blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c4106a3a82de881295cbb5035a067e59df162f59 | [
"super().__init__()\nself.add_module('norm1', Norm(num_input_features))\nself.add_module('relu1', nn.ReLU(inplace=True))\nself.add_module('conv1', Conv(num_input_features, bn_size * growth_rate, kernel_size=1, stride=1, bias=False))\nself.add_module('norm2', Norm(bn_size * growth_rate))\nself.add_module('relu2', nn... | <|body_start_0|>
super().__init__()
self.add_module('norm1', Norm(num_input_features))
self.add_module('relu1', nn.ReLU(inplace=True))
self.add_module('conv1', Conv(num_input_features, bn_size * growth_rate, kernel_size=1, stride=1, bias=False))
self.add_module('norm2', Norm(bn_s... | _DenseLayer | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _DenseLayer:
def __init__(self, num_input_features, growth_rate, bn_size, drop_rate, Norm, Conv):
"""Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of input channels to the layer. growth_rate (int): Number of output channels of each convolution operation ... | stack_v2_sparse_classes_36k_train_031600 | 12,081 | permissive | [
{
"docstring": "Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of input channels to the layer. growth_rate (int): Number of output channels of each convolution operation in the layer. bn_size (int): Factor to scale the number of intermediate channels between the 1x1 and 3x3 conv... | 2 | null | Implement the Python class `_DenseLayer` described below.
Class description:
Implement the _DenseLayer class.
Method signatures and docstrings:
- def __init__(self, num_input_features, growth_rate, bn_size, drop_rate, Norm, Conv): Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of inpu... | Implement the Python class `_DenseLayer` described below.
Class description:
Implement the _DenseLayer class.
Method signatures and docstrings:
- def __init__(self, num_input_features, growth_rate, bn_size, drop_rate, Norm, Conv): Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of inpu... | 72eb99f68205afd5f8d49a3bb6cfc08cfd467582 | <|skeleton|>
class _DenseLayer:
def __init__(self, num_input_features, growth_rate, bn_size, drop_rate, Norm, Conv):
"""Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of input channels to the layer. growth_rate (int): Number of output channels of each convolution operation ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _DenseLayer:
def __init__(self, num_input_features, growth_rate, bn_size, drop_rate, Norm, Conv):
"""Constructor for _DenseLayer class. Parameters: num_input_features (int): Number of input channels to the layer. growth_rate (int): Number of output channels of each convolution operation in the layer. ... | the_stack_v2_python_sparse | GANDLF/models/densenet.py | mlcommons/GaNDLF | train | 45 | |
46396dbb544954d67ac2f79ad1f9cbdd32931612 | [
"self.raw = raw\nself.timestamp = self.parse_timestamp(raw[self.TIMESTAMP])\nself.customer_ID = str(raw[self.CUSTOMER_ID])\nself.note = raw[self.NOTE]\nself.note_snippet = raw[self.NOTE_SNIPPET]\nself.name = raw[self.NAME]\nself.customer_user_name = raw[self.CUSTOMER_USER_NAME]\nself.added_by_username = raw[self.AD... | <|body_start_0|>
self.raw = raw
self.timestamp = self.parse_timestamp(raw[self.TIMESTAMP])
self.customer_ID = str(raw[self.CUSTOMER_ID])
self.note = raw[self.NOTE]
self.note_snippet = raw[self.NOTE_SNIPPET]
self.name = raw[self.NAME]
self.customer_user_name = raw[... | Wrapper for Cloud Commerce customer log records. | CustomerLog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomerLog:
"""Wrapper for Cloud Commerce customer log records."""
def __init__(self, raw):
"""Create log record from API response."""
<|body_0|>
def parse_timestamp(timestamp_string):
"""Return log date string as datetime.datetime. Convert a timestamp in the fo... | stack_v2_sparse_classes_36k_train_031601 | 2,977 | permissive | [
{
"docstring": "Create log record from API response.",
"name": "__init__",
"signature": "def __init__(self, raw)"
},
{
"docstring": "Return log date string as datetime.datetime. Convert a timestamp in the format \"05/11/2018 10:23\" to a datetime.datetime object.",
"name": "parse_timestamp",... | 2 | stack_v2_sparse_classes_30k_train_018530 | Implement the Python class `CustomerLog` described below.
Class description:
Wrapper for Cloud Commerce customer log records.
Method signatures and docstrings:
- def __init__(self, raw): Create log record from API response.
- def parse_timestamp(timestamp_string): Return log date string as datetime.datetime. Convert ... | Implement the Python class `CustomerLog` described below.
Class description:
Wrapper for Cloud Commerce customer log records.
Method signatures and docstrings:
- def __init__(self, raw): Create log record from API response.
- def parse_timestamp(timestamp_string): Return log date string as datetime.datetime. Convert ... | 2df4ac6e350a7eacb377cfecea25bacdb9b73975 | <|skeleton|>
class CustomerLog:
"""Wrapper for Cloud Commerce customer log records."""
def __init__(self, raw):
"""Create log record from API response."""
<|body_0|>
def parse_timestamp(timestamp_string):
"""Return log date string as datetime.datetime. Convert a timestamp in the fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomerLog:
"""Wrapper for Cloud Commerce customer log records."""
def __init__(self, raw):
"""Create log record from API response."""
self.raw = raw
self.timestamp = self.parse_timestamp(raw[self.TIMESTAMP])
self.customer_ID = str(raw[self.CUSTOMER_ID])
self.note... | the_stack_v2_python_sparse | ccapi/requests/customers/getlogs.py | stcstores/ccapi | train | 1 |
5533738cfe772ea3bb4f6f84500b97841a7e4725 | [
"if self.field:\n return 'Summary aggregations for \"{0:s}\"'.format(self.field)\nreturn 'Summary aggregations for an unknown field.'",
"self.field = field\nself.field_query_string = field_query_string\nformatted_field_name = self.format_field_by_type(field)\nif field_query_string == '*':\n formatted_field_... | <|body_start_0|>
if self.field:
return 'Summary aggregations for "{0:s}"'.format(self.field)
return 'Summary aggregations for an unknown field.'
<|end_body_0|>
<|body_start_1|>
self.field = field
self.field_query_string = field_query_string
formatted_field_name = sel... | Summary Aggregations. | SummaryAggregation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit=5):
"""Runs the Summary... | stack_v2_sparse_classes_36k_train_031602 | 13,136 | permissive | [
{
"docstring": "Returns a title for the chart.",
"name": "chart_title",
"signature": "def chart_title(self)"
},
{
"docstring": "Runs the SummaryAggregation aggregator. Args: field: What field to aggregate on. field_query_string: The field value(s) to aggregate on. supported_charts: The chart typ... | 2 | stack_v2_sparse_classes_30k_train_010983 | Implement the Python class `SummaryAggregation` described below.
Class description:
Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit... | Implement the Python class `SummaryAggregation` described below.
Class description:
Summary Aggregations.
Method signatures and docstrings:
- def chart_title(self): Returns a title for the chart.
- def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
<|body_0|>
def run(self, field, field_query_string='*', start_time='', end_time='', most_common_limit=10, rare_value_document_limit=5):
"""Runs the Summary... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SummaryAggregation:
"""Summary Aggregations."""
def chart_title(self):
"""Returns a title for the chart."""
if self.field:
return 'Summary aggregations for "{0:s}"'.format(self.field)
return 'Summary aggregations for an unknown field.'
def run(self, field, field_q... | the_stack_v2_python_sparse | timesketch/lib/aggregators/summary.py | google/timesketch | train | 2,263 |
e605f353656a8dceab4f7be24fc03942ac20f4fc | [
"if len(A) < 3:\n return 0\nA.append(2 ** 32)\nlast = 0\nret = 0\nold = 2 ** 32\nfor i in range(len(A) - 1):\n if A[i + 1] - A[i] == old:\n last += 1\n else:\n old = A[i + 1] - A[i]\n if last > 1:\n last -= 1\n ret += last * (last + 1) / 2\n last = 1\nretur... | <|body_start_0|>
if len(A) < 3:
return 0
A.append(2 ** 32)
last = 0
ret = 0
old = 2 ** 32
for i in range(len(A) - 1):
if A[i + 1] - A[i] == old:
last += 1
else:
old = A[i + 1] - A[i]
if la... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numberOfArithmeticSlices(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def numberOfArithmeticSlices1(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(A) < 3:
ret... | stack_v2_sparse_classes_36k_train_031603 | 1,349 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "numberOfArithmeticSlices",
"signature": "def numberOfArithmeticSlices(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "numberOfArithmeticSlices1",
"signature": "def numberOfArithmeticSlices1(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfArithmeticSlices(self, A): :type A: List[int] :rtype: int
- def numberOfArithmeticSlices1(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numberOfArithmeticSlices(self, A): :type A: List[int] :rtype: int
- def numberOfArithmeticSlices1(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def numberOfArithmeticSlices(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def numberOfArithmeticSlices1(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numberOfArithmeticSlices(self, A):
""":type A: List[int] :rtype: int"""
if len(A) < 3:
return 0
A.append(2 ** 32)
last = 0
ret = 0
old = 2 ** 32
for i in range(len(A) - 1):
if A[i + 1] - A[i] == old:
... | the_stack_v2_python_sparse | python/leetcode/413_Arithmetic_Slices.py | bobcaoge/my-code | train | 0 | |
419312cb8dc2220351eab71ae3594c7d722cba4b | [
"n_features = self.n_features\nplaceholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes)\nwith graph.as_default():\n with placeholder_scope:\n self.mol_features = tf.placeholder(tf.float32, shape=[None, n_features], name='mol_features')\n layer_sizes = self.layer_sizes\n weight_i... | <|body_start_0|>
n_features = self.n_features
placeholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes)
with graph.as_default():
with placeholder_scope:
self.mol_features = tf.placeholder(tf.float32, shape=[None, n_features], name='mol_features')
... | Implements an icml model as configured in a model_config.proto. | TensorflowMultiTaskRegressor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule d... | stack_v2_sparse_classes_36k_train_031604 | 32,492 | permissive | [
{
"docstring": "Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule descriptor (e.g. fingerprint) tensor with shape batch_size x n_features.",
"name": "build",
"signature": "def build(self, graph, name_scopes, training)"
... | 2 | stack_v2_sparse_classes_30k_train_005599 | Implement the Python class `TensorflowMultiTaskRegressor` described below.
Class description:
Implements an icml model as configured in a model_config.proto.
Method signatures and docstrings:
- def build(self, graph, name_scopes, training): Constructs the graph architecture as specified in its config. This method cre... | Implement the Python class `TensorflowMultiTaskRegressor` described below.
Class description:
Implements an icml model as configured in a model_config.proto.
Method signatures and docstrings:
- def build(self, graph, name_scopes, training): Constructs the graph architecture as specified in its config. This method cre... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule descriptor (e.... | the_stack_v2_python_sparse | contrib/atomicconv/models/legacy.py | deepchem/deepchem | train | 4,876 |
a6baefee293177b5f32bb3be0ade3a0113d477b4 | [
"L = self.codomain().base_ring()\nWR = self.codomain().weil_restriction()\nif L.is_finite():\n d = L.degree()\n if d == 1:\n return self\n newP = []\n for t in self:\n c = t.polynomial().coefficients(sparse=False)\n c = c + (d - len(c)) * [0]\n newP += c\nelse:\n d = L.rel... | <|body_start_0|>
L = self.codomain().base_ring()
WR = self.codomain().weil_restriction()
if L.is_finite():
d = L.degree()
if d == 1:
return self
newP = []
for t in self:
c = t.polynomial().coefficients(sparse=False)
... | SchemeMorphism_point_affine_field | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchemeMorphism_point_affine_field:
def weil_restriction(self):
"""Compute the Weil restriction of this point over some extension field. If the field is a finite field, then this computes the Weil restriction to the prime subfield. A Weil restriction of scalars - denoted `Res_{L/k}` - is ... | stack_v2_sparse_classes_36k_train_031605 | 15,505 | no_license | [
{
"docstring": "Compute the Weil restriction of this point over some extension field. If the field is a finite field, then this computes the Weil restriction to the prime subfield. A Weil restriction of scalars - denoted `Res_{L/k}` - is a functor which, for any finite extension of fields `L/k` and any algebrai... | 3 | null | Implement the Python class `SchemeMorphism_point_affine_field` described below.
Class description:
Implement the SchemeMorphism_point_affine_field class.
Method signatures and docstrings:
- def weil_restriction(self): Compute the Weil restriction of this point over some extension field. If the field is a finite field... | Implement the Python class `SchemeMorphism_point_affine_field` described below.
Class description:
Implement the SchemeMorphism_point_affine_field class.
Method signatures and docstrings:
- def weil_restriction(self): Compute the Weil restriction of this point over some extension field. If the field is a finite field... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class SchemeMorphism_point_affine_field:
def weil_restriction(self):
"""Compute the Weil restriction of this point over some extension field. If the field is a finite field, then this computes the Weil restriction to the prime subfield. A Weil restriction of scalars - denoted `Res_{L/k}` - is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchemeMorphism_point_affine_field:
def weil_restriction(self):
"""Compute the Weil restriction of this point over some extension field. If the field is a finite field, then this computes the Weil restriction to the prime subfield. A Weil restriction of scalars - denoted `Res_{L/k}` - is a functor whic... | the_stack_v2_python_sparse | sage/src/sage/schemes/affine/affine_point.py | bopopescu/geosci | train | 0 | |
3ae529ed25137259e089590503d195acaeb11622 | [
"kwargs = locals()\nimage, mask = zipp.zipper_interp_rows(**kwargs)\nreturn (image, mask)",
"min_cols = config.getint(cls.step_name, 'min_cols')\nmax_cols = config.getint(cls.step_name, 'max_cols')\ninterp_mask = maskbits.parse_badpix_mask(config.get(cls.step_name, 'interp_mask'))\ninvalid_mask = maskbits.parse_b... | <|body_start_0|>
kwargs = locals()
image, mask = zipp.zipper_interp_rows(**kwargs)
return (image, mask)
<|end_body_0|>
<|body_start_1|>
min_cols = config.getint(cls.step_name, 'min_cols')
max_cols = config.getint(cls.step_name, 'max_cols')
interp_mask = maskbits.parse_ba... | ZipperInterp | [
"NCSA"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZipperInterp:
def __call__(cls, image, mask, interp_mask=DEFAULT_INTERP_MASK, BADPIX_INTERP=maskbits.BADPIX_INTERP, min_cols=DEFAULT_MINCOLS, max_cols=DEFAULT_MAXCOLS, invalid_mask=DEFAULT_INVALID_MASK, add_noise=DEFAULT_ADD_NOISE, clobber=DEFAULT_CLOBBER, block_size=DEFAULT_BLOCK_SIZE, logger=l... | stack_v2_sparse_classes_36k_train_031606 | 5,753 | permissive | [
{
"docstring": "Interpolate over selected pixels by inserting average of pixels to left and right of any bunch of adjacent selected pixels. If the interpolation region touches an edge, or the adjacent pixel has flags marking it as invalid, than the value at other border is used for interpolation. No interpolati... | 3 | stack_v2_sparse_classes_30k_train_001438 | Implement the Python class `ZipperInterp` described below.
Class description:
Implement the ZipperInterp class.
Method signatures and docstrings:
- def __call__(cls, image, mask, interp_mask=DEFAULT_INTERP_MASK, BADPIX_INTERP=maskbits.BADPIX_INTERP, min_cols=DEFAULT_MINCOLS, max_cols=DEFAULT_MAXCOLS, invalid_mask=DEF... | Implement the Python class `ZipperInterp` described below.
Class description:
Implement the ZipperInterp class.
Method signatures and docstrings:
- def __call__(cls, image, mask, interp_mask=DEFAULT_INTERP_MASK, BADPIX_INTERP=maskbits.BADPIX_INTERP, min_cols=DEFAULT_MINCOLS, max_cols=DEFAULT_MAXCOLS, invalid_mask=DEF... | 8a299e9368d01cac51f53af6e4937e797f378d7a | <|skeleton|>
class ZipperInterp:
def __call__(cls, image, mask, interp_mask=DEFAULT_INTERP_MASK, BADPIX_INTERP=maskbits.BADPIX_INTERP, min_cols=DEFAULT_MINCOLS, max_cols=DEFAULT_MAXCOLS, invalid_mask=DEFAULT_INVALID_MASK, add_noise=DEFAULT_ADD_NOISE, clobber=DEFAULT_CLOBBER, block_size=DEFAULT_BLOCK_SIZE, logger=l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZipperInterp:
def __call__(cls, image, mask, interp_mask=DEFAULT_INTERP_MASK, BADPIX_INTERP=maskbits.BADPIX_INTERP, min_cols=DEFAULT_MINCOLS, max_cols=DEFAULT_MAXCOLS, invalid_mask=DEFAULT_INVALID_MASK, add_noise=DEFAULT_ADD_NOISE, clobber=DEFAULT_CLOBBER, block_size=DEFAULT_BLOCK_SIZE, logger=logger):
... | the_stack_v2_python_sparse | python/pixcorrect/row_zipper.py | DarkEnergySurvey/pixcorrect | train | 1 | |
80d987c09743f66d7c7997655523d5e0aa163d1d | [
"result = 0\nfor i in xrange(0, len(nums)):\n for j in xrange(i + 1, len(nums)):\n result += self.findHammingDistance(nums[i] ^ nums[j])\nreturn result",
"count = 0\nwhile num != 0:\n count += num & 1\n num >>= 1\nreturn count"
] | <|body_start_0|>
result = 0
for i in xrange(0, len(nums)):
for j in xrange(i + 1, len(nums)):
result += self.findHammingDistance(nums[i] ^ nums[j])
return result
<|end_body_0|>
<|body_start_1|>
count = 0
while num != 0:
count += num & 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findHammingDistance(self, num):
""":param num: int :return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = 0
for i in xrange... | stack_v2_sparse_classes_36k_train_031607 | 561 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "totalHammingDistance",
"signature": "def totalHammingDistance(self, nums)"
},
{
"docstring": ":param num: int :return: int",
"name": "findHammingDistance",
"signature": "def findHammingDistance(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012471 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int
- def findHammingDistance(self, num): :param num: int :return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int
- def findHammingDistance(self, num): :param num: int :return: int
<|skeleton|>
class Solution:
def ... | 0a833b8f666385500de5a55731b1a5590827b207 | <|skeleton|>
class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findHammingDistance(self, num):
""":param num: int :return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
result = 0
for i in xrange(0, len(nums)):
for j in xrange(i + 1, len(nums)):
result += self.findHammingDistance(nums[i] ^ nums[j])
return result
def findHamm... | the_stack_v2_python_sparse | LeetCode-Python/477. Total Hamming Distance.py | KaranJaswani/Codes | train | 0 | |
fa84ce7c05b9b606acab73a0155ebd59b63af657 | [
"self.center = Joint(origin, original_orientation, (False, False))\nself.neck = Joint(self.center.location + self.NECK_OFFSET_Z * e3, original_orientation, (False, [False, (number('-38.5'), number('29.5')), (number('-119.5'), number('119.5'))]))\nself.laser = Joint(self.neck.location + self.LASER_OFFSET_Z * e3, ori... | <|body_start_0|>
self.center = Joint(origin, original_orientation, (False, False))
self.neck = Joint(self.center.location + self.NECK_OFFSET_Z * e3, original_orientation, (False, [False, (number('-38.5'), number('29.5')), (number('-119.5'), number('119.5'))]))
self.laser = Joint(self.neck.locati... | NAO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NAO:
def __init__(self):
"""Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's "name space"."""
<|body_0|>
def compute_move(self, chain_name, target):
"""Compute the angles between the joints for the target posit... | stack_v2_sparse_classes_36k_train_031608 | 4,066 | no_license | [
{
"docstring": "Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's \"name space\".",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compute the angles between the joints for the target position. It does not send the... | 2 | stack_v2_sparse_classes_30k_train_018033 | Implement the Python class `NAO` described below.
Class description:
Implement the NAO class.
Method signatures and docstrings:
- def __init__(self): Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's "name space".
- def compute_move(self, chain_name, target): Co... | Implement the Python class `NAO` described below.
Class description:
Implement the NAO class.
Method signatures and docstrings:
- def __init__(self): Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's "name space".
- def compute_move(self, chain_name, target): Co... | d4491170d154e44212d4d1b6356980ff4fbf840f | <|skeleton|>
class NAO:
def __init__(self):
"""Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's "name space"."""
<|body_0|>
def compute_move(self, chain_name, target):
"""Compute the angles between the joints for the target posit... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NAO:
def __init__(self):
"""Generate the skeletal structure of the robot. It puts all the joints and kinematic chains in the object's "name space"."""
self.center = Joint(origin, original_orientation, (False, False))
self.neck = Joint(self.center.location + self.NECK_OFFSET_Z * e3, ori... | the_stack_v2_python_sparse | old/code/model.py | pkok/bsc-thesis | train | 1 | |
9e7a32ae9f6da41d06b0a066bc8fd2ff2d931ced | [
"for testvalue, expected in self.knownvalues:\n p = project.Project()\n result = p.dat_lump(testvalue, validate=True)\n self.assertEqual(expected, result)",
"for testvalue, expected in self.knownvalues:\n p = project.Project()\n result = p.dat_lump(testvalue)\n self.assertEqual(expected, result)... | <|body_start_0|>
for testvalue, expected in self.knownvalues:
p = project.Project()
result = p.dat_lump(testvalue, validate=True)
self.assertEqual(expected, result)
<|end_body_0|>
<|body_start_1|>
for testvalue, expected in self.knownvalues:
p = project.P... | Test dat_lump validator | dat_lump_knownvalues | [
"BSD-2-Clause",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class dat_lump_knownvalues:
"""Test dat_lump validator"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
<|body_0|>
def test_knownvalues_set(self):
"""Test that known values are set correctly"""
<|body_1|>
def tes... | stack_v2_sparse_classes_36k_train_031609 | 3,994 | permissive | [
{
"docstring": "Test that known values are validated correctly",
"name": "test_knownvalues_validate",
"signature": "def test_knownvalues_validate(self)"
},
{
"docstring": "Test that known values are set correctly",
"name": "test_knownvalues_set",
"signature": "def test_knownvalues_set(se... | 3 | stack_v2_sparse_classes_30k_train_012408 | Implement the Python class `dat_lump_knownvalues` described below.
Class description:
Test dat_lump validator
Method signatures and docstrings:
- def test_knownvalues_validate(self): Test that known values are validated correctly
- def test_knownvalues_set(self): Test that known values are set correctly
- def test_se... | Implement the Python class `dat_lump_knownvalues` described below.
Class description:
Test dat_lump validator
Method signatures and docstrings:
- def test_knownvalues_validate(self): Test that known values are validated correctly
- def test_knownvalues_set(self): Test that known values are set correctly
- def test_se... | 307a9de864566fece1a999888e19048aeef9734c | <|skeleton|>
class dat_lump_knownvalues:
"""Test dat_lump validator"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
<|body_0|>
def test_knownvalues_set(self):
"""Test that known values are set correctly"""
<|body_1|>
def tes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class dat_lump_knownvalues:
"""Test dat_lump validator"""
def test_knownvalues_validate(self):
"""Test that known values are validated correctly"""
for testvalue, expected in self.knownvalues:
p = project.Project()
result = p.dat_lump(testvalue, validate=True)
... | the_stack_v2_python_sparse | project_test.py | An-dz/tilecutter | train | 4 |
c0ae908c559fe007b7d36782d7643370e2131a72 | [
"self.url = args.url\nif args.token is not None:\n self.token = args.token\nelse:\n self.netrcfile = args.netrcfile\n self.token = self.netrc()",
"gitlab_connection = gitlab.Gitlab(self.url, self.token)\ngitlab_connection.auth()\nreturn gitlab_connection",
"try:\n parser = netrc.netrc(self.netrcfile... | <|body_start_0|>
self.url = args.url
if args.token is not None:
self.token = args.token
else:
self.netrcfile = args.netrcfile
self.token = self.netrc()
<|end_body_0|>
<|body_start_1|>
gitlab_connection = gitlab.Gitlab(self.url, self.token)
git... | Main user auth class. | User | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
"""Main user auth class."""
def __init__(self, args):
"""Init a thing"""
<|body_0|>
def auth(self):
"""Authorize user using token to GitLab API."""
<|body_1|>
def netrc(self):
"""Use Netrc default or --netrcfile if passed as fallback.""... | stack_v2_sparse_classes_36k_train_031610 | 1,433 | permissive | [
{
"docstring": "Init a thing",
"name": "__init__",
"signature": "def __init__(self, args)"
},
{
"docstring": "Authorize user using token to GitLab API.",
"name": "auth",
"signature": "def auth(self)"
},
{
"docstring": "Use Netrc default or --netrcfile if passed as fallback.",
... | 3 | stack_v2_sparse_classes_30k_train_005239 | Implement the Python class `User` described below.
Class description:
Main user auth class.
Method signatures and docstrings:
- def __init__(self, args): Init a thing
- def auth(self): Authorize user using token to GitLab API.
- def netrc(self): Use Netrc default or --netrcfile if passed as fallback. | Implement the Python class `User` described below.
Class description:
Main user auth class.
Method signatures and docstrings:
- def __init__(self, args): Init a thing
- def auth(self): Authorize user using token to GitLab API.
- def netrc(self): Use Netrc default or --netrcfile if passed as fallback.
<|skeleton|>
cl... | 8ced932bf143148fe5a41fe7a5b5ef17cd7720af | <|skeleton|>
class User:
"""Main user auth class."""
def __init__(self, args):
"""Init a thing"""
<|body_0|>
def auth(self):
"""Authorize user using token to GitLab API."""
<|body_1|>
def netrc(self):
"""Use Netrc default or --netrcfile if passed as fallback.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class User:
"""Main user auth class."""
def __init__(self, args):
"""Init a thing"""
self.url = args.url
if args.token is not None:
self.token = args.token
else:
self.netrcfile = args.netrcfile
self.token = self.netrc()
def auth(self):
... | the_stack_v2_python_sparse | gitlab_api/auth/user.py | mrlesmithjr/python-gitlab-api | train | 1 |
6bb164861316ce0e8cd53a7bf584b50ab695464d | [
"self.nums = nums\nself.lens = len(nums)\nself.BIT = [0] * (self.lens + 1)\nfor i in range(self.lens):\n k = i + 1\n while k <= self.lens:\n self.BIT[k] += nums[i]\n k += k & -k",
"diff = val - self.nums[i]\nself.nums[i] = val\ni += 1\nwhile i <= self.lens:\n self.BIT[i] += diff\n i += i... | <|body_start_0|>
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
k += k & -k
<|end_body_0|>
<|body_start_1|>
diff = v... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_36k_train_031611 | 1,866 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, i, val)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
... | 3 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): :type i: int :type j: int :rtype:... | 212f8b83d6ac22db1a777f980075d9e12ce521d2 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
""":type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
... | the_stack_v2_python_sparse | LeetCode/python/307_(Binary Indexed Tree)_hard_Range Sum Query - Mutable.py | FrankieZhen/Lookoop | train | 1 | |
60782add4eab9020f5eeb94e8d669daff1d8dc72 | [
"if padding:\n for item in input:\n item.insert(0, 0)\n item.append(0)\n z = [0] * len(input[0])\n input.insert(0, z)\n input.append(z)\ni_h = len(input)\ni_w = len(input[0])\nf_h = len(filter)\nf_w = len(filter[0])\nif (i_h - f_h) % stride != 0:\n print('!!请重新分配padding的长度')\n return... | <|body_start_0|>
if padding:
for item in input:
item.insert(0, 0)
item.append(0)
z = [0] * len(input[0])
input.insert(0, z)
input.append(z)
i_h = len(input)
i_w = len(input[0])
f_h = len(filter)
f_w =... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def test(self, input, filter, padding, stride):
"""input为输入矩阵，filter为卷积核，返回卷积之后的结果"""
<|body_0|>
def sum(self, input, row, col, filter):
"""row,col为卷积操作在input的起始位置"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if padding:
for... | stack_v2_sparse_classes_36k_train_031612 | 1,599 | no_license | [
{
"docstring": "input为输入矩阵，filter为卷积核，返回卷积之后的结果",
"name": "test",
"signature": "def test(self, input, filter, padding, stride)"
},
{
"docstring": "row,col为卷积操作在input的起始位置",
"name": "sum",
"signature": "def sum(self, input, row, col, filter)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020056 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def test(self, input, filter, padding, stride): input为输入矩阵，filter为卷积核，返回卷积之后的结果
- def sum(self, input, row, col, filter): row,col为卷积操作在input的起始位置 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def test(self, input, filter, padding, stride): input为输入矩阵，filter为卷积核，返回卷积之后的结果
- def sum(self, input, row, col, filter): row,col为卷积操作在input的起始位置
<|skeleton|>
class Solution:
... | ef6aee94c7990d734271c204034ec273b665226d | <|skeleton|>
class Solution:
def test(self, input, filter, padding, stride):
"""input为输入矩阵，filter为卷积核，返回卷积之后的结果"""
<|body_0|>
def sum(self, input, row, col, filter):
"""row,col为卷积操作在input的起始位置"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def test(self, input, filter, padding, stride):
"""input为输入矩阵，filter为卷积核，返回卷积之后的结果"""
if padding:
for item in input:
item.insert(0, 0)
item.append(0)
z = [0] * len(input[0])
input.insert(0, z)
input.appen... | the_stack_v2_python_sparse | 卷积操作.py | godzzbboss/leetcode | train | 0 | |
df94bd2dae0d74c9245f3edd8ee9e9820dc07ef6 | [
"self.user = user\nself.first_name = first_name\nself.last_name = last_name\nself.facebook = facebook\nself.google = google\nself.github = github\nCreator.__init__(self)",
"names = str(full_name).split(' ')\nself.last_name = ''\nself.first_name = names.pop(0)\nif len(names) > 0:\n self.last_name = ' '.join(nam... | <|body_start_0|>
self.user = user
self.first_name = first_name
self.last_name = last_name
self.facebook = facebook
self.google = google
self.github = github
Creator.__init__(self)
<|end_body_0|>
<|body_start_1|>
names = str(full_name).split(' ')
s... | UserProfileCreator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional param... | stack_v2_sparse_classes_36k_train_031613 | 12,165 | no_license | [
{
"docstring": "The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional params are scalar column values belonging on the UserProfile table. :param user: :param first_name: :param last_name: :param f... | 3 | stack_v2_sparse_classes_30k_train_016766 | Implement the Python class `UserProfileCreator` described below.
Class description:
Implement the UserProfileCreator class.
Method signatures and docstrings:
- def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''): The User Object must be passed into UserProfileCreator on init, the ... | Implement the Python class `UserProfileCreator` described below.
Class description:
Implement the UserProfileCreator class.
Method signatures and docstrings:
- def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''): The User Object must be passed into UserProfileCreator on init, the ... | e5401680f13299ece8d78f51e45c90773015cde4 | <|skeleton|>
class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional param... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserProfileCreator:
def __init__(self, user, first_name='', last_name='', facebook='', google='', github=''):
"""The User Object must be passed into UserProfileCreator on init, the rest of the arguments are optional and could also be set after __init__ if needed. All the additional params are scalar c... | the_stack_v2_python_sparse | doc_docs/public/creator/creator.py | mrosata/doc-docs | train | 0 | |
744b1263b0fd6f8b6ce1192b112096f5b9851353 | [
"queryset = super().get_queryset()\nif self.exclude_unverified:\n return queryset.filter(verified=True)\nreturn queryset",
"kwargs['verified'] = kwargs.get('verified', False)\nobject: 'ModeratedModel' = super().create(*args, **kwargs)\nreturn object",
"object: 'ModeratedModel'\nobject, created = super().get_... | <|body_start_0|>
queryset = super().get_queryset()
if self.exclude_unverified:
return queryset.filter(verified=True)
return queryset
<|end_body_0|>
<|body_start_1|>
kwargs['verified'] = kwargs.get('verified', False)
object: 'ModeratedModel' = super().create(*args, **... | Manager for moderated models. | ModeratedManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModeratedManager:
"""Manager for moderated models."""
def get_queryset(self) -> ModeratedQuerySet:
"""Return the default queryset to be used by the manager."""
<|body_0|>
def create(self, *args, **kwargs) -> 'ModeratedModel':
"""Create and return a model instance... | stack_v2_sparse_classes_36k_train_031614 | 2,139 | no_license | [
{
"docstring": "Return the default queryset to be used by the manager.",
"name": "get_queryset",
"signature": "def get_queryset(self) -> ModeratedQuerySet"
},
{
"docstring": "Create and return a model instance.",
"name": "create",
"signature": "def create(self, *args, **kwargs) -> 'Moder... | 3 | null | Implement the Python class `ModeratedManager` described below.
Class description:
Manager for moderated models.
Method signatures and docstrings:
- def get_queryset(self) -> ModeratedQuerySet: Return the default queryset to be used by the manager.
- def create(self, *args, **kwargs) -> 'ModeratedModel': Create and re... | Implement the Python class `ModeratedManager` described below.
Class description:
Manager for moderated models.
Method signatures and docstrings:
- def get_queryset(self) -> ModeratedQuerySet: Return the default queryset to be used by the manager.
- def create(self, *args, **kwargs) -> 'ModeratedModel': Create and re... | 8bbdc8eec3622af22c17214051c34e36bea8e05a | <|skeleton|>
class ModeratedManager:
"""Manager for moderated models."""
def get_queryset(self) -> ModeratedQuerySet:
"""Return the default queryset to be used by the manager."""
<|body_0|>
def create(self, *args, **kwargs) -> 'ModeratedModel':
"""Create and return a model instance... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModeratedManager:
"""Manager for moderated models."""
def get_queryset(self) -> ModeratedQuerySet:
"""Return the default queryset to be used by the manager."""
queryset = super().get_queryset()
if self.exclude_unverified:
return queryset.filter(verified=True)
r... | the_stack_v2_python_sparse | apps/moderation/models/moderated_model/manager.py | abdulwahed-mansour/modularhistory | train | 1 |
e864327a837f59188aa01a10d763c0827779d836 | [
"self.supervised_input = ImageNetInput(split=supervised_split, is_training=True, batch_size=supervised_batch_size, augmentation=supervised_augmentation, **kwargs)\nself.unsupervised_input = ImageNetInput(split='train', is_training=True, batch_size=unsupervised_batch_size, augmentation=unsupervised_augmentation, **k... | <|body_start_0|>
self.supervised_input = ImageNetInput(split=supervised_split, is_training=True, batch_size=supervised_batch_size, augmentation=supervised_augmentation, **kwargs)
self.unsupervised_input = ImageNetInput(split='train', is_training=True, batch_size=unsupervised_batch_size, augmentation=uns... | Generates Imagenet input_fn for semi-supervised training. | ImageNetSslTrainInput | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageNetSslTrainInput:
"""Generates Imagenet input_fn for semi-supervised training."""
def __init__(self, supervised_split, supervised_batch_size, unsupervised_batch_size, supervised_augmentation, unsupervised_augmentation, **kwargs):
"""Initialize ImageNetSslTrainInput. Args: superv... | stack_v2_sparse_classes_36k_train_031615 | 16,434 | permissive | [
{
"docstring": "Initialize ImageNetSslTrainInput. Args: supervised_split: split of supervised data. supervised_batch_size: batch size for supervised data. unsupervised_batch_size: batch size for unsupervised data. supervised_augmentation: augmentation for supervised data. unsupervised_augmentation: augmentation... | 2 | stack_v2_sparse_classes_30k_test_000924 | Implement the Python class `ImageNetSslTrainInput` described below.
Class description:
Generates Imagenet input_fn for semi-supervised training.
Method signatures and docstrings:
- def __init__(self, supervised_split, supervised_batch_size, unsupervised_batch_size, supervised_augmentation, unsupervised_augmentation, ... | Implement the Python class `ImageNetSslTrainInput` described below.
Class description:
Generates Imagenet input_fn for semi-supervised training.
Method signatures and docstrings:
- def __init__(self, supervised_split, supervised_batch_size, unsupervised_batch_size, supervised_augmentation, unsupervised_augmentation, ... | f8b7f184b91d6144927c7c4b34f7d9c0313f8a39 | <|skeleton|>
class ImageNetSslTrainInput:
"""Generates Imagenet input_fn for semi-supervised training."""
def __init__(self, supervised_split, supervised_batch_size, unsupervised_batch_size, supervised_augmentation, unsupervised_augmentation, **kwargs):
"""Initialize ImageNetSslTrainInput. Args: superv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageNetSslTrainInput:
"""Generates Imagenet input_fn for semi-supervised training."""
def __init__(self, supervised_split, supervised_batch_size, unsupervised_batch_size, supervised_augmentation, unsupervised_augmentation, **kwargs):
"""Initialize ImageNetSslTrainInput. Args: supervised_split: s... | the_stack_v2_python_sparse | imagenet/datasets/imagenet.py | paulxiong/fixmatch | train | 1 |
c4d309a75020ab6eeafd6255881ba5197980b08b | [
"import revitron\ntry:\n return revitron.Document(self.element.GetLinkDocument()).getPath()\nexcept:\n pass",
"import revitron\ntry:\n return revitron.DOC.GetElement(self.get('Type'))\nexcept:\n pass"
] | <|body_start_0|>
import revitron
try:
return revitron.Document(self.element.GetLinkDocument()).getPath()
except:
pass
<|end_body_0|>
<|body_start_1|>
import revitron
try:
return revitron.DOC.GetElement(self.get('Type'))
except:
... | A wrapper class for Revit links. | LinkRvt | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
<|body_0|>
def getType(self):
"""Gets the type object of the link. Returns: object: The Link type"""
<|body_1|... | stack_v2_sparse_classes_36k_train_031616 | 621 | permissive | [
{
"docstring": "Gets the path of the linked document. Returns: string: The path on disk",
"name": "getPath",
"signature": "def getPath(self)"
},
{
"docstring": "Gets the type object of the link. Returns: object: The Link type",
"name": "getType",
"signature": "def getType(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012585 | Implement the Python class `LinkRvt` described below.
Class description:
A wrapper class for Revit links.
Method signatures and docstrings:
- def getPath(self): Gets the path of the linked document. Returns: string: The path on disk
- def getType(self): Gets the type object of the link. Returns: object: The Link type | Implement the Python class `LinkRvt` described below.
Class description:
A wrapper class for Revit links.
Method signatures and docstrings:
- def getPath(self): Gets the path of the linked document. Returns: string: The path on disk
- def getType(self): Gets the type object of the link. Returns: object: The Link type... | f373a0388c8b45f14f93510c9e8870190dba3b78 | <|skeleton|>
class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
<|body_0|>
def getType(self):
"""Gets the type object of the link. Returns: object: The Link type"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkRvt:
"""A wrapper class for Revit links."""
def getPath(self):
"""Gets the path of the linked document. Returns: string: The path on disk"""
import revitron
try:
return revitron.Document(self.element.GetLinkDocument()).getPath()
except:
pass
... | the_stack_v2_python_sparse | revitron/link.py | Thomas84/revitron | train | 0 |
f2c774a34b6fb013001e9d10ec56cb84462cea63 | [
"self.datasets = datasets\nself.templates = {dataset_name: datasets[dataset_name]['template'] for dataset_name in datasets}\nself.phrases = {dataset_name: datasets[dataset_name]['phrases'] for dataset_name in datasets}\nself.texts = {dataset_name: datasets[dataset_name]['texts'] for dataset_name in datasets}",
"i... | <|body_start_0|>
self.datasets = datasets
self.templates = {dataset_name: datasets[dataset_name]['template'] for dataset_name in datasets}
self.phrases = {dataset_name: datasets[dataset_name]['phrases'] for dataset_name in datasets}
self.texts = {dataset_name: datasets[dataset_name]['tex... | DemoData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DemoData:
def __init__(self):
"""A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized 18th century Dutch newspapers from the National Library of the Netherlands. It contains a small ... | stack_v2_sparse_classes_36k_train_031617 | 3,633 | permissive | [
{
"docstring": "A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized 18th century Dutch newspapers from the National Library of the Netherlands. It contains a small sample of texts from newspaper advertisem... | 5 | stack_v2_sparse_classes_30k_test_000282 | Implement the Python class `DemoData` described below.
Class description:
Implement the DemoData class.
Method signatures and docstrings:
- def __init__(self): A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized... | Implement the Python class `DemoData` described below.
Class description:
Implement the DemoData class.
Method signatures and docstrings:
- def __init__(self): A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized... | 1ac61e558f16b5a35918f55ac1f65857c740601e | <|skeleton|>
class DemoData:
def __init__(self):
"""A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized 18th century Dutch newspapers from the National Library of the Netherlands. It contains a small ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DemoData:
def __init__(self):
"""A object for accessing datasets for demonstrations and testing. It contains the following datasets: 1. auction_advertisements: this is a use case of digitized 18th century Dutch newspapers from the National Library of the Netherlands. It contains a small sample of text... | the_stack_v2_python_sparse | data/demo_data.py | marijnkoolen/fuzzy-search | train | 18 | |
8a5e866c031c4cb5a5b6bdb532290ce72f1ffc34 | [
"kwargs = locals().copy()\nself._is_ray_client = ray.util.client.ray.is_connected()\nif _tuner_internal:\n if not self._is_ray_client:\n self._local_tuner = kwargs[_TUNER_INTERNAL]\n else:\n self._remote_tuner = kwargs[_TUNER_INTERNAL]\nelse:\n kwargs.pop(_TUNER_INTERNAL, None)\n kwargs.po... | <|body_start_0|>
kwargs = locals().copy()
self._is_ray_client = ray.util.client.ray.is_connected()
if _tuner_internal:
if not self._is_ray_client:
self._local_tuner = kwargs[_TUNER_INTERNAL]
else:
self._remote_tuner = kwargs[_TUNER_INTERNAL... | HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210. | TunerRay210 | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TunerRay210:
"""HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210."""
def __init__(self, trainable: Optional[Union[str, Callable, Type[Trainable], 'BaseTrai... | stack_v2_sparse_classes_36k_train_031618 | 5,763 | permissive | [
{
"docstring": "Configure and construct a tune run.",
"name": "__init__",
"signature": "def __init__(self, trainable: Optional[Union[str, Callable, Type[Trainable], 'BaseTrainer']]=None, *, param_space: Optional[Dict[str, Any]]=None, tune_config: Optional[TuneConfig]=None, run_config: Optional[RunConfig... | 2 | null | Implement the Python class `TunerRay210` described below.
Class description:
HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210.
Method signatures and docstrings:
- def __init__(self,... | Implement the Python class `TunerRay210` described below.
Class description:
HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210.
Method signatures and docstrings:
- def __init__(self,... | e1d023e41606c9b76b35e1d231c2f13368a30eca | <|skeleton|>
class TunerRay210:
"""HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210."""
def __init__(self, trainable: Optional[Union[str, Callable, Type[Trainable], 'BaseTrai... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TunerRay210:
"""HACK(geoffrey): This is a temporary fix to support Ray 2.1.0. Specifically, this Tuner ensures that TunerInternalRay210 is called by the class. For more details, see TunerInternalRay210."""
def __init__(self, trainable: Optional[Union[str, Callable, Type[Trainable], 'BaseTrainer']]=None, ... | the_stack_v2_python_sparse | ludwig/backend/_ray210_compat.py | ludwig-ai/ludwig | train | 2,567 |
a970b507741bcd2b7bd2659887c6c90985b6b7c5 | [
"super(AlternatingCoattention, self).__init__()\nself.n_entities = 1 if weight_tying else 2\nwith self.init_scope():\n self.energy_layers_1 = chainer.ChainList(*[GraphLinear(hidden_dim + out_dim, head) for _ in range(self.n_entities)])\n self.energy_layers_2 = chainer.ChainList(*[GraphLinear(head, 1)])\n s... | <|body_start_0|>
super(AlternatingCoattention, self).__init__()
self.n_entities = 1 if weight_tying else 2
with self.init_scope():
self.energy_layers_1 = chainer.ChainList(*[GraphLinear(hidden_dim + out_dim, head) for _ in range(self.n_entities)])
self.energy_layers_2 = c... | AlternatingCoattention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlternatingCoattention:
def __init__(self, hidden_dim, out_dim, head, weight_tying=False):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism :param weight_tying: indicate whethe... | stack_v2_sparse_classes_36k_train_031619 | 3,771 | permissive | [
{
"docstring": ":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism :param weight_tying: indicate whether the weights should be shared between two attention computation",
"name": "__init__",
"signat... | 3 | stack_v2_sparse_classes_30k_train_002795 | Implement the Python class `AlternatingCoattention` described below.
Class description:
Implement the AlternatingCoattention class.
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, weight_tying=False): :param hidden_dim: dimension of atom representation :param out_dim: dimension of mo... | Implement the Python class `AlternatingCoattention` described below.
Class description:
Implement the AlternatingCoattention class.
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, weight_tying=False): :param hidden_dim: dimension of atom representation :param out_dim: dimension of mo... | 21b64a3c8cc9bc33718ae09c65aa917e575132eb | <|skeleton|>
class AlternatingCoattention:
def __init__(self, hidden_dim, out_dim, head, weight_tying=False):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism :param weight_tying: indicate whethe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlternatingCoattention:
def __init__(self, hidden_dim, out_dim, head, weight_tying=False):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism :param weight_tying: indicate whether the weights ... | the_stack_v2_python_sparse | models/coattention/alternating_coattention.py | Minys233/GCN-BMP | train | 1 | |
669321487c7e8da628aacbe3607a78982325e376 | [
"for model, trained_examples in trained_examples_by_model.items():\n if not trained_examples:\n continue\n if trained_examples[-1].span < max_span:\n return model\nraise exceptions.SkipSignal()",
"_validate_input_dict(input_dict)\nops_utils.validate_argument('wait_spans_before_eval', self.wait... | <|body_start_0|>
for model, trained_examples in trained_examples_by_model.items():
if not trained_examples:
continue
if trained_examples[-1].span < max_span:
return model
raise exceptions.SkipSignal()
<|end_body_0|>
<|body_start_1|>
_valid... | SpanDrivenEvaluatorInputs operator. | SpanDrivenEvaluatorInputs | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpanDrivenEvaluatorInputs:
"""SpanDrivenEvaluatorInputs operator."""
def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]:
"""Finds the latest Model not trained on Examples with span max_spa... | stack_v2_sparse_classes_36k_train_031620 | 7,595 | permissive | [
{
"docstring": "Finds the latest Model not trained on Examples with span max_span.",
"name": "_get_model_to_evaluate",
"signature": "def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]"
},
{
"docstring... | 2 | stack_v2_sparse_classes_30k_train_011892 | Implement the Python class `SpanDrivenEvaluatorInputs` described below.
Class description:
SpanDrivenEvaluatorInputs operator.
Method signatures and docstrings:
- def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]: Finds t... | Implement the Python class `SpanDrivenEvaluatorInputs` described below.
Class description:
SpanDrivenEvaluatorInputs operator.
Method signatures and docstrings:
- def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]: Finds t... | 1b328504fa08a70388691e4072df76f143631325 | <|skeleton|>
class SpanDrivenEvaluatorInputs:
"""SpanDrivenEvaluatorInputs operator."""
def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]:
"""Finds the latest Model not trained on Examples with span max_spa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpanDrivenEvaluatorInputs:
"""SpanDrivenEvaluatorInputs operator."""
def _get_model_to_evaluate(self, trained_examples_by_model: Dict[types.Artifact, List[types.Artifact]], max_span: int) -> Optional[types.Artifact]:
"""Finds the latest Model not trained on Examples with span max_span."""
... | the_stack_v2_python_sparse | tfx/dsl/input_resolution/ops/span_driven_evaluator_inputs_op.py | tensorflow/tfx | train | 2,116 |
f05dd71590142c1a397e6b0e8867eed031b89d3e | [
"dirpath = path + os.sep + dirname_\nif os.path.exists(dirpath):\n print()\nelse:\n os.makedirs(dirpath)\nif os.path.exists(dirpath + os.sep + dirname):\n print('文件夹和文件已经存在')\nelse:\n os.makedirs(dirpath + os.sep + dirname)\n file = open(dirpath + os.sep + dirname + os.sep + '1.html', 'w')\n file.... | <|body_start_0|>
dirpath = path + os.sep + dirname_
if os.path.exists(dirpath):
print()
else:
os.makedirs(dirpath)
if os.path.exists(dirpath + os.sep + dirname):
print('文件夹和文件已经存在')
else:
os.makedirs(dirpath + os.sep + dirname)
... | Test_1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_1:
def check_dir(self, dirname, dirname_):
"""检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:"""
<|body_0|>
def build_dir(self, dirname):
"""创建3级目录 :param dirname: :return:"""
<|body_1|>
def md5_get(self, filename):
"""获取文... | stack_v2_sparse_classes_36k_train_031621 | 2,241 | no_license | [
{
"docstring": "检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:",
"name": "check_dir",
"signature": "def check_dir(self, dirname, dirname_)"
},
{
"docstring": "创建3级目录 :param dirname: :return:",
"name": "build_dir",
"signature": "def build_dir(self, dirname)"
},
{
... | 4 | null | Implement the Python class `Test_1` described below.
Class description:
Implement the Test_1 class.
Method signatures and docstrings:
- def check_dir(self, dirname, dirname_): 检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:
- def build_dir(self, dirname): 创建3级目录 :param dirname: :return:
- def md5_g... | Implement the Python class `Test_1` described below.
Class description:
Implement the Test_1 class.
Method signatures and docstrings:
- def check_dir(self, dirname, dirname_): 检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:
- def build_dir(self, dirname): 创建3级目录 :param dirname: :return:
- def md5_g... | 25986e44b65228dd0f5ccdee6bedb0fcd93e5b7c | <|skeleton|>
class Test_1:
def check_dir(self, dirname, dirname_):
"""检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:"""
<|body_0|>
def build_dir(self, dirname):
"""创建3级目录 :param dirname: :return:"""
<|body_1|>
def md5_get(self, filename):
"""获取文... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_1:
def check_dir(self, dirname, dirname_):
"""检查上面的文件夹和文件是否存在，如果不存在就创建 :param dirname: :param filename: :return:"""
dirpath = path + os.sep + dirname_
if os.path.exists(dirpath):
print()
else:
os.makedirs(dirpath)
if os.path.exists(dirpath +... | the_stack_v2_python_sparse | Project/testcase/Test_1.py | Nightwish555/Weekly---practice | train | 3 | |
3d96f9353c027b7e870fb988fab584746903c16e | [
"tails = [0] * len(nums)\nsize = 0\nfor num in nums:\n left, right = (0, size)\n while left != right:\n mid = (left + right) / 2\n if tails[mid] < num:\n left = mid + 1\n else:\n right = mid\n tails[left] = num\n size = max(left + 1, size)\nreturn size",
"num... | <|body_start_0|>
tails = [0] * len(nums)
size = 0
for num in nums:
left, right = (0, size)
while left != right:
mid = (left + right) / 2
if tails[mid] < num:
left = mid + 1
else:
right... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-monotonically-increasing-subsequence-size-n-log-n/ tails is an array storing the smallest tail of ... | stack_v2_sparse_classes_36k_train_031622 | 2,432 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-monotonically-increasing-subsequence-size-n-log-n/ tails is an array storing the smallest tail of all increasing sub-sequences with length i+1 in ta... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-m... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-m... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-monotonically-increasing-subsequence-size-n-log-n/ tails is an array storing the smallest tail of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int https://leetcode.com/problems/longest-increasing-subsequence/discuss/74824/ https://www.geeksforgeeks.org/longest-monotonically-increasing-subsequence-size-n-log-n/ tails is an array storing the smallest tail of all increasing... | the_stack_v2_python_sparse | LeetCode/300_longest_increasing_subsequence.py | yao23/Machine_Learning_Playground | train | 12 | |
e3ad3381da166e859bc34e0b7b16f2cdda4d6aea | [
"ret = []\n\ndef helper(node):\n if node == None:\n return ''\n ret.append(str(node.val))\n helper(node.left)\n helper(node.right)\nhelper(root)\nreturn ','.join(ret)",
"if not data:\n return None\n\ndef helper(data):\n if data == []:\n return\n cur = int(data.pop(0))\n root ... | <|body_start_0|>
ret = []
def helper(node):
if node == None:
return ''
ret.append(str(node.val))
helper(node.left)
helper(node.right)
helper(root)
return ','.join(ret)
<|end_body_0|>
<|body_start_1|>
if not data:
... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
... | stack_v2_sparse_classes_36k_train_031623 | 1,245 | permissive | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_test_000247 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | b4ecd5cb7122467ee479f38497faaabb17e6025e | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
ret = []
def helper(node):
if node == None:
return ''
ret.append(str(node.val))
helper(node.left)
helper(node.right)
help... | the_stack_v2_python_sparse | solutions/0449.serialize-and-deserialize-bst/serialize-and-deserialize-bst.py | cocobear/LeetCode_in_Python | train | 0 | |
ebec1c7b19099ff206c70ca4350ebff1b1651e90 | [
"m = len(grid)\nif m > 0:\n n = len(grid[0])\nelse:\n return 0\ncost = [[0 for _ in range(n)] for _ in range(m)]\ncost[0][0] = grid[0][0]\nfor j in range(1, n):\n cost[0][j] = grid[0][j] = grid[0][j] + cost[0][j - 1]\nfor i in range(1, m):\n cost[i][0] = grid[i][0] + cost[i - 1][0]\nfor i in range(1, m)... | <|body_start_0|>
m = len(grid)
if m > 0:
n = len(grid[0])
else:
return 0
cost = [[0 for _ in range(n)] for _ in range(m)]
cost[0][0] = grid[0][0]
for j in range(1, n):
cost[0][j] = grid[0][j] = grid[0][j] + cost[0][j - 1]
for i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum0(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m = len(grid)
if m > 0:
... | stack_v2_sparse_classes_36k_train_031624 | 1,214 | no_license | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum",
"signature": "def minPathSum(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum0",
"signature": "def minPathSum0(self, grid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003740 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum0(self, grid): :type grid: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum0(self, grid): :type grid: List[List[int]] :rtype: int
<|skeleton|>
class Solution:
def ... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum0(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
m = len(grid)
if m > 0:
n = len(grid[0])
else:
return 0
cost = [[0 for _ in range(n)] for _ in range(m)]
cost[0][0] = grid[0][0]
for j in range(1,... | the_stack_v2_python_sparse | PythonCode/src/0064_Minimum_Path_Sum.py | oneyuan/CodeforFun | train | 0 | |
394828d907cf0f2b3ee48f0e5351684adb771078 | [
"assert bias.shape[0] == 4\nassert weight_hh.shape[0] == 4\nassert weight_hh.shape[1] == 1\nself.hidden_size: int = 1\nself.input_size: int = input_size\nself.bias: np.ndarray = bias\nself.weight_hh: np.ndarray = weight_hh\nself.weight_xh: np.ndarray = weight_xh\nself.hx: np.ndarray = np.asarray([])\nself.c: np.nda... | <|body_start_0|>
assert bias.shape[0] == 4
assert weight_hh.shape[0] == 4
assert weight_hh.shape[1] == 1
self.hidden_size: int = 1
self.input_size: int = input_size
self.bias: np.ndarray = bias
self.weight_hh: np.ndarray = weight_hh
self.weight_xh: np.ndar... | Custom implementation of the single LSTM-cell. | LSTMCell | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bia... | stack_v2_sparse_classes_36k_train_031625 | 2,345 | permissive | [
{
"docstring": "Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bias: Bias-vector from each of the internal nodes :param weight_hh: Weight-vector from hidden to hidden states :param weight_xh: Weight-vector from input to hidden states",
"name... | 2 | stack_v2_sparse_classes_30k_train_002988 | Implement the Python class `LSTMCell` described below.
Class description:
Custom implementation of the single LSTM-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the LSTM-cell with the provided parameters. :param in... | Implement the Python class `LSTMCell` described below.
Class description:
Custom implementation of the single LSTM-cell.
Method signatures and docstrings:
- def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray): Create the LSTM-cell with the provided parameters. :param in... | 818a4ce941536611c0f1780f7c4a6238f0e1884e | <|skeleton|>
class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bia... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LSTMCell:
"""Custom implementation of the single LSTM-cell."""
def __init__(self, input_size: int, bias: np.ndarray, weight_hh: np.ndarray, weight_xh: np.ndarray):
"""Create the LSTM-cell with the provided parameters. :param input_size: Number of inputs going into the cell :param bias: Bias-vecto... | the_stack_v2_python_sparse | population/utils/rnn_cell_util/lstm.py | RubenPants/EvolvableRNN | train | 1 |
ec67429fb2fb8fed002590ecf6fe34a524f7f753 | [
"logger.info('Training the model.')\nconfig = self.get_config()\nif seed:\n logger.info(f'Setting seed to {seed}')\n seed_everything(seed, workers=True)\nconfig.trainer.deterministic = 'warn' if deterministic else deterministic\nlogger.info(\"Training Configs '%s'\", config)\ndatamodule = OTXAnomalyDataModule... | <|body_start_0|>
logger.info('Training the model.')
config = self.get_config()
if seed:
logger.info(f'Setting seed to {seed}')
seed_everything(seed, workers=True)
config.trainer.deterministic = 'warn' if deterministic else deterministic
logger.info("Traini... | Base Anomaly Task. | TrainingTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingTask:
"""Base Anomaly Task."""
def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters, seed: Optional[int]=None, deterministic: bool=False) -> None:
"""Train the anomaly classification model. Args: dataset (DatasetEntity): Input d... | stack_v2_sparse_classes_36k_train_031626 | 5,264 | permissive | [
{
"docstring": "Train the anomaly classification model. Args: dataset (DatasetEntity): Input dataset. output_model (ModelEntity): Output model to save the model weights. train_parameters (TrainParameters): Training parameters seed (Optional[int]): Setting seed to a value other than 0 deterministic (bool): Setti... | 2 | stack_v2_sparse_classes_30k_train_004048 | Implement the Python class `TrainingTask` described below.
Class description:
Base Anomaly Task.
Method signatures and docstrings:
- def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters, seed: Optional[int]=None, deterministic: bool=False) -> None: Train the anomaly cla... | Implement the Python class `TrainingTask` described below.
Class description:
Base Anomaly Task.
Method signatures and docstrings:
- def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters, seed: Optional[int]=None, deterministic: bool=False) -> None: Train the anomaly cla... | 80454808b38727e358e8b880043eeac0f18152fb | <|skeleton|>
class TrainingTask:
"""Base Anomaly Task."""
def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters, seed: Optional[int]=None, deterministic: bool=False) -> None:
"""Train the anomaly classification model. Args: dataset (DatasetEntity): Input d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrainingTask:
"""Base Anomaly Task."""
def train(self, dataset: DatasetEntity, output_model: ModelEntity, train_parameters: TrainParameters, seed: Optional[int]=None, deterministic: bool=False) -> None:
"""Train the anomaly classification model. Args: dataset (DatasetEntity): Input dataset. outpu... | the_stack_v2_python_sparse | src/otx/algorithms/anomaly/tasks/train.py | openvinotoolkit/training_extensions | train | 397 |
e12f36c4fdfe164205d9e207fee538cae27ef937 | [
"self.command_output = ''\nself.browsers = []\nself.data = ''\nself.current_path = os.getcwd()",
"ret_data = {'List of Installed Browsers': []}\nself.command_output = os.popen(\"apropos 'web browser'\").read()\nself.browsers = self.command_output.split('\\n')\nself.browsers.pop()\nself.browsers = [i[:i.find('(') ... | <|body_start_0|>
self.command_output = ''
self.browsers = []
self.data = ''
self.current_path = os.getcwd()
<|end_body_0|>
<|body_start_1|>
ret_data = {'List of Installed Browsers': []}
self.command_output = os.popen("apropos 'web browser'").read()
self.browsers ... | ********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHICH IS GOING TO BE USED LATE... | get_browsers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED ... | stack_v2_sparse_classes_36k_train_031627 | 2,883 | permissive | [
{
"docstring": "__init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHICH IS GOING TO BE USED LATER BY OTHER MEMBER FUNCTION.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "WORK() DOCFILE: THE FUNCTION WORKS IN FOLLOWI... | 2 | stack_v2_sparse_classes_30k_test_001133 | Implement the Python class `get_browsers` described below.
Class description:
********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZ... | Implement the Python class `get_browsers` described below.
Class description:
********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZ... | 256149b6f22828ac668a68e8cac17f86925ccd5c | <|skeleton|>
class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class get_browsers:
"""********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM ********* CLASS get_browsers DOCINFO: get_browsers HAVE TWO FUNCTIONS I.E., 1) __init__ 2) work() __init__ DOCFILE: __init__ BLOCK SERVES THE INITIALIZATION FUNCTION, CONTAINING INITIALIZED VARIABLES WHI... | the_stack_v2_python_sparse | lib/linux/get_browsers.py | chavarera/Cinfo | train | 9 |
8ccab11af213921a549e0a623ec97cb18b27c996 | [
"json_data = request.data.decode()\nkwargs = {'description': None, 'email': None}\ntry:\n parameters = json_data and loads(json_data)\n if parameters:\n for param in kwargs:\n if param in parameters:\n kwargs[param] = parameters[param]\nexcept ValueError:\n return generate_... | <|body_start_0|>
json_data = request.data.decode()
kwargs = {'description': None, 'email': None}
try:
parameters = json_data and loads(json_data)
if parameters:
for param in kwargs:
if param in parameters:
kwargs... | Add and update a VO. | VO | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VO:
"""Add and update a VO."""
def post(self, vo):
"""Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :status 201: VO created successfully. :status 401: Invalid A... | stack_v2_sparse_classes_36k_train_031628 | 9,092 | permissive | [
{
"docstring": "Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :status 201: VO created successfully. :status 401: Invalid Auth Token. :status 409: Unsupported operation. :status 500: Intern... | 2 | stack_v2_sparse_classes_30k_test_000645 | Implement the Python class `VO` described below.
Class description:
Add and update a VO.
Method signatures and docstrings:
- def post(self, vo): Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :st... | Implement the Python class `VO` described below.
Class description:
Add and update a VO.
Method signatures and docstrings:
- def post(self, vo): Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :st... | bf33d9441d3b4ff160a392eed56724f635a03fe6 | <|skeleton|>
class VO:
"""Add and update a VO."""
def post(self, vo):
"""Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :status 201: VO created successfully. :status 401: Invalid A... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VO:
"""Add and update a VO."""
def post(self, vo):
"""Add a VO with a given name. .. :quickref: VO; Add a VOs. :param vo: VO to be added. :<json string description: Desciption of VO. :<json string email: Admin email for VO. :status 201: VO created successfully. :status 401: Invalid Auth Token. :s... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/vos.py | viveknigam3003/rucio | train | 1 |
66f19c2bd040e0a7bfc6131cbf1b69063e33276b | [
"credentials = pika.PlainCredentials(username, password)\nparams = pika.ConnectionParameters(host, port, vhost, credentials, socket_timeout=3, retry_delay=3)\nconnection = pika.BlockingConnection(params)\nself.channel = connection.channel()",
"self.extra_callback = callback\nself.channel.queue_declare(queue=queue... | <|body_start_0|>
credentials = pika.PlainCredentials(username, password)
params = pika.ConnectionParameters(host, port, vhost, credentials, socket_timeout=3, retry_delay=3)
connection = pika.BlockingConnection(params)
self.channel = connection.channel()
<|end_body_0|>
<|body_start_1|>
... | Queue consumer. | Consumer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Consumer:
"""Queue consumer."""
def __init__(self, host, port, vhost, username, password):
"""Initialize LogConsumer."""
<|body_0|>
def consume(self, queue, callback, args={}):
"""Consuming listener."""
<|body_1|>
def callback(self, ch, method, props... | stack_v2_sparse_classes_36k_train_031629 | 1,991 | no_license | [
{
"docstring": "Initialize LogConsumer.",
"name": "__init__",
"signature": "def __init__(self, host, port, vhost, username, password)"
},
{
"docstring": "Consuming listener.",
"name": "consume",
"signature": "def consume(self, queue, callback, args={})"
},
{
"docstring": "Called ... | 3 | stack_v2_sparse_classes_30k_train_005373 | Implement the Python class `Consumer` described below.
Class description:
Queue consumer.
Method signatures and docstrings:
- def __init__(self, host, port, vhost, username, password): Initialize LogConsumer.
- def consume(self, queue, callback, args={}): Consuming listener.
- def callback(self, ch, method, props, bo... | Implement the Python class `Consumer` described below.
Class description:
Queue consumer.
Method signatures and docstrings:
- def __init__(self, host, port, vhost, username, password): Initialize LogConsumer.
- def consume(self, queue, callback, args={}): Consuming listener.
- def callback(self, ch, method, props, bo... | b1067b8b90a4d0e2269a7a57779f81dd4209100c | <|skeleton|>
class Consumer:
"""Queue consumer."""
def __init__(self, host, port, vhost, username, password):
"""Initialize LogConsumer."""
<|body_0|>
def consume(self, queue, callback, args={}):
"""Consuming listener."""
<|body_1|>
def callback(self, ch, method, props... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Consumer:
"""Queue consumer."""
def __init__(self, host, port, vhost, username, password):
"""Initialize LogConsumer."""
credentials = pika.PlainCredentials(username, password)
params = pika.ConnectionParameters(host, port, vhost, credentials, socket_timeout=3, retry_delay=3)
... | the_stack_v2_python_sparse | packages/amqp/consumer.py | michaelmob/it490-car-calendar | train | 0 |
6aad17c5e193f3eb93ad8ed0b9d6255d2cbf01da | [
"if isinstance(value, (int, float)):\n return datetime.fromtimestamp(value, tz=timezone.utc)\nelif isinstance(value, str):\n if value.startswith('+'):\n return timedelta(seconds=float(value[1:]))\n else:\n return datetime.fromtimestamp(float(value), tz=timezone.utc)\nelse:\n raise NotImple... | <|body_start_0|>
if isinstance(value, (int, float)):
return datetime.fromtimestamp(value, tz=timezone.utc)
elif isinstance(value, str):
if value.startswith('+'):
return timedelta(seconds=float(value[1:]))
else:
return datetime.fromtimes... | TimerField | [
"GPL-1.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimerField:
def _deserialize(self, value: typing.Any, attr: typing.Optional[str], data: typing.Optional[typing.Mapping[str, typing.Any]], **kwargs):
"""Deserialize value. Concrete :class:`Field` classes should implement this method. :param value: The value to be deserialized. :param attr... | stack_v2_sparse_classes_36k_train_031630 | 2,769 | permissive | [
{
"docstring": "Deserialize value. Concrete :class:`Field` classes should implement this method. :param value: The value to be deserialized. :param attr: The attribute/key in `data` to be deserialized. :param data: The raw input data passed to the `Schema.load`. :param kwargs: Field-specific keyword arguments. ... | 2 | null | Implement the Python class `TimerField` described below.
Class description:
Implement the TimerField class.
Method signatures and docstrings:
- def _deserialize(self, value: typing.Any, attr: typing.Optional[str], data: typing.Optional[typing.Mapping[str, typing.Any]], **kwargs): Deserialize value. Concrete :class:`F... | Implement the Python class `TimerField` described below.
Class description:
Implement the TimerField class.
Method signatures and docstrings:
- def _deserialize(self, value: typing.Any, attr: typing.Optional[str], data: typing.Optional[typing.Mapping[str, typing.Any]], **kwargs): Deserialize value. Concrete :class:`F... | b260bd41d5aa091e6a4f1818328426fbe6f625c0 | <|skeleton|>
class TimerField:
def _deserialize(self, value: typing.Any, attr: typing.Optional[str], data: typing.Optional[typing.Mapping[str, typing.Any]], **kwargs):
"""Deserialize value. Concrete :class:`Field` classes should implement this method. :param value: The value to be deserialized. :param attr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimerField:
def _deserialize(self, value: typing.Any, attr: typing.Optional[str], data: typing.Optional[typing.Mapping[str, typing.Any]], **kwargs):
"""Deserialize value. Concrete :class:`Field` classes should implement this method. :param value: The value to be deserialized. :param attr: The attribut... | the_stack_v2_python_sparse | aiokraken/rest/schemas/ktm.py | asmodehn/aiokraken | train | 1 | |
b751186e072b41eaa4a4d57ebaa6fe20be4b4161 | [
"obj = self.objects[0]\nupdate = self.update_object.copy()\n[self.assertNotEqual(getattr(obj, k), v) for k, v in update.items()]\npayload = self.get_object_template(self.template_object, 0)\npayload.update(update)\nurl = reverse(self.update_url, args=(obj.id,))\nresponse = self.client.put(url, data=payload)\nself.a... | <|body_start_0|>
obj = self.objects[0]
update = self.update_object.copy()
[self.assertNotEqual(getattr(obj, k), v) for k, v in update.items()]
payload = self.get_object_template(self.template_object, 0)
payload.update(update)
url = reverse(self.update_url, args=(obj.id,))... | BasicUpdateApiTestCaseRunMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicUpdateApiTestCaseRunMixin:
def test_update_anonymous(self):
"""Anonymous user should NOT be able to update"""
<|body_0|>
def test_update_staff_user(self):
"""Staff user should be able to update EVERY object"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_031631 | 9,174 | permissive | [
{
"docstring": "Anonymous user should NOT be able to update",
"name": "test_update_anonymous",
"signature": "def test_update_anonymous(self)"
},
{
"docstring": "Staff user should be able to update EVERY object",
"name": "test_update_staff_user",
"signature": "def test_update_staff_user(s... | 2 | null | Implement the Python class `BasicUpdateApiTestCaseRunMixin` described below.
Class description:
Implement the BasicUpdateApiTestCaseRunMixin class.
Method signatures and docstrings:
- def test_update_anonymous(self): Anonymous user should NOT be able to update
- def test_update_staff_user(self): Staff user should be ... | Implement the Python class `BasicUpdateApiTestCaseRunMixin` described below.
Class description:
Implement the BasicUpdateApiTestCaseRunMixin class.
Method signatures and docstrings:
- def test_update_anonymous(self): Anonymous user should NOT be able to update
- def test_update_staff_user(self): Staff user should be ... | 9baa530f2f3405322f74ccc145641148f253341b | <|skeleton|>
class BasicUpdateApiTestCaseRunMixin:
def test_update_anonymous(self):
"""Anonymous user should NOT be able to update"""
<|body_0|>
def test_update_staff_user(self):
"""Staff user should be able to update EVERY object"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicUpdateApiTestCaseRunMixin:
def test_update_anonymous(self):
"""Anonymous user should NOT be able to update"""
obj = self.objects[0]
update = self.update_object.copy()
[self.assertNotEqual(getattr(obj, k), v) for k, v in update.items()]
payload = self.get_object_tem... | the_stack_v2_python_sparse | palvelutori/test_mixins.py | City-of-Turku/munpalvelut_backend | train | 0 | |
c608cb67843adb3d589064298bd0732b03a07bb4 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn DriveItemUploadableProperties()",
"from .file_system_info import FileSystemInfo\nfrom .file_system_info import FileSystemInfo\nfields: Dict[str, Callable[[Any], None]] = {'description': lambda n: setattr(self, 'description', n.get_str_... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return DriveItemUploadableProperties()
<|end_body_0|>
<|body_start_1|>
from .file_system_info import FileSystemInfo
from .file_system_info import FileSystemInfo
fields: Dict[str, Callab... | DriveItemUploadableProperties | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DriveItemUploadableProperties:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DriveItemUploadableProperties:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k_train_031632 | 3,548 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: DriveItemUploadableProperties",
"name": "create_from_discriminator_value",
"signature": "def create_from_dis... | 3 | null | Implement the Python class `DriveItemUploadableProperties` described below.
Class description:
Implement the DriveItemUploadableProperties class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DriveItemUploadableProperties: Creates a new instance of th... | Implement the Python class `DriveItemUploadableProperties` described below.
Class description:
Implement the DriveItemUploadableProperties class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DriveItemUploadableProperties: Creates a new instance of th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class DriveItemUploadableProperties:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DriveItemUploadableProperties:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DriveItemUploadableProperties:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> DriveItemUploadableProperties:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | the_stack_v2_python_sparse | msgraph/generated/models/drive_item_uploadable_properties.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
69c6794caf97f6a75638252e8c598e6039e9d4e1 | [
"super(chorin, self).__init__(mesh, boundaryDomains, nu, cfl, uMax)\nself.solverName = 'chorin'\nself.us = dolfin.Function(self.V)\nself.F1 = 1 / self.k * dolfin.inner(self.v, self.u - self.u0) * dolfin.dx + dolfin.inner(self.v, dolfin.grad(self.u0) * self.u0) * dolfin.dx + self.nu * dolfin.inner(dolfin.grad(self.v... | <|body_start_0|>
super(chorin, self).__init__(mesh, boundaryDomains, nu, cfl, uMax)
self.solverName = 'chorin'
self.us = dolfin.Function(self.V)
self.F1 = 1 / self.k * dolfin.inner(self.v, self.u - self.u0) * dolfin.dx + dolfin.inner(self.v, dolfin.grad(self.u0) * self.u0) * dolfin.dx + ... | chorin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class chorin:
def __init__(self, mesh, boundaryDomains, nu, cfl, uMax):
"""### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(mesh, nu, dt, f) Parameters ---------- mesh :: the geometry mesh data file location. ---- (type:... | stack_v2_sparse_classes_36k_train_031633 | 12,599 | no_license | [
{
"docstring": "### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(mesh, nu, dt, f) Parameters ---------- mesh :: the geometry mesh data file location. ---- (type: dolfin.cpp.Mesh; single object) nu :: the fluid kinematic viscosity. -- (typ... | 2 | null | Implement the Python class `chorin` described below.
Class description:
Implement the chorin class.
Method signatures and docstrings:
- def __init__(self, mesh, boundaryDomains, nu, cfl, uMax): ### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(m... | Implement the Python class `chorin` described below.
Class description:
Implement the chorin class.
Method signatures and docstrings:
- def __init__(self, mesh, boundaryDomains, nu, cfl, uMax): ### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(m... | 98fbad93b2d1615e670ebdce71996ec3447a6917 | <|skeleton|>
class chorin:
def __init__(self, mesh, boundaryDomains, nu, cfl, uMax):
"""### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(mesh, nu, dt, f) Parameters ---------- mesh :: the geometry mesh data file location. ---- (type:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class chorin:
def __init__(self, mesh, boundaryDomains, nu, cfl, uMax):
"""### WORK IN PROGRESS #### Initialize the solver specific parameters (for the chorin scheme). Usage ----- Solver.initialize(mesh, nu, dt, f) Parameters ---------- mesh :: the geometry mesh data file location. ---- (type: dolfin.cpp.Me... | the_stack_v2_python_sparse | src/python/eulerian/base/chorin.py | apalha/pHyFlow2.0 | train | 0 | |
34a833cc3edb0affa150773b0707f27fc86f6fd4 | [
"re = AlarmSetting(userLogin).setAlarm(send_data['parkName'], send_data['enterConfidence'])\nresult = re['status']\nAssertions().assert_text(result, expect['enableConfidenceAlarm'])",
"re = cloudparking_service(centerMonitorLogin).mockCarInOut(send_data['carNum'], 0, send_data['inClientID'], confidence=send_data[... | <|body_start_0|>
re = AlarmSetting(userLogin).setAlarm(send_data['parkName'], send_data['enterConfidence'])
result = re['status']
Assertions().assert_text(result, expect['enableConfidenceAlarm'])
<|end_body_0|>
<|body_start_1|>
re = cloudparking_service(centerMonitorLogin).mockCarInOut(... | 远程值班室收到置信度提醒-并校正车牌 | TestAdjustCarNumByConfidence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAdjustCarNumByConfidence:
"""远程值班室收到置信度提醒-并校正车牌"""
def test_enableConfidenceAlarm(self, userLogin, send_data, expect):
"""开启告警配置-置信度告警功能"""
<|body_0|>
def test_mockCarIn(self, centerMonitorLogin, send_data, expect):
"""模拟进场"""
<|body_1|>
def test... | stack_v2_sparse_classes_36k_train_031634 | 2,956 | no_license | [
{
"docstring": "开启告警配置-置信度告警功能",
"name": "test_enableConfidenceAlarm",
"signature": "def test_enableConfidenceAlarm(self, userLogin, send_data, expect)"
},
{
"docstring": "模拟进场",
"name": "test_mockCarIn",
"signature": "def test_mockCarIn(self, centerMonitorLogin, send_data, expect)"
},... | 6 | null | Implement the Python class `TestAdjustCarNumByConfidence` described below.
Class description:
远程值班室收到置信度提醒-并校正车牌
Method signatures and docstrings:
- def test_enableConfidenceAlarm(self, userLogin, send_data, expect): 开启告警配置-置信度告警功能
- def test_mockCarIn(self, centerMonitorLogin, send_data, expect): 模拟进场
- def test_adj... | Implement the Python class `TestAdjustCarNumByConfidence` described below.
Class description:
远程值班室收到置信度提醒-并校正车牌
Method signatures and docstrings:
- def test_enableConfidenceAlarm(self, userLogin, send_data, expect): 开启告警配置-置信度告警功能
- def test_mockCarIn(self, centerMonitorLogin, send_data, expect): 模拟进场
- def test_adj... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class TestAdjustCarNumByConfidence:
"""远程值班室收到置信度提醒-并校正车牌"""
def test_enableConfidenceAlarm(self, userLogin, send_data, expect):
"""开启告警配置-置信度告警功能"""
<|body_0|>
def test_mockCarIn(self, centerMonitorLogin, send_data, expect):
"""模拟进场"""
<|body_1|>
def test... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAdjustCarNumByConfidence:
"""远程值班室收到置信度提醒-并校正车牌"""
def test_enableConfidenceAlarm(self, userLogin, send_data, expect):
"""开启告警配置-置信度告警功能"""
re = AlarmSetting(userLogin).setAlarm(send_data['parkName'], send_data['enterConfidence'])
result = re['status']
Assertions().ass... | the_stack_v2_python_sparse | test_suite/parkingConfig/settingParking/alarmSetting/test_adjustCarNumByConfidence.py | oyebino/pomp_api | train | 1 |
019c9362a9d03118b14561e470d5de8aafeae4aa | [
"self.id = str(identity)\nself.direction = 'none'\nself.speed = 0",
"self.speed = speed\noutput = '0' + self.id\nif self.speed < 11 and self.speed > -11:\n self.speed = 0\nelif self.speed < 0:\n output += '-'\n self.speed = self.speed * -1\nfor _ in range(4 - len(str(self.speed))):\n output += '0'\nou... | <|body_start_0|>
self.id = str(identity)
self.direction = 'none'
self.speed = 0
<|end_body_0|>
<|body_start_1|>
self.speed = speed
output = '0' + self.id
if self.speed < 11 and self.speed > -11:
self.speed = 0
elif self.speed < 0:
output +... | A Wheel class representing a wheel of the emubot | Wheel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
<|body_0|>
def move_wheel(self, speed):
"""Move the wheel"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_031635 | 2,748 | permissive | [
{
"docstring": "Wheel.__init__(ID): parameters - the ID of the wheel",
"name": "__init__",
"signature": "def __init__(self, identity)"
},
{
"docstring": "Move the wheel",
"name": "move_wheel",
"signature": "def move_wheel(self, speed)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010619 | Implement the Python class `Wheel` described below.
Class description:
A Wheel class representing a wheel of the emubot
Method signatures and docstrings:
- def __init__(self, identity): Wheel.__init__(ID): parameters - the ID of the wheel
- def move_wheel(self, speed): Move the wheel | Implement the Python class `Wheel` described below.
Class description:
A Wheel class representing a wheel of the emubot
Method signatures and docstrings:
- def __init__(self, identity): Wheel.__init__(ID): parameters - the ID of the wheel
- def move_wheel(self, speed): Move the wheel
<|skeleton|>
class Wheel:
""... | a39dc01f7c1213c8079216d49d376b317efbf5f3 | <|skeleton|>
class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
<|body_0|>
def move_wheel(self, speed):
"""Move the wheel"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Wheel:
"""A Wheel class representing a wheel of the emubot"""
def __init__(self, identity):
"""Wheel.__init__(ID): parameters - the ID of the wheel"""
self.id = str(identity)
self.direction = 'none'
self.speed = 0
def move_wheel(self, speed):
"""Move the wheel... | the_stack_v2_python_sparse | Client-Code-2018/CurrentEmuBotCode2/basic_classes.py | maxgodfrey2004/RoboCup-2018-Driving-Code | train | 1 |
57c437f895c844480d51b6d36a121ea67646e701 | [
"super(Decoder, self).__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(target_vocab, self.dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nself.blocks = [DecoderBlock(self.dm, h, hidden, drop_rate) for n in range(self.N)]\nself.dropout = tf.keras.layers.Drop... | <|body_start_0|>
super(Decoder, self).__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(target_vocab, self.dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
self.blocks = [DecoderBlock(self.dm, h, hidden, drop_rate) for n... | Decorder class | Decoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Decorder class"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of ... | stack_v2_sparse_classes_36k_train_031636 | 2,514 | no_license | [
{
"docstring": "Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hidden units in the fully connected layer. target_vocab (int): the size of the target vocabulary. max_seq_len (int): the maxi... | 2 | null | Implement the Python class `Decoder` described below.
Class description:
Decorder class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h... | Implement the Python class `Decoder` described below.
Class description:
Decorder class
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1): Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h... | 5aff923277cfe9f2b5324a773e4e5c3cac810a0c | <|skeleton|>
class Decoder:
"""Decorder class"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Decorder class"""
def __init__(self, N, dm, h, hidden, target_vocab, max_seq_len, drop_rate=0.1):
"""Class constructor Args: N (int): the number of blocks in the encoder. dm (int): the dimensionality of the model. h (int): the number of heads. hidden (int): the number of hidden units ... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/10-transformer_decoder.py | cmmolanos1/holbertonschool-machine_learning | train | 1 |
c6ec567468c7630ac8a91de88384b13f9d3f557b | [
"super(BitCountingGroupList, self).__init__(group_list)\nif bits is not None:\n self.bits = bits\n return\nbits = 0.0\nfor group in group_list:\n bits += group.metadata.bits\nself.bits = bits",
"group_list = list(self)\nif group_list:\n last_group = group_list[-1]\n factory = BitCountingMetadataFac... | <|body_start_0|>
super(BitCountingGroupList, self).__init__(group_list)
if bits is not None:
self.bits = bits
return
bits = 0.0
for group in group_list:
bits += group.metadata.bits
self.bits = bits
<|end_body_0|>
<|body_start_1|>
group... | List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages around. Method with_value_added_to_last_group() delegates to BitCountingGroup, with_group... | BitCountingGroupList | [
"Apache-2.0",
"CC-BY-4.0",
"LicenseRef-scancode-dco-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitCountingGroupList:
"""List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages around. Method with_value_added_to_last_g... | stack_v2_sparse_classes_36k_train_031637 | 3,450 | permissive | [
{
"docstring": "Create a group list from given list of groups. :param group_list: List of groups to compose this group. :param bits: Bit count if known, else None. :type group_list: list of BitCountingGroup :type bits: float or None",
"name": "__init__",
"signature": "def __init__(self, group_list=[], b... | 3 | null | Implement the Python class `BitCountingGroupList` described below.
Class description:
List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages ar... | Implement the Python class `BitCountingGroupList` described below.
Class description:
List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages ar... | 3151c98618c78e3782e48bbe4d9c8f906c126f69 | <|skeleton|>
class BitCountingGroupList:
"""List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages around. Method with_value_added_to_last_g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BitCountingGroupList:
"""List of BitCountingGroup which tracks overall bit count. This is useful, as bit count of a subsequent group depends on average of the previous group. Having the logic encapsulated here spares the caller the effort to pass averages around. Method with_value_added_to_last_group() delega... | the_stack_v2_python_sparse | PyPI/jumpavg/jumpavg/BitCountingGroupList.py | preym17/csit | train | 0 |
bc8a90a6d596fd8c8c4c9964076a79dfd8239ec6 | [
"self.id = id\nself._rk = RedisKeyWrapper(self.id)\nself.rdb = redis.StrictRedis(host=redis_address[0], port=redis_address[1], db=redis_db, decode_responses=True)",
"assert isinstance(file_path, str)\nd = {'FILE_PATH': file_path, 'TTL': ttl}\nd.update(kwargs)\ntry:\n task = json.dumps(d)\n self.rdb.rpush(se... | <|body_start_0|>
self.id = id
self._rk = RedisKeyWrapper(self.id)
self.rdb = redis.StrictRedis(host=redis_address[0], port=redis_address[1], db=redis_db, decode_responses=True)
<|end_body_0|>
<|body_start_1|>
assert isinstance(file_path, str)
d = {'FILE_PATH': file_path, 'TTL': ... | This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read the file locally by provided file's directory)to the queue, and then our zmq ... | FileManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileManager:
"""This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read the file locally by provided file's di... | stack_v2_sparse_classes_36k_train_031638 | 24,489 | permissive | [
{
"docstring": ":param id: publisher's id",
"name": "__init__",
"signature": "def __init__(self, id, redis_address=('127.0.0.1', 6379), redis_db=0)"
},
{
"docstring": ":param ttl: if ttl is 0, then it will live forever in boxes, otherwise time unit is sec :param kwargs: other headers",
"name... | 3 | stack_v2_sparse_classes_30k_train_014899 | Implement the Python class `FileManager` described below.
Class description:
This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read... | Implement the Python class `FileManager` described below.
Class description:
This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read... | 01c92ae15a12ddce2fe61348a829f77a5e02bb41 | <|skeleton|>
class FileManager:
"""This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read the file locally by provided file's di... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileManager:
"""This class is an api for other users to connect to Publisher. The basic usage for now is that users should push their file's name or directory, (assuming that user's process and Publisher are running on the same machine, so that we could read the file locally by provided file's directory)to th... | the_stack_v2_python_sparse | dandelion/httpclient.py | ktshen/Dandelion | train | 0 |
c29dcfecdb2451b745ad56f625420de53e70a4f5 | [
"client = APIServiceClient(timeout=2)\nif network_name is None:\n topologies = await client.request_all('getTopology', return_exceptions=True)\nelse:\n topologies = {network_name: await client.request(network_name, 'getTopology')}\ncoroutines = []\nfor name, topology in topologies.items():\n if isinstance(... | <|body_start_0|>
client = APIServiceClient(timeout=2)
if network_name is None:
topologies = await client.request_all('getTopology', return_exceptions=True)
else:
topologies = {network_name: await client.request(network_name, 'getTopology')}
coroutines = []
... | Topology | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Topology:
async def update_topologies(cls, network_name: Optional[str]=None) -> None:
"""Fetch latest topologies and update class params."""
<|body_0|>
def get_site_maps(cls, network_name: str) -> None:
"""Generate node macs and site name maps."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_031639 | 4,262 | permissive | [
{
"docstring": "Fetch latest topologies and update class params.",
"name": "update_topologies",
"signature": "async def update_topologies(cls, network_name: Optional[str]=None) -> None"
},
{
"docstring": "Generate node macs and site name maps.",
"name": "get_site_maps",
"signature": "def... | 4 | null | Implement the Python class `Topology` described below.
Class description:
Implement the Topology class.
Method signatures and docstrings:
- async def update_topologies(cls, network_name: Optional[str]=None) -> None: Fetch latest topologies and update class params.
- def get_site_maps(cls, network_name: str) -> None: ... | Implement the Python class `Topology` described below.
Class description:
Implement the Topology class.
Method signatures and docstrings:
- async def update_topologies(cls, network_name: Optional[str]=None) -> None: Fetch latest topologies and update class params.
- def get_site_maps(cls, network_name: str) -> None: ... | 93c0c4bef28c1ed15dc61e9fd340a9faef4902e3 | <|skeleton|>
class Topology:
async def update_topologies(cls, network_name: Optional[str]=None) -> None:
"""Fetch latest topologies and update class params."""
<|body_0|>
def get_site_maps(cls, network_name: str) -> None:
"""Generate node macs and site name maps."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Topology:
async def update_topologies(cls, network_name: Optional[str]=None) -> None:
"""Fetch latest topologies and update class params."""
client = APIServiceClient(timeout=2)
if network_name is None:
topologies = await client.request_all('getTopology', return_exceptions=... | the_stack_v2_python_sparse | scan_service/scan_service/utils/topology.py | terragraph/tgnms | train | 15 | |
c235f3fe930ecc07f178311983aad70f6f0706f1 | [
"super().__init__(name, instrument, **kwargs)\nself._reference = instrument.root_instrument.reference\nself._dll_get_function = partial(dll_get_function, self._reference)\nself._dll_set_function = partial(dll_set_function, self._reference)",
"if hasattr(self.instrument, 'channel_number'):\n instr = cast(Instru... | <|body_start_0|>
super().__init__(name, instrument, **kwargs)
self._reference = instrument.root_instrument.reference
self._dll_get_function = partial(dll_get_function, self._reference)
self._dll_set_function = partial(dll_set_function, self._reference)
<|end_body_0|>
<|body_start_1|>
... | LdaParameter | [
"GPL-2.0-only",
"GPL-2.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA chann... | stack_v2_sparse_classes_36k_train_031640 | 12,103 | permissive | [
{
"docstring": "Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA channel dll_get_function: DLL function that gets the value dll_get_function: DLL function that sets the value",
"name": "__init__",
"signature": "def __init__(sel... | 4 | stack_v2_sparse_classes_30k_train_006616 | Implement the Python class `LdaParameter` described below.
Class description:
Implement the LdaParameter class.
Method signatures and docstrings:
- def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs): Parameter associated with one ... | Implement the Python class `LdaParameter` described below.
Class description:
Implement the LdaParameter class.
Method signatures and docstrings:
- def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs): Parameter associated with one ... | e07c9f23339ab00b0f4c4cc46711593d88f7fc84 | <|skeleton|>
class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA chann... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LdaParameter:
def __init__(self, name: str, instrument: Union[Vaunix_LDA, LdaChannel], dll_get_function: Callable, dll_set_function: Callable, **kwargs):
"""Parameter associated with one channel of the LDA. Args: name: parameter name instrument: parent instrument, either LDA or LDA channel dll_get_fun... | the_stack_v2_python_sparse | qcodes_contrib_drivers/drivers/Vaunix/LDA.py | QCoDeS/Qcodes_contrib_drivers | train | 32 | |
7a8bb2005a21974171ed36617195bc873b499240 | [
"flags.AddParentFlagsToParser(parser)\nparser.add_argument('--location', metavar='LOCATION', required=True, help='Location')\nparser.add_argument('--recommender', metavar='RECOMMENDER', required=True, help='Recommender to list recommendations for. Supported recommenders can be found here: https://cloud.google.com/r... | <|body_start_0|>
flags.AddParentFlagsToParser(parser)
parser.add_argument('--location', metavar='LOCATION', required=True, help='Location')
parser.add_argument('--recommender', metavar='RECOMMENDER', required=True, help='Recommender to list recommendations for. Supported recommenders can be foun... | List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently the following cloud_entity_types are supported: project, billing_account, folder... | ListOriginal | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ListOriginal:
"""List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently the following cloud_entity_types are sup... | stack_v2_sparse_classes_36k_train_031641 | 6,552 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Run 'gcloud recommender recomme... | 2 | null | Implement the Python class `ListOriginal` described below.
Class description:
List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently t... | Implement the Python class `ListOriginal` described below.
Class description:
List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently t... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class ListOriginal:
"""List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently the following cloud_entity_types are sup... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ListOriginal:
"""List operations for a recommendation. This command lists all recommendations for a given cloud_entity_id, location and recommender. Supported recommenders can be found here: https://cloud.google.com/recommender/docs/recommenders. Currently the following cloud_entity_types are supported: proje... | the_stack_v2_python_sparse | lib/surface/recommender/recommendations/list.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
a33d9ebca4a7476b41a3c0ab88702e913a5d60ba | [
"self.mode = mode\nself.allowed_urls = allowed_urls\nself.allowed_files = allowed_files",
"if dictionary is None:\n return None\nmode = dictionary.get('mode')\nallowed_urls = None\nif dictionary.get('allowedUrls') != None:\n allowed_urls = list()\n for structure in dictionary.get('allowedUrls'):\n ... | <|body_start_0|>
self.mode = mode
self.allowed_urls = allowed_urls
self.allowed_files = allowed_files
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
mode = dictionary.get('mode')
allowed_urls = None
if dictionary.get('allowedUrls')... | Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_urls (list of AllowedUrlModel): The urls that should be permitted by the malware detection engine. If omitted... | UpdateNetworkSecurityMalwareSettingsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkSecurityMalwareSettingsModel:
"""Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_urls (list of AllowedUrlModel): The urls... | stack_v2_sparse_classes_36k_train_031642 | 3,077 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkSecurityMalwareSettingsModel class",
"name": "__init__",
"signature": "def __init__(self, mode=None, allowed_urls=None, allowed_files=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A di... | 2 | stack_v2_sparse_classes_30k_test_000457 | Implement the Python class `UpdateNetworkSecurityMalwareSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_u... | Implement the Python class `UpdateNetworkSecurityMalwareSettingsModel` described below.
Class description:
Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_u... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkSecurityMalwareSettingsModel:
"""Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_urls (list of AllowedUrlModel): The urls... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNetworkSecurityMalwareSettingsModel:
"""Implementation of the 'updateNetworkSecurityMalwareSettings' model. TODO: type model description here. Attributes: mode (string): Set mode to 'enabled' to enable malware prevention, otherwise 'disabled' allowed_urls (list of AllowedUrlModel): The urls that should ... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_security_malware_settings_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
48ffa6e64fd085a4e1938612c7097c9ec4669a96 | [
"cache_directory = self.config['cache_directory']\nsimulation_state = SimulationState()\nsimulation_state.set_current_time(year)\nsimulation_state.set_cache_directory(cache_directory)\ntmconfig = self.config['travel_model_configuration']\nyear_config = tmconfig[year]\nmatrix_directory = tmconfig.get('matrix_h5_dire... | <|body_start_0|>
cache_directory = self.config['cache_directory']
simulation_state = SimulationState()
simulation_state.set_current_time(year)
simulation_state.set_cache_directory(cache_directory)
tmconfig = self.config['travel_model_configuration']
year_config = tmconfig... | Copy skims stored in hdf5 format into the UrbanSim cache. | GetEmme4DataFromH5IntoCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetEmme4DataFromH5IntoCache:
"""Copy skims stored in hdf5 format into the UrbanSim cache."""
def run(self, year):
"""Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_skims which creates the skims hdf5 file. It creates a tra... | stack_v2_sparse_classes_36k_train_031643 | 5,542 | no_license | [
{
"docstring": "Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_skims which creates the skims hdf5 file. It creates a travel_model dataset with each skim being an attribute of it. Zones are assumed to have no gaps. Arguments: year -- year of the urba... | 2 | null | Implement the Python class `GetEmme4DataFromH5IntoCache` described below.
Class description:
Copy skims stored in hdf5 format into the UrbanSim cache.
Method signatures and docstrings:
- def run(self, year): Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_... | Implement the Python class `GetEmme4DataFromH5IntoCache` described below.
Class description:
Copy skims stored in hdf5 format into the UrbanSim cache.
Method signatures and docstrings:
- def run(self, year): Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_... | c392d15b35aa1d47bbc185ed76314f8e6dd9f92f | <|skeleton|>
class GetEmme4DataFromH5IntoCache:
"""Copy skims stored in hdf5 format into the UrbanSim cache."""
def run(self, year):
"""Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_skims which creates the skims hdf5 file. It creates a tra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetEmme4DataFromH5IntoCache:
"""Copy skims stored in hdf5 format into the UrbanSim cache."""
def run(self, year):
"""Copy skims stored in hdf5 format into the UrbanSim cache. Should run after psrc_parcel.emme.models.run_export_skims which creates the skims hdf5 file. It creates a travel_model dat... | the_stack_v2_python_sparse | psrc_parcel/emme/models/get_emme4_data_from_h5_into_cache.py | psrc/urbansim | train | 4 |
0cf6592c04a57755ddeb987922308f852cc5f643 | [
"if not nums:\n return 0\nf = 1\nd = 1\nfor i in range(1, len(nums)):\n if nums[i] > nums[i - 1]:\n f = d + 1\n elif nums[i] < nums[i - 1]:\n d = f + 1\nreturn max(f, d)",
"if len(nums) < 2:\n return len(nums)\ndp = [None for _ in range(len(nums))]\ndp[0] = [1, None]\nfor i in range(1, l... | <|body_start_0|>
if not nums:
return 0
f = 1
d = 1
for i in range(1, len(nums)):
if nums[i] > nums[i - 1]:
f = d + 1
elif nums[i] < nums[i - 1]:
d = f + 1
return max(f, d)
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wiggleMaxLength(self, nums):
"""nearly the same as linear house rob :type nums: List[int] :rtype: int"""
<|body_0|>
def wiggleMaxLength2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_031644 | 1,231 | no_license | [
{
"docstring": "nearly the same as linear house rob :type nums: List[int] :rtype: int",
"name": "wiggleMaxLength",
"signature": "def wiggleMaxLength(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "wiggleMaxLength2",
"signature": "def wiggleMaxLength2(self, nu... | 2 | stack_v2_sparse_classes_30k_train_019343 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleMaxLength(self, nums): nearly the same as linear house rob :type nums: List[int] :rtype: int
- def wiggleMaxLength2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wiggleMaxLength(self, nums): nearly the same as linear house rob :type nums: List[int] :rtype: int
- def wiggleMaxLength2(self, nums): :type nums: List[int] :rtype: int
<|sk... | e16702d2b3ec4e5054baad56f4320bc3b31676ad | <|skeleton|>
class Solution:
def wiggleMaxLength(self, nums):
"""nearly the same as linear house rob :type nums: List[int] :rtype: int"""
<|body_0|>
def wiggleMaxLength2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wiggleMaxLength(self, nums):
"""nearly the same as linear house rob :type nums: List[int] :rtype: int"""
if not nums:
return 0
f = 1
d = 1
for i in range(1, len(nums)):
if nums[i] > nums[i - 1]:
f = d + 1
... | the_stack_v2_python_sparse | leetcode/medium/wiggle_sequence.py | SuperMartinYang/learning_algorithm | train | 0 | |
ae5bf63ab906639b1019c584f295a456ac4a63cd | [
"if not isinstance(dictionary, ImmutableDictionary):\n for k, v in dictionary.iteritems():\n dictionary[k] = Utils.make_immutable(v)\nsuper(ImmutableDictionary, self).__init__(dictionary)",
"if name in self:\n return self[name]\ntry:\n return self[name]\nexcept KeyError:\n raise AttributeError(... | <|body_start_0|>
if not isinstance(dictionary, ImmutableDictionary):
for k, v in dictionary.iteritems():
dictionary[k] = Utils.make_immutable(v)
super(ImmutableDictionary, self).__init__(dictionary)
<|end_body_0|>
<|body_start_1|>
if name in self:
return ... | ImmutableDictionary | [
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"OFL-1.1",
"MS-PL",
"AFL-2.1",
"GPL-2.0-only",
"Python-2.0",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImmutableDictionary:
def __init__(self, dictionary):
"""Recursively turn dict to ImmutableDictionary"""
<|body_0|>
def __getattr__(self, name):
"""Access to self['attribute'] as self.attribute"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not i... | stack_v2_sparse_classes_36k_train_031645 | 7,150 | permissive | [
{
"docstring": "Recursively turn dict to ImmutableDictionary",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": "Access to self['attribute'] as self.attribute",
"name": "__getattr__",
"signature": "def __getattr__(self, name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014866 | Implement the Python class `ImmutableDictionary` described below.
Class description:
Implement the ImmutableDictionary class.
Method signatures and docstrings:
- def __init__(self, dictionary): Recursively turn dict to ImmutableDictionary
- def __getattr__(self, name): Access to self['attribute'] as self.attribute | Implement the Python class `ImmutableDictionary` described below.
Class description:
Implement the ImmutableDictionary class.
Method signatures and docstrings:
- def __init__(self, dictionary): Recursively turn dict to ImmutableDictionary
- def __getattr__(self, name): Access to self['attribute'] as self.attribute
<... | 23881f23577a65de396238998e8672d6c4c5a250 | <|skeleton|>
class ImmutableDictionary:
def __init__(self, dictionary):
"""Recursively turn dict to ImmutableDictionary"""
<|body_0|>
def __getattr__(self, name):
"""Access to self['attribute'] as self.attribute"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImmutableDictionary:
def __init__(self, dictionary):
"""Recursively turn dict to ImmutableDictionary"""
if not isinstance(dictionary, ImmutableDictionary):
for k, v in dictionary.iteritems():
dictionary[k] = Utils.make_immutable(v)
super(ImmutableDictionary,... | the_stack_v2_python_sparse | ambari-agent/src/main/python/ambari_agent/Utils.py | apache/ambari | train | 2,078 | |
c6c1ff53c73e6fbbb92f57162d5e0a99189a4ac6 | [
"user = get_jwt_identity()\ndata = request.get_json()\nbooking = {'flight_name': data.get('flight_name'), 'seat_number': data.get('seat_number'), 'payment': data.get('payment')}\ntry:\n cleaned_data = validate_data(**booking)\nexcept AssertionError as error:\n return (jsonify({'error': error.args[0]}), 409)\n... | <|body_start_0|>
user = get_jwt_identity()
data = request.get_json()
booking = {'flight_name': data.get('flight_name'), 'seat_number': data.get('seat_number'), 'payment': data.get('payment')}
try:
cleaned_data = validate_data(**booking)
except AssertionError as error:... | Controls all bookings and those of each flight | BookingController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookingController:
"""Controls all bookings and those of each flight"""
def create():
"""creat booking objects for logged in users"""
<|body_0|>
def bookings():
"""Returns all the bookings of a specific user"""
<|body_1|>
def flight_bookings(flight_i... | stack_v2_sparse_classes_36k_train_031646 | 2,523 | no_license | [
{
"docstring": "creat booking objects for logged in users",
"name": "create",
"signature": "def create()"
},
{
"docstring": "Returns all the bookings of a specific user",
"name": "bookings",
"signature": "def bookings()"
},
{
"docstring": "\"Returns all the flight bookings",
... | 3 | stack_v2_sparse_classes_30k_train_005861 | Implement the Python class `BookingController` described below.
Class description:
Controls all bookings and those of each flight
Method signatures and docstrings:
- def create(): creat booking objects for logged in users
- def bookings(): Returns all the bookings of a specific user
- def flight_bookings(flight_id): ... | Implement the Python class `BookingController` described below.
Class description:
Controls all bookings and those of each flight
Method signatures and docstrings:
- def create(): creat booking objects for logged in users
- def bookings(): Returns all the bookings of a specific user
- def flight_bookings(flight_id): ... | f4174888ebaf0902d842894bb48f51b9ec0c3e7e | <|skeleton|>
class BookingController:
"""Controls all bookings and those of each flight"""
def create():
"""creat booking objects for logged in users"""
<|body_0|>
def bookings():
"""Returns all the bookings of a specific user"""
<|body_1|>
def flight_bookings(flight_i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BookingController:
"""Controls all bookings and those of each flight"""
def create():
"""creat booking objects for logged in users"""
user = get_jwt_identity()
data = request.get_json()
booking = {'flight_name': data.get('flight_name'), 'seat_number': data.get('seat_number... | the_stack_v2_python_sparse | flights/controller/booking_controller.py | Bonifase/flight-reservation-api | train | 0 |
a13a2ecb0cd7c0bebe278951c7f0406fad3582aa | [
"super(subMemberEmbeddedObjectListNode, self).__init__(subMember, tree, container)\nself._parentTreeItemId = parentTreeItemId\nself._previousTreeItemId = tree.GetLastChild(parentTreeItemId)",
"if pos == 0:\n if len(self._subTreeItemIds) == 0:\n if not self._previousTreeItemId.IsOk():\n treeIt... | <|body_start_0|>
super(subMemberEmbeddedObjectListNode, self).__init__(subMember, tree, container)
self._parentTreeItemId = parentTreeItemId
self._previousTreeItemId = tree.GetLastChild(parentTreeItemId)
<|end_body_0|>
<|body_start_1|>
if pos == 0:
if len(self._subTreeItemId... | Private class. Information for a submember node that wraps a single object. | subMemberEmbeddedObjectListNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class subMemberEmbeddedObjectListNode:
"""Private class. Information for a submember node that wraps a single object."""
def __init__(self, subMember, tree, container, parentTreeItemId):
"""Create a new node inside the tree that wraps the specified submember"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k_train_031647 | 11,787 | no_license | [
{
"docstring": "Create a new node inside the tree that wraps the specified submember",
"name": "__init__",
"signature": "def __init__(self, subMember, tree, container, parentTreeItemId)"
},
{
"docstring": "Private. Wraps the specified object in a new NodeData and inserts it at the specified posi... | 2 | stack_v2_sparse_classes_30k_train_000816 | Implement the Python class `subMemberEmbeddedObjectListNode` described below.
Class description:
Private class. Information for a submember node that wraps a single object.
Method signatures and docstrings:
- def __init__(self, subMember, tree, container, parentTreeItemId): Create a new node inside the tree that wrap... | Implement the Python class `subMemberEmbeddedObjectListNode` described below.
Class description:
Private class. Information for a submember node that wraps a single object.
Method signatures and docstrings:
- def __init__(self, subMember, tree, container, parentTreeItemId): Create a new node inside the tree that wrap... | f5ecde937663091fd324c9d22fd72542d4eb1e16 | <|skeleton|>
class subMemberEmbeddedObjectListNode:
"""Private class. Information for a submember node that wraps a single object."""
def __init__(self, subMember, tree, container, parentTreeItemId):
"""Create a new node inside the tree that wraps the specified submember"""
<|body_0|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class subMemberEmbeddedObjectListNode:
"""Private class. Information for a submember node that wraps a single object."""
def __init__(self, subMember, tree, container, parentTreeItemId):
"""Create a new node inside the tree that wraps the specified submember"""
super(subMemberEmbeddedObjectList... | the_stack_v2_python_sparse | Python/App/Proxys/NodeData.py | kujira70/simbicon | train | 3 |
e21a20afbea56534d5163025dc7f9af39c5520cd | [
"assert len(observation_space.shape) == 1, 'Only flat spaces supported by MLP model'\nassert len(action_space.shape) == 1, 'Only flat action spaces supported by MLP model'\nsuper().__init__(observation_space, action_space, signal_space)\nself.policy_weight = policy_weight\nself.reward_scale = signal_space.span\nsel... | <|body_start_0|>
assert len(observation_space.shape) == 1, 'Only flat spaces supported by MLP model'
assert len(action_space.shape) == 1, 'Only flat action spaces supported by MLP model'
super().__init__(observation_space, action_space, signal_space)
self.policy_weight = policy_weight
... | Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded action computes predicts the encode... | MLPICM | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded a... | stack_v2_sparse_classes_36k_train_031648 | 8,668 | permissive | [
{
"docstring": ":param policy_weight: weight to be applied to the ``policy_loss`` in the ``loss`` method. Allows to control how important optimizing policy to optimizing the curiosity module :param signal_space: used for scaling the intrinsic reward returned by this module. Can be used to control how the fluctu... | 4 | stack_v2_sparse_classes_30k_train_014774 | Implement the Python class `MLPICM` described below.
Class description:
Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model tha... | Implement the Python class `MLPICM` described below.
Class description:
Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model tha... | 21e3564696062b67151b013fd5e47df46cf44aa5 | <|skeleton|>
class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLPICM:
"""Implements the Intrinsic Curiosity Module described in paper: https://arxiv.org/pdf/1705.05363.pdf The overview of the idea is to reward the agent for exploring unseen states. It is achieved by implementing two models. One called forward model that given the encoded state and encoded action compute... | the_stack_v2_python_sparse | neodroidagent/utilities/exploration/intrinsic_signals/torch_isp/curiosity/icm.py | sintefneodroid/agent | train | 9 |
cf929f5a18ad3789f7a86ddd26c0fe42368527a5 | [
"self.env.revert_snapshot('ready_with_3_slaves')\nself.prepare_plugin()\nself.helpers.create_cluster(name=self.__class__.__name__)\nself.activate_plugin()",
"self.check_run('deploy_zabbix_monitoring_ha')\nself.env.revert_snapshot('ready_with_5_slaves')\nself.prepare_plugin()\nself.helpers.create_cluster(name=self... | <|body_start_0|>
self.env.revert_snapshot('ready_with_3_slaves')
self.prepare_plugin()
self.helpers.create_cluster(name=self.__class__.__name__)
self.activate_plugin()
<|end_body_0|>
<|body_start_1|>
self.check_run('deploy_zabbix_monitoring_ha')
self.env.revert_snapshot(... | Class for smoke testing the zabbix plugin. | TestZabbix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestZabbix:
"""Class for smoke testing the zabbix plugin."""
def install_zabbix(self):
"""Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster 4. Check that the plugin can be enabled Duration 20m"""
... | stack_v2_sparse_classes_36k_train_031649 | 4,155 | no_license | [
{
"docstring": "Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster 4. Check that the plugin can be enabled Duration 20m",
"name": "install_zabbix",
"signature": "def install_zabbix(self)"
},
{
"docstring": "Dep... | 4 | stack_v2_sparse_classes_30k_train_010599 | Implement the Python class `TestZabbix` described below.
Class description:
Class for smoke testing the zabbix plugin.
Method signatures and docstrings:
- def install_zabbix(self): Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster ... | Implement the Python class `TestZabbix` described below.
Class description:
Class for smoke testing the zabbix plugin.
Method signatures and docstrings:
- def install_zabbix(self): Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster ... | 179249df2d206eeabb3955c9dc8cb78cac3c36c6 | <|skeleton|>
class TestZabbix:
"""Class for smoke testing the zabbix plugin."""
def install_zabbix(self):
"""Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster 4. Check that the plugin can be enabled Duration 20m"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestZabbix:
"""Class for smoke testing the zabbix plugin."""
def install_zabbix(self):
"""Install Zabbix plugin and check it exists Scenario: 1. Upload Zabbix plugin to the master node 2. Install the plugin 3. Create a cluster 4. Check that the plugin can be enabled Duration 20m"""
self.e... | the_stack_v2_python_sparse | stacklight_tests/zabbix/test_smoke_bvt.py | rkhozinov/stacklight-integration-tests | train | 1 |
ae0e412dc35b56ae593b9a2bc3e50320f1708142 | [
"m = len(obstacleGrid)\nn = len(obstacleGrid[0])\ndp = [[0 for _ in range(n)] for _ in range(m)]\nfor i in range(m):\n for j in range(n):\n if obstacleGrid[0][0] == 1:\n return 0\n if obstacleGrid[i][j] == 1:\n dp[i][j] = 0\n elif i == 0 or j == 0:\n dp[i][j]... | <|body_start_0|>
m = len(obstacleGrid)
n = len(obstacleGrid[0])
dp = [[0 for _ in range(n)] for _ in range(m)]
for i in range(m):
for j in range(n):
if obstacleGrid[0][0] == 1:
return 0
if obstacleGrid[i][j] == 1:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])"""
<|body_0|>
def uniquePathsWithObstacles1(self, obstacleGrid):
""":type obstacleGrid: List[List[... | stack_v2_sparse_classes_36k_train_031650 | 2,622 | no_license | [
{
"docstring": ":type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])",
"name": "uniquePathsWithObstacles",
"signature": "def uniquePathsWithObstacles(self, obstacleGrid)"
},
{
"docstring": ":type obstacleGrid: List[List[int]] :rtype: int",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid): :type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])
- def uniquePathsWithO... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePathsWithObstacles(self, obstacleGrid): :type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])
- def uniquePathsWithO... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])"""
<|body_0|>
def uniquePathsWithObstacles1(self, obstacleGrid):
""":type obstacleGrid: List[List[... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePathsWithObstacles(self, obstacleGrid):
""":type obstacleGrid: List[List[int]] :rtype: int 记住：二维数组的row 是 len(obstacleGrid) col 是len(obstacleGrid{0])"""
m = len(obstacleGrid)
n = len(obstacleGrid[0])
dp = [[0 for _ in range(n)] for _ in range(m)]
for ... | the_stack_v2_python_sparse | 算法/动态规划/不同路径2.py | RichieSong/algorithm | train | 0 | |
1304f8f616f91930fafd0307a67fd2fb1c24ad44 | [
"next_index = next_object_key(self)\nelement_ids = self.get_member_ids_from_nodes_ids(node_A, node_B)\nif element_ids != None:\n print('There is more than one member with the same end nodes. Ensure they have different offsets.')\nmember = Member(node_A, node_B, section_id, fixity_A, fixity_B, type, cable_length)... | <|body_start_0|>
next_index = next_object_key(self)
element_ids = self.get_member_ids_from_nodes_ids(node_A, node_B)
if element_ids != None:
print('There is more than one member with the same end nodes. Ensure they have different offsets.')
member = Member(node_A, node_B, sec... | Creates an instance of the SkyCiv Members class. | Members | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Members:
"""Creates an instance of the SkyCiv Members class."""
def add(self, node_A: int, node_B: int, section_id: int, fixity_A: str='FFFFFF', fixity_B: str='FFFFFF', type: Literal['normal', 'normal_continuous', 'cable', 'rigid']='normal', cable_length: float=None) -> int:
"""Creat... | stack_v2_sparse_classes_36k_train_031651 | 2,666 | permissive | [
{
"docstring": "Create a member with the next available ID. Args: node_A (int): The ID of the node at the beginning of the member. node_B (int): The ID of the node at the end of the member. section_id (int): The ID of the section to apply to the member. fixity_A (str, optional): See docs for restraint code. htt... | 2 | stack_v2_sparse_classes_30k_train_012880 | Implement the Python class `Members` described below.
Class description:
Creates an instance of the SkyCiv Members class.
Method signatures and docstrings:
- def add(self, node_A: int, node_B: int, section_id: int, fixity_A: str='FFFFFF', fixity_B: str='FFFFFF', type: Literal['normal', 'normal_continuous', 'cable', '... | Implement the Python class `Members` described below.
Class description:
Creates an instance of the SkyCiv Members class.
Method signatures and docstrings:
- def add(self, node_A: int, node_B: int, section_id: int, fixity_A: str='FFFFFF', fixity_B: str='FFFFFF', type: Literal['normal', 'normal_continuous', 'cable', '... | 1cf3dad7f8d451760df02886df41684add72a4eb | <|skeleton|>
class Members:
"""Creates an instance of the SkyCiv Members class."""
def add(self, node_A: int, node_B: int, section_id: int, fixity_A: str='FFFFFF', fixity_B: str='FFFFFF', type: Literal['normal', 'normal_continuous', 'cable', 'rigid']='normal', cable_length: float=None) -> int:
"""Creat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Members:
"""Creates an instance of the SkyCiv Members class."""
def add(self, node_A: int, node_B: int, section_id: int, fixity_A: str='FFFFFF', fixity_B: str='FFFFFF', type: Literal['normal', 'normal_continuous', 'cable', 'rigid']='normal', cable_length: float=None) -> int:
"""Create a member wi... | the_stack_v2_python_sparse | src/skyciv/classes/model/components/members/members.py | osasanchezme/skyciv-pip | train | 0 |
a3b5b67bccd916f09f37fb18587f6d9f64adf8da | [
"super().__init__()\nif backbone not in FLEXUNET_BACKBONE.register_dict:\n raise ValueError(f'invalid model_name {backbone} found, must be one of {FLEXUNET_BACKBONE.register_dict.keys()}.')\nif spatial_dims not in (2, 3):\n raise ValueError('spatial_dims can only be 2 or 3.')\nencoder = FLEXUNET_BACKBONE.regi... | <|body_start_0|>
super().__init__()
if backbone not in FLEXUNET_BACKBONE.register_dict:
raise ValueError(f'invalid model_name {backbone} found, must be one of {FLEXUNET_BACKBONE.register_dict.keys()}.')
if spatial_dims not in (2, 3):
raise ValueError('spatial_dims can onl... | A flexible implementation of UNet-like encoder-decoder architecture. | FlexibleUNet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.0... | stack_v2_sparse_classes_36k_train_031652 | 14,147 | permissive | [
{
"docstring": "A flexible implement of UNet, in which the backbone/encoder can be replaced with any efficient network. Currently the input must have a 2 or 3 spatial dimension and the spatial size of each dimension must be a multiple of 32 if is_pad parameter is False. Please notice each output of backbone mus... | 2 | stack_v2_sparse_classes_30k_train_004433 | Implement the Python class `FlexibleUNet` described below.
Class description:
A flexible implementation of UNet-like encoder-decoder architecture.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 3... | Implement the Python class `FlexibleUNet` described below.
Class description:
A flexible implementation of UNet-like encoder-decoder architecture.
Method signatures and docstrings:
- def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 3... | e48c3e2c741fa3fc705c4425d17ac4a5afac6c47 | <|skeleton|>
class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlexibleUNet:
"""A flexible implementation of UNet-like encoder-decoder architecture."""
def __init__(self, in_channels: int, out_channels: int, backbone: str, pretrained: bool=False, decoder_channels: tuple=(256, 128, 64, 32, 16), spatial_dims: int=2, norm: str | tuple=('batch', {'eps': 0.001, 'momentum... | the_stack_v2_python_sparse | monai/networks/nets/flexible_unet.py | Project-MONAI/MONAI | train | 4,805 |
df8a70864db222d8fddd04e3ab2491a2a178eb39 | [
"res = 0\ns = []\nfor i in range(len(height)):\n while s and height[i] > height[s[-1]]:\n top = s.pop()\n if s:\n w = i - s[-1] - 1\n l = min(height[s[-1]], height[i]) - height[top]\n res += w * l\n s.append(i)\nreturn res",
"res = 0\nn = len(height)\nfor i in ... | <|body_start_0|>
res = 0
s = []
for i in range(len(height)):
while s and height[i] > height[s[-1]]:
top = s.pop()
if s:
w = i - s[-1] - 1
l = min(height[s[-1]], height[i]) - height[top]
res +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
<|body_0|>
def trap1(self, height):
""":type height: List[int] :rtype: int brute forth"""
<|body_1|>
def trap2(self, height):
""":type height: List[int] :rtyp... | stack_v2_sparse_classes_36k_train_031653 | 3,225 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int using stack",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int brute forth",
"name": "trap1",
"signature": "def trap1(self, height)"
},
{
"docstring": ":type height: Li... | 5 | stack_v2_sparse_classes_30k_train_017904 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int using stack
- def trap1(self, height): :type height: List[int] :rtype: int brute forth
- def trap2(self, height): :typ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int using stack
- def trap1(self, height): :type height: List[int] :rtype: int brute forth
- def trap2(self, height): :typ... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
<|body_0|>
def trap1(self, height):
""":type height: List[int] :rtype: int brute forth"""
<|body_1|>
def trap2(self, height):
""":type height: List[int] :rtyp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
res = 0
s = []
for i in range(len(height)):
while s and height[i] > height[s[-1]]:
top = s.pop()
if s:
w = i - s[-1] - 1
... | the_stack_v2_python_sparse | PythonCode/src/0042_Trapping_Rain_Water.py | oneyuan/CodeforFun | train | 0 | |
17ee0daaafa97c0964a24881ac8b96baf8a1f688 | [
"n = len(nums)\nM = [0] * n\nj = n - 1\nfor i in range(n - 2, -1, -1):\n if nums[i] != 0:\n M[i] = 1 + min(M[j:j + nums[i]])\n else:\n M[i] = 1 + M[j]\n j = i\nreturn M[0]",
"length = len(nums)\njumps, curEnd, curFarthest = (0, 0, 0)\nfor i in range(length - 1):\n curFarthest = max(curFa... | <|body_start_0|>
n = len(nums)
M = [0] * n
j = n - 1
for i in range(n - 2, -1, -1):
if nums[i] != 0:
M[i] = 1 + min(M[j:j + nums[i]])
else:
M[i] = 1 + M[j]
j = i
return M[0]
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k_train_031654 | 1,304 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump",
"signature": "def jump(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "jump",
"signature": "def jump(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "j... | 3 | stack_v2_sparse_classes_30k_val_001121 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump(self, nums): :type nums: List[int] :rtype: int
- def jump(self, nums): :type nums: List[int] :rtype: int
<|ske... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def jump(self, nums):
""":type nums: List[int] :rtype: int"""
n = len(nums)
M = [0] * n
j = n - 1
for i in range(n - 2, -1, -1):
if nums[i] != 0:
M[i] = 1 + min(M[j:j + nums[i]])
else:
M[i] = 1 + M[j]
... | the_stack_v2_python_sparse | 0045_Jump_Game_II.py | bingli8802/leetcode | train | 0 | |
a01f0b92b5474681ef51e6c9fe9d37b7d31b7413 | [
"self.__bit = BIT(n)\nself.__lookup = {i: i + 1 for i in xrange(n)}\nself.__curr = n",
"pos = self.__bit.binary_lift(k)\nval = self.__lookup.pop(pos)\nself.__bit.add(pos, -1)\nself.__bit.add(self.__curr, 1)\nself.__lookup[self.__curr] = val\nself.__curr += 1\nreturn val"
] | <|body_start_0|>
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in xrange(n)}
self.__curr = n
<|end_body_0|>
<|body_start_1|>
pos = self.__bit.binary_lift(k)
val = self.__lookup.pop(pos)
self.__bit.add(pos, -1)
self.__bit.add(self.__curr, 1)
self.__l... | MRUQueue2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in xrange(n)}
self.__... | stack_v2_sparse_classes_36k_train_031655 | 3,178 | permissive | [
{
"docstring": ":type n: int",
"name": "__init__",
"signature": "def __init__(self, n)"
},
{
"docstring": ":type k: int :rtype: int",
"name": "fetch",
"signature": "def fetch(self, k)"
}
] | 2 | null | Implement the Python class `MRUQueue2` described below.
Class description:
Implement the MRUQueue2 class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int | Implement the Python class `MRUQueue2` described below.
Class description:
Implement the MRUQueue2 class.
Method signatures and docstrings:
- def __init__(self, n): :type n: int
- def fetch(self, k): :type k: int :rtype: int
<|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
... | 4dc4e6642dc92f1983c13564cc0fd99917cab358 | <|skeleton|>
class MRUQueue2:
def __init__(self, n):
""":type n: int"""
<|body_0|>
def fetch(self, k):
""":type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MRUQueue2:
def __init__(self, n):
""":type n: int"""
self.__bit = BIT(n)
self.__lookup = {i: i + 1 for i in xrange(n)}
self.__curr = n
def fetch(self, k):
""":type k: int :rtype: int"""
pos = self.__bit.binary_lift(k)
val = self.__lookup.pop(pos)
... | the_stack_v2_python_sparse | Python/design-most-recently-used-queue.py | kamyu104/LeetCode-Solutions | train | 4,549 | |
06e53bb7f00685fe2d0908c1c4d8fcfddc6f4fb5 | [
"from two1.server.machine_auth_wallet import MachineAuthWallet\nsuper().__init__()\nif isinstance(wallet, MachineAuthWallet):\n self.wallet = wallet\nelse:\n self.wallet = MachineAuthWallet(wallet)\nif username is None:\n import two1.commands.util.config as config\n self.username = config.Config().usern... | <|body_start_0|>
from two1.server.machine_auth_wallet import MachineAuthWallet
super().__init__()
if isinstance(wallet, MachineAuthWallet):
self.wallet = wallet
else:
self.wallet = MachineAuthWallet(wallet)
if username is None:
import two1.comm... | BitRequests for making bit-transfer payments. | BitTransferRequests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BitTransferRequests:
"""BitRequests for making bit-transfer payments."""
def __init__(self, wallet, username=None):
"""Initialize the bittransfer with wallet and username."""
<|body_0|>
def make_402_payment(self, response, max_price):
"""Make a bit-transfer payme... | stack_v2_sparse_classes_36k_train_031656 | 16,246 | permissive | [
{
"docstring": "Initialize the bittransfer with wallet and username.",
"name": "__init__",
"signature": "def __init__(self, wallet, username=None)"
},
{
"docstring": "Make a bit-transfer payment to the payment-handling service.",
"name": "make_402_payment",
"signature": "def make_402_pay... | 3 | null | Implement the Python class `BitTransferRequests` described below.
Class description:
BitRequests for making bit-transfer payments.
Method signatures and docstrings:
- def __init__(self, wallet, username=None): Initialize the bittransfer with wallet and username.
- def make_402_payment(self, response, max_price): Make... | Implement the Python class `BitTransferRequests` described below.
Class description:
BitRequests for making bit-transfer payments.
Method signatures and docstrings:
- def __init__(self, wallet, username=None): Initialize the bittransfer with wallet and username.
- def make_402_payment(self, response, max_price): Make... | a5e99fccf11ed75420775ae3e924c9ce94f2e86d | <|skeleton|>
class BitTransferRequests:
"""BitRequests for making bit-transfer payments."""
def __init__(self, wallet, username=None):
"""Initialize the bittransfer with wallet and username."""
<|body_0|>
def make_402_payment(self, response, max_price):
"""Make a bit-transfer payme... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BitTransferRequests:
"""BitRequests for making bit-transfer payments."""
def __init__(self, wallet, username=None):
"""Initialize the bittransfer with wallet and username."""
from two1.server.machine_auth_wallet import MachineAuthWallet
super().__init__()
if isinstance(wal... | the_stack_v2_python_sparse | two1/bitrequests/bitrequests.py | shayanb/two1 | train | 4 |
d3d1c460503f3a9a83bceb566fbb2ffdd01e3dde | [
"super(InvoerFrame, self).__init__(parent, id, title, pos, size, style, name)\nself.Paneel = SubPaneel(self)\nself.Opslaan = OpslaanPaneel(self.Paneel, id)\nself.Knoppen = KnoppenPaneel(self.Paneel, butid, id)\nself.Zetten = ZettenPaneel(self.Paneel, id)\nallbox = wx.BoxSizer(wx.VERTICAL)\nallbox.Add(self.Opslaan, ... | <|body_start_0|>
super(InvoerFrame, self).__init__(parent, id, title, pos, size, style, name)
self.Paneel = SubPaneel(self)
self.Opslaan = OpslaanPaneel(self.Paneel, id)
self.Knoppen = KnoppenPaneel(self.Paneel, butid, id)
self.Zetten = ZettenPaneel(self.Paneel, id)
allbo... | Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie. | InvoerFrame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InvoerFrame:
"""Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie."""
def __init__(self, parent, butid, id=wx.ID_ANY, title='DNA-Mind', pos=wx.DefaultPosition, size=(300, 450), styl... | stack_v2_sparse_classes_36k_train_031657 | 3,857 | no_license | [
{
"docstring": "Maakt en toont InvoerScherm. De __init__ methode heeft 8 parameters nodig. parent De ouder van het paneel. butid Getal die gebruikt wordt om door te sturen naar KnoppenPaneel. Zie documentatie KnoppenPaneel voor meer informatie. id=wx.ID_ANY id voor frame. Als er geen id aanwezig is, dan zal dez... | 2 | stack_v2_sparse_classes_30k_train_019183 | Implement the Python class `InvoerFrame` described below.
Class description:
Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie.
Method signatures and docstrings:
- def __init__(self, parent, butid, id=wx.ID_... | Implement the Python class `InvoerFrame` described below.
Class description:
Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie.
Method signatures and docstrings:
- def __init__(self, parent, butid, id=wx.ID_... | 6093fb23294f0a5d42f61113e607d3c1fb94542f | <|skeleton|>
class InvoerFrame:
"""Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie."""
def __init__(self, parent, butid, id=wx.ID_ANY, title='DNA-Mind', pos=wx.DefaultPosition, size=(300, 450), styl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InvoerFrame:
"""Klasse maakt een frame met daarin een opslag module en de mogelijkheid om aantal zetten te bepalen voor DNA-Mind. Zie documentatie __init__ voor meer informatie."""
def __init__(self, parent, butid, id=wx.ID_ANY, title='DNA-Mind', pos=wx.DefaultPosition, size=(300, 450), style=wx.DEFAULT_... | the_stack_v2_python_sparse | DNA-Mastermind-application/InvoerScherm.py | sdevriend/Student-Portfolio | train | 0 |
bf9053c6e6f73810fbb974f84e797cbf6d39f7c4 | [
"ans = []\nself.combination(ans, [], [i + 1 for i in range(n)], k)\nreturn ans",
"if len(pre) == k:\n ans.append(pre.copy())\nelse:\n for i in range(len(nums)):\n num = nums[i]\n if pre and num < pre[-1]:\n continue\n pre.append(num)\n nums.pop(i)\n self.combina... | <|body_start_0|>
ans = []
self.combination(ans, [], [i + 1 for i in range(n)], k)
return ans
<|end_body_0|>
<|body_start_1|>
if len(pre) == k:
ans.append(pre.copy())
else:
for i in range(len(nums)):
num = nums[i]
if pre and... | 20190907 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""20190907"""
def combine(self, n: int, k: int) -> List[List[int]]:
"""从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行"""
<|body_0|>
def combination(self, ans: List[List[int]], pre: List[int], nums: List[int], k: int):
"""组合"""
<|body_1|>
def permutation(... | stack_v2_sparse_classes_36k_train_031658 | 1,670 | no_license | [
{
"docstring": "从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行",
"name": "combine",
"signature": "def combine(self, n: int, k: int) -> List[List[int]]"
},
{
"docstring": "组合",
"name": "combination",
"signature": "def combination(self, ans: List[List[int]], pre: List[int], nums: List[int], k: int)"
},... | 3 | null | Implement the Python class `Solution` described below.
Class description:
20190907
Method signatures and docstrings:
- def combine(self, n: int, k: int) -> List[List[int]]: 从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行
- def combination(self, ans: List[List[int]], pre: List[int], nums: List[int], k: int): 组合
- def permutation(self... | Implement the Python class `Solution` described below.
Class description:
20190907
Method signatures and docstrings:
- def combine(self, n: int, k: int) -> List[List[int]]: 从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行
- def combination(self, ans: List[List[int]], pre: List[int], nums: List[int], k: int): 组合
- def permutation(self... | efea806d49f07d78e3db0390696778d4a7fc6c28 | <|skeleton|>
class Solution:
"""20190907"""
def combine(self, n: int, k: int) -> List[List[int]]:
"""从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行"""
<|body_0|>
def combination(self, ans: List[List[int]], pre: List[int], nums: List[int], k: int):
"""组合"""
<|body_1|>
def permutation(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""20190907"""
def combine(self, n: int, k: int) -> List[List[int]]:
"""从 n 里面选 k 个，但是注意是组合，不是排列 结果慢得不行"""
ans = []
self.combination(ans, [], [i + 1 for i in range(n)], k)
return ans
def combination(self, ans: List[List[int]], pre: List[int], nums: List[int]... | the_stack_v2_python_sparse | ToolsX/leetcode/0077/0077.py | JunLei-MI/PythonX | train | 0 |
f014376d5dce38c1fe70606fb04b3cf8007194c5 | [
"wrapper = getSAWrapper('gites_wallons')\nsession = wrapper.session\nquery = session.query(Commune)\nquery = query.order_by(Commune.com_nom)\nallCommunes = query.all()\nreturn allCommunes",
"if langue == 'N':\n provincePk = [0]\nif langue == 'F':\n provincePk = [1, 2, 3, 4, 5, 6]\nif langue == 'E':\n pro... | <|body_start_0|>
wrapper = getSAWrapper('gites_wallons')
session = wrapper.session
query = session.query(Commune)
query = query.order_by(Commune.com_nom)
allCommunes = query.all()
return allCommunes
<|end_body_0|>
<|body_start_1|>
if langue == 'N':
pr... | CommuneView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommuneView:
def getAllCommunes(self):
"""recuperation de toutes les communes"""
<|body_0|>
def getAllCommunesByRegion(self, langue, tri=None):
"""recuperation de toutes les communes selon leur langues basé sur la com_prov_pk (table priovince) 0 --> toutes les provin... | stack_v2_sparse_classes_36k_train_031659 | 4,194 | no_license | [
{
"docstring": "recuperation de toutes les communes",
"name": "getAllCommunes",
"signature": "def getAllCommunes(self)"
},
{
"docstring": "recuperation de toutes les communes selon leur langues basé sur la com_prov_pk (table priovince) 0 --> toutes les provinces flamandes",
"name": "getAllCo... | 6 | stack_v2_sparse_classes_30k_train_005890 | Implement the Python class `CommuneView` described below.
Class description:
Implement the CommuneView class.
Method signatures and docstrings:
- def getAllCommunes(self): recuperation de toutes les communes
- def getAllCommunesByRegion(self, langue, tri=None): recuperation de toutes les communes selon leur langues b... | Implement the Python class `CommuneView` described below.
Class description:
Implement the CommuneView class.
Method signatures and docstrings:
- def getAllCommunes(self): recuperation de toutes les communes
- def getAllCommunesByRegion(self, langue, tri=None): recuperation de toutes les communes selon leur langues b... | 1135360f71efb6f19ecf420a521787fe36b3f77d | <|skeleton|>
class CommuneView:
def getAllCommunes(self):
"""recuperation de toutes les communes"""
<|body_0|>
def getAllCommunesByRegion(self, langue, tri=None):
"""recuperation de toutes les communes selon leur langues basé sur la com_prov_pk (table priovince) 0 --> toutes les provin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommuneView:
def getAllCommunes(self):
"""recuperation de toutes les communes"""
wrapper = getSAWrapper('gites_wallons')
session = wrapper.session
query = session.query(Commune)
query = query.order_by(Commune.com_nom)
allCommunes = query.all()
return all... | the_stack_v2_python_sparse | gites/gdwadmin/browser/manage_commune.py | gitesdewallonie/gites.gdwadmin | train | 0 | |
8646305231138426c8f84f194405b45dedd8ec38 | [
"fin = open(filein, 'r')\nfout = open(fileout, 'w')\nl_cnt = 0\nfor line in fin:\n l_List = line.rstrip('|').lstrip('|').split('|')\n l_List = [el.strip() for el in l_List]\n if l_cnt == 0:\n l_cnt += 1\n line_o = ','.join(l_List).rstrip(',') + '\\n'\n fout.write(line_o)\n conti... | <|body_start_0|>
fin = open(filein, 'r')
fout = open(fileout, 'w')
l_cnt = 0
for line in fin:
l_List = line.rstrip('|').lstrip('|').split('|')
l_List = [el.strip() for el in l_List]
if l_cnt == 0:
l_cnt += 1
line_o = ','... | SAPFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SAPFile:
def fixLines1(self, filein, fileout):
"""This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file data source to the same DSO a) fixes quantities by removing trailing minus and adding to the front ... | stack_v2_sparse_classes_36k_train_031660 | 3,793 | no_license | [
{
"docstring": "This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file data source to the same DSO a) fixes quantities by removing trailing minus and adding to the front b) Puts dates in the correct format dd.mm.yyyy -> YYYYMMDD... | 4 | stack_v2_sparse_classes_30k_train_003708 | Implement the Python class `SAPFile` described below.
Class description:
Implement the SAPFile class.
Method signatures and docstrings:
- def fixLines1(self, filein, fileout): This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file dat... | Implement the Python class `SAPFile` described below.
Class description:
Implement the SAPFile class.
Method signatures and docstrings:
- def fixLines1(self, filein, fileout): This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file dat... | 553f5e4da3c68856159664cb56408ffcc470cb97 | <|skeleton|>
class SAPFile:
def fixLines1(self, filein, fileout):
"""This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file data source to the same DSO a) fixes quantities by removing trailing minus and adding to the front ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SAPFile:
def fixLines1(self, filein, fileout):
"""This class takes a sap file from ZSE16 on a DSO in unconverted format. It reformats the data so that it can be loaded back via a flat file data source to the same DSO a) fixes quantities by removing trailing minus and adding to the front b) Puts dates ... | the_stack_v2_python_sparse | Utilities.py | JonathanWaterhouse/FileManipulation | train | 0 | |
6d77a849b98c8cd2c36dd676ce4807063d3ed048 | [
"super(RNNDecoder, self).__init__()\nself.embedding = tf.keras.layers.Embedding(vocab, embedding)\nself.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)\nself.F = tf.keras.layers.Dense(vocab)",
"batch, units = s_prev.shape\nattention = SelfAttentio... | <|body_start_0|>
super(RNNDecoder, self).__init__()
self.embedding = tf.keras.layers.Embedding(vocab, embedding)
self.gru = tf.keras.layers.GRU(units, recurrent_initializer='glorot_uniform', return_sequences=True, return_state=True)
self.F = tf.keras.layers.Dense(vocab)
<|end_body_0|>
<... | RNNDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNNDecoder:
def __init__(self, vocab, embedding, units, batch):
"""Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of the embedding vector units: integer representing the number of hidden units in the RNN cell batch: ... | stack_v2_sparse_classes_36k_train_031661 | 2,520 | no_license | [
{
"docstring": "Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of the embedding vector units: integer representing the number of hidden units in the RNN cell batch: integer representing the batch size",
"name": "__init__",
"signatur... | 2 | null | Implement the Python class `RNNDecoder` described below.
Class description:
Implement the RNNDecoder class.
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of ... | Implement the Python class `RNNDecoder` described below.
Class description:
Implement the RNNDecoder class.
Method signatures and docstrings:
- def __init__(self, vocab, embedding, units, batch): Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of ... | 7f9a040f23eda32c5aa154c991c930a01b490f0f | <|skeleton|>
class RNNDecoder:
def __init__(self, vocab, embedding, units, batch):
"""Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of the embedding vector units: integer representing the number of hidden units in the RNN cell batch: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNNDecoder:
def __init__(self, vocab, embedding, units, batch):
"""Args: vocab: integer representing the size of the output vocabulary embedding: integer representing the dimensionality of the embedding vector units: integer representing the number of hidden units in the RNN cell batch: integer repres... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/2-rnn_decoder.py | dbaroli/holbertonschool-machine_learning | train | 0 | |
7ada38ce3f9e547a2bbc91c707b9c16f68211b33 | [
"view = ElasticListAPIView()\nview.Meta.model = None\nwith self.assertRaises(AssertionError):\n view.get_queryset()",
"expectation = Search().query('match', field='value')\nview = ElasticListAPIView()\nview.Meta.model = MagicMock()\nview.Meta.model.return_value = 'Some'\nview.Meta.model.search.return_value = e... | <|body_start_0|>
view = ElasticListAPIView()
view.Meta.model = None
with self.assertRaises(AssertionError):
view.get_queryset()
<|end_body_0|>
<|body_start_1|>
expectation = Search().query('match', field='value')
view = ElasticListAPIView()
view.Meta.model = ... | View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic. | ViewTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewTests:
"""View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic."""
def test_model_not_set(self):
"""Test handling of no model"""
<|body_0|>
def test_model_set(self):
"""Test handling when model is set"""... | stack_v2_sparse_classes_36k_train_031662 | 12,045 | permissive | [
{
"docstring": "Test handling of no model",
"name": "test_model_not_set",
"signature": "def test_model_not_set(self)"
},
{
"docstring": "Test handling when model is set",
"name": "test_model_set",
"signature": "def test_model_set(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000785 | Implement the Python class `ViewTests` described below.
Class description:
View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic.
Method signatures and docstrings:
- def test_model_not_set(self): Test handling of no model
- def test_model_set(self): Test handling... | Implement the Python class `ViewTests` described below.
Class description:
View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic.
Method signatures and docstrings:
- def test_model_not_set(self): Test handling of no model
- def test_model_set(self): Test handling... | 73d334a9f0df7c044c06989977a9a22dd2ff9b7a | <|skeleton|>
class ViewTests:
"""View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic."""
def test_model_not_set(self):
"""Test handling of no model"""
<|body_0|>
def test_model_set(self):
"""Test handling when model is set"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewTests:
"""View testing. Testing the actual get would take a lot of mocking for little value since it is pretty generic."""
def test_model_not_set(self):
"""Test handling of no model"""
view = ElasticListAPIView()
view.Meta.model = None
with self.assertRaises(AssertionE... | the_stack_v2_python_sparse | goldstone/drfes/tests.py | bhuvan-rk/goldstone-server | train | 0 |
337045cc7722463867f6cd9f0d62f1d6cae18876 | [
"password1 = self.cleaned_data.get('password1')\npassword2 = self.cleaned_data.get('password2')\nif password1 and password2 and (password1 != password2):\n raise forms.ValidationError(_('Passwords Mismatch'))\nself.instance.username = self.cleaned_data.get('username')\npassword_validation.validate_password(self.... | <|body_start_0|>
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2 and (password1 != password2):
raise forms.ValidationError(_('Passwords Mismatch'))
self.instance.username = self.cleaned_data.get('usernam... | Validates the user creation process. | UserCreationForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserCreationForm:
"""Validates the user creation process."""
def clean_password2(self):
"""Validates two passwords and username."""
<|body_0|>
def save(self, commit=True):
"""Saves the user data."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
p... | stack_v2_sparse_classes_36k_train_031663 | 2,027 | permissive | [
{
"docstring": "Validates two passwords and username.",
"name": "clean_password2",
"signature": "def clean_password2(self)"
},
{
"docstring": "Saves the user data.",
"name": "save",
"signature": "def save(self, commit=True)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002963 | Implement the Python class `UserCreationForm` described below.
Class description:
Validates the user creation process.
Method signatures and docstrings:
- def clean_password2(self): Validates two passwords and username.
- def save(self, commit=True): Saves the user data. | Implement the Python class `UserCreationForm` described below.
Class description:
Validates the user creation process.
Method signatures and docstrings:
- def clean_password2(self): Validates two passwords and username.
- def save(self, commit=True): Saves the user data.
<|skeleton|>
class UserCreationForm:
"""V... | 3fdc01eabdff459b31e016f9f6d1cafc19c5a292 | <|skeleton|>
class UserCreationForm:
"""Validates the user creation process."""
def clean_password2(self):
"""Validates two passwords and username."""
<|body_0|>
def save(self, commit=True):
"""Saves the user data."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserCreationForm:
"""Validates the user creation process."""
def clean_password2(self):
"""Validates two passwords and username."""
password1 = self.cleaned_data.get('password1')
password2 = self.cleaned_data.get('password2')
if password1 and password2 and (password1 != pa... | the_stack_v2_python_sparse | apps/accounts/forms.py | jimialex/django-wise | train | 0 |
419dfd4b3a05a126410ab8ba58573027ef391d5c | [
"indice_or_slice, old_values = self.convert_to_list(indice_or_slice, old_values)\nif new_values is not None and (not isinstance(new_values, list)):\n new_values = [new_values]\nif mod_type == Relation.TYPE_DELETE:\n for old_object in old_values:\n self.inverse.set_related(old_object, None)\n return\... | <|body_start_0|>
indice_or_slice, old_values = self.convert_to_list(indice_or_slice, old_values)
if new_values is not None and (not isinstance(new_values, list)):
new_values = [new_values]
if mod_type == Relation.TYPE_DELETE:
for old_object in old_values:
... | Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse relation is a One2Many. | Many2OneRelation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Many2OneRelation:
"""Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse relation is a One2Many."""
def affec... | stack_v2_sparse_classes_36k_train_031664 | 4,896 | permissive | [
{
"docstring": "Affect the inverse's side (a single object). Depending on the mod_type attribute (delete, add or modify), different actions are performed. In any case, the List4Many representing the many's part of this relation (the owning's side) affects the inverse's side (the one part of the many2one relatio... | 3 | null | Implement the Python class `Many2OneRelation` described below.
Class description:
Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse re... | Implement the Python class `Many2OneRelation` described below.
Class description:
Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse re... | f459733c9307c2f843dd9ad5d1d82feafc065816 | <|skeleton|>
class Many2OneRelation:
"""Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse relation is a One2Many."""
def affec... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Many2OneRelation:
"""Abstract class defining a many-to-one relation. This relation is used when the owning side defines a HasMany field type and the inverse side defines a HasOne field type. If the relation is bidirectional (the default), then the inverse relation is a One2Many."""
def affect(self, model... | the_stack_v2_python_sparse | src/model/relations/many2one.py | v-legoff/pa-poc3 | train | 0 |
7acfaad2df0755913dd9ea8e663b7639942ece3b | [
"if f is not None:\n self.f = f\n if hasattr(f, '__name__'):\n self.__name__ = f.__name__\n else:\n self.__name__ = f.__name__\n self.__module__ = f.__module__\n self.af = ArgumentFixer(f)\nif name is not None:\n self.name = name\nself.options = options",
"options = self.options\ni... | <|body_start_0|>
if f is not None:
self.f = f
if hasattr(f, '__name__'):
self.__name__ = f.__name__
else:
self.__name__ = f.__name__
self.__module__ = f.__module__
self.af = ArgumentFixer(f)
if name is not None:
... | Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the example below. EXAMPLES:: sage: from sage.sets.set_from_iterator import ... | EnumeratedSetFromIterator_function_decorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the ... | stack_v2_sparse_classes_36k_train_031665 | 34,216 | no_license | [
{
"docstring": "Initialize ``self``. TESTS:: sage: from sage.sets.set_from_iterator import set_from_function sage: F = set_from_function(category=FiniteEnumeratedSets())(xsrange) sage: TestSuite(F(100)).run() sage: TestSuite(F(1,5,2)).run() sage: TestSuite(F(0)).run()",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_021171 | Implement the Python class `EnumeratedSetFromIterator_function_decorator` described below.
Class description:
Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place ... | Implement the Python class `EnumeratedSetFromIterator_function_decorator` described below.
Class description:
Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place ... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the example below... | the_stack_v2_python_sparse | sage/src/sage/sets/set_from_iterator.py | bopopescu/geosci | train | 0 |
7a60a9eb60fc6e2149bedc1f8e4aa229a2b906f1 | [
"self._strategy = strategy\nself._listener = listener\nself._telemetry_runtime_producer = telemetry_runtime_producer",
"for_log, for_listener = self._strategy.process_impressions(impressions)\nif len(impressions) > len(for_log):\n self._telemetry_runtime_producer.record_impression_stats(telemetry.CounterConsta... | <|body_start_0|>
self._strategy = strategy
self._listener = listener
self._telemetry_runtime_producer = telemetry_runtime_producer
<|end_body_0|>
<|body_start_1|>
for_log, for_listener = self._strategy.process_impressions(impressions)
if len(impressions) > len(for_log):
... | Impression manager. | Manager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manager:
"""Impression manager."""
def __init__(self, strategy, telemetry_runtime_producer, listener=None):
"""Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener that will capture all seen impressions. :type listener: spli... | stack_v2_sparse_classes_36k_train_031666 | 2,373 | permissive | [
{
"docstring": "Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener that will capture all seen impressions. :type listener: splitio.client.listener.ImpressionListenerWrapper :param strategy: Impressions stragetgy instance :type strategy: (BaseStrategy... | 3 | null | Implement the Python class `Manager` described below.
Class description:
Impression manager.
Method signatures and docstrings:
- def __init__(self, strategy, telemetry_runtime_producer, listener=None): Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener tha... | Implement the Python class `Manager` described below.
Class description:
Impression manager.
Method signatures and docstrings:
- def __init__(self, strategy, telemetry_runtime_producer, listener=None): Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener tha... | 523d2395d39d189772b1db1c944db0cf4ca5769a | <|skeleton|>
class Manager:
"""Impression manager."""
def __init__(self, strategy, telemetry_runtime_producer, listener=None):
"""Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener that will capture all seen impressions. :type listener: spli... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Manager:
"""Impression manager."""
def __init__(self, strategy, telemetry_runtime_producer, listener=None):
"""Construct a manger to track and forward impressions to the queue. :param listener: Optional impressions listener that will capture all seen impressions. :type listener: splitio.client.li... | the_stack_v2_python_sparse | splitio/engine/impressions/impressions.py | splitio/python-client | train | 17 |
eddf2ead8fe6bd9a355f21e5ae1f12a83ed34bfa | [
"self.metric_name = metric_name\nself.timestamp_msecs = timestamp_msecs\nself.value = value",
"if dictionary is None:\n return None\nmetric_name = dictionary.get('metricName')\ntimestamp_msecs = dictionary.get('timestampMsecs')\nvalue = cohesity_management_sdk.models.value.Value.from_dictionary(dictionary.get(... | <|body_start_0|>
self.metric_name = metric_name
self.timestamp_msecs = timestamp_msecs
self.value = value
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
metric_name = dictionary.get('metricName')
timestamp_msecs = dictionary.get('timestamp... | Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (in milliseconds). value (Value): Specifies the value of the data point. | MetricValue | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricValue:
"""Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (in milliseconds). value (Value): Specifi... | stack_v2_sparse_classes_36k_train_031667 | 2,016 | permissive | [
{
"docstring": "Constructor for the MetricValue class",
"name": "__init__",
"signature": "def __init__(self, metric_name=None, timestamp_msecs=None, value=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of t... | 2 | stack_v2_sparse_classes_30k_train_015190 | Implement the Python class `MetricValue` described below.
Class description:
Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (i... | Implement the Python class `MetricValue` described below.
Class description:
Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (i... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MetricValue:
"""Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (in milliseconds). value (Value): Specifi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetricValue:
"""Implementation of the 'MetricValue' model. Specifies one data point of a metric. Attributes: metric_name (string): Specifies the metric name. timestamp_msecs (long|int): Specifies the creation time of a data point as a Unix epoch Timestamp (in milliseconds). value (Value): Specifies the value ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/metric_value.py | cohesity/management-sdk-python | train | 24 |
8b6e75cb154509f310f46801a1f5e93530d2ef52 | [
"super().__init__()\nself.down_rate = down_rate\nself.residual = residual\nself.c1 = get_1x1(in_width, middle_width)\nself.c2 = get_3x3(middle_width, middle_width) if use_3x3 else get_1x1(middle_width, middle_width)\nself.c3 = get_3x3(middle_width, middle_width) if use_3x3 else get_1x1(middle_width, middle_width)\n... | <|body_start_0|>
super().__init__()
self.down_rate = down_rate
self.residual = residual
self.c1 = get_1x1(in_width, middle_width)
self.c2 = get_3x3(middle_width, middle_width) if use_3x3 else get_1x1(middle_width, middle_width)
self.c3 = get_3x3(middle_width, middle_width... | Block | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Block:
def __init__(self, in_width: int, middle_width: int, out_width: int, down_rate: int=None, residual=False, use_3x3=True, zero_last=False):
"""Bottleneck Residual Block Parameters ---------- in_width : int Number of input features middle_width : int Number of intermediate features o... | stack_v2_sparse_classes_36k_train_031668 | 9,154 | permissive | [
{
"docstring": "Bottleneck Residual Block Parameters ---------- in_width : int Number of input features middle_width : int Number of intermediate features out_width : int Number of output features down_rate : int, optional Input downsampling rate, by default None residual : bool, optional Whether to include res... | 2 | stack_v2_sparse_classes_30k_train_004660 | Implement the Python class `Block` described below.
Class description:
Implement the Block class.
Method signatures and docstrings:
- def __init__(self, in_width: int, middle_width: int, out_width: int, down_rate: int=None, residual=False, use_3x3=True, zero_last=False): Bottleneck Residual Block Parameters ---------... | Implement the Python class `Block` described below.
Class description:
Implement the Block class.
Method signatures and docstrings:
- def __init__(self, in_width: int, middle_width: int, out_width: int, down_rate: int=None, residual=False, use_3x3=True, zero_last=False): Bottleneck Residual Block Parameters ---------... | 65a46e41845982def17e553a46be849d948f9f45 | <|skeleton|>
class Block:
def __init__(self, in_width: int, middle_width: int, out_width: int, down_rate: int=None, residual=False, use_3x3=True, zero_last=False):
"""Bottleneck Residual Block Parameters ---------- in_width : int Number of input features middle_width : int Number of intermediate features o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Block:
def __init__(self, in_width: int, middle_width: int, out_width: int, down_rate: int=None, residual=False, use_3x3=True, zero_last=False):
"""Bottleneck Residual Block Parameters ---------- in_width : int Number of input features middle_width : int Number of intermediate features out_width : int... | the_stack_v2_python_sparse | src/models/resnet/modules.py | yizhe-ang/vi-lab | train | 1 | |
2805a1c497e4f93966678b95a82387d37a5da1a9 | [
"super(PseTae_pretrained, self).__init__()\nself.weight_folder = weight_folder\nself.hyperparameters = hyperparameters\nself.fold_folders = [os.path.join(weight_folder, f) for f in os.listdir(weight_folder) if os.path.isdir(os.path.join(weight_folder, f))]\nif fold == 'all':\n self.n_folds = len(self.fold_folder... | <|body_start_0|>
super(PseTae_pretrained, self).__init__()
self.weight_folder = weight_folder
self.hyperparameters = hyperparameters
self.fold_folders = [os.path.join(weight_folder, f) for f in os.listdir(weight_folder) if os.path.isdir(os.path.join(weight_folder, f))]
if fold ==... | PseTae_pretrained | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PseTae_pretrained:
def __init__(self, weight_folder, hyperparameters, device='cuda', fold='all'):
"""Pretrained PseTea classifier. The class can either load the weights of a single fold or aggregate the predictions of the different sets of weights obtained during k-fold cross-validation ... | stack_v2_sparse_classes_36k_train_031669 | 19,964 | no_license | [
{
"docstring": "Pretrained PseTea classifier. The class can either load the weights of a single fold or aggregate the predictions of the different sets of weights obtained during k-fold cross-validation and produces a single prediction. Args: weight_folder (str): Path to the folder containing the different sets... | 3 | null | Implement the Python class `PseTae_pretrained` described below.
Class description:
Implement the PseTae_pretrained class.
Method signatures and docstrings:
- def __init__(self, weight_folder, hyperparameters, device='cuda', fold='all'): Pretrained PseTea classifier. The class can either load the weights of a single f... | Implement the Python class `PseTae_pretrained` described below.
Class description:
Implement the PseTae_pretrained class.
Method signatures and docstrings:
- def __init__(self, weight_folder, hyperparameters, device='cuda', fold='all'): Pretrained PseTea classifier. The class can either load the weights of a single f... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class PseTae_pretrained:
def __init__(self, weight_folder, hyperparameters, device='cuda', fold='all'):
"""Pretrained PseTea classifier. The class can either load the weights of a single fold or aggregate the predictions of the different sets of weights obtained during k-fold cross-validation ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PseTae_pretrained:
def __init__(self, weight_folder, hyperparameters, device='cuda', fold='all'):
"""Pretrained PseTea classifier. The class can either load the weights of a single fold or aggregate the predictions of the different sets of weights obtained during k-fold cross-validation and produces a... | the_stack_v2_python_sparse | generated/test_VSainteuf_pytorch_psetae.py | jansel/pytorch-jit-paritybench | train | 35 | |
c2325c19d82323e374c65c6de9fe5b1ceb86f727 | [
"if not root:\n return root\nqueue = deque([root, None])\npre_node = None\nwhile len(queue) > 0:\n node = queue.popleft()\n if node:\n if not pre_node:\n pre_node = node\n else:\n pre_node.next = node\n pre_node = node\n if node.left:\n queue... | <|body_start_0|>
if not root:
return root
queue = deque([root, None])
pre_node = None
while len(queue) > 0:
node = queue.popleft()
if node:
if not pre_node:
pre_node = node
else:
p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def connect(self, root: Node) -> Node:
"""BFS（一次遍历）。"""
<|body_0|>
def connect2(self, root: Node) -> Node:
"""层序遍历（迭代）。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return root
queue = deque([root, None]... | stack_v2_sparse_classes_36k_train_031670 | 6,787 | no_license | [
{
"docstring": "BFS（一次遍历）。",
"name": "connect",
"signature": "def connect(self, root: Node) -> Node"
},
{
"docstring": "层序遍历（迭代）。",
"name": "connect2",
"signature": "def connect2(self, root: Node) -> Node"
}
] | 2 | stack_v2_sparse_classes_30k_train_016940 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect(self, root: Node) -> Node: BFS（一次遍历）。
- def connect2(self, root: Node) -> Node: 层序遍历（迭代）。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def connect(self, root: Node) -> Node: BFS（一次遍历）。
- def connect2(self, root: Node) -> Node: 层序遍历（迭代）。
<|skeleton|>
class Solution:
def connect(self, root: Node) -> Node:
... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def connect(self, root: Node) -> Node:
"""BFS（一次遍历）。"""
<|body_0|>
def connect2(self, root: Node) -> Node:
"""层序遍历（迭代）。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def connect(self, root: Node) -> Node:
"""BFS（一次遍历）。"""
if not root:
return root
queue = deque([root, None])
pre_node = None
while len(queue) > 0:
node = queue.popleft()
if node:
if not pre_node:
... | the_stack_v2_python_sparse | 0116_populating-next-right-pointers-in-each-node.py | Nigirimeshi/leetcode | train | 0 | |
feb77b35af1dff64dce2c0a5a9701f4861715d0b | [
"super(FeedForwardGenerator, self).__init__()\nword_ids = sorted(word_ids)\nself.word_embedd = word_embedd\nself.word_ids = word_ids\nself.word_ids_set = set(word_ids)\nm_emb = word_embedd.weight.size(-1)\nweight = torch.index_select(word_embedd.weight, 0, torch.tensor(word_ids, device=cfg.device))\nself.obfenc = O... | <|body_start_0|>
super(FeedForwardGenerator, self).__init__()
word_ids = sorted(word_ids)
self.word_embedd = word_embedd
self.word_ids = word_ids
self.word_ids_set = set(word_ids)
m_emb = word_embedd.weight.size(-1)
weight = torch.index_select(word_embedd.weight, ... | FeedForwardGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeedForwardGenerator:
def __init__(self, word_ids, word_embedd, word_alphabet, char_alphabet):
"""in the generator, we try to hijack the biaffine parser model provided by Max thanks for the dynamic feature of python, we want to substitute the embedd_word all the ablation study is done he... | stack_v2_sparse_classes_36k_train_031671 | 10,807 | no_license | [
{
"docstring": "in the generator, we try to hijack the biaffine parser model provided by Max thanks for the dynamic feature of python, we want to substitute the embedd_word all the ablation study is done here, notice that once done, we need the result from the final decoder. It seems impossible to this end. But... | 2 | stack_v2_sparse_classes_30k_val_000919 | Implement the Python class `FeedForwardGenerator` described below.
Class description:
Implement the FeedForwardGenerator class.
Method signatures and docstrings:
- def __init__(self, word_ids, word_embedd, word_alphabet, char_alphabet): in the generator, we try to hijack the biaffine parser model provided by Max than... | Implement the Python class `FeedForwardGenerator` described below.
Class description:
Implement the FeedForwardGenerator class.
Method signatures and docstrings:
- def __init__(self, word_ids, word_embedd, word_alphabet, char_alphabet): in the generator, we try to hijack the biaffine parser model provided by Max than... | aa1da79dea82c36bc1b8d4d83e1d8ad40871d330 | <|skeleton|>
class FeedForwardGenerator:
def __init__(self, word_ids, word_embedd, word_alphabet, char_alphabet):
"""in the generator, we try to hijack the biaffine parser model provided by Max thanks for the dynamic feature of python, we want to substitute the embedd_word all the ablation study is done he... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeedForwardGenerator:
def __init__(self, word_ids, word_embedd, word_alphabet, char_alphabet):
"""in the generator, we try to hijack the biaffine parser model provided by Max thanks for the dynamic feature of python, we want to substitute the embedd_word all the ablation study is done here, notice tha... | the_stack_v2_python_sparse | net/generator/ff.py | ichn-hu/Parsing-Obfuscation | train | 3 | |
d94e4d1a2c61f4612ff95f8c0dd4113042e00815 | [
"for i in range(len(arr)):\n arr[i] = -float('inf')\n replace_val = max(arr)\n if replace_val == -float('inf'):\n replace_val = -1\n arr[i] = -replace_val\nreturn [-x for x in arr]",
"for i in range(len(A) - 1, -1, -1):\n A[i], mx = (mx, max(mx, A[i]))\nreturn A"
] | <|body_start_0|>
for i in range(len(arr)):
arr[i] = -float('inf')
replace_val = max(arr)
if replace_val == -float('inf'):
replace_val = -1
arr[i] = -replace_val
return [-x for x in arr]
<|end_body_0|>
<|body_start_1|>
for i in rang... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def replaceElements(self, arr):
""":type arr: List[int] :rtype: List[int]"""
<|body_0|>
def replaceElements(self, A, mx=-1):
"""mx = 1 A[i] = 1 mx = (1, 6) = 6 Input: arr = [17,18,5,4,1,-1] i"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_031672 | 1,032 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: List[int]",
"name": "replaceElements",
"signature": "def replaceElements(self, arr)"
},
{
"docstring": "mx = 1 A[i] = 1 mx = (1, 6) = 6 Input: arr = [17,18,5,4,1,-1] i",
"name": "replaceElements",
"signature": "def replaceElements(self, A, mx=... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def replaceElements(self, arr): :type arr: List[int] :rtype: List[int]
- def replaceElements(self, A, mx=-1): mx = 1 A[i] = 1 mx = (1, 6) = 6 Input: arr = [17,18,5,4,1,-1] i | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def replaceElements(self, arr): :type arr: List[int] :rtype: List[int]
- def replaceElements(self, A, mx=-1): mx = 1 A[i] = 1 mx = (1, 6) = 6 Input: arr = [17,18,5,4,1,-1] i
<|s... | 2e1751263f484709102f7f2caf18776a004c8230 | <|skeleton|>
class Solution:
def replaceElements(self, arr):
""":type arr: List[int] :rtype: List[int]"""
<|body_0|>
def replaceElements(self, A, mx=-1):
"""mx = 1 A[i] = 1 mx = (1, 6) = 6 Input: arr = [17,18,5,4,1,-1] i"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def replaceElements(self, arr):
""":type arr: List[int] :rtype: List[int]"""
for i in range(len(arr)):
arr[i] = -float('inf')
replace_val = max(arr)
if replace_val == -float('inf'):
replace_val = -1
arr[i] = -replace_val... | the_stack_v2_python_sparse | Python/Leetcode Daily Practice/Array/1299. Replace Elements with Greatest Element on Right Side.py | YaqianQi/Algorithm-and-Data-Structure | train | 1 | |
8b723db43a5ab241fb6a084d0eeb1fd2143eed7f | [
"from expedient.common.permissions.models import Permittee\nfrom expedient.common.permissions.models import ObjectPermission\nfrom expedient.common.permissions.models import PermissionOwnership\ntry:\n obj_permission = ObjectPermission.objects.get_for_object_or_class(permission, obj_or_class)\nexcept ObjectPermi... | <|body_start_0|>
from expedient.common.permissions.models import Permittee
from expedient.common.permissions.models import ObjectPermission
from expedient.common.permissions.models import PermissionOwnership
try:
obj_permission = ObjectPermission.objects.get_for_object_or_cla... | Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager. | PermissionOwnershipManager | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PermissionOwnershipManager:
"""Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager."""
def get_ownership(self, permission, obj_or_class, owner):
"""Get a PermissionOwnership instance. @param permission: The name of the per... | stack_v2_sparse_classes_36k_train_031673 | 21,795 | permissive | [
{
"docstring": "Get a PermissionOwnership instance. @param permission: The name of the permission or its L{ExpedientPermission} instance. @type permission: C{str} or L{ExpedientPermission}. @param obj_or_class: The target object or class for the permission. @type obj_or_class: C{Model} instance or C{class}. @pa... | 3 | null | Implement the Python class `PermissionOwnershipManager` described below.
Class description:
Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager.
Method signatures and docstrings:
- def get_ownership(self, permission, obj_or_class, owner): Get a PermissionO... | Implement the Python class `PermissionOwnershipManager` described below.
Class description:
Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager.
Method signatures and docstrings:
- def get_ownership(self, permission, obj_or_class, owner): Get a PermissionO... | 059ed2b3308bda2af5e1942dc9967e6573dd6a53 | <|skeleton|>
class PermissionOwnershipManager:
"""Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager."""
def get_ownership(self, permission, obj_or_class, owner):
"""Get a PermissionOwnership instance. @param permission: The name of the per... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PermissionOwnershipManager:
"""Manager for PermissionOwnership model. Adds the delete_ownership and get_ownership methods to the default manager."""
def get_ownership(self, permission, obj_or_class, owner):
"""Get a PermissionOwnership instance. @param permission: The name of the permission or it... | the_stack_v2_python_sparse | expedient/src/python/expedient/common/permissions/managers.py | dana-i2cat/felix | train | 4 |
97121c708408294e0bb9804efec9e695d6907591 | [
"location = self._parse_location(response)\nmeeting_map = {}\nfor item in response.css('.layoutArea li'):\n start = self._parse_start(item)\n if not start:\n continue\n meeting = Meeting(title='State Street Commission', description='', classification=COMMISSION, start=start, end=None, time_notes='',... | <|body_start_0|>
location = self._parse_location(response)
meeting_map = {}
for item in response.css('.layoutArea li'):
start = self._parse_start(item)
if not start:
continue
meeting = Meeting(title='State Street Commission', description='', cl... | ChiSsa1Spider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start date and time."""
<|body_1|... | stack_v2_sparse_classes_36k_train_031674 | 2,987 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse start date and time.",
"name": "_parse_start",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_020091 | Implement the Python class `ChiSsa1Spider` described below.
Class description:
Implement the ChiSsa1Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _parse_... | Implement the Python class `ChiSsa1Spider` described below.
Class description:
Implement the ChiSsa1Spider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- def _parse_... | 611fce6a2705446e25a2fc33e32090a571eb35d1 | <|skeleton|>
class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start date and time."""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChiSsa1Spider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
location = self._parse_location(response)
meeting_map = {}
for item in response.css('.layoutArea li'):... | the_stack_v2_python_sparse | city_scrapers/spiders/chi_ssa_1.py | City-Bureau/city-scrapers | train | 308 | |
8e777edd2101493e12c6b87c386837f52062e5e8 | [
"self.qobj_model = qobj_model\nself.default_qubit_los = default_qubit_los\nself.default_meas_los = default_meas_los\nself.run_config = run_config",
"lo_config = {}\nq_los = self.get_qubit_los(user_lo_config)\nif q_los:\n lo_config['qubit_lo_freq'] = q_los\nm_los = self.get_meas_los(user_lo_config)\nif m_los:\n... | <|body_start_0|>
self.qobj_model = qobj_model
self.default_qubit_los = default_qubit_los
self.default_meas_los = default_meas_los
self.run_config = run_config
<|end_body_0|>
<|body_start_1|>
lo_config = {}
q_los = self.get_qubit_los(user_lo_config)
if q_los:
... | This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend. | LoConfigConverter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoConfigConverter:
"""This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend."""
def __init__(self, qobj_model, default_qubit_los, default... | stack_v2_sparse_classes_36k_train_031675 | 3,391 | permissive | [
{
"docstring": "Create new converter. Args: qobj_model (PulseQobjExperimentConfig): qobj model for experiment config. default_qubit_los (list): List of default qubit lo frequencies. default_meas_los (list): List of default meas lo frequencies. run_config (dict): experimental configuration.",
"name": "__init... | 4 | stack_v2_sparse_classes_30k_train_009647 | Implement the Python class `LoConfigConverter` described below.
Class description:
This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend.
Method signatures and doc... | Implement the Python class `LoConfigConverter` described below.
Class description:
This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend.
Method signatures and doc... | 56ee4ca815dd0165dd62684abd364ae706b4fe10 | <|skeleton|>
class LoConfigConverter:
"""This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend."""
def __init__(self, qobj_model, default_qubit_los, default... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoConfigConverter:
"""This class supports to convert LoConfig into ~`lo_freq` attribute of configs. The format of LO frequency setup can be easily modified by replacing `get_qubit_los` and `get_meas_los` to align with your backend."""
def __init__(self, qobj_model, default_qubit_los, default_meas_los, **... | the_stack_v2_python_sparse | qiskit/qobj/converters/lo_config.py | uguraba/qiskit-terra | train | 0 |
f811a14b2db36a66f2d787b29be2f53fd04d5aef | [
"self.sizes = sizes\nself.num_layers = len(sizes) - 1\nself.weights = [np.random.randn(ch2, ch1) for ch1, ch2 in zip(sizes[:-1], sizes[1:])]\nself.biases = [np.random.randn(ch, 1) for ch in sizes[1:]]",
"for b, w in zip(self.biases, self.weights):\n z = np.dot(w, x) + b\n x = sigmoid(z)\nreturn x",
"nabla... | <|body_start_0|>
self.sizes = sizes
self.num_layers = len(sizes) - 1
self.weights = [np.random.randn(ch2, ch1) for ch1, ch2 in zip(sizes[:-1], sizes[1:])]
self.biases = [np.random.randn(ch, 1) for ch in sizes[1:]]
<|end_body_0|>
<|body_start_1|>
for b, w in zip(self.biases, self... | MLP_np | [
"LicenseRef-scancode-mulanpsl-1.0-en",
"MulanPSL-1.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLP_np:
def __init__(self, sizes):
"""size :[784,30,10]"""
<|body_0|>
def forward(self, x):
"""x:[784,1]"""
<|body_1|>
def backprop(self, x, y):
"""x:[784,1] y:[10,1]"""
<|body_2|>
def train(self, training_data, epochs, batchsz, lr, ... | stack_v2_sparse_classes_36k_train_031676 | 5,469 | permissive | [
{
"docstring": "size :[784,30,10]",
"name": "__init__",
"signature": "def __init__(self, sizes)"
},
{
"docstring": "x:[784,1]",
"name": "forward",
"signature": "def forward(self, x)"
},
{
"docstring": "x:[784,1] y:[10,1]",
"name": "backprop",
"signature": "def backprop(se... | 6 | null | Implement the Python class `MLP_np` described below.
Class description:
Implement the MLP_np class.
Method signatures and docstrings:
- def __init__(self, sizes): size :[784,30,10]
- def forward(self, x): x:[784,1]
- def backprop(self, x, y): x:[784,1] y:[10,1]
- def train(self, training_data, epochs, batchsz, lr, te... | Implement the Python class `MLP_np` described below.
Class description:
Implement the MLP_np class.
Method signatures and docstrings:
- def __init__(self, sizes): size :[784,30,10]
- def forward(self, x): x:[784,1]
- def backprop(self, x, y): x:[784,1] y:[10,1]
- def train(self, training_data, epochs, batchsz, lr, te... | 17a225169873b3c232bdfcccf7c0366d2a688354 | <|skeleton|>
class MLP_np:
def __init__(self, sizes):
"""size :[784,30,10]"""
<|body_0|>
def forward(self, x):
"""x:[784,1]"""
<|body_1|>
def backprop(self, x, y):
"""x:[784,1] y:[10,1]"""
<|body_2|>
def train(self, training_data, epochs, batchsz, lr, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLP_np:
def __init__(self, sizes):
"""size :[784,30,10]"""
self.sizes = sizes
self.num_layers = len(sizes) - 1
self.weights = [np.random.randn(ch2, ch1) for ch1, ch2 in zip(sizes[:-1], sizes[1:])]
self.biases = [np.random.randn(ch, 1) for ch in sizes[1:]]
def forwa... | the_stack_v2_python_sparse | 深度学习/手写数字例子/学生 NUMPY构建BP深度神经网络 自己写的.py | 3453566/pythonbook | train | 1 | |
4816b461155108cc8c60633c0f746c9de3096cd7 | [
"if status == 'CANCELLED' and (not cancel_reason):\n raise AcquisitionError('You have to provide a cancel reason when cancelling the order')\nif cancel_reason and (not status == 'CANCELLED'):\n raise AcquisitionError('If you select a cancel reason you need to select \"Cancelled\" in the state')",
"Provider ... | <|body_start_0|>
if status == 'CANCELLED' and (not cancel_reason):
raise AcquisitionError('You have to provide a cancel reason when cancelling the order')
if cancel_reason and (not status == 'CANCELLED'):
raise AcquisitionError('If you select a cancel reason you need to select "C... | Order record validator. | OrderValidator | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderValidator:
"""Order record validator."""
def validate_cancel(self, status, cancel_reason):
"""Validate decline is correct."""
<|body_0|>
def ensure_provider_exists(self, provider_pid):
"""Ensure provider exists or raise."""
<|body_1|>
def ensure... | stack_v2_sparse_classes_36k_train_031677 | 5,122 | permissive | [
{
"docstring": "Validate decline is correct.",
"name": "validate_cancel",
"signature": "def validate_cancel(self, status, cancel_reason)"
},
{
"docstring": "Ensure provider exists or raise.",
"name": "ensure_provider_exists",
"signature": "def ensure_provider_exists(self, provider_pid)"
... | 6 | null | Implement the Python class `OrderValidator` described below.
Class description:
Order record validator.
Method signatures and docstrings:
- def validate_cancel(self, status, cancel_reason): Validate decline is correct.
- def ensure_provider_exists(self, provider_pid): Ensure provider exists or raise.
- def ensure_doc... | Implement the Python class `OrderValidator` described below.
Class description:
Order record validator.
Method signatures and docstrings:
- def validate_cancel(self, status, cancel_reason): Validate decline is correct.
- def ensure_provider_exists(self, provider_pid): Ensure provider exists or raise.
- def ensure_doc... | 1c36526e85510100c5f64059518d1b716d87ac10 | <|skeleton|>
class OrderValidator:
"""Order record validator."""
def validate_cancel(self, status, cancel_reason):
"""Validate decline is correct."""
<|body_0|>
def ensure_provider_exists(self, provider_pid):
"""Ensure provider exists or raise."""
<|body_1|>
def ensure... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderValidator:
"""Order record validator."""
def validate_cancel(self, status, cancel_reason):
"""Validate decline is correct."""
if status == 'CANCELLED' and (not cancel_reason):
raise AcquisitionError('You have to provide a cancel reason when cancelling the order')
... | the_stack_v2_python_sparse | invenio_app_ils/acquisition/api.py | inveniosoftware/invenio-app-ils | train | 64 |
742da9a67f06192b7f0716ea788b6498591a8de7 | [
"B = A[::-1]\nfor i in range(1, len(A)):\n A[i] *= A[i - 1] or 1\n B[i] *= B[i - 1] or 1\nreturn max(A + B)",
"dp = [None] * len(nums)\ndp[0] = nums[0]\nfor i in range(1, len(nums)):\n dp[i] = max(dp[i - 1] + nums[i], nums[i])\nprint(dp)\nreturn max(dp)",
"dp = nums.copy()\nfor i in range(2, len(nums))... | <|body_start_0|>
B = A[::-1]
for i in range(1, len(A)):
A[i] *= A[i - 1] or 1
B[i] *= B[i - 1] or 1
return max(A + B)
<|end_body_0|>
<|body_start_1|>
dp = [None] * len(nums)
dp[0] = nums[0]
for i in range(1, len(nums)):
dp[i] = max(dp[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_031678 | 1,014 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxProduct",
"signature": "def maxProduct(self, A)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtyp... | 3 | stack_v2_sparse_classes_30k_train_015117 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, A): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, A): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: i... | 7bcba42556475f56fad995b97a37b98f4981da8c | <|skeleton|>
class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProduct(self, A):
""":type nums: List[int] :rtype: int"""
B = A[::-1]
for i in range(1, len(A)):
A[i] *= A[i - 1] or 1
B[i] *= B[i - 1] or 1
return max(A + B)
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int... | the_stack_v2_python_sparse | Problems/152. Maximum Product Subarray.py | chendingyan/My-Leetcode | train | 0 | |
0670e3c6c8cf4576effc01a6d76e614c73b7bf12 | [
"self.set = set()\nself.list = []\nself.label = True",
"if val not in self.set:\n self.set.add(val)\n self.list.append(val)\n return True\nelse:\n return False",
"if val in self.set:\n self.set.remove(val)\n self.label = False\n return True\nelse:\n return False",
"if self.label is Fal... | <|body_start_0|>
self.set = set()
self.list = []
self.label = True
<|end_body_0|>
<|body_start_1|>
if val not in self.set:
self.set.add(val)
self.list.append(val)
return True
else:
return False
<|end_body_1|>
<|body_start_2|>
... | RandomizedSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val):
"""Inserts a value to the set. Returns true if the set did not already contain the specified element. :type val: int :rtype: bool"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_031679 | 1,619 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a value to the set. Returns true if the set did not already contain the specified element. :type val: int :rtype: bool",
"name": "insert",
"signature": ... | 4 | stack_v2_sparse_classes_30k_train_009368 | Implement the Python class `RandomizedSet` described below.
Class description:
Implement the RandomizedSet class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val): Inserts a value to the set. Returns true if the set did not already contain the specif... | Implement the Python class `RandomizedSet` described below.
Class description:
Implement the RandomizedSet class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val): Inserts a value to the set. Returns true if the set did not already contain the specif... | 0c4c38849309124121b03cc0b4bf39071b5d1c8c | <|skeleton|>
class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val):
"""Inserts a value to the set. Returns true if the set did not already contain the specified element. :type val: int :rtype: bool"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomizedSet:
def __init__(self):
"""Initialize your data structure here."""
self.set = set()
self.list = []
self.label = True
def insert(self, val):
"""Inserts a value to the set. Returns true if the set did not already contain the specified element. :type val: i... | the_stack_v2_python_sparse | 380.py | zhangchizju2012/LeetCode | train | 7 | |
01fdc9653946bbcc5aa8a50a99b38c7a267ceb31 | [
"state_space, action_space = super().setup_spaces()\nstate_space.add_dim(Dimension(p_name_long='alpha 1', p_name_short='a1', p_description='Angular Acceleration of Pendulum 1', p_name_latex='', p_unit='degrees/second^2', p_unit_latex='\\text/s^2', p_boundaries=[-8500000, 8500000]))\nstate_space.add_dim(Dimension(p_... | <|body_start_0|>
state_space, action_space = super().setup_spaces()
state_space.add_dim(Dimension(p_name_long='alpha 1', p_name_short='a1', p_description='Angular Acceleration of Pendulum 1', p_name_latex='', p_unit='degrees/second^2', p_unit_latex='\text/s^2', p_boundaries=[-8500000, 8500000]))
... | This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root class. Parameters ---------- p_mode Mode of environment. Possible values are Mode.C_MODE_SIM... | DoublePendulumSystemS7 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoublePendulumSystemS7:
"""This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root class. Parameters ---------- p_mode Mode o... | stack_v2_sparse_classes_36k_train_031680 | 34,346 | permissive | [
{
"docstring": "Method to set up the state and action spaces of the classic Double Pendulum Environment. Inheriting from the root class, this method adds 3 dimensions for accelerations and torque respectively.",
"name": "setup_spaces",
"signature": "def setup_spaces(self)"
},
{
"docstring": "Thi... | 3 | null | Implement the Python class `DoublePendulumSystemS7` described below.
Class description:
This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root cla... | Implement the Python class `DoublePendulumSystemS7` described below.
Class description:
This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root cla... | 43faa99508d29191dd3edea05d28892db8ddd357 | <|skeleton|>
class DoublePendulumSystemS7:
"""This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root class. Parameters ---------- p_mode Mode o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoublePendulumSystemS7:
"""This is the classic implementation of Double Pendulum with 7 dimensional state space including derived accelerations of both the poles and the input torque. The dynamics of the system are inherited from the Double Pendulum Root class. Parameters ---------- p_mode Mode of environment... | the_stack_v2_python_sparse | src/mlpro/bf/systems/pool/doublependulum.py | fhswf/MLPro | train | 15 |
438982ed06b3dfe85696f774892ac9ab800ee085 | [
"self.res = 0\n\ndef solve(tmps):\n if len(tmps) == 0:\n self.res += 1\n return\n for i in range(min(len(tmps), 2)):\n if int(tmps[:i + 1]) > 0 and int(tmps[:i + 1]) <= 26:\n solve(tmps[i + 1:])\n else:\n return\nsolve(s)\nreturn self.res",
"n = len(s)\nif n... | <|body_start_0|>
self.res = 0
def solve(tmps):
if len(tmps) == 0:
self.res += 1
return
for i in range(min(len(tmps), 2)):
if int(tmps[:i + 1]) > 0 and int(tmps[:i + 1]) <= 26:
solve(tmps[i + 1:])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def numDecodings2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.res = 0
def solve(tmps):
if len(tmps) ==... | stack_v2_sparse_classes_36k_train_031681 | 1,150 | no_license | [
{
"docstring": ":type s: str :rtype: int",
"name": "numDecodings",
"signature": "def numDecodings(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "numDecodings2",
"signature": "def numDecodings2(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s): :type s: str :rtype: int
- def numDecodings2(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numDecodings(self, s): :type s: str :rtype: int
- def numDecodings2(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def numDecodings(self, s):
"... | a4018931622cb29dea2ba6a202aad0a4873e73d3 | <|skeleton|>
class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def numDecodings2(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numDecodings(self, s):
""":type s: str :rtype: int"""
self.res = 0
def solve(tmps):
if len(tmps) == 0:
self.res += 1
return
for i in range(min(len(tmps), 2)):
if int(tmps[:i + 1]) > 0 and int(tmps[:i... | the_stack_v2_python_sparse | 0091. 解码方法/main.py | swbuild1988/leetcode | train | 0 | |
a38036e61c7488377c8a4d98f9cbbd428f47f133 | [
"SIZE = 512\nx, y = np.meshgrid(np.linspace(-1, 1, SIZE), np.linspace(-1, 1, SIZE))\nd = np.sqrt(x ** 2 + y ** 2)\nsigma, mu = (1.0, 0.0)\ngaussian = np.exp(-((d - mu) ** 2 / (2.0 * sigma ** 2)))\nimg = binarize_mat(gaussian)\nself.assertEqual(len(np.unique(img)), 2)",
"verticies = get_ts_verticies(img, u=20, z=0... | <|body_start_0|>
SIZE = 512
x, y = np.meshgrid(np.linspace(-1, 1, SIZE), np.linspace(-1, 1, SIZE))
d = np.sqrt(x ** 2 + y ** 2)
sigma, mu = (1.0, 0.0)
gaussian = np.exp(-((d - mu) ** 2 / (2.0 * sigma ** 2)))
img = binarize_mat(gaussian)
self.assertEqual(len(np.uni... | Image normalizer tester. | TestNormalizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNormalizer:
"""Image normalizer tester."""
def test_binarize(self):
"""Test image binarizer."""
<|body_0|>
def visualize_ts(self, img):
"""Visualize the ts space representation of an image, points with a value of 1 will be converted to ts space. Parameters --... | stack_v2_sparse_classes_36k_train_031682 | 1,362 | no_license | [
{
"docstring": "Test image binarizer.",
"name": "test_binarize",
"signature": "def test_binarize(self)"
},
{
"docstring": "Visualize the ts space representation of an image, points with a value of 1 will be converted to ts space. Parameters ---------- img: opencv mat Image to be converted to ts ... | 2 | stack_v2_sparse_classes_30k_train_009979 | Implement the Python class `TestNormalizer` described below.
Class description:
Image normalizer tester.
Method signatures and docstrings:
- def test_binarize(self): Test image binarizer.
- def visualize_ts(self, img): Visualize the ts space representation of an image, points with a value of 1 will be converted to ts... | Implement the Python class `TestNormalizer` described below.
Class description:
Image normalizer tester.
Method signatures and docstrings:
- def test_binarize(self): Test image binarizer.
- def visualize_ts(self, img): Visualize the ts space representation of an image, points with a value of 1 will be converted to ts... | 6228d8a4f0396b422b2803f24873070ea5c8b4e1 | <|skeleton|>
class TestNormalizer:
"""Image normalizer tester."""
def test_binarize(self):
"""Test image binarizer."""
<|body_0|>
def visualize_ts(self, img):
"""Visualize the ts space representation of an image, points with a value of 1 will be converted to ts space. Parameters --... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestNormalizer:
"""Image normalizer tester."""
def test_binarize(self):
"""Test image binarizer."""
SIZE = 512
x, y = np.meshgrid(np.linspace(-1, 1, SIZE), np.linspace(-1, 1, SIZE))
d = np.sqrt(x ** 2 + y ** 2)
sigma, mu = (1.0, 0.0)
gaussian = np.exp(-((d ... | the_stack_v2_python_sparse | vision/unit_tests/test_normalize.py | MissouriMRR/IARC-2019 | train | 6 |
d31134d6d03f1a33bffb33e259ea0347f0e0f75b | [
"HTTPBasicAuthHandler.__init__(self, *args, **kwargs)\nself._tried_login = False\nself._otp_token_method = None\nself._otp_token_attempts = 0\nself._last_otp_token = None",
"otp_header = headers.get(self.OTP_TOKEN_HEADER, '')\nif otp_header and otp_header.startswith('required'):\n try:\n self._otp_token... | <|body_start_0|>
HTTPBasicAuthHandler.__init__(self, *args, **kwargs)
self._tried_login = False
self._otp_token_method = None
self._otp_token_attempts = 0
self._last_otp_token = None
<|end_body_0|>
<|body_start_1|>
otp_header = headers.get(self.OTP_TOKEN_HEADER, '')
... | Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and password. It will then fail so we can use our own retry handler. This also supports two-factor auth, for... | ReviewBoardHTTPBasicAuthHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReviewBoardHTTPBasicAuthHandler:
"""Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and password. It will then fail so we can use our... | stack_v2_sparse_classes_36k_train_031683 | 29,345 | permissive | [
{
"docstring": "Initialize the Basic Auth handler. Args: *args (tuple): Positional arguments to pass to the parent class. **kwargs (dict): Keyword arguments to pass to the parent class.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Handle an HTTP 401... | 3 | null | Implement the Python class `ReviewBoardHTTPBasicAuthHandler` described below.
Class description:
Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and passwo... | Implement the Python class `ReviewBoardHTTPBasicAuthHandler` described below.
Class description:
Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and passwo... | b106c84c274c59f7944ba5bf7706d865c78a3408 | <|skeleton|>
class ReviewBoardHTTPBasicAuthHandler:
"""Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and password. It will then fail so we can use our... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReviewBoardHTTPBasicAuthHandler:
"""Custom Basic Auth handler that doesn't retry excessively. urllib's HTTPBasicAuthHandler retries over and over, which is useless. This subclass only retries once to make sure we've attempted with a valid username and password. It will then fail so we can use our own retry ha... | the_stack_v2_python_sparse | rbtools/api/request.py | anirudha-banerjee/rbtools | train | 1 |
6190f73c9b46a8789549bcd0427fc8cae5ed743c | [
"self.conf = conf\nself.kwarg = kwargs\nself.last_status_code = None\nself.last_exception = None\nif 'timeout' not in self.kwarg:\n self.kwarg['timeout'] = self.conf['timeout']",
"retries = self.conf['retries']\nwhile retries > 0:\n try:\n response = requests.get(url, **self.kwarg)\n return re... | <|body_start_0|>
self.conf = conf
self.kwarg = kwargs
self.last_status_code = None
self.last_exception = None
if 'timeout' not in self.kwarg:
self.kwarg['timeout'] = self.conf['timeout']
<|end_body_0|>
<|body_start_1|>
retries = self.conf['retries']
w... | This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception. | Scraper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Scraper:
"""This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception."""
def __init__(self, conf, **kwargs):
"""This __init__ sets the necessary arguments for connecting with request. Args: conf (dict): This di... | stack_v2_sparse_classes_36k_train_031684 | 3,023 | no_license | [
{
"docstring": "This __init__ sets the necessary arguments for connecting with request. Args: conf (dict): This dict contains scraper configuration. **kwargs: Request arguments.",
"name": "__init__",
"signature": "def __init__(self, conf, **kwargs)"
},
{
"docstring": "Try to get a response from ... | 5 | stack_v2_sparse_classes_30k_train_013042 | Implement the Python class `Scraper` described below.
Class description:
This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception.
Method signatures and docstrings:
- def __init__(self, conf, **kwargs): This __init__ sets the necessary argument... | Implement the Python class `Scraper` described below.
Class description:
This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception.
Method signatures and docstrings:
- def __init__(self, conf, **kwargs): This __init__ sets the necessary argument... | 51bf1b08aaf75373c9e9e88a41d5df154f675160 | <|skeleton|>
class Scraper:
"""This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception."""
def __init__(self, conf, **kwargs):
"""This __init__ sets the necessary arguments for connecting with request. Args: conf (dict): This di... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Scraper:
"""This class enables easy usage of request module. Its main feature is trying to connect multiple times before throwing an exception."""
def __init__(self, conf, **kwargs):
"""This __init__ sets the necessary arguments for connecting with request. Args: conf (dict): This dict contains s... | the_stack_v2_python_sparse | python_package/pytraffic/collectors/util/scraper.py | robertcv/DICE-BigData-Traffic | train | 0 |
3aba6aa9e4795f157e89b4b3bf5f188091d6b390 | [
"super().__init__(data, *args, **kwargs)\nif user is None:\n raise TypeError(\"'user' argument must not be None\")\nself.user = user",
"if not self.user.check_password(self.cleaned_data['password']):\n raise forms.ValidationError(_('Please enter the correct password!'))\nreturn self.cleaned_data['password']... | <|body_start_0|>
super().__init__(data, *args, **kwargs)
if user is None:
raise TypeError("'user' argument must not be None")
self.user = user
<|end_body_0|>
<|body_start_1|>
if not self.user.check_password(self.cleaned_data['password']):
raise forms.ValidationEr... | Simple form with one password field for confirmation when deleting a Team. | DeleteForm | [
"MIT",
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeleteForm:
"""Simple form with one password field for confirmation when deleting a Team."""
def __init__(self, data=None, *args, user=None, **kwargs):
"""Custom initializer which takes the user account to be deleted as an additional argument."""
<|body_0|>
def clean_pas... | stack_v2_sparse_classes_36k_train_031685 | 8,844 | permissive | [
{
"docstring": "Custom initializer which takes the user account to be deleted as an additional argument.",
"name": "__init__",
"signature": "def __init__(self, data=None, *args, user=None, **kwargs)"
},
{
"docstring": "Ensures that the entered password is valid for the specified user account.",
... | 2 | stack_v2_sparse_classes_30k_train_014403 | Implement the Python class `DeleteForm` described below.
Class description:
Simple form with one password field for confirmation when deleting a Team.
Method signatures and docstrings:
- def __init__(self, data=None, *args, user=None, **kwargs): Custom initializer which takes the user account to be deleted as an addi... | Implement the Python class `DeleteForm` described below.
Class description:
Simple form with one password field for confirmation when deleting a Team.
Method signatures and docstrings:
- def __init__(self, data=None, *args, user=None, **kwargs): Custom initializer which takes the user account to be deleted as an addi... | 03e0d0377e9687c60dd0454c1c1dc0efb5151bff | <|skeleton|>
class DeleteForm:
"""Simple form with one password field for confirmation when deleting a Team."""
def __init__(self, data=None, *args, user=None, **kwargs):
"""Custom initializer which takes the user account to be deleted as an additional argument."""
<|body_0|>
def clean_pas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DeleteForm:
"""Simple form with one password field for confirmation when deleting a Team."""
def __init__(self, data=None, *args, user=None, **kwargs):
"""Custom initializer which takes the user account to be deleted as an additional argument."""
super().__init__(data, *args, **kwargs)
... | the_stack_v2_python_sparse | src/ctf_gameserver/web/registration/forms.py | fausecteam/ctf-gameserver | train | 43 |
4f71fa459c4bca6fea712763a181b5c51296e448 | [
"self.config = lib.get_config()\nself.logger = lib.get_logger()\nself.color_gpio = self.config['simon']['colors']\nself.color_detectors = dict()\nfor color in self.color_gpio:\n self.color_detectors[color] = bbb.mod.GPIO(self.color_gpio[color])\nself.pot = Pot('pot1', self.color_detectors)\nfor d in self.color_d... | <|body_start_0|>
self.config = lib.get_config()
self.logger = lib.get_logger()
self.color_gpio = self.config['simon']['colors']
self.color_detectors = dict()
for color in self.color_gpio:
self.color_detectors[color] = bbb.mod.GPIO(self.color_gpio[color])
self.... | LightDetector | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LightDetector:
def __init(self):
"""Sets up the light detecting hardware."""
<|body_0|>
def read_all(self):
"""read current value from all four detectors. :return: dict {"red":<val>, "green":<val>, "blue":<val>, "yellow":<val>}"""
<|body_1|>
def read_inp... | stack_v2_sparse_classes_36k_train_031686 | 1,488 | permissive | [
{
"docstring": "Sets up the light detecting hardware.",
"name": "__init",
"signature": "def __init(self)"
},
{
"docstring": "read current value from all four detectors. :return: dict {\"red\":<val>, \"green\":<val>, \"blue\":<val>, \"yellow\":<val>}",
"name": "read_all",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_009541 | Implement the Python class `LightDetector` described below.
Class description:
Implement the LightDetector class.
Method signatures and docstrings:
- def __init(self): Sets up the light detecting hardware.
- def read_all(self): read current value from all four detectors. :return: dict {"red":<val>, "green":<val>, "bl... | Implement the Python class `LightDetector` described below.
Class description:
Implement the LightDetector class.
Method signatures and docstrings:
- def __init(self): Sets up the light detecting hardware.
- def read_all(self): read current value from all four detectors. :return: dict {"red":<val>, "green":<val>, "bl... | 96908d2f4d8cd652d8bfc98416c45ea9f5cefc3a | <|skeleton|>
class LightDetector:
def __init(self):
"""Sets up the light detecting hardware."""
<|body_0|>
def read_all(self):
"""read current value from all four detectors. :return: dict {"red":<val>, "green":<val>, "blue":<val>, "yellow":<val>}"""
<|body_1|>
def read_inp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LightDetector:
def __init(self):
"""Sets up the light detecting hardware."""
self.config = lib.get_config()
self.logger = lib.get_logger()
self.color_gpio = self.config['simon']['colors']
self.color_detectors = dict()
for color in self.color_gpio:
se... | the_stack_v2_python_sparse | bot/hardware/lightDetector.py | imohame/bot | train | 0 | |
6ed0931aa391e0ed7a075e0203ae4e836df71b01 | [
"self.width = width\nself.progress = progress\nself.last_status = ''\nself.time = time\nself.start_time = perf_counter() if time else None\nself.update(progress, skip_erase=True)",
"self.progress = progress\nif self.time:\n now = perf_counter()\n elapsed = self.format_time(now - self.start_time)\n remain... | <|body_start_0|>
self.width = width
self.progress = progress
self.last_status = ''
self.time = time
self.start_time = perf_counter() if time else None
self.update(progress, skip_erase=True)
<|end_body_0|>
<|body_start_1|>
self.progress = progress
if self.... | A command-line progress bar. | ProgressBar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProgressBar:
"""A command-line progress bar."""
def __init__(self, width=50, progress=0, time=False):
"""Create a progress bar. This writes it to the console."""
<|body_0|>
def update(self, progress, status='', skip_erase=False):
"""Update the progress bar, rewri... | stack_v2_sparse_classes_36k_train_031687 | 4,529 | no_license | [
{
"docstring": "Create a progress bar. This writes it to the console.",
"name": "__init__",
"signature": "def __init__(self, width=50, progress=0, time=False)"
},
{
"docstring": "Update the progress bar, rewriting it to the console.",
"name": "update",
"signature": "def update(self, prog... | 4 | null | Implement the Python class `ProgressBar` described below.
Class description:
A command-line progress bar.
Method signatures and docstrings:
- def __init__(self, width=50, progress=0, time=False): Create a progress bar. This writes it to the console.
- def update(self, progress, status='', skip_erase=False): Update th... | Implement the Python class `ProgressBar` described below.
Class description:
A command-line progress bar.
Method signatures and docstrings:
- def __init__(self, width=50, progress=0, time=False): Create a progress bar. This writes it to the console.
- def update(self, progress, status='', skip_erase=False): Update th... | cb87ccf8d77244c92ea57148124e9aa8654d2a46 | <|skeleton|>
class ProgressBar:
"""A command-line progress bar."""
def __init__(self, width=50, progress=0, time=False):
"""Create a progress bar. This writes it to the console."""
<|body_0|>
def update(self, progress, status='', skip_erase=False):
"""Update the progress bar, rewri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProgressBar:
"""A command-line progress bar."""
def __init__(self, width=50, progress=0, time=False):
"""Create a progress bar. This writes it to the console."""
self.width = width
self.progress = progress
self.last_status = ''
self.time = time
self.start_t... | the_stack_v2_python_sparse | hw2/src/helpers.py | ariporad/FAI | train | 0 |
2779914145f1d58dc6ad77af9955395c51c9336c | [
"self.sdo_data = sdo_data\nself.external_reference = external_reference\nself.fetch_ssn = fetch_ssn\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nsdo_data = dictionary.get('sdoData')\nexternal_reference = dictionary.get('externalReference')\nfetch_ssn = dictionary... | <|body_start_0|>
self.sdo_data = sdo_data
self.external_reference = external_reference
self.fetch_ssn = fetch_ssn
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
sdo_data = dictionary.get('... | Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for auditlog, and invoicing fetch_ssn (bool): Fetch social security number (Requires val... | ParseSDORequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParseSDORequest:
"""Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for auditlog, and invoicing fetch_ssn (bool):... | stack_v2_sparse_classes_36k_train_031688 | 2,474 | permissive | [
{
"docstring": "Constructor for the ParseSDORequest class",
"name": "__init__",
"signature": "def __init__(self, sdo_data=None, external_reference=None, fetch_ssn=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary)... | 2 | null | Implement the Python class `ParseSDORequest` described below.
Class description:
Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for au... | Implement the Python class `ParseSDORequest` described below.
Class description:
Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for au... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class ParseSDORequest:
"""Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for auditlog, and invoicing fetch_ssn (bool):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParseSDORequest:
"""Implementation of the 'ParseSDORequest' model. TODO: type model description here. Attributes: sdo_data (string): Base 64 encoded SDO (Signed document) external_reference (string): The service reference for the signing. Will be used for auditlog, and invoicing fetch_ssn (bool): Fetch social... | the_stack_v2_python_sparse | idfy_rest_client/models/parse_sdo_request.py | dealflowteam/Idfy | train | 0 |
a5843c092b533200e039c8b9013af4c99543248a | [
"lengths = [len(s) for s in strs]\nnstrs = len(strs)\nencoded = str(nstrs) + '|' + '|'.join([str(l) for l in lengths]) + '|'\nencoded += ''.join(strs)\nreturn encoded",
"i, j = (0, 0)\nwhile s[j] != '|':\n j += 1\nnstrs = int(s[i:j])\ni = j + 1\nj += 1\nlengths = list()\nfor _ in range(nstrs):\n while s[j] ... | <|body_start_0|>
lengths = [len(s) for s in strs]
nstrs = len(strs)
encoded = str(nstrs) + '|' + '|'.join([str(l) for l in lengths]) + '|'
encoded += ''.join(strs)
return encoded
<|end_body_0|>
<|body_start_1|>
i, j = (0, 0)
while s[j] != '|':
j += 1
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
lengths =... | stack_v2_sparse_classes_36k_train_031689 | 995 | no_license | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | 78ed11f34fd03e9a188c9c6cb352e883016d05d9 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
lengths = [len(s) for s in strs]
nstrs = len(strs)
encoded = str(nstrs) + '|' + '|'.join([str(l) for l in lengths]) + '|'
encoded += ''.join(strs)
return encoded
... | the_stack_v2_python_sparse | 271_Encode_and_Decode_Strings.py | 26XINXIN/leetcode | train | 0 | |
09d3a4dd719a692522aa0b105199cf0e5108e1bf | [
"count0 = 0\ncount1 = 0\ncount2 = 0\nfor i in nums:\n if i == 0:\n count0 += 1\n if i == 1:\n count1 += 1\n if i == 2:\n count2 += 1\nnums[0:count0] = [0 for _ in range(count0)]\nnums[count0:count0 + count1] = [1 for _ in range(count1)]\nnums[count0 + count1:count0 + count1 + count2] =... | <|body_start_0|>
count0 = 0
count1 = 0
count2 = 0
for i in nums:
if i == 0:
count0 += 1
if i == 1:
count1 += 1
if i == 2:
count2 += 1
nums[0:count0] = [0 for _ in range(count0)]
nums[count... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortColors(self, nums) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_031690 | 1,211 | no_license | [
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "sortColors",
"signature": "def sortColors(self, nums) -> None"
},
{
"docstring": "Do not return anything, modify nums in-place instead.",
"name": "sortColors2",
"signature": "def sortColors2(self, nums) -> N... | 2 | stack_v2_sparse_classes_30k_train_020665 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums) -> None: Do not return anything, modify nums in-place instead.
- def sortColors2(self, nums) -> None: Do not return anything, modify nums in-place inst... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums) -> None: Do not return anything, modify nums in-place instead.
- def sortColors2(self, nums) -> None: Do not return anything, modify nums in-place inst... | 39d765c4580fcb0d411c485213232bb404447f11 | <|skeleton|>
class Solution:
def sortColors(self, nums) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_0|>
def sortColors2(self, nums) -> None:
"""Do not return anything, modify nums in-place instead."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortColors(self, nums) -> None:
"""Do not return anything, modify nums in-place instead."""
count0 = 0
count1 = 0
count2 = 0
for i in nums:
if i == 0:
count0 += 1
if i == 1:
count1 += 1
if... | the_stack_v2_python_sparse | num75.py | wuchenxi118/lc | train | 0 | |
c8f08f4e6f6571f8ee62ee8afd601ed7ebd2e0cb | [
"def neighbors(i, j):\n if i > 0:\n yield (i - 1, j)\n if j > 0:\n yield (i, j - 1)\n if i < len(matrix) - 1:\n yield (i + 1, j)\n if j < len(matrix[0]) - 1:\n yield (i, j + 1)\nmemo = [[0] * len(matrix[0]) for _ in matrix]\n\ndef dfs(i, j):\n if memo[i][j] != 0:\n ... | <|body_start_0|>
def neighbors(i, j):
if i > 0:
yield (i - 1, j)
if j > 0:
yield (i, j - 1)
if i < len(matrix) - 1:
yield (i + 1, j)
if j < len(matrix[0]) - 1:
yield (i, j + 1)
memo = [[0] * l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""10/01/2020 19:52"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""04/29/2021 10:00 DFS from each cell leveraging cache Time complexity: O(m*n) Space complex... | stack_v2_sparse_classes_36k_train_031691 | 4,753 | no_license | [
{
"docstring": "10/01/2020 19:52",
"name": "longestIncreasingPath",
"signature": "def longestIncreasingPath(self, matrix: List[List[int]]) -> int"
},
{
"docstring": "04/29/2021 10:00 DFS from each cell leveraging cache Time complexity: O(m*n) Space complexity: O(m*n)",
"name": "longestIncrea... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: 10/01/2020 19:52
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: 04/29/2021 10:00 DFS from eac... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: 10/01/2020 19:52
- def longestIncreasingPath(self, matrix: List[List[int]]) -> int: 04/29/2021 10:00 DFS from eac... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""10/01/2020 19:52"""
<|body_0|>
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""04/29/2021 10:00 DFS from each cell leveraging cache Time complexity: O(m*n) Space complex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestIncreasingPath(self, matrix: List[List[int]]) -> int:
"""10/01/2020 19:52"""
def neighbors(i, j):
if i > 0:
yield (i - 1, j)
if j > 0:
yield (i, j - 1)
if i < len(matrix) - 1:
yield (i + 1,... | the_stack_v2_python_sparse | leetcode/solved/329_Longest_Increasing_Path_in_a_Matrix/solution.py | sungminoh/algorithms | train | 0 | |
2f6fc69f1cf0df52636e94f11100818f7ff3d96c | [
"filetypes = (('text files', '*.txt'), ('pcd files', '*.pcd'), ('ply files', '*.ply'), ('All files', '*.*'))\nselectedFile = filedialog.askopenfilename(title='Open a file', initialdir='.', filetypes=filetypes)\nif selectedFile == None or selectedFile == () or selectedFile == '':\n return\nself.selectedFile = sel... | <|body_start_0|>
filetypes = (('text files', '*.txt'), ('pcd files', '*.pcd'), ('ply files', '*.ply'), ('All files', '*.*'))
selectedFile = filedialog.askopenfilename(title='Open a file', initialdir='.', filetypes=filetypes)
if selectedFile == None or selectedFile == () or selectedFile == '':
... | :Description: window to allow the user to select a file from their filesystem along with its exact format | FileSelect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSelect:
""":Description: window to allow the user to select a file from their filesystem along with its exact format"""
def select_file(self):
""":Description: prompt the user to select a file from their filesystem"""
<|body_0|>
def runCloseFunction(self):
""... | stack_v2_sparse_classes_36k_train_031692 | 3,573 | no_license | [
{
"docstring": ":Description: prompt the user to select a file from their filesystem",
"name": "select_file",
"signature": "def select_file(self)"
},
{
"docstring": ":Description: run the specified callback function when the window is closed",
"name": "runCloseFunction",
"signature": "de... | 3 | stack_v2_sparse_classes_30k_train_016912 | Implement the Python class `FileSelect` described below.
Class description:
:Description: window to allow the user to select a file from their filesystem along with its exact format
Method signatures and docstrings:
- def select_file(self): :Description: prompt the user to select a file from their filesystem
- def ru... | Implement the Python class `FileSelect` described below.
Class description:
:Description: window to allow the user to select a file from their filesystem along with its exact format
Method signatures and docstrings:
- def select_file(self): :Description: prompt the user to select a file from their filesystem
- def ru... | 8dda8fc474f3af1fe7ed611c801a541b1723b985 | <|skeleton|>
class FileSelect:
""":Description: window to allow the user to select a file from their filesystem along with its exact format"""
def select_file(self):
""":Description: prompt the user to select a file from their filesystem"""
<|body_0|>
def runCloseFunction(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileSelect:
""":Description: window to allow the user to select a file from their filesystem along with its exact format"""
def select_file(self):
""":Description: prompt the user to select a file from their filesystem"""
filetypes = (('text files', '*.txt'), ('pcd files', '*.pcd'), ('ply... | the_stack_v2_python_sparse | src/GUI/file_select.py | nchaconbgeo/pointcloudpackage | train | 1 |
ba47d5cff5803b1ab354517493b6c1d14210dc85 | [
"self._cache_whitelist = set(benchmark_setup['cache_whitelist'])\nself._original_requests = set(cache_validation_result['effective_encoded_data_lengths'].keys())\nself._original_post_requests = set(cache_validation_result['effective_post_requests'])\nself._original_cached_requests = self._original_requests.intersec... | <|body_start_0|>
self._cache_whitelist = set(benchmark_setup['cache_whitelist'])
self._original_requests = set(cache_validation_result['effective_encoded_data_lengths'].keys())
self._original_post_requests = set(cache_validation_result['effective_post_requests'])
self._original_cached_re... | Object to verify benchmark run from traces and WPR log stored in the runner output directory. | _RunOutputVerifier | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"LicenseRef-scancode-unknown-license-reference",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-unknown",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSO... | stack_v2_sparse_classes_36k_train_031693 | 28,927 | permissive | [
{
"docstring": "Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSON of the benchmark setup.",
"name": "__init__",
"signature": "def __init__(self, cache_validation_result, benchmark_setup)"
},
{
"docstring": "Verifies a trace with the cache valida... | 3 | stack_v2_sparse_classes_30k_train_012694 | Implement the Python class `_RunOutputVerifier` described below.
Class description:
Object to verify benchmark run from traces and WPR log stored in the runner output directory.
Method signatures and docstrings:
- def __init__(self, cache_validation_result, benchmark_setup): Constructor. Args: cache_validation_result... | Implement the Python class `_RunOutputVerifier` described below.
Class description:
Object to verify benchmark run from traces and WPR log stored in the runner output directory.
Method signatures and docstrings:
- def __init__(self, cache_validation_result, benchmark_setup): Constructor. Args: cache_validation_result... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSO... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _RunOutputVerifier:
"""Object to verify benchmark run from traces and WPR log stored in the runner output directory."""
def __init__(self, cache_validation_result, benchmark_setup):
"""Constructor. Args: cache_validation_result: JSON of the cache validation task. benchmark_setup: JSON of the benc... | the_stack_v2_python_sparse | tools/android/loading/sandwich_prefetch.py | metux/chromium-suckless | train | 5 |
b788c401a0d172e09009ea433b224665ee1c62da | [
"super().__init__(device=device, env=env, tx_conn=tx_conn, topics_to_subs=topics_to_subs)\nself.done = False\nself.stop_queue = stop_queue\nself.received_event = False",
"ev = DummyServiceEvent(self.env, 'aa:aa:aa:aa:aa:aa', 'dummy_value')\nyield self.async_wait_for_event(ev)\nself.received_event = True\nself.sto... | <|body_start_0|>
super().__init__(device=device, env=env, tx_conn=tx_conn, topics_to_subs=topics_to_subs)
self.done = False
self.stop_queue = stop_queue
self.received_event = False
<|end_body_0|>
<|body_start_1|>
ev = DummyServiceEvent(self.env, 'aa:aa:aa:aa:aa:aa', 'dummy_value... | WaiterService | [
"Apache-2.0",
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"GPL-2.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) us... | stack_v2_sparse_classes_36k_train_031694 | 4,078 | permissive | [
{
"docstring": "Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) used to send packets.",
"name": "__init__",
"signature": "def __init__(self, device, env, ... | 2 | stack_v2_sparse_classes_30k_train_018274 | Implement the Python class `WaiterService` described below.
Class description:
Implement the WaiterService class.
Method signatures and docstrings:
- def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue): Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice ... | Implement the Python class `WaiterService` described below.
Class description:
Implement the WaiterService class.
Method signatures and docstrings:
- def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue): Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice ... | 3a6d63af1ff468f94887a091e3a408a8449cf832 | <|skeleton|>
class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) us... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WaiterService:
def __init__(self, device, env, tx_conn, topics_to_subs, stop_queue):
"""Instanciate a Dummy WirelessService that waits for Events to happen. Args: device: WirelessDevice that owns the service env: simpy environment tx_conn: Connection (e.g. pipe end with 'send' method) used to send pac... | the_stack_v2_python_sparse | scripts/automation/trex_control_plane/interactive/trex/wireless/services/unit_tests/wireless_service_event_test.py | elados93/trex-core | train | 1 | |
7a64897f4330d833ad9b04294c4e0fb4de834ad5 | [
"super(GibbsSamplingInference, self).__init__(model)\nself.traces = {}\nself._initial_values = initial_values\nself._samples = samples\nself._burn_in = burn_in\nself._callback = callback",
"if self._initial_values:\n self.traces = {variable: [initial_value] for variable, initial_value in self._initial_values.i... | <|body_start_0|>
super(GibbsSamplingInference, self).__init__(model)
self.traces = {}
self._initial_values = initial_values
self._samples = samples
self._burn_in = burn_in
self._callback = callback
<|end_body_0|>
<|body_start_1|>
if self._initial_values:
... | An inference object to calibrate the potentials. | GibbsSamplingInference | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GibbsSamplingInference:
"""An inference object to calibrate the potentials."""
def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None):
"""Constructor. :param model: The model."""
<|body_0|>
def _calibrate(self, evidence):
"""Cali... | stack_v2_sparse_classes_36k_train_031695 | 3,924 | permissive | [
{
"docstring": "Constructor. :param model: The model.",
"name": "__init__",
"signature": "def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None)"
},
{
"docstring": "Calibrate all the factors in the model.",
"name": "_calibrate",
"signature": "def _calibr... | 3 | stack_v2_sparse_classes_30k_train_001286 | Implement the Python class `GibbsSamplingInference` described below.
Class description:
An inference object to calibrate the potentials.
Method signatures and docstrings:
- def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None): Constructor. :param model: The model.
- def _calibrate(... | Implement the Python class `GibbsSamplingInference` described below.
Class description:
An inference object to calibrate the potentials.
Method signatures and docstrings:
- def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None): Constructor. :param model: The model.
- def _calibrate(... | 445b2cf8736a4a28cff2b074a32afe8fe6986d53 | <|skeleton|>
class GibbsSamplingInference:
"""An inference object to calibrate the potentials."""
def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None):
"""Constructor. :param model: The model."""
<|body_0|>
def _calibrate(self, evidence):
"""Cali... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GibbsSamplingInference:
"""An inference object to calibrate the potentials."""
def __init__(self, model, initial_values=None, samples=1000, burn_in=100, callback=None):
"""Constructor. :param model: The model."""
super(GibbsSamplingInference, self).__init__(model)
self.traces = {}... | the_stack_v2_python_sparse | Statistical_methods/LoopyBeliefPropagation/pyugm/infer_sampling.py | WN1695173791/Background-Subtraction-Unsupervised-Learning | train | 1 |
e00d6c369bcfcecdd10a257d4e9da71a74ec6b10 | [
"self.predictions = class_counts(data, classCol)\nkeys = self.predictions.keys()\nls = []\nfor key in keys:\n ls.append([key, self.predictions[key]])\nls.sort(key=lambda x: x[1], reverse=True)\nself.mostLikely = ls[0][0]",
"keys = self.predictions.keys()\nvalues = self.predictions.values()\ntotal = sum(values)... | <|body_start_0|>
self.predictions = class_counts(data, classCol)
keys = self.predictions.keys()
ls = []
for key in keys:
ls.append([key, self.predictions[key]])
ls.sort(key=lambda x: x[1], reverse=True)
self.mostLikely = ls[0][0]
<|end_body_0|>
<|body_start_1... | A leaf of a decision tree aka the very bottom node. | Leaf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Leaf:
"""A leaf of a decision tree aka the very bottom node."""
def __init__(self, data, classCol):
"""The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class is on"""
<|body_0|>
def getAllChances(self)... | stack_v2_sparse_classes_36k_train_031696 | 15,954 | no_license | [
{
"docstring": "The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class is on",
"name": "__init__",
"signature": "def __init__(self, data, classCol)"
},
{
"docstring": "Gets the chances for each class to be in the leaf.",
"... | 2 | stack_v2_sparse_classes_30k_test_001196 | Implement the Python class `Leaf` described below.
Class description:
A leaf of a decision tree aka the very bottom node.
Method signatures and docstrings:
- def __init__(self, data, classCol): The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class... | Implement the Python class `Leaf` described below.
Class description:
A leaf of a decision tree aka the very bottom node.
Method signatures and docstrings:
- def __init__(self, data, classCol): The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class... | 0022c0bee14cdc3a773c0fe60d196cb12a0dd9f0 | <|skeleton|>
class Leaf:
"""A leaf of a decision tree aka the very bottom node."""
def __init__(self, data, classCol):
"""The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class is on"""
<|body_0|>
def getAllChances(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Leaf:
"""A leaf of a decision tree aka the very bottom node."""
def __init__(self, data, classCol):
"""The constructor for a leaf object Key word arguments: data: self explanatory classCol: The index for each rpw that the class is on"""
self.predictions = class_counts(data, classCol)
... | the_stack_v2_python_sparse | random forest tree/InsuranceClaimPrediction.py | ShaaficiAli/PersonalProjects | train | 0 |
2d9b0e4ac0596a74cd5b7d4f4f3be33a071d72ad | [
"fieldsets = super().get_fieldsets(request, obj)\nfieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)\nreturn fieldsets",
"readonly_fields = super().get_readonly_fields(request, obj)\nreadonly_fields = readonly_fields + ('created', 'modified')\nif not self.create_only_fields or not obj:\n re... | <|body_start_0|>
fieldsets = super().get_fieldsets(request, obj)
fieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)
return fieldsets
<|end_body_0|>
<|body_start_1|>
readonly_fields = super().get_readonly_fields(request, obj)
readonly_fields = readonly_fields ... | Base admin representation. | BaseAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Add created and modified to readonly_fields. Also if create_only_f... | stack_v2_sparse_classes_36k_train_031697 | 1,885 | no_license | [
{
"docstring": "Add created and modified to fieldsets.",
"name": "get_fieldsets",
"signature": "def get_fieldsets(self, request, obj=None)"
},
{
"docstring": "Add created and modified to readonly_fields. Also if create_only_fields were specified add them to readonly_fields, if user is working on... | 2 | stack_v2_sparse_classes_30k_train_012963 | Implement the Python class `BaseAdmin` described below.
Class description:
Base admin representation.
Method signatures and docstrings:
- def get_fieldsets(self, request, obj=None): Add created and modified to fieldsets.
- def get_readonly_fields(self, request, obj=None): Add created and modified to readonly_fields. ... | Implement the Python class `BaseAdmin` described below.
Class description:
Base admin representation.
Method signatures and docstrings:
- def get_fieldsets(self, request, obj=None): Add created and modified to fieldsets.
- def get_readonly_fields(self, request, obj=None): Add created and modified to readonly_fields. ... | 0879ade24685b628624dce06698f8a0afd042000 | <|skeleton|>
class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
<|body_0|>
def get_readonly_fields(self, request, obj=None):
"""Add created and modified to readonly_fields. Also if create_only_f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseAdmin:
"""Base admin representation."""
def get_fieldsets(self, request, obj=None):
"""Add created and modified to fieldsets."""
fieldsets = super().get_fieldsets(request, obj)
fieldsets += ((_('Extra info'), {'fields': ['created', 'modified']}),)
return fieldsets
... | the_stack_v2_python_sparse | project_template/apps/core/admin.py | rhanmar/oi_projects_summer_2021 | train | 0 |
8c543d33c6500bdd96f6404b8fd23c2a8caf78dc | [
"self.lowest_new_price = lowest_new_price\nself.lowest_used_price = lowest_used_price\nself.lowest_collectible_price = lowest_collectible_price\nself.lowest_refurbished_price = lowest_refurbished_price\nself.total_new = total_new\nself.total_used = total_used\nself.total_collectible = total_collectible\nself.total_... | <|body_start_0|>
self.lowest_new_price = lowest_new_price
self.lowest_used_price = lowest_used_price
self.lowest_collectible_price = lowest_collectible_price
self.lowest_refurbished_price = lowest_refurbished_price
self.total_new = total_new
self.total_used = total_used
... | Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO: type description here. lowest_refurbished_price (Price): TODO: type descriptio... | OfferSummary | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfferSummary:
"""Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO: type description here. lowest_refurbis... | stack_v2_sparse_classes_36k_train_031698 | 4,010 | permissive | [
{
"docstring": "Constructor for the OfferSummary class",
"name": "__init__",
"signature": "def __init__(self, lowest_new_price=None, lowest_used_price=None, lowest_collectible_price=None, lowest_refurbished_price=None, total_new=None, total_used=None, total_collectible=None, total_refurbished=None)"
}... | 2 | stack_v2_sparse_classes_30k_train_017624 | Implement the Python class `OfferSummary` described below.
Class description:
Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO:... | Implement the Python class `OfferSummary` described below.
Class description:
Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO:... | 26ea1019115a1de3b1b37a4b830525e164ac55ce | <|skeleton|>
class OfferSummary:
"""Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO: type description here. lowest_refurbis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfferSummary:
"""Implementation of the 'OfferSummary' model. TODO: type model description here. Attributes: lowest_new_price (Price): TODO: type description here. lowest_used_price (Price): TODO: type description here. lowest_collectible_price (Price): TODO: type description here. lowest_refurbished_price (Pr... | the_stack_v2_python_sparse | awsecommerceservice/models/offer_summary.py | nidaizamir/Test-PY | train | 0 |
801a861f2d8fab540fb6225be46064eb4f81564a | [
"self.driver.get(detail_url)\nsleep(2)\nself.driver.execute_script('window.scrollTo(0, 1300)')\nreport_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text\ntt_check.assertEqual('检测报告', report_title, '检测报告tab的title，期望是检测报告，实际是%s' % report_title)",
"self.driver.get(detail_url)\nsleep(2)\nself.driv... | <|body_start_0|>
self.driver.get(detail_url)
sleep(2)
self.driver.execute_script('window.scrollTo(0, 1300)')
report_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text
tt_check.assertEqual('检测报告', report_title, '检测报告tab的title，期望是检测报告，实际是%s' % report_title)
<|end... | Report | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
<|body_0|>
def test_report_type(self):
"""测试检测报告各类型显示的是否正确@author:zhangyanli"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver.get(detail_url)
sleep(2)... | stack_v2_sparse_classes_36k_train_031699 | 1,735 | no_license | [
{
"docstring": "测试检测报告title显示的是否正确@author:zhangyanli",
"name": "test_report_title",
"signature": "def test_report_title(self)"
},
{
"docstring": "测试检测报告各类型显示的是否正确@author:zhangyanli",
"name": "test_report_type",
"signature": "def test_report_type(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016996 | Implement the Python class `Report` described below.
Class description:
Implement the Report class.
Method signatures and docstrings:
- def test_report_title(self): 测试检测报告title显示的是否正确@author:zhangyanli
- def test_report_type(self): 测试检测报告各类型显示的是否正确@author:zhangyanli | Implement the Python class `Report` described below.
Class description:
Implement the Report class.
Method signatures and docstrings:
- def test_report_title(self): 测试检测报告title显示的是否正确@author:zhangyanli
- def test_report_type(self): 测试检测报告各类型显示的是否正确@author:zhangyanli
<|skeleton|>
class Report:
def test_report_ti... | a73e4ed1dc02f05e93f11788591efe68109fd277 | <|skeleton|>
class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
<|body_0|>
def test_report_type(self):
"""测试检测报告各类型显示的是否正确@author:zhangyanli"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Report:
def test_report_title(self):
"""测试检测报告title显示的是否正确@author:zhangyanli"""
self.driver.get(detail_url)
sleep(2)
self.driver.execute_script('window.scrollTo(0, 1300)')
report_title = self.driver.find_element(CarDetail_Locator.REPORT_TITLE).text
tt_check.asse... | the_stack_v2_python_sparse | taocheM/test_detail/test_carreport.py | zhangyanli616/TaoCheAuto | train | 0 |
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