Using form's Image: " + image) else: image = defaults["image"]["value"] logger.info("Using default Image: " + image) notebook["spec"]["template"]["spec"]["containers"][0]["image"] = image def set_notebook_cpu(notebook, body, defaults):
64
64
126
12
51
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_cpu
set_notebook_cpu
379
392
379
379
26d34b065acb1bffdb8792d3627ae40222e54755
bigcode/the-stack
train
b4fa3bc197f63b7e1844b774
train
function
def add_notebook_volume(notebook, vol_name, claim, mnt_path): spec = notebook["spec"]["template"]["spec"] container = notebook["spec"]["template"]["spec"]["containers"][0] volume = {"name": vol_name, "persistentVolumeClaim": {"claimName": claim}} spec["volumes"].append(volume) # Container Mounts ...
def add_notebook_volume(notebook, vol_name, claim, mnt_path):
spec = notebook["spec"]["template"]["spec"] container = notebook["spec"]["template"]["spec"]["containers"][0] volume = {"name": vol_name, "persistentVolumeClaim": {"claimName": claim}} spec["volumes"].append(volume) # Container Mounts mnt = {"mountPath": mnt_path, "name": vol_name} contain...
notebook_spec["volumes"].append(shm_volume) shm_mnt = {"mountPath": "/dev/shm", "name": "dshm"} notebook_cont["volumeMounts"].append(shm_mnt) def add_notebook_volume(notebook, vol_name, claim, mnt_path):
64
64
107
17
47
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
add_notebook_volume
add_notebook_volume
534
543
534
534
910b8f5538ef46593d6fc36532ec6a02c2ac1cbd
bigcode/the-stack
train
f1a16a48941c37a74b0b14d3
train
function
def process_pvc(rsrc): # VAR: change this function according to the main resource res = { "name": rsrc.metadata.name, "namespace": rsrc.metadata.namespace, "size": rsrc.spec.resources.requests["storage"], "mode": rsrc.spec.access_modes[0], "class": rsrc.spec.storage_class...
def process_pvc(rsrc): # VAR: change this function according to the main resource
res = { "name": rsrc.metadata.name, "namespace": rsrc.metadata.namespace, "size": rsrc.spec.resources.requests["storage"], "mode": rsrc.spec.access_modes[0], "class": rsrc.spec.storage_class_name, } return res
s)) else: vols = default_vols logger.info("Using the default Data Volumes: {}".format(vols)) return vols # Functions for transforming the data from k8s api def process_pvc(rsrc): # VAR: change this function according to the main resource
64
64
83
20
43
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
process_pvc
process_pvc
250
259
250
251
8821054f5d0d277a4063eee71895a3b557b14339
bigcode/the-stack
train
1fb75c7f7e6ad057fcf579d1
train
function
def pvc_from_dict(vol, namespace): if vol is None: return None return client.V1PersistentVolumeClaim( metadata=client.V1ObjectMeta(name=vol["name"], namespace=namespace,), spec=client.V1PersistentVolumeClaimSpec( access_modes=[vol["mode"]], storage_class_name=han...
def pvc_from_dict(vol, namespace):
if vol is None: return None return client.V1PersistentVolumeClaim( metadata=client.V1ObjectMeta(name=vol["name"], namespace=namespace,), spec=client.V1PersistentVolumeClaimSpec( access_modes=[vol["mode"]], storage_class_name=handle_storage_class(vol), ...
"size": config_vol["size"]["value"], "mode": config_vol["accessModes"]["value"], "path": config_vol["mountPath"]["value"], "class": vol_class, "extraFields": config_vol.get("extra", {}), } def pvc_from_dict(vol, namespace):
64
64
98
8
56
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
pvc_from_dict
pvc_from_dict
184
197
184
184
43bc5ca672a9c08644ec9f9938e516610907c0c7
bigcode/the-stack
train
4d3d063be0c6a8e6276211da
train
function
def set_notebook_extra_resources(notebook, body, defaults): r = {"success": True, "log": ""} container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["extraResources"].get("readOnly", False): resources_str = defaults["extraResources"]["value"] logger.info("Using the def...
def set_notebook_extra_resources(notebook, body, defaults):
r = {"success": True, "log": ""} container = notebook["spec"]["template"]["spec"]["containers"][0] if defaults["extraResources"].get("readOnly", False): resources_str = defaults["extraResources"]["value"] logger.info("Using the default Extra Resources: " + resources_str) elif body.get("...
: {}".format(labels)) if not isinstance(labels, list): logger.warning( "Labels for PodDefaults are not list: {}".format(labels) ) return for l in labels: notebook_labels[l] = "true" def set_notebook_extra_resources(notebook, body, defaults):
64
64
196
13
51
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
set_notebook_extra_resources
set_notebook_extra_resources
489
511
489
489
2b3917ed242a4896c20fbd6cfe1cc71d075920c1
bigcode/the-stack
train
8b7d00b3add34655720b6a6e
train
function
def load_param_yaml(f, **kwargs): c = None try: with open(f, "r") as f: c = f.read().format(**kwargs) except IOError: logger.info("Error opening: {}".format(f)) return None try: if yaml.safe_load(c) is None: # YAML exists but is empty ...
def load_param_yaml(f, **kwargs):
c = None try: with open(f, "r") as f: c = f.read().format(**kwargs) except IOError: logger.info("Error opening: {}".format(f)) return None try: if yaml.safe_load(c) is None: # YAML exists but is empty return {} else: ...
else: user = request.headers[USER_HEADER] username = user.replace(USER_PREFIX, "") logger.debug( "User: '{}' | Headers: '{}' '{}'".format( username, USER_HEADER, USER_PREFIX ) ) return username def load_param_yaml(f, **kwargs):
64
64
125
9
54
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
load_param_yaml
load_param_yaml
67
85
67
67
c32cad169df827b1748a980c12f441c1ad2f49e4
bigcode/the-stack
train
62a71a3db2a9543962f2fd55
train
function
def find_error_event(rsrc_events): ''' Returns status and reason from the latest event that surfaces the cause of why the resource could not be created. For a Notebook, it can be due to: EVENT_TYPE EVENT_REASON DESCRIPTION Warning FailedCreate pods "x" is forbi...
def find_error_event(rsrc_events):
''' Returns status and reason from the latest event that surfaces the cause of why the resource could not be created. For a Notebook, it can be due to: EVENT_TYPE EVENT_REASON DESCRIPTION Warning FailedCreate pods "x" is forbidden: error looking up service acco...
# Provide the user with detailed information (if any) about why the notebook is not starting status_event, reason_event = find_error_event(rsrc_events) if status_event: status, reason = status_event, reason_event return status, reason def find_error_event(rsrc_events):
64
64
148
8
55
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
find_error_event
find_error_event
338
351
338
338
e431aa8c6739ed8683e28e8ddf1d7d528dec8347
bigcode/the-stack
train
f971ffc3207f8ed63b63fcd9
train
function
def process_status(rsrc, rsrc_events): """ Return status and reason. Status may be [running|waiting|warning|error] """ # If the Notebook is being deleted, the status will be waiting if "deletionTimestamp" in rsrc["metadata"]: return STATUS_WAITING, "Deleting Notebook Server" # Check the...
def process_status(rsrc, rsrc_events):
""" Return status and reason. Status may be [running|waiting|warning|error] """ # If the Notebook is being deleted, the status will be waiting if "deletionTimestamp" in rsrc["metadata"]: return STATUS_WAITING, "Deleting Notebook Server" # Check the status try: s = rsrc["stat...
("/")[-1], "cpu": cntr["resources"]["requests"]["cpu"], "gpu": gpu, "gpuvendor": gpuvendor, "memory": cntr["resources"]["requests"]["memory"], "volumes": [v["name"] for v in cntr["volumeMounts"]], "status": status, "reason": reason, } return res def proces...
92
92
309
10
81
StefanoFioravanzo/kubeflow
components/jupyter-web-app/backend/kubeflow_jupyter/common/utils.py
Python
process_status
process_status
303
335
303
303
cb5bd042135cdf4185cd6289c55a6d9444d7934f
bigcode/the-stack
train
ad7ce6cc479a77f5691123ea
train
function
def update_config(config_file): exp_config = None with open(config_file) as f: exp_config = edict(yaml.load(f)) for k, v in exp_config.items(): if k in config: if isinstance(v, dict): if k == 'TRAIN': if 'BBOX_WEIGHTS' in v:...
def update_config(config_file):
exp_config = None with open(config_file) as f: exp_config = edict(yaml.load(f)) for k, v in exp_config.items(): if k in config: if isinstance(v, dict): if k == 'TRAIN': if 'BBOX_WEIGHTS' in v: v['...
# RCNN nms config.TEST.NMS = 0.3 config.TEST.max_per_image = 300 # config.TEST.KEY_FRAME_INTERVAL = 9 config.TEST.SEQ_NMS = False # Test Model Epoch config.TEST.test_epoch = 0 def update_config(config_file):
64
64
193
6
57
sdroh1027/track_to_learn
fgfa_rfcn/config/config.py
Python
update_config
update_config
160
181
160
160
68cfcc526328d53b03b06f87b4d662730dcd6186
bigcode/the-stack
train
6ca4919d3730c30b94ac5aa0
train
class
class TestDynamicsBindings(TestCase): def setUp(self): self.model = pin.buildSampleModelHumanoidRandom() self.data = self.model.createData() qmax = np.matrix(np.full((self.model.nq,1),np.pi)) self.q = pin.randomConfiguration(self.model,-qmax,qmax) self.v = rand(self.model.n...
class TestDynamicsBindings(TestCase):
def setUp(self): self.model = pin.buildSampleModelHumanoidRandom() self.data = self.model.createData() qmax = np.matrix(np.full((self.model.nq,1),np.pi)) self.q = pin.randomConfiguration(self.model,-qmax,qmax) self.v = rand(self.model.nv) self.tau = rand(self.model.n...
import unittest from test_case import TestCase import pinocchio as pin from pinocchio.utils import rand, zero import numpy as np # common quantities for all tests. # They correspond to the default values of the arguments, and they need to stay this way r_coeff = 0.0 inv_damping = 0.0 update_kinematics = True class Tes...
90
241
805
7
82
mkatliar/pinocchio
unittest/python/bindings_dynamics.py
Python
TestDynamicsBindings
TestDynamicsBindings
14
80
14
15
d566aff01f8eeb697e0f6b928a6b86f8170b73f1
bigcode/the-stack
train
08cd1af0f79acebcee7fc305
train
class
class PythonSH(BaseSH): """Python Syntax Highlighter""" # Syntax highlighting rules: add_kw = ['async', 'await'] PROG = re.compile(make_python_patterns(additional_keywords=add_kw), re.S) IDPROG = re.compile(r"\s+(\w+)", re.S) ASPROG = re.compile(r"\b(as)\b") # Syntax highlighting stat...
class PythonSH(BaseSH):
"""Python Syntax Highlighter""" # Syntax highlighting rules: add_kw = ['async', 'await'] PROG = re.compile(make_python_patterns(additional_keywords=add_kw), re.S) IDPROG = re.compile(r"\s+(\w+)", re.S) ASPROG = re.compile(r"\b(as)\b") # Syntax highlighting states (from one text block t...
string1 = any("uf_sqstring", [uf_sqstring]) ufstring2 = any("uf_dqstring", [uf_dqstring]) ufstring3 = any("uf_sq3string", [uf_sq3string]) ufstring4 = any("uf_dq3string", [uf_dq3string]) ufstring5 = any("ufe_sqstring", [ufe_sqstring]) ufstring6 = any("ufe_dqstring", [ufe_dqstring]) return "...
256
256
1,871
6
249
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
PythonSH
PythonSH
486
684
486
486
f72b81664a907106eaa52eff0c6e40e2eb309c9b
bigcode/the-stack
train
54f8b5eeeaabfb646a7d84cc
train
class
class BaseWebSH(BaseSH): """Base class for CSS and HTML syntax highlighters""" NORMAL = 0 COMMENT = 1 def __init__(self, parent, font=None, color_scheme=None): BaseSH.__init__(self, parent, font, color_scheme) def highlight_block(self, text): """Implement highlight specif...
class BaseWebSH(BaseSH):
"""Base class for CSS and HTML syntax highlighters""" NORMAL = 0 COMMENT = 1 def __init__(self, parent, font=None, color_scheme=None): BaseSH.__init__(self, parent, font, color_scheme) def highlight_block(self, text): """Implement highlight specific for CSS and HTML.""" ...
[rRuU])?'[^'\\\n]*(\\.[^'\\\n]*)*'?" dqstring = r'(\b[rRuU])?"[^"\\\n]*(\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) return "|".join([kw, string, number, links, comment, any("SYNC", [r"\n"])]) class YamlSH(GenericSH): """yaml Syntax Highlighter""" # Sy...
144
144
482
7
136
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
BaseWebSH
BaseWebSH
1,015
1,072
1,015
1,015
f4cf602a45840a5fb91709d4a60d78270b5c2405
bigcode/the-stack
train
6886a152e6833775ed1c21c0
train
class
class YamlSH(GenericSH): """yaml Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_yaml_patterns(), re.S)
class YamlSH(GenericSH):
"""yaml Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_yaml_patterns(), re.S)
"\\\n]*(\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) return "|".join([kw, string, number, links, comment, any("SYNC", [r"\n"])]) class YamlSH(GenericSH):
64
64
33
7
57
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
YamlSH
YamlSH
1,006
1,009
1,006
1,006
4fb008920039619762d684a4b27282a6a2a0c716
bigcode/the-stack
train
82a0c45b752d17aa88de936c
train
class
class DiffSH(BaseSH): """Simple Diff/Patch Syntax Highlighter Class""" def highlight_block(self, text): """Implement highlight specific Diff/Patch files.""" text = to_text_string(text) if text.startswith("+++"): self.setFormat(0, qstring_length(text), self.formats["keyw...
class DiffSH(BaseSH):
"""Simple Diff/Patch Syntax Highlighter Class""" def highlight_block(self, text): """Implement highlight specific Diff/Patch files.""" text = to_text_string(text) if text.startswith("+++"): self.setFormat(0, qstring_length(text), self.formats["keyword"]) elif te...
, builtin, any("SYNC", [r"\n"])]) class IdlSH(GenericSH): """IDL Syntax Highlighter""" PROG = re.compile(make_idl_patterns(), re.S|re.I) #============================================================================== # Diff/Patch highlighter #===================================...
64
64
178
6
57
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
DiffSH
DiffSH
923
939
923
923
f0c9d6d4db63a69f503f672ca54340400e8a7723
bigcode/the-stack
train
0a26bdd9a0187278b99252e1
train
function
def get_code_cell_name(text): """Returns a code cell name from a code cell comment.""" name = text.strip().lstrip("#% ") if name.startswith("<codecell>"): name = name[10:].lstrip() elif name.startswith("In["): name = name[2:] if name.endswith("]:"): name = nam...
def get_code_cell_name(text):
"""Returns a code cell name from a code cell comment.""" name = text.strip().lstrip("#% ") if name.startswith("<codecell>"): name = name[10:].lstrip() elif name.startswith("In["): name = name[2:] if name.endswith("]:"): name = name[:-1] name = name.str...
string]) return "|".join([instance, kw, builtin, comment, ufstring1, ufstring2, ufstring3, ufstring4, ufstring5, ufstring6, string, number, any("SYNC", [r"\n"])]) def get_code_cell_name(text):
63
64
91
7
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
get_code_cell_name
get_code_cell_name
473
483
473
473
15b81eeddf7a54dc59357ca5a0604398c33d517e
bigcode/the-stack
train
1d9aab97523f0b7ebf55ca61
train
class
class CppSH(BaseSH): """C/C++ Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_cpp_patterns(), re.S) # Syntax highlighting states (from one text block to another): NORMAL = 0 INSIDE_COMMENT = 1 def __init__(self, parent, font=None, color_scheme=None): ...
class CppSH(BaseSH):
"""C/C++ Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_cpp_patterns(), re.S) # Syntax highlighting states (from one text block to another): NORMAL = 0 INSIDE_COMMENT = 1 def __init__(self, parent, font=None, color_scheme=None): BaseSH.__init__(self,...
\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) if define is None: define = any("define", [r"#[^\n]*"]) return "|".join([instance, kw, comment, string, number, comment_start, comment_end, builtin, define, any("SYNC", [r"\n"])]) def ma...
119
119
399
7
112
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
CppSH
CppSH
753
799
753
753
8075126f3ecaf05d8dc610c7379373ab04b8d8f4
bigcode/the-stack
train
f0b5da096378c89cb919cfbb
train
class
class FortranSH(BaseSH): """Fortran Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_fortran_patterns(), re.S|re.I) IDPROG = re.compile(r"\s+(\w+)", re.S) # Syntax highlighting states (from one text block to another): NORMAL = 0 def __init__(self, parent, font...
class FortranSH(BaseSH):
"""Fortran Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_fortran_patterns(), re.S|re.I) IDPROG = re.compile(r"\s+(\w+)", re.S) # Syntax highlighting states (from one text block to another): NORMAL = 0 def __init__(self, parent, font=None, color_scheme=None):...
\n]*(\\.[^'\\\n]*)*'?" dqstring = r'(\b[rRuU])?"[^"\\\n]*(\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) return "|".join([kw, comment, string, number, builtin, any("SYNC", [r"\n"])]) class FortranSH(BaseSH):
91
92
308
7
84
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
FortranSH
FortranSH
841
873
841
841
90571861d80099d7f155bf2384c52471e44605c7
bigcode/the-stack
train
b8b1bf150f8e5cb9977e9040
train
class
class NsisSH(CppSH): """NSIS Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_nsis_patterns(), re.S)
class NsisSH(CppSH):
"""NSIS Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_nsis_patterns(), re.S)
r"\#[^\n]*", r"\/\*(.*?)\*\/"]) return make_generic_c_patterns(kwstr1+' '+kwstr2+' '+kwstr3, bistr, instance=instance, define=define, comment=comment) class NsisSH(CppSH):
64
64
36
8
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
NsisSH
NsisSH
957
960
957
957
5ae452351f8d27605194282c1addb8f3f41e6d15
bigcode/the-stack
train
4614fad58c7e4ed050a07976
train
class
class PygmentsSH(BaseSH): """Generic Pygments syntax highlighter.""" # Store the language name and a ref to the lexer _lang_name = None _lexer = None # Syntax highlighting states (from one text block to another): NORMAL = 0 def __init__(self, parent, font=None, color_scheme=None): ...
class PygmentsSH(BaseSH):
"""Generic Pygments syntax highlighter.""" # Store the language name and a ref to the lexer _lang_name = None _lexer = None # Syntax highlighting states (from one text block to another): NORMAL = 0 def __init__(self, parent, font=None, color_scheme=None): # Map Pygments toke...
QTextCharFormat(self.formats['normal']) font.setFontStrikeOut(True) self.formats['strikethrough'] = font font = QTextCharFormat(self.formats['string']) font.setUnderlineStyle(True) self.formats['link'] = font self.formats['code'] = self.formats['string'] ...
249
249
832
8
241
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
PygmentsSH
PygmentsSH
1,230
1,336
1,230
1,230
3523e53ea042948058e5440d2d46ccbb7b95475a
bigcode/the-stack
train
92d073928a0941a5dde127b9
train
function
def make_generic_c_patterns(keywords, builtins, instance=None, define=None, comment=None): "Strongly inspired from idlelib.ColorDelegator.make_pat" kw = r"\b" + any("keyword", keywords.split()) + r"\b" builtin = r"\b" + any("builtin", builtins.split()+C_TYPES.split()) + r"\b"...
def make_generic_c_patterns(keywords, builtins, instance=None, define=None, comment=None):
"Strongly inspired from idlelib.ColorDelegator.make_pat" kw = r"\b" + any("keyword", keywords.split()) + r"\b" builtin = r"\b" + any("builtin", builtins.split()+C_TYPES.split()) + r"\b" if comment is None: comment = any("comment", [r"//[^\n]*", r"\/\*(.*?)\*\/"]) comment_start = any("co...
latexonly endlink endverbatim enum example exception f$ file fn hideinitializer htmlinclude htmlonly if image include ingroup internal invariant interface latexonly li line link mainpage name namespace nosubgrouping note overload p page par param post pre ref relates remarks return retval sa section see showinitializer...
117
117
392
21
96
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_generic_c_patterns
make_generic_c_patterns
726
748
726
727
959e78c17537b219c01a06849b7c6ad97946c697
bigcode/the-stack
train
52d84c5b5314a530065eb646
train
function
def make_md_patterns(): h1 = '^#[^#]+' h2 = '^##[^#]+' h3 = '^###[^#]+' h4 = '^####[^#]+' h5 = '^#####[^#]+' h6 = '^######[^#]+' titles = any('title', [h1, h2, h3, h4, h5, h6]) html_tags = any("builtin", [r"<", r"[\?/]?>", r"(?<=<).*?(?=[ >])"]) html_symbols = '&[^; ].+;...
def make_md_patterns():
h1 = '^#[^#]+' h2 = '^##[^#]+' h3 = '^###[^#]+' h4 = '^####[^#]+' h5 = '^#####[^#]+' h6 = '^######[^#]+' titles = any('title', [h1, h2, h3, h4, h5, h6]) html_tags = any("builtin", [r"<", r"[\?/]?>", r"(?<=<).*?(?=[ >])"]) html_symbols = '&[^; ].+;' html_comment = '<!...
keywords = any("keyword", [r" [\w:-]*?(?==)"]) string = any("string", [r'".*?"']) comment = any("comment", [r"<!--.*?-->"]) multiline_comment_start = any("multiline_comment_start", [r"<!--"]) multiline_comment_end = any("multiline_comment_end", [r"-->"]) return "|".join([comment, multiline_com...
152
152
508
5
146
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_md_patterns
make_md_patterns
1,093
1,137
1,093
1,093
7b1786d11f8750fc9f71ef6ee7f08cfed8ad440c
bigcode/the-stack
train
21b594b6a27ebbac21f8464d
train
function
def any(name, alternates): "Return a named group pattern matching list of alternates." return "(?P<%s>" % name + "|".join(alternates) + ")"
def any(name, alternates):
"Return a named group pattern matching list of alternates." return "(?P<%s>" % name + "|".join(alternates) + ")"
= name.lower() scheme = {} for key in COLOR_SCHEME_KEYS: try: scheme[key] = CONF.get('appearance', name+'/'+key) except: scheme[key] = CONF.get('appearance', 'spyder/'+key) return scheme def any(name, alternates):
64
64
42
7
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
any
any
127
129
127
127
a4cada7d554ddd82b74c1077387c0e6dfc1dfdaf
bigcode/the-stack
train
7950d0cf313a094a0e2d1e69
train
class
class HtmlSH(BaseWebSH): """HTML Syntax Highlighter""" PROG = re.compile(make_html_patterns(), re.S)
class HtmlSH(BaseWebSH):
"""HTML Syntax Highlighter""" PROG = re.compile(make_html_patterns(), re.S)
_comment_start = any("multiline_comment_start", [r"<!--"]) multiline_comment_end = any("multiline_comment_end", [r"-->"]) return "|".join([comment, multiline_comment_start, multiline_comment_end, tags, keywords, string]) class HtmlSH(BaseWebSH):
64
64
27
7
57
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
HtmlSH
HtmlSH
1,085
1,087
1,085
1,085
a40da1ab919de03ea5c1024296f79c64f5d8af22
bigcode/the-stack
train
2f761f3d2edb5e63bdeed873
train
function
def make_opencl_patterns(): # Keywords: kwstr1 = 'cl_char cl_uchar cl_short cl_ushort cl_int cl_uint cl_long cl_ulong cl_half cl_float cl_double cl_platform_id cl_device_id cl_context cl_command_queue cl_mem cl_program cl_kernel cl_event cl_sampler cl_bool cl_bitfield cl_device_type cl_platform_info cl_device...
def make_opencl_patterns(): # Keywords:
kwstr1 = 'cl_char cl_uchar cl_short cl_ushort cl_int cl_uint cl_long cl_ulong cl_half cl_float cl_double cl_platform_id cl_device_id cl_context cl_command_queue cl_mem cl_program cl_kernel cl_event cl_sampler cl_bool cl_bitfield cl_device_type cl_platform_info cl_device_info cl_device_address_info cl_device_fp_conf...
self.formats["comment" if inside_comment else "normal"]) match = self.PROG.search(text) index = 0 while match: for key, value in list(match.groupdict().items()): if value: start, end = get_span(match, key) ...
256
256
2,154
10
246
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_opencl_patterns
make_opencl_patterns
802
813
802
803
79a104b4125ee45bd296a656f424577c9c146c83
bigcode/the-stack
train
ea5303812d1fec0f1f17a982
train
class
class Fortran77SH(FortranSH): """Fortran 77 Syntax Highlighter""" def highlight_block(self, text): """Implement highlight specific for Fortran77.""" text = to_text_string(text) if text.startswith(("c", "C")): self.setFormat(0, qstring_length(text), self.formats["comment...
class Fortran77SH(FortranSH):
"""Fortran 77 Syntax Highlighter""" def highlight_block(self, text): """Implement highlight specific for Fortran77.""" text = to_text_string(text) if text.startswith(("c", "C")): self.setFormat(0, qstring_length(text), self.formats["comment"]) self.highlight...
start1, end1 = get_span(match1, 1) self.setFormat(start1, end1-start1, self.formats["definition"]) match = self.PROG.search(text, match.end()) self.highlight_extras(text) class Fortran77SH(FortranSH):
64
64
139
10
54
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
Fortran77SH
Fortran77SH
875
887
875
875
5ec9ceb74335a5477f88ecb0a9d66eee35aacd7b
bigcode/the-stack
train
d6fb2328db07c696ab883270
train
class
class CythonSH(PythonSH): """Cython Syntax Highlighter""" ADDITIONAL_KEYWORDS = [ "cdef", "ctypedef", "cpdef", "inline", "cimport", "extern", "include", "begin", "end", "by", "gil", "nogil", "const", "public", "readonly", "fused", "static", "api", "DEF", "IF", "ELIF", "ELSE"] ...
class CythonSH(PythonSH):
"""Cython Syntax Highlighter""" ADDITIONAL_KEYWORDS = [ "cdef", "ctypedef", "cpdef", "inline", "cimport", "extern", "include", "begin", "end", "by", "gil", "nogil", "const", "public", "readonly", "fused", "static", "api", "DEF", "IF", "ELIF", "ELSE"] ADDITIONAL_BUILTINS = C_TY...
block = block.next() return statments def rehighlight(self): BaseSH.rehighlight(self) #============================================================================== # Cython syntax highlighter #============================================================================== C...
64
64
189
8
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
CythonSH
CythonSH
692
703
692
692
334d9149bcffd1905227b1bb6e3c85946c65de75
bigcode/the-stack
train
60e53d9656c2ab9e756990ab
train
function
def get_color_scheme(name): """Get a color scheme from config using its name""" name = name.lower() scheme = {} for key in COLOR_SCHEME_KEYS: try: scheme[key] = CONF.get('appearance', name+'/'+key) except: scheme[key] = CONF.get('appearance', 'spyder/'+key...
def get_color_scheme(name):
"""Get a color scheme from config using its name""" name = name.lower() scheme = {} for key in COLOR_SCHEME_KEYS: try: scheme[key] = CONF.get('appearance', name+'/'+key) except: scheme[key] = CONF.get('appearance', 'spyder/'+key) return scheme
key=None): if key is not None: start, end = match.span(key) else: start, end = match.span() start = qstring_length(match.string[:start]) end = qstring_length(match.string[:end]) return start, end def get_color_scheme(name):
64
64
77
6
57
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
get_color_scheme
get_color_scheme
115
124
115
115
aa35812aaea3131279889a7f070860f5b941f92c
bigcode/the-stack
train
8da66116fa25cda17de6fdd1
train
class
class IdlSH(GenericSH): """IDL Syntax Highlighter""" PROG = re.compile(make_idl_patterns(), re.S|re.I)
class IdlSH(GenericSH):
"""IDL Syntax Highlighter""" PROG = re.compile(make_idl_patterns(), re.S|re.I)
"\\\n]*(\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) return "|".join([kw, comment, string, number, builtin, any("SYNC", [r"\n"])]) class IdlSH(GenericSH):
64
64
31
7
57
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
IdlSH
IdlSH
915
917
915
915
00e3654fc518e8eb0369700d7eb2d3182023cca7
bigcode/the-stack
train
4c563bca1ca50681c1d4d776
train
function
def get_span(match, key=None): if key is not None: start, end = match.span(key) else: start, end = match.span() start = qstring_length(match.string[:start]) end = qstring_length(match.string[:end]) return start, end
def get_span(match, key=None):
if key is not None: start, end = match.span(key) else: start, end = match.span() start = qstring_length(match.string[:start]) end = qstring_length(match.string[:end]) return start, end
custom_extension_lexer_mapping[key] = value # Tuple of keys is iterated over and each is mapped to value. else: for k in key: custom_extension_lexer_mapping[k] = value #============================================================================== # Auxiliary functions #=========...
64
64
63
8
55
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
get_span
get_span
105
112
105
105
fca06891b09e63714e9679fed3547ee76738139e
bigcode/the-stack
train
67ea9883b639aa99ca87c5f3
train
function
def make_fortran_patterns(): "Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr = 'access action advance allocatable allocate apostrophe assign assignment associate asynchronous backspace bind blank blockdata call case character class close common complex contains continue cycle data deallocate de...
def make_fortran_patterns():
"Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr = 'access action advance allocatable allocate apostrophe assign assignment associate asynchronous backspace bind blank blockdata call case character class close common complex contains continue cycle data deallocate decimal delim default dimension ...
clGetEventInfo, clRetainEvent, clReleaseEvent, clGetEventProfilingInfo, clFlush, clFinish, clEnqueueReadBuffer, clEnqueueWriteBuffer, clEnqueueCopyBuffer, clEnqueueReadImage, clEnqueueWriteImage, clEnqueueCopyImage, clEnqueueCopyImageToBuffer, clEnqueueCopyBufferToImage, clEnqueueMapBuffer, clEnqueueMapImage, clEnqueu...
256
256
1,306
6
249
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_fortran_patterns
make_fortran_patterns
823
839
823
823
7ab534112812704d4a1592aafebbb56919cf1d44
bigcode/the-stack
train
9bad8df02793626b416bef4b
train
function
def make_nsis_patterns(): "Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr1 = 'Abort AddBrandingImage AddSize AllowRootDirInstall AllowSkipFiles AutoCloseWindow BGFont BGGradient BrandingText BringToFront Call CallInstDLL Caption ClearErrors CompletedText ComponentText CopyFiles CRCCheck CreateD...
def make_nsis_patterns():
"Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr1 = 'Abort AddBrandingImage AddSize AllowRootDirInstall AllowSkipFiles AutoCloseWindow BGFont BGGradient BrandingText BringToFront Call CallInstDLL Caption ClearErrors CompletedText ComponentText CopyFiles CRCCheck CreateDirectory CreateFont CreateS...
, number, builtin, any("SYNC", [r"\n"])]) class IdlSH(GenericSH): """IDL Syntax Highlighter""" PROG = re.compile(make_idl_patterns(), re.S|re.I) #============================================================================== # Diff/Patch highlighter #===========================...
256
256
2,068
6
249
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_nsis_patterns
make_nsis_patterns
944
955
944
944
d84981154891637dd8906ecebeda7a388d5be0bf
bigcode/the-stack
train
1c1c197fdf49f9ea56b2e98a
train
class
class TextSH(BaseSH): """Simple Text Syntax Highlighter Class (only highlight spaces).""" def highlight_block(self, text): """Implement highlight, only highlight spaces.""" text = to_text_string(text) self.setFormat(0, qstring_length(text), self.formats["normal"]) self.hi...
class TextSH(BaseSH):
"""Simple Text Syntax Highlighter Class (only highlight spaces).""" def highlight_block(self, text): """Implement highlight, only highlight spaces.""" text = to_text_string(text) self.setFormat(0, qstring_length(text), self.formats["normal"]) self.highlight_extras(text)
highlight_block(). """ self.highlight_spaces(text, offset=offset) self.highlight_patterns(text, offset=offset) def rehighlight(self): QApplication.setOverrideCursor(QCursor(Qt.WaitCursor)) QSyntaxHighlighter.rehighlight(self) QApplication.restoreOverrideCurs...
64
64
72
6
58
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
TextSH
TextSH
369
376
369
369
8a5fef7fb0d9530d0e9000cfb3ff44c7e495fe3a
bigcode/the-stack
train
20637203f3f219a1a50308ff
train
class
class MarkdownSH(BaseSH): """Markdown Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_md_patterns(), re.S) NORMAL = 0 CODE = 1 def highlightBlock(self, text): text = to_text_string(text) previous_state = self.previousBlockState() if ...
class MarkdownSH(BaseSH):
"""Markdown Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_md_patterns(), re.S) NORMAL = 0 CODE = 1 def highlightBlock(self, text): text = to_text_string(text) previous_state = self.previousBlockState() if previous_state == self.CODE...
r'|(^(?: |\t)*[0-9]+\. )' r'|(^(?: |\t)*- )' r'|(^(?: |\t)*\* )') # code code = any('code', ['^`{3,}.*$']) inline_code = any('inline_code', ['`[^`]*`']) # math - $$ math = any('number', [r'^(?:\${2}).*$', html_symbols]) comment = any('c...
161
162
543
6
155
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
MarkdownSH
MarkdownSH
1,140
1,215
1,140
1,140
8a5dde16ab3c5d2bebde49ff1bbb18232658bd17
bigcode/the-stack
train
3ec64f7a784d4ba0083cdcfc
train
function
def guess_pygments_highlighter(filename): """ Factory to generate syntax highlighter for the given filename. If a syntax highlighter is not available for a particular file, this function will attempt to generate one based on the lexers in Pygments. If Pygments is not available or does not hav...
def guess_pygments_highlighter(filename):
""" Factory to generate syntax highlighter for the given filename. If a syntax highlighter is not available for a particular file, this function will attempt to generate one based on the lexers in Pygments. If Pygments is not available or does not have an appropriate lexer, TextSH will be...
.+)', bygroups(Generic.Error, Name.Constant), '#pop'), (r'(\sTRACE)(\s.+)', bygroups(Generic.Error, Name.Constant), '#pop'), (r'(\s\w+)(\s.+)', bygroups(Comment, Generic.Output), '#pop'), ], } def guess_pygments_highlighter(filename):
80
80
268
9
71
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
guess_pygments_highlighter
guess_pygments_highlighter
1,378
1,413
1,378
1,378
5318eb5d0db8a7090e79399d99e4dc045f263104
bigcode/the-stack
train
4346344af7da85d451fa18c6
train
function
def make_python_patterns(additional_keywords=[], additional_builtins=[]): "Strongly inspired from idlelib.ColorDelegator.make_pat" kwlist = keyword.kwlist + additional_keywords builtinlist = [str(name) for name in dir(builtins) if not name.startswith('_')] + additional_builtins r...
def make_python_patterns(additional_keywords=[], additional_builtins=[]):
"Strongly inspired from idlelib.ColorDelegator.make_pat" kwlist = keyword.kwlist + additional_keywords builtinlist = [str(name) for name in dir(builtins) if not name.startswith('_')] + additional_builtins repeated = set(kwlist) & set(builtinlist) for repeated_element in repea...
Highlighter Class (only highlight spaces).""" def highlight_block(self, text): """Implement highlight, only highlight spaces.""" text = to_text_string(text) self.setFormat(0, qstring_length(text), self.formats["normal"]) self.highlight_extras(text) class GenericSH(BaseSH...
256
256
1,402
14
241
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_python_patterns
make_python_patterns
406
470
406
406
b2ea059ea45a0174df117f010712afaca63a1f08
bigcode/the-stack
train
c2cc8ee12b71da9f2093dc68
train
class
class EnamlSH(PythonSH): """Enaml Syntax Highlighter""" ADDITIONAL_KEYWORDS = ["enamldef", "template", "attr", "event", "const", "alias", "func"] ADDITIONAL_BUILTINS = [] PROG = re.compile(make_python_patterns(ADDITIONAL_KEYWORDS, ...
class EnamlSH(PythonSH):
"""Enaml Syntax Highlighter""" ADDITIONAL_KEYWORDS = ["enamldef", "template", "attr", "event", "const", "alias", "func"] ADDITIONAL_BUILTINS = [] PROG = re.compile(make_python_patterns(ADDITIONAL_KEYWORDS, ADDITIONAL_BUILTINS), r...
= re.compile(make_python_patterns(ADDITIONAL_KEYWORDS, ADDITIONAL_BUILTINS), re.S) IDPROG = re.compile(r"\s+([\w\.]+)", re.S) #============================================================================== # Enaml syntax highlighter #=============================...
64
64
103
8
55
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
EnamlSH
EnamlSH
709
716
709
709
bf394f1543d702124d78b3370d34395128777c64
bigcode/the-stack
train
841f170cbb5bb7f1454f65af
train
function
def make_cpp_patterns(): return make_generic_c_patterns(C_KEYWORDS1+' '+C_KEYWORDS2, C_KEYWORDS3)
def make_cpp_patterns():
return make_generic_c_patterns(C_KEYWORDS1+' '+C_KEYWORDS2, C_KEYWORDS3)
if define is None: define = any("define", [r"#[^\n]*"]) return "|".join([instance, kw, comment, string, number, comment_start, comment_end, builtin, define, any("SYNC", [r"\n"])]) def make_cpp_patterns():
64
64
27
5
59
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_cpp_patterns
make_cpp_patterns
750
751
750
750
fd0135a60a4a4873bdc6522e35fc02cca8b78c15
bigcode/the-stack
train
8b2a13825f7489dbace66b05
train
class
class OpenCLSH(CppSH): """OpenCL Syntax Highlighter""" PROG = re.compile(make_opencl_patterns(), re.S)
class OpenCLSH(CppSH):
"""OpenCL Syntax Highlighter""" PROG = re.compile(make_opencl_patterns(), re.S)
kernel' keyword_list = C_KEYWORDS1+' '+C_KEYWORDS2+' '+kwstr1+' '+kwstr2 builtin_list = C_KEYWORDS3+' '+builtins+' '+qualifiers return make_generic_c_patterns(keyword_list, builtin_list) class OpenCLSH(CppSH):
64
64
30
8
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
OpenCLSH
OpenCLSH
815
817
815
815
144649bde3a206d732267eb9566b9b72f248641a
bigcode/the-stack
train
63743306335ac33496f0db05
train
class
class GenericSH(BaseSH): """Generic Syntax Highlighter""" # Syntax highlighting rules: PROG = None # to be redefined in child classes def highlight_block(self, text): """Implement highlight using regex defined in children classes.""" text = to_text_string(text) self.set...
class GenericSH(BaseSH):
"""Generic Syntax Highlighter""" # Syntax highlighting rules: PROG = None # to be redefined in child classes def highlight_block(self, text): """Implement highlight using regex defined in children classes.""" text = to_text_string(text) self.setFormat(0, qstring_length(t...
(only highlight spaces).""" def highlight_block(self, text): """Implement highlight, only highlight spaces.""" text = to_text_string(text) self.setFormat(0, qstring_length(text), self.formats["normal"]) self.highlight_extras(text) class GenericSH(BaseSH):
64
64
169
6
58
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
GenericSH
GenericSH
379
400
379
379
284140110fa5bdc6bb2a9caa44a0c79519ad4600
bigcode/the-stack
train
c68105a841ec577f46bbaa24
train
function
def make_html_patterns(): """Strongly inspired from idlelib.ColorDelegator.make_pat """ tags = any("builtin", [r"<", r"[\?/]?>", r"(?<=<).*?(?=[ >])"]) keywords = any("keyword", [r" [\w:-]*?(?==)"]) string = any("string", [r'".*?"']) comment = any("comment", [r"<!--.*?-->"]) multiline_comm...
def make_html_patterns():
"""Strongly inspired from idlelib.ColorDelegator.make_pat """ tags = any("builtin", [r"<", r"[\?/]?>", r"(?<=<).*?(?=[ >])"]) keywords = any("keyword", [r" [\w:-]*?(?==)"]) string = any("string", [r'".*?"']) comment = any("comment", [r"<!--.*?-->"]) multiline_comment_start = any("multiline_...
[key]) except KeyError: # Happens with unmatched end-of-comment. # See spyder-ide/spyder#1462. pass match = self.PROG.search(text, match.end()) match_count += 1 ...
64
64
160
5
59
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_html_patterns
make_html_patterns
1,074
1,083
1,074
1,074
a851d5ba021f91e6bd9feae383269ed5e1a7d037
bigcode/the-stack
train
be3f779da768f7e3c9f39001
train
class
class BaseSH(QSyntaxHighlighter): """Base Syntax Highlighter Class""" # Syntax highlighting rules: PROG = None BLANKPROG = re.compile(r"\s+") # Syntax highlighting states (from one text block to another): NORMAL = 0 # Syntax highlighting parameters. BLANK_ALPHA_FACTOR = 0.31 ...
class BaseSH(QSyntaxHighlighter):
"""Base Syntax Highlighter Class""" # Syntax highlighting rules: PROG = None BLANKPROG = re.compile(r"\s+") # Syntax highlighting states (from one text block to another): NORMAL = 0 # Syntax highlighting parameters. BLANK_ALPHA_FACTOR = 0.31 sig_outline_explorer_data_change...
color scheme from config using its name""" name = name.lower() scheme = {} for key in COLOR_SCHEME_KEYS: try: scheme[key] = CONF.get('appearance', name+'/'+key) except: scheme[key] = CONF.get('appearance', 'spyder/'+key) return scheme def any(name, a...
256
256
1,600
8
247
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
BaseSH
BaseSH
159
366
159
159
44ceffe1b642a38650008c5b92fd02c05e9e3659
bigcode/the-stack
train
24f9ccf9509792c2502b365a
train
class
class PythonLoggingLexer(RegexLexer): """ A lexer for logs generated by the Python builtin 'logging' library. Taken from https://bitbucket.org/birkenfeld/pygments-main/pull-requests/451/add-python-logging-lexer """ name = 'Python Logging' aliases = ['pylog', 'pythonlogging'] ...
class PythonLoggingLexer(RegexLexer):
""" A lexer for logs generated by the Python builtin 'logging' library. Taken from https://bitbucket.org/birkenfeld/pygments-main/pull-requests/451/add-python-logging-lexer """ name = 'Python Logging' aliases = ['pylog', 'pythonlogging'] filenames = ['*.log'] tokens = { ...
(self, text): """ Actually highlight the block""" # Note that an undefined blockstate is equal to -1, so the first block # will have the correct behaviour of starting at 0. if self._allow_highlight: start = self.previousBlockState() + 1 end = start + qstring...
126
126
423
8
118
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
PythonLoggingLexer
PythonLoggingLexer
1,339
1,375
1,339
1,339
f5b03ffe9f71ae00891fac6c1816677ae229ad49
bigcode/the-stack
train
23ae14bf2dac64f02385c549
train
class
class GetTextSH(GenericSH): """gettext Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_gettext_patterns(), re.S)
class GetTextSH(GenericSH):
"""gettext Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_gettext_patterns(), re.S)
\n]*(\\.[^"\\\n]*)*"?' string = any("string", [sqstring, dqstring]) return "|".join([kw, string, number, fuzzy, links, comment, any("SYNC", [r"\n"])]) class GetTextSH(GenericSH):
63
64
34
7
56
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
GetTextSH
GetTextSH
983
986
983
983
f457d7455c83c6a30912b7158ea09fcf3698891b
bigcode/the-stack
train
5b502cb2d0d4b95637aabccd
train
function
def make_idl_patterns(): """Strongly inspired by idlelib.ColorDelegator.make_pat.""" kwstr = 'begin of pro function endfor endif endwhile endrep endcase endswitch end if then else for do while repeat until break case switch common continue exit return goto help message print read retall stop' bistr1 = 'a...
def make_idl_patterns():
"""Strongly inspired by idlelib.ColorDelegator.make_pat.""" kwstr = 'begin of pro function endfor endif endwhile endrep endcase endswitch end if then else for do while repeat until break case switch common continue exit return goto help message print read retall stop' bistr1 = 'a_correlate abs acos adapt_...
G.match(text, end) if match1: start1, end1 = get_span(match1, 1) self.setFormat(start1, end1-start1, self.formats["definition"]) match = self.PROG.search(text, match.end()) ...
256
256
2,004
6
249
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_idl_patterns
make_idl_patterns
896
913
896
896
21b3f5948d78af14f29b37df319df4ea6579f59a
bigcode/the-stack
train
bcaab8e9aad6c74f15e4443b
train
function
def create_patterns(patterns, compile=False): """ Create patterns from pattern dictionary. The key correspond to the group name and the values a list of possible pattern alternatives. """ all_patterns = [] for key, value in patterns.items(): all_patterns.append(any(key, [va...
def create_patterns(patterns, compile=False):
""" Create patterns from pattern dictionary. The key correspond to the group name and the values a list of possible pattern alternatives. """ all_patterns = [] for key, value in patterns.items(): all_patterns.append(any(key, [value])) regex = '|'.join(all_patterns) ...
('appearance', 'spyder/'+key) return scheme def any(name, alternates): "Return a named group pattern matching list of alternates." return "(?P<%s>" % name + "|".join(alternates) + ")" def create_patterns(patterns, compile=False):
64
64
89
9
54
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
create_patterns
create_patterns
132
148
132
132
0b94c0d0e6439a4492ddff3aee7f642ac2c6cdf2
bigcode/the-stack
train
41fec9caf9a8983c9e30378d
train
function
def make_gettext_patterns(): "Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr = 'msgid msgstr' kw = r"\b" + any("keyword", kwstr.split()) + r"\b" fuzzy = any("builtin", [r"#,[^\n]*"]) links = any("normal", [r"#:[^\n]*"]) comment = any("comment", [r"#[^\n]*"]) number = an...
def make_gettext_patterns():
"Strongly inspired from idlelib.ColorDelegator.make_pat" kwstr = 'msgid msgstr' kw = r"\b" + any("keyword", kwstr.split()) + r"\b" fuzzy = any("builtin", [r"#,[^\n]*"]) links = any("normal", [r"#:[^\n]*"]) comment = any("comment", [r"#[^\n]*"]) number = any("number", ...
_c_patterns(kwstr1+' '+kwstr2+' '+kwstr3, bistr, instance=instance, define=define, comment=comment) class NsisSH(CppSH): """NSIS Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_nsis_patterns(), re.S) ...
87
87
293
6
80
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_gettext_patterns
make_gettext_patterns
966
981
966
966
aa4176de0ff0f96136511adc7e9b4b4046b51850
bigcode/the-stack
train
f65b5717d6dcdaf6369c59ee
train
function
def make_yaml_patterns(): "Strongly inspired from sublime highlighter " kw = any("keyword", [r":|>|-|\||\[|\]|[A-Za-z][\w\s\-\_ ]+(?=:)"]) links = any("normal", [r"#:[^\n]*"]) comment = any("comment", [r"#[^\n]*"]) number = any("number", [r"\b[+-]?[0-9]+[lL]?\b", ...
def make_yaml_patterns():
"Strongly inspired from sublime highlighter " kw = any("keyword", [r":|>|-|\||\[|\]|[A-Za-z][\w\s\-\_ ]+(?=:)"]) links = any("normal", [r"#:[^\n]*"]) comment = any("comment", [r"#[^\n]*"]) number = any("number", [r"\b[+-]?[0-9]+[lL]?\b", r"\b[+-]?0[xX][0-9A-F...
dqstring]) return "|".join([kw, string, number, fuzzy, links, comment, any("SYNC", [r"\n"])]) class GetTextSH(GenericSH): """gettext Syntax Highlighter""" # Syntax highlighting rules: PROG = re.compile(make_gettext_patterns(), re.S) #=====================================...
82
82
275
5
76
TediaN97/spyder
spyder/utils/syntaxhighlighters.py
Python
make_yaml_patterns
make_yaml_patterns
991
1,004
991
991
48c2585374cd11ae48662ef888809e0d96110532
bigcode/the-stack
train
7a32edc85b22d7742b0fb049
train
function
def image_data_augmentation(x_train): print('Using real-time data augmentation.') # This will do preprocessing and realtime data augmentation: datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, # set each sample mean to ...
def image_data_augmentation(x_train):
print('Using real-time data augmentation.') # This will do preprocessing and realtime data augmentation: datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, # set each sample mean to 0 featurewise_std_normalizatio...
= y_train[indexTrain[0:noTrainingSamples], :] x_test = x_test[indexTest[0:noTestingSamples], :] y_test = y_test[indexTest[0:noTestingSamples], :] # normalize data xTrainMean = np.mean(x_train, axis=0) xTtrainStd = np.std(x_train, axis=0) x_train = (x_train - xTrainMean) / xTtrainStd x_test...
135
135
450
8
126
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
image_data_augmentation
image_data_augmentation
619
658
619
619
22dea84f384c3214151e7ad0d1f6a40bb1b59ced
bigcode/the-stack
train
e8f23e163e9b1c8d20a40e39
train
class
class NoActivation: """ This is a plugin function for no activation. f(x) = x * 1 """ @staticmethod def activation(z): """ :param z: (array) w(x) + b :return: z (array) """ return z @staticmethod def prime(z): """ The prime of z ...
class NoActivation:
""" This is a plugin function for no activation. f(x) = x * 1 """ @staticmethod def activation(z): """ :param z: (array) w(x) + b :return: z (array) """ return z @staticmethod def prime(z): """ The prime of z * 1 = 1 :par...
, y_pred): return y_pred - y_true def delta(self, y_true, y_pred): """ Back propagation error delta :return: (array) """ return self.prime(y_true, y_pred) * self.activation_fn.prime(y_pred) class NoActivation:
64
64
116
4
60
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
NoActivation
NoActivation
145
167
145
145
789d8adee74c5bc1db335876c67372e07bdbfee8
bigcode/the-stack
train
ea7e56022edb5923a3db4c94
train
class
class Sigmoid: @staticmethod def activation(z): return 1 / (1 + np.exp(-z)) @staticmethod def prime(z): return Sigmoid.activation(z) * (1 - Sigmoid.activation(z))
class Sigmoid: @staticmethod
def activation(z): return 1 / (1 + np.exp(-z)) @staticmethod def prime(z): return Sigmoid.activation(z) * (1 - Sigmoid.activation(z))
def activation(z): z[z < 0] = 0 return z @staticmethod def prime(z): z[z < 0] = 0 z[z > 0] = 1 return z class Sigmoid: @staticmethod
64
64
51
8
55
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
Sigmoid
Sigmoid
101
108
101
102
0f5612bbac63fb7acf3e524acdee72e465e07910
bigcode/the-stack
train
805d069d9ac3d60d39c63769
train
function
def createSparseWeights(epsilon, noRows, noCols): # generate an Erdos Renyi sparse weights mask weights = lil_matrix((noRows, noCols)) for i in range(epsilon * (noRows + noCols)): weights[np.random.randint(0, noRows), np.random.randint(0, noCols)] = np.float64(np.random.randn() * np.sqrt(2 / (noRows...
def createSparseWeights(epsilon, noRows, noCols): # generate an Erdos Renyi sparse weights mask
weights = lil_matrix((noRows, noCols)) for i in range(epsilon * (noRows + noCols)): weights[np.random.randint(0, noRows), np.random.randint(0, noCols)] = np.float64(np.random.randn() * np.sqrt(2 / (noRows + noCols))) print("Create sparse matrix with ", weights.getnnz(), " connections and ", ...
() return idx def find_last_pos(array, value): idx = (np.abs(array - value))[::-1].argmin() return array.shape[0] - idx def createSparseWeights(epsilon, noRows, noCols): # generate an Erdos Renyi sparse weights mask
64
64
145
25
38
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
createSparseWeights
createSparseWeights
70
78
70
71
00bf13094c36dbf8f907e65c94150748e94acfea
bigcode/the-stack
train
ae430f6bb65f9f91a7423aef
train
class
class SET_MLP: def __init__(self, dimensions, activations, epsilon=20): """ :param dimensions: (tpl/ list) Dimensions of the neural net. (input, hidden layer, output) :param activations: (tpl/ list) Activations functions. Example of three hidden layer with - 3312 input featu...
class SET_MLP:
def __init__(self, dimensions, activations, epsilon=20): """ :param dimensions: (tpl/ list) Dimensions of the neural net. (input, hidden layer, output) :param activations: (tpl/ list) Activations functions. Example of three hidden layer with - 3312 input features - 3...
@staticmethod def loss(y_true, y_pred): """ :param y_true: (array) One hot encoded truth vector. :param y_pred: (array) Prediction vector :return: (flt) """ return np.mean((y_pred - y_true) ** 2) @staticmethod def prime(y_true, y_pred): return y_p...
256
256
4,511
5
251
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
SET_MLP
SET_MLP
170
564
170
170
d9b7c1d4f6b8fb503fb93345653f6b22f536ef05
bigcode/the-stack
train
40b751ef342b0993b0d20585
train
function
def find_first_pos(array, value): idx = (np.abs(array - value)).argmin() return idx
def find_first_pos(array, value):
idx = (np.abs(array - value)).argmin() return idx
out): for i in range(out.shape[0]): s = 0 for j in range(a.shape[0]): s += a[j, rows[i]] * delta[j, cols[i]] out[i] = s / a.shape[0] def find_first_pos(array, value):
64
64
25
8
56
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
find_first_pos
find_first_pos
60
62
60
60
cc096e36090d6cc78597ece20e256700aceaeddc
bigcode/the-stack
train
d4c15cabcb722bb5e4886402
train
function
def find_last_pos(array, value): idx = (np.abs(array - value))[::-1].argmin() return array.shape[0] - idx
def find_last_pos(array, value):
idx = (np.abs(array - value))[::-1].argmin() return array.shape[0] - idx
[0]): s += a[j, rows[i]] * delta[j, cols[i]] out[i] = s / a.shape[0] def find_first_pos(array, value): idx = (np.abs(array - value)).argmin() return idx def find_last_pos(array, value):
64
64
34
8
55
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
find_last_pos
find_last_pos
65
67
65
65
8498d10341c72b51e2462ee6225ab2416558c8fe
bigcode/the-stack
train
df303120f42e1c1ff2f3018c
train
function
def load_fashion_mnist_data(noTrainingSamples,noTestingSamples): np.random.seed(0) data=np.load("../Tutorial-IJCAI-2019-Scalable-Deep-Learning/data/fashion_mnist.npz") indexTrain=np.arange(data["X_train"].shape[0]) np.random.shuffle(indexTrain) indexTest=np.arange(data["X_test"].shape[0]) np....
def load_fashion_mnist_data(noTrainingSamples,noTestingSamples):
np.random.seed(0) data=np.load("../Tutorial-IJCAI-2019-Scalable-Deep-Learning/data/fashion_mnist.npz") indexTrain=np.arange(data["X_train"].shape[0]) np.random.shuffle(indexTrain) indexTest=np.arange(data["X_test"].shape[0]) np.random.shuffle(indexTest) X_train=data["X_train"][indexTrain...
range(y_test.shape[0]): if (np.argmax(activations[j]) == np.argmax(y_test[j])): correctClassification += 1 accuracy = correctClassification / y_test.shape[0] return accuracy, activations def load_fashion_mnist_data(noTrainingSamples,noTestingSamples):
64
64
212
14
49
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
load_fashion_mnist_data
load_fashion_mnist_data
566
586
566
566
da13660542654fa0dc9f7192d9b0840005823e75
bigcode/the-stack
train
55e08e5d3da9a49d5d9b3119
train
class
class ReLU: @staticmethod def activation(z): z[z < 0] = 0 return z @staticmethod def prime(z): z[z < 0] = 0 z[z > 0] = 1 return z
class ReLU: @staticmethod
def activation(z): z[z < 0] = 0 return z @staticmethod def prime(z): z[z < 0] = 0 z[z > 0] = 1 return z
rows, ncols = A.shape dtype = {'names': ['f{}'.format(i) for i in range(ncols)], 'formats': ncols * [A.dtype]} return np.in1d(A.view(dtype), B.view(dtype)) # boolean return class ReLU: @staticmethod
64
64
63
8
55
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
ReLU
ReLU
88
98
88
89
ae3ba771b574f6f5d5d0c27aa743cac27edad32d
bigcode/the-stack
train
578e3f7931f19c613e5ed3f1
train
function
def backpropagation_updates_Numpy(a, delta, rows, cols, out): for i in range(out.shape[0]): s = 0 for j in range(a.shape[0]): s += a[j, rows[i]] * delta[j, cols[i]] out[i] = s / a.shape[0]
def backpropagation_updates_Numpy(a, delta, rows, cols, out):
for i in range(out.shape[0]): s = 0 for j in range(a.shape[0]): s += a[j, rows[i]] * delta[j, cols[i]] out[i] = s / a.shape[0]
may encounter some "solvable" issues if you compile it in Windows. import sparseoperations import datetime from keras.datasets import cifar10 from keras.utils import np_utils from keras.preprocessing.image import ImageDataGenerator def backpropagation_updates_Numpy(a, delta, rows, cols, out):
64
64
71
17
46
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
backpropagation_updates_Numpy
backpropagation_updates_Numpy
52
57
52
52
e78296b1abf5dffebf92ca2d733c8400600ef4c6
bigcode/the-stack
train
e11646ccd64294f365c457bc
train
function
def array_intersect(A, B): # this are for array intersection nrows, ncols = A.shape dtype = {'names': ['f{}'.format(i) for i in range(ncols)], 'formats': ncols * [A.dtype]} return np.in1d(A.view(dtype), B.view(dtype)) # boolean return
def array_intersect(A, B): # this are for array intersection
nrows, ncols = A.shape dtype = {'names': ['f{}'.format(i) for i in range(ncols)], 'formats': ncols * [A.dtype]} return np.in1d(A.view(dtype), B.view(dtype)) # boolean return
sparse matrix with ", weights.getnnz(), " connections and ", (weights.getnnz() / (noRows * noCols)) * 100, "% density level") weights = weights.tocsr() return weights def array_intersect(A, B): # this are for array intersection
64
64
74
16
47
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
array_intersect
array_intersect
81
85
81
82
56f33caec5d9646effb2d797eb16c438a6edc38e
bigcode/the-stack
train
6c13a066f2f71db77ab3bdbf
train
function
def load_cifar10_data(noTrainingSamples,noTestingSamples): np.random.seed(0) # read CIFAR10 data (x_train, y_train), (x_test, y_test) = cifar10.load_data() y_train = np_utils.to_categorical(y_train, 10) y_test = np_utils.to_categorical(y_test, 10) x_train = x_train.astype('float32') x_test...
def load_cifar10_data(noTrainingSamples,noTestingSamples):
np.random.seed(0) # read CIFAR10 data (x_train, y_train), (x_test, y_test) = cifar10.load_data() y_train = np_utils.to_categorical(y_train, 10) y_test = np_utils.to_categorical(y_test, 10) x_train = x_train.astype('float32') x_test = x_test.astype('float32') indexTrain = np.arange(x_t...
],:] Y_test=data["Y_test"][indexTest[0:noTestingSamples],:] #normalize in 0..1 X_train = X_train.astype('float64') / 255. X_test = X_test.astype('float64') / 255. return X_train, Y_train, X_test, Y_test def load_cifar10_data(noTrainingSamples,noTestingSamples):
85
85
285
13
71
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
load_cifar10_data
load_cifar10_data
588
616
588
588
7be4c17ad70d6b5e5cc89bf4f19357d06702b8b4
bigcode/the-stack
train
d8eb753d4a1056a520522abf
train
class
class MSE: def __init__(self, activation_fn=None): """ :param activation_fn: Class object of the activation function. """ if activation_fn: self.activation_fn = activation_fn else: self.activation_fn = NoActivation def activation(self, z): ...
class MSE:
def __init__(self, activation_fn=None): """ :param activation_fn: Class object of the activation function. """ if activation_fn: self.activation_fn = activation_fn else: self.activation_fn = NoActivation def activation(self, z): return sel...
] = 1 return z class Sigmoid: @staticmethod def activation(z): return 1 / (1 + np.exp(-z)) @staticmethod def prime(z): return Sigmoid.activation(z) * (1 - Sigmoid.activation(z)) class MSE:
64
64
206
4
60
emielsteerneman/sparse-evolutionary-artificial-neural-networks
Tutorial-ECMLPKDD-2019-Scalable-Deep-Learning/set_mlp.py
Python
MSE
MSE
111
142
111
111
f146441bb9455efc7ea4f950d4ff21cd866c2af9
bigcode/the-stack
train
3703448ba6a755e7d18c0f2a
train
function
def downgrade(): """Downgrade database schema and/or data back to the previous revision.""" # recreate Request table (query generated with SHOW CREATE TABLE) op.execute(""" CREATE TABLE `requests` ( `id` int(11) NOT NULL AUTO_INCREMENT, `request_type` enum('documentation','interview','popula...
def downgrade():
"""Downgrade database schema and/or data back to the previous revision.""" # recreate Request table (query generated with SHOW CREATE TABLE) op.execute(""" CREATE TABLE `requests` ( `id` int(11) NOT NULL AUTO_INCREMENT, `request_type` enum('documentation','interview','population sample') ...
", "auditable_type"), ("custom_attribute_definitions", "definition_type"), ("fulltext_record_properties", "type"), ("notifications", "object_type"), ("object_documents", "documentable_type"), ("object_owners", "ownable_type"), ("object_people", "personable_type"), ("relationshi...
136
136
454
3
133
Killswitchz/ggrc-core
src/ggrc/migrations/versions/20170719165433_1e3f798a4cc6_remove_request_model.py
Python
downgrade
downgrade
45
87
45
45
17dd4aa67c49a4cf83a79a7cb9573b970c580e72
bigcode/the-stack
train
3e8fd81239526824ac2fa4e6
train
function
def upgrade(): """Upgrade database schema and/or data, creating a new revision.""" op.execute("DROP TABLE `requests`") replace(op, "audits", "object_type", old_value="Request", new_value="Assessment") deletions_required = ( ("audit_objects", "auditable_type"), ("custom_attribute_definiti...
def upgrade():
"""Upgrade database schema and/or data, creating a new revision.""" op.execute("DROP TABLE `requests`") replace(op, "audits", "object_type", old_value="Request", new_value="Assessment") deletions_required = ( ("audit_objects", "auditable_type"), ("custom_attribute_definitions", "definiti...
ic import op from ggrc.migrations.utils.cleanup import replace from ggrc.migrations.utils.cleanup import delete # revision identifiers, used by Alembic. revision = '1e3f798a4cc6' down_revision = '47d3cb39bad7' def upgrade():
64
64
193
3
61
Killswitchz/ggrc-core
src/ggrc/migrations/versions/20170719165433_1e3f798a4cc6_remove_request_model.py
Python
upgrade
upgrade
19
42
19
19
d77a06bb88828cf7496b723636136e6f94b98b26
bigcode/the-stack
train
dc7367ce63fd00341e2c9c52
train
function
def format_convert_test(): # mass format [2, 3, 6] masses = [2, 3, 6] # position format (1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 3) positions = convert_masses_to_positions(masses) # boundary_string ({0},{1},{0},{0},{1},{0},{0},{0},{0},{0},) boundary_string = boundary_string_from_masses(masses) print(p...
def format_convert_test(): # mass format [2, 3, 6]
masses = [2, 3, 6] # position format (1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 3) positions = convert_masses_to_positions(masses) # boundary_string ({0},{1},{0},{0},{1},{0},{0},{0},{0},{0},) boundary_string = boundary_string_from_masses(masses) print(positions) print(boundary_string)
3f, S=%.3f" % (pk(h, gold, one_minus=True), WD(h, gold, one_minus=True, window_size=2), B(h, gold), S(h, gold))) def format_convert_test(): # mass format [2, 3, 6]
63
64
127
18
45
liuxuan320/text_segmentation_evaluation
single_test.py
Python
format_convert_test
format_convert_test
22
30
22
23
1502c481b3856a8c8108f1db367d53ba6012e224
bigcode/the-stack
train
50c20d69ba5babeefa8a8031
train
function
def example_in_paper_test(): gold = [2, 3, 6] h_list = [[5, 6], [2, 2, 7], [2, 3, 3, 3], [1, 1, 3, 1, 5]] for n, h in enumerate(h_list): cm = boundary_confusion_matrix(h, gold) print("第%d次实验" % int(n + 1)) # The P, R and F values are different from those in the normal method because ...
def example_in_paper_test():
gold = [2, 3, 6] h_list = [[5, 6], [2, 2, 7], [2, 3, 3, 3], [1, 1, 3, 1, 5]] for n, h in enumerate(h_list): cm = boundary_confusion_matrix(h, gold) print("第%d次实验" % int(n + 1)) # The P, R and F values are different from those in the normal method because it will correct the near miss...
from segeval.similarity.boundary import boundary_similarity as B from segeval.similarity.segmentation import segmentation_similarity as S from segeval.format import * from segeval.similarity import boundary_confusion_matrix from segeval.ml import precision, recall, fmeasure def example_in_paper_test():
68
68
227
7
60
liuxuan320/text_segmentation_evaluation
single_test.py
Python
example_in_paper_test
example_in_paper_test
10
19
10
10
6867023b9fa7fc0893165d7d60f49ce3f9ee0fd1
bigcode/the-stack
train
ec60bc32612963c1284d20e9
train
function
def resnet44(): return ResNet(BasicBlock, [7, 7, 7])
def resnet44():
return ResNet(BasicBlock, [7, 7, 7])
(hist1+hist2+hist3) return out#,hist def resnet20(): return ResNet(BasicBlock, [3, 3, 3]) def resnet32(): return ResNet(BasicBlock, [5, 5, 5]) def resnet44():
64
64
22
5
59
hecate64/CSQ
modelscifar/resnet20hist.py
Python
resnet44
resnet44
167
168
167
167
d0d9baf7864ee905c2603d5b33f0120d97c8e33b
bigcode/the-stack
train
7a8afb156400818756cc6239
train
class
class BasicBlock(nn.Module): expansion = 1 def __init__(self, in_planes, planes, stride=1, option='A'): super(BasicBlock, self).__init__() self.conv1 = conv(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = con...
class BasicBlock(nn.Module):
expansion = 1 def __init__(self, in_planes, planes, stride=1, option='A'): super(BasicBlock, self).__init__() self.conv1 = conv(in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False) self.bn1 = nn.BatchNorm2d(planes) self.conv2 = conv(planes, planes, kernel_size...
=padding, bias=bias, nbits=nbits) def _weights_init(m): classname = m.__class__.__name__ #print(classname) if isinstance(m, nn.Linear) or isinstance(m, nn.Conv2d): init.kaiming_normal_(m.weight) class LambdaLayer(nn.Module): def __init__(self, lambd): super(LambdaLayer, self).__init...
117
117
390
6
111
hecate64/CSQ
modelscifar/resnet20hist.py
Python
BasicBlock
BasicBlock
61
94
61
61
f8868dd47d5d74f85de56d082a24c7e96ade2df9
bigcode/the-stack
train
36a01b11d74a026ec9f0499f
train
function
def resnet110(): return ResNet(BasicBlock, [18, 18, 18])
def resnet110():
return ResNet(BasicBlock, [18, 18, 18])
ResNet(BasicBlock, [5, 5, 5]) def resnet44(): return ResNet(BasicBlock, [7, 7, 7]) def resnet56(): return ResNet(BasicBlock, [9, 9, 9]) def resnet110():
64
64
22
5
59
hecate64/CSQ
modelscifar/resnet20hist.py
Python
resnet110
resnet110
175
176
175
175
a7320ea2c109103e27272ebffb697d9a079a69a9
bigcode/the-stack
train
e74c5ef5feccaaa7d3abfbda
train
class
class LambdaLayer(nn.Module): def __init__(self, lambd): super(LambdaLayer, self).__init__() self.lambd = lambd def forward(self, x): return self.lambd(x)
class LambdaLayer(nn.Module):
def __init__(self, lambd): super(LambdaLayer, self).__init__() self.lambd = lambd def forward(self, x): return self.lambd(x)
bias=bias, nbits=nbits) def _weights_init(m): classname = m.__class__.__name__ #print(classname) if isinstance(m, nn.Linear) or isinstance(m, nn.Conv2d): init.kaiming_normal_(m.weight) class LambdaLayer(nn.Module):
64
64
50
6
58
hecate64/CSQ
modelscifar/resnet20hist.py
Python
LambdaLayer
LambdaLayer
52
58
52
52
31c41e5723b911369ee9f539c39c78102219f37b
bigcode/the-stack
train
b4d1a78211f1206bb2e6a694
train
function
def resnet20(): return ResNet(BasicBlock, [3, 3, 3])
def resnet20():
return ResNet(BasicBlock, [3, 3, 3])
), -1) out = self.linear(out) hist = hist1+hist2+hist3+hist4+hist5+hist6+hist7+hist8+hist9 #print(hist1+hist2+hist3) return out#,hist def resnet20():
64
64
22
5
58
hecate64/CSQ
modelscifar/resnet20hist.py
Python
resnet20
resnet20
159
160
159
159
ff2adbdcff30b5dc260e9b376ffdce0dfec38f07
bigcode/the-stack
train
c92aa08adb26336dabbaac1a
train
function
def resnet56(): return ResNet(BasicBlock, [9, 9, 9])
def resnet56():
return ResNet(BasicBlock, [9, 9, 9])
ResNet(BasicBlock, [3, 3, 3]) def resnet32(): return ResNet(BasicBlock, [5, 5, 5]) def resnet44(): return ResNet(BasicBlock, [7, 7, 7]) def resnet56():
64
64
22
5
59
hecate64/CSQ
modelscifar/resnet20hist.py
Python
resnet56
resnet56
171
172
171
171
e1f3f95929cada8e53b96d5cdeea78f5e9260237
bigcode/the-stack
train
17ece859435f830a798d1061
train
function
def resnet32(): return ResNet(BasicBlock, [5, 5, 5])
def resnet32():
return ResNet(BasicBlock, [5, 5, 5])
+hist4+hist5+hist6+hist7+hist8+hist9 #print(hist1+hist2+hist3) return out#,hist def resnet20(): return ResNet(BasicBlock, [3, 3, 3]) def resnet32():
64
64
22
5
59
hecate64/CSQ
modelscifar/resnet20hist.py
Python
resnet32
resnet32
163
164
163
163
e7f420e57bf814a7caa1dfaafd7f62973a02a84c
bigcode/the-stack
train
58752fdc58944ed2887fe1a3
train
function
def conv(input, output, kernel_size=3, stride=1, padding=1, bias=False,nbits=2): return Q.Conv2dLSQ_sym(input, output, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias, nbits=nbits)
def conv(input, output, kernel_size=3, stride=1, padding=1, bias=False,nbits=2):
return Q.Conv2dLSQ_sym(input, output, kernel_size=kernel_size, stride=stride, padding=padding, bias=bias, nbits=nbits)
__ = ['ResNet', 'resnet20', 'resnet32', 'resnet44', 'resnet56', 'resnet110', 'resnet1202'] def conv(input, output, kernel_size=3, stride=1, padding=1, bias=False,nbits=2):
64
64
64
27
37
hecate64/CSQ
modelscifar/resnet20hist.py
Python
conv
conv
40
41
40
40
9976fe4bb9452e7b3b7c6898a69e4e73ec4a3776
bigcode/the-stack
train