body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def create_corp_faucet_config(self):
'Create Faucet config for corp network'
setup_vlan = SETUP_VLAN
switch = 'corp'
dps = {}
interfaces = self._build_dp_interfaces(CORP_DP_ID, tagged_vlans=[setup_vlan], access_ports=1, access_port_start=1, native_vlan=setup_vlan, egress_port=CORP_EGRESS_PORT)
d... | -8,864,064,651,153,820,000 | Create Faucet config for corp network | testing/python_lib/build_config.py | create_corp_faucet_config | henry54809/forch | python | def create_corp_faucet_config(self):
setup_vlan = SETUP_VLAN
switch = 'corp'
dps = {}
interfaces = self._build_dp_interfaces(CORP_DP_ID, tagged_vlans=[setup_vlan], access_ports=1, access_port_start=1, native_vlan=setup_vlan, egress_port=CORP_EGRESS_PORT)
dps[switch] = self._build_datapath_confi... |
def scan():
'Caller function that tries to scans the file and write the report.'
spec_path = settings['spec_path']
try:
api_spec = load_config_file(spec_path)
except FileNotFoundError as e:
error_message = f'Could not find API spec file: {spec_path}. {str(e)}'
logger.error(error_... | -2,529,913,209,857,200,000 | Caller function that tries to scans the file and write the report. | scanapi/scan.py | scan | hebertjulio/scanapi | python | def scan():
spec_path = settings['spec_path']
try:
api_spec = load_config_file(spec_path)
except FileNotFoundError as e:
error_message = f'Could not find API spec file: {spec_path}. {str(e)}'
logger.error(error_message)
raise SystemExit(ExitCode.USAGE_ERROR)
except E... |
def write_report(results):
'Constructs a Reporter object and calls the write method of Reporter to\n push the results to a file.\n '
reporter = Reporter(settings['output_path'], settings['template'])
reporter.write(results) | -3,180,117,976,623,210,500 | Constructs a Reporter object and calls the write method of Reporter to
push the results to a file. | scanapi/scan.py | write_report | hebertjulio/scanapi | python | def write_report(results):
'Constructs a Reporter object and calls the write method of Reporter to\n push the results to a file.\n '
reporter = Reporter(settings['output_path'], settings['template'])
reporter.write(results) |
def _ConvertBoxToCOCOFormat(box):
'Converts a box in [ymin, xmin, ymax, xmax] format to COCO format.\n\n This is a utility function for converting from our internal\n [ymin, xmin, ymax, xmax] convention to the convention used by the COCO API\n i.e., [xmin, ymin, width, height].\n\n Args:\n box: a [ymin, xmin... | -6,747,070,920,789,550,000 | Converts a box in [ymin, xmin, ymax, xmax] format to COCO format.
This is a utility function for converting from our internal
[ymin, xmin, ymax, xmax] convention to the convention used by the COCO API
i.e., [xmin, ymin, width, height].
Args:
box: a [ymin, xmin, ymax, xmax] numpy array
Returns:
a list of floats r... | research/object_detection/metrics/coco_tools.py | _ConvertBoxToCOCOFormat | 1911590204/models | python | def _ConvertBoxToCOCOFormat(box):
'Converts a box in [ymin, xmin, ymax, xmax] format to COCO format.\n\n This is a utility function for converting from our internal\n [ymin, xmin, ymax, xmax] convention to the convention used by the COCO API\n i.e., [xmin, ymin, width, height].\n\n Args:\n box: a [ymin, xmin... |
def _RleCompress(masks):
'Compresses mask using Run-length encoding provided by pycocotools.\n\n Args:\n masks: uint8 numpy array of shape [mask_height, mask_width] with values in\n {0, 1}.\n\n Returns:\n A pycocotools Run-length encoding of the mask.\n '
rle = mask.encode(np.asfortranarray(masks))
... | -4,503,842,151,480,810,000 | Compresses mask using Run-length encoding provided by pycocotools.
Args:
masks: uint8 numpy array of shape [mask_height, mask_width] with values in
{0, 1}.
Returns:
A pycocotools Run-length encoding of the mask. | research/object_detection/metrics/coco_tools.py | _RleCompress | 1911590204/models | python | def _RleCompress(masks):
'Compresses mask using Run-length encoding provided by pycocotools.\n\n Args:\n masks: uint8 numpy array of shape [mask_height, mask_width] with values in\n {0, 1}.\n\n Returns:\n A pycocotools Run-length encoding of the mask.\n '
rle = mask.encode(np.asfortranarray(masks))
... |
def ExportSingleImageGroundtruthToCoco(image_id, next_annotation_id, category_id_set, groundtruth_boxes, groundtruth_classes, groundtruth_keypoints=None, groundtruth_keypoint_visibilities=None, groundtruth_masks=None, groundtruth_is_crowd=None, groundtruth_area=None):
'Export groundtruth of a single image to COCO f... | -6,087,324,160,309,731,000 | Export groundtruth of a single image to COCO format.
This function converts groundtruth detection annotations represented as numpy
arrays to dictionaries that can be ingested by the COCO evaluation API. Note
that the image_ids provided here must match the ones given to
ExportSingleImageDetectionsToCoco. We assume that... | research/object_detection/metrics/coco_tools.py | ExportSingleImageGroundtruthToCoco | 1911590204/models | python | def ExportSingleImageGroundtruthToCoco(image_id, next_annotation_id, category_id_set, groundtruth_boxes, groundtruth_classes, groundtruth_keypoints=None, groundtruth_keypoint_visibilities=None, groundtruth_masks=None, groundtruth_is_crowd=None, groundtruth_area=None):
'Export groundtruth of a single image to COCO f... |
def ExportGroundtruthToCOCO(image_ids, groundtruth_boxes, groundtruth_classes, categories, output_path=None):
'Export groundtruth detection annotations in numpy arrays to COCO API.\n\n This function converts a set of groundtruth detection annotations represented\n as numpy arrays to dictionaries that can be inges... | -3,856,544,612,097,964,000 | Export groundtruth detection annotations in numpy arrays to COCO API.
This function converts a set of groundtruth detection annotations represented
as numpy arrays to dictionaries that can be ingested by the COCO API.
Inputs to this function are three lists: image ids for each groundtruth image,
groundtruth boxes for ... | research/object_detection/metrics/coco_tools.py | ExportGroundtruthToCOCO | 1911590204/models | python | def ExportGroundtruthToCOCO(image_ids, groundtruth_boxes, groundtruth_classes, categories, output_path=None):
'Export groundtruth detection annotations in numpy arrays to COCO API.\n\n This function converts a set of groundtruth detection annotations represented\n as numpy arrays to dictionaries that can be inges... |
def ExportSingleImageDetectionBoxesToCoco(image_id, category_id_set, detection_boxes, detection_scores, detection_classes, detection_keypoints=None, detection_keypoint_visibilities=None):
'Export detections of a single image to COCO format.\n\n This function converts detections represented as numpy arrays to dicti... | 3,486,113,173,692,428,300 | Export detections of a single image to COCO format.
This function converts detections represented as numpy arrays to dictionaries
that can be ingested by the COCO evaluation API. Note that the image_ids
provided here must match the ones given to the
ExporSingleImageDetectionBoxesToCoco. We assume that boxes, and class... | research/object_detection/metrics/coco_tools.py | ExportSingleImageDetectionBoxesToCoco | 1911590204/models | python | def ExportSingleImageDetectionBoxesToCoco(image_id, category_id_set, detection_boxes, detection_scores, detection_classes, detection_keypoints=None, detection_keypoint_visibilities=None):
'Export detections of a single image to COCO format.\n\n This function converts detections represented as numpy arrays to dicti... |
def ExportSingleImageDetectionMasksToCoco(image_id, category_id_set, detection_masks, detection_scores, detection_classes):
'Export detection masks of a single image to COCO format.\n\n This function converts detections represented as numpy arrays to dictionaries\n that can be ingested by the COCO evaluation API.... | 38,152,405,171,328,380 | Export detection masks of a single image to COCO format.
This function converts detections represented as numpy arrays to dictionaries
that can be ingested by the COCO evaluation API. We assume that
detection_masks, detection_scores, and detection_classes are in correspondence
- that is: detection_masks[i, :], detecti... | research/object_detection/metrics/coco_tools.py | ExportSingleImageDetectionMasksToCoco | 1911590204/models | python | def ExportSingleImageDetectionMasksToCoco(image_id, category_id_set, detection_masks, detection_scores, detection_classes):
'Export detection masks of a single image to COCO format.\n\n This function converts detections represented as numpy arrays to dictionaries\n that can be ingested by the COCO evaluation API.... |
def ExportDetectionsToCOCO(image_ids, detection_boxes, detection_scores, detection_classes, categories, output_path=None):
"Export detection annotations in numpy arrays to COCO API.\n\n This function converts a set of predicted detections represented\n as numpy arrays to dictionaries that can be ingested by the C... | -1,430,712,689,237,600,800 | Export detection annotations in numpy arrays to COCO API.
This function converts a set of predicted detections represented
as numpy arrays to dictionaries that can be ingested by the COCO API.
Inputs to this function are lists, consisting of boxes, scores and
classes, respectively, corresponding to each image for whic... | research/object_detection/metrics/coco_tools.py | ExportDetectionsToCOCO | 1911590204/models | python | def ExportDetectionsToCOCO(image_ids, detection_boxes, detection_scores, detection_classes, categories, output_path=None):
"Export detection annotations in numpy arrays to COCO API.\n\n This function converts a set of predicted detections represented\n as numpy arrays to dictionaries that can be ingested by the C... |
def ExportSegmentsToCOCO(image_ids, detection_masks, detection_scores, detection_classes, categories, output_path=None):
"Export segmentation masks in numpy arrays to COCO API.\n\n This function converts a set of predicted instance masks represented\n as numpy arrays to dictionaries that can be ingested by the CO... | -927,010,710,476,147,200 | Export segmentation masks in numpy arrays to COCO API.
This function converts a set of predicted instance masks represented
as numpy arrays to dictionaries that can be ingested by the COCO API.
Inputs to this function are lists, consisting of segments, scores and
classes, respectively, corresponding to each image for ... | research/object_detection/metrics/coco_tools.py | ExportSegmentsToCOCO | 1911590204/models | python | def ExportSegmentsToCOCO(image_ids, detection_masks, detection_scores, detection_classes, categories, output_path=None):
"Export segmentation masks in numpy arrays to COCO API.\n\n This function converts a set of predicted instance masks represented\n as numpy arrays to dictionaries that can be ingested by the CO... |
def ExportKeypointsToCOCO(image_ids, detection_keypoints, detection_scores, detection_classes, categories, output_path=None):
"Exports keypoints in numpy arrays to COCO API.\n\n This function converts a set of predicted keypoints represented\n as numpy arrays to dictionaries that can be ingested by the COCO API.\... | 7,840,153,829,423,577,000 | Exports keypoints in numpy arrays to COCO API.
This function converts a set of predicted keypoints represented
as numpy arrays to dictionaries that can be ingested by the COCO API.
Inputs to this function are lists, consisting of keypoints, scores and
classes, respectively, corresponding to each image for which detect... | research/object_detection/metrics/coco_tools.py | ExportKeypointsToCOCO | 1911590204/models | python | def ExportKeypointsToCOCO(image_ids, detection_keypoints, detection_scores, detection_classes, categories, output_path=None):
"Exports keypoints in numpy arrays to COCO API.\n\n This function converts a set of predicted keypoints represented\n as numpy arrays to dictionaries that can be ingested by the COCO API.\... |
def __init__(self, dataset, detection_type='bbox'):
"COCOWrapper constructor.\n\n See http://mscoco.org/dataset/#format for a description of the format.\n By default, the coco.COCO class constructor reads from a JSON file.\n This function duplicates the same behavior but loads from a dictionary,\n allow... | 3,777,113,071,917,594,000 | COCOWrapper constructor.
See http://mscoco.org/dataset/#format for a description of the format.
By default, the coco.COCO class constructor reads from a JSON file.
This function duplicates the same behavior but loads from a dictionary,
allowing us to perform evaluation without writing to external storage.
Args:
dat... | research/object_detection/metrics/coco_tools.py | __init__ | 1911590204/models | python | def __init__(self, dataset, detection_type='bbox'):
"COCOWrapper constructor.\n\n See http://mscoco.org/dataset/#format for a description of the format.\n By default, the coco.COCO class constructor reads from a JSON file.\n This function duplicates the same behavior but loads from a dictionary,\n allow... |
def LoadAnnotations(self, annotations):
"Load annotations dictionary into COCO datastructure.\n\n See http://mscoco.org/dataset/#format for a description of the annotations\n format. As above, this function replicates the default behavior of the API\n but does not require writing to external storage.\n\n ... | 8,178,324,416,221,913,000 | Load annotations dictionary into COCO datastructure.
See http://mscoco.org/dataset/#format for a description of the annotations
format. As above, this function replicates the default behavior of the API
but does not require writing to external storage.
Args:
annotations: python list holding object detection result... | research/object_detection/metrics/coco_tools.py | LoadAnnotations | 1911590204/models | python | def LoadAnnotations(self, annotations):
"Load annotations dictionary into COCO datastructure.\n\n See http://mscoco.org/dataset/#format for a description of the annotations\n format. As above, this function replicates the default behavior of the API\n but does not require writing to external storage.\n\n ... |
def __init__(self, groundtruth=None, detections=None, agnostic_mode=False, iou_type='bbox', oks_sigmas=None):
"COCOEvalWrapper constructor.\n\n Note that for the area-based metrics to be meaningful, detection and\n groundtruth boxes must be in image coordinates measured in pixels.\n\n Args:\n groundtr... | -4,644,386,061,494,226,000 | COCOEvalWrapper constructor.
Note that for the area-based metrics to be meaningful, detection and
groundtruth boxes must be in image coordinates measured in pixels.
Args:
groundtruth: a coco.COCO (or coco_tools.COCOWrapper) object holding
groundtruth annotations
detections: a coco.COCO (or coco_tools.COCOWrap... | research/object_detection/metrics/coco_tools.py | __init__ | 1911590204/models | python | def __init__(self, groundtruth=None, detections=None, agnostic_mode=False, iou_type='bbox', oks_sigmas=None):
"COCOEvalWrapper constructor.\n\n Note that for the area-based metrics to be meaningful, detection and\n groundtruth boxes must be in image coordinates measured in pixels.\n\n Args:\n groundtr... |
def GetCategory(self, category_id):
"Fetches dictionary holding category information given category id.\n\n Args:\n category_id: integer id\n Returns:\n dictionary holding 'id', 'name'.\n "
return self.cocoGt.cats[category_id] | -3,998,284,783,981,275,000 | Fetches dictionary holding category information given category id.
Args:
category_id: integer id
Returns:
dictionary holding 'id', 'name'. | research/object_detection/metrics/coco_tools.py | GetCategory | 1911590204/models | python | def GetCategory(self, category_id):
"Fetches dictionary holding category information given category id.\n\n Args:\n category_id: integer id\n Returns:\n dictionary holding 'id', 'name'.\n "
return self.cocoGt.cats[category_id] |
def GetAgnosticMode(self):
'Returns true if COCO Eval is configured to evaluate in agnostic mode.'
return (self.params.useCats == 0) | -4,317,986,916,639,350,300 | Returns true if COCO Eval is configured to evaluate in agnostic mode. | research/object_detection/metrics/coco_tools.py | GetAgnosticMode | 1911590204/models | python | def GetAgnosticMode(self):
return (self.params.useCats == 0) |
def GetCategoryIdList(self):
'Returns list of valid category ids.'
return self.params.catIds | -2,981,913,091,674,385,400 | Returns list of valid category ids. | research/object_detection/metrics/coco_tools.py | GetCategoryIdList | 1911590204/models | python | def GetCategoryIdList(self):
return self.params.catIds |
def ComputeMetrics(self, include_metrics_per_category=False, all_metrics_per_category=False):
"Computes detection/keypoint metrics.\n\n Args:\n include_metrics_per_category: If True, will include metrics per category.\n all_metrics_per_category: If true, include all the summery metrics for\n eac... | 5,216,740,938,967,259,000 | Computes detection/keypoint metrics.
Args:
include_metrics_per_category: If True, will include metrics per category.
all_metrics_per_category: If true, include all the summery metrics for
each category in per_category_ap. Be careful with setting it to true if
you have more than handful of categories, becau... | research/object_detection/metrics/coco_tools.py | ComputeMetrics | 1911590204/models | python | def ComputeMetrics(self, include_metrics_per_category=False, all_metrics_per_category=False):
"Computes detection/keypoint metrics.\n\n Args:\n include_metrics_per_category: If True, will include metrics per category.\n all_metrics_per_category: If true, include all the summery metrics for\n eac... |
def accept(self):
'\n Override the accept method so that we can confirm saving an\n invalid configuration.\n '
result = QtWidgets.QMessageBox.Yes
if (not self.validate()):
result = QtWidgets.QMessageBox.warning(self, 'Invalid Configuration', "This configuration is invalid. Unpr... | 7,433,577,860,333,540,000 | Override the accept method so that we can confirm saving an
invalid configuration. | mapclientplugins/filechooserstep/configuredialog.py | accept | mapclient-plugins/mapclientplugins.filechooserstep | python | def accept(self):
'\n Override the accept method so that we can confirm saving an\n invalid configuration.\n '
result = QtWidgets.QMessageBox.Yes
if (not self.validate()):
result = QtWidgets.QMessageBox.warning(self, 'Invalid Configuration', "This configuration is invalid. Unpr... |
def validate(self):
'\n Validate the configuration dialog fields. For any field that is not valid\n set the style sheet to the INVALID_STYLE_SHEET. Return the outcome of the\n overall validity of the configuration.\n '
value = self.identifierOccursCount(self._ui.lineEdit0.text())
... | 441,426,544,836,570,000 | Validate the configuration dialog fields. For any field that is not valid
set the style sheet to the INVALID_STYLE_SHEET. Return the outcome of the
overall validity of the configuration. | mapclientplugins/filechooserstep/configuredialog.py | validate | mapclient-plugins/mapclientplugins.filechooserstep | python | def validate(self):
'\n Validate the configuration dialog fields. For any field that is not valid\n set the style sheet to the INVALID_STYLE_SHEET. Return the outcome of the\n overall validity of the configuration.\n '
value = self.identifierOccursCount(self._ui.lineEdit0.text())
... |
def getConfig(self):
'\n Get the current value of the configuration from the dialog. Also\n set the _previousIdentifier value so that we can check uniqueness of the\n identifier over the whole of the workflow.\n '
self._previousIdentifier = self._ui.lineEdit0.text()
config = {'i... | -1,545,015,863,487,636,500 | Get the current value of the configuration from the dialog. Also
set the _previousIdentifier value so that we can check uniqueness of the
identifier over the whole of the workflow. | mapclientplugins/filechooserstep/configuredialog.py | getConfig | mapclient-plugins/mapclientplugins.filechooserstep | python | def getConfig(self):
'\n Get the current value of the configuration from the dialog. Also\n set the _previousIdentifier value so that we can check uniqueness of the\n identifier over the whole of the workflow.\n '
self._previousIdentifier = self._ui.lineEdit0.text()
config = {'i... |
def setConfig(self, config):
'\n Set the current value of the configuration for the dialog. Also\n set the _previousIdentifier value so that we can check uniqueness of the\n identifier over the whole of the workflow.\n '
self._previousIdentifier = config['identifier']
self._ui.l... | 5,738,320,274,872,744,000 | Set the current value of the configuration for the dialog. Also
set the _previousIdentifier value so that we can check uniqueness of the
identifier over the whole of the workflow. | mapclientplugins/filechooserstep/configuredialog.py | setConfig | mapclient-plugins/mapclientplugins.filechooserstep | python | def setConfig(self, config):
'\n Set the current value of the configuration for the dialog. Also\n set the _previousIdentifier value so that we can check uniqueness of the\n identifier over the whole of the workflow.\n '
self._previousIdentifier = config['identifier']
self._ui.l... |
def verify(self, hash, sig):
'Verify a DER signature'
return (ssl.AMBKSA_verify(0, hash, len(hash), sig, len(sig), self.k) == 1) | -2,046,395,906,615,599,900 | Verify a DER signature | test/functional/test_framework/key.py | verify | Alonewolf-123/AmbankCoin-Core | python | def verify(self, hash, sig):
return (ssl.AMBKSA_verify(0, hash, len(hash), sig, len(sig), self.k) == 1) |
def parse_python_version(output):
"Parse a Python version output returned by `python --version`.\n\n Return a dict with three keys: major, minor, and micro. Each value is a\n string containing a version part.\n\n Note: The micro part would be `'0'` if it's missing from the input string.\n "
version_... | -7,576,245,133,647,391,000 | Parse a Python version output returned by `python --version`.
Return a dict with three keys: major, minor, and micro. Each value is a
string containing a version part.
Note: The micro part would be `'0'` if it's missing from the input string. | pipenv/utils.py | parse_python_version | bryant1410/pipenv | python | def parse_python_version(output):
"Parse a Python version output returned by `python --version`.\n\n Return a dict with three keys: major, minor, and micro. Each value is a\n string containing a version part.\n\n Note: The micro part would be `'0'` if it's missing from the input string.\n "
version_... |
def escape_grouped_arguments(s):
'Prepares a string for the shell (on Windows too!)\n\n Only for use on grouped arguments (passed as a string to Popen)\n '
if (s is None):
return None
if (os.name == 'nt'):
s = '{}'.format(s.replace('\\', '\\\\'))
return (('"' + s.replace("'", "'\\'... | 2,562,507,320,774,941,700 | Prepares a string for the shell (on Windows too!)
Only for use on grouped arguments (passed as a string to Popen) | pipenv/utils.py | escape_grouped_arguments | bryant1410/pipenv | python | def escape_grouped_arguments(s):
'Prepares a string for the shell (on Windows too!)\n\n Only for use on grouped arguments (passed as a string to Popen)\n '
if (s is None):
return None
if (os.name == 'nt'):
s = '{}'.format(s.replace('\\', '\\\\'))
return (('"' + s.replace("'", "'\\"... |
def clean_pkg_version(version):
'Uses pip to prepare a package version string, from our internal version.'
return six.u(pep440_version(str(version).replace('==', ''))) | 1,798,999,973,971,679,200 | Uses pip to prepare a package version string, from our internal version. | pipenv/utils.py | clean_pkg_version | bryant1410/pipenv | python | def clean_pkg_version(version):
return six.u(pep440_version(str(version).replace('==', ))) |
def resolve_deps(deps, which, project, sources=None, verbose=False, python=False, clear=False, pre=False, allow_global=False):
'Given a list of dependencies, return a resolved list of dependencies,\n using pip-tools -- and their hashes, using the warehouse API / pip9.\n '
index_lookup = {}
markers_loo... | 5,097,824,507,640,910,000 | Given a list of dependencies, return a resolved list of dependencies,
using pip-tools -- and their hashes, using the warehouse API / pip9. | pipenv/utils.py | resolve_deps | bryant1410/pipenv | python | def resolve_deps(deps, which, project, sources=None, verbose=False, python=False, clear=False, pre=False, allow_global=False):
'Given a list of dependencies, return a resolved list of dependencies,\n using pip-tools -- and their hashes, using the warehouse API / pip9.\n '
index_lookup = {}
markers_loo... |
def multi_split(s, split):
'Splits on multiple given separators.'
for r in split:
s = s.replace(r, '|')
return [i for i in s.split('|') if (len(i) > 0)] | -6,995,361,326,840,965,000 | Splits on multiple given separators. | pipenv/utils.py | multi_split | bryant1410/pipenv | python | def multi_split(s, split):
for r in split:
s = s.replace(r, '|')
return [i for i in s.split('|') if (len(i) > 0)] |
def convert_deps_from_pip(dep):
'"Converts a pip-formatted dependency to a Pipfile-formatted one.'
dependency = {}
req = get_requirement(dep)
extras = {'extras': req.extras}
if ((req.uri or req.path or is_installable_file(req.name)) and (not req.vcs)):
if ((not req.uri) and (not req.path)):
... | 6,363,460,669,016,941,000 | "Converts a pip-formatted dependency to a Pipfile-formatted one. | pipenv/utils.py | convert_deps_from_pip | bryant1410/pipenv | python | def convert_deps_from_pip(dep):
dependency = {}
req = get_requirement(dep)
extras = {'extras': req.extras}
if ((req.uri or req.path or is_installable_file(req.name)) and (not req.vcs)):
if ((not req.uri) and (not req.path)):
req.path = os.path.abspath(req.name)
hashable_... |
def convert_deps_to_pip(deps, project=None, r=True, include_index=False):
'"Converts a Pipfile-formatted dependency to a pip-formatted one.'
dependencies = []
for dep in deps.keys():
extra = (deps[dep] if isinstance(deps[dep], six.string_types) else '')
version = ''
index = ''
... | 3,140,597,842,437,439,500 | "Converts a Pipfile-formatted dependency to a pip-formatted one. | pipenv/utils.py | convert_deps_to_pip | bryant1410/pipenv | python | def convert_deps_to_pip(deps, project=None, r=True, include_index=False):
dependencies = []
for dep in deps.keys():
extra = (deps[dep] if isinstance(deps[dep], six.string_types) else )
version =
index =
if (is_star(deps[dep]) or (str(extra) == '{}')):
extra =
... |
def mkdir_p(newdir):
'works the way a good mkdir should :)\n - already exists, silently complete\n - regular file in the way, raise an exception\n - parent directory(ies) does not exist, make them as well\n From: http://code.activestate.com/recipes/82465-a-friendly-mkdir/\n '
if o... | -8,025,579,765,829,738,000 | works the way a good mkdir should :)
- already exists, silently complete
- regular file in the way, raise an exception
- parent directory(ies) does not exist, make them as well
From: http://code.activestate.com/recipes/82465-a-friendly-mkdir/ | pipenv/utils.py | mkdir_p | bryant1410/pipenv | python | def mkdir_p(newdir):
'works the way a good mkdir should :)\n - already exists, silently complete\n - regular file in the way, raise an exception\n - parent directory(ies) does not exist, make them as well\n From: http://code.activestate.com/recipes/82465-a-friendly-mkdir/\n '
if o... |
def is_required_version(version, specified_version):
"Check to see if there's a hard requirement for version\n number provided in the Pipfile.\n "
if isinstance(specified_version, dict):
specified_version = specified_version.get('version', '')
if specified_version.startswith('=='):
ret... | 3,528,375,736,170,234,000 | Check to see if there's a hard requirement for version
number provided in the Pipfile. | pipenv/utils.py | is_required_version | bryant1410/pipenv | python | def is_required_version(version, specified_version):
"Check to see if there's a hard requirement for version\n number provided in the Pipfile.\n "
if isinstance(specified_version, dict):
specified_version = specified_version.get('version', )
if specified_version.startswith('=='):
retur... |
def strip_ssh_from_git_uri(uri):
'Return git+ssh:// formatted URI to git+git@ format'
if isinstance(uri, six.string_types):
uri = uri.replace('git+ssh://', 'git+')
return uri | -5,153,976,107,256,773,000 | Return git+ssh:// formatted URI to git+git@ format | pipenv/utils.py | strip_ssh_from_git_uri | bryant1410/pipenv | python | def strip_ssh_from_git_uri(uri):
if isinstance(uri, six.string_types):
uri = uri.replace('git+ssh://', 'git+')
return uri |
def clean_git_uri(uri):
'Cleans VCS uris from pip9 format'
if isinstance(uri, six.string_types):
if (uri.startswith('git+') and ('://' not in uri)):
uri = uri.replace('git+', 'git+ssh://')
return uri | 8,837,214,570,924,101,000 | Cleans VCS uris from pip9 format | pipenv/utils.py | clean_git_uri | bryant1410/pipenv | python | def clean_git_uri(uri):
if isinstance(uri, six.string_types):
if (uri.startswith('git+') and ('://' not in uri)):
uri = uri.replace('git+', 'git+ssh://')
return uri |
def is_installable_file(path):
'Determine if a path can potentially be installed'
from .vendor.pip9.utils import is_installable_dir
from .vendor.pip9.utils.packaging import specifiers
if (hasattr(path, 'keys') and any((key for key in path.keys() if (key in ['file', 'path'])))):
path = (urlparse(... | -8,326,956,013,517,452,000 | Determine if a path can potentially be installed | pipenv/utils.py | is_installable_file | bryant1410/pipenv | python | def is_installable_file(path):
from .vendor.pip9.utils import is_installable_dir
from .vendor.pip9.utils.packaging import specifiers
if (hasattr(path, 'keys') and any((key for key in path.keys() if (key in ['file', 'path'])))):
path = (urlparse(path['file']).path if ('file' in path) else path['... |
def is_file(package):
'Determine if a package name is for a File dependency.'
if hasattr(package, 'keys'):
return any((key for key in package.keys() if (key in ['file', 'path'])))
if os.path.exists(str(package)):
return True
for start in SCHEME_LIST:
if str(package).startswith(st... | 1,091,657,782,702,303,400 | Determine if a package name is for a File dependency. | pipenv/utils.py | is_file | bryant1410/pipenv | python | def is_file(package):
if hasattr(package, 'keys'):
return any((key for key in package.keys() if (key in ['file', 'path'])))
if os.path.exists(str(package)):
return True
for start in SCHEME_LIST:
if str(package).startswith(start):
return True
return False |
def pep440_version(version):
'Normalize version to PEP 440 standards'
from .vendor.pip9.index import parse_version
return str(parse_version(version)) | 5,361,031,010,979,994,000 | Normalize version to PEP 440 standards | pipenv/utils.py | pep440_version | bryant1410/pipenv | python | def pep440_version(version):
from .vendor.pip9.index import parse_version
return str(parse_version(version)) |
def pep423_name(name):
'Normalize package name to PEP 423 style standard.'
name = name.lower()
if any(((i not in name) for i in (VCS_LIST + SCHEME_LIST))):
return name.replace('_', '-')
else:
return name | 6,748,167,606,597,170,000 | Normalize package name to PEP 423 style standard. | pipenv/utils.py | pep423_name | bryant1410/pipenv | python | def pep423_name(name):
name = name.lower()
if any(((i not in name) for i in (VCS_LIST + SCHEME_LIST))):
return name.replace('_', '-')
else:
return name |
def proper_case(package_name):
'Properly case project name from pypi.org.'
r = requests.get('https://pypi.org/pypi/{0}/json'.format(package_name), timeout=0.3, stream=True)
if (not r.ok):
raise IOError('Unable to find package {0} in PyPI repository.'.format(package_name))
r = parse.parse('https:... | 5,332,965,172,988,998,000 | Properly case project name from pypi.org. | pipenv/utils.py | proper_case | bryant1410/pipenv | python | def proper_case(package_name):
r = requests.get('https://pypi.org/pypi/{0}/json'.format(package_name), timeout=0.3, stream=True)
if (not r.ok):
raise IOError('Unable to find package {0} in PyPI repository.'.format(package_name))
r = parse.parse('https://pypi.org/pypi/{name}/json', r.url)
go... |
def split_section(input_file, section_suffix, test_function):
'\n Split a pipfile or a lockfile section out by section name and test function\n\n :param dict input_file: A dictionary containing either a pipfile or lockfile\n :param str section_suffix: A string of the name of the section\n :p... | 3,888,405,553,536,379,400 | Split a pipfile or a lockfile section out by section name and test function
:param dict input_file: A dictionary containing either a pipfile or lockfile
:param str section_suffix: A string of the name of the section
:param func test_function: A test function to test against the value in the key/value pair
... | pipenv/utils.py | split_section | bryant1410/pipenv | python | def split_section(input_file, section_suffix, test_function):
'\n Split a pipfile or a lockfile section out by section name and test function\n\n :param dict input_file: A dictionary containing either a pipfile or lockfile\n :param str section_suffix: A string of the name of the section\n :p... |
def split_file(file_dict):
'Split VCS and editable dependencies out from file.'
sections = {'vcs': is_vcs, 'editable': (lambda x: (hasattr(x, 'keys') and x.get('editable')))}
for (k, func) in sections.items():
file_dict = split_section(file_dict, k, func)
return file_dict | 1,330,811,071,559,589,000 | Split VCS and editable dependencies out from file. | pipenv/utils.py | split_file | bryant1410/pipenv | python | def split_file(file_dict):
sections = {'vcs': is_vcs, 'editable': (lambda x: (hasattr(x, 'keys') and x.get('editable')))}
for (k, func) in sections.items():
file_dict = split_section(file_dict, k, func)
return file_dict |
def merge_deps(file_dict, project, dev=False, requirements=False, ignore_hashes=False, blocking=False, only=False):
'\n Given a file_dict, merges dependencies and converts them to pip dependency lists.\n :param dict file_dict: The result of calling :func:`pipenv.utils.split_file`\n :param :class:`p... | 6,053,193,627,376,801,000 | Given a file_dict, merges dependencies and converts them to pip dependency lists.
:param dict file_dict: The result of calling :func:`pipenv.utils.split_file`
:param :class:`pipenv.project.Project` project: Pipenv project
:param bool dev=False: Flag indicating whether dev dependencies are to be installed
... | pipenv/utils.py | merge_deps | bryant1410/pipenv | python | def merge_deps(file_dict, project, dev=False, requirements=False, ignore_hashes=False, blocking=False, only=False):
'\n Given a file_dict, merges dependencies and converts them to pip dependency lists.\n :param dict file_dict: The result of calling :func:`pipenv.utils.split_file`\n :param :class:`p... |
def recase_file(file_dict):
'Recase file before writing to output.'
if (('packages' in file_dict) or ('dev-packages' in file_dict)):
sections = ('packages', 'dev-packages')
elif (('default' in file_dict) or ('develop' in file_dict)):
sections = ('default', 'develop')
for section in secti... | -392,200,137,092,393,150 | Recase file before writing to output. | pipenv/utils.py | recase_file | bryant1410/pipenv | python | def recase_file(file_dict):
if (('packages' in file_dict) or ('dev-packages' in file_dict)):
sections = ('packages', 'dev-packages')
elif (('default' in file_dict) or ('develop' in file_dict)):
sections = ('default', 'develop')
for section in sections:
file_section = file_dict.g... |
def get_windows_path(*args):
'Sanitize a path for windows environments\n\n Accepts an arbitrary list of arguments and makes a clean windows path'
return os.path.normpath(os.path.join(*args)) | -5,803,461,582,242,583,000 | Sanitize a path for windows environments
Accepts an arbitrary list of arguments and makes a clean windows path | pipenv/utils.py | get_windows_path | bryant1410/pipenv | python | def get_windows_path(*args):
'Sanitize a path for windows environments\n\n Accepts an arbitrary list of arguments and makes a clean windows path'
return os.path.normpath(os.path.join(*args)) |
def find_windows_executable(bin_path, exe_name):
'Given an executable name, search the given location for an executable'
requested_path = get_windows_path(bin_path, exe_name)
if os.path.exists(requested_path):
return requested_path
exe_name = os.path.splitext(exe_name)[0]
files = ['{0}.{1}'.... | -2,987,833,260,518,996,000 | Given an executable name, search the given location for an executable | pipenv/utils.py | find_windows_executable | bryant1410/pipenv | python | def find_windows_executable(bin_path, exe_name):
requested_path = get_windows_path(bin_path, exe_name)
if os.path.exists(requested_path):
return requested_path
exe_name = os.path.splitext(exe_name)[0]
files = ['{0}.{1}'.format(exe_name, ext) for ext in [, 'py', 'exe', 'bat']]
exec_paths... |
def get_converted_relative_path(path, relative_to=os.curdir):
'Given a vague relative path, return the path relative to the given location'
return os.path.join('.', os.path.relpath(path, start=relative_to)) | -8,656,903,140,058,767,000 | Given a vague relative path, return the path relative to the given location | pipenv/utils.py | get_converted_relative_path | bryant1410/pipenv | python | def get_converted_relative_path(path, relative_to=os.curdir):
return os.path.join('.', os.path.relpath(path, start=relative_to)) |
def walk_up(bottom):
"Mimic os.walk, but walk 'up' instead of down the directory tree.\n From: https://gist.github.com/zdavkeos/1098474\n "
bottom = os.path.realpath(bottom)
try:
names = os.listdir(bottom)
except Exception:
return
(dirs, nondirs) = ([], [])
for name in name... | -7,195,392,152,588,847,000 | Mimic os.walk, but walk 'up' instead of down the directory tree.
From: https://gist.github.com/zdavkeos/1098474 | pipenv/utils.py | walk_up | bryant1410/pipenv | python | def walk_up(bottom):
"Mimic os.walk, but walk 'up' instead of down the directory tree.\n From: https://gist.github.com/zdavkeos/1098474\n "
bottom = os.path.realpath(bottom)
try:
names = os.listdir(bottom)
except Exception:
return
(dirs, nondirs) = ([], [])
for name in name... |
def find_requirements(max_depth=3):
'Returns the path of a Pipfile in parent directories.'
i = 0
for (c, d, f) in walk_up(os.getcwd()):
i += 1
if (i < max_depth):
if 'requirements.txt':
r = os.path.join(c, 'requirements.txt')
if os.path.isfile(r):
... | -8,605,925,904,386,501,000 | Returns the path of a Pipfile in parent directories. | pipenv/utils.py | find_requirements | bryant1410/pipenv | python | def find_requirements(max_depth=3):
i = 0
for (c, d, f) in walk_up(os.getcwd()):
i += 1
if (i < max_depth):
if 'requirements.txt':
r = os.path.join(c, 'requirements.txt')
if os.path.isfile(r):
return r
raise RuntimeError('N... |
@contextmanager
def temp_environ():
'Allow the ability to set os.environ temporarily'
environ = dict(os.environ)
try:
(yield)
finally:
os.environ.clear()
os.environ.update(environ) | -5,083,302,786,420,072,000 | Allow the ability to set os.environ temporarily | pipenv/utils.py | temp_environ | bryant1410/pipenv | python | @contextmanager
def temp_environ():
environ = dict(os.environ)
try:
(yield)
finally:
os.environ.clear()
os.environ.update(environ) |
def is_valid_url(url):
'Checks if a given string is an url'
pieces = urlparse(url)
return all([pieces.scheme, pieces.netloc]) | -4,789,592,044,157,309,000 | Checks if a given string is an url | pipenv/utils.py | is_valid_url | bryant1410/pipenv | python | def is_valid_url(url):
pieces = urlparse(url)
return all([pieces.scheme, pieces.netloc]) |
def download_file(url, filename):
'Downloads file from url to a path with filename'
r = requests.get(url, stream=True)
if (not r.ok):
raise IOError('Unable to download file')
with open(filename, 'wb') as f:
f.write(r.content) | -7,474,985,168,864,853,000 | Downloads file from url to a path with filename | pipenv/utils.py | download_file | bryant1410/pipenv | python | def download_file(url, filename):
r = requests.get(url, stream=True)
if (not r.ok):
raise IOError('Unable to download file')
with open(filename, 'wb') as f:
f.write(r.content) |
def need_update_check():
'Determines whether we need to check for updates.'
mkdir_p(PIPENV_CACHE_DIR)
p = os.sep.join((PIPENV_CACHE_DIR, '.pipenv_update_check'))
if (not os.path.exists(p)):
return True
out_of_date_time = (time() - ((24 * 60) * 60))
if (os.path.isfile(p) and (os.path.getm... | -8,032,898,415,673,751,000 | Determines whether we need to check for updates. | pipenv/utils.py | need_update_check | bryant1410/pipenv | python | def need_update_check():
mkdir_p(PIPENV_CACHE_DIR)
p = os.sep.join((PIPENV_CACHE_DIR, '.pipenv_update_check'))
if (not os.path.exists(p)):
return True
out_of_date_time = (time() - ((24 * 60) * 60))
if (os.path.isfile(p) and (os.path.getmtime(p) <= out_of_date_time)):
return True... |
def touch_update_stamp():
'Touches PIPENV_CACHE_DIR/.pipenv_update_check'
mkdir_p(PIPENV_CACHE_DIR)
p = os.sep.join((PIPENV_CACHE_DIR, '.pipenv_update_check'))
try:
os.utime(p, None)
except OSError:
with open(p, 'w') as fh:
fh.write('') | -4,278,246,743,979,614,000 | Touches PIPENV_CACHE_DIR/.pipenv_update_check | pipenv/utils.py | touch_update_stamp | bryant1410/pipenv | python | def touch_update_stamp():
mkdir_p(PIPENV_CACHE_DIR)
p = os.sep.join((PIPENV_CACHE_DIR, '.pipenv_update_check'))
try:
os.utime(p, None)
except OSError:
with open(p, 'w') as fh:
fh.write() |
def normalize_drive(path):
'Normalize drive in path so they stay consistent.\n\n This currently only affects local drives on Windows, which can be\n identified with either upper or lower cased drive names. The case is\n always converted to uppercase because it seems to be preferred.\n\n See: <https://gi... | 7,206,725,071,959,051,000 | Normalize drive in path so they stay consistent.
This currently only affects local drives on Windows, which can be
identified with either upper or lower cased drive names. The case is
always converted to uppercase because it seems to be preferred.
See: <https://github.com/pypa/pipenv/issues/1218> | pipenv/utils.py | normalize_drive | bryant1410/pipenv | python | def normalize_drive(path):
'Normalize drive in path so they stay consistent.\n\n This currently only affects local drives on Windows, which can be\n identified with either upper or lower cased drive names. The case is\n always converted to uppercase because it seems to be preferred.\n\n See: <https://gi... |
def is_readonly_path(fn):
'Check if a provided path exists and is readonly.\n\n Permissions check is `bool(path.stat & stat.S_IREAD)` or `not os.access(path, os.W_OK)`\n '
if os.path.exists(fn):
return ((os.stat(fn).st_mode & stat.S_IREAD) or (not os.access(fn, os.W_OK)))
return False | 4,072,325,937,409,912,000 | Check if a provided path exists and is readonly.
Permissions check is `bool(path.stat & stat.S_IREAD)` or `not os.access(path, os.W_OK)` | pipenv/utils.py | is_readonly_path | bryant1410/pipenv | python | def is_readonly_path(fn):
'Check if a provided path exists and is readonly.\n\n Permissions check is `bool(path.stat & stat.S_IREAD)` or `not os.access(path, os.W_OK)`\n '
if os.path.exists(fn):
return ((os.stat(fn).st_mode & stat.S_IREAD) or (not os.access(fn, os.W_OK)))
return False |
def handle_remove_readonly(func, path, exc):
'Error handler for shutil.rmtree.\n\n Windows source repo folders are read-only by default, so this error handler\n attempts to set them as writeable and then proceed with deletion.'
default_warning_message = 'Unable to remove file due to permissions restrictio... | -2,753,335,397,450,273,000 | Error handler for shutil.rmtree.
Windows source repo folders are read-only by default, so this error handler
attempts to set them as writeable and then proceed with deletion. | pipenv/utils.py | handle_remove_readonly | bryant1410/pipenv | python | def handle_remove_readonly(func, path, exc):
'Error handler for shutil.rmtree.\n\n Windows source repo folders are read-only by default, so this error handler\n attempts to set them as writeable and then proceed with deletion.'
default_warning_message = 'Unable to remove file due to permissions restrictio... |
def _deduplicate(data):
'Remove duplicated records.'
cnt = collections.Counter((row['id'] for row in data))
nonuniq_ids = set((id for (id, count) in cnt.items() if (count > 1)))
nonuniq_data = [row for row in data if (row['id'] in nonuniq_ids)]
unique_data = [row for row in data if (row['id'] not in... | 4,788,760,498,953,770,000 | Remove duplicated records. | tensorflow_datasets/text/reddit_disentanglement.py | _deduplicate | Ak0303/datasets | python | def _deduplicate(data):
cnt = collections.Counter((row['id'] for row in data))
nonuniq_ids = set((id for (id, count) in cnt.items() if (count > 1)))
nonuniq_data = [row for row in data if (row['id'] in nonuniq_ids)]
unique_data = [row for row in data if (row['id'] not in nonuniq_ids)]
nonuniq_d... |
def _split_generators(self, dl_manager):
'Returns SplitGenerators.'
return [tfds.core.SplitGenerator(name=tfds.Split.TRAIN, gen_kwargs={'path': os.path.join(dl_manager.manual_dir, 'train.csv')}), tfds.core.SplitGenerator(name=tfds.Split.VALIDATION, gen_kwargs={'path': os.path.join(dl_manager.manual_dir, 'val.cs... | -2,188,673,168,850,584,000 | Returns SplitGenerators. | tensorflow_datasets/text/reddit_disentanglement.py | _split_generators | Ak0303/datasets | python | def _split_generators(self, dl_manager):
return [tfds.core.SplitGenerator(name=tfds.Split.TRAIN, gen_kwargs={'path': os.path.join(dl_manager.manual_dir, 'train.csv')}), tfds.core.SplitGenerator(name=tfds.Split.VALIDATION, gen_kwargs={'path': os.path.join(dl_manager.manual_dir, 'val.csv')}), tfds.core.SplitGene... |
def _generate_examples(self, path):
'Yields examples.'
data = list(_read_csv(path))
data = _deduplicate(data)
for (link_id, one_topic_data) in itertools.groupby(data, (lambda row: row['link_id'])):
one_topic_data = list(one_topic_data)
for row in one_topic_data:
row['text'] =... | 6,543,013,553,364,795,000 | Yields examples. | tensorflow_datasets/text/reddit_disentanglement.py | _generate_examples | Ak0303/datasets | python | def _generate_examples(self, path):
data = list(_read_csv(path))
data = _deduplicate(data)
for (link_id, one_topic_data) in itertools.groupby(data, (lambda row: row['link_id'])):
one_topic_data = list(one_topic_data)
for row in one_topic_data:
row['text'] = row.pop('body')
... |
def detect(image: str, verbose: bool=False):
'Detects faces on a given image using dlib and returns matches.\n\n :param image: Path to access the image to be searched\n :type image: [string]\n :param verbose: Wether or not command should output informations\n :type image: [bool], default to False\n\n ... | -7,453,832,317,566,232,000 | Detects faces on a given image using dlib and returns matches.
:param image: Path to access the image to be searched
:type image: [string]
:param verbose: Wether or not command should output informations
:type image: [bool], default to False
:raises RuntimeError: When the provided image_path is invalid
:return: The ... | face_cropper/core/detector.py | detect | Dave-Lopper/face_cropper | python | def detect(image: str, verbose: bool=False):
'Detects faces on a given image using dlib and returns matches.\n\n :param image: Path to access the image to be searched\n :type image: [string]\n :param verbose: Wether or not command should output informations\n :type image: [bool], default to False\n\n ... |
def download_progress_hook(count, blockSize, totalSize):
'A hook to report the progress of a download. This is mostly intended for users with\n slow internet connections. Reports every 5% change in download progress.\n '
global last_percent_reported
percent = int((((count * blockSize) * 100) / totalSi... | 2,470,292,000,998,774,300 | A hook to report the progress of a download. This is mostly intended for users with
slow internet connections. Reports every 5% change in download progress. | udacity_deep_learning/download_data.py | download_progress_hook | fcarsten/ai_playground | python | def download_progress_hook(count, blockSize, totalSize):
'A hook to report the progress of a download. This is mostly intended for users with\n slow internet connections. Reports every 5% change in download progress.\n '
global last_percent_reported
percent = int((((count * blockSize) * 100) / totalSi... |
def maybe_download(filename, expected_bytes, force=False):
"Download a file if not present, and make sure it's the right size."
dest_filename = os.path.join(data_root, filename)
if (force or (not os.path.exists(dest_filename))):
print('Attempting to download:', filename)
(filename, _) = urlr... | 2,058,923,476,989,784,600 | Download a file if not present, and make sure it's the right size. | udacity_deep_learning/download_data.py | maybe_download | fcarsten/ai_playground | python | def maybe_download(filename, expected_bytes, force=False):
dest_filename = os.path.join(data_root, filename)
if (force or (not os.path.exists(dest_filename))):
print('Attempting to download:', filename)
(filename, _) = urlretrieve((url + filename), dest_filename, reporthook=download_progres... |
def channel_split_naive(r, channel_ranges):
'Slower but simpler implementation of straxen.split_channel_ranges'
results = []
for (left, right) in channel_ranges:
results.append(r[np.in1d(r['channel'], np.arange(left, (right + 1)))])
return results | -3,514,169,492,615,701,500 | Slower but simpler implementation of straxen.split_channel_ranges | tests/test_channel_split.py | channel_split_naive | AlexElykov/straxen | python | def channel_split_naive(r, channel_ranges):
results = []
for (left, right) in channel_ranges:
results.append(r[np.in1d(r['channel'], np.arange(left, (right + 1)))])
return results |
def __init__(self, obs_space, action_space, config, loss_fn, stats_fn=None, grad_stats_fn=None, before_loss_init=None, make_model=None, action_sampler_fn=None, existing_inputs=None, existing_model=None, get_batch_divisibility_req=None, obs_include_prev_action_reward=True):
'Initialize a dynamic TF policy.\n\n ... | 5,892,416,507,873,919,000 | Initialize a dynamic TF policy.
Arguments:
observation_space (gym.Space): Observation space of the policy.
action_space (gym.Space): Action space of the policy.
config (dict): Policy-specific configuration data.
loss_fn (func): function that returns a loss tensor the policy
graph, and dict of e... | rllib/policy/dynamic_tf_policy.py | __init__ | lisadunlap/ray | python | def __init__(self, obs_space, action_space, config, loss_fn, stats_fn=None, grad_stats_fn=None, before_loss_init=None, make_model=None, action_sampler_fn=None, existing_inputs=None, existing_model=None, get_batch_divisibility_req=None, obs_include_prev_action_reward=True):
'Initialize a dynamic TF policy.\n\n ... |
@override(TFPolicy)
def copy(self, existing_inputs):
'Creates a copy of self using existing input placeholders.'
if self._state_inputs:
num_state_inputs = (len(self._state_inputs) + 1)
else:
num_state_inputs = 0
if ((len(self._loss_inputs) + num_state_inputs) != len(existing_inputs)):
... | -2,234,550,702,876,427,800 | Creates a copy of self using existing input placeholders. | rllib/policy/dynamic_tf_policy.py | copy | lisadunlap/ray | python | @override(TFPolicy)
def copy(self, existing_inputs):
if self._state_inputs:
num_state_inputs = (len(self._state_inputs) + 1)
else:
num_state_inputs = 0
if ((len(self._loss_inputs) + num_state_inputs) != len(existing_inputs)):
raise ValueError('Tensor list mismatch', self._loss_i... |
def main():
"The entry point for the console script xbmcswift2.\n\n The 'xbcmswift2' script is command bassed, so the second argument is always\n the command to execute. Each command has its own parser options and usages.\n If no command is provided or the -h flag is used without any other\n commands, t... | -6,102,954,789,046,832,000 | The entry point for the console script xbmcswift2.
The 'xbcmswift2' script is command bassed, so the second argument is always
the command to execute. Each command has its own parser options and usages.
If no command is provided or the -h flag is used without any other
commands, the general help message is shown. | resources/lib/xbmcswift2/cli/cli.py | main | liberty-developer/plugin.video.metalliq-forqed | python | def main():
"The entry point for the console script xbmcswift2.\n\n The 'xbcmswift2' script is command bassed, so the second argument is always\n the command to execute. Each command has its own parser options and usages.\n If no command is provided or the -h flag is used without any other\n commands, t... |
def compute_benchmark(synthesizer, datasets=DEFAULT_DATASETS, iterations=3):
'Compute the scores of a synthesizer over a list of datasets.\n\n The results are returned in a raw format as a ``pandas.DataFrame`` containing:\n - One row for each dataset+scoring method (for example, a classifier)\n - O... | 6,867,888,405,591,949,000 | Compute the scores of a synthesizer over a list of datasets.
The results are returned in a raw format as a ``pandas.DataFrame`` containing:
- One row for each dataset+scoring method (for example, a classifier)
- One column for each computed metric
- The columns:
- dataset
- distance
... | sdgym/benchmark.py | compute_benchmark | csala/SDGym | python | def compute_benchmark(synthesizer, datasets=DEFAULT_DATASETS, iterations=3):
'Compute the scores of a synthesizer over a list of datasets.\n\n The results are returned in a raw format as a ``pandas.DataFrame`` containing:\n - One row for each dataset+scoring method (for example, a classifier)\n - O... |
def _summarize_scores(scores):
'Computes a summary of the scores obtained by a synthesizer.\n\n The raw scores returned by the ``compute_benchmark`` function are summarized\n by grouping them by dataset and computing the average.\n\n The results are then put in a ``pandas.Series`` object with one value per... | -9,160,691,643,630,375,000 | Computes a summary of the scores obtained by a synthesizer.
The raw scores returned by the ``compute_benchmark`` function are summarized
by grouping them by dataset and computing the average.
The results are then put in a ``pandas.Series`` object with one value per
dataset and metric.
As an example, the summary of a... | sdgym/benchmark.py | _summarize_scores | csala/SDGym | python | def _summarize_scores(scores):
'Computes a summary of the scores obtained by a synthesizer.\n\n The raw scores returned by the ``compute_benchmark`` function are summarized\n by grouping them by dataset and computing the average.\n\n The results are then put in a ``pandas.Series`` object with one value per... |
def _get_synthesizer_name(synthesizer):
'Get the name of the synthesizer function or class.\n\n If the given synthesizer is a function, return its name.\n If it is a method, return the name of the class to which\n the method belongs.\n\n Args:\n synthesizer (function or method):\n The ... | 6,233,313,625,423,672,000 | Get the name of the synthesizer function or class.
If the given synthesizer is a function, return its name.
If it is a method, return the name of the class to which
the method belongs.
Args:
synthesizer (function or method):
The synthesizer function or method.
Returns:
str:
Name of the functi... | sdgym/benchmark.py | _get_synthesizer_name | csala/SDGym | python | def _get_synthesizer_name(synthesizer):
'Get the name of the synthesizer function or class.\n\n If the given synthesizer is a function, return its name.\n If it is a method, return the name of the class to which\n the method belongs.\n\n Args:\n synthesizer (function or method):\n The ... |
def _get_synthesizers(synthesizers):
'Get the dict of synthesizers from the input value.\n\n If the input is a synthesizer or an iterable of synthesizers, get their names\n and put them on a dict.\n\n Args:\n synthesizers (function, class, list, tuple or dict):\n A synthesizer (function o... | 256,732,817,812,438,270 | Get the dict of synthesizers from the input value.
If the input is a synthesizer or an iterable of synthesizers, get their names
and put them on a dict.
Args:
synthesizers (function, class, list, tuple or dict):
A synthesizer (function or method or class) or an iterable of synthesizers
or a dict c... | sdgym/benchmark.py | _get_synthesizers | csala/SDGym | python | def _get_synthesizers(synthesizers):
'Get the dict of synthesizers from the input value.\n\n If the input is a synthesizer or an iterable of synthesizers, get their names\n and put them on a dict.\n\n Args:\n synthesizers (function, class, list, tuple or dict):\n A synthesizer (function o... |
def benchmark(synthesizers, datasets=DEFAULT_DATASETS, iterations=3, add_leaderboard=True, leaderboard_path=LEADERBOARD_PATH, replace_existing=True):
'Compute the benchmark scores for the synthesizers and return a leaderboard.\n\n The ``synthesizers`` object can either be a single synthesizer or, an iterable of\... | -6,008,760,859,194,131,000 | Compute the benchmark scores for the synthesizers and return a leaderboard.
The ``synthesizers`` object can either be a single synthesizer or, an iterable of
synthesizers or a dict containing synthesizer names as keys and synthesizers as values.
If ``add_leaderboard`` is ``True``, append the obtained scores to the le... | sdgym/benchmark.py | benchmark | csala/SDGym | python | def benchmark(synthesizers, datasets=DEFAULT_DATASETS, iterations=3, add_leaderboard=True, leaderboard_path=LEADERBOARD_PATH, replace_existing=True):
'Compute the benchmark scores for the synthesizers and return a leaderboard.\n\n The ``synthesizers`` object can either be a single synthesizer or, an iterable of\... |
def hello():
'\n This is a docstring\n '
print('hello') | -6,392,466,694,877,974,000 | This is a docstring | tests/example.py | hello | bwohlberg/py2jn | python | def hello():
'\n \n '
print('hello') |
def parse_env(config_schema, env):
'Parse the values from a given environment against a given config schema\n\n Args:\n config_schema: A dict which maps the variable name to a Schema object\n that describes the requested value.\n env: A dict which represents the value of each variable in... | 2,493,724,030,623,137,300 | Parse the values from a given environment against a given config schema
Args:
config_schema: A dict which maps the variable name to a Schema object
that describes the requested value.
env: A dict which represents the value of each variable in the
environment. | envpy/parser.py | parse_env | jonathanlloyd/envpy | python | def parse_env(config_schema, env):
'Parse the values from a given environment against a given config schema\n\n Args:\n config_schema: A dict which maps the variable name to a Schema object\n that describes the requested value.\n env: A dict which represents the value of each variable in... |
def parse(self, key, value):
'Parse the environment value for a given key against the schema.\n\n Args:\n key: The name of the environment variable.\n value: The value to be parsed.\n '
if (value is not None):
try:
return self._parser(value)
except... | -3,832,913,277,313,911,300 | Parse the environment value for a given key against the schema.
Args:
key: The name of the environment variable.
value: The value to be parsed. | envpy/parser.py | parse | jonathanlloyd/envpy | python | def parse(self, key, value):
'Parse the environment value for a given key against the schema.\n\n Args:\n key: The name of the environment variable.\n value: The value to be parsed.\n '
if (value is not None):
try:
return self._parser(value)
except... |
def global_scope():
'\n Get the global/default scope instance. There are a lot of APIs use\n :code:`global_scope` as its default value, e.g., :code:`Executor.run`\n\n Examples:\n .. code-block:: python\n\n import paddle.fluid as fluid\n import numpy\n\n fluid.global_scope(... | -2,561,556,626,074,283,000 | Get the global/default scope instance. There are a lot of APIs use
:code:`global_scope` as its default value, e.g., :code:`Executor.run`
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy
fluid.global_scope().var("data").get_tensor().set(numpy.ones((2, 2)), fluid.CPUPlac... | python/paddle/fluid/executor.py | global_scope | AnKingOne/Paddle | python | def global_scope():
'\n Get the global/default scope instance. There are a lot of APIs use\n :code:`global_scope` as its default value, e.g., :code:`Executor.run`\n\n Examples:\n .. code-block:: python\n\n import paddle.fluid as fluid\n import numpy\n\n fluid.global_scope(... |
@signature_safe_contextmanager
def scope_guard(scope):
'\n Change the global/default scope instance by Python `with` statement. All\n variable in runtime will assigned to the new scope.\n\n Args:\n scope: The new global/default scope.\n\n Examples:\n .. code-block:: python\n\n i... | 1,367,163,491,478,758,700 | Change the global/default scope instance by Python `with` statement. All
variable in runtime will assigned to the new scope.
Args:
scope: The new global/default scope.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy
new_scope = fluid.Scope()
with fl... | python/paddle/fluid/executor.py | scope_guard | AnKingOne/Paddle | python | @signature_safe_contextmanager
def scope_guard(scope):
'\n Change the global/default scope instance by Python `with` statement. All\n variable in runtime will assigned to the new scope.\n\n Args:\n scope: The new global/default scope.\n\n Examples:\n .. code-block:: python\n\n i... |
def as_numpy(tensor):
'\n Convert a Tensor to a numpy.ndarray, its only support Tensor without LoD information.\n For higher dimensional sequence data, please use LoDTensor directly.\n\n Examples:\n .. code-block:: python\n\n import paddle.fluid as fluid\n import numpy\n\n ... | -7,444,017,813,485,285,000 | Convert a Tensor to a numpy.ndarray, its only support Tensor without LoD information.
For higher dimensional sequence data, please use LoDTensor directly.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy
new_scope = fluid.Scope()
with fluid.scope_guard(new_scope)... | python/paddle/fluid/executor.py | as_numpy | AnKingOne/Paddle | python | def as_numpy(tensor):
'\n Convert a Tensor to a numpy.ndarray, its only support Tensor without LoD information.\n For higher dimensional sequence data, please use LoDTensor directly.\n\n Examples:\n .. code-block:: python\n\n import paddle.fluid as fluid\n import numpy\n\n ... |
def has_feed_operators(block, feed_targets, feed_holder_name):
' Check whether the block already has feed operators.\n\n Return false if the block does not have any feed operators.\n If some feed operators have been prepended to the block, check that\n the info contained in these feed operators matches the... | -4,258,719,829,844,028,000 | Check whether the block already has feed operators.
Return false if the block does not have any feed operators.
If some feed operators have been prepended to the block, check that
the info contained in these feed operators matches the feed_targets
and feed_holder_name. Raise exception when any mismatch is found.
Retur... | python/paddle/fluid/executor.py | has_feed_operators | AnKingOne/Paddle | python | def has_feed_operators(block, feed_targets, feed_holder_name):
' Check whether the block already has feed operators.\n\n Return false if the block does not have any feed operators.\n If some feed operators have been prepended to the block, check that\n the info contained in these feed operators matches the... |
def has_fetch_operators(block, fetch_targets, fetch_holder_name):
' Check whether the block already has fetch operators.\n\n Return false if the block does not have any fetch operators.\n If some fetch operators have been appended to the block, check that\n the info contained in these fetch operators match... | -1,140,413,373,672,059,300 | Check whether the block already has fetch operators.
Return false if the block does not have any fetch operators.
If some fetch operators have been appended to the block, check that
the info contained in these fetch operators matches the fetch_targets
and fetch_holder_name. Raise exception when any mismatch is found.
... | python/paddle/fluid/executor.py | has_fetch_operators | AnKingOne/Paddle | python | def has_fetch_operators(block, fetch_targets, fetch_holder_name):
' Check whether the block already has fetch operators.\n\n Return false if the block does not have any fetch operators.\n If some fetch operators have been appended to the block, check that\n the info contained in these fetch operators match... |
def _fetch_var(name, scope=None, return_numpy=True):
'\n Fetch the value of the variable with the given name from the\n given scope.\n\n Args:\n name(str): name of the variable. Typically, only persistable variables\n can be found in the scope used for running the program.\n scope(... | -6,382,690,931,197,901,000 | Fetch the value of the variable with the given name from the
given scope.
Args:
name(str): name of the variable. Typically, only persistable variables
can be found in the scope used for running the program.
scope(core.Scope|None): scope object. It should be the scope where
you pass to Executor.... | python/paddle/fluid/executor.py | _fetch_var | AnKingOne/Paddle | python | def _fetch_var(name, scope=None, return_numpy=True):
'\n Fetch the value of the variable with the given name from the\n given scope.\n\n Args:\n name(str): name of the variable. Typically, only persistable variables\n can be found in the scope used for running the program.\n scope(... |
def _as_lodtensor(data, place):
'\n Convert numpy.ndarray to Tensor, its only support Tensor without LoD information.\n For higher dimensional sequence data, please use LoDTensor directly.\n\n Examples:\n >>> import paddle.fluid as fluid\n >>> place = fluid.CPUPlace()\n ... | -7,073,756,137,704,113,000 | Convert numpy.ndarray to Tensor, its only support Tensor without LoD information.
For higher dimensional sequence data, please use LoDTensor directly.
Examples:
>>> import paddle.fluid as fluid
>>> place = fluid.CPUPlace()
>>> exe = fluid.executor(place)
>>> data = np.array(size=(100, 200, 300))
>>... | python/paddle/fluid/executor.py | _as_lodtensor | AnKingOne/Paddle | python | def _as_lodtensor(data, place):
'\n Convert numpy.ndarray to Tensor, its only support Tensor without LoD information.\n For higher dimensional sequence data, please use LoDTensor directly.\n\n Examples:\n >>> import paddle.fluid as fluid\n >>> place = fluid.CPUPlace()\n ... |
def close(self):
'\n Close this executor.\n\n You can no longer use this executor after calling this method.\n For the distributed training, this method would free the resource\n on PServers related to the current Trainer.\n\n Examples:\n .. code-block:: python\n\n ... | -7,197,737,734,027,222,000 | Close this executor.
You can no longer use this executor after calling this method.
For the distributed training, this method would free the resource
on PServers related to the current Trainer.
Examples:
.. code-block:: python
import paddle.fluid as fluid
cpu = fluid.CPUPlace()
exe = fluid.Exe... | python/paddle/fluid/executor.py | close | AnKingOne/Paddle | python | def close(self):
'\n Close this executor.\n\n You can no longer use this executor after calling this method.\n For the distributed training, this method would free the resource\n on PServers related to the current Trainer.\n\n Examples:\n .. code-block:: python\n\n ... |
def run(self, program=None, feed=None, fetch_list=None, feed_var_name='feed', fetch_var_name='fetch', scope=None, return_numpy=True, use_program_cache=False):
'\n Run program by this Executor. Feed data by feed map, fetch result by\n fetch_list. Python executor takes a program, add feed operators and\... | -8,958,766,470,868,862,000 | Run program by this Executor. Feed data by feed map, fetch result by
fetch_list. Python executor takes a program, add feed operators and
fetch operators to this program according to feed map and fetch_list.
Feed map provides input data for the program. fetch_list provides
the variables(or names) that user want to get a... | python/paddle/fluid/executor.py | run | AnKingOne/Paddle | python | def run(self, program=None, feed=None, fetch_list=None, feed_var_name='feed', fetch_var_name='fetch', scope=None, return_numpy=True, use_program_cache=False):
'\n Run program by this Executor. Feed data by feed map, fetch result by\n fetch_list. Python executor takes a program, add feed operators and\... |
def infer_from_dataset(self, program=None, dataset=None, scope=None, thread=0, debug=False, fetch_list=None, fetch_info=None, print_period=100):
'\n The document of infer_from_dataset is almost the same as\n train_from_dataset, except that in distributed training,\n push gradients will be disab... | 5,420,110,943,490,376,000 | The document of infer_from_dataset is almost the same as
train_from_dataset, except that in distributed training,
push gradients will be disabled in infer_from_dataset.
infer_from_dataset() can be used for evaluation in multi-thread
very easily.
Args:
program(Program|CompiledProgram): the program that needs to be ... | python/paddle/fluid/executor.py | infer_from_dataset | AnKingOne/Paddle | python | def infer_from_dataset(self, program=None, dataset=None, scope=None, thread=0, debug=False, fetch_list=None, fetch_info=None, print_period=100):
'\n The document of infer_from_dataset is almost the same as\n train_from_dataset, except that in distributed training,\n push gradients will be disab... |
def train_from_dataset(self, program=None, dataset=None, scope=None, thread=0, debug=False, fetch_list=None, fetch_info=None, print_period=100):
'\n Train from a pre-defined Dataset. Dataset is defined in paddle.fluid.dataset.\n Given a program, either a program or compiled program, train_from_dataset... | -4,721,268,134,907,001,000 | Train from a pre-defined Dataset. Dataset is defined in paddle.fluid.dataset.
Given a program, either a program or compiled program, train_from_dataset will
consume all data samples in dataset. Input scope can be given by users. By default,
scope is global_scope(). The total number of thread run in training is `thread`... | python/paddle/fluid/executor.py | train_from_dataset | AnKingOne/Paddle | python | def train_from_dataset(self, program=None, dataset=None, scope=None, thread=0, debug=False, fetch_list=None, fetch_info=None, print_period=100):
'\n Train from a pre-defined Dataset. Dataset is defined in paddle.fluid.dataset.\n Given a program, either a program or compiled program, train_from_dataset... |
def placeholder_inputs(batch_size):
'Generate placeholder variables to represent the input tensors.\n These placeholders are used as inputs by the rest of the model building\n code and will be fed from the downloaded data in the .run() loop, below.\n Args:\n batch_size: The batch size will be baked ... | 4,792,516,056,658,818,000 | Generate placeholder variables to represent the input tensors.
These placeholders are used as inputs by the rest of the model building
code and will be fed from the downloaded data in the .run() loop, below.
Args:
batch_size: The batch size will be baked into both placeholders.
Returns:
images_placeholder: Imag... | c3d_model/predict_c3d_ucf101.py | placeholder_inputs | b-safwat/multi_action_recognition | python | def placeholder_inputs(batch_size):
'Generate placeholder variables to represent the input tensors.\n These placeholders are used as inputs by the rest of the model building\n code and will be fed from the downloaded data in the .run() loop, below.\n Args:\n batch_size: The batch size will be baked ... |
def GenerateCSRFToken(user_id, time):
'Generates a CSRF token based on a secret key, id and time.'
precondition.AssertType(user_id, Text)
precondition.AssertOptionalType(time, int)
time = (time or rdfvalue.RDFDatetime.Now().AsMicrosecondsSinceEpoch())
secret = config.CONFIG.Get('AdminUI.csrf_secret_... | 6,125,651,692,541,662,000 | Generates a CSRF token based on a secret key, id and time. | grr/server/grr_response_server/gui/wsgiapp.py | GenerateCSRFToken | Codehardt/grr | python | def GenerateCSRFToken(user_id, time):
precondition.AssertType(user_id, Text)
precondition.AssertOptionalType(time, int)
time = (time or rdfvalue.RDFDatetime.Now().AsMicrosecondsSinceEpoch())
secret = config.CONFIG.Get('AdminUI.csrf_secret_key', None)
if (secret is None):
raise ValueErro... |
def StoreCSRFCookie(user, response):
'Decorator for WSGI handler that inserts CSRF cookie into response.'
csrf_token = GenerateCSRFToken(user, None)
response.set_cookie('csrftoken', csrf_token, max_age=CSRF_TOKEN_DURATION.seconds) | 4,536,204,827,103,691,300 | Decorator for WSGI handler that inserts CSRF cookie into response. | grr/server/grr_response_server/gui/wsgiapp.py | StoreCSRFCookie | Codehardt/grr | python | def StoreCSRFCookie(user, response):
csrf_token = GenerateCSRFToken(user, None)
response.set_cookie('csrftoken', csrf_token, max_age=CSRF_TOKEN_DURATION.seconds) |
def ValidateCSRFTokenOrRaise(request):
'Decorator for WSGI handler that checks CSRF cookie against the request.'
if (request.method in ('GET', 'HEAD')):
return
csrf_token = request.headers.get('X-CSRFToken', '').encode('ascii')
if (not csrf_token):
logging.info('Did not find headers CSRF... | -7,794,270,443,633,931,000 | Decorator for WSGI handler that checks CSRF cookie against the request. | grr/server/grr_response_server/gui/wsgiapp.py | ValidateCSRFTokenOrRaise | Codehardt/grr | python | def ValidateCSRFTokenOrRaise(request):
if (request.method in ('GET', 'HEAD')):
return
csrf_token = request.headers.get('X-CSRFToken', ).encode('ascii')
if (not csrf_token):
logging.info('Did not find headers CSRF token for: %s', request.path)
raise werkzeug_exceptions.Forbidden(... |
def LogAccessWrapper(func):
'Decorator that ensures that HTTP access is logged.'
def Wrapper(request, *args, **kwargs):
'Wrapping function.'
try:
response = func(request, *args, **kwargs)
server_logging.LOGGER.LogHttpAdminUIAccess(request, response)
except Except... | -115,557,866,535,678,200 | Decorator that ensures that HTTP access is logged. | grr/server/grr_response_server/gui/wsgiapp.py | LogAccessWrapper | Codehardt/grr | python | def LogAccessWrapper(func):
def Wrapper(request, *args, **kwargs):
'Wrapping function.'
try:
response = func(request, *args, **kwargs)
server_logging.LOGGER.LogHttpAdminUIAccess(request, response)
except Exception:
response = werkzeug_wrappers.Respon... |
def Wrapper(request, *args, **kwargs):
'Wrapping function.'
try:
response = func(request, *args, **kwargs)
server_logging.LOGGER.LogHttpAdminUIAccess(request, response)
except Exception:
response = werkzeug_wrappers.Response('', status=500)
server_logging.LOGGER.LogHttpAdminU... | -986,668,722,510,930,300 | Wrapping function. | grr/server/grr_response_server/gui/wsgiapp.py | Wrapper | Codehardt/grr | python | def Wrapper(request, *args, **kwargs):
try:
response = func(request, *args, **kwargs)
server_logging.LOGGER.LogHttpAdminUIAccess(request, response)
except Exception:
response = werkzeug_wrappers.Response(, status=500)
server_logging.LOGGER.LogHttpAdminUIAccess(request, respo... |
def _BuildToken(self, request, execution_time):
'Build an ACLToken from the request.'
token = access_control.ACLToken(username=request.user, reason=request.args.get('reason', ''), process='GRRAdminUI', expiry=(rdfvalue.RDFDatetime.Now() + execution_time))
for field in ['Remote_Addr', 'X-Forwarded-For']:
... | 3,942,364,055,699,815,400 | Build an ACLToken from the request. | grr/server/grr_response_server/gui/wsgiapp.py | _BuildToken | Codehardt/grr | python | def _BuildToken(self, request, execution_time):
token = access_control.ACLToken(username=request.user, reason=request.args.get('reason', ), process='GRRAdminUI', expiry=(rdfvalue.RDFDatetime.Now() + execution_time))
for field in ['Remote_Addr', 'X-Forwarded-For']:
remote_addr = request.headers.get(... |
def _HandleHomepage(self, request):
'Renders GRR home page by rendering base.html Jinja template.'
_ = request
env = jinja2.Environment(loader=jinja2.FileSystemLoader(config.CONFIG['AdminUI.template_root']), autoescape=True)
create_time = psutil.Process(os.getpid()).create_time()
context = {'heading... | 6,814,278,485,432,112,000 | Renders GRR home page by rendering base.html Jinja template. | grr/server/grr_response_server/gui/wsgiapp.py | _HandleHomepage | Codehardt/grr | python | def _HandleHomepage(self, request):
_ = request
env = jinja2.Environment(loader=jinja2.FileSystemLoader(config.CONFIG['AdminUI.template_root']), autoescape=True)
create_time = psutil.Process(os.getpid()).create_time()
context = {'heading': config.CONFIG['AdminUI.heading'], 'report_url': config.CONF... |
def _HandleApi(self, request):
'Handles API requests.'
ValidateCSRFTokenOrRaise(request)
response = http_api.RenderHttpResponse(request)
if (('csrftoken' not in request.cookies) or (response.headers.get('X-API-Method', '') == 'GetPendingUserNotificationsCount')):
StoreCSRFCookie(request.user, re... | 6,756,775,622,371,802,000 | Handles API requests. | grr/server/grr_response_server/gui/wsgiapp.py | _HandleApi | Codehardt/grr | python | def _HandleApi(self, request):
ValidateCSRFTokenOrRaise(request)
response = http_api.RenderHttpResponse(request)
if (('csrftoken' not in request.cookies) or (response.headers.get('X-API-Method', ) == 'GetPendingUserNotificationsCount')):
StoreCSRFCookie(request.user, response)
return respon... |
def _RedirectToRemoteHelp(self, path):
'Redirect to GitHub-hosted documentation.'
allowed_chars = set(((string.ascii_letters + string.digits) + '._-/'))
if (not (set(path) <= allowed_chars)):
raise RuntimeError(('Unusual chars in path %r - possible exploit attempt.' % path))
target_path = os.pat... | -4,929,114,115,641,130,000 | Redirect to GitHub-hosted documentation. | grr/server/grr_response_server/gui/wsgiapp.py | _RedirectToRemoteHelp | Codehardt/grr | python | def _RedirectToRemoteHelp(self, path):
allowed_chars = set(((string.ascii_letters + string.digits) + '._-/'))
if (not (set(path) <= allowed_chars)):
raise RuntimeError(('Unusual chars in path %r - possible exploit attempt.' % path))
target_path = os.path.join(config.CONFIG['AdminUI.docs_locatio... |
def _HandleHelp(self, request):
'Handles help requests.'
help_path = request.path.split('/', 2)[(- 1)]
if (not help_path):
raise werkzeug_exceptions.Forbidden('Error: Invalid help path.')
return self._RedirectToRemoteHelp(help_path) | -810,152,685,980,187,800 | Handles help requests. | grr/server/grr_response_server/gui/wsgiapp.py | _HandleHelp | Codehardt/grr | python | def _HandleHelp(self, request):
help_path = request.path.split('/', 2)[(- 1)]
if (not help_path):
raise werkzeug_exceptions.Forbidden('Error: Invalid help path.')
return self._RedirectToRemoteHelp(help_path) |
@werkzeug_wsgi.responder
def __call__(self, environ, start_response):
'Dispatches a request.'
request = self._BuildRequest(environ)
matcher = self.routing_map.bind_to_environ(environ)
try:
(endpoint, _) = matcher.match(request.path, request.method)
return endpoint(request)
except wer... | -6,936,825,454,743,817,000 | Dispatches a request. | grr/server/grr_response_server/gui/wsgiapp.py | __call__ | Codehardt/grr | python | @werkzeug_wsgi.responder
def __call__(self, environ, start_response):
request = self._BuildRequest(environ)
matcher = self.routing_map.bind_to_environ(environ)
try:
(endpoint, _) = matcher.match(request.path, request.method)
return endpoint(request)
except werkzeug_exceptions.NotFou... |
def WSGIHandler(self):
"Returns GRR's WSGI handler."
sdm = werkzeug_wsgi.SharedDataMiddleware(self, {'/': config.CONFIG['AdminUI.document_root']})
return werkzeug_wsgi.DispatcherMiddleware(self, {'/static': sdm}) | -4,133,702,679,565,647,400 | Returns GRR's WSGI handler. | grr/server/grr_response_server/gui/wsgiapp.py | WSGIHandler | Codehardt/grr | python | def WSGIHandler(self):
sdm = werkzeug_wsgi.SharedDataMiddleware(self, {'/': config.CONFIG['AdminUI.document_root']})
return werkzeug_wsgi.DispatcherMiddleware(self, {'/static': sdm}) |
def scope_vars(scope, trainable_only=False):
'\n Get variables inside a scope\n The scope can be specified as a string\n Parameters\n ----------\n scope: str or VariableScope\n scope in which the variables reside.\n trainable_only: bool\n whether or not to return only the variables t... | -3,037,051,232,383,622,000 | Get variables inside a scope
The scope can be specified as a string
Parameters
----------
scope: str or VariableScope
scope in which the variables reside.
trainable_only: bool
whether or not to return only the variables that were marked as trainable.
Returns
-------
vars: [tf.Variable]
list of variables in ... | baselines/deepq/build_graph.py | scope_vars | rwill128/baselines | python | def scope_vars(scope, trainable_only=False):
'\n Get variables inside a scope\n The scope can be specified as a string\n Parameters\n ----------\n scope: str or VariableScope\n scope in which the variables reside.\n trainable_only: bool\n whether or not to return only the variables t... |
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