body_hash stringlengths 64 64 | body stringlengths 23 109k | docstring stringlengths 1 57k | path stringlengths 4 198 | name stringlengths 1 115 | repository_name stringlengths 7 111 | repository_stars float64 0 191k | lang stringclasses 1
value | body_without_docstring stringlengths 14 108k | unified stringlengths 45 133k |
|---|---|---|---|---|---|---|---|---|---|
51f920af5fa6baef21adc57328d0d0b064eb7ba476d92da836f84444d933afca | def extract_configurations_from_yml(config_path: Path=None) -> YAML:
'\n Parse YAML for package and model configurations.\n '
if (not config_path):
config_path = detect_config_file()
if config_path:
with open(config_path, 'r') as config_file:
parsed_config_file = load(confi... | Parse YAML for package and model configurations. | costa_rica_poverty/packages/model/model/config/config.py | extract_configurations_from_yml | Cawiess/costa_rica_poverty | 0 | python | def extract_configurations_from_yml(config_path: Path=None) -> YAML:
'\n \n '
if (not config_path):
config_path = detect_config_file()
if config_path:
with open(config_path, 'r') as config_file:
parsed_config_file = load(config_file.read())
return parsed_config_... | def extract_configurations_from_yml(config_path: Path=None) -> YAML:
'\n \n '
if (not config_path):
config_path = detect_config_file()
if config_path:
with open(config_path, 'r') as config_file:
parsed_config_file = load(config_file.read())
return parsed_config_... |
976ce31aa1ce2256927ad6df2219f7105509eb9bca2abea2385b2df46c93c209 | def create_and_validate_configurations(parsed_config_file: YAML=None) -> Config:
'\n Run valdidation procedure for configuration information.\n '
if (parsed_config_file is None):
parsed_config_file = extract_configurations_from_yml()
_config = Config(package_config=PackageConfig(**parsed_confi... | Run valdidation procedure for configuration information. | costa_rica_poverty/packages/model/model/config/config.py | create_and_validate_configurations | Cawiess/costa_rica_poverty | 0 | python | def create_and_validate_configurations(parsed_config_file: YAML=None) -> Config:
'\n \n '
if (parsed_config_file is None):
parsed_config_file = extract_configurations_from_yml()
_config = Config(package_config=PackageConfig(**parsed_config_file.data), preprocessing_config=PreprocessingConfig(*... | def create_and_validate_configurations(parsed_config_file: YAML=None) -> Config:
'\n \n '
if (parsed_config_file is None):
parsed_config_file = extract_configurations_from_yml()
_config = Config(package_config=PackageConfig(**parsed_config_file.data), preprocessing_config=PreprocessingConfig(*... |
1ca65446e529cf4cefa5d551080792ba1c0b88438be135186c9fb22247f655f6 | def __genrandomstruct__(self):
'generating randomstruct'
oxyz = self.xyz.copy()
Ri = np.random.uniform(low=self.l_val, high=self.h_val, size=None)
oxyz = (oxyz + (Ri * self.nmo))
return oxyz | generating randomstruct | lib/nmstools.py | __genrandomstruct__ | Jussmith01/ANI-Tools | 8 | python | def __genrandomstruct__(self):
oxyz = self.xyz.copy()
Ri = np.random.uniform(low=self.l_val, high=self.h_val, size=None)
oxyz = (oxyz + (Ri * self.nmo))
return oxyz | def __genrandomstruct__(self):
oxyz = self.xyz.copy()
Ri = np.random.uniform(low=self.l_val, high=self.h_val, size=None)
oxyz = (oxyz + (Ri * self.nmo))
return oxyz<|docstring|>generating randomstruct<|endoftext|> |
461019696e6f34db88e6bc7d83a7e539ecd453bbecda391e5c145ef07af7169d | def normalize_rgb_values(color: tuple) -> tuple:
'\n Clean-up any slight color differences in PIL sampling.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: a tuple of RGB color values\n '
return tuple([(0 if (val <= 3) else (255 if (val >= 253) else val)) for val in col... | Clean-up any slight color differences in PIL sampling.
:param color: a tuple of RGB color values eg. (255, 255, 255)
:returns: a tuple of RGB color values | swatcher/color.py | normalize_rgb_values | joshbduncan/swatcher | 0 | python | def normalize_rgb_values(color: tuple) -> tuple:
'\n Clean-up any slight color differences in PIL sampling.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: a tuple of RGB color values\n '
return tuple([(0 if (val <= 3) else (255 if (val >= 253) else val)) for val in col... | def normalize_rgb_values(color: tuple) -> tuple:
'\n Clean-up any slight color differences in PIL sampling.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: a tuple of RGB color values\n '
return tuple([(0 if (val <= 3) else (255 if (val >= 253) else val)) for val in col... |
74e8a9fef75226090d92d65d529e559fc1caae8b62ab8be933ddd141359fd2db | def rgb_2_luma(color: tuple) -> int:
'\n Calculate the "brightness" of a color.\n\n ...and, yes I know this is a debated subject\n but this way works for just fine my purposes.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: luminance "brightness" value\n '
(r, g,... | Calculate the "brightness" of a color.
...and, yes I know this is a debated subject
but this way works for just fine my purposes.
:param color: a tuple of RGB color values eg. (255, 255, 255)
:returns: luminance "brightness" value | swatcher/color.py | rgb_2_luma | joshbduncan/swatcher | 0 | python | def rgb_2_luma(color: tuple) -> int:
'\n Calculate the "brightness" of a color.\n\n ...and, yes I know this is a debated subject\n but this way works for just fine my purposes.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: luminance "brightness" value\n '
(r, g,... | def rgb_2_luma(color: tuple) -> int:
'\n Calculate the "brightness" of a color.\n\n ...and, yes I know this is a debated subject\n but this way works for just fine my purposes.\n\n :param color: a tuple of RGB color values eg. (255, 255, 255)\n :returns: luminance "brightness" value\n '
(r, g,... |
8df9262c0b0db73f057ab79e59dfb9b66843ee60d05af3001c466a67964386a4 | def sort_by_brightness(colors: list) -> list:
'\n Sort of list of RGB colors values by their brightness.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
l = {color: rgb_2_luma(color) for color in colors}
return sorted(l, key=l.... | Sort of list of RGB colors values by their brightness.
:param color: tuple of RGB values for color eg. (255, 255, 255)
:returns: list of color value dictionaries | swatcher/color.py | sort_by_brightness | joshbduncan/swatcher | 0 | python | def sort_by_brightness(colors: list) -> list:
'\n Sort of list of RGB colors values by their brightness.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
l = {color: rgb_2_luma(color) for color in colors}
return sorted(l, key=l.... | def sort_by_brightness(colors: list) -> list:
'\n Sort of list of RGB colors values by their brightness.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
l = {color: rgb_2_luma(color) for color in colors}
return sorted(l, key=l.... |
9e46bdd4ebafabddd30c675e9d0f73203347566f808181f7e40bb96620e7ea06 | def rgb_2_hex(color: tuple) -> str:
'\n Convert RGB color vales to Hex code (eg. #ffffff).\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: color Hex code\n '
(r, g, b) = color
return f'#{r:02x}{g:02x}{b:02x}' | Convert RGB color vales to Hex code (eg. #ffffff).
:param color: tuple of RGB values for color eg. (255, 255, 255)
:returns: color Hex code | swatcher/color.py | rgb_2_hex | joshbduncan/swatcher | 0 | python | def rgb_2_hex(color: tuple) -> str:
'\n Convert RGB color vales to Hex code (eg. #ffffff).\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: color Hex code\n '
(r, g, b) = color
return f'#{r:02x}{g:02x}{b:02x}' | def rgb_2_hex(color: tuple) -> str:
'\n Convert RGB color vales to Hex code (eg. #ffffff).\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: color Hex code\n '
(r, g, b) = color
return f'#{r:02x}{g:02x}{b:02x}'<|docstring|>Convert RGB color vales to Hex code (eg. #f... |
0d0598aad30ebf071e3f8b57569e8d5144c34b663c53e681eeff8c6233f1f889 | def rgb_2_cmyk(color: tuple) -> tuple:
'\n Convert RGB color vales to CMYK color values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: CMYK values eg. (C, M, Y, K)\n '
if (color == (0, 0, 0)):
return (0, 0, 0, 100)
(r, g, b) = color
k = (1 - (max((r,... | Convert RGB color vales to CMYK color values.
:param color: tuple of RGB values for color eg. (255, 255, 255)
:returns: CMYK values eg. (C, M, Y, K) | swatcher/color.py | rgb_2_cmyk | joshbduncan/swatcher | 0 | python | def rgb_2_cmyk(color: tuple) -> tuple:
'\n Convert RGB color vales to CMYK color values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: CMYK values eg. (C, M, Y, K)\n '
if (color == (0, 0, 0)):
return (0, 0, 0, 100)
(r, g, b) = color
k = (1 - (max((r,... | def rgb_2_cmyk(color: tuple) -> tuple:
'\n Convert RGB color vales to CMYK color values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: CMYK values eg. (C, M, Y, K)\n '
if (color == (0, 0, 0)):
return (0, 0, 0, 100)
(r, g, b) = color
k = (1 - (max((r,... |
a1336c0130cc307d89b1509a1b6a93996c3dea0127213434b3a1053d2d9e33af | def color_2_dict(color: tuple) -> dict:
'\n Convert tuple of RGB color vales to HEX and CMYK then\n combine into a dictionary in the following format.\n\n {"rgb": (0, 0, 0), "hex": "#000000", "cmyk": (0, 0, 0, 100)}\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: RGB, ... | Convert tuple of RGB color vales to HEX and CMYK then
combine into a dictionary in the following format.
{"rgb": (0, 0, 0), "hex": "#000000", "cmyk": (0, 0, 0, 100)}
:param color: tuple of RGB values for color eg. (255, 255, 255)
:returns: RGB, HEX and CMYK values | swatcher/color.py | color_2_dict | joshbduncan/swatcher | 0 | python | def color_2_dict(color: tuple) -> dict:
'\n Convert tuple of RGB color vales to HEX and CMYK then\n combine into a dictionary in the following format.\n\n {"rgb": (0, 0, 0), "hex": "#000000", "cmyk": (0, 0, 0, 100)}\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: RGB, ... | def color_2_dict(color: tuple) -> dict:
'\n Convert tuple of RGB color vales to HEX and CMYK then\n combine into a dictionary in the following format.\n\n {"rgb": (0, 0, 0), "hex": "#000000", "cmyk": (0, 0, 0, 100)}\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: RGB, ... |
72d548b4c3da78de241885e98dc1aad4625654bccd516d491edb880fedc36ca9 | def colors_2_dicts(colors: list) -> list:
'\n Convert a list of RGB color vales to a list of\n dicts with RGB, HEX, and CMYK values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
return [color_2_dict(color) for color in colors... | Convert a list of RGB color vales to a list of
dicts with RGB, HEX, and CMYK values.
:param color: tuple of RGB values for color eg. (255, 255, 255)
:returns: list of color value dictionaries | swatcher/color.py | colors_2_dicts | joshbduncan/swatcher | 0 | python | def colors_2_dicts(colors: list) -> list:
'\n Convert a list of RGB color vales to a list of\n dicts with RGB, HEX, and CMYK values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
return [color_2_dict(color) for color in colors... | def colors_2_dicts(colors: list) -> list:
'\n Convert a list of RGB color vales to a list of\n dicts with RGB, HEX, and CMYK values.\n\n :param color: tuple of RGB values for color eg. (255, 255, 255)\n :returns: list of color value dictionaries\n '
return [color_2_dict(color) for color in colors... |
8b5b3bb1c1fab7a9447d8368574c6e981f5a61ce6ca68e82d23497672ceb4201 | def color_distance(color1: tuple, color2: tuple) -> int:
'\n Calculate the Euclidean distance between two colors.\n\n https://en.wikipedia.org/wiki/Color_difference\n\n :param color1: tuple of RGB color values eg. (255, 255, 255)\n :param color2: tuple of RGB color values\n :returns: Euclidean distan... | Calculate the Euclidean distance between two colors.
https://en.wikipedia.org/wiki/Color_difference
:param color1: tuple of RGB color values eg. (255, 255, 255)
:param color2: tuple of RGB color values
:returns: Euclidean distance of two colors | swatcher/color.py | color_distance | joshbduncan/swatcher | 0 | python | def color_distance(color1: tuple, color2: tuple) -> int:
'\n Calculate the Euclidean distance between two colors.\n\n https://en.wikipedia.org/wiki/Color_difference\n\n :param color1: tuple of RGB color values eg. (255, 255, 255)\n :param color2: tuple of RGB color values\n :returns: Euclidean distan... | def color_distance(color1: tuple, color2: tuple) -> int:
'\n Calculate the Euclidean distance between two colors.\n\n https://en.wikipedia.org/wiki/Color_difference\n\n :param color1: tuple of RGB color values eg. (255, 255, 255)\n :param color2: tuple of RGB color values\n :returns: Euclidean distan... |
8fc2ea9b2fa17e8a7727d77e6bdf2379325192deb0695a61d0d0dbc0828b2448 | def get_colors(image: object) -> list:
'\n Sample all pixels from an image and sort their RGB values by most common\n\n :param image: PIL Image object\n :returns: list of RGB tuples (255, 255, 255)\n '
colors = Counter([pixel for pixel in image.getdata()])
return [color for (color, _) in colors.... | Sample all pixels from an image and sort their RGB values by most common
:param image: PIL Image object
:returns: list of RGB tuples (255, 255, 255) | swatcher/color.py | get_colors | joshbduncan/swatcher | 0 | python | def get_colors(image: object) -> list:
'\n Sample all pixels from an image and sort their RGB values by most common\n\n :param image: PIL Image object\n :returns: list of RGB tuples (255, 255, 255)\n '
colors = Counter([pixel for pixel in image.getdata()])
return [color for (color, _) in colors.... | def get_colors(image: object) -> list:
'\n Sample all pixels from an image and sort their RGB values by most common\n\n :param image: PIL Image object\n :returns: list of RGB tuples (255, 255, 255)\n '
colors = Counter([pixel for pixel in image.getdata()])
return [color for (color, _) in colors.... |
6b76a04239ffde15001f2e46049a3194f75b1d11557fbf07b501d024676ed7b1 | def get_worker_registrar_for(head):
'Return a class that will handle worker registration for the given head.'
class WorkerRegistrarService(Service):
'An RPyC service to register workers with a head.'
def exposed_register_worker(self, host, port):
'Register a worker with my head, in... | Return a class that will handle worker registration for the given head. | tgen/parallel_seq2seq_train.py | get_worker_registrar_for | schneider20/tgen | 222 | python | def get_worker_registrar_for(head):
class WorkerRegistrarService(Service):
'An RPyC service to register workers with a head.'
def exposed_register_worker(self, host, port):
'Register a worker with my head, initialize it.'
log_info(('Worker %s:%d connected, initializing... | def get_worker_registrar_for(head):
class WorkerRegistrarService(Service):
'An RPyC service to register workers with a head.'
def exposed_register_worker(self, host, port):
'Register a worker with my head, initialize it.'
log_info(('Worker %s:%d connected, initializing... |
cf6fe97ce2190d1e760c9bd7552d8b0dcbf3fb72ede61f6947ac7af7223f76fd | def run_training(head_host, head_port, debug_out=None):
'Main worker training routine (creates the Seq2SeqTrainingService and connects it to the\n head.\n\n @param head_host: hostname of the head\n @param head_port: head port number\n @param debug_out: path to the debugging output file (debug output dis... | Main worker training routine (creates the Seq2SeqTrainingService and connects it to the
head.
@param head_host: hostname of the head
@param head_port: head port number
@param debug_out: path to the debugging output file (debug output discarded if None) | tgen/parallel_seq2seq_train.py | run_training | schneider20/tgen | 222 | python | def run_training(head_host, head_port, debug_out=None):
'Main worker training routine (creates the Seq2SeqTrainingService and connects it to the\n head.\n\n @param head_host: hostname of the head\n @param head_port: head port number\n @param debug_out: path to the debugging output file (debug output dis... | def run_training(head_host, head_port, debug_out=None):
'Main worker training routine (creates the Seq2SeqTrainingService and connects it to the\n head.\n\n @param head_host: hostname of the head\n @param head_port: head port number\n @param debug_out: path to the debugging output file (debug output dis... |
3869d33bfa5b81dee685bc8f4d9b1f0f9b14fe5de56864b35e84583d04f688cf | def train(self, das_file, ttree_file, data_portion=1.0, context_file=None, validation_files=None):
'Run parallel perceptron training, start and manage workers.'
log_info('Initializing...')
self._init_server()
log_info('Spawning jobs...')
(host_short, _) = self.host.split('.', 1)
for j in range(s... | Run parallel perceptron training, start and manage workers. | tgen/parallel_seq2seq_train.py | train | schneider20/tgen | 222 | python | def train(self, das_file, ttree_file, data_portion=1.0, context_file=None, validation_files=None):
log_info('Initializing...')
self._init_server()
log_info('Spawning jobs...')
(host_short, _) = self.host.split('.', 1)
for j in range(self.jobs_number):
debug_logfile = (('"PRT%02d.debug-o... | def train(self, das_file, ttree_file, data_portion=1.0, context_file=None, validation_files=None):
log_info('Initializing...')
self._init_server()
log_info('Spawning jobs...')
(host_short, _) = self.host.split('.', 1)
for j in range(self.jobs_number):
debug_logfile = (('"PRT%02d.debug-o... |
97f2dfb3de785e17d3482387d3bd6c341be0aecde0ebd844f16482911ed5da5b | def _check_pending_request(self, sc, job_no, req):
'Check whether the given request has finished (i.e., job is loaded or job has\n processed the given data portion.\n\n If the request is finished, the worker that processed it is moved to the pool\n of free services.\n\n @param iter_no: c... | Check whether the given request has finished (i.e., job is loaded or job has
processed the given data portion.
If the request is finished, the worker that processed it is moved to the pool
of free services.
@param iter_no: current iteration number (for logging)
@param sc: a ServiceConn object that stores the worker c... | tgen/parallel_seq2seq_train.py | _check_pending_request | schneider20/tgen | 222 | python | def _check_pending_request(self, sc, job_no, req):
'Check whether the given request has finished (i.e., job is loaded or job has\n processed the given data portion.\n\n If the request is finished, the worker that processed it is moved to the pool\n of free services.\n\n @param iter_no: c... | def _check_pending_request(self, sc, job_no, req):
'Check whether the given request has finished (i.e., job is loaded or job has\n processed the given data portion.\n\n If the request is finished, the worker that processed it is moved to the pool\n of free services.\n\n @param iter_no: c... |
a929ed9c7e1610876e90c2d602ada1f0fe35c7ba087bda361119eafc78ba469e | def _init_server(self):
'Initializes a server that registers new workers.'
registrar_class = get_worker_registrar_for(self)
n_tries = 0
self.server = None
last_error = None
while ((self.server is None) and (n_tries < 10)):
try:
n_tries += 1
self.server = ThreadPoo... | Initializes a server that registers new workers. | tgen/parallel_seq2seq_train.py | _init_server | schneider20/tgen | 222 | python | def _init_server(self):
registrar_class = get_worker_registrar_for(self)
n_tries = 0
self.server = None
last_error = None
while ((self.server is None) and (n_tries < 10)):
try:
n_tries += 1
self.server = ThreadPoolServer(service=registrar_class, nbThreads=1, port... | def _init_server(self):
registrar_class = get_worker_registrar_for(self)
n_tries = 0
self.server = None
last_error = None
while ((self.server is None) and (n_tries < 10)):
try:
n_tries += 1
self.server = ThreadPoolServer(service=registrar_class, nbThreads=1, port... |
c0289781dd099ef76a405e6fbee4636dd53b1787bf4eb84ea76302efc090bb7b | def save_to_file(self, model_fname):
'This will actually just move the best generator (which is saved in a temporary file)\n to the final location.'
log_info(('Moving generator to %s...' % model_fname))
orig_model_fname = self.model_temp_path
shutil.move(orig_model_fname, model_fname)
orig_tf... | This will actually just move the best generator (which is saved in a temporary file)
to the final location. | tgen/parallel_seq2seq_train.py | save_to_file | schneider20/tgen | 222 | python | def save_to_file(self, model_fname):
'This will actually just move the best generator (which is saved in a temporary file)\n to the final location.'
log_info(('Moving generator to %s...' % model_fname))
orig_model_fname = self.model_temp_path
shutil.move(orig_model_fname, model_fname)
orig_tf... | def save_to_file(self, model_fname):
'This will actually just move the best generator (which is saved in a temporary file)\n to the final location.'
log_info(('Moving generator to %s...' % model_fname))
orig_model_fname = self.model_temp_path
shutil.move(orig_model_fname, model_fname)
orig_tf... |
88f0b25a8d0970f292c8f7d97d6ce8f352eea43105a277bcd7f1a2f6a9e6d370 | def build_ensemble_model(self, results):
'Load the models computed by the individual jobs and compose them into a single\n ensemble model.\n\n @param results: list of tuples (cost, ServiceConn object), where cost is not used'
ensemble = Seq2SeqEnsemble(self.cfg)
models = []
for (_, sc) in ... | Load the models computed by the individual jobs and compose them into a single
ensemble model.
@param results: list of tuples (cost, ServiceConn object), where cost is not used | tgen/parallel_seq2seq_train.py | build_ensemble_model | schneider20/tgen | 222 | python | def build_ensemble_model(self, results):
'Load the models computed by the individual jobs and compose them into a single\n ensemble model.\n\n @param results: list of tuples (cost, ServiceConn object), where cost is not used'
ensemble = Seq2SeqEnsemble(self.cfg)
models = []
for (_, sc) in ... | def build_ensemble_model(self, results):
'Load the models computed by the individual jobs and compose them into a single\n ensemble model.\n\n @param results: list of tuples (cost, ServiceConn object), where cost is not used'
ensemble = Seq2SeqEnsemble(self.cfg)
models = []
for (_, sc) in ... |
e910177b001692621666204a8af7f415263d401ebfe2d6c57cdb5e102ea76163 | def exposed_init_training(self, cfg):
'Create the Seq2SeqGen object.'
cfg = pickle.loads(cfg)
tstart = time.time()
log_info('Initializing training...')
self.seq2seq = Seq2SeqGen(cfg)
log_info(('Training initialized. Time taken: %f secs.' % (time.time() - tstart))) | Create the Seq2SeqGen object. | tgen/parallel_seq2seq_train.py | exposed_init_training | schneider20/tgen | 222 | python | def exposed_init_training(self, cfg):
cfg = pickle.loads(cfg)
tstart = time.time()
log_info('Initializing training...')
self.seq2seq = Seq2SeqGen(cfg)
log_info(('Training initialized. Time taken: %f secs.' % (time.time() - tstart))) | def exposed_init_training(self, cfg):
cfg = pickle.loads(cfg)
tstart = time.time()
log_info('Initializing training...')
self.seq2seq = Seq2SeqGen(cfg)
log_info(('Training initialized. Time taken: %f secs.' % (time.time() - tstart)))<|docstring|>Create the Seq2SeqGen object.<|endoftext|> |
278c73819d3eb6d7e997e1b284e2f4d489c89cec83da26a9c4ef70982be6efd9 | def exposed_train(self, rnd_seed, das_file, ttree_file, data_portion, context_file, validation_files):
'Run the whole training.\n '
rnd.seed(rnd_seed)
log_info(('Random seed: %f' % rnd_seed))
tstart = time.time()
log_info('Starting training...')
self.seq2seq.train(das_file, ttree_file, da... | Run the whole training. | tgen/parallel_seq2seq_train.py | exposed_train | schneider20/tgen | 222 | python | def exposed_train(self, rnd_seed, das_file, ttree_file, data_portion, context_file, validation_files):
'\n '
rnd.seed(rnd_seed)
log_info(('Random seed: %f' % rnd_seed))
tstart = time.time()
log_info('Starting training...')
self.seq2seq.train(das_file, ttree_file, data_portion, context_fil... | def exposed_train(self, rnd_seed, das_file, ttree_file, data_portion, context_file, validation_files):
'\n '
rnd.seed(rnd_seed)
log_info(('Random seed: %f' % rnd_seed))
tstart = time.time()
log_info('Starting training...')
self.seq2seq.train(das_file, ttree_file, data_portion, context_fil... |
f4e5078bc2e9d3c299cce111abff46066da5ce2a1b1829c91fb0a6ce62a752fb | def exposed_save_model(self, model_fname):
"Save the model to the given file (must be given relative to the worker's working\n directory!).\n @param model_fname: target path where to save the model (relative to worker's working directory)\n "
self.seq2seq.save_to_file(model_... | Save the model to the given file (must be given relative to the worker's working
directory!).
@param model_fname: target path where to save the model (relative to worker's working directory) | tgen/parallel_seq2seq_train.py | exposed_save_model | schneider20/tgen | 222 | python | def exposed_save_model(self, model_fname):
"Save the model to the given file (must be given relative to the worker's working\n directory!).\n @param model_fname: target path where to save the model (relative to worker's working directory)\n "
self.seq2seq.save_to_file(model_... | def exposed_save_model(self, model_fname):
"Save the model to the given file (must be given relative to the worker's working\n directory!).\n @param model_fname: target path where to save the model (relative to worker's working directory)\n "
self.seq2seq.save_to_file(model_... |
96e94d97761df30e982f581b95ce81fa12dec17394abed2d83402a0047d781b8 | def exposed_get_model_params(self):
"Retrieve all parameters of the worker's local model (as a dictionary)\n @return: model parameters in a pickled dictionary -- keys are names, values are numpy arrays\n "
p_dump = pickle.dumps(self.seq2seq.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
... | Retrieve all parameters of the worker's local model (as a dictionary)
@return: model parameters in a pickled dictionary -- keys are names, values are numpy arrays | tgen/parallel_seq2seq_train.py | exposed_get_model_params | schneider20/tgen | 222 | python | def exposed_get_model_params(self):
"Retrieve all parameters of the worker's local model (as a dictionary)\n @return: model parameters in a pickled dictionary -- keys are names, values are numpy arrays\n "
p_dump = pickle.dumps(self.seq2seq.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
... | def exposed_get_model_params(self):
"Retrieve all parameters of the worker's local model (as a dictionary)\n @return: model parameters in a pickled dictionary -- keys are names, values are numpy arrays\n "
p_dump = pickle.dumps(self.seq2seq.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
... |
41e39d4ce8280375c23a89461f9861fcd57bb33499a886e040ee7e4ca6301cbb | def exposed_get_all_settings(self):
'Call `get_all_settings` on the worker and return the result as a pickle.'
settings = pickle.dumps(self.seq2seq.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings | Call `get_all_settings` on the worker and return the result as a pickle. | tgen/parallel_seq2seq_train.py | exposed_get_all_settings | schneider20/tgen | 222 | python | def exposed_get_all_settings(self):
settings = pickle.dumps(self.seq2seq.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings | def exposed_get_all_settings(self):
settings = pickle.dumps(self.seq2seq.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings<|docstring|>Call `get_all_settings` on the worker and return the result as a pickle.<|endoftext|> |
cfeb87a24cc9de9476998de9706008b8fbd321e360fb5c8cef8d32d4f76f676a | def exposed_get_rerank_params(self):
"Call `get_model_params` on the worker's reranker and return the result as a pickle."
if (not self.seq2seq.classif_filter):
return None
p_dump = pickle.dumps(self.seq2seq.classif_filter.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
return p_dump | Call `get_model_params` on the worker's reranker and return the result as a pickle. | tgen/parallel_seq2seq_train.py | exposed_get_rerank_params | schneider20/tgen | 222 | python | def exposed_get_rerank_params(self):
if (not self.seq2seq.classif_filter):
return None
p_dump = pickle.dumps(self.seq2seq.classif_filter.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
return p_dump | def exposed_get_rerank_params(self):
if (not self.seq2seq.classif_filter):
return None
p_dump = pickle.dumps(self.seq2seq.classif_filter.get_model_params(), protocol=pickle.HIGHEST_PROTOCOL)
return p_dump<|docstring|>Call `get_model_params` on the worker's reranker and return the result as a pi... |
dfcc42685b5d50d07c7c65807a0c44055fd5830945b39bc51a6529fe19809f28 | def exposed_get_rerank_settings(self):
"Call `get_all_settings` on the worker's reranker and return the result as a pickle."
if (not self.seq2seq.classif_filter):
return None
settings = pickle.dumps(self.seq2seq.classif_filter.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings | Call `get_all_settings` on the worker's reranker and return the result as a pickle. | tgen/parallel_seq2seq_train.py | exposed_get_rerank_settings | schneider20/tgen | 222 | python | def exposed_get_rerank_settings(self):
if (not self.seq2seq.classif_filter):
return None
settings = pickle.dumps(self.seq2seq.classif_filter.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings | def exposed_get_rerank_settings(self):
if (not self.seq2seq.classif_filter):
return None
settings = pickle.dumps(self.seq2seq.classif_filter.get_all_settings(), protocol=pickle.HIGHEST_PROTOCOL)
return settings<|docstring|>Call `get_all_settings` on the worker's reranker and return the result a... |
3a17389ed453a77c8ac95d3a67496b2993c98476bc2d5f9d4cb94282003ba822 | def exposed_register_worker(self, host, port):
'Register a worker with my head, initialize it.'
log_info(('Worker %s:%d connected, initializing training.' % (host, port)))
conn = connect(host, port, config={'allow_pickle': True})
init_func = async_(conn.root.init_training)
head.cfg['scope_suffix'] =... | Register a worker with my head, initialize it. | tgen/parallel_seq2seq_train.py | exposed_register_worker | schneider20/tgen | 222 | python | def exposed_register_worker(self, host, port):
log_info(('Worker %s:%d connected, initializing training.' % (host, port)))
conn = connect(host, port, config={'allow_pickle': True})
init_func = async_(conn.root.init_training)
head.cfg['scope_suffix'] = hashlib.md5(('%s:%d' % (host, port))).hexdigest... | def exposed_register_worker(self, host, port):
log_info(('Worker %s:%d connected, initializing training.' % (host, port)))
conn = connect(host, port, config={'allow_pickle': True})
init_func = async_(conn.root.init_training)
head.cfg['scope_suffix'] = hashlib.md5(('%s:%d' % (host, port))).hexdigest... |
64cb90bb146c85f0e11adef8163a314f4a42996e3ad3152e4a2ba67bef930958 | def insert_items(table_name: str, columns: List[str], values: List[List[Union[(str, int, float)]]]) -> str:
'\n 单表插入\n 支持同时插入多条记录\n Args:\n table_name: 要插入的表名\n columns: 指明要插入的表属性，必须包含表中没有默认参数的属性，不允许为空列表\n values: 对应要插入的属性的值列表，列表里每个值要与colums对应\n Return:\n "success"\n Example:\n insert_... | 单表插入
支持同时插入多条记录
Args:
table_name: 要插入的表名
columns: 指明要插入的表属性，必须包含表中没有默认参数的属性，不允许为空列表
values: 对应要插入的属性的值列表，列表里每个值要与colums对应
Return:
"success"
Example:
insert_items(table_name='person',
columns=['name', 'age'],
values=[['周杰伦', 30], ['马云', 35]]) | dao/crud.py | insert_items | leexinhao/boya-backend | 0 | python | def insert_items(table_name: str, columns: List[str], values: List[List[Union[(str, int, float)]]]) -> str:
'\n 单表插入\n 支持同时插入多条记录\n Args:\n table_name: 要插入的表名\n columns: 指明要插入的表属性，必须包含表中没有默认参数的属性，不允许为空列表\n values: 对应要插入的属性的值列表，列表里每个值要与colums对应\n Return:\n "success"\n Example:\n insert_... | def insert_items(table_name: str, columns: List[str], values: List[List[Union[(str, int, float)]]]) -> str:
'\n 单表插入\n 支持同时插入多条记录\n Args:\n table_name: 要插入的表名\n columns: 指明要插入的表属性，必须包含表中没有默认参数的属性，不允许为空列表\n values: 对应要插入的属性的值列表，列表里每个值要与colums对应\n Return:\n "success"\n Example:\n insert_... |
8fa5881bba8fbcd3bcb7196f4b95604a3930bbd6bbae51f5833d2ade16321384 | def delete_items(table_name: str, where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表删除\n 一次可以根据传入条件删除多条记录，注意传入where要小心，不然很容易误删\n 如果指定的条件对应的记录不存在也会返回success\n Args:\n table_name: 要删除的表名\n where: 要删除的条件键值对，若为None或空字典删除整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"code": 20... | 单表删除
一次可以根据传入条件删除多条记录，注意传入where要小心，不然很容易误删
如果指定的条件对应的记录不存在也会返回success
Args:
table_name: 要删除的表名
where: 要删除的条件键值对，若为None或空字典删除整个表或所有指定的colums条目，目前只能使用=判断
Return:
{"code": 200, "message": "success"}
Example:
delete_items(table_name='person',
where={"name": "周杰伦", "age": 30}) | dao/crud.py | delete_items | leexinhao/boya-backend | 0 | python | def delete_items(table_name: str, where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表删除\n 一次可以根据传入条件删除多条记录，注意传入where要小心，不然很容易误删\n 如果指定的条件对应的记录不存在也会返回success\n Args:\n table_name: 要删除的表名\n where: 要删除的条件键值对，若为None或空字典删除整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"code": 20... | def delete_items(table_name: str, where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表删除\n 一次可以根据传入条件删除多条记录，注意传入where要小心，不然很容易误删\n 如果指定的条件对应的记录不存在也会返回success\n Args:\n table_name: 要删除的表名\n where: 要删除的条件键值对，若为None或空字典删除整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"code": 20... |
53bbb0bb2d3a9f0e98d9d8314a10cc0c5acf9ef3b281aabd58cdb5c502e8728d | def select_items(table_name: str, columns: Optional[List[str]]=None, where: Optional[Dict[(str, Union[(str, int, float)])]]=None, limit: Optional[int]=None, skip: int=0, use_like=False) -> List[Dict[(str, Union[(str, int, float)])]]:
"\n 单表查询\n Args:\n table_name: 要查询的表名\n columns: 要查询的属性，若为None或空列表则返回全... | 单表查询
Args:
table_name: 要查询的表名
columns: 要查询的属性，若为None或空列表则返回全部属性
where: 要查询的条件键值对，若为None或空字典返回整个表或所有指定的colums条目，目前只能使用=判断
limit: 返回条目的最大数量，为None时全部返回
skip: 返回条目的查询偏移
Return:
一个包含数个查询条目的列表
Example:
select_items(table_name='person',
columns=['name', 'age'],
where={'name':'周杰伦', 'age':20}) | dao/crud.py | select_items | leexinhao/boya-backend | 0 | python | def select_items(table_name: str, columns: Optional[List[str]]=None, where: Optional[Dict[(str, Union[(str, int, float)])]]=None, limit: Optional[int]=None, skip: int=0, use_like=False) -> List[Dict[(str, Union[(str, int, float)])]]:
"\n 单表查询\n Args:\n table_name: 要查询的表名\n columns: 要查询的属性，若为None或空列表则返回全... | def select_items(table_name: str, columns: Optional[List[str]]=None, where: Optional[Dict[(str, Union[(str, int, float)])]]=None, limit: Optional[int]=None, skip: int=0, use_like=False) -> List[Dict[(str, Union[(str, int, float)])]]:
"\n 单表查询\n Args:\n table_name: 要查询的表名\n columns: 要查询的属性，若为None或空列表则返回全... |
1c02ee727d4b8a79a3b837ad3e8cb18ea3a6ef53058687ca212c97b85dedccd1 | def update_items(table_name: str, items: Dict[(str, Union[(str, int, float)])], where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表更新\n Args:\n table_name: 要更新的表名\n items: 要更新的属性与值，若为None或者大小为0则不更新\n where: 要更新的条件键值对，若为None或空字典更新整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"... | 单表更新
Args:
table_name: 要更新的表名
items: 要更新的属性与值，若为None或者大小为0则不更新
where: 要更新的条件键值对，若为None或空字典更新整个表或所有指定的colums条目，目前只能使用=判断
Return:
{"code": 200, "message": "success"}
Example:
update_items(table_name='person',
items={'name': 'Jay', 'age': 21},
where={'name': '周杰伦', 'age': 20}) | dao/crud.py | update_items | leexinhao/boya-backend | 0 | python | def update_items(table_name: str, items: Dict[(str, Union[(str, int, float)])], where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表更新\n Args:\n table_name: 要更新的表名\n items: 要更新的属性与值，若为None或者大小为0则不更新\n where: 要更新的条件键值对，若为None或空字典更新整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"... | def update_items(table_name: str, items: Dict[(str, Union[(str, int, float)])], where: Optional[Dict[(str, Union[(str, int, float)])]]=None) -> str:
'\n 单表更新\n Args:\n table_name: 要更新的表名\n items: 要更新的属性与值，若为None或者大小为0则不更新\n where: 要更新的条件键值对，若为None或空字典更新整个表或所有指定的colums条目，目前只能使用=判断\n Return:\n {"... |
1e6bed32b0a21551a8643aabc4b2934df50dc375eea32f283ae46800fd9def2c | def hold(unit: 'Unit', seperation: float, direction: float) -> None:
'This unit will never move'
unit.hold() | This unit will never move | src/stratgey.py | hold | alexdawn/battle-cogitator | 1 | python | def hold(unit: 'Unit', seperation: float, direction: float) -> None:
unit.hold() | def hold(unit: 'Unit', seperation: float, direction: float) -> None:
unit.hold()<|docstring|>This unit will never move<|endoftext|> |
53532cd40a3dcb5c9706879b54d4bab8cf388936c0dcf387e0c5462afaf941f8 | def slow_advance(unit: 'Unit', seperation: float, direction: float) -> None:
'This unit will move into range and hold'
if (seperation > unit.max_effective_range()):
unit.move(min(unit.unit_movement(), (seperation - unit.max_effective_range())), direction)
else:
unit.hold() | This unit will move into range and hold | src/stratgey.py | slow_advance | alexdawn/battle-cogitator | 1 | python | def slow_advance(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > unit.max_effective_range()):
unit.move(min(unit.unit_movement(), (seperation - unit.max_effective_range())), direction)
else:
unit.hold() | def slow_advance(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > unit.max_effective_range()):
unit.move(min(unit.unit_movement(), (seperation - unit.max_effective_range())), direction)
else:
unit.hold()<|docstring|>This unit will move into range and hold<|endoft... |
717862329067f809e3e10608dc3269043e89dce3299a82accab68bbfacc3282e | def charge(unit: 'Unit', seperation: float, direction: float) -> None:
'This unit will move, shoot and attempt to charge when in range'
if (seperation > (12 + unit.unit_movement())):
unit.move(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (sepera... | This unit will move, shoot and attempt to charge when in range | src/stratgey.py | charge | alexdawn/battle-cogitator | 1 | python | def charge(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > (12 + unit.unit_movement())):
unit.move(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (seperation - 1)), direction)
else:
unit.hold() | def charge(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > (12 + unit.unit_movement())):
unit.move(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (seperation - 1)), direction)
else:
unit.hold()<|docstring|... |
cf525eff76b4b67d244b6ffd44bf3f1751b0796ae973efc2a4781b52fdffa7da | def headlong_charge(unit: 'Unit', seperation: float, direction: float) -> None:
'This unit will move as fast as it can, then charge'
if (seperation > (12 + unit.unit_movement())):
unit.advance(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (sepera... | This unit will move as fast as it can, then charge | src/stratgey.py | headlong_charge | alexdawn/battle-cogitator | 1 | python | def headlong_charge(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > (12 + unit.unit_movement())):
unit.advance(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (seperation - 1)), direction)
else:
unit.hold() | def headlong_charge(unit: 'Unit', seperation: float, direction: float) -> None:
if (seperation > (12 + unit.unit_movement())):
unit.advance(unit.unit_movement(), direction)
elif (seperation > 1):
unit.move(min(unit.unit_movement(), (seperation - 1)), direction)
else:
unit.hold()... |
8e88f80c7e7efe52367fd44d6a58b8a6753f58d69c0849e5c49ae1bf2031135c | def keep_seperation(unit: 'Unit', seperation: float, direction: float) -> None:
'This unit will actively try and keep its range from enemies'
if unit.engaged:
unit.fall_back(unit.unit_movement(), (- direction))
elif (seperation < unit.max_effective_range()):
unit.move(min(unit.unit_movement(... | This unit will actively try and keep its range from enemies | src/stratgey.py | keep_seperation | alexdawn/battle-cogitator | 1 | python | def keep_seperation(unit: 'Unit', seperation: float, direction: float) -> None:
if unit.engaged:
unit.fall_back(unit.unit_movement(), (- direction))
elif (seperation < unit.max_effective_range()):
unit.move(min(unit.unit_movement(), (unit.max_effective_range() - seperation)), (- direction))... | def keep_seperation(unit: 'Unit', seperation: float, direction: float) -> None:
if unit.engaged:
unit.fall_back(unit.unit_movement(), (- direction))
elif (seperation < unit.max_effective_range()):
unit.move(min(unit.unit_movement(), (unit.max_effective_range() - seperation)), (- direction))... |
d022024079d6ecfba32ab14a0bb35bb5800f99fa49681d31abc787af055427c5 | def query(self, question):
'\n Args:\n - quesion (str) : utterance\n Return:\n result (dict) { \n "answers" (list) ,\n "ner_response" (list of dict),\n "answer_dislay" (list): \n }\n '
entities = self.ner.inferenc... | Args:
- quesion (str) : utterance
Return:
result (dict) {
"answers" (list) ,
"ner_response" (list of dict),
"answer_dislay" (list):
} | src/search_engine/entity_search.py | query | phamnam-mta/know-life | 0 | python | def query(self, question):
'\n Args:\n - quesion (str) : utterance\n Return:\n result (dict) { \n "answers" (list) ,\n "ner_response" (list of dict),\n "answer_dislay" (list): \n }\n '
entities = self.ner.inferenc... | def query(self, question):
'\n Args:\n - quesion (str) : utterance\n Return:\n result (dict) { \n "answers" (list) ,\n "ner_response" (list of dict),\n "answer_dislay" (list): \n }\n '
entities = self.ner.inferenc... |
4ff00235968a576c2c3d35946cc162876880dba1505e38919a569eb43a13636a | def query_single_entity(self, entity, relation):
'\n Return:\n - result (list)\n - kb_answer (list)\n '
results = []
scores = []
kb_answer = []
result = ''
for sample in self.database:
if (SYNONYM_KEY in sample):
for synonym in sample[SYNON... | Return:
- result (list)
- kb_answer (list) | src/search_engine/entity_search.py | query_single_entity | phamnam-mta/know-life | 0 | python | def query_single_entity(self, entity, relation):
'\n Return:\n - result (list)\n - kb_answer (list)\n '
results = []
scores = []
kb_answer = []
result =
for sample in self.database:
if (SYNONYM_KEY in sample):
for synonym in sample[SYNONYM... | def query_single_entity(self, entity, relation):
'\n Return:\n - result (list)\n - kb_answer (list)\n '
results = []
scores = []
kb_answer = []
result =
for sample in self.database:
if (SYNONYM_KEY in sample):
for synonym in sample[SYNONYM... |
d8216f21b56497bcba420a57d010f13e5a90a53de0bbd267dfbd846b02282ba3 | def main(args=None):
'The main routine.'
if (args is None):
args = sys.argv[1:]
app = TimecardGenerator()
app.run() | The main routine. | timecardgenerator/__main__.py | main | TBPixel/Sage300-TimecardGenerator | 0 | python | def main(args=None):
if (args is None):
args = sys.argv[1:]
app = TimecardGenerator()
app.run() | def main(args=None):
if (args is None):
args = sys.argv[1:]
app = TimecardGenerator()
app.run()<|docstring|>The main routine.<|endoftext|> |
2928013096e7dd225d4ece838f324e21920bfa88b5bb694c9412bc7ed7f8736c | async def set_isolation_level(self, connection, level):
'\n Given an asyncpg connection, set its isolation level.\n\n '
level = level.replace('_', ' ')
if (level not in self._isolation_lookup):
raise exc.ArgumentError(("Invalid value '%s' for isolation_level. Valid isolation levels for... | Given an asyncpg connection, set its isolation level. | src/gino/dialects/asyncpg.py | set_isolation_level | wwwjfy/gino | 1,376 | python | async def set_isolation_level(self, connection, level):
'\n \n\n '
level = level.replace('_', ' ')
if (level not in self._isolation_lookup):
raise exc.ArgumentError(("Invalid value '%s' for isolation_level. Valid isolation levels for %s are %s" % (level, self.name, ', '.join(self._isol... | async def set_isolation_level(self, connection, level):
'\n \n\n '
level = level.replace('_', ' ')
if (level not in self._isolation_lookup):
raise exc.ArgumentError(("Invalid value '%s' for isolation_level. Valid isolation levels for %s are %s" % (level, self.name, ', '.join(self._isol... |
e4ced2191b0fb960d9b0c98b3ea4ad963479e4f3388030c56faccf8b44af30c2 | async def get_isolation_level(self, connection):
'\n Given an asyncpg connection, return its isolation level.\n\n '
val = (await connection.fetchval('show transaction isolation level'))
return val.upper() | Given an asyncpg connection, return its isolation level. | src/gino/dialects/asyncpg.py | get_isolation_level | wwwjfy/gino | 1,376 | python | async def get_isolation_level(self, connection):
'\n \n\n '
val = (await connection.fetchval('show transaction isolation level'))
return val.upper() | async def get_isolation_level(self, connection):
'\n \n\n '
val = (await connection.fetchval('show transaction isolation level'))
return val.upper()<|docstring|>Given an asyncpg connection, return its isolation level.<|endoftext|> |
a2171c156266c597b6bf0d5f5ae01ab2d9b0a9d3973cfdc57fba9080a490220a | def _temporal_cross_entropy_loss(logits, labels, label_lengths, mx_seq_length):
'Do cross-entropy loss accounting for sequence lengths\n\n :param logits: a `Tensor` with shape `[timesteps, batch, timesteps, vocab]`\n :param labels: an integer `Tensor` with shape `[batch, timesteps]`\n :param label_lengths:... | Do cross-entropy loss accounting for sequence lengths
:param logits: a `Tensor` with shape `[timesteps, batch, timesteps, vocab]`
:param labels: an integer `Tensor` with shape `[batch, timesteps]`
:param label_lengths: The actual length of the target text. Assume right-padded
:param mx_seq_length: The maximum length ... | baseline/tf/seq2seq/model.py | _temporal_cross_entropy_loss | sagnik/baseline | 20 | python | def _temporal_cross_entropy_loss(logits, labels, label_lengths, mx_seq_length):
'Do cross-entropy loss accounting for sequence lengths\n\n :param logits: a `Tensor` with shape `[timesteps, batch, timesteps, vocab]`\n :param labels: an integer `Tensor` with shape `[batch, timesteps]`\n :param label_lengths:... | def _temporal_cross_entropy_loss(logits, labels, label_lengths, mx_seq_length):
'Do cross-entropy loss accounting for sequence lengths\n\n :param logits: a `Tensor` with shape `[timesteps, batch, timesteps, vocab]`\n :param labels: an integer `Tensor` with shape `[batch, timesteps]`\n :param label_lengths:... |
41afc2ae8a3101ea12a6bbf9429ce206d167bdb4b827a659c9a23d0e7a33b094 | def embed(self, inputs):
'This method performs "embedding" of the inputs. The base method here then concatenates along depth\n dimension to form word embeddings\n\n :return: A 3-d vector where the last dimension is the concatenated dimensions of all embeddings\n '
return self.s... | This method performs "embedding" of the inputs. The base method here then concatenates along depth
dimension to form word embeddings
:return: A 3-d vector where the last dimension is the concatenated dimensions of all embeddings | baseline/tf/seq2seq/model.py | embed | sagnik/baseline | 20 | python | def embed(self, inputs):
'This method performs "embedding" of the inputs. The base method here then concatenates along depth\n dimension to form word embeddings\n\n :return: A 3-d vector where the last dimension is the concatenated dimensions of all embeddings\n '
return self.s... | def embed(self, inputs):
'This method performs "embedding" of the inputs. The base method here then concatenates along depth\n dimension to form word embeddings\n\n :return: A 3-d vector where the last dimension is the concatenated dimensions of all embeddings\n '
return self.s... |
98c1620715b9bc0efe4cb54fabd0ab99655f4c7ecdb9df818f412d67614e6cfa | def step(self, batch_dict):
'\n Generate probability distribution over output V for next token\n '
feed_dict = self.make_input(batch_dict)
x = self.sess.run(self.decoder.probs, feed_dict=feed_dict)
return x | Generate probability distribution over output V for next token | baseline/tf/seq2seq/model.py | step | sagnik/baseline | 20 | python | def step(self, batch_dict):
'\n \n '
feed_dict = self.make_input(batch_dict)
x = self.sess.run(self.decoder.probs, feed_dict=feed_dict)
return x | def step(self, batch_dict):
'\n \n '
feed_dict = self.make_input(batch_dict)
x = self.sess.run(self.decoder.probs, feed_dict=feed_dict)
return x<|docstring|>Generate probability distribution over output V for next token<|endoftext|> |
60c6394c275aea106db9cf9ac7c5dfabad4e6585497c0f9c9326a1d74a5f1942 | def make_input(self, batch_dict: Dict[(str, TensorDef)], train: bool=False) -> Dict[(str, TensorDef)]:
'Transform a `batch_dict` into format suitable for tagging\n :param batch_dict: (``dict``) A dictionary containing all inputs to the embeddings for this model\n :param train: (``bool``) Are w... | Transform a `batch_dict` into format suitable for tagging
:param batch_dict: (``dict``) A dictionary containing all inputs to the embeddings for this model
:param train: (``bool``) Are we training. Defaults to False
:return: A dictionary representation of this batch suitable for processing | baseline/tf/seq2seq/model.py | make_input | sagnik/baseline | 20 | python | def make_input(self, batch_dict: Dict[(str, TensorDef)], train: bool=False) -> Dict[(str, TensorDef)]:
'Transform a `batch_dict` into format suitable for tagging\n :param batch_dict: (``dict``) A dictionary containing all inputs to the embeddings for this model\n :param train: (``bool``) Are w... | def make_input(self, batch_dict: Dict[(str, TensorDef)], train: bool=False) -> Dict[(str, TensorDef)]:
'Transform a `batch_dict` into format suitable for tagging\n :param batch_dict: (``dict``) A dictionary containing all inputs to the embeddings for this model\n :param train: (``bool``) Are w... |
53252b07e24f1452c391dc3bd9462164285a6c29e58b0e57906f8c46c3c7f17a | def drop_inputs(self, key, x, do_dropout):
'Do dropout on inputs, using the dropout value (or none if not set)\n This works by applying a dropout mask with the probability given by a\n value within the `dropin_value: Dict[str, float]`, keyed off the text name\n of the feature\n ... | Do dropout on inputs, using the dropout value (or none if not set)
This works by applying a dropout mask with the probability given by a
value within the `dropin_value: Dict[str, float]`, keyed off the text name
of the feature
:param key: The feature name
:param x: The tensor to drop inputs for
:param do_dropout: A `bo... | baseline/tf/seq2seq/model.py | drop_inputs | sagnik/baseline | 20 | python | def drop_inputs(self, key, x, do_dropout):
'Do dropout on inputs, using the dropout value (or none if not set)\n This works by applying a dropout mask with the probability given by a\n value within the `dropin_value: Dict[str, float]`, keyed off the text name\n of the feature\n ... | def drop_inputs(self, key, x, do_dropout):
'Do dropout on inputs, using the dropout value (or none if not set)\n This works by applying a dropout mask with the probability given by a\n value within the `dropin_value: Dict[str, float]`, keyed off the text name\n of the feature\n ... |
4808f044382012b34fda9725f665d3e444947ef9625b7df3863509da81e92371 | def init_embed(self, src_embeddings, tgt_embedding, **kwargs):
'This is the hook for providing embeddings. It takes in a dictionary of `src_embeddings` and a single\n tgt_embedding` of type `PyTorchEmbedding`\n :param src_embeddings: (``dict``) A dictionary of PyTorchEmbeddings, one per embed... | This is the hook for providing embeddings. It takes in a dictionary of `src_embeddings` and a single
tgt_embedding` of type `PyTorchEmbedding`
:param src_embeddings: (``dict``) A dictionary of PyTorchEmbeddings, one per embedding
:param tgt_embedding: (``PyTorchEmbeddings``) A single PyTorchEmbeddings object
:param kw... | baseline/tf/seq2seq/model.py | init_embed | sagnik/baseline | 20 | python | def init_embed(self, src_embeddings, tgt_embedding, **kwargs):
'This is the hook for providing embeddings. It takes in a dictionary of `src_embeddings` and a single\n tgt_embedding` of type `PyTorchEmbedding`\n :param src_embeddings: (``dict``) A dictionary of PyTorchEmbeddings, one per embed... | def init_embed(self, src_embeddings, tgt_embedding, **kwargs):
'This is the hook for providing embeddings. It takes in a dictionary of `src_embeddings` and a single\n tgt_embedding` of type `PyTorchEmbedding`\n :param src_embeddings: (``dict``) A dictionary of PyTorchEmbeddings, one per embed... |
3ba01c0372179dfe29e9add56b2c56492b5fff127632f3b5fbf11db779319b98 | def encode(self, input, lengths):
'\n\n :param input:\n :param lengths:\n :return:\n '
embed_in_seq = self.embed(input)
return self.encoder((embed_in_seq, lengths)) | :param input:
:param lengths:
:return: | baseline/tf/seq2seq/model.py | encode | sagnik/baseline | 20 | python | def encode(self, input, lengths):
'\n\n :param input:\n :param lengths:\n :return:\n '
embed_in_seq = self.embed(input)
return self.encoder((embed_in_seq, lengths)) | def encode(self, input, lengths):
'\n\n :param input:\n :param lengths:\n :return:\n '
embed_in_seq = self.embed(input)
return self.encoder((embed_in_seq, lengths))<|docstring|>:param input:
:param lengths:
:return:<|endoftext|> |
b0ea69133d551a41fb231c17aa0e46dd9c2a316d4d4e9c7525a2fde6ec31b0a6 | def save_values(self, basename):
'Save tensor files out\n\n :param basename: Base name of model\n :return:\n '
self.save_weights(f'{basename}.wgt') | Save tensor files out
:param basename: Base name of model
:return: | baseline/tf/seq2seq/model.py | save_values | sagnik/baseline | 20 | python | def save_values(self, basename):
'Save tensor files out\n\n :param basename: Base name of model\n :return:\n '
self.save_weights(f'{basename}.wgt') | def save_values(self, basename):
'Save tensor files out\n\n :param basename: Base name of model\n :return:\n '
self.save_weights(f'{basename}.wgt')<|docstring|>Save tensor files out
:param basename: Base name of model
:return:<|endoftext|> |
fb1f9765c85be169387777bed544012ab45a9ce2ca50ebc4d16faaf9be3927cd | def predict(self, inputs, **kwargs):
'Predict based on the batch.\n\n If `make_input` is True then run make_input on the batch_dict.\n This is false for being used during dev eval where the inputs\n are already transformed.\n '
SET_TRAIN_FLAG(False)
make = kwargs.... | Predict based on the batch.
If `make_input` is True then run make_input on the batch_dict.
This is false for being used during dev eval where the inputs
are already transformed. | baseline/tf/seq2seq/model.py | predict | sagnik/baseline | 20 | python | def predict(self, inputs, **kwargs):
'Predict based on the batch.\n\n If `make_input` is True then run make_input on the batch_dict.\n This is false for being used during dev eval where the inputs\n are already transformed.\n '
SET_TRAIN_FLAG(False)
make = kwargs.... | def predict(self, inputs, **kwargs):
'Predict based on the batch.\n\n If `make_input` is True then run make_input on the batch_dict.\n This is false for being used during dev eval where the inputs\n are already transformed.\n '
SET_TRAIN_FLAG(False)
make = kwargs.... |
776678b78f288945264cfec4e26787b46bb594ddb75d3a53aa20f2973e57db83 | def __init__(self, src_embeddings, tgt_embedding, **kwargs):
'This base model is extensible for attention and other uses. It declares minimal fields allowing the\n subclass to take over most of the duties for drastically different implementations\n\n :param src_embeddings: (``dict``) A dictio... | This base model is extensible for attention and other uses. It declares minimal fields allowing the
subclass to take over most of the duties for drastically different implementations
:param src_embeddings: (``dict``) A dictionary of PyTorchEmbeddings
:param tgt_embedding: (``PyTorchEmbeddings``) A single PyTorchEmbed... | baseline/tf/seq2seq/model.py | __init__ | sagnik/baseline | 20 | python | def __init__(self, src_embeddings, tgt_embedding, **kwargs):
'This base model is extensible for attention and other uses. It declares minimal fields allowing the\n subclass to take over most of the duties for drastically different implementations\n\n :param src_embeddings: (``dict``) A dictio... | def __init__(self, src_embeddings, tgt_embedding, **kwargs):
'This base model is extensible for attention and other uses. It declares minimal fields allowing the\n subclass to take over most of the duties for drastically different implementations\n\n :param src_embeddings: (``dict``) A dictio... |
4c9f50890162355adfa88ddf3cebbf14163b90bfc631e9dc94e649f53e47c89e | def __init__(self, sync_async_store: pa.PersistenceAdaptor=None, work_description_store: pa.PersistenceAdaptor=None, resynchroniser: sync_async_resynchroniser.SyncAsyncResynchroniser=None):
'Create a new SyncAsyncWorkflow that uses the specified dependencies to load config, build a message and\n send it.\n ... | Create a new SyncAsyncWorkflow that uses the specified dependencies to load config, build a message and
send it.
:param sync_async_store: The resynchronisor state store
:param work_description_store: The persistence store instance that holds the work description data
:param sync_async_store_retry_delay: time between sy... | mhs/common/mhs_common/workflow/sync_async.py | __init__ | petervdm/integration-adaptors | 15 | python | def __init__(self, sync_async_store: pa.PersistenceAdaptor=None, work_description_store: pa.PersistenceAdaptor=None, resynchroniser: sync_async_resynchroniser.SyncAsyncResynchroniser=None):
'Create a new SyncAsyncWorkflow that uses the specified dependencies to load config, build a message and\n send it.\n ... | def __init__(self, sync_async_store: pa.PersistenceAdaptor=None, work_description_store: pa.PersistenceAdaptor=None, resynchroniser: sync_async_resynchroniser.SyncAsyncResynchroniser=None):
'Create a new SyncAsyncWorkflow that uses the specified dependencies to load config, build a message and\n send it.\n ... |
357fdc1a79e085b5318336d553e4bfe46bb00ad1166053a91cf5e7750d33b302 | @pytest.mark.parametrize('code,expected_kinds', [['def fun(a): pass', [POSITIONAL_OR_KEYWORD]], ['def fun(a, b): pass', ([POSITIONAL_OR_KEYWORD] * 2)], ['def fun(a, b, /): pass', ([POSITIONAL_ONLY] * 2)], ['def fun(a, b, /, c): pass', [POSITIONAL_ONLY, POSITIONAL_ONLY, POSITIONAL_OR_KEYWORD]], ['def fun(a, b, *args): p... | Tests that it processes argument names correctly | tests/utils/test_get_argument_kinds.py | test_it_processes_argument_kinds_correctly | marco-rubio/sphinx-ast-autodoc | 0 | python | @pytest.mark.parametrize('code,expected_kinds', [['def fun(a): pass', [POSITIONAL_OR_KEYWORD]], ['def fun(a, b): pass', ([POSITIONAL_OR_KEYWORD] * 2)], ['def fun(a, b, /): pass', ([POSITIONAL_ONLY] * 2)], ['def fun(a, b, /, c): pass', [POSITIONAL_ONLY, POSITIONAL_ONLY, POSITIONAL_OR_KEYWORD]], ['def fun(a, b, *args): p... | @pytest.mark.parametrize('code,expected_kinds', [['def fun(a): pass', [POSITIONAL_OR_KEYWORD]], ['def fun(a, b): pass', ([POSITIONAL_OR_KEYWORD] * 2)], ['def fun(a, b, /): pass', ([POSITIONAL_ONLY] * 2)], ['def fun(a, b, /, c): pass', [POSITIONAL_ONLY, POSITIONAL_ONLY, POSITIONAL_OR_KEYWORD]], ['def fun(a, b, *args): p... |
70e34169b2a38de9bf7e043b5ca89f0137d559afe54db66d2d30e573adc1615d | def cleanup(self) -> None:
' Closes the database connection'
self.conn.close() | Closes the database connection | postr/schedule/reader.py | cleanup | dbgrigsby/Postr | 3 | python | def cleanup(self) -> None:
' '
self.conn.close() | def cleanup(self) -> None:
' '
self.conn.close()<|docstring|>Closes the database connection<|endoftext|> |
4a1bb8d66283ea1d7c030965067ad7910aee6779bd00a92fdb17e43e7645f72c | @classmethod
def now(cls) -> int:
' Returns the current time '
return int(dt.now().timestamp()) | Returns the current time | postr/schedule/reader.py | now | dbgrigsby/Postr | 3 | python | @classmethod
def now(cls) -> int:
' '
return int(dt.now().timestamp()) | @classmethod
def now(cls) -> int:
' '
return int(dt.now().timestamp())<|docstring|>Returns the current time<|endoftext|> |
79b18950d81c10b11ec06d040dc69dbb45f5e1e92cf56c83cc3f26f691bcb715 | def scan_custom_jobs(self, seconds: int=30) -> List[Dict[(str, Any)]]:
" Scans jobs every 'seconds' seconds, and returns a JSON\n object representing any jobs to be operated on "
lower = self.schedule_range(seconds)
upper = self.now()
self.cursor.execute(f'''SELECT * FROM CustomJob
... | Scans jobs every 'seconds' seconds, and returns a JSON
object representing any jobs to be operated on | postr/schedule/reader.py | scan_custom_jobs | dbgrigsby/Postr | 3 | python | def scan_custom_jobs(self, seconds: int=30) -> List[Dict[(str, Any)]]:
" Scans jobs every 'seconds' seconds, and returns a JSON\n object representing any jobs to be operated on "
lower = self.schedule_range(seconds)
upper = self.now()
self.cursor.execute(f'SELECT * FROM CustomJob
... | def scan_custom_jobs(self, seconds: int=30) -> List[Dict[(str, Any)]]:
" Scans jobs every 'seconds' seconds, and returns a JSON\n object representing any jobs to be operated on "
lower = self.schedule_range(seconds)
upper = self.now()
self.cursor.execute(f'SELECT * FROM CustomJob
... |
a5884fa5bcf6951099f00b115af1b0e2c11fafa09dc2cb12754892e95ea5ef91 | async def scan(self) -> Any:
' Scans every 30 seconds for new jobs in the past 30 seconds '
while True:
time.sleep(30)
tasks = self.scan_custom_jobs()
cleaned_tasks = [clean_empty_strings(task) for task in tasks]
(await process_scheduler_events(cleaned_tasks)) | Scans every 30 seconds for new jobs in the past 30 seconds | postr/schedule/reader.py | scan | dbgrigsby/Postr | 3 | python | async def scan(self) -> Any:
' '
while True:
time.sleep(30)
tasks = self.scan_custom_jobs()
cleaned_tasks = [clean_empty_strings(task) for task in tasks]
(await process_scheduler_events(cleaned_tasks)) | async def scan(self) -> Any:
' '
while True:
time.sleep(30)
tasks = self.scan_custom_jobs()
cleaned_tasks = [clean_empty_strings(task) for task in tasks]
(await process_scheduler_events(cleaned_tasks))<|docstring|>Scans every 30 seconds for new jobs in the past 30 seconds<|endof... |
b22cc9fc586aca663d241a9c3e3ff3dae8467f8da787ad4a0cd13f84b6393054 | def schedule_range(self, seconds: int) -> int:
' Returns the lower bound for a scheduled range '
now = self.now()
return (now - seconds) | Returns the lower bound for a scheduled range | postr/schedule/reader.py | schedule_range | dbgrigsby/Postr | 3 | python | def schedule_range(self, seconds: int) -> int:
' '
now = self.now()
return (now - seconds) | def schedule_range(self, seconds: int) -> int:
' '
now = self.now()
return (now - seconds)<|docstring|>Returns the lower bound for a scheduled range<|endoftext|> |
e4156cf88966d6c07b164c274db63df3fbc0f1b0832592eaaf0e25e940bd902e | def degree_prune(graph, max_degree=20):
'Prune the k-neighbors graph back so that nodes have a maximum\n degree of ``max_degree``.\n\n Parameters\n ----------\n graph: sparse matrix\n The adjacency matrix of the graph\n\n max_degree: int (optional, default 20)\n The maximum degree of an... | Prune the k-neighbors graph back so that nodes have a maximum
degree of ``max_degree``.
Parameters
----------
graph: sparse matrix
The adjacency matrix of the graph
max_degree: int (optional, default 20)
The maximum degree of any node in the pruned graph
Returns
-------
result: sparse matrix
The pruned g... | pynndescent/pynndescent_.py | degree_prune | yupbank/pynndescent | 0 | python | def degree_prune(graph, max_degree=20):
'Prune the k-neighbors graph back so that nodes have a maximum\n degree of ``max_degree``.\n\n Parameters\n ----------\n graph: sparse matrix\n The adjacency matrix of the graph\n\n max_degree: int (optional, default 20)\n The maximum degree of an... | def degree_prune(graph, max_degree=20):
'Prune the k-neighbors graph back so that nodes have a maximum\n degree of ``max_degree``.\n\n Parameters\n ----------\n graph: sparse matrix\n The adjacency matrix of the graph\n\n max_degree: int (optional, default 20)\n The maximum degree of an... |
1a7f81a6949a263866c54ee8b810bc0a6ac849a6f0a61bcee932829362bf35ea | def prune(graph, prune_level=0, n_neighbors=10):
'Perform pruning on the graph so that there are fewer edges to\n be followed. In practice this operates in two passes. The first pass\n removes edges such that no node has degree more than ``3 * n_neighbors -\n prune_level``. The second pass builds up a grap... | Perform pruning on the graph so that there are fewer edges to
be followed. In practice this operates in two passes. The first pass
removes edges such that no node has degree more than ``3 * n_neighbors -
prune_level``. The second pass builds up a graph out of spanning trees;
each iteration constructs a minimum panning ... | pynndescent/pynndescent_.py | prune | yupbank/pynndescent | 0 | python | def prune(graph, prune_level=0, n_neighbors=10):
'Perform pruning on the graph so that there are fewer edges to\n be followed. In practice this operates in two passes. The first pass\n removes edges such that no node has degree more than ``3 * n_neighbors -\n prune_level``. The second pass builds up a grap... | def prune(graph, prune_level=0, n_neighbors=10):
'Perform pruning on the graph so that there are fewer edges to\n be followed. In practice this operates in two passes. The first pass\n removes edges such that no node has degree more than ``3 * n_neighbors -\n prune_level``. The second pass builds up a grap... |
fbbb6baa7b83d7a47ad2ca75911f7c30fad0155927346b32a6dc2bc964415cb8 | def query(self, query_data, k=10, queue_size=5.0):
'Query the training data for the k nearest neighbors\n\n Parameters\n ----------\n query_data: array-like, last dimension self.dim\n An array of points to query\n\n k: integer (default = 10)\n The number of nearest ... | Query the training data for the k nearest neighbors
Parameters
----------
query_data: array-like, last dimension self.dim
An array of points to query
k: integer (default = 10)
The number of nearest neighbors to return
queue_size: float (default 5.0)
The multiplier of the internal search queue. This contr... | pynndescent/pynndescent_.py | query | yupbank/pynndescent | 0 | python | def query(self, query_data, k=10, queue_size=5.0):
'Query the training data for the k nearest neighbors\n\n Parameters\n ----------\n query_data: array-like, last dimension self.dim\n An array of points to query\n\n k: integer (default = 10)\n The number of nearest ... | def query(self, query_data, k=10, queue_size=5.0):
'Query the training data for the k nearest neighbors\n\n Parameters\n ----------\n query_data: array-like, last dimension self.dim\n An array of points to query\n\n k: integer (default = 10)\n The number of nearest ... |
e08d055a05280624476f0c88a5f89036e2b54c87e44553bc2c71225ff5cbad8f | def fit(self, X):
'Fit the PyNNDescent transformer to build KNN graphs with\n neighbors given by the dataset X.\n\n Parameters\n ----------\n X : array-like, shape (n_samples, n_features)\n Sample data\n\n Returns\n -------\n transformer : PyNNDescentTrans... | Fit the PyNNDescent transformer to build KNN graphs with
neighbors given by the dataset X.
Parameters
----------
X : array-like, shape (n_samples, n_features)
Sample data
Returns
-------
transformer : PyNNDescentTransformer
The trained transformer | pynndescent/pynndescent_.py | fit | yupbank/pynndescent | 0 | python | def fit(self, X):
'Fit the PyNNDescent transformer to build KNN graphs with\n neighbors given by the dataset X.\n\n Parameters\n ----------\n X : array-like, shape (n_samples, n_features)\n Sample data\n\n Returns\n -------\n transformer : PyNNDescentTrans... | def fit(self, X):
'Fit the PyNNDescent transformer to build KNN graphs with\n neighbors given by the dataset X.\n\n Parameters\n ----------\n X : array-like, shape (n_samples, n_features)\n Sample data\n\n Returns\n -------\n transformer : PyNNDescentTrans... |
6da5d2922c15e5c3ef1eea1ac8f7f9cf7bec8a90b987a0ac5097435fb67a67ed | def transform(self, X, y=None):
'Computes the (weighted) graph of Neighbors for points in X\n\n Parameters\n ----------\n X : array-like, shape (n_samples_transform, n_features)\n Sample data\n\n Returns\n -------\n Xt : CSR sparse matrix, shape (n_samples_fit, n... | Computes the (weighted) graph of Neighbors for points in X
Parameters
----------
X : array-like, shape (n_samples_transform, n_features)
Sample data
Returns
-------
Xt : CSR sparse matrix, shape (n_samples_fit, n_samples_transform)
Xt[i, j] is assigned the weight of edge that connects i to j.
Only the nei... | pynndescent/pynndescent_.py | transform | yupbank/pynndescent | 0 | python | def transform(self, X, y=None):
'Computes the (weighted) graph of Neighbors for points in X\n\n Parameters\n ----------\n X : array-like, shape (n_samples_transform, n_features)\n Sample data\n\n Returns\n -------\n Xt : CSR sparse matrix, shape (n_samples_fit, n... | def transform(self, X, y=None):
'Computes the (weighted) graph of Neighbors for points in X\n\n Parameters\n ----------\n X : array-like, shape (n_samples_transform, n_features)\n Sample data\n\n Returns\n -------\n Xt : CSR sparse matrix, shape (n_samples_fit, n... |
8ed833a7428b3b126a3cd0e9226e4222164b49e6680613c6591906e19ce1a827 | def fit_transform(self, X, y=None, **fit_params):
'Fit to data, then transform it.\n\n Fits transformer to X and y with optional parameters fit_params\n and returns a transformed version of X.\n\n Parameters\n ----------\n X : numpy array of shape (n_samples, n_features)\n ... | Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params
and returns a transformed version of X.
Parameters
----------
X : numpy array of shape (n_samples, n_features)
Training set.
y : ignored
Returns
-------
Xt : CSR sparse matrix, shape (n_samples, n_samples)
Xt[i, ... | pynndescent/pynndescent_.py | fit_transform | yupbank/pynndescent | 0 | python | def fit_transform(self, X, y=None, **fit_params):
'Fit to data, then transform it.\n\n Fits transformer to X and y with optional parameters fit_params\n and returns a transformed version of X.\n\n Parameters\n ----------\n X : numpy array of shape (n_samples, n_features)\n ... | def fit_transform(self, X, y=None, **fit_params):
'Fit to data, then transform it.\n\n Fits transformer to X and y with optional parameters fit_params\n and returns a transformed version of X.\n\n Parameters\n ----------\n X : numpy array of shape (n_samples, n_features)\n ... |
31a3c86890022d77e9ffeb480a7effe2f34bbc19c422c975fb59cb2b92b00597 | def encrypt_text(text: StrOrBytes, password: str=None) -> bytes:
'Encrypts text.\n\n Args:\n text (StrOrBytes): text to encrypt.\n password (str, optional): password to encrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Returns:\n bytes: text encr... | Encrypts text.
Args:
text (StrOrBytes): text to encrypt.
password (str, optional): password to encrypt the file. If None,
the user will have to type it. Defaults to None.
Returns:
bytes: text encrypted. | aes/text.py | encrypt_text | sralloza/aes | 0 | python | def encrypt_text(text: StrOrBytes, password: str=None) -> bytes:
'Encrypts text.\n\n Args:\n text (StrOrBytes): text to encrypt.\n password (str, optional): password to encrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Returns:\n bytes: text encr... | def encrypt_text(text: StrOrBytes, password: str=None) -> bytes:
'Encrypts text.\n\n Args:\n text (StrOrBytes): text to encrypt.\n password (str, optional): password to encrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Returns:\n bytes: text encr... |
31b67c8db9635f71ac129e8ddfa7b892dfb6eab16ad919dbef85e2be0075033c | def decrypt_text(text: StrOrBytes, password: str=None) -> bytes:
"Decrypts text.\n\n Args:\n text (StrOrBytes): text to decrypt.\n password (str, optional): password to decrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Raises:\n IncorrectPassword... | Decrypts text.
Args:
text (StrOrBytes): text to decrypt.
password (str, optional): password to decrypt the file. If None,
the user will have to type it. Defaults to None.
Raises:
IncorrectPasswordError: if the AES algorithm doesn't work due
to an incorrect password.
Returns:
bytes: te... | aes/text.py | decrypt_text | sralloza/aes | 0 | python | def decrypt_text(text: StrOrBytes, password: str=None) -> bytes:
"Decrypts text.\n\n Args:\n text (StrOrBytes): text to decrypt.\n password (str, optional): password to decrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Raises:\n IncorrectPassword... | def decrypt_text(text: StrOrBytes, password: str=None) -> bytes:
"Decrypts text.\n\n Args:\n text (StrOrBytes): text to decrypt.\n password (str, optional): password to decrypt the file. If None,\n the user will have to type it. Defaults to None.\n\n Raises:\n IncorrectPassword... |
690ce9ed801ce1436c042d68474c46ff8ae9fdc4d8df627c04efec07c263d814 | def remediate(session, alert, lambda_context):
'\n Main Function invoked by index_prisma.py\n '
resource = None
region = alert['region']
ec2 = session.client('ec2', region_name=region)
try:
eips = ec2.describe_addresses()['Addresses']
except ClientError as e:
print(e.response['... | Main Function invoked by index_prisma.py | AWS/lambda_package/runbooks/AWS-VPC-013.py | remediate | nathanawmk/Prisma-Enhanced-Remediation | 34 | python | def remediate(session, alert, lambda_context):
'\n \n '
resource = None
region = alert['region']
ec2 = session.client('ec2', region_name=region)
try:
eips = ec2.describe_addresses()['Addresses']
except ClientError as e:
print(e.response['Error']['Message'])
return
u... | def remediate(session, alert, lambda_context):
'\n \n '
resource = None
region = alert['region']
ec2 = session.client('ec2', region_name=region)
try:
eips = ec2.describe_addresses()['Addresses']
except ClientError as e:
print(e.response['Error']['Message'])
return
u... |
7a5685afdbc6c16a7b3f67a4dc58adf26bcad7233e335d8470d87fa4a458cfdc | def __init__(self, temboo_session):
'\n Create a new instance of the SpacialFeaturesSearch Choreo. A TembooSession object, containing a valid\n set of Temboo credentials, must be supplied.\n '
super(SpacialFeaturesSearch, self).__init__(temboo_session, '/Library/UnlockPlaces/SpacialFeatures... | Create a new instance of the SpacialFeaturesSearch Choreo. A TembooSession object, containing a valid
set of Temboo credentials, must be supplied. | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | __init__ | jordanemedlock/psychtruths | 7 | python | def __init__(self, temboo_session):
'\n Create a new instance of the SpacialFeaturesSearch Choreo. A TembooSession object, containing a valid\n set of Temboo credentials, must be supplied.\n '
super(SpacialFeaturesSearch, self).__init__(temboo_session, '/Library/UnlockPlaces/SpacialFeatures... | def __init__(self, temboo_session):
'\n Create a new instance of the SpacialFeaturesSearch Choreo. A TembooSession object, containing a valid\n set of Temboo credentials, must be supplied.\n '
super(SpacialFeaturesSearch, self).__init__(temboo_session, '/Library/UnlockPlaces/SpacialFeatures... |
93b4fb65117e0e32903881110e7cac5357f35fd9fc9a046931069a72a155f47d | def set_FeatureType(self, value):
'\n Set the value of the FeatureType input for this Choreo. ((string) The feature type that the place is (i.e. "Cities"). See http://unlock.edina.ac.uk/ws/supportedFeatureTypes?format=txt for a complete list of supported Feature Types.)\n '
super(SpacialFeaturesSe... | Set the value of the FeatureType input for this Choreo. ((string) The feature type that the place is (i.e. "Cities"). See http://unlock.edina.ac.uk/ws/supportedFeatureTypes?format=txt for a complete list of supported Feature Types.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_FeatureType | jordanemedlock/psychtruths | 7 | python | def set_FeatureType(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('FeatureType', value) | def set_FeatureType(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('FeatureType', value)<|docstring|>Set the value of the FeatureType input for this Choreo. ((string) The feature type that the place is (i.e. "Cities"). See http://unlock.edina.ac.uk/ws/supportedFeature... |
8bbfb53f4977627b1ff94b74a65b017000cec138a71276ed547115ed6d95ba0f | def set_Format(self, value):
'\n Set the value of the Format input for this Choreo. ((optional, string) The format of the place search results. One of xml, kml, json, georss or txt. Defaults to "xml".)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Format', value) | Set the value of the Format input for this Choreo. ((optional, string) The format of the place search results. One of xml, kml, json, georss or txt. Defaults to "xml".) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_Format | jordanemedlock/psychtruths | 7 | python | def set_Format(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Format', value) | def set_Format(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Format', value)<|docstring|>Set the value of the Format input for this Choreo. ((optional, string) The format of the place search results. One of xml, kml, json, georss or txt. Defaults to "xml".)<|endofte... |
a5b0ffdc8c39c8a5e823d85e3e9d3d7480492d239337ae659aa6e91fb3e9bce4 | def set_Gazetteer(self, value):
'\n Set the value of the Gazetteer input for this Choreo. ((optional, string) The place-name source to take locations from. The options are geonames, os, naturalearth or unlock which combines all the previous. Defaults to "unlock".)\n '
super(SpacialFeaturesSearchIn... | Set the value of the Gazetteer input for this Choreo. ((optional, string) The place-name source to take locations from. The options are geonames, os, naturalearth or unlock which combines all the previous. Defaults to "unlock".) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_Gazetteer | jordanemedlock/psychtruths | 7 | python | def set_Gazetteer(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Gazetteer', value) | def set_Gazetteer(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Gazetteer', value)<|docstring|>Set the value of the Gazetteer input for this Choreo. ((optional, string) The place-name source to take locations from. The options are geonames, os, naturalearth or unloc... |
0d57d6e7a84b11f0ec30b6c6e5827829bad8a45b696af1ff855b27cb6ae91187 | def set_MaxLatitude(self, value):
'\n Set the value of the MaxLatitude input for this Choreo. ((decimal) The maximum latitude point of a bounding box.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLatitude', value) | Set the value of the MaxLatitude input for this Choreo. ((decimal) The maximum latitude point of a bounding box.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_MaxLatitude | jordanemedlock/psychtruths | 7 | python | def set_MaxLatitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLatitude', value) | def set_MaxLatitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLatitude', value)<|docstring|>Set the value of the MaxLatitude input for this Choreo. ((decimal) The maximum latitude point of a bounding box.)<|endoftext|> |
75e30e7c1fba1fb59d468c3220f6a3a83f56195a3e638aaa669fe0622c2f3a3f | def set_MaxLongitude(self, value):
'\n Set the value of the MaxLongitude input for this Choreo. ((decimal) The maximum longitude point of a bounding box.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLongitude', value) | Set the value of the MaxLongitude input for this Choreo. ((decimal) The maximum longitude point of a bounding box.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_MaxLongitude | jordanemedlock/psychtruths | 7 | python | def set_MaxLongitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLongitude', value) | def set_MaxLongitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxLongitude', value)<|docstring|>Set the value of the MaxLongitude input for this Choreo. ((decimal) The maximum longitude point of a bounding box.)<|endoftext|> |
45094b63cc4e5d0ed743f2f2b363da83f2db02bcb246475fe7fcf0fb6c49b081 | def set_MaxRows(self, value):
'\n Set the value of the MaxRows input for this Choreo. ((optional, integer) The maximum number of results to return. Defaults to 20. Cannot exceed 1000.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxRows', value) | Set the value of the MaxRows input for this Choreo. ((optional, integer) The maximum number of results to return. Defaults to 20. Cannot exceed 1000.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_MaxRows | jordanemedlock/psychtruths | 7 | python | def set_MaxRows(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxRows', value) | def set_MaxRows(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MaxRows', value)<|docstring|>Set the value of the MaxRows input for this Choreo. ((optional, integer) The maximum number of results to return. Defaults to 20. Cannot exceed 1000.)<|endoftext|> |
6d4d15b6d9b2549c9a8faa9458e322b6cb234e4a2833d6ff1cc101bf7427dc65 | def set_MinLatitude(self, value):
'\n Set the value of the MinLatitude input for this Choreo. ((decimal) The minimum latitude point of a bounding box.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLatitude', value) | Set the value of the MinLatitude input for this Choreo. ((decimal) The minimum latitude point of a bounding box.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_MinLatitude | jordanemedlock/psychtruths | 7 | python | def set_MinLatitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLatitude', value) | def set_MinLatitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLatitude', value)<|docstring|>Set the value of the MinLatitude input for this Choreo. ((decimal) The minimum latitude point of a bounding box.)<|endoftext|> |
e638407d4e8f71ab64f5f236e4507e46fb351a287b69450d663e265a8632cab2 | def set_MinLongitude(self, value):
'\n Set the value of the MinLongitude input for this Choreo. ((decimal) The minimum longitude point of a bounding box.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLongitude', value) | Set the value of the MinLongitude input for this Choreo. ((decimal) The minimum longitude point of a bounding box.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_MinLongitude | jordanemedlock/psychtruths | 7 | python | def set_MinLongitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLongitude', value) | def set_MinLongitude(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('MinLongitude', value)<|docstring|>Set the value of the MinLongitude input for this Choreo. ((decimal) The minimum longitude point of a bounding box.)<|endoftext|> |
9a2a42afd8ef301dbc6b93199d0c8cc821589bffbea6ea656b2bf1ea1a6fad9c | def set_Operator(self, value):
'\n Set the value of the Operator input for this Choreo. (Valid values are: "within" and "intersect". The results will therefore be entirely within, or overlapping with (intersecting), the bounding box. Defaults to "within".)\n '
super(SpacialFeaturesSearchInputSet, ... | Set the value of the Operator input for this Choreo. (Valid values are: "within" and "intersect". The results will therefore be entirely within, or overlapping with (intersecting), the bounding box. Defaults to "within".) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_Operator | jordanemedlock/psychtruths | 7 | python | def set_Operator(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Operator', value) | def set_Operator(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('Operator', value)<|docstring|>Set the value of the Operator input for this Choreo. (Valid values are: "within" and "intersect". The results will therefore be entirely within, or overlapping with (interse... |
17ec1e4060a8b97fda8193292242c64bde8cc595ae800b6562c15a5b2f3cf0be | def set_StartRow(self, value):
'\n Set the value of the StartRow input for this Choreo. ((optional, integer) The row to start results display from. Defaults to 1.)\n '
super(SpacialFeaturesSearchInputSet, self)._set_input('StartRow', value) | Set the value of the StartRow input for this Choreo. ((optional, integer) The row to start results display from. Defaults to 1.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | set_StartRow | jordanemedlock/psychtruths | 7 | python | def set_StartRow(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('StartRow', value) | def set_StartRow(self, value):
'\n \n '
super(SpacialFeaturesSearchInputSet, self)._set_input('StartRow', value)<|docstring|>Set the value of the StartRow input for this Choreo. ((optional, integer) The row to start results display from. Defaults to 1.)<|endoftext|> |
903db85b29fdabcd6cde9351247086ecd192732d71cb1c45be1e973f9ff48627 | def get_Response(self):
'\n Retrieve the value for the "Response" output from this Choreo execution. ((XML) The response from Unlock. Defaults to XML based on the format input parameter.)\n '
return self._output.get('Response', None) | Retrieve the value for the "Response" output from this Choreo execution. ((XML) The response from Unlock. Defaults to XML based on the format input parameter.) | temboo/core/Library/UnlockPlaces/SpacialFeaturesSearch.py | get_Response | jordanemedlock/psychtruths | 7 | python | def get_Response(self):
'\n \n '
return self._output.get('Response', None) | def get_Response(self):
'\n \n '
return self._output.get('Response', None)<|docstring|>Retrieve the value for the "Response" output from this Choreo execution. ((XML) The response from Unlock. Defaults to XML based on the format input parameter.)<|endoftext|> |
e5f402993ba4c499abe40c24fcf66917917eed26045359fd34af0e7463aa4f0c | def test_student_code():
'Homemade unit test for student work\n Return True if all of the tests pass\n Return False if at least one test fails'
test1 = False
test2 = False
test3 = False
print('<h2>Testing your code...</h2>')
if (recursive_power(5, 5) == 3125):
test1 = True
... | Homemade unit test for student work
Return True if all of the tests pass
Return False if at least one test fails | .guides/secure/unit_tests/recursion/lab_challenge_test.py | test_student_code | codio-content/cs-intro-python-fundamentals | 0 | python | def test_student_code():
'Homemade unit test for student work\n Return True if all of the tests pass\n Return False if at least one test fails'
test1 = False
test2 = False
test3 = False
print('<h2>Testing your code...</h2>')
if (recursive_power(5, 5) == 3125):
test1 = True
... | def test_student_code():
'Homemade unit test for student work\n Return True if all of the tests pass\n Return False if at least one test fails'
test1 = False
test2 = False
test3 = False
print('<h2>Testing your code...</h2>')
if (recursive_power(5, 5) == 3125):
test1 = True
... |
699f9a839bb04e8900d0aba1202b079dfc1547b7c86ded3a4bda5094e20b7316 | def create_or_update_packages(self, child_inst):
'\n Since m2m and foreignkey accept objects in their set\n '
child_instances = []
for data in child_inst:
(child_instance, _) = self.child.objects.update_or_create(pk=data.get('id'), defaults=data)
child_instances.append(child_in... | Since m2m and foreignkey accept objects in their set | backend/core/utils.py | create_or_update_packages | harryface/cbt-django-react | 0 | python | def create_or_update_packages(self, child_inst):
'\n \n '
child_instances = []
for data in child_inst:
(child_instance, _) = self.child.objects.update_or_create(pk=data.get('id'), defaults=data)
child_instances.append(child_instance)
return child_instances | def create_or_update_packages(self, child_inst):
'\n \n '
child_instances = []
for data in child_inst:
(child_instance, _) = self.child.objects.update_or_create(pk=data.get('id'), defaults=data)
child_instances.append(child_instance)
return child_instances<|docstring|>Since... |
dcc758f040a330000ff477c6227419511f7363de80455aff660d6cc278697cd7 | def repr2hash(repr):
'\n repr = representation of board state, 0 for empty, 1 for current player, 2 for the other player\n '
hash = 0
for i in repr:
hash = ((hash * 3) + i)
return hash | repr = representation of board state, 0 for empty, 1 for current player, 2 for the other player | tic_toc_toe.py | repr2hash | lzhang12/Reinforcement_Learning | 0 | python | def repr2hash(repr):
'\n \n '
hash = 0
for i in repr:
hash = ((hash * 3) + i)
return hash | def repr2hash(repr):
'\n \n '
hash = 0
for i in repr:
hash = ((hash * 3) + i)
return hash<|docstring|>repr = representation of board state, 0 for empty, 1 for current player, 2 for the other player<|endoftext|> |
6a7398aa24c10093ab603cfa10fb750757fcce0641dd855bd8f9cfa07559e5d8 | @inlineCallbacks
def _remoteHome(self, txn, uid):
"\n Create a synthetic external home object that maps to the actual remote home.\n\n @param ownerUID: directory uid of the user's home\n @type ownerUID: L{str}\n "
from txdav.caldav.datastore.sql_external import CalendarHomeExternal
... | Create a synthetic external home object that maps to the actual remote home.
@param ownerUID: directory uid of the user's home
@type ownerUID: L{str} | txdav/common/datastore/podding/test/test_store_api.py | _remoteHome | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def _remoteHome(self, txn, uid):
"\n Create a synthetic external home object that maps to the actual remote home.\n\n @param ownerUID: directory uid of the user's home\n @type ownerUID: L{str}\n "
from txdav.caldav.datastore.sql_external import CalendarHomeExternal
... | @inlineCallbacks
def _remoteHome(self, txn, uid):
"\n Create a synthetic external home object that maps to the actual remote home.\n\n @param ownerUID: directory uid of the user's home\n @type ownerUID: L{str}\n "
from txdav.caldav.datastore.sql_external import CalendarHomeExternal
... |
60f04730a69ae8c0479d258b6fbcece4eb5079aff8c239312632ce70bb42b1df | @inlineCallbacks
def test_remote_home(self):
'\n Test that a remote home can be accessed.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield self.commitTransaction(0))
home = (yield self.... | Test that a remote home can be accessed. | txdav/common/datastore/podding/test/test_store_api.py | test_remote_home | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_remote_home(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield self.commitTransaction(0))
home = (yield self._remoteHome(self.theTransactionUnderTest... | @inlineCallbacks
def test_remote_home(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield self.commitTransaction(0))
home = (yield self._remoteHome(self.theTransactionUnderTest... |
e4c2230ef617df6f7f9e1527882d0f82db080d3b99b328823973e0a6187c45ef | @inlineCallbacks
def test_homechild_listobjects(self):
'\n Test that a remote home L{listChildren} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.listChildren()... | Test that a remote home L{listChildren} works. | txdav/common/datastore/podding/test/test_store_api.py | test_homechild_listobjects | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_homechild_listobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.listChildren())
(yield self.commitTransaction(0))
ho... | @inlineCallbacks
def test_homechild_listobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.listChildren())
(yield self.commitTransaction(0))
ho... |
8f21e6bd964b13afceeb9febeb3e043bd8d9409dbe9912e45a6443d2b3dfcab7 | @inlineCallbacks
def test_homechild_loadallobjects(self):
'\n Test that a remote home L{loadChildren} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.loadChildre... | Test that a remote home L{loadChildren} works. | txdav/common/datastore/podding/test/test_store_api.py | test_homechild_loadallobjects | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_homechild_loadallobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.loadChildren())
names01 = [child.name() for child in ... | @inlineCallbacks
def test_homechild_loadallobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
children01 = (yield home01.loadChildren())
names01 = [child.name() for child in ... |
2a8b860a6da77b5a9d4219b6228a8e6a592c312c64296421465d3f64b28c96ce | @inlineCallbacks
def test_homechild_objectwith(self):
'\n Test that a remote home L{loadChildren} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('... | Test that a remote home L{loadChildren} works. | txdav/common/datastore/podding/test/test_store_api.py | test_homechild_objectwith | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_homechild_objectwith(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield self.commitTransaction(... | @inlineCallbacks
def test_homechild_objectwith(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield self.commitTransaction(... |
5a744d1ebf469b61eb59807d01b1de6ea65f68d209e0fe068f8840fbfe20998e | @inlineCallbacks
def test_objectresource_loadallobjects(self):
'\n Test that a remote home child L{objectResources} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home... | Test that a remote home child L{objectResources} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_loadallobjects | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_loadallobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.cre... | @inlineCallbacks
def test_objectresource_loadallobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.cre... |
11627a6b5bc94a85153c1e02e908c22b758aaf1c920b482acb16c247727a188f | @inlineCallbacks
def test_objectresource_loadallobjectswithnames(self):
'\n Test that a remote home child L{objectResourcesWithNames} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calend... | Test that a remote home child L{objectResourcesWithNames} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_loadallobjectswithnames | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_loadallobjectswithnames(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calen... | @inlineCallbacks
def test_objectresource_loadallobjectswithnames(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calen... |
1a56a774e62db5338e5decce8dc166913533829633e2b157f498c5c9e89c87b4 | @inlineCallbacks
def test_objectresource_listobjects(self):
'\n Test that a remote home child L{listObjectResources} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield hom... | Test that a remote home child L{listObjectResources} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_listobjects | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_listobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.create... | @inlineCallbacks
def test_objectresource_listobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.create... |
41bf513a1ea5c2e7b43ce637db5ce76c6037958997a26bf2df5151bf5b5e82a9 | @inlineCallbacks
def test_objectresource_countobjects(self):
'\n Test that a remote home child L{countObjectResources} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield h... | Test that a remote home child L{countObjectResources} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_countobjects | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_countobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.creat... | @inlineCallbacks
def test_objectresource_countobjects(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.creat... |
c83dc6848aa5e72d19b04f04a7d8553cb06993e3912dbe2defdeb66d7759c262 | @inlineCallbacks
def test_objectresource_objectwith(self):
'\n Test that a remote home child L{objectResourceWithName} and L{objectResourceWithUID} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not Non... | Test that a remote home child L{objectResourceWithName} and L{objectResourceWithUID} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_objectwith | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_objectwith(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
resource01 = (yield calen... | @inlineCallbacks
def test_objectresource_objectwith(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
resource01 = (yield calen... |
4f8699888e86e0b1db3848b9084fa5ec2e2da4f83e200f36e4471d5328421ec7 | @inlineCallbacks
def test_objectresource_resourcenameforuid(self):
'\n Test that a remote home child L{resourceNameForUID} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yie... | Test that a remote home child L{resourceNameForUID} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_resourcenameforuid | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_resourcenameforuid(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01... | @inlineCallbacks
def test_objectresource_resourcenameforuid(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01... |
c14249e02c94c981eb4cb867e07d61059532f8e73728a25bbeb1683546bc74cd | @inlineCallbacks
def test_objectresource_resourceuidforname(self):
'\n Test that a remote home child L{resourceUIDForName} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yie... | Test that a remote home child L{resourceUIDForName} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_resourceuidforname | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_resourceuidforname(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01... | @inlineCallbacks
def test_objectresource_resourceuidforname(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01... |
c86b52b0cb84e17529add8dff51e9134536424217c045c9b861a4a11e4333de9 | @inlineCallbacks
def test_objectresource_create(self):
'\n Test that a remote object resource L{create} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield home01.childWithName('calenda... | Test that a remote object resource L{create} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_create | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_create(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield home01.childWithName('calendar'))
(yield self.commitTransaction(0))
home... | @inlineCallbacks
def test_objectresource_create(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
(yield home01.childWithName('calendar'))
(yield self.commitTransaction(0))
home... |
08552266f09d4a5dd904f66bcf3c3f1a1fe611adc13920c626ca6c048a3c193d | @inlineCallbacks
def test_objectresource_setcomponent(self):
'\n Test that a remote object resource L{setComponent} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home... | Test that a remote object resource L{setComponent} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_setcomponent | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_setcomponent(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.creat... | @inlineCallbacks
def test_objectresource_setcomponent(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.creat... |
e1ea8781830aa0be596475386518944908fa1e8301d373dd3a623f8a5fad5f8b | @inlineCallbacks
def test_objectresource_component(self):
'\n Test that a remote object resource L{component} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.chi... | Test that a remote object resource L{component} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_component | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_component(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.createCa... | @inlineCallbacks
def test_objectresource_component(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.createCa... |
a48d30afc1ca037d7211b148b368c37136c130339c4abbe59fdd7f825fe5ff40 | @inlineCallbacks
def test_objectresource_remove(self):
'\n Test that a remote object resource L{component} works.\n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childW... | Test that a remote object resource L{component} works. | txdav/common/datastore/podding/test/test_store_api.py | test_objectresource_remove | m-thielen/ccs-calendarserver | 462 | python | @inlineCallbacks
def test_objectresource_remove(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.createCalen... | @inlineCallbacks
def test_objectresource_remove(self):
'\n \n '
home01 = (yield self.homeUnderTest(txn=self.theTransactionUnderTest(0), name='user01', create=True))
self.assertTrue((home01 is not None))
calendar01 = (yield home01.childWithName('calendar'))
(yield calendar01.createCalen... |
0af699aa2776576a528425f31aeb7f08b119c94a6611bee09da6fe6fcc542efc | def random_mask(input_ids: torch.Tensor, attention_mask: torch.tensor, masking_percent: float=0.15, min_char_replacement: int=1, max_char_replacement: int=CodepointTokenizer.MAX_CODEPOINT) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
'The standard way to do this (how HuggingFace does it) is to randomly mas... | The standard way to do this (how HuggingFace does it) is to randomly mask each token with masking_prob. However,
this can result in a different number of masks for different sentences, which would prevent us from using gather()
to save compute like CANINE does. consequently, we instead always mask exactly length * mask... | training/masking.py | random_mask | cdleong/shiba | 71 | python | def random_mask(input_ids: torch.Tensor, attention_mask: torch.tensor, masking_percent: float=0.15, min_char_replacement: int=1, max_char_replacement: int=CodepointTokenizer.MAX_CODEPOINT) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
'The standard way to do this (how HuggingFace does it) is to randomly mas... | def random_mask(input_ids: torch.Tensor, attention_mask: torch.tensor, masking_percent: float=0.15, min_char_replacement: int=1, max_char_replacement: int=CodepointTokenizer.MAX_CODEPOINT) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
'The standard way to do this (how HuggingFace does it) is to randomly mas... |
cbca5dac9e725427da15134c14a03fd32d40aade438e603b469b5463d9f66aa8 | def random_span_mask(input_ids: torch.Tensor, attention_mask: torch.Tensor, replacement_vocab: Dict[(int, List[str])], masking_percent: float=0.15, span_length: int=2) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
"randomly mask spans, and replace some of the spans with same length subwords. note that chara... | randomly mask spans, and replace some of the spans with same length subwords. note that character-trained canine
only does masking (no replacement) for some reason, so this is slightly different to what we're doing | training/masking.py | random_span_mask | cdleong/shiba | 71 | python | def random_span_mask(input_ids: torch.Tensor, attention_mask: torch.Tensor, replacement_vocab: Dict[(int, List[str])], masking_percent: float=0.15, span_length: int=2) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
"randomly mask spans, and replace some of the spans with same length subwords. note that chara... | def random_span_mask(input_ids: torch.Tensor, attention_mask: torch.Tensor, replacement_vocab: Dict[(int, List[str])], masking_percent: float=0.15, span_length: int=2) -> Tuple[(torch.Tensor, torch.Tensor, torch.Tensor)]:
"randomly mask spans, and replace some of the spans with same length subwords. note that chara... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.