blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ea91e84824249c3a79c9289202c100aa87b2880d | [
"twython.TwythonStreamer.__init__(self, app_key, app_secret, oauth_token, oauth_token_secret)\nself.response_queue = response_queue\nself.db_queue = db_queue\nself.filter_list = filter_list\nself.message_received = False\nreturn",
"message = ''\nuser_name = ''\nscreen_name = ''\nprint(data)\nif 'text' in data:\n ... | <|body_start_0|>
twython.TwythonStreamer.__init__(self, app_key, app_secret, oauth_token, oauth_token_secret)
self.response_queue = response_queue
self.db_queue = db_queue
self.filter_list = filter_list
self.message_received = False
return
<|end_body_0|>
<|body_start_1|>... | This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it. | TwitterStreamer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwitterStreamer:
"""This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it."""
def __init__(self, app_key=None, app_secret=None, oauth_token=None, oauth_token_secret=None, response_... | stack_v2_sparse_classes_75kplus_train_067400 | 4,693 | no_license | [
{
"docstring": "Create our instance of the TwythonStreamer",
"name": "__init__",
"signature": "def __init__(self, app_key=None, app_secret=None, oauth_token=None, oauth_token_secret=None, response_queue=None, filter_list=None, db_queue=None)"
},
{
"docstring": "Come here when we receive a tweet ... | 2 | stack_v2_sparse_classes_30k_train_004514 | Implement the Python class `TwitterStreamer` described below.
Class description:
This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it.
Method signatures and docstrings:
- def __init__(self, app_key=None, a... | Implement the Python class `TwitterStreamer` described below.
Class description:
This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it.
Method signatures and docstrings:
- def __init__(self, app_key=None, a... | 7d4a27126f7f2a93f7216b9ea4eed15789599bf3 | <|skeleton|>
class TwitterStreamer:
"""This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it."""
def __init__(self, app_key=None, app_secret=None, oauth_token=None, oauth_token_secret=None, response_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TwitterStreamer:
"""This class is an extension of the twython.TwythonStreamer. The on_success method is called when we get a message from our list of commands and we can then process it."""
def __init__(self, app_key=None, app_secret=None, oauth_token=None, oauth_token_secret=None, response_queue=None, f... | the_stack_v2_python_sparse | python3/RaspberryPi/twitter.py | ptracton/experimental | train | 4 |
e3c91798aacd8fc5db48d4aff2d559f3e1a10766 | [
"s = pattern\nt = str.split()\nreturn list(map(s.find, s)) == list(map(t.index, t))",
"s = pattern\nt = str.split()\nif len(s) != len(t):\n return False\nelse:\n return len(set(zip(s, t))) == len(set(s)) == len(set(t))"
] | <|body_start_0|>
s = pattern
t = str.split()
return list(map(s.find, s)) == list(map(t.index, t))
<|end_body_0|>
<|body_start_1|>
s = pattern
t = str.split()
if len(s) != len(t):
return False
else:
return len(set(zip(s, t))) == len(set(s))... | Solution1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def wordPattern1(self, pattern, str):
""":type pattern: str :type str: str :rtype: bool"""
<|body_0|>
def wordPattern(self, pattern, str):
""":type pattern: str :type str: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_75kplus_train_067401 | 1,385 | no_license | [
{
"docstring": ":type pattern: str :type str: str :rtype: bool",
"name": "wordPattern1",
"signature": "def wordPattern1(self, pattern, str)"
},
{
"docstring": ":type pattern: str :type str: str :rtype: bool",
"name": "wordPattern",
"signature": "def wordPattern(self, pattern, str)"
}
] | 2 | stack_v2_sparse_classes_30k_train_028399 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def wordPattern1(self, pattern, str): :type pattern: str :type str: str :rtype: bool
- def wordPattern(self, pattern, str): :type pattern: str :type str: str :rtype: bool | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def wordPattern1(self, pattern, str): :type pattern: str :type str: str :rtype: bool
- def wordPattern(self, pattern, str): :type pattern: str :type str: str :rtype: bool
<|sk... | 4a1747b6497305f3821612d9c358a6795b1690da | <|skeleton|>
class Solution1:
def wordPattern1(self, pattern, str):
""":type pattern: str :type str: str :rtype: bool"""
<|body_0|>
def wordPattern(self, pattern, str):
""":type pattern: str :type str: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution1:
def wordPattern1(self, pattern, str):
""":type pattern: str :type str: str :rtype: bool"""
s = pattern
t = str.split()
return list(map(s.find, s)) == list(map(t.index, t))
def wordPattern(self, pattern, str):
""":type pattern: str :type str: str :rtype: ... | the_stack_v2_python_sparse | String/q290_word_pattern.py | sevenhe716/LeetCode | train | 0 | |
8555721f123b1a72ec96c19a099efaed1920814f | [
"self.nstates = nstates\nself.beta = beta\nself.precision = precision\nself.two_stage = two_stage\nself.burnin = True\nself.time = 0\nself.burnin_length = None\nif zetas is None:\n self.zetas = np.zeros(self.nstates)\nelif len(zetas) != self.nstates:\n raise Exception('The length of the bias/estimate (zetas)... | <|body_start_0|>
self.nstates = nstates
self.beta = beta
self.precision = precision
self.two_stage = two_stage
self.burnin = True
self.time = 0
self.burnin_length = None
if zetas is None:
self.zetas = np.zeros(self.nstates)
elif len(zet... | Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling over states and configurations. [1] Z. Tan, "Optimally adjusted mixture sampling ... | SAMSAdaptor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SAMSAdaptor:
"""Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling over states and configurations. [1] Z. Tan... | stack_v2_sparse_classes_75kplus_train_067402 | 11,523 | permissive | [
{
"docstring": "Parameters ---------- nstates: int The number of free energies to infer zeta: numpy array The estimate of the free energy and the current state biasing potential target_weights: numpy array vector of the state probabilities that the sampler should converge to. two_stage: bool whether to perform ... | 3 | stack_v2_sparse_classes_30k_train_023322 | Implement the Python class `SAMSAdaptor` described below.
Class description:
Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling ove... | Implement the Python class `SAMSAdaptor` described below.
Class description:
Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling ove... | d30804beb158960a62f94182c694df6dd9130fb8 | <|skeleton|>
class SAMSAdaptor:
"""Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling over states and configurations. [1] Z. Tan... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SAMSAdaptor:
"""Implements the update scheme for self adjusted mixture sampling as described by Z. Tan in [1]. Can use either the Rao-Blackwellized or binary update schemes. To function, this class must be paired with a method to perform mixture sampling over states and configurations. [1] Z. Tan, "Optimally ... | the_stack_v2_python_sparse | saltswap/sams_adapter.py | Byun-jinyoung/saltswap | train | 0 |
76f32816b81a2645b48c5f143d13198f86ec11e7 | [
"try:\n return float(value)\nexcept ValueError:\n raise ValueError('Attempted to set value for an %s field which is not compatible: %s' % (self.typeName(), repr(value)))",
"if isinstance(value, float):\n return 1\nreturn 0"
] | <|body_start_0|>
try:
return float(value)
except ValueError:
raise ValueError('Attempted to set value for an %s field which is not compatible: %s' % (self.typeName(), repr(value)))
<|end_body_0|>
<|body_start_1|>
if isinstance(value, float):
return 1
... | SFFloat field/event type base-class | _SFFloat | [
"GPL-1.0-or-later",
"MIT",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-other-copyleft",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LGPL-2.0-or-later",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _SFFloat:
"""SFFloat field/event type base-class"""
def coerce(self, value):
"""Coerce the given value to our type Allowable types: any object with true/false protocol"""
<|body_0|>
def check(self, value):
"""Check that value is of precisely the expected data typ... | stack_v2_sparse_classes_75kplus_train_067403 | 34,853 | permissive | [
{
"docstring": "Coerce the given value to our type Allowable types: any object with true/false protocol",
"name": "coerce",
"signature": "def coerce(self, value)"
},
{
"docstring": "Check that value is of precisely the expected data type",
"name": "check",
"signature": "def check(self, v... | 2 | stack_v2_sparse_classes_30k_train_046935 | Implement the Python class `_SFFloat` described below.
Class description:
SFFloat field/event type base-class
Method signatures and docstrings:
- def coerce(self, value): Coerce the given value to our type Allowable types: any object with true/false protocol
- def check(self, value): Check that value is of precisely ... | Implement the Python class `_SFFloat` described below.
Class description:
SFFloat field/event type base-class
Method signatures and docstrings:
- def coerce(self, value): Coerce the given value to our type Allowable types: any object with true/false protocol
- def check(self, value): Check that value is of precisely ... | 7f600ad153270feff12aa7aa86d7ed0a49ebc71c | <|skeleton|>
class _SFFloat:
"""SFFloat field/event type base-class"""
def coerce(self, value):
"""Coerce the given value to our type Allowable types: any object with true/false protocol"""
<|body_0|>
def check(self, value):
"""Check that value is of precisely the expected data typ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _SFFloat:
"""SFFloat field/event type base-class"""
def coerce(self, value):
"""Coerce the given value to our type Allowable types: any object with true/false protocol"""
try:
return float(value)
except ValueError:
raise ValueError('Attempted to set value f... | the_stack_v2_python_sparse | pythonAnimations/pyOpenGLChess/engineDirectory/oglc-env/lib/python2.7/site-packages/vrml/fieldtypes.py | alexus37/AugmentedRealityChess | train | 1 |
74605ab539252f68c06bc37e7f59ff8c898113a1 | [
"test_keys = ['o.c.test.Test', 'o.c.testing.Test', 'o.c.test.Wrong']\nvalid_keys = print_dependencies_helper.get_valid_keys_matching_input(test_keys, 'test')\nself.assertEqual(valid_keys, sorted(['o.c.test.Test', 'o.c.testing.Test']))",
"test_keys = ['o.c.test.Test', 'o.c.testing.Test', 'o.c.test.Wrong']\nvalid_k... | <|body_start_0|>
test_keys = ['o.c.test.Test', 'o.c.testing.Test', 'o.c.test.Wrong']
valid_keys = print_dependencies_helper.get_valid_keys_matching_input(test_keys, 'test')
self.assertEqual(valid_keys, sorted(['o.c.test.Test', 'o.c.testing.Test']))
<|end_body_0|>
<|body_start_1|>
test_k... | Unit tests for the helper functions in the module. | TestHelperFunctions | [
"Zlib",
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.1-only",
"LGPL-2.0-or-later",
"APSL-2.0",
"MIT",
"Apache-2.0",
"LGPL-2.0-only",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestHelperFunctions:
"""Unit tests for the helper functions in the module."""
def test_get_valid_keys_matching_input(self):
"""Tests getting all valid keys for the given input."""
<|body_0|>
def test_get_valid_keys_matching_input_no_match(self):
"""Tests getting ... | stack_v2_sparse_classes_75kplus_train_067404 | 1,183 | permissive | [
{
"docstring": "Tests getting all valid keys for the given input.",
"name": "test_get_valid_keys_matching_input",
"signature": "def test_get_valid_keys_matching_input(self)"
},
{
"docstring": "Tests getting all valid keys when there is no matching key.",
"name": "test_get_valid_keys_matching... | 2 | stack_v2_sparse_classes_30k_val_002993 | Implement the Python class `TestHelperFunctions` described below.
Class description:
Unit tests for the helper functions in the module.
Method signatures and docstrings:
- def test_get_valid_keys_matching_input(self): Tests getting all valid keys for the given input.
- def test_get_valid_keys_matching_input_no_match(... | Implement the Python class `TestHelperFunctions` described below.
Class description:
Unit tests for the helper functions in the module.
Method signatures and docstrings:
- def test_get_valid_keys_matching_input(self): Tests getting all valid keys for the given input.
- def test_get_valid_keys_matching_input_no_match(... | 64bee65c921db7e78e25d08f1e98da2668b57be5 | <|skeleton|>
class TestHelperFunctions:
"""Unit tests for the helper functions in the module."""
def test_get_valid_keys_matching_input(self):
"""Tests getting all valid keys for the given input."""
<|body_0|>
def test_get_valid_keys_matching_input_no_match(self):
"""Tests getting ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestHelperFunctions:
"""Unit tests for the helper functions in the module."""
def test_get_valid_keys_matching_input(self):
"""Tests getting all valid keys for the given input."""
test_keys = ['o.c.test.Test', 'o.c.testing.Test', 'o.c.test.Wrong']
valid_keys = print_dependencies_h... | the_stack_v2_python_sparse | tools/android/dependency_analysis/print_dependencies_helper_unittest.py | otcshare/chromium-src | train | 18 |
65faf6d1b9d2b7c2c348ad115c20fc840e0dcd4c | [
"if isinstance(key, int):\n return ESPTransformSuite(key)\nif key not in ESPTransformSuite._member_map_:\n return extend_enum(ESPTransformSuite, key, default)\nreturn ESPTransformSuite[key]",
"if not (isinstance(value, int) and 0 <= value <= 65535):\n raise ValueError('%r is not a valid %s' % (value, cls... | <|body_start_0|>
if isinstance(key, int):
return ESPTransformSuite(key)
if key not in ESPTransformSuite._member_map_:
return extend_enum(ESPTransformSuite, key, default)
return ESPTransformSuite[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) ... | [ESPTransformSuite] ESP Transform Suite IDs | ESPTransformSuite | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>... | stack_v2_sparse_classes_75kplus_train_067405 | 2,727 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite'"
},
{
"docstring": "Lookup function used when value is not ... | 2 | stack_v2_sparse_classes_30k_train_020119 | Implement the Python class `ESPTransformSuite` described below.
Class description:
[ESPTransformSuite] ESP Transform Suite IDs
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite': Backport support for original codes. Args: key: Key to get enum item. default: Default... | Implement the Python class `ESPTransformSuite` described below.
Class description:
[ESPTransformSuite] ESP Transform Suite IDs
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite': Backport support for original codes. Args: key: Key to get enum item. default: Default... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int)... | the_stack_v2_python_sparse | pcapkit/const/hip/esp_transform_suite.py | JarryShaw/PyPCAPKit | train | 204 |
a4f2fbee19340abc9dcda81ed3aaf0b6a8b7c920 | [
"self.FILEPATH = filename\nself.DATETIME_OBJ = None\nself.LANDSAT_SCENE_ID = None\nself.DATA_TYPE = None\nself.ELEVATION_SOURCE = None\nself.OUTPUT_FORMAT = None\nself.SPACECRAFT_ID = None\nself.SENSOR_ID = None\nself.WRS_PATH = None\nself.WRS_ROW = None\nself.NADIR_OFFNADIR = None\nself.TARGET_WRS_PATH = None\nsel... | <|body_start_0|>
self.FILEPATH = filename
self.DATETIME_OBJ = None
self.LANDSAT_SCENE_ID = None
self.DATA_TYPE = None
self.ELEVATION_SOURCE = None
self.OUTPUT_FORMAT = None
self.SPACECRAFT_ID = None
self.SENSOR_ID = None
self.WRS_PATH = None
... | A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata. You can access explore these attributes by using, for example .. code-block:: pyt... | landsat_metadata | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class landsat_metadata:
"""A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata. You can access explore these attribut... | stack_v2_sparse_classes_75kplus_train_067406 | 15,909 | permissive | [
{
"docstring": "There are several critical attributes that keep a common naming convention between all landsat versions, so they are initialized in this class for good record keeping and reference",
"name": "__init__",
"signature": "def __init__(self, filename)"
},
{
"docstring": "reads the cont... | 2 | stack_v2_sparse_classes_30k_train_035815 | Implement the Python class `landsat_metadata` described below.
Class description:
A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata... | Implement the Python class `landsat_metadata` described below.
Class description:
A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata... | 052ed7cf313be8418c4429ab31600d778c552de0 | <|skeleton|>
class landsat_metadata:
"""A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata. You can access explore these attribut... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class landsat_metadata:
"""A landsat metadata object. This class builds is attributes from the names of each tag in the xml formatted .MTL files that come with landsat data. So, any tag that appears in the MTL file will populate as an attribute of landsat_metadata. You can access explore these attributes by using, ... | the_stack_v2_python_sparse | pydisalexi/landsatTools.py | bucricket/projectMAS | train | 3 |
c4814eb6d8881635d582095fd5a545edccf7c6cf | [
"self.Factors = dict()\nself.Rank = Rank\nself.Dimensions = len(Size)\nself.Size = Size\nself.Type = 'ktensor'\nself.Weights = np.ones(Rank)\nif Minit == 'random':\n np.random.seed(random_state)\n for d in range(self.Dimensions):\n self.Factors[str(d)] = np.random.uniform(low=0, high=1, size=(Size[d], ... | <|body_start_0|>
self.Factors = dict()
self.Rank = Rank
self.Dimensions = len(Size)
self.Size = Size
self.Type = 'ktensor'
self.Weights = np.ones(Rank)
if Minit == 'random':
np.random.seed(random_state)
for d in range(self.Dimensions):
... | K_TENSOR | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class K_TENSOR:
def __init__(self, Rank, Size, Minit='random', random_state=42, order=-1):
"""Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by default, creates M from uniform distribution. Parameters ---------- Rank : int Tensor rank, i.e. nu... | stack_v2_sparse_classes_75kplus_train_067407 | 3,574 | permissive | [
{
"docstring": "Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by default, creates M from uniform distribution. Parameters ---------- Rank : int Tensor rank, i.e. number of components in M. Size : list Shape of the tensor. Minit : string or dictionary of latent... | 2 | stack_v2_sparse_classes_30k_train_001469 | Implement the Python class `K_TENSOR` described below.
Class description:
Implement the K_TENSOR class.
Method signatures and docstrings:
- def __init__(self, Rank, Size, Minit='random', random_state=42, order=-1): Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by de... | Implement the Python class `K_TENSOR` described below.
Class description:
Implement the K_TENSOR class.
Method signatures and docstrings:
- def __init__(self, Rank, Size, Minit='random', random_state=42, order=-1): Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by de... | bdaed6e820e1ded21836d904f9012fb921e27e6a | <|skeleton|>
class K_TENSOR:
def __init__(self, Rank, Size, Minit='random', random_state=42, order=-1):
"""Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by default, creates M from uniform distribution. Parameters ---------- Rank : int Tensor rank, i.e. nu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class K_TENSOR:
def __init__(self, Rank, Size, Minit='random', random_state=42, order=-1):
"""Initilize the K_TENSOR class. Creates the object representation of M. If initial M is not passed, by default, creates M from uniform distribution. Parameters ---------- Rank : int Tensor rank, i.e. number of compon... | the_stack_v2_python_sparse | pyCP_APR/numpy_backend/ktensor.py | lanl/pyCP_APR | train | 9 | |
e948749d11cba7758f6fd7c2a2b5a1353b94b31d | [
"buffer = []\n\ndef _serialize(node: 'TreeNode') -> None:\n if node is None:\n return\n buffer.append(str(node.val))\n _serialize(node.left)\n _serialize(node.right)\n_serialize(root)\nreturn ','.join(buffer)",
"if len(data) == 0:\n return None\nbuffer = list(map(int, data.split(',')))\n\nde... | <|body_start_0|>
buffer = []
def _serialize(node: 'TreeNode') -> None:
if node is None:
return
buffer.append(str(node.val))
_serialize(node.left)
_serialize(node.right)
_serialize(root)
return ','.join(buffer)
<|end_body_0|... | 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|>
buffer = []
... | stack_v2_sparse_classes_75kplus_train_067408 | 1,683 | 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_train_010169 | 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... | f35305c618b383a79d05074d891cf0f7acabd88f | <|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_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
buffer = []
def _serialize(node: 'TreeNode') -> None:
if node is None:
return
buffer.append(str(node.val))
_serialize(node.left)
... | the_stack_v2_python_sparse | p449m/codec.py | l33tdaima/l33tdaima | train | 1 | |
dc92843aa5e5d967194dd284517e082eb1df4776 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Onenote()",
"from .entity import Entity\nfrom .notebook import Notebook\nfrom .onenote_operation import OnenoteOperation\nfrom .onenote_page import OnenotePage\nfrom .onenote_resource import OnenoteResource\nfrom .onenote_section impor... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Onenote()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .notebook import Notebook
from .onenote_operation import OnenoteOperation
from .onenote_page imp... | Onenote | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""... | stack_v2_sparse_classes_75kplus_train_067409 | 4,865 | 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: Onenote",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse... | 3 | stack_v2_sparse_classes_30k_train_022079 | Implement the Python class `Onenote` described below.
Class description:
Implement the Onenote class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | Implement the Python class `Onenote` described below.
Class description:
Implement the Onenote class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote: Creates a new instance of the appropriate class based on discriminator value Args: parse_node:... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Onenote:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Onenote:
"""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: Onenote"""
if no... | the_stack_v2_python_sparse | msgraph/generated/models/onenote.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
4ba4d94433caa510db0cf6f095714a45ac3148fc | [
"self.config = config\nself.executor = executor\nself.cacheobj = cacheobj\nself.pii_salt = self.config.piisalt\nself.nworkers = self.config.workers\nself.ratelimits = self.config.ratelimits",
"self.set_header('content-type', 'text/plain; charset=UTF-8')\nif status_code == 400:\n self.write(f'HTTP {status_code}... | <|body_start_0|>
self.config = config
self.executor = executor
self.cacheobj = cacheobj
self.pii_salt = self.config.piisalt
self.nworkers = self.config.workers
self.ratelimits = self.config.ratelimits
<|end_body_0|>
<|body_start_1|>
self.set_header('content-type'... | This handles health check endpoints. | HealthCheckHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HealthCheckHandler:
"""This handles health check endpoints."""
def initialize(self, config, executor, cacheobj):
"""This sets up some config."""
<|body_0|>
def write_error(self, status_code, **kwargs):
"""This writes the error as a response."""
<|body_1|>... | stack_v2_sparse_classes_75kplus_train_067410 | 4,066 | permissive | [
{
"docstring": "This sets up some config.",
"name": "initialize",
"signature": "def initialize(self, config, executor, cacheobj)"
},
{
"docstring": "This writes the error as a response.",
"name": "write_error",
"signature": "def write_error(self, status_code, **kwargs)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_train_051229 | Implement the Python class `HealthCheckHandler` described below.
Class description:
This handles health check endpoints.
Method signatures and docstrings:
- def initialize(self, config, executor, cacheobj): This sets up some config.
- def write_error(self, status_code, **kwargs): This writes the error as a response.
... | Implement the Python class `HealthCheckHandler` described below.
Class description:
This handles health check endpoints.
Method signatures and docstrings:
- def initialize(self, config, executor, cacheobj): This sets up some config.
- def write_error(self, status_code, **kwargs): This writes the error as a response.
... | 9a038e3734bb8f66115384a1e0917042a4bc4681 | <|skeleton|>
class HealthCheckHandler:
"""This handles health check endpoints."""
def initialize(self, config, executor, cacheobj):
"""This sets up some config."""
<|body_0|>
def write_error(self, status_code, **kwargs):
"""This writes the error as a response."""
<|body_1|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HealthCheckHandler:
"""This handles health check endpoints."""
def initialize(self, config, executor, cacheobj):
"""This sets up some config."""
self.config = config
self.executor = executor
self.cacheobj = cacheobj
self.pii_salt = self.config.piisalt
self.... | the_stack_v2_python_sparse | authnzerver/healthcheck.py | waqasbhatti/authnzerver | train | 3 |
82201f83aae589b4cba33ac2b165d20d7a18f196 | [
"self.url = url\nself.make_soup()\nself.get_title()\nself.get_image()\nself.get_ingredients()\nself.get_contents()\nself.get_portions()",
"try:\n self.title = self.soup.find(class_='recipe-header__title').text.strip()\nexcept Exception:\n current_app.logger.error(f'Could not extract title: {traceback.format... | <|body_start_0|>
self.url = url
self.make_soup()
self.get_title()
self.get_image()
self.get_ingredients()
self.get_contents()
self.get_portions()
<|end_body_0|>
<|body_start_1|>
try:
self.title = self.soup.find(class_='recipe-header__title').t... | Parser for recipes at ica.se. | ICAParser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ICAParser:
"""Parser for recipes at ica.se."""
def __init__(self, url):
"""Init the parser."""
<|body_0|>
def get_title(self):
"""Get recipe title."""
<|body_1|>
def get_image(self):
"""Get recipe main image."""
<|body_2|>
def ge... | stack_v2_sparse_classes_75kplus_train_067411 | 3,852 | permissive | [
{
"docstring": "Init the parser.",
"name": "__init__",
"signature": "def __init__(self, url)"
},
{
"docstring": "Get recipe title.",
"name": "get_title",
"signature": "def get_title(self)"
},
{
"docstring": "Get recipe main image.",
"name": "get_image",
"signature": "def ... | 6 | stack_v2_sparse_classes_30k_train_016272 | Implement the Python class `ICAParser` described below.
Class description:
Parser for recipes at ica.se.
Method signatures and docstrings:
- def __init__(self, url): Init the parser.
- def get_title(self): Get recipe title.
- def get_image(self): Get recipe main image.
- def get_ingredients(self): Get recipe ingredie... | Implement the Python class `ICAParser` described below.
Class description:
Parser for recipes at ica.se.
Method signatures and docstrings:
- def __init__(self, url): Init the parser.
- def get_title(self): Get recipe title.
- def get_image(self): Get recipe main image.
- def get_ingredients(self): Get recipe ingredie... | df3ca44eeefb1c3c3f4c54272f63059be47990bf | <|skeleton|>
class ICAParser:
"""Parser for recipes at ica.se."""
def __init__(self, url):
"""Init the parser."""
<|body_0|>
def get_title(self):
"""Get recipe title."""
<|body_1|>
def get_image(self):
"""Get recipe main image."""
<|body_2|>
def ge... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ICAParser:
"""Parser for recipes at ica.se."""
def __init__(self, url):
"""Init the parser."""
self.url = url
self.make_soup()
self.get_title()
self.get_image()
self.get_ingredients()
self.get_contents()
self.get_portions()
def get_titl... | the_stack_v2_python_sparse | recapi/html_parsers/icaparser.py | anne17/recapi | train | 2 |
d371e24d9b9ab89426acb2f2c42d96cbfa19a97a | [
"self._flat_layer_suffix = '_flat'\nself.old_layer = old_layer\nself.new_layer = new_layer\nself.diff_attribs = diff_attribs\nself.focus_attribs = focus_attribs\nself.morph_diff_tagger = DiffTagger(layer_a=old_layer + self._flat_layer_suffix, layer_b=new_layer + self._flat_layer_suffix, output_layer='morph_diff_lay... | <|body_start_0|>
self._flat_layer_suffix = '_flat'
self.old_layer = old_layer
self.new_layer = new_layer
self.diff_attribs = diff_attribs
self.focus_attribs = focus_attribs
self.morph_diff_tagger = DiffTagger(layer_a=old_layer + self._flat_layer_suffix, layer_b=new_layer ... | Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping spans (missing and extra spans) will be lef... | MorphDiffFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping ... | stack_v2_sparse_classes_75kplus_train_067412 | 35,998 | no_license | [
{
"docstring": "Initializes MorphDiffFinder. A specification of comparable layers must be provided. :param old_layer: str Name of the old morph_analysis layer. :param new_layer: str Name of the new morph_analysis layer. :param diff_attribs: list List containing morph_analysis attributes which will be used for f... | 2 | stack_v2_sparse_classes_30k_train_038554 | Implement the Python class `MorphDiffFinder` described below.
Class description:
Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified... | Implement the Python class `MorphDiffFinder` described below.
Class description:
Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified... | d0b498a08a938b204fc34c3ea5e3ee3eb57bb25d | <|skeleton|>
class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MorphDiffFinder:
"""Finds all differences between two (Vabamorf's) morphological analysis layers, and groups differences in modified spans in a way that both matching and mismatching annotations are shown. Note: output grouped differences only cover modified spans; annotations on non-overlapping spans (missin... | the_stack_v2_python_sparse | diff_morph_analysis/morph_eval_utils.py | estnltk/estnltk-workflows | train | 0 |
b6941a852d51fb4a92441a683ecbec3ce34e0ae2 | [
"if task_token is None:\n task_token = self.last_tasktoken\nreturn self._swf.respond_activity_task_canceled(task_token, details)",
"if task_token is None:\n task_token = self.last_tasktoken\nreturn self._swf.respond_activity_task_completed(task_token, result)",
"if task_token is None:\n task_token = se... | <|body_start_0|>
if task_token is None:
task_token = self.last_tasktoken
return self._swf.respond_activity_task_canceled(task_token, details)
<|end_body_0|>
<|body_start_1|>
if task_token is None:
task_token = self.last_tasktoken
return self._swf.respond_activity... | Base class for SimpleWorkflow activity workers. | ActivityWorker | [
"CC-BY-3.0",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-unknown-license-reference",
"ZPL-2.0",
"Unlicense",
"LGPL-3.0-only",
"CC0-1.0",
"LicenseRef-scancode-other-permissive",
"CNRI-Python",
"LicenseRef-scancode-warranty-disclaimer",
"GPL-2.0-or-later",
"Python-2.0",
"GPL-3.0... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityWorker:
"""Base class for SimpleWorkflow activity workers."""
def cancel(self, task_token=None, details=None):
"""RespondActivityTaskCanceled."""
<|body_0|>
def complete(self, task_token=None, result=None):
"""RespondActivityTaskCompleted."""
<|bo... | stack_v2_sparse_classes_75kplus_train_067413 | 13,056 | permissive | [
{
"docstring": "RespondActivityTaskCanceled.",
"name": "cancel",
"signature": "def cancel(self, task_token=None, details=None)"
},
{
"docstring": "RespondActivityTaskCompleted.",
"name": "complete",
"signature": "def complete(self, task_token=None, result=None)"
},
{
"docstring":... | 5 | stack_v2_sparse_classes_30k_train_023230 | Implement the Python class `ActivityWorker` described below.
Class description:
Base class for SimpleWorkflow activity workers.
Method signatures and docstrings:
- def cancel(self, task_token=None, details=None): RespondActivityTaskCanceled.
- def complete(self, task_token=None, result=None): RespondActivityTaskCompl... | Implement the Python class `ActivityWorker` described below.
Class description:
Base class for SimpleWorkflow activity workers.
Method signatures and docstrings:
- def cancel(self, task_token=None, details=None): RespondActivityTaskCanceled.
- def complete(self, task_token=None, result=None): RespondActivityTaskCompl... | dccb9467675c67b9c3399fc76c5de6d31bfb8255 | <|skeleton|>
class ActivityWorker:
"""Base class for SimpleWorkflow activity workers."""
def cancel(self, task_token=None, details=None):
"""RespondActivityTaskCanceled."""
<|body_0|>
def complete(self, task_token=None, result=None):
"""RespondActivityTaskCompleted."""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ActivityWorker:
"""Base class for SimpleWorkflow activity workers."""
def cancel(self, task_token=None, details=None):
"""RespondActivityTaskCanceled."""
if task_token is None:
task_token = self.last_tasktoken
return self._swf.respond_activity_task_canceled(task_token,... | the_stack_v2_python_sparse | desktop/core/ext-py3/boto-2.49.0/boto/swf/layer2.py | cloudera/hue | train | 5,655 |
c1916aa2ee5846bed8d09c1eb08d4fa6a271ed88 | [
"params = Differ.get_valid_params()\nparams.add_param('rel_err', '', 'Relative Error for csv files')\nparams.add_param('zero_threshold', sys.float_info.min * 4.0, 'it represents the value below which a float is ' + 'considered zero (XML comparison only)')\nparams.add_param('ignore_sign', False, 'if true, then only ... | <|body_start_0|>
params = Differ.get_valid_params()
params.add_param('rel_err', '', 'Relative Error for csv files')
params.add_param('zero_threshold', sys.float_info.min * 4.0, 'it represents the value below which a float is ' + 'considered zero (XML comparison only)')
params.add_param('... | This is the class to use for handling the parameters block. | UnorderedCSV | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnorderedCSV:
"""This is the class to use for handling the parameters block."""
def get_valid_params():
"""Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters."""
<|body_0|>
def __init__(self, name, params, testD... | stack_v2_sparse_classes_75kplus_train_067414 | 14,039 | permissive | [
{
"docstring": "Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters.",
"name": "get_valid_params",
"signature": "def get_valid_params()"
},
{
"docstring": "Initializer for the class. Takes a String name and a dictionary params @ In, name... | 3 | stack_v2_sparse_classes_30k_train_013174 | Implement the Python class `UnorderedCSV` described below.
Class description:
This is the class to use for handling the parameters block.
Method signatures and docstrings:
- def get_valid_params(): Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters.
- def __... | Implement the Python class `UnorderedCSV` described below.
Class description:
This is the class to use for handling the parameters block.
Method signatures and docstrings:
- def get_valid_params(): Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters.
- def __... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class UnorderedCSV:
"""This is the class to use for handling the parameters block."""
def get_valid_params():
"""Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters."""
<|body_0|>
def __init__(self, name, params, testD... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnorderedCSV:
"""This is the class to use for handling the parameters block."""
def get_valid_params():
"""Returns the valid parameters for this class. @ In, None @ Out, params, _ValidParameters, return the parameters."""
params = Differ.get_valid_params()
params.add_param('rel_er... | the_stack_v2_python_sparse | scripts/TestHarness/testers/UnorderedCSVDiffer.py | idaholab/raven | train | 201 |
78831c3f27120e24f4da27d75f37b3c6f53641a2 | [
"super().__init__()\nassert len(kernel_sizes) == 2\nassert kernel_sizes[0] % 2 == 1, 'Kernel size must be odd number.'\nassert kernel_sizes[1] % 2 == 1, 'Kernel size must be odd number.'\nself.period = period\nself.convs = torch.nn.ModuleList()\nin_chs = in_channels\nout_chs = channels\nfor downsample_scale in down... | <|body_start_0|>
super().__init__()
assert len(kernel_sizes) == 2
assert kernel_sizes[0] % 2 == 1, 'Kernel size must be odd number.'
assert kernel_sizes[1] % 2 == 1, 'Kernel size must be odd number.'
self.period = period
self.convs = torch.nn.ModuleList()
in_chs =... | HiFiGAN period discriminator module. | HiFiGANPeriodDiscriminator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HiFiGANPeriodDiscriminator:
"""HiFiGAN period discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, period: int=3, kernel_sizes: List[int]=[5, 3], channels: int=32, downsample_scales: List[int]=[3, 3, 3, 3, 1], max_downsample_channels: int=1024, bias: bool=True... | stack_v2_sparse_classes_75kplus_train_067415 | 31,567 | permissive | [
{
"docstring": "Initialize HiFiGANPeriodDiscriminator module. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. period (int): Period. kernel_sizes (list): Kernel sizes of initial conv layers and the final conv layer. channels (int): Number of initial channels. dow... | 4 | stack_v2_sparse_classes_30k_train_002367 | Implement the Python class `HiFiGANPeriodDiscriminator` described below.
Class description:
HiFiGAN period discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, period: int=3, kernel_sizes: List[int]=[5, 3], channels: int=32, downsample_scales: List[int]... | Implement the Python class `HiFiGANPeriodDiscriminator` described below.
Class description:
HiFiGAN period discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, period: int=3, kernel_sizes: List[int]=[5, 3], channels: int=32, downsample_scales: List[int]... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class HiFiGANPeriodDiscriminator:
"""HiFiGAN period discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, period: int=3, kernel_sizes: List[int]=[5, 3], channels: int=32, downsample_scales: List[int]=[3, 3, 3, 3, 1], max_downsample_channels: int=1024, bias: bool=True... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HiFiGANPeriodDiscriminator:
"""HiFiGAN period discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, period: int=3, kernel_sizes: List[int]=[5, 3], channels: int=32, downsample_scales: List[int]=[3, 3, 3, 3, 1], max_downsample_channels: int=1024, bias: bool=True, nonlinear_a... | the_stack_v2_python_sparse | espnet2/gan_tts/hifigan/hifigan.py | espnet/espnet | train | 7,242 |
4a71f04531553bea773f9325ef730f66dcb1d6ba | [
"result = []\n\ndef recursive(node, result):\n if node:\n result.append(node.val)\n recursive(node.left, result)\n recursive(node.right, result)\n else:\n result.append('$')\nrecursive(root, result)\nreturn result",
"def recursive(nums, length, index):\n if index < length and ... | <|body_start_0|>
result = []
def recursive(node, result):
if node:
result.append(node.val)
recursive(node.left, result)
recursive(node.right, result)
else:
result.append('$')
recursive(root, result)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def serialize(self, root):
""":type root:BinaryTreeNode :rtype:list"""
<|body_0|>
def deserialize(self, nums):
""":type nums:list :rtype:BinaryTreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = []
def recursive(node... | stack_v2_sparse_classes_75kplus_train_067416 | 1,091 | no_license | [
{
"docstring": ":type root:BinaryTreeNode :rtype:list",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": ":type nums:list :rtype:BinaryTreeNode",
"name": "deserialize",
"signature": "def deserialize(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_022359 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def serialize(self, root): :type root:BinaryTreeNode :rtype:list
- def deserialize(self, nums): :type nums:list :rtype:BinaryTreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def serialize(self, root): :type root:BinaryTreeNode :rtype:list
- def deserialize(self, nums): :type nums:list :rtype:BinaryTreeNode
<|skeleton|>
class Solution:
def seria... | 42a15943394ae533dcd0d5bbf52e4366ab0756ab | <|skeleton|>
class Solution:
def serialize(self, root):
""":type root:BinaryTreeNode :rtype:list"""
<|body_0|>
def deserialize(self, nums):
""":type nums:list :rtype:BinaryTreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def serialize(self, root):
""":type root:BinaryTreeNode :rtype:list"""
result = []
def recursive(node, result):
if node:
result.append(node.val)
recursive(node.left, result)
recursive(node.right, result)
... | the_stack_v2_python_sparse | test37.py | nihao-hit/jianzhiOffer | train | 0 | |
5892b812a1567363c1e04a041948d8a1f91997f9 | [
"self.pq = nums\nself.k = k\nheapify(self.pq)\nwhile len(self.pq) > k:\n heappop(self.pq)",
"heappush(self.pq, val)\nwhile len(self.pq) > self.k:\n heappop(self.pq)\nreturn self.pq[0]"
] | <|body_start_0|>
self.pq = nums
self.k = k
heapify(self.pq)
while len(self.pq) > k:
heappop(self.pq)
<|end_body_0|>
<|body_start_1|>
heappush(self.pq, val)
while len(self.pq) > self.k:
heappop(self.pq)
return self.pq[0]
<|end_body_1|>
| KthLargest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pq = nums
self.k = k
heapify(self.pq)... | stack_v2_sparse_classes_75kplus_train_067417 | 936 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021150 | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest` described below.
Class description:
Implement the KthLargest class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest:
def __init__(self, k, nu... | 76d767ec001649b2df07aac211ac4b43b415ebdd | <|skeleton|>
class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KthLargest:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.pq = nums
self.k = k
heapify(self.pq)
while len(self.pq) > k:
heappop(self.pq)
def add(self, val):
""":type val: int :rtype: int"""
heappush(self.pq, ... | the_stack_v2_python_sparse | leetcode703 Kth Largest Element in a Stream.py | whglamrock/leetcode_series | train | 2 | |
dcc927e97f7a5740227eb6f200bf0b80dea44f0f | [
"if path[:5] == 's3://':\n folders = path.split('/')\n self.path = '/'.join(folders[3:])\n self.bucket = folders[2]\n if aws_access_key_id is not None and aws_secret_access_key is not None:\n self.S3 = boto3.client('s3', aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access... | <|body_start_0|>
if path[:5] == 's3://':
folders = path.split('/')
self.path = '/'.join(folders[3:])
self.bucket = folders[2]
if aws_access_key_id is not None and aws_secret_access_key is not None:
self.S3 = boto3.client('s3', aws_access_key_id=aws... | Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash. | AlignmentMemoizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlignmentMemoizer:
"""Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash."""
def __init__(self, path, aws_access_key_id=None, aws_secret_access_key=None):
"""Args: path: pa... | stack_v2_sparse_classes_75kplus_train_067418 | 22,491 | permissive | [
{
"docstring": "Args: path: path to directory in which to read and store memoized alignments; if path begins with \"s3://\", stores bucket",
"name": "__init__",
"signature": "def __init__(self, path, aws_access_key_id=None, aws_secret_access_key=None)"
},
{
"docstring": "Generate a path or S3 ke... | 4 | stack_v2_sparse_classes_30k_train_036587 | Implement the Python class `AlignmentMemoizer` described below.
Class description:
Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash.
Method signatures and docstrings:
- def __init__(self, path, aws_access... | Implement the Python class `AlignmentMemoizer` described below.
Class description:
Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash.
Method signatures and docstrings:
- def __init__(self, path, aws_access... | b8464e7bb2dda44cb9a24325fef9ce0c93951c5e | <|skeleton|>
class AlignmentMemoizer:
"""Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash."""
def __init__(self, path, aws_access_key_id=None, aws_secret_access_key=None):
"""Args: path: pa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AlignmentMemoizer:
"""Memoizer for alignments. This stores an alignment using a hash of the accession.version in the alignments. This stores alignments as fasta files named by the hash."""
def __init__(self, path, aws_access_key_id=None, aws_secret_access_key=None):
"""Args: path: path to directo... | the_stack_v2_python_sparse | adapt/prepare/align.py | broadinstitute/adapt | train | 22 |
406664b5e107f0f1f36995c3aa8d69dbb8a1b201 | [
"self._entries = entries\nself._att_reporter = att_reporter\nself._ctc_reporter = ctc_reporter\nself._logger = logger\nself._epoch = epoch",
"observation = trainer.observation\nfor k, v in observation.items():\n if self._entries is not None and k not in self._entries:\n continue\n if k is not None an... | <|body_start_0|>
self._entries = entries
self._att_reporter = att_reporter
self._ctc_reporter = ctc_reporter
self._logger = logger
self._epoch = epoch
<|end_body_0|>
<|body_start_1|>
observation = trainer.observation
for k, v in observation.items():
i... | A tensorboard logger extension | TensorboardLogger | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorboardLogger:
"""A tensorboard logger extension"""
def __init__(self, logger, att_reporter=None, ctc_reporter=None, entries=None, epoch=0):
"""Init the extension :param SummaryWriter logger: The logger to use :param PlotAttentionReporter att_reporter: The (optional) PlotAttentio... | stack_v2_sparse_classes_75kplus_train_067419 | 1,915 | permissive | [
{
"docstring": "Init the extension :param SummaryWriter logger: The logger to use :param PlotAttentionReporter att_reporter: The (optional) PlotAttentionReporter :param entries: The entries to watch :param int epoch: The starting epoch",
"name": "__init__",
"signature": "def __init__(self, logger, att_r... | 2 | null | Implement the Python class `TensorboardLogger` described below.
Class description:
A tensorboard logger extension
Method signatures and docstrings:
- def __init__(self, logger, att_reporter=None, ctc_reporter=None, entries=None, epoch=0): Init the extension :param SummaryWriter logger: The logger to use :param PlotAt... | Implement the Python class `TensorboardLogger` described below.
Class description:
A tensorboard logger extension
Method signatures and docstrings:
- def __init__(self, logger, att_reporter=None, ctc_reporter=None, entries=None, epoch=0): Init the extension :param SummaryWriter logger: The logger to use :param PlotAt... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class TensorboardLogger:
"""A tensorboard logger extension"""
def __init__(self, logger, att_reporter=None, ctc_reporter=None, entries=None, epoch=0):
"""Init the extension :param SummaryWriter logger: The logger to use :param PlotAttentionReporter att_reporter: The (optional) PlotAttentio... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TensorboardLogger:
"""A tensorboard logger extension"""
def __init__(self, logger, att_reporter=None, ctc_reporter=None, entries=None, epoch=0):
"""Init the extension :param SummaryWriter logger: The logger to use :param PlotAttentionReporter att_reporter: The (optional) PlotAttentionReporter :pa... | the_stack_v2_python_sparse | espnet/utils/training/tensorboard_logger.py | espnet/espnet | train | 7,242 |
fb58a4fe2b2c1de6e4b8d3aaef538228377031a6 | [
"super(OwnedEntityForm, self).__init__(*args, **kwargs)\nif not self.instance.id:\n self.instance.owner = self.user.owner\nself.restrict_fields()\nself.restrict_querysets()\nself.modernize_fields()",
"disallowed_fields = self.user.get_disallowed_fields_for(self.instance)\nif self.is_bound:\n for k in disall... | <|body_start_0|>
super(OwnedEntityForm, self).__init__(*args, **kwargs)
if not self.instance.id:
self.instance.owner = self.user.owner
self.restrict_fields()
self.restrict_querysets()
self.modernize_fields()
<|end_body_0|>
<|body_start_1|>
disallowed_fields =... | Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model are disabled by default, so any extra fields added to the form MUST BE handled by th... | OwnedEntityForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OwnedEntityForm:
"""Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model are disabled by default, so any extra fie... | stack_v2_sparse_classes_75kplus_train_067420 | 2,435 | no_license | [
{
"docstring": "Set owner to new insstance, restrict fields, querysets and modernize fields.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Disable or remove fields for data that the user is not allowed to modify.",
"name": "restrict_fields",
... | 2 | stack_v2_sparse_classes_30k_train_018383 | Implement the Python class `OwnedEntityForm` described below.
Class description:
Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model ar... | Implement the Python class `OwnedEntityForm` described below.
Class description:
Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model ar... | 4dcf0e6a37e8753ae9d69d663c0c280fcca0a26c | <|skeleton|>
class OwnedEntityForm:
"""Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model are disabled by default, so any extra fie... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OwnedEntityForm:
"""Base model form for OwnedEntity subclasses, providing automatic disabled fields based on permissions, filters for choice fields based on user account (owner of instances) and HTML5 widgets. IMPORTANT: Only fields belonging to the model are disabled by default, so any extra fields added to ... | the_stack_v2_python_sparse | apps/common/forms/base.py | ESCL/pjtracker | train | 1 |
2a5d9ab8b81474b26ddf5d86e0407a644c3a480f | [
"self.n = model.n\nself.probs = probs = dict()\nself.sorted_probs = dict()\npre = [elem for elem in model.counts.keys() if not len(elem) == self.n]\nsuf = [elem for elem in model.counts.keys() if len(elem) == self.n]\nfor elem in suf:\n prfx = elem[:-1]\n sfx = elem[-1]\n if prfx in probs:\n aux = p... | <|body_start_0|>
self.n = model.n
self.probs = probs = dict()
self.sorted_probs = dict()
pre = [elem for elem in model.counts.keys() if not len(elem) == self.n]
suf = [elem for elem in model.counts.keys() if len(elem) == self.n]
for elem in suf:
prfx = elem[:-... | n-gram generator. | NGramGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NGramGenerator:
"""n-gram generator."""
def __init__(self, model):
"""model -- n-gram model."""
<|body_0|>
def generate_sent(self):
"""Randomly generate a sentence."""
<|body_1|>
def generate_token(self, prev_tokens=None):
"""Randomly generat... | stack_v2_sparse_classes_75kplus_train_067421 | 2,740 | permissive | [
{
"docstring": "model -- n-gram model.",
"name": "__init__",
"signature": "def __init__(self, model)"
},
{
"docstring": "Randomly generate a sentence.",
"name": "generate_sent",
"signature": "def generate_sent(self)"
},
{
"docstring": "Randomly generate a token, given prev_tokens... | 3 | stack_v2_sparse_classes_30k_val_002609 | Implement the Python class `NGramGenerator` described below.
Class description:
n-gram generator.
Method signatures and docstrings:
- def __init__(self, model): model -- n-gram model.
- def generate_sent(self): Randomly generate a sentence.
- def generate_token(self, prev_tokens=None): Randomly generate a token, give... | Implement the Python class `NGramGenerator` described below.
Class description:
n-gram generator.
Method signatures and docstrings:
- def __init__(self, model): model -- n-gram model.
- def generate_sent(self): Randomly generate a sentence.
- def generate_token(self, prev_tokens=None): Randomly generate a token, give... | cb163f203ae3ce21d210d7751c457b18443e43d0 | <|skeleton|>
class NGramGenerator:
"""n-gram generator."""
def __init__(self, model):
"""model -- n-gram model."""
<|body_0|>
def generate_sent(self):
"""Randomly generate a sentence."""
<|body_1|>
def generate_token(self, prev_tokens=None):
"""Randomly generat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NGramGenerator:
"""n-gram generator."""
def __init__(self, model):
"""model -- n-gram model."""
self.n = model.n
self.probs = probs = dict()
self.sorted_probs = dict()
pre = [elem for elem in model.counts.keys() if not len(elem) == self.n]
suf = [elem for e... | the_stack_v2_python_sparse | pagi/utils/ngram/ngram_generator.py | yoelm/pagi | train | 0 |
bd57c8c3a2954ec8ce319dc67205c2a7e27456fb | [
"result = factual_client.resolve(name='primanti brothers', town='pittsburgh', state='PA', latitude=40.45, longitude=-79.98).get_resolved_result()\nself.assertIsNotNone(result)\nself.assertEquals(result['name'], 'Primanti Brothers')\nself.assertEquals(result['postcode'], '15222')\nresult = factual_client.resolve(nam... | <|body_start_0|>
result = factual_client.resolve(name='primanti brothers', town='pittsburgh', state='PA', latitude=40.45, longitude=-79.98).get_resolved_result()
self.assertIsNotNone(result)
self.assertEquals(result['name'], 'Primanti Brothers')
self.assertEquals(result['postcode'], '152... | FactualResolveTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FactualResolveTest:
def test_successful_request(self):
"""Tests response from a few Resolve API calls known to work"""
<|body_0|>
def test_unsuccessful_request(self):
"""Tests response from a few Resolve API calls known to not work"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus_train_067422 | 18,595 | no_license | [
{
"docstring": "Tests response from a few Resolve API calls known to work",
"name": "test_successful_request",
"signature": "def test_successful_request(self)"
},
{
"docstring": "Tests response from a few Resolve API calls known to not work",
"name": "test_unsuccessful_request",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_031757 | Implement the Python class `FactualResolveTest` described below.
Class description:
Implement the FactualResolveTest class.
Method signatures and docstrings:
- def test_successful_request(self): Tests response from a few Resolve API calls known to work
- def test_unsuccessful_request(self): Tests response from a few ... | Implement the Python class `FactualResolveTest` described below.
Class description:
Implement the FactualResolveTest class.
Method signatures and docstrings:
- def test_successful_request(self): Tests response from a few Resolve API calls known to work
- def test_unsuccessful_request(self): Tests response from a few ... | 3ed85e856a026001a1d91d09d31d944c64704824 | <|skeleton|>
class FactualResolveTest:
def test_successful_request(self):
"""Tests response from a few Resolve API calls known to work"""
<|body_0|>
def test_unsuccessful_request(self):
"""Tests response from a few Resolve API calls known to not work"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FactualResolveTest:
def test_successful_request(self):
"""Tests response from a few Resolve API calls known to work"""
result = factual_client.resolve(name='primanti brothers', town='pittsburgh', state='PA', latitude=40.45, longitude=-79.98).get_resolved_result()
self.assertIsNotNone(r... | the_stack_v2_python_sparse | scenable/outsourcing/apitools/tests.py | gregarious/betasite | train | 0 | |
7c1f032ccb30f943e5d04d80e7adbd5448b38a3c | [
"queryset = NewUser.objects.all()\nserializer = UserSerializer(queryset, many=True)\nreturn Response(serializer.data)",
"queryset = NewUser.objects.all().order_by('first_name')\nuser = get_object_or_404(queryset, pk=pk)\nserializer = UserSerializer(user)\nreturn Response(serializer.data)"
] | <|body_start_0|>
queryset = NewUser.objects.all()
serializer = UserSerializer(queryset, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
queryset = NewUser.objects.all().order_by('first_name')
user = get_object_or_404(queryset, pk=pk)
serialize... | View que retorna informações de todos os usuários | UserView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserView:
"""View que retorna informações de todos os usuários"""
def list(self, request):
"""Retorna a lista de usuários"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Retorna um usuário em específico"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_75kplus_train_067423 | 4,671 | no_license | [
{
"docstring": "Retorna a lista de usuários",
"name": "list",
"signature": "def list(self, request)"
},
{
"docstring": "Retorna um usuário em específico",
"name": "retrieve",
"signature": "def retrieve(self, request, pk=None)"
}
] | 2 | null | Implement the Python class `UserView` described below.
Class description:
View que retorna informações de todos os usuários
Method signatures and docstrings:
- def list(self, request): Retorna a lista de usuários
- def retrieve(self, request, pk=None): Retorna um usuário em específico | Implement the Python class `UserView` described below.
Class description:
View que retorna informações de todos os usuários
Method signatures and docstrings:
- def list(self, request): Retorna a lista de usuários
- def retrieve(self, request, pk=None): Retorna um usuário em específico
<|skeleton|>
class UserView:
... | 4ee69ab46a33c326bf41fca5b9fe0d6746ce683d | <|skeleton|>
class UserView:
"""View que retorna informações de todos os usuários"""
def list(self, request):
"""Retorna a lista de usuários"""
<|body_0|>
def retrieve(self, request, pk=None):
"""Retorna um usuário em específico"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UserView:
"""View que retorna informações de todos os usuários"""
def list(self, request):
"""Retorna a lista de usuários"""
queryset = NewUser.objects.all()
serializer = UserSerializer(queryset, many=True)
return Response(serializer.data)
def retrieve(self, request, ... | the_stack_v2_python_sparse | manage_users/views.py | gomeslucasm/Backend_canil | train | 1 |
2acd034ef3caa4a68ef922c687606857b7431922 | [
"ageAnnees = situation.AgeEnAnnees()\ntraitsPerso = situation.GetDicoTraits()\nreturn self.DeterminerPortraits(situation, ageAnnees, 'Saint Louis', traitsPerso, masculin)",
"portraits = []\nportraitCourant = situation.GetValCarac(portrait.Portrait.C_PORTRAIT)\nif nom == heros.Heros.C_NOM:\n if ageAnnees >= 30 ... | <|body_start_0|>
ageAnnees = situation.AgeEnAnnees()
traitsPerso = situation.GetDicoTraits()
return self.DeterminerPortraits(situation, ageAnnees, 'Saint Louis', traitsPerso, masculin)
<|end_body_0|>
<|body_start_1|>
portraits = []
portraitCourant = situation.GetValCarac(portrai... | PortraitSpe | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortraitSpe:
def DeterminerPortraitPersoPrincipal(self, situation, masculin):
"""retourne l'adresse du portrait à afficher pour le perso courant"""
<|body_0|>
def DeterminerPortraits(self, situation, ageAnnees, nom, valeursTraits, masculin):
"""retourne l'adresse du ... | stack_v2_sparse_classes_75kplus_train_067424 | 1,861 | no_license | [
{
"docstring": "retourne l'adresse du portrait à afficher pour le perso courant",
"name": "DeterminerPortraitPersoPrincipal",
"signature": "def DeterminerPortraitPersoPrincipal(self, situation, masculin)"
},
{
"docstring": "retourne l'adresse du portrait à afficher pour le perso courant valeursT... | 2 | stack_v2_sparse_classes_30k_train_008943 | Implement the Python class `PortraitSpe` described below.
Class description:
Implement the PortraitSpe class.
Method signatures and docstrings:
- def DeterminerPortraitPersoPrincipal(self, situation, masculin): retourne l'adresse du portrait à afficher pour le perso courant
- def DeterminerPortraits(self, situation, ... | Implement the Python class `PortraitSpe` described below.
Class description:
Implement the PortraitSpe class.
Method signatures and docstrings:
- def DeterminerPortraitPersoPrincipal(self, situation, masculin): retourne l'adresse du portrait à afficher pour le perso courant
- def DeterminerPortraits(self, situation, ... | ece5e7b6aeac787bd3d5dee2c245496a5a4f4c50 | <|skeleton|>
class PortraitSpe:
def DeterminerPortraitPersoPrincipal(self, situation, masculin):
"""retourne l'adresse du portrait à afficher pour le perso courant"""
<|body_0|>
def DeterminerPortraits(self, situation, ageAnnees, nom, valeursTraits, masculin):
"""retourne l'adresse du ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PortraitSpe:
def DeterminerPortraitPersoPrincipal(self, situation, masculin):
"""retourne l'adresse du portrait à afficher pour le perso courant"""
ageAnnees = situation.AgeEnAnnees()
traitsPerso = situation.GetDicoTraits()
return self.DeterminerPortraits(situation, ageAnnees, ... | the_stack_v2_python_sparse | game/spe/humanite/portrait_saint_louis.py | gabriellevy/destinSaintLouis | train | 2 | |
6d277752a793592cc0109d2f19dc55cc28451a60 | [
"self.__chip_dataset = chip_dataset\nself.__chip_key_maker = chip_key_maker\nself.__set_root_dir()\nself.__class_to_index = attributes_to_classes(self.__chip_dataset, self.__chip_key_maker)\nprint(self.__class_to_index)",
"ROOTMAP = {SetType.ALL.value: 'all', SetType.QUERY.value: 'query', SetType.TEST.value: 'tes... | <|body_start_0|>
self.__chip_dataset = chip_dataset
self.__chip_key_maker = chip_key_maker
self.__set_root_dir()
self.__class_to_index = attributes_to_classes(self.__chip_dataset, self.__chip_key_maker)
print(self.__class_to_index)
<|end_body_0|>
<|body_start_1|>
ROOTMAP... | KerasDirectory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KerasDirectory:
def __init__(self, chip_dataset, chip_key_maker):
"""Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset, or other iterable of Chips chip_key_maker: A callable that takes a chip and returns a string represent... | stack_v2_sparse_classes_75kplus_train_067425 | 12,062 | permissive | [
{
"docstring": "Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset, or other iterable of Chips chip_key_maker: A callable that takes a chip and returns a string representing the attributes in that chip that you care about. For example, you might w... | 4 | stack_v2_sparse_classes_30k_test_002664 | Implement the Python class `KerasDirectory` described below.
Class description:
Implement the KerasDirectory class.
Method signatures and docstrings:
- def __init__(self, chip_dataset, chip_key_maker): Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset,... | Implement the Python class `KerasDirectory` described below.
Class description:
Implement the KerasDirectory class.
Method signatures and docstrings:
- def __init__(self, chip_dataset, chip_key_maker): Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset,... | c39b91d7f6b8837d77130598c0778c59b5b82669 | <|skeleton|>
class KerasDirectory:
def __init__(self, chip_dataset, chip_key_maker):
"""Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset, or other iterable of Chips chip_key_maker: A callable that takes a chip and returns a string represent... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KerasDirectory:
def __init__(self, chip_dataset, chip_key_maker):
"""Takes a ChipDataset and hard links the files to custom defined class directories. Args: chip_dataset: A ChipDataset, or other iterable of Chips chip_key_maker: A callable that takes a chip and returns a string representing the attrib... | the_stack_v2_python_sparse | pelops/training/utils.py | d-grossman/pelops | train | 1 | |
5c55ad70bdf19449d3426a47e5f7804f7bb0883d | [
"self.argument_spec = netapp_utils.na_ontap_host_argument_spec()\nself.argument_spec.update(dict(state=dict(required=False, choices=['present'], default='present'), address_type=dict(required=True, choices=['ipv4', 'ipv6']), is_enabled=dict(required=True, type='bool'), node=dict(required=True, type='str'), dhcp=dic... | <|body_start_0|>
self.argument_spec = netapp_utils.na_ontap_host_argument_spec()
self.argument_spec.update(dict(state=dict(required=False, choices=['present'], default='present'), address_type=dict(required=True, choices=['ipv4', 'ipv6']), is_enabled=dict(required=True, type='bool'), node=dict(required=... | Modify a Service Processor Network | NetAppOntapServiceProcessorNetwork | [
"MIT",
"GPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetAppOntapServiceProcessorNetwork:
"""Modify a Service Processor Network"""
def __init__(self):
"""Initialize the NetAppOntapServiceProcessorNetwork class"""
<|body_0|>
def get_service_processor_network(self):
"""Return details about service processor network :p... | stack_v2_sparse_classes_75kplus_train_067426 | 9,677 | permissive | [
{
"docstring": "Initialize the NetAppOntapServiceProcessorNetwork class",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Return details about service processor network :param: name : name of the vserver :return: Details about service processor network. None if not found... | 4 | null | Implement the Python class `NetAppOntapServiceProcessorNetwork` described below.
Class description:
Modify a Service Processor Network
Method signatures and docstrings:
- def __init__(self): Initialize the NetAppOntapServiceProcessorNetwork class
- def get_service_processor_network(self): Return details about service... | Implement the Python class `NetAppOntapServiceProcessorNetwork` described below.
Class description:
Modify a Service Processor Network
Method signatures and docstrings:
- def __init__(self): Initialize the NetAppOntapServiceProcessorNetwork class
- def get_service_processor_network(self): Return details about service... | 0cd0c003884155ac922e3e301305ac202de7028c | <|skeleton|>
class NetAppOntapServiceProcessorNetwork:
"""Modify a Service Processor Network"""
def __init__(self):
"""Initialize the NetAppOntapServiceProcessorNetwork class"""
<|body_0|>
def get_service_processor_network(self):
"""Return details about service processor network :p... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NetAppOntapServiceProcessorNetwork:
"""Modify a Service Processor Network"""
def __init__(self):
"""Initialize the NetAppOntapServiceProcessorNetwork class"""
self.argument_spec = netapp_utils.na_ontap_host_argument_spec()
self.argument_spec.update(dict(state=dict(required=False, ... | the_stack_v2_python_sparse | ansible/my_env/lib/python2.7/site-packages/ansible/modules/storage/netapp/na_ontap_service_processor_network.py | otus-devops-2019-02/yyashkin_infra | train | 0 |
07ecf50c0038c082a958b4d591516608e9eae747 | [
"self.root = TrieNode()\nfor word in word_list:\n if word:\n self.insert(word)",
"node = self.root\nfor w in word:\n if w not in node.child:\n node.child[w] = TrieNode()\n node = node.child[w]\nnode.is_end = True"
] | <|body_start_0|>
self.root = TrieNode()
for word in word_list:
if word:
self.insert(word)
<|end_body_0|>
<|body_start_1|>
node = self.root
for w in word:
if w not in node.child:
node.child[w] = TrieNode()
node = node.ch... | Trie | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trie:
def __init__(self, word_list):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, word: str) -> None:
"""Inserts a word into the trie."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.root = TrieNode()
for word ... | stack_v2_sparse_classes_75kplus_train_067427 | 1,352 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self, word_list)"
},
{
"docstring": "Inserts a word into the trie.",
"name": "insert",
"signature": "def insert(self, word: str) -> None"
}
] | 2 | null | Implement the Python class `Trie` described below.
Class description:
Implement the Trie class.
Method signatures and docstrings:
- def __init__(self, word_list): Initialize your data structure here.
- def insert(self, word: str) -> None: Inserts a word into the trie. | Implement the Python class `Trie` described below.
Class description:
Implement the Trie class.
Method signatures and docstrings:
- def __init__(self, word_list): Initialize your data structure here.
- def insert(self, word: str) -> None: Inserts a word into the trie.
<|skeleton|>
class Trie:
def __init__(self,... | ffc5606817a666aa6241cfab27364326f5c066ff | <|skeleton|>
class Trie:
def __init__(self, word_list):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, word: str) -> None:
"""Inserts a word into the trie."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Trie:
def __init__(self, word_list):
"""Initialize your data structure here."""
self.root = TrieNode()
for word in word_list:
if word:
self.insert(word)
def insert(self, word: str) -> None:
"""Inserts a word into the trie."""
node = self... | the_stack_v2_python_sparse | Code/CodeRecords/2776/8246/306416.py | AdamZhouSE/pythonHomework | train | 2 | |
dcabea67fbb716277c8c157eb8f0cd15b6494927 | [
"reader = sitk.ImageSeriesReader()\ndicom_names = reader.GetGDCMSeriesFileNames(self.image_path)\nreader.SetFileNames(dicom_names)\nimage = reader.Execute()\ntest_image = np.swapaxes(sitk.GetArrayFromImage(image), 0, 2).astype('float32')\nreturn test_image",
"reader = sitk.ImageSeriesReader()\ndicom_names = reade... | <|body_start_0|>
reader = sitk.ImageSeriesReader()
dicom_names = reader.GetGDCMSeriesFileNames(self.image_path)
reader.SetFileNames(dicom_names)
image = reader.Execute()
test_image = np.swapaxes(sitk.GetArrayFromImage(image), 0, 2).astype('float32')
return test_image
<|en... | Class to read DICOM MRI images | DICOMReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DICOMReader:
"""Class to read DICOM MRI images"""
def get_np_array(self):
"""Return the DICOM image as a Numpy array"""
<|body_0|>
def get_resolution(self):
"""Return the spacing between the slices"""
<|body_1|>
def set_itk_image(self):
"""Se... | stack_v2_sparse_classes_75kplus_train_067428 | 2,416 | no_license | [
{
"docstring": "Return the DICOM image as a Numpy array",
"name": "get_np_array",
"signature": "def get_np_array(self)"
},
{
"docstring": "Return the spacing between the slices",
"name": "get_resolution",
"signature": "def get_resolution(self)"
},
{
"docstring": "Set ITK image ob... | 3 | stack_v2_sparse_classes_30k_train_042875 | Implement the Python class `DICOMReader` described below.
Class description:
Class to read DICOM MRI images
Method signatures and docstrings:
- def get_np_array(self): Return the DICOM image as a Numpy array
- def get_resolution(self): Return the spacing between the slices
- def set_itk_image(self): Set ITK image obj... | Implement the Python class `DICOMReader` described below.
Class description:
Class to read DICOM MRI images
Method signatures and docstrings:
- def get_np_array(self): Return the DICOM image as a Numpy array
- def get_resolution(self): Return the spacing between the slices
- def set_itk_image(self): Set ITK image obj... | 4cf3ea43aaf4ab435fb46587e0fa51a5f9c2657e | <|skeleton|>
class DICOMReader:
"""Class to read DICOM MRI images"""
def get_np_array(self):
"""Return the DICOM image as a Numpy array"""
<|body_0|>
def get_resolution(self):
"""Return the spacing between the slices"""
<|body_1|>
def set_itk_image(self):
"""Se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DICOMReader:
"""Class to read DICOM MRI images"""
def get_np_array(self):
"""Return the DICOM image as a Numpy array"""
reader = sitk.ImageSeriesReader()
dicom_names = reader.GetGDCMSeriesFileNames(self.image_path)
reader.SetFileNames(dicom_names)
image = reader.Ex... | the_stack_v2_python_sparse | home_backup/mask_SegSRGAN/utils/ImageReader.py | sai36/SRGAN | train | 0 |
9ab2e0373d28cc580f231323a9211093dc7f7de4 | [
"self.logger = logging.getLogger('app')\nself.logger.debug('instantiated')\nself.cfg = cfg\nself.web_util = web_util\nself.session_manager = session_manager",
"user_token = req.context['user']['user']\nif self.web_util.check_csrf(user_token['ses'], csrf):\n self.logger.debug('Ending session %s for user %s', us... | <|body_start_0|>
self.logger = logging.getLogger('app')
self.logger.debug('instantiated')
self.cfg = cfg
self.web_util = web_util
self.session_manager = session_manager
<|end_body_0|>
<|body_start_1|>
user_token = req.context['user']['user']
if self.web_util.chec... | provides logout functionality | LogoutResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogoutResource:
"""provides logout functionality"""
def __init__(self, session_manager, cfg, web_util):
"""Initialization function"""
<|body_0|>
def on_get(self, req, resp, csrf):
"""Processes Get Request to logout, requires csrf token in url"""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_067429 | 1,318 | no_license | [
{
"docstring": "Initialization function",
"name": "__init__",
"signature": "def __init__(self, session_manager, cfg, web_util)"
},
{
"docstring": "Processes Get Request to logout, requires csrf token in url",
"name": "on_get",
"signature": "def on_get(self, req, resp, csrf)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017888 | Implement the Python class `LogoutResource` described below.
Class description:
provides logout functionality
Method signatures and docstrings:
- def __init__(self, session_manager, cfg, web_util): Initialization function
- def on_get(self, req, resp, csrf): Processes Get Request to logout, requires csrf token in url | Implement the Python class `LogoutResource` described below.
Class description:
provides logout functionality
Method signatures and docstrings:
- def __init__(self, session_manager, cfg, web_util): Initialization function
- def on_get(self, req, resp, csrf): Processes Get Request to logout, requires csrf token in url... | 3c774731b054c38a273371450a451c951d73b726 | <|skeleton|>
class LogoutResource:
"""provides logout functionality"""
def __init__(self, session_manager, cfg, web_util):
"""Initialization function"""
<|body_0|>
def on_get(self, req, resp, csrf):
"""Processes Get Request to logout, requires csrf token in url"""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LogoutResource:
"""provides logout functionality"""
def __init__(self, session_manager, cfg, web_util):
"""Initialization function"""
self.logger = logging.getLogger('app')
self.logger.debug('instantiated')
self.cfg = cfg
self.web_util = web_util
self.sessi... | the_stack_v2_python_sparse | genesis/logoutresource.py | wbmartin/exodus-app | train | 0 |
f479d0c043e81307d4dad56f088843eb3c85a051 | [
"if not self.server.shutdown_flag:\n raw = self.request[0]\n if raw:\n raw = bytearray(raw)\n self.handle_raw_line(raw)",
"try:\n self.request[1].sendto(event.create_response(), self.client_address)\nexcept Exception as exp:\n _LOGGER.error('Exception caught while responding to event: %s... | <|body_start_0|>
if not self.server.shutdown_flag:
raw = self.request[0]
if raw:
raw = bytearray(raw)
self.handle_raw_line(raw)
<|end_body_0|>
<|body_start_1|>
try:
self.request[1].sendto(event.create_response(), self.client_address)
... | Class for UDP Handling. | SIAUDPHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SIAUDPHandler:
"""Class for UDP Handling."""
def handle(self) -> None:
"""Overwritten method for the RequestHandler."""
<|body_0|>
def respond(self, event: SIAEvent) -> None:
"""Respond to the event."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_067430 | 2,823 | permissive | [
{
"docstring": "Overwritten method for the RequestHandler.",
"name": "handle",
"signature": "def handle(self) -> None"
},
{
"docstring": "Respond to the event.",
"name": "respond",
"signature": "def respond(self, event: SIAEvent) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_015031 | Implement the Python class `SIAUDPHandler` described below.
Class description:
Class for UDP Handling.
Method signatures and docstrings:
- def handle(self) -> None: Overwritten method for the RequestHandler.
- def respond(self, event: SIAEvent) -> None: Respond to the event. | Implement the Python class `SIAUDPHandler` described below.
Class description:
Class for UDP Handling.
Method signatures and docstrings:
- def handle(self) -> None: Overwritten method for the RequestHandler.
- def respond(self, event: SIAEvent) -> None: Respond to the event.
<|skeleton|>
class SIAUDPHandler:
"""... | c5394b7e2911d154b0aac5600cd57878ec7094ac | <|skeleton|>
class SIAUDPHandler:
"""Class for UDP Handling."""
def handle(self) -> None:
"""Overwritten method for the RequestHandler."""
<|body_0|>
def respond(self, event: SIAEvent) -> None:
"""Respond to the event."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SIAUDPHandler:
"""Class for UDP Handling."""
def handle(self) -> None:
"""Overwritten method for the RequestHandler."""
if not self.server.shutdown_flag:
raw = self.request[0]
if raw:
raw = bytearray(raw)
self.handle_raw_line(raw)
... | the_stack_v2_python_sparse | src/pysiaalarm/sync/handler.py | mach0gr/pysiaalarm | train | 1 |
fbf41b4e737bc5ca4f3a10c8adbb0a3e8a84c4ea | [
"new_items = self.__class__()\nfor k, v in self.iteritems():\n new_items[k] = v\nreturn new_items",
"sections = []\nfor key in self.iterkeys():\n if self.separator in key:\n sec, _ = key.rsplit(self.separator, 1)\n if sec not in sections:\n sections.append(sec)\nreturn sections",
... | <|body_start_0|>
new_items = self.__class__()
for k, v in self.iteritems():
new_items[k] = v
return new_items
<|end_body_0|>
<|body_start_1|>
sections = []
for key in self.iterkeys():
if self.separator in key:
sec, _ = key.rsplit(self.sepa... | A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotted setting names, where each component indicates one section in the settings hei... | SettingsDict | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SettingsDict:
"""A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotted setting names, where each component i... | stack_v2_sparse_classes_75kplus_train_067431 | 9,249 | permissive | [
{
"docstring": "D.copy() -> a shallow copy of D. This overrides the default dict.copy method to ensure that the copy is also an instance of SettingsDict.",
"name": "copy",
"signature": "def copy(self)"
},
{
"docstring": "Return a list of sections for this dict",
"name": "sections",
"sign... | 4 | null | Implement the Python class `SettingsDict` described below.
Class description:
A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotte... | Implement the Python class `SettingsDict` described below.
Class description:
A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotte... | d2f663f11d2b439ede5f0dca77f9d5f552b0fa36 | <|skeleton|>
class SettingsDict:
"""A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotted setting names, where each component i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SettingsDict:
"""A dict subclass with some extra helpers for dealing with app settings. This class extends the standard dictionary interface with some extra helper methods that are handy when dealing with application settings. It expects the keys to be dotted setting names, where each component indicates one ... | the_stack_v2_python_sparse | vaurien/config.py | searchspring/vaurien | train | 0 |
d208ca4db22c8cf8466a505e4ff0d86271a9748e | [
"BaseDustNode.__init__(self, xml_node)\nself._value = utils.parse_coords(xml_node.text)\nunits = u.deg\nself._columns = [Column(name=col_names[0], unit=units), Column(name=col_names[1], unit=units), Column(name=col_names[2], dtype='S25')]",
"base_string = BaseDustNode.__str__(self)\nvalues_str = 'values: ' + str(... | <|body_start_0|>
BaseDustNode.__init__(self, xml_node)
self._value = utils.parse_coords(xml_node.text)
units = u.deg
self._columns = [Column(name=col_names[0], unit=units), Column(name=col_names[1], unit=units), Column(name=col_names[2], dtype='S25')]
<|end_body_0|>
<|body_start_1|>
... | A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string. | CoordNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoordNode:
"""A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string."""
def __init__(self, xml_node, col_names):
"""Parameters ---------- xml_node : `xml.etree.ElementTree` the xml node that provides the raw data ... | stack_v2_sparse_classes_75kplus_train_067432 | 41,056 | permissive | [
{
"docstring": "Parameters ---------- xml_node : `xml.etree.ElementTree` the xml node that provides the raw data for this DustNode col_names : str the names of the columns associated with this item",
"name": "__init__",
"signature": "def __init__(self, xml_node, col_names)"
},
{
"docstring": "Re... | 2 | stack_v2_sparse_classes_30k_train_001407 | Implement the Python class `CoordNode` described below.
Class description:
A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string.
Method signatures and docstrings:
- def __init__(self, xml_node, col_names): Parameters ---------- xml_node : `xml.et... | Implement the Python class `CoordNode` described below.
Class description:
A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string.
Method signatures and docstrings:
- def __init__(self, xml_node, col_names): Parameters ---------- xml_node : `xml.et... | 51316d7417d7daf01a8b29d1df99037b9227c2bc | <|skeleton|>
class CoordNode:
"""A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string."""
def __init__(self, xml_node, col_names):
"""Parameters ---------- xml_node : `xml.etree.ElementTree` the xml node that provides the raw data ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CoordNode:
"""A node that contains RA, Dec coordinates. Outputs three values / columns: RA, Dec and a coordinate system description string."""
def __init__(self, xml_node, col_names):
"""Parameters ---------- xml_node : `xml.etree.ElementTree` the xml node that provides the raw data for this Dust... | the_stack_v2_python_sparse | astroquery/ipac/irsa/irsa_dust/core.py | astropy/astroquery | train | 636 |
f275cb47faca3b046385f94c356da4ad879ec7ac | [
"self.main_window = QtGui.QWidget()\nself.gui = Ui_StopwatchGui()\nself.gui.setupUi(self.main_window)\nself.gui.start_stop_button.clicked.connect(self.start_stop)\nself.stop_event = Event()\nself.stop_event.set()\nself.main_window.show()",
"if self.stop_event.is_set():\n self.stop_event.clear()\n self.timer... | <|body_start_0|>
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.clicked.connect(self.start_stop)
self.stop_event = Event()
self.stop_event.set()
self.main_window.show()
<|end_body_0|>
... | Application class to instantiate and control a StopwatchGui. | StopwatchApp | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_067433 | 2,727 | no_license | [
{
"docstring": "Initialize and show the gui.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Start the stopwatch if it is not running; stop it if it is running.",
"name": "start_stop",
"signature": "def start_stop(self)"
},
{
"docstring": "Runs a stopwa... | 3 | stack_v2_sparse_classes_30k_train_004951 | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | Implement the Python class `StopwatchApp` described below.
Class description:
Application class to instantiate and control a StopwatchGui.
Method signatures and docstrings:
- def __init__(self): Initialize and show the gui.
- def start_stop(self): Start the stopwatch if it is not running; stop it if it is running.
- ... | e1ad9c8f3e09aec3ee72821bd8374c957f047589 | <|skeleton|>
class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
<|body_0|>
def start_stop(self):
"""Start the stopwatch if it is not running; stop it if it is running."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StopwatchApp:
"""Application class to instantiate and control a StopwatchGui."""
def __init__(self):
"""Initialize and show the gui."""
self.main_window = QtGui.QWidget()
self.gui = Ui_StopwatchGui()
self.gui.setupUi(self.main_window)
self.gui.start_stop_button.cli... | the_stack_v2_python_sparse | DailyLabs/Lsn35/StopwatchApp.py | NathanRuprecht/CS210_IntroToProgramming | train | 0 |
35ebaf649bc0b5900856d6582efda4851f59517c | [
"with tempfile.TemporaryDirectory() as tmp_dir:\n test_repo = test_repos.TEST_REPOS[1]\n self.assertTrue(helper.build_image_impl(test_repo.project_name))\n host_src_dir = build_specified_commit.copy_src_from_docker(test_repo.project_name, tmp_dir)\n test_repo_manager = repo_manager.clone_repo_and_get_ma... | <|body_start_0|>
with tempfile.TemporaryDirectory() as tmp_dir:
test_repo = test_repos.TEST_REPOS[1]
self.assertTrue(helper.build_image_impl(test_repo.project_name))
host_src_dir = build_specified_commit.copy_src_from_docker(test_repo.project_name, tmp_dir)
test_r... | Tests if an image can be built from different states e.g. a commit. | BuildImageIntegrationTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old com... | stack_v2_sparse_classes_75kplus_train_067434 | 5,754 | permissive | [
{
"docstring": "Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old commit should show the error when its fuzzers run and the new one should not.",
"name": "test_build_fuzzers_from_commit",
"signature": "def test_build_fu... | 3 | stack_v2_sparse_classes_30k_train_051992 | Implement the Python class `BuildImageIntegrationTest` described below.
Class description:
Tests if an image can be built from different states e.g. a commit.
Method signatures and docstrings:
- def test_build_fuzzers_from_commit(self): Tests if the fuzzers can build at a specified commit. This is done by using a kno... | Implement the Python class `BuildImageIntegrationTest` described below.
Class description:
Tests if an image can be built from different states e.g. a commit.
Method signatures and docstrings:
- def test_build_fuzzers_from_commit(self): Tests if the fuzzers can build at a specified commit. This is done by using a kno... | f0275421f84b8f80ee767fb9230134ac97cb687b | <|skeleton|>
class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old com... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BuildImageIntegrationTest:
"""Tests if an image can be built from different states e.g. a commit."""
def test_build_fuzzers_from_commit(self):
"""Tests if the fuzzers can build at a specified commit. This is done by using a known regression range for a specific test case. The old commit should sh... | the_stack_v2_python_sparse | infra/build_specified_commit_test.py | google/oss-fuzz | train | 9,438 |
3aa50cd82b1ac77df7f38e50c8ac6d3dd0fe65b5 | [
"Continuum.__init__(self, *args, **kwargs)\nself.frac = frac\nself.sbin = sbin",
"if valid is None:\n valid = np.ones(x.shape, dtype=np.bool)\nbins_x = np.zeros(self.sbin)\nbins_y = np.zeros(self.sbin)\nw1 = 0\nw2 = float(len(x)) / self.sbin\nfor i in range(self.sbin):\n bindata = y[int(w1):int(w2)].copy()\... | <|body_start_0|>
Continuum.__init__(self, *args, **kwargs)
self.frac = frac
self.sbin = sbin
<|end_body_0|>
<|body_start_1|>
if valid is None:
valid = np.ones(x.shape, dtype=np.bool)
bins_x = np.zeros(self.sbin)
bins_y = np.zeros(self.sbin)
w1 = 0
... | Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins. | MaximumBin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaximumBin:
"""Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins."""
def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs):
"""Initialize a new MaximumBin continuum. Args: frac: Fraction of largest poi... | stack_v2_sparse_classes_75kplus_train_067435 | 15,610 | permissive | [
{
"docstring": "Initialize a new MaximumBin continuum. Args: frac: Fraction of largest points in each bin to use for fitting the continuum. sbin: Number of bins.",
"name": "__init__",
"signature": "def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs)"
},
{
"docstring": "Calculate... | 2 | null | Implement the Python class `MaximumBin` described below.
Class description:
Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins.
Method signatures and docstrings:
- def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs): Initialize a new ... | Implement the Python class `MaximumBin` described below.
Class description:
Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins.
Method signatures and docstrings:
- def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs): Initialize a new ... | 648eb1758e3744d9e3d6669edc4a0c4753559f17 | <|skeleton|>
class MaximumBin:
"""Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins."""
def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs):
"""Initialize a new MaximumBin continuum. Args: frac: Fraction of largest poi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MaximumBin:
"""Derive continuum as spline to all points that are within a given fraction of largest points in a given number of bins."""
def __init__(self, frac: float=0.15, sbin: int=100, *args, **kwargs):
"""Initialize a new MaximumBin continuum. Args: frac: Fraction of largest points in each b... | the_stack_v2_python_sparse | spexxy/utils/continuum.py | thusser/spexxy | train | 4 |
1c091674cc144b1908d815eed32fc2210101fac5 | [
"if additional_help is not None:\n self._help = additional_help\nelse:\n self._help = ''",
"width = 80\nparser = _Parser(description=self._help, formatter_class=argparse.RawTextHelpFormatter)\nsubparsers = parser.add_subparsers(dest='action')\n_Install(subparsers, width=width)\nif len(sys.argv) == 1:\n p... | <|body_start_0|>
if additional_help is not None:
self._help = additional_help
else:
self._help = ''
<|end_body_0|>
<|body_start_1|>
width = 80
parser = _Parser(description=self._help, formatter_class=argparse.RawTextHelpFormatter)
subparsers = parser.add_... | Class gathers all CLI information. | Parser | [
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
<|body_0|>
def args(self):
"""Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects -... | stack_v2_sparse_classes_75kplus_train_067436 | 11,324 | permissive | [
{
"docstring": "Intialize the class.",
"name": "__init__",
"signature": "def __init__(self, additional_help=None)"
},
{
"docstring": "Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects - filename: Path to the configuration file",
... | 2 | stack_v2_sparse_classes_30k_train_052342 | Implement the Python class `Parser` described below.
Class description:
Class gathers all CLI information.
Method signatures and docstrings:
- def __init__(self, additional_help=None): Intialize the class.
- def args(self): Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI a... | Implement the Python class `Parser` described below.
Class description:
Class gathers all CLI information.
Method signatures and docstrings:
- def __init__(self, additional_help=None): Intialize the class.
- def args(self): Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI a... | 57bd3e82e49d51e3426b13ad53ed8326a735ce29 | <|skeleton|>
class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
<|body_0|>
def args(self):
"""Return all the CLI options. Args: None Returns: _args: Namespace() containing all of our CLI arguments as objects -... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Parser:
"""Class gathers all CLI information."""
def __init__(self, additional_help=None):
"""Intialize the class."""
if additional_help is not None:
self._help = additional_help
else:
self._help = ''
def args(self):
"""Return all the CLI optio... | the_stack_v2_python_sparse | setup/pattoo_installation.py | palisadoes/pattoo | train | 0 |
187b3b682caf0497131f5fc1d82fe4dfea6621fd | [
"self._check()\nself.calc_derivatives(first=True)\nself.ffd_order = 1\nself.differentiator.calc_gradient()\nself.ffd_order = 0\ninputs = self.get_parameters().keys()\nobjs = self.get_objectives().keys()\nconstraints = list(self.get_eq_constraints().keys() + self.get_ineq_constraints().keys())\nself.dF = zeros((len(... | <|body_start_0|>
self._check()
self.calc_derivatives(first=True)
self.ffd_order = 1
self.differentiator.calc_gradient()
self.ffd_order = 0
inputs = self.get_parameters().keys()
objs = self.get_objectives().keys()
constraints = list(self.get_eq_constraints(... | Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot where the differentiation method can be plugged. Fake finite difference is supported. | SensitivityDriver | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SensitivityDriver:
"""Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot where the differentiation method can be plu... | stack_v2_sparse_classes_75kplus_train_067437 | 5,240 | no_license | [
{
"docstring": "Calculate the gradient of the workflow.",
"name": "execute",
"signature": "def execute(self)"
},
{
"docstring": "Make sure we aren't missing inputs or outputs",
"name": "_check",
"signature": "def _check(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_045043 | Implement the Python class `SensitivityDriver` described below.
Class description:
Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot wher... | Implement the Python class `SensitivityDriver` described below.
Class description:
Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot wher... | 7b4d9c2804bfd84773bad6cbac37a7175f47104f | <|skeleton|>
class SensitivityDriver:
"""Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot where the differentiation method can be plu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SensitivityDriver:
"""Driver to calculate the gradient of a workflow, and return it as a driver output. The gradient is calculated from all inputs (Parameters) to all outputs (Objectives and Constraints). SensitivityDriver includes a differentiator slot where the differentiation method can be plugged. Fake fi... | the_stack_v2_python_sparse | openmdao.lib/src/openmdao/lib/drivers/sensitivity.py | hschilling/OpenMDAO-Framework | train | 0 |
b498195670ccbd3330a0e62d5d2073a56a80bdce | [
"max_date_filter = ' AND o.orderdate <= %(max_date)s' if max_date else ' '\nquery = '\\n SELECT\\n z.countyname,\\n z.countypop,\\n count(o.orderid) as NumofOrders,\\n sum(o.totalprice) as TotalSpending\\n FROM\\n zipco... | <|body_start_0|>
max_date_filter = ' AND o.orderdate <= %(max_date)s' if max_date else ' '
query = '\n SELECT\n z.countyname,\n z.countypop,\n count(o.orderid) as NumofOrders,\n sum(o.totalprice) as TotalSpending\n FROM\n ... | Orders | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Orders:
def statsByZipcode(self, min_date='1900-1-1', max_date=None, sample_size=100):
"""For each zipcode, determine the number of orders and the total amount of money has been spent. Args: min_date (string): optional. date. Limits the search result timeframe. max_date (string): optiona... | stack_v2_sparse_classes_75kplus_train_067438 | 6,046 | no_license | [
{
"docstring": "For each zipcode, determine the number of orders and the total amount of money has been spent. Args: min_date (string): optional. date. Limits the search result timeframe. max_date (string): optional. date. Limits the search result timeframe. sample_size (int): optional. Percentage of the data t... | 2 | null | Implement the Python class `Orders` described below.
Class description:
Implement the Orders class.
Method signatures and docstrings:
- def statsByZipcode(self, min_date='1900-1-1', max_date=None, sample_size=100): For each zipcode, determine the number of orders and the total amount of money has been spent. Args: mi... | Implement the Python class `Orders` described below.
Class description:
Implement the Orders class.
Method signatures and docstrings:
- def statsByZipcode(self, min_date='1900-1-1', max_date=None, sample_size=100): For each zipcode, determine the number of orders and the total amount of money has been spent. Args: mi... | 047d8f2c420e69b0cb7f3e2838e1c5e30d738918 | <|skeleton|>
class Orders:
def statsByZipcode(self, min_date='1900-1-1', max_date=None, sample_size=100):
"""For each zipcode, determine the number of orders and the total amount of money has been spent. Args: min_date (string): optional. date. Limits the search result timeframe. max_date (string): optiona... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Orders:
def statsByZipcode(self, min_date='1900-1-1', max_date=None, sample_size=100):
"""For each zipcode, determine the number of orders and the total amount of money has been spent. Args: min_date (string): optional. date. Limits the search result timeframe. max_date (string): optional. date. Limit... | the_stack_v2_python_sparse | data_exploration/dora/orders.py | j-goldsmith/dse203-group-project | train | 0 | |
447a2628a8fd2f102efa973d12b8218c4926567d | [
"zk_client = KazooClient(hosts=','.join(zk_locations), connection_retry=ZK_PERSISTENT_RECONNECTS)\nzk_client.start()\nself.ioloop = io_loop\nself.source = source\nself.start_time = None\nself.status = 'Not started'\nself.finish_time = None\nself.api_methods = api_methods.APIMethods(zk_client)\nself.scheduled_indexe... | <|body_start_0|>
zk_client = KazooClient(hosts=','.join(zk_locations), connection_retry=ZK_PERSISTENT_RECONNECTS)
zk_client.start()
self.ioloop = io_loop
self.source = source
self.start_time = None
self.status = 'Not started'
self.finish_time = None
self.a... | Importer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Importer:
def __init__(self, io_loop, source, zk_locations, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locations: a list - Zookeeper locations. max_concurrency: an int - maximum number of concurrent jobs.""... | stack_v2_sparse_classes_75kplus_train_067439 | 6,138 | permissive | [
{
"docstring": "Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locations: a list - Zookeeper locations. max_concurrency: an int - maximum number of concurrent jobs.",
"name": "__init__",
"signature": "def __init__(self, io_loop, source, zk_locatio... | 4 | stack_v2_sparse_classes_30k_test_002736 | Implement the Python class `Importer` described below.
Class description:
Implement the Importer class.
Method signatures and docstrings:
- def __init__(self, io_loop, source, zk_locations, max_concurrency): Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locati... | Implement the Python class `Importer` described below.
Class description:
Implement the Importer class.
Method signatures and docstrings:
- def __init__(self, io_loop, source, zk_locations, max_concurrency): Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locati... | be17e5f658d7b42b5aa7eeb7a5ddd4962f3ea82f | <|skeleton|>
class Importer:
def __init__(self, io_loop, source, zk_locations, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locations: a list - Zookeeper locations. max_concurrency: an int - maximum number of concurrent jobs.""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Importer:
def __init__(self, io_loop, source, zk_locations, max_concurrency):
"""Args: io_loop: an instance of tornado IOLoop. source: an instance of import Source (e.g.: S3Source). zk_locations: a list - Zookeeper locations. max_concurrency: an int - maximum number of concurrent jobs."""
zk_c... | the_stack_v2_python_sparse | SearchService2/appscale/search/backup_restore/restore_to_v2.py | obino/appscale | train | 1 | |
7942d5556e07b63ce4e8bf5fc006d31ecfd4ea81 | [
"staff_orser_event_qs = StaffOrderEvent.query(**search_info)\nstaff_orser_event_qs = staff_orser_event_qs.order_by('-create_time')\nreturn Splitor(current_page, staff_orser_event_qs)",
"try:\n return StaffOrderEvent.query(order=order)[0]\nexcept:\n return None",
"try:\n return StaffOrderEvent.search(st... | <|body_start_0|>
staff_orser_event_qs = StaffOrderEvent.query(**search_info)
staff_orser_event_qs = staff_orser_event_qs.order_by('-create_time')
return Splitor(current_page, staff_orser_event_qs)
<|end_body_0|>
<|body_start_1|>
try:
return StaffOrderEvent.query(order=order)... | StaffOrderEventServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StaffOrderEventServer:
def search(cls, current_page, **search_info):
"""查询事件列表"""
<|body_0|>
def get_event_byorder(cls, order):
"""通过订单查询事件"""
<|body_1|>
def get_event_bystaff(cls, staff_list):
"""通过员工查询事件"""
<|body_2|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_067440 | 5,325 | no_license | [
{
"docstring": "查询事件列表",
"name": "search",
"signature": "def search(cls, current_page, **search_info)"
},
{
"docstring": "通过订单查询事件",
"name": "get_event_byorder",
"signature": "def get_event_byorder(cls, order)"
},
{
"docstring": "通过员工查询事件",
"name": "get_event_bystaff",
"s... | 3 | stack_v2_sparse_classes_30k_train_009593 | Implement the Python class `StaffOrderEventServer` described below.
Class description:
Implement the StaffOrderEventServer class.
Method signatures and docstrings:
- def search(cls, current_page, **search_info): 查询事件列表
- def get_event_byorder(cls, order): 通过订单查询事件
- def get_event_bystaff(cls, staff_list): 通过员工查询事件 | Implement the Python class `StaffOrderEventServer` described below.
Class description:
Implement the StaffOrderEventServer class.
Method signatures and docstrings:
- def search(cls, current_page, **search_info): 查询事件列表
- def get_event_byorder(cls, order): 通过订单查询事件
- def get_event_bystaff(cls, staff_list): 通过员工查询事件
<... | c22e772bc24381f7f57e1d6e41ae0289e7f11e57 | <|skeleton|>
class StaffOrderEventServer:
def search(cls, current_page, **search_info):
"""查询事件列表"""
<|body_0|>
def get_event_byorder(cls, order):
"""通过订单查询事件"""
<|body_1|>
def get_event_bystaff(cls, staff_list):
"""通过员工查询事件"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StaffOrderEventServer:
def search(cls, current_page, **search_info):
"""查询事件列表"""
staff_orser_event_qs = StaffOrderEvent.query(**search_info)
staff_orser_event_qs = staff_orser_event_qs.order_by('-create_time')
return Splitor(current_page, staff_orser_event_qs)
def get_eve... | the_stack_v2_python_sparse | codes/crm-be/tuoen/abs/service/order/manager.py | MaseraTiGo/Maserati_Go | train | 0 | |
2e2fee5932ac93c2a07c63bb4fa7628b1d9d03d6 | [
"LeoCloudIOBase.__init__(self, c, p, kwargs)\nself.basepath = os.path.expanduser(kwargs['root'])\nif not os.path.exists(self.basepath):\n os.makedirs(self.basepath)",
"filepath = os.path.join(self.basepath, lc_id + '.json')\nwith open(filepath) as data:\n return json.load(data)",
"filepath = os.path.join(... | <|body_start_0|>
LeoCloudIOBase.__init__(self, c, p, kwargs)
self.basepath = os.path.expanduser(kwargs['root'])
if not os.path.exists(self.basepath):
os.makedirs(self.basepath)
<|end_body_0|>
<|body_start_1|>
filepath = os.path.join(self.basepath, lc_id + '.json')
wi... | Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing | LeoCloudIOFileSystem | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeoCloudIOFileSystem:
"""Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing"""
def __init__(self, c, p, kwargs):
"""Args: basepath (str): root folder for data"""
<|body_0|>
def get_data(self, lc_id):
"""get_data - get ... | stack_v2_sparse_classes_75kplus_train_067441 | 26,949 | permissive | [
{
"docstring": "Args: basepath (str): root folder for data",
"name": "__init__",
"signature": "def __init__(self, c, p, kwargs)"
},
{
"docstring": "get_data - get a Leo Cloud resource Args: lc_id (str(?)): resource to get Returns: object loaded from JSON",
"name": "get_data",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_003501 | Implement the Python class `LeoCloudIOFileSystem` described below.
Class description:
Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing
Method signatures and docstrings:
- def __init__(self, c, p, kwargs): Args: basepath (str): root folder for data
- def get_data(self, lc... | Implement the Python class `LeoCloudIOFileSystem` described below.
Class description:
Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing
Method signatures and docstrings:
- def __init__(self, c, p, kwargs): Args: basepath (str): root folder for data
- def get_data(self, lc... | a3f6c3ebda805dc40cd93123948f153a26eccee5 | <|skeleton|>
class LeoCloudIOFileSystem:
"""Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing"""
def __init__(self, c, p, kwargs):
"""Args: basepath (str): root folder for data"""
<|body_0|>
def get_data(self, lc_id):
"""get_data - get ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LeoCloudIOFileSystem:
"""Leo Cloud IO layer that just loads / saves local files. i.e it's just for development / testing"""
def __init__(self, c, p, kwargs):
"""Args: basepath (str): root folder for data"""
LeoCloudIOBase.__init__(self, c, p, kwargs)
self.basepath = os.path.expand... | the_stack_v2_python_sparse | leo/plugins/leo_cloud.py | leo-editor/leo-editor | train | 1,671 |
174ef5425da4c050a820da829e8e8bad350e1da7 | [
"CHOICES = ('dark', 'caramel', 'mint', 'surprise', 'stats', 'shutdown')\nchoice = 'dark'\nself.chocolate_machine = ChocolateMachine(CHOICES)\nself.selection = CHOCOLATE_CHOICES[choice]",
"d_raw_materials = {'sugar': 2, 'butter': 2, 'caramel': 15, 'dark chocolate': 30, 'mint chocolate': 30, 'milk chocolate': 30, '... | <|body_start_0|>
CHOICES = ('dark', 'caramel', 'mint', 'surprise', 'stats', 'shutdown')
choice = 'dark'
self.chocolate_machine = ChocolateMachine(CHOICES)
self.selection = CHOCOLATE_CHOICES[choice]
<|end_body_0|>
<|body_start_1|>
d_raw_materials = {'sugar': 2, 'butter': 2, 'cara... | Test class to test chocolate_machine module | TestChocolateMachine | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestChocolateMachine:
"""Test class to test chocolate_machine module"""
def setUp(self):
"""setUp class"""
<|body_0|>
def test_stats(self):
"""test stats functionality"""
<|body_1|>
def test_has_raw_materials(self):
"""test has_raw_materials ... | stack_v2_sparse_classes_75kplus_train_067442 | 4,538 | permissive | [
{
"docstring": "setUp class",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "test stats functionality",
"name": "test_stats",
"signature": "def test_stats(self)"
},
{
"docstring": "test has_raw_materials functionality",
"name": "test_has_raw_materials",
... | 5 | stack_v2_sparse_classes_30k_test_002771 | Implement the Python class `TestChocolateMachine` described below.
Class description:
Test class to test chocolate_machine module
Method signatures and docstrings:
- def setUp(self): setUp class
- def test_stats(self): test stats functionality
- def test_has_raw_materials(self): test has_raw_materials functionality
-... | Implement the Python class `TestChocolateMachine` described below.
Class description:
Test class to test chocolate_machine module
Method signatures and docstrings:
- def setUp(self): setUp class
- def test_stats(self): test stats functionality
- def test_has_raw_materials(self): test has_raw_materials functionality
-... | 3ad0990ee100d0dcf7a69a6851ce84ba262a6f5e | <|skeleton|>
class TestChocolateMachine:
"""Test class to test chocolate_machine module"""
def setUp(self):
"""setUp class"""
<|body_0|>
def test_stats(self):
"""test stats functionality"""
<|body_1|>
def test_has_raw_materials(self):
"""test has_raw_materials ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestChocolateMachine:
"""Test class to test chocolate_machine module"""
def setUp(self):
"""setUp class"""
CHOICES = ('dark', 'caramel', 'mint', 'surprise', 'stats', 'shutdown')
choice = 'dark'
self.chocolate_machine = ChocolateMachine(CHOICES)
self.selection = CHO... | the_stack_v2_python_sparse | Part_7_Unittest/p_0006_wonka_chocolate_machine/test_chocolate_machine.py | mytechnotalent/Python-For-Kids | train | 697 |
f1f1617b69267399b90f989cb1ffaf1e7f911d32 | [
"BaseMailingProcess.__init__(self)\nself.user = None\nself.unit_problem = None\nself.stripe_session = None\nself.future_pro_user = None",
"self.user = user\nself.unit_problem = problem\nself.stripe_session = stripe_session\nself.future_pro_user = future_pro_user\ngateway_token = generate_gateway_token()\nbackslas... | <|body_start_0|>
BaseMailingProcess.__init__(self)
self.user = None
self.unit_problem = None
self.stripe_session = None
self.future_pro_user = None
<|end_body_0|>
<|body_start_1|>
self.user = user
self.unit_problem = problem
self.stripe_session = stripe_s... | UnitMailingProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UnitMailingProcess:
def __init__(self):
"""The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit mail with the solution is directly sent)"""
<|body_0|>
def run(self, user, problem, stripe_se... | stack_v2_sparse_classes_75kplus_train_067443 | 24,237 | no_license | [
{
"docstring": "The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit mail with the solution is directly sent)",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run the unit mailing proc... | 2 | stack_v2_sparse_classes_30k_train_005850 | Implement the Python class `UnitMailingProcess` described below.
Class description:
Implement the UnitMailingProcess class.
Method signatures and docstrings:
- def __init__(self): The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit... | Implement the Python class `UnitMailingProcess` described below.
Class description:
Implement the UnitMailingProcess class.
Method signatures and docstrings:
- def __init__(self): The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit... | 048e349a413b075da9cc0e0b497c40ab6620e245 | <|skeleton|>
class UnitMailingProcess:
def __init__(self):
"""The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit mail with the solution is directly sent)"""
<|body_0|>
def run(self, user, problem, stripe_se... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UnitMailingProcess:
def __init__(self):
"""The UnitMailingProcess handle the core logic for sending one mail given a problem. It's when a user decide to go for the PRO offer (a unit mail with the solution is directly sent)"""
BaseMailingProcess.__init__(self)
self.user = None
s... | the_stack_v2_python_sparse | 1interviewparjour/oneinterviewparjour/mail_scheduler/engine.py | gabrielmougard/1interviewparjour | train | 1 | |
23a074fc3d6d6deb18ded23cbf8b2d2b4d04c29b | [
"things = self.model_factory.create_batch(20)\ntable = self.table_class(things)\nself.assertEqual(self.model.objects.count(), len(table.rows))",
"things = self.model_factory.create_batch(20)\ntable = self.table_class(things)\nrow = table.rows[0]\nself.assertIn(row.record.i_trait_name, row.get_cell_value('i_trait_... | <|body_start_0|>
things = self.model_factory.create_batch(20)
table = self.table_class(things)
self.assertEqual(self.model.objects.count(), len(table.rows))
<|end_body_0|>
<|body_start_1|>
things = self.model_factory.create_batch(20)
table = self.table_class(things)
row ... | SourceTraitTableTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceTraitTableTest:
def test_row_count(self):
"""Table has expected number of rows."""
<|body_0|>
def test_trait_name(self):
"""Trait name column value is as expected."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
things = self.model_factory.cre... | stack_v2_sparse_classes_75kplus_train_067444 | 9,256 | permissive | [
{
"docstring": "Table has expected number of rows.",
"name": "test_row_count",
"signature": "def test_row_count(self)"
},
{
"docstring": "Trait name column value is as expected.",
"name": "test_trait_name",
"signature": "def test_trait_name(self)"
}
] | 2 | null | Implement the Python class `SourceTraitTableTest` described below.
Class description:
Implement the SourceTraitTableTest class.
Method signatures and docstrings:
- def test_row_count(self): Table has expected number of rows.
- def test_trait_name(self): Trait name column value is as expected. | Implement the Python class `SourceTraitTableTest` described below.
Class description:
Implement the SourceTraitTableTest class.
Method signatures and docstrings:
- def test_row_count(self): Table has expected number of rows.
- def test_trait_name(self): Trait name column value is as expected.
<|skeleton|>
class Sour... | 89ae277f5ba1357580d78c3527f26200686308a6 | <|skeleton|>
class SourceTraitTableTest:
def test_row_count(self):
"""Table has expected number of rows."""
<|body_0|>
def test_trait_name(self):
"""Trait name column value is as expected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourceTraitTableTest:
def test_row_count(self):
"""Table has expected number of rows."""
things = self.model_factory.create_batch(20)
table = self.table_class(things)
self.assertEqual(self.model.objects.count(), len(table.rows))
def test_trait_name(self):
"""Trait ... | the_stack_v2_python_sparse | trait_browser/test_tables.py | UW-GAC/pie | train | 0 | |
d2cc412e30fb8ab6432776ebfa83e70e630a5bec | [
"super().__init__(cv)\nself._nextrocket = 0\nself._time = 0\nself._cv = cv\nself._pos = pos",
"super().update(dt)\nself._time = self._time + dt\nif self._time > self._nextrocket:\n r = RocketRocket(self._cv, self._pos, 1000, ['red', 'blue', 'yellow', 'chartreuse2'], [500, 500], 3, 3)\n entities.append(r)\n ... | <|body_start_0|>
super().__init__(cv)
self._nextrocket = 0
self._time = 0
self._cv = cv
self._pos = pos
<|end_body_0|>
<|body_start_1|>
super().update(dt)
self._time = self._time + dt
if self._time > self._nextrocket:
r = RocketRocket(self._cv... | RocketRocketLauncher | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old roc... | stack_v2_sparse_classes_75kplus_train_067445 | 16,427 | permissive | [
{
"docstring": "Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old rocket",
"name": "__init__",
"signature": "def __init__(s... | 2 | stack_v2_sparse_classes_30k_train_027180 | Implement the Python class `RocketRocketLauncher` described below.
Class description:
Implement the RocketRocketLauncher class.
Method signatures and docstrings:
- def __init__(self, cv, pos): Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow}... | Implement the Python class `RocketRocketLauncher` described below.
Class description:
Implement the RocketRocketLauncher class.
Method signatures and docstrings:
- def __init__(self, cv, pos): Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow}... | c6b6d80e9d59f5d115ca8b8fc020fcd6cb030af8 | <|skeleton|>
class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old roc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RocketRocketLauncher:
def __init__(self, cv, pos):
"""Barrages the skies with a relentless series of badass explosions. (repetadly executes RocketRocket) Arguments: cv {idontknow} -- the canvas upon which this wonderful display pos {int} -- the position of the new rocket from the old rocket"""
... | the_stack_v2_python_sparse | scripts/sheet9/9.2.py | LennartElbe/PythOnline | train | 0 | |
ee2aed7b3678c8c22b05c04c50adf7571f4228b0 | [
"super(DumpConfiguration, self).__init__(*args, **kwargs)\nself.allow_extras = True\nreturn",
"if self._configspec_source is None:\n self._configspec_source = dump_configspec\nreturn self._configspec_source"
] | <|body_start_0|>
super(DumpConfiguration, self).__init__(*args, **kwargs)
self.allow_extras = True
return
<|end_body_0|>
<|body_start_1|>
if self._configspec_source is None:
self._configspec_source = dump_configspec
return self._configspec_source
<|end_body_1|>
| A configuration for the dump | DumpConfiguration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DumpConfiguration:
"""A configuration for the dump"""
def __init__(self, *args, **kwargs):
"""DumpConfiguration constructor (allow_extras=True)"""
<|body_0|>
def configspec_source(self):
"""string configuration specification"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus_train_067446 | 18,096 | no_license | [
{
"docstring": "DumpConfiguration constructor (allow_extras=True)",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "string configuration specification",
"name": "configspec_source",
"signature": "def configspec_source(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_033130 | Implement the Python class `DumpConfiguration` described below.
Class description:
A configuration for the dump
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): DumpConfiguration constructor (allow_extras=True)
- def configspec_source(self): string configuration specification | Implement the Python class `DumpConfiguration` described below.
Class description:
A configuration for the dump
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): DumpConfiguration constructor (allow_extras=True)
- def configspec_source(self): string configuration specification
<|skeleton|>
cla... | cd735b8c0fec06f7f9083714900ff88395c9443f | <|skeleton|>
class DumpConfiguration:
"""A configuration for the dump"""
def __init__(self, *args, **kwargs):
"""DumpConfiguration constructor (allow_extras=True)"""
<|body_0|>
def configspec_source(self):
"""string configuration specification"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DumpConfiguration:
"""A configuration for the dump"""
def __init__(self, *args, **kwargs):
"""DumpConfiguration constructor (allow_extras=True)"""
super(DumpConfiguration, self).__init__(*args, **kwargs)
self.allow_extras = True
return
def configspec_source(self):
... | the_stack_v2_python_sparse | cameraobscura/plugins/rvrplugin.py | russell-n/cameraobscura | train | 0 |
2955a24ef7d61ddce4e07a01bdd518262cab889f | [
"differentiator.refresh()\nop = differentiator.generate_differentiable_op(sampled_op=op)\nqubit = cirq.GridQubit(0, 0)\ncircuit = util.convert_to_tensor([cirq.Circuit(cirq.X(qubit) ** sympy.Symbol('alpha'))])\npsums = util.convert_to_tensor([[cirq.Z(qubit)]])\nsymbol_values_array = np.array([[0.123]], dtype=np.floa... | <|body_start_0|>
differentiator.refresh()
op = differentiator.generate_differentiable_op(sampled_op=op)
qubit = cirq.GridQubit(0, 0)
circuit = util.convert_to_tensor([cirq.Circuit(cirq.X(qubit) ** sympy.Symbol('alpha'))])
psums = util.convert_to_tensor([[cirq.Z(qubit)]])
... | Test approximate correctness of noisy methods. | NoisyGradientCorrectnessTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NoisyGradientCorrectnessTest:
"""Test approximate correctness of noisy methods."""
def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples):
"""Test the value of sampled differentiator with simple circuit."""
<|body_0|>
def test_approx_equality_s... | stack_v2_sparse_classes_75kplus_train_067447 | 22,303 | permissive | [
{
"docstring": "Test the value of sampled differentiator with simple circuit.",
"name": "test_sampled_value_with_simple_circuit",
"signature": "def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples)"
},
{
"docstring": "Test small circuits with limited depth.",
"nam... | 3 | stack_v2_sparse_classes_30k_train_021605 | Implement the Python class `NoisyGradientCorrectnessTest` described below.
Class description:
Test approximate correctness of noisy methods.
Method signatures and docstrings:
- def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples): Test the value of sampled differentiator with simple circu... | Implement the Python class `NoisyGradientCorrectnessTest` described below.
Class description:
Test approximate correctness of noisy methods.
Method signatures and docstrings:
- def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples): Test the value of sampled differentiator with simple circu... | f56257bceb988b743790e1e480eac76fd036d4ff | <|skeleton|>
class NoisyGradientCorrectnessTest:
"""Test approximate correctness of noisy methods."""
def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples):
"""Test the value of sampled differentiator with simple circuit."""
<|body_0|>
def test_approx_equality_s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NoisyGradientCorrectnessTest:
"""Test approximate correctness of noisy methods."""
def test_sampled_value_with_simple_circuit(self, differentiator, op, num_samples):
"""Test the value of sampled differentiator with simple circuit."""
differentiator.refresh()
op = differentiator.ge... | the_stack_v2_python_sparse | tensorflow_quantum/python/differentiators/gradient_test.py | tensorflow/quantum | train | 1,799 |
f4c83df86710cab187ff272df237ae5067e5e0d7 | [
"values = board_config_string.split(delimiter)\ncount = len(values)\nif not values[0]:\n raise ValueError('board_config_string')\nself.name = values[0]\ntry:\n self.difficulty = Difficulty[values[1]]\nexcept:\n self.difficulty = Difficulty.default\ntry:\n self.attribute = CharacterAttribute[values[2]]\n... | <|body_start_0|>
values = board_config_string.split(delimiter)
count = len(values)
if not values[0]:
raise ValueError('board_config_string')
self.name = values[0]
try:
self.difficulty = Difficulty[values[1]]
except:
self.difficulty = Di... | Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default difficulty for this board. attribute (script... | BoardConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default diffi... | stack_v2_sparse_classes_75kplus_train_067448 | 2,453 | permissive | [
{
"docstring": "Initialises the BoardConfig instance. Args: board_config_string (str): The board configuration string. This is a packed string containing up to four options, delimited by `delimiter`. E.G.:: 'board_name|difficulty|attribute|user' If the user field is not specified, then it defaults to `all_cards... | 2 | stack_v2_sparse_classes_30k_test_001299 | Implement the Python class `BoardConfig` described below.
Class description:
Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (sc... | Implement the Python class `BoardConfig` described below.
Class description:
Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (sc... | 0d0cf71814e98954850891fa0887bdcffcf7147d | <|skeleton|>
class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default diffi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BoardConfig:
"""Board configuration details, parsed from the command line arguments. Attributes: name (str): the board name. all_cards (bool): If True, all cards should be used; otherwise only cards assigned to the current user should be used. difficulty (scriptabit.Difficulty): the default difficulty for thi... | the_stack_v2_python_sparse | scriptabit/plugins/trello/board_config.py | DC23/scriptabit | train | 10 |
7360adda5d8607c2abe59635521d999d501126f2 | [
"examples, metadata = tfds.load('ted_hrlr_translate/pt_to_en', with_info=True, as_supervised=True)\nself.data_train = examples['train']\nself.data_valid = examples['validation']\nPT, EN = self.tokenize_dataset(self.data_train)\nself.tokenizer_pt, self.tokenizer_en = (PT, EN)",
"tokenizer_en = tfds.features.text.S... | <|body_start_0|>
examples, metadata = tfds.load('ted_hrlr_translate/pt_to_en', with_info=True, as_supervised=True)
self.data_train = examples['train']
self.data_valid = examples['validation']
PT, EN = self.tokenize_dataset(self.data_train)
self.tokenizer_pt, self.tokenizer_en = (... | Class Dataset | Dataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Class Dataset"""
def __init__(self):
"""* data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset validate split, loaded as_supervided * token... | stack_v2_sparse_classes_75kplus_train_067449 | 1,982 | no_license | [
{
"docstring": "* data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset validate split, loaded as_supervided * tokenizer_pt is the Portuguese tokenizer created from the training se... | 2 | stack_v2_sparse_classes_30k_train_053752 | Implement the Python class `Dataset` described below.
Class description:
Class Dataset
Method signatures and docstrings:
- def __init__(self): * data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.... | Implement the Python class `Dataset` described below.
Class description:
Class Dataset
Method signatures and docstrings:
- def __init__(self): * data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class Dataset:
"""Class Dataset"""
def __init__(self):
"""* data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset validate split, loaded as_supervided * token... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dataset:
"""Class Dataset"""
def __init__(self):
"""* data_train, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset train split, loaded as_supervided * data_valid, which contains the ted_hrlr_translate/pt_to_en tf.data.Dataset validate split, loaded as_supervided * tokenizer_pt is th... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/0-dataset.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
b2502ba68a4bf752c0f29effc64c3d37b8e977ad | [
"if not root:\n return None\nif root.val < L:\n root = self.trimBST(root.right, L, R)\nelif root.val > R:\n root = self.trimBST(root.left, L, R)\nelse:\n root.left = self.trimBST(root.left, L, R)\n root.right = self.trimBST(root.right, L, R)\nreturn root",
"if not root:\n return None\ncontour = ... | <|body_start_0|>
if not root:
return None
if root.val < L:
root = self.trimBST(root.right, L, R)
elif root.val > R:
root = self.trimBST(root.left, L, R)
else:
root.left = self.trimBST(root.left, L, R)
root.right = self.trimBST(r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trimBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: TreeNode"""
<|body_0|>
def trimBST2_WRONG(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_067450 | 4,018 | no_license | [
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: TreeNode",
"name": "trimBST",
"signature": "def trimBST(self, root, L, R)"
},
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: TreeNode",
"name": "trimBST2_WRONG",
"signature": "def trimBST2_WRON... | 2 | stack_v2_sparse_classes_30k_train_042731 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trimBST(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: TreeNode
- def trimBST2_WRONG(self, root, L, R): :type root: TreeNode :type L: int :type R: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trimBST(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: TreeNode
- def trimBST2_WRONG(self, root, L, R): :type root: TreeNode :type L: int :type R: ... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def trimBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: TreeNode"""
<|body_0|>
def trimBST2_WRONG(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def trimBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: TreeNode"""
if not root:
return None
if root.val < L:
root = self.trimBST(root.right, L, R)
elif root.val > R:
root = self.trimBST(root.left, L... | the_stack_v2_python_sparse | code669TrimABinarySearchTree.py | cybelewang/leetcode-python | train | 0 | |
50e3429995b38107c4c50ff208aac2ee12d8fd09 | [
"try:\n queryEstate = self.queryEstate_parameter(xiaoqu_Name=estateName)\n logging.info(queryEstate)\n estateId = queryEstate[0]\n estateName = queryEstate[1]\n querySubEstates = self.querySubEstates_parameter(estateId=estateId)\n logging.info(querySubEstates)\n subEstateId = querySubEstates[1]... | <|body_start_0|>
try:
queryEstate = self.queryEstate_parameter(xiaoqu_Name=estateName)
logging.info(queryEstate)
estateId = queryEstate[0]
estateName = queryEstate[1]
querySubEstates = self.querySubEstates_parameter(estateId=estateId)
loggi... | 创建房屋 | Create_house | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Create_house:
"""创建房屋"""
def rented_house(self, estateName=''):
"""创建合租房屋"""
<|body_0|>
def rented_house_create_apply(self, estateName=''):
"""创建房源并且填写房间信息，且申请装锁成功"""
<|body_1|>
def rented_house_delete(self, estateName=''):
"""创建房源并且删除房屋"""
... | stack_v2_sparse_classes_75kplus_train_067451 | 6,277 | no_license | [
{
"docstring": "创建合租房屋",
"name": "rented_house",
"signature": "def rented_house(self, estateName='')"
},
{
"docstring": "创建房源并且填写房间信息，且申请装锁成功",
"name": "rented_house_create_apply",
"signature": "def rented_house_create_apply(self, estateName='')"
},
{
"docstring": "创建房源并且删除房屋",
... | 5 | null | Implement the Python class `Create_house` described below.
Class description:
创建房屋
Method signatures and docstrings:
- def rented_house(self, estateName=''): 创建合租房屋
- def rented_house_create_apply(self, estateName=''): 创建房源并且填写房间信息，且申请装锁成功
- def rented_house_delete(self, estateName=''): 创建房源并且删除房屋
- def rented_house_... | Implement the Python class `Create_house` described below.
Class description:
创建房屋
Method signatures and docstrings:
- def rented_house(self, estateName=''): 创建合租房屋
- def rented_house_create_apply(self, estateName=''): 创建房源并且填写房间信息，且申请装锁成功
- def rented_house_delete(self, estateName=''): 创建房源并且删除房屋
- def rented_house_... | e173d4e535ac22b72b67371b8a2524ee425cdcbf | <|skeleton|>
class Create_house:
"""创建房屋"""
def rented_house(self, estateName=''):
"""创建合租房屋"""
<|body_0|>
def rented_house_create_apply(self, estateName=''):
"""创建房源并且填写房间信息，且申请装锁成功"""
<|body_1|>
def rented_house_delete(self, estateName=''):
"""创建房源并且删除房屋"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Create_house:
"""创建房屋"""
def rented_house(self, estateName=''):
"""创建合租房屋"""
try:
queryEstate = self.queryEstate_parameter(xiaoqu_Name=estateName)
logging.info(queryEstate)
estateId = queryEstate[0]
estateName = queryEstate[1]
qu... | the_stack_v2_python_sparse | public/aYiLou_fangdong/yilou_fangdong_operation_flow/Business_process.py | GSIL-Monitor/mrbao_python | train | 0 |
a3db018269fd598436ba04f10bdc6860f888b833 | [
"build_directory = self.stage.source_path\nif self.spec.variants['build_type'].value == 'Debug':\n build_directory = join_path(build_directory, 'build', 'debug')\nelse:\n build_directory = join_path(build_directory, 'build', 'release')\nreturn build_directory",
"spec = self.spec\nargs = ['../..', '-DCMAKE_I... | <|body_start_0|>
build_directory = self.stage.source_path
if self.spec.variants['build_type'].value == 'Debug':
build_directory = join_path(build_directory, 'build', 'debug')
else:
build_directory = join_path(build_directory, 'build', 'release')
return build_direc... | AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPMV function with CSR and ELLPACK formats. | AoclSparse | [
"Apache-2.0",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"LGPL-2.1-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AoclSparse:
"""AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPMV function with CSR and ELLPACK formats... | stack_v2_sparse_classes_75kplus_train_067452 | 3,906 | permissive | [
{
"docstring": "Returns the directory to use when building the package :return: directory where to build the package",
"name": "build_directory",
"signature": "def build_directory(self)"
},
{
"docstring": "Runs ``cmake`` in the build directory",
"name": "cmake_args",
"signature": "def cm... | 3 | stack_v2_sparse_classes_30k_train_013791 | Implement the Python class `AoclSparse` described below.
Class description:
AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPM... | Implement the Python class `AoclSparse` described below.
Class description:
AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPM... | 6c2df00443a2cd092446c7d84431ae37e64e4296 | <|skeleton|>
class AoclSparse:
"""AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPMV function with CSR and ELLPACK formats... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AoclSparse:
"""AOCL-Sparse is a library that contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD EPYC family of processors. It is designed to be used with C and C++. Current functionality of sparse library supports SPMV function with CSR and ELLPACK formats."""
def... | the_stack_v2_python_sparse | var/spack/repos/builtin/packages/aocl-sparse/package.py | JayjeetAtGithub/spack | train | 0 |
694f2c32d491f7891ab522fa1f2d0488e09bdb6f | [
"self.visitedNodes = set()\nself.validNodes = set(validNodes)\nself.next_node_to_visit = [node]\nself.next_node = None",
"self.visitedNodes.add(node)\nself.next_node_to_visit.extend(node.edges)\nself.next_node = node",
"if self.next_node is not None:\n return True\nif len(self.next_node_to_visit) < 1:\n r... | <|body_start_0|>
self.visitedNodes = set()
self.validNodes = set(validNodes)
self.next_node_to_visit = [node]
self.next_node = None
<|end_body_0|>
<|body_start_1|>
self.visitedNodes.add(node)
self.next_node_to_visit.extend(node.edges)
self.next_node = node
<|end_... | Walk through the connected nodes with BFS | BFS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BFS:
"""Walk through the connected nodes with BFS"""
def __init__(self, node, validNodes):
""":param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse"""
<|body_0|>
def visit_node(self, node):
"""Visits the given node... | stack_v2_sparse_classes_75kplus_train_067453 | 15,542 | permissive | [
{
"docstring": ":param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse",
"name": "__init__",
"signature": "def __init__(self, node, validNodes)"
},
{
"docstring": "Visits the given node :param node: the node to visit",
"name": "visit_node",
... | 4 | null | Implement the Python class `BFS` described below.
Class description:
Walk through the connected nodes with BFS
Method signatures and docstrings:
- def __init__(self, node, validNodes): :param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse
- def visit_node(self, node): ... | Implement the Python class `BFS` described below.
Class description:
Walk through the connected nodes with BFS
Method signatures and docstrings:
- def __init__(self, node, validNodes): :param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse
- def visit_node(self, node): ... | 64f360fd97410682e9f88a37373e1f64b89b62a4 | <|skeleton|>
class BFS:
"""Walk through the connected nodes with BFS"""
def __init__(self, node, validNodes):
""":param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse"""
<|body_0|>
def visit_node(self, node):
"""Visits the given node... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BFS:
"""Walk through the connected nodes with BFS"""
def __init__(self, node, validNodes):
""":param node: the starting node :param validNodes: the set of valid nodes that this BFS will transverse"""
self.visitedNodes = set()
self.validNodes = set(validNodes)
self.next_nod... | the_stack_v2_python_sparse | sbp_env/utils/common.py | soraxas/sbp-env | train | 16 |
83d6930320f6613c25436c740822fab1b5aa44b3 | [
"if not tx_id:\n return False\nif order.sys_tx_id == tx_id:\n return False\nif order.mch_tx_id == tx_id:\n return False\nreturn True",
"if not channel:\n return False\norder_channel = channel_dict.get(order.channel_id)\nif not order_channel:\n return True\nif order_channel.channel_enum == channel:\... | <|body_start_0|>
if not tx_id:
return False
if order.sys_tx_id == tx_id:
return False
if order.mch_tx_id == tx_id:
return False
return True
<|end_body_0|>
<|body_start_1|>
if not channel:
return False
order_channel = channe... | OrderFilters | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderFilters:
def filter_tx_id(cls, tx_id, order):
"""根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤"""
<|body_0|>
def filter_channel(cls, channel_dict, channel, order):
"""根据交易通道类型过滤 :param channel_dict: :param channel: :param order: :return: True... | stack_v2_sparse_classes_75kplus_train_067454 | 14,827 | no_license | [
{
"docstring": "根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤",
"name": "filter_tx_id",
"signature": "def filter_tx_id(cls, tx_id, order)"
},
{
"docstring": "根据交易通道类型过滤 :param channel_dict: :param channel: :param order: :return: True: 过滤；False：不过滤",
"name": "filter_channe... | 5 | stack_v2_sparse_classes_30k_train_048330 | Implement the Python class `OrderFilters` described below.
Class description:
Implement the OrderFilters class.
Method signatures and docstrings:
- def filter_tx_id(cls, tx_id, order): 根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤
- def filter_channel(cls, channel_dict, channel, order): 根据交易通道类型过滤... | Implement the Python class `OrderFilters` described below.
Class description:
Implement the OrderFilters class.
Method signatures and docstrings:
- def filter_tx_id(cls, tx_id, order): 根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤
- def filter_channel(cls, channel_dict, channel, order): 根据交易通道类型过滤... | ff36deb73e667de16a73b1666bbeaf28f993f944 | <|skeleton|>
class OrderFilters:
def filter_tx_id(cls, tx_id, order):
"""根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤"""
<|body_0|>
def filter_channel(cls, channel_dict, channel, order):
"""根据交易通道类型过滤 :param channel_dict: :param channel: :param order: :return: True... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OrderFilters:
def filter_tx_id(cls, tx_id, order):
"""根据交易ID来过滤 :param tx_id: :param order: :return: True: 过滤；False：不过滤"""
if not tx_id:
return False
if order.sys_tx_id == tx_id:
return False
if order.mch_tx_id == tx_id:
return False
... | the_stack_v2_python_sparse | backend/app/logics/backoffice/order_list_helper.py | LyanJin/check-pay | train | 0 | |
6082b5b7f56dbd47afdd762443e3491b517aff30 | [
"self.A_ = A\nself.coeff_ = coeff\nself.xmin_ = xmin\nself.xSpan_ = xSpan",
"nc = len(self.coeff_) / 2\nA = np.ones(nc * 2) * 0.5\nA[1] = x\nA[2::2] = np.sin(2.0 * np.pi * np.arange(1, nc) * (x - self.xmin_) / self.xSpan_)\nA[3::2] = np.cos(2.0 * np.pi * np.arange(1, nc) * (x - self.xmin_) / self.xSpan_)\nreturn ... | <|body_start_0|>
self.A_ = A
self.coeff_ = coeff
self.xmin_ = xmin
self.xSpan_ = xSpan
<|end_body_0|>
<|body_start_1|>
nc = len(self.coeff_) / 2
A = np.ones(nc * 2) * 0.5
A[1] = x
A[2::2] = np.sin(2.0 * np.pi * np.arange(1, nc) * (x - self.xmin_) / self.x... | Functor for harmonic functions plus offset and drift. | HarmFunctor | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HarmFunctor:
"""Functor for harmonic functions plus offset and drift."""
def __init__(self, A, coeff, xmin, xSpan):
"""Initialize."""
<|body_0|>
def __call__(self, x):
"""Yield function call."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_75kplus_train_067455 | 7,677 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, A, coeff, xmin, xSpan)"
},
{
"docstring": "Yield function call.",
"name": "__call__",
"signature": "def __call__(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015889 | Implement the Python class `HarmFunctor` described below.
Class description:
Functor for harmonic functions plus offset and drift.
Method signatures and docstrings:
- def __init__(self, A, coeff, xmin, xSpan): Initialize.
- def __call__(self, x): Yield function call. | Implement the Python class `HarmFunctor` described below.
Class description:
Functor for harmonic functions plus offset and drift.
Method signatures and docstrings:
- def __init__(self, A, coeff, xmin, xSpan): Initialize.
- def __call__(self, x): Yield function call.
<|skeleton|>
class HarmFunctor:
"""Functor fo... | 0f55444b624f390a674053f62ba1a05506deafa6 | <|skeleton|>
class HarmFunctor:
"""Functor for harmonic functions plus offset and drift."""
def __init__(self, A, coeff, xmin, xSpan):
"""Initialize."""
<|body_0|>
def __call__(self, x):
"""Yield function call."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HarmFunctor:
"""Functor for harmonic functions plus offset and drift."""
def __init__(self, A, coeff, xmin, xSpan):
"""Initialize."""
self.A_ = A
self.coeff_ = coeff
self.xmin_ = xmin
self.xSpan_ = xSpan
def __call__(self, x):
"""Yield function call.""... | the_stack_v2_python_sparse | pygimli/frameworks/harmfit.py | gimli-org/gimli | train | 307 |
17abbb44f11fe6e4d095091fb05d61291939d3b1 | [
"self.options.declare('vec_size', types=int, default=1, desc='The number of points at which the vector magnitude is computed')\nself.options.declare('length', types=int, default=3, desc='The length of the input vector at each point')\nself.options.declare('in_name', types=string_types, default='a', desc='The variab... | <|body_start_0|>
self.options.declare('vec_size', types=int, default=1, desc='The number of points at which the vector magnitude is computed')
self.options.declare('length', types=int, default=3, desc='The length of the input vector at each point')
self.options.declare('in_name', types=string_ty... | Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n) | VectorUnitizeComp | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VectorUnitizeComp:
"""Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n)"""
def initialize(self):
"""Declare options."""
<|body_0|>
def setup(self):
"""Declare inputs, outputs, and derivatives for the v... | stack_v2_sparse_classes_75kplus_train_067456 | 4,551 | permissive | [
{
"docstring": "Declare options.",
"name": "initialize",
"signature": "def initialize(self)"
},
{
"docstring": "Declare inputs, outputs, and derivatives for the vector magnitude component.",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Compute the vector mag... | 4 | null | Implement the Python class `VectorUnitizeComp` described below.
Class description:
Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n)
Method signatures and docstrings:
- def initialize(self): Declare options.
- def setup(self): Declare inputs, outputs, and ... | Implement the Python class `VectorUnitizeComp` described below.
Class description:
Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n)
Method signatures and docstrings:
- def initialize(self): Declare options.
- def setup(self): Declare inputs, outputs, and ... | a4ffd61582b8474953fc309aa540838a14f29dcf | <|skeleton|>
class VectorUnitizeComp:
"""Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n)"""
def initialize(self):
"""Declare options."""
<|body_0|>
def setup(self):
"""Declare inputs, outputs, and derivatives for the v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VectorUnitizeComp:
"""Computes the unitized vector math:: \\hat{a} = ar{a} / np.sqrt(np.dot(a, a)) where a is of shape (vec_size, n)"""
def initialize(self):
"""Declare options."""
self.options.declare('vec_size', types=int, default=1, desc='The number of points at which the vector magni... | the_stack_v2_python_sparse | CADRE/attitude_dymos/VectorUnitizeComp.py | johnjasa/CADRE | train | 0 |
1a96938658bb3d23e5e9b6d2b81b9aadc352ee3b | [
"interview: Interview = self.get_object()\nif interview.company.interviews.filter(is_top=True).count() >= 10:\n raise MaxFavoriteInterview\ninterview.is_top = True\ninterview.save()\nserializer: InterviewSerializer = self.get_serializer(interview)\nreturn Response(data=serializer.data, status=status.HTTP_200_OK)... | <|body_start_0|>
interview: Interview = self.get_object()
if interview.company.interviews.filter(is_top=True).count() >= 10:
raise MaxFavoriteInterview
interview.is_top = True
interview.save()
serializer: InterviewSerializer = self.get_serializer(interview)
re... | Interview favorite view. | InterviewTop | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InterviewTop:
"""Interview favorite view."""
def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response:
"""Set the interview as favorite. :param request: Request :return: Interview instance"""
<|body_0|>
def delete(self, request: Request, *args: tuple, *... | stack_v2_sparse_classes_75kplus_train_067457 | 5,804 | no_license | [
{
"docstring": "Set the interview as favorite. :param request: Request :return: Interview instance",
"name": "post",
"signature": "def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response"
},
{
"docstring": "Unset the interview as favorite. :param request: Request :return: Inte... | 2 | null | Implement the Python class `InterviewTop` described below.
Class description:
Interview favorite view.
Method signatures and docstrings:
- def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response: Set the interview as favorite. :param request: Request :return: Interview instance
- def delete(self, r... | Implement the Python class `InterviewTop` described below.
Class description:
Interview favorite view.
Method signatures and docstrings:
- def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response: Set the interview as favorite. :param request: Request :return: Interview instance
- def delete(self, r... | 713b9d84ac70d964d46f189ab1f9c7b944b9684b | <|skeleton|>
class InterviewTop:
"""Interview favorite view."""
def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response:
"""Set the interview as favorite. :param request: Request :return: Interview instance"""
<|body_0|>
def delete(self, request: Request, *args: tuple, *... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InterviewTop:
"""Interview favorite view."""
def post(self, request: Request, *args: tuple, **kwargs: dict) -> Response:
"""Set the interview as favorite. :param request: Request :return: Interview instance"""
interview: Interview = self.get_object()
if interview.company.interview... | the_stack_v2_python_sparse | jobadvisor/reviews/views/interview.py | ewgen19892/jobadvisor | train | 0 |
a6b67a05aa54125d2195b5b30c293370bc4e10cc | [
"base_options = _BaseOptions(model_asset_path=model_path)\noptions = InteractiveSegmenterOptions(base_options=base_options)\nreturn cls.create_from_options(options)",
"output_streams = [':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME])]\nif options.output_confidence_masks:\n output_streams.append(':'.join([_CONFI... | <|body_start_0|>
base_options = _BaseOptions(model_asset_path=model_path)
options = InteractiveSegmenterOptions(base_options=base_options)
return cls.create_from_options(options)
<|end_body_0|>
<|body_start_1|>
output_streams = [':'.join([_IMAGE_TAG, _IMAGE_OUT_STREAM_NAME])]
if... | Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandatory TFLite Model Metadata. Input tensor: (kTfLit... | InteractiveSegmenter | [
"Apache-2.0",
"dtoa"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InteractiveSegmenter:
"""Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandat... | stack_v2_sparse_classes_75kplus_train_067458 | 10,462 | permissive | [
{
"docstring": "Creates an `InteractiveSegmenter` object from a TensorFlow Lite model and the default `InteractiveSegmenterOptions`. Note that the created `InteractiveSegmenter` instance is in image mode, for performing image segmentation on single image inputs. Args: model_path: Path to the model. Returns: `In... | 3 | stack_v2_sparse_classes_30k_train_028476 | Implement the Python class `InteractiveSegmenter` described below.
Class description:
Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The... | Implement the Python class `InteractiveSegmenter` described below.
Class description:
Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The... | 007824594bf1d07c7c1467df03a43886f8a4b3ad | <|skeleton|>
class InteractiveSegmenter:
"""Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandat... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InteractiveSegmenter:
"""Class that performs interactive segmentation on images. Users can represent user interaction through `RegionOfInterest`, which gives a hint to InteractiveSegmenter to perform segmentation focusing on the given region of interest. The API expects a TFLite model with mandatory TFLite Mo... | the_stack_v2_python_sparse | mediapipe/tasks/python/vision/interactive_segmenter.py | google/mediapipe | train | 23,940 |
874dbeffc3a6c99b07837c4dfa9ac138d6a2b4d6 | [
"self._app = app\nself._collection = collection\nself._kv = kv\nself._owner = owner",
"excludes_search = 'NOT ' + '(' + ' OR '.join(['type=\"%s\"' % i for i in excludes_list]) + ')'\ngetargs = {'output_mode': 'json', 'search': excludes_search, 'count': 0}\nupdate_times = {}\nresponse, content = splunk.rest.simple... | <|body_start_0|>
self._app = app
self._collection = collection
self._kv = kv
self._owner = owner
<|end_body_0|>
<|body_start_1|>
excludes_search = 'NOT ' + '(' + ' OR '.join(['type="%s"' % i for i in excludes_list]) + ')'
getargs = {'output_mode': 'json', 'search': exclu... | ThreatIntelMeta | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreatIntelMeta:
def __init__(self, app, collection, kv, owner):
"""Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is housed. collection - The name of the collection. kv - a KVStoreHandler object. owner - The owner of the ... | stack_v2_sparse_classes_75kplus_train_067459 | 39,192 | no_license | [
{
"docstring": "Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is housed. collection - The name of the collection. kv - a KVStoreHandler object. owner - The owner of the collection",
"name": "__init__",
"signature": "def __init__(self, ap... | 4 | stack_v2_sparse_classes_30k_train_008748 | Implement the Python class `ThreatIntelMeta` described below.
Class description:
Implement the ThreatIntelMeta class.
Method signatures and docstrings:
- def __init__(self, app, collection, kv, owner): Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is ... | Implement the Python class `ThreatIntelMeta` described below.
Class description:
Implement the ThreatIntelMeta class.
Method signatures and docstrings:
- def __init__(self, app, collection, kv, owner): Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is ... | 70689c54d1a67e809bf134dd586b2ea05ff4c431 | <|skeleton|>
class ThreatIntelMeta:
def __init__(self, app, collection, kv, owner):
"""Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is housed. collection - The name of the collection. kv - a KVStoreHandler object. owner - The owner of the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThreatIntelMeta:
def __init__(self, app, collection, kv, owner):
"""Initialize a class for handling of threat intel metadata. Arguments: app - The app where the metadata collection is housed. collection - The name of the collection. kv - a KVStoreHandler object. owner - The owner of the collection"""
... | the_stack_v2_python_sparse | DA-ESS-ThreatIntelligence/bin/threat_intelligence_manager.py | reza/es_eventgens | train | 0 | |
6a153b4f0ed1d50bede1bdc3be7752c7ee772ded | [
"try:\n if g.user is None or g.user.is_anonymous:\n return self.response_401()\nexcept NoAuthorizationError:\n return self.response_401()\nreturn self.response(200, result=user_response_schema.dump(g.user))",
"try:\n if g.user is None or g.user.is_anonymous:\n return self.response_401()\nex... | <|body_start_0|>
try:
if g.user is None or g.user.is_anonymous:
return self.response_401()
except NoAuthorizationError:
return self.response_401()
return self.response(200, result=user_response_schema.dump(g.user))
<|end_body_0|>
<|body_start_1|>
... | An api to get information about the current user | CurrentUserRestApi | [
"Apache-2.0",
"OFL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CurrentUserRestApi:
"""An api to get information about the current user"""
def get_me(self) -> Response:
"""Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corresponding to the agent making the request, or returns a 4... | stack_v2_sparse_classes_75kplus_train_067460 | 3,395 | permissive | [
{
"docstring": "Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corresponding to the agent making the request, or returns a 401 error if the user is unauthenticated. responses: 200: description: The current user content: application/json: schema... | 2 | stack_v2_sparse_classes_30k_train_038258 | Implement the Python class `CurrentUserRestApi` described below.
Class description:
An api to get information about the current user
Method signatures and docstrings:
- def get_me(self) -> Response: Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corr... | Implement the Python class `CurrentUserRestApi` described below.
Class description:
An api to get information about the current user
Method signatures and docstrings:
- def get_me(self) -> Response: Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corr... | 0945d4a2f46667aebb9b93d0d7685215627ad237 | <|skeleton|>
class CurrentUserRestApi:
"""An api to get information about the current user"""
def get_me(self) -> Response:
"""Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corresponding to the agent making the request, or returns a 4... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CurrentUserRestApi:
"""An api to get information about the current user"""
def get_me(self) -> Response:
"""Get the user object corresponding to the agent making the request --- get: description: >- Returns the user object corresponding to the agent making the request, or returns a 401 error if t... | the_stack_v2_python_sparse | superset/views/users/api.py | apache-superset/incubator-superset | train | 21 |
f336cd96cf813ec8daa9f4ea73b96fa49779c260 | [
"self.file_path = source_file\nself.public = IdentifierSet()\nself.doxygen_groupings = []\nself.interfaces = IdentifierDict()\nself.subroutines = IdentifierDict()\nself.constants = IdentifierDict()\nself.types = IdentifierDict()\nself.parse_file(params_only)",
"source_lines = _join_lines(open(self.file_path, 'r')... | <|body_start_0|>
self.file_path = source_file
self.public = IdentifierSet()
self.doxygen_groupings = []
self.interfaces = IdentifierDict()
self.subroutines = IdentifierDict()
self.constants = IdentifierDict()
self.types = IdentifierDict()
self.parse_file(p... | Info for an individual source file | SourceFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceFile:
"""Info for an individual source file"""
def __init__(self, source_file, params_only=False):
"""Initialise SourceFile object Arguments: source_file -- Path to the source file"""
<|body_0|>
def parse_file(self, params_only=False):
"""Run through file o... | stack_v2_sparse_classes_75kplus_train_067461 | 28,119 | no_license | [
{
"docstring": "Initialise SourceFile object Arguments: source_file -- Path to the source file",
"name": "__init__",
"signature": "def __init__(self, source_file, params_only=False)"
},
{
"docstring": "Run through file once, getting everything we'll need",
"name": "parse_file",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_035884 | Implement the Python class `SourceFile` described below.
Class description:
Info for an individual source file
Method signatures and docstrings:
- def __init__(self, source_file, params_only=False): Initialise SourceFile object Arguments: source_file -- Path to the source file
- def parse_file(self, params_only=False... | Implement the Python class `SourceFile` described below.
Class description:
Info for an individual source file
Method signatures and docstrings:
- def __init__(self, source_file, params_only=False): Initialise SourceFile object Arguments: source_file -- Path to the source file
- def parse_file(self, params_only=False... | 38c0755396efea44feb87a4c01b5e956d6736691 | <|skeleton|>
class SourceFile:
"""Info for an individual source file"""
def __init__(self, source_file, params_only=False):
"""Initialise SourceFile object Arguments: source_file -- Path to the source file"""
<|body_0|>
def parse_file(self, params_only=False):
"""Run through file o... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SourceFile:
"""Info for an individual source file"""
def __init__(self, source_file, params_only=False):
"""Initialise SourceFile object Arguments: source_file -- Path to the source file"""
self.file_path = source_file
self.public = IdentifierSet()
self.doxygen_groupings =... | the_stack_v2_python_sparse | bindings/generate_bindings/parse.py | OpenCMISS/iron | train | 10 |
40e198602353e77b64080812be3ba2809408dbbe | [
"super().__init__(**kwargs)\ntry:\n from InstructorEmbedding import INSTRUCTOR\n self.client = INSTRUCTOR(self.model_name)\nexcept ImportError as e:\n raise ValueError('Dependencies for InstructorEmbedding not found.') from e",
"instruction_pairs = [[self.embed_instruction, text] for text in texts]\nembe... | <|body_start_0|>
super().__init__(**kwargs)
try:
from InstructorEmbedding import INSTRUCTOR
self.client = INSTRUCTOR(self.model_name)
except ImportError as e:
raise ValueError('Dependencies for InstructorEmbedding not found.') from e
<|end_body_0|>
<|body_sta... | Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings import HuggingFaceInstructEmbeddings model_name = "hkunlp/instructor-large" hf = HuggingFaceInstruc... | HuggingFaceInstructEmbeddings | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HuggingFaceInstructEmbeddings:
"""Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings import HuggingFaceInstructEmbeddings model... | stack_v2_sparse_classes_75kplus_train_067462 | 4,545 | permissive | [
{
"docstring": "Initialize the sentence_transformer.",
"name": "__init__",
"signature": "def __init__(self, **kwargs: Any)"
},
{
"docstring": "Compute doc embeddings using a HuggingFace instruct model. Args: texts: The list of texts to embed. Returns: List of embeddings, one for each text.",
... | 3 | stack_v2_sparse_classes_30k_train_020700 | Implement the Python class `HuggingFaceInstructEmbeddings` described below.
Class description:
Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings imp... | Implement the Python class `HuggingFaceInstructEmbeddings` described below.
Class description:
Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings imp... | b8f29af7f3c24cf3a4554bebfa2053064467fbdb | <|skeleton|>
class HuggingFaceInstructEmbeddings:
"""Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings import HuggingFaceInstructEmbeddings model... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HuggingFaceInstructEmbeddings:
"""Wrapper around sentence_transformers embedding models. To use, you should have the ``sentence_transformers`` and ``InstructorEmbedding`` python package installed. Example: .. code-block:: python from langchain.embeddings import HuggingFaceInstructEmbeddings model_name = "hkun... | the_stack_v2_python_sparse | langchain/embeddings/huggingface.py | microsoft/MM-REACT | train | 705 |
803ab85ac425511dcee71923e21499053c053a5d | [
"self.matrix = matrix\nself.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]\nfor i in range(len(matrix)):\n for j in range(len(matrix[0])):\n if i == 0:\n self.prefix_sum[i][j] = matrix[i][j]\n else:\n self.prefix_sum[i][j] = matrix[i][j] + self.p... | <|body_start_0|>
self.matrix = matrix
self.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
if i == 0:
self.prefix_sum[i][j] = matrix[i][j]
el... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_75kplus_train_067463 | 16,103 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row: int :type col: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, row, col, val)"
},
{
"docstring": ":type r... | 3 | stack_v2_sparse_classes_30k_train_031417 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def update(self, row, col, val): :type row: int :type col: int :type val: int :rtype: void
- def sumRegion(self, row... | fa3704af37d9e04ab6fd13b7b17cc83c239946f7 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def update(self, row, col, val):
""":type row: int :type col: int :type val: int :rtype: void"""
<|body_1|>
def sumRegion(self, row1, col1, row2, col2):
""":typ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
self.matrix = matrix
self.prefix_sum = [[0 for i in range(len(matrix[0]))] for j in range(len(matrix))]
for i in range(len(matrix)):
for j in range(len(matrix[0])):
if i == 0:... | the_stack_v2_python_sparse | lintcode/medium/817_range_sum_query_2d_mutable.py | simonfqy/SimonfqyGitHub | train | 2 | |
93499e764ab2fedf78334f02a049a6fcf22bbf53 | [
"all_data = [self.match.serialize(), struct.pack(self.FORMAT2, self.duration_sec, self.duration_nsec, self.priority, self.idle_timeout, self.hard_timeout, self.cookie, self.packet_count, self.byte_count)]\nfor a in self.actions:\n all_data.extend(serialize_action(a))\nlength = self.FORMAT1_LENGTH + sum((len(d) f... | <|body_start_0|>
all_data = [self.match.serialize(), struct.pack(self.FORMAT2, self.duration_sec, self.duration_nsec, self.priority, self.idle_timeout, self.hard_timeout, self.cookie, self.packet_count, self.byte_count)]
for a in self.actions:
all_data.extend(serialize_action(a))
len... | The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as a 32-bit unsigned integer. duration_nsec: Time flow has been alive in nanose... | FlowStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlowStats:
"""The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as a 32-bit unsigned integer. duration_nse... | stack_v2_sparse_classes_75kplus_train_067464 | 17,066 | permissive | [
{
"docstring": "Serialize this object into an OpenFlow ofp_flow_stats. The returned string can be passed to deserialize() to recreate a copy of this object. Args: serialize_action: A callable with signature serialize_action(action) that takes an Action* object and returns the serialized form of the action as a ... | 2 | stack_v2_sparse_classes_30k_train_005723 | Implement the Python class `FlowStats` described below.
Class description:
The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as ... | Implement the Python class `FlowStats` described below.
Class description:
The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as ... | 4ef1783fc74320e66ee7a71576dc91511f238a81 | <|skeleton|>
class FlowStats:
"""The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as a 32-bit unsigned integer. duration_nse... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FlowStats:
"""The stats about an individual flow. The attributes of the flow statistics are: table_id: The ID of the table the flow came from. match: A Match object describing the fields of the flow. duration_sec: Time the flow has been alive in seconds, as a 32-bit unsigned integer. duration_nsec: Time flow ... | the_stack_v2_python_sparse | src/openfaucet/ofstats.py | bharathi26/openfaucet | train | 0 |
88275f7142b479087596e4887fbb824f1f9597aa | [
"params = base.get_params(None, locals())\nurl = '{0}/deals'.format(self.get_url())\nreturn (http.Request('GET', url, params), parsers.parse_json)",
"params = base.get_params(None, locals())\nurl = '{0}/conversion_statistics'.format(self.get_url())\nreturn (http.Request('GET', url, params), parsers.parse_json)",
... | <|body_start_0|>
params = base.get_params(None, locals())
url = '{0}/deals'.format(self.get_url())
return (http.Request('GET', url, params), parsers.parse_json)
<|end_body_0|>
<|body_start_1|>
params = base.get_params(None, locals())
url = '{0}/conversion_statistics'.format(self... | Pipeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Pipeline:
def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None):
"""Lists deals in a specific pipeline across all its stages. Upstream documentation: https://developers.pipedrive.com/v1#methods-Pipelines"""
<|body_0|>
def convers... | stack_v2_sparse_classes_75kplus_train_067465 | 2,938 | permissive | [
{
"docstring": "Lists deals in a specific pipeline across all its stages. Upstream documentation: https://developers.pipedrive.com/v1#methods-Pipelines",
"name": "deals",
"signature": "def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_train_051583 | Implement the Python class `Pipeline` described below.
Class description:
Implement the Pipeline class.
Method signatures and docstrings:
- def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None): Lists deals in a specific pipeline across all its stages. Upstream documentat... | Implement the Python class `Pipeline` described below.
Class description:
Implement the Pipeline class.
Method signatures and docstrings:
- def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None): Lists deals in a specific pipeline across all its stages. Upstream documentat... | 25caa745a104c8dc209584fa359294c65dbf88bb | <|skeleton|>
class Pipeline:
def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None):
"""Lists deals in a specific pipeline across all its stages. Upstream documentation: https://developers.pipedrive.com/v1#methods-Pipelines"""
<|body_0|>
def convers... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Pipeline:
def deals(self, filter_id=None, user_id=None, everyone=None, stage_id=None, start=None, limit=None):
"""Lists deals in a specific pipeline across all its stages. Upstream documentation: https://developers.pipedrive.com/v1#methods-Pipelines"""
params = base.get_params(None, locals())
... | the_stack_v2_python_sparse | libsaas/services/pipedrive/pipelines.py | piplcom/libsaas | train | 1 | |
00443d1ea00a666e3243f663a74f5c852162aecc | [
"metByAny = False\nfor singleValue in value:\n metByAny = self.MetBy(singleValue, ValueType.SINGLE_VALUE)\n if metByAny:\n break\nreturn metByAny",
"metByAll = True\nfor singleValue in value:\n metByAll = self.MetBy(singleValue, ValueType.SINGLE_VALUE)\n if metByAll == False:\n break\nre... | <|body_start_0|>
metByAny = False
for singleValue in value:
metByAny = self.MetBy(singleValue, ValueType.SINGLE_VALUE)
if metByAny:
break
return metByAny
<|end_body_0|>
<|body_start_1|>
metByAll = True
for singleValue in value:
... | Base-class for all conditions. | Condition | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Condition:
"""Base-class for all conditions."""
def __MetByAny(self, value):
"""In: value - list of values to test. Out: True if condition was met by any in list, False otherwise."""
<|body_0|>
def __MetByAll(self, value):
"""In: value - list of values to test. O... | stack_v2_sparse_classes_75kplus_train_067466 | 6,558 | no_license | [
{
"docstring": "In: value - list of values to test. Out: True if condition was met by any in list, False otherwise.",
"name": "__MetByAny",
"signature": "def __MetByAny(self, value)"
},
{
"docstring": "In: value - list of values to test. Out: True if condition was met by all in list, False other... | 3 | stack_v2_sparse_classes_30k_train_012521 | Implement the Python class `Condition` described below.
Class description:
Base-class for all conditions.
Method signatures and docstrings:
- def __MetByAny(self, value): In: value - list of values to test. Out: True if condition was met by any in list, False otherwise.
- def __MetByAll(self, value): In: value - list... | Implement the Python class `Condition` described below.
Class description:
Base-class for all conditions.
Method signatures and docstrings:
- def __MetByAny(self, value): In: value - list of values to test. Out: True if condition was met by any in list, False otherwise.
- def __MetByAll(self, value): In: value - list... | 5e7cc7de3495145501ca53deb9efee2233ab7e1c | <|skeleton|>
class Condition:
"""Base-class for all conditions."""
def __MetByAny(self, value):
"""In: value - list of values to test. Out: True if condition was met by any in list, False otherwise."""
<|body_0|>
def __MetByAll(self, value):
"""In: value - list of values to test. O... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Condition:
"""Base-class for all conditions."""
def __MetByAny(self, value):
"""In: value - list of values to test. Out: True if condition was met by any in list, False otherwise."""
metByAny = False
for singleValue in value:
metByAny = self.MetBy(singleValue, ValueTyp... | the_stack_v2_python_sparse | Extensions/Default/FPythonCode/FOperationsRuleEngine.py | webclinic017/fa-absa-py3 | train | 0 |
f89139c2774cece69f0e7269000d6edd245210ef | [
"tests = [((8, 8), 1, [(8, 8)]), ((8, 8), 2, [(8, 8), (4, 4)]), ((8, 8), 3, [(8, 8), (4, 4), (2, 2)]), ((8, 8), 4, [(8, 8), (4, 4), (2, 2), (1, 1)])]\nfor i, ((width, height), levels, want_layers) in enumerate(tests):\n image = Image()\n image.create(width, height)\n pyramid = Pyramid(image, levels)\n h... | <|body_start_0|>
tests = [((8, 8), 1, [(8, 8)]), ((8, 8), 2, [(8, 8), (4, 4)]), ((8, 8), 3, [(8, 8), (4, 4), (2, 2)]), ((8, 8), 4, [(8, 8), (4, 4), (2, 2), (1, 1)])]
for i, ((width, height), levels, want_layers) in enumerate(tests):
image = Image()
image.create(width, height)
... | Tests for the Pyramid class. | TestPyramid | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPyramid:
"""Tests for the Pyramid class."""
def test_init(self):
"""Tests the Pyramid.__init__() function."""
<|body_0|>
def test_reconstruct(self):
"""Tests the Pyramid.reconstruct() function."""
<|body_1|>
def test_items(self):
"""Tests... | stack_v2_sparse_classes_75kplus_train_067467 | 2,570 | permissive | [
{
"docstring": "Tests the Pyramid.__init__() function.",
"name": "test_init",
"signature": "def test_init(self)"
},
{
"docstring": "Tests the Pyramid.reconstruct() function.",
"name": "test_reconstruct",
"signature": "def test_reconstruct(self)"
},
{
"docstring": "Tests the Pyram... | 3 | stack_v2_sparse_classes_30k_train_024044 | Implement the Python class `TestPyramid` described below.
Class description:
Tests for the Pyramid class.
Method signatures and docstrings:
- def test_init(self): Tests the Pyramid.__init__() function.
- def test_reconstruct(self): Tests the Pyramid.reconstruct() function.
- def test_items(self): Tests the Pyramid.__... | Implement the Python class `TestPyramid` described below.
Class description:
Tests for the Pyramid class.
Method signatures and docstrings:
- def test_init(self): Tests the Pyramid.__init__() function.
- def test_reconstruct(self): Tests the Pyramid.reconstruct() function.
- def test_items(self): Tests the Pyramid.__... | 7e7282698befd53383cbd6566039340babb0a289 | <|skeleton|>
class TestPyramid:
"""Tests for the Pyramid class."""
def test_init(self):
"""Tests the Pyramid.__init__() function."""
<|body_0|>
def test_reconstruct(self):
"""Tests the Pyramid.reconstruct() function."""
<|body_1|>
def test_items(self):
"""Tests... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestPyramid:
"""Tests for the Pyramid class."""
def test_init(self):
"""Tests the Pyramid.__init__() function."""
tests = [((8, 8), 1, [(8, 8)]), ((8, 8), 2, [(8, 8), (4, 4)]), ((8, 8), 3, [(8, 8), (4, 4), (2, 2)]), ((8, 8), 4, [(8, 8), (4, 4), (2, 2), (1, 1)])]
for i, ((width, he... | the_stack_v2_python_sparse | sandbox/image/pyramid_test.py | Mandrenkov/SVBRDF-Texture-Synthesis | train | 3 |
359eabcdcddd484abe382f0c95c6e34762a8ffcd | [
"np.random.seed(seed)\nself.n_inputs = n_inputs\nself.n_outputs = n_outputs\nself.activation = activation\nself.w = np.random.randn(self.n_inputs, self.n_outputs)\nself.b = np.random.randn(1, self.n_outputs)",
"self.z = X @ self.w + self.b\nself.a = self.activation(self.z)\nself.a_deriv = self.activation.deriv(se... | <|body_start_0|>
np.random.seed(seed)
self.n_inputs = n_inputs
self.n_outputs = n_outputs
self.activation = activation
self.w = np.random.randn(self.n_inputs, self.n_outputs)
self.b = np.random.randn(1, self.n_outputs)
<|end_body_0|>
<|body_start_1|>
self.z = X @... | DenseLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DenseLayer:
def __init__(self, n_inputs, n_outputs, activation, seed=1004):
"""Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs -- number of outputs to the layer activation -- activation function used on input to get output"""... | stack_v2_sparse_classes_75kplus_train_067468 | 5,478 | no_license | [
{
"docstring": "Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs -- number of outputs to the layer activation -- activation function used on input to get output",
"name": "__init__",
"signature": "def __init__(self, n_inputs, n_outputs, activ... | 2 | null | Implement the Python class `DenseLayer` described below.
Class description:
Implement the DenseLayer class.
Method signatures and docstrings:
- def __init__(self, n_inputs, n_outputs, activation, seed=1004): Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs... | Implement the Python class `DenseLayer` described below.
Class description:
Implement the DenseLayer class.
Method signatures and docstrings:
- def __init__(self, n_inputs, n_outputs, activation, seed=1004): Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs... | f9fbe289ebe1e90dddf288a6e713cabc8d02b1f0 | <|skeleton|>
class DenseLayer:
def __init__(self, n_inputs, n_outputs, activation, seed=1004):
"""Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs -- number of outputs to the layer activation -- activation function used on input to get output"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DenseLayer:
def __init__(self, n_inputs, n_outputs, activation, seed=1004):
"""Create one layer in the neural network. Keyword arguments: n_inputs -- number of inputs to the layer n_outputs -- number of outputs to the layer activation -- activation function used on input to get output"""
np.ra... | the_stack_v2_python_sparse | Project2/source/NeuralNetwork.py | elinfi/FYS-STK4155 | train | 1 | |
2ec6bc1ebc4c0d9a6f0ab7cb6626d7b8051cb91e | [
"salt = hashlib.sha1(str(random.random())).hexdigest()[:5]\nuser_pk = str(user.pk)\ntoken_key = hashlib.sha1(salt + user_pk).hexdigest()\nreturn self.create(token_key=token_key, created_by=user, expiration_days=expiration_days, url=url, url_params=url_params)",
"token_key = request.GET.get('tk')\nif token_key and... | <|body_start_0|>
salt = hashlib.sha1(str(random.random())).hexdigest()[:5]
user_pk = str(user.pk)
token_key = hashlib.sha1(salt + user_pk).hexdigest()
return self.create(token_key=token_key, created_by=user, expiration_days=expiration_days, url=url, url_params=url_params)
<|end_body_0|>
... | Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens. | UrlTokenManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UrlTokenManager:
"""Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens."""
def create_url_token(self, user, expiration_days, url, url_params=None):
"""Create a ``UrlToken`` for a given ``url`` a... | stack_v2_sparse_classes_75kplus_train_067469 | 2,760 | no_license | [
{
"docstring": "Create a ``UrlToken`` for a given ``url`` and ``days``, and return the ``UrlToken``. The token key for the ``UrlToken`` will be a SHA1 hash, generated from a combination of the ``url``, days and a random salt.",
"name": "create_url_token",
"signature": "def create_url_token(self, user, e... | 2 | stack_v2_sparse_classes_30k_test_002202 | Implement the Python class `UrlTokenManager` described below.
Class description:
Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens.
Method signatures and docstrings:
- def create_url_token(self, user, expiration_days, url, url_... | Implement the Python class `UrlTokenManager` described below.
Class description:
Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens.
Method signatures and docstrings:
- def create_url_token(self, user, expiration_days, url, url_... | 8d8be00502977431297d2138f72d153695b9f06a | <|skeleton|>
class UrlTokenManager:
"""Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens."""
def create_url_token(self, user, expiration_days, url, url_params=None):
"""Create a ``UrlToken`` for a given ``url`` a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UrlTokenManager:
"""Custom manager for the ``UrlToken`` model. The methods defined here provide shortcuts for token creation and for cleaning out expired tokens."""
def create_url_token(self, user, expiration_days, url, url_params=None):
"""Create a ``UrlToken`` for a given ``url`` and ``days``, ... | the_stack_v2_python_sparse | tokens/models.py | qazmaxlow/edms | train | 0 |
39017c91fcb49dc9a62c590010bfd0dd887e318e | [
"super(ProxyNCALoss, self).__init__()\nself.num_proxies = num_proxies\nself.embedding_dim = embedding_dim\nself.PROXIES = torch.nn.Parameter(torch.randn(num_proxies, self.embedding_dim) / 8)\nself.all_classes = torch.arange(num_proxies)",
"batch = 3 * torch.nn.functional.normalize(batch, dim=1)\nPROXIES = 3 * tor... | <|body_start_0|>
super(ProxyNCALoss, self).__init__()
self.num_proxies = num_proxies
self.embedding_dim = embedding_dim
self.PROXIES = torch.nn.Parameter(torch.randn(num_proxies, self.embedding_dim) / 8)
self.all_classes = torch.arange(num_proxies)
<|end_body_0|>
<|body_start_1|... | ProxyNCALoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProxyNCALoss:
def __init__(self, num_proxies, embedding_dim):
"""Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of proxies to use to estimate data groups. Usually set to number of classes. embedding_dim: int, Required t... | stack_v2_sparse_classes_75kplus_train_067470 | 29,027 | no_license | [
{
"docstring": "Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of proxies to use to estimate data groups. Usually set to number of classes. embedding_dim: int, Required to generate initial proxies which are the same size as the actual data emb... | 2 | stack_v2_sparse_classes_30k_val_001869 | Implement the Python class `ProxyNCALoss` described below.
Class description:
Implement the ProxyNCALoss class.
Method signatures and docstrings:
- def __init__(self, num_proxies, embedding_dim): Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of pro... | Implement the Python class `ProxyNCALoss` described below.
Class description:
Implement the ProxyNCALoss class.
Method signatures and docstrings:
- def __init__(self, num_proxies, embedding_dim): Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of pro... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ProxyNCALoss:
def __init__(self, num_proxies, embedding_dim):
"""Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of proxies to use to estimate data groups. Usually set to number of classes. embedding_dim: int, Required t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProxyNCALoss:
def __init__(self, num_proxies, embedding_dim):
"""Basic ProxyNCA Loss as proposed in 'No Fuss Distance Metric Learning using Proxies'. Args: num_proxies: int, number of proxies to use to estimate data groups. Usually set to number of classes. embedding_dim: int, Required to generate ini... | the_stack_v2_python_sparse | generated/test_Confusezius_Deep_Metric_Learning_Baselines.py | jansel/pytorch-jit-paritybench | train | 35 | |
08d6d950974a21c19ecf1ae273ee63ceb2f47534 | [
"with self.assertLogs(level='WARNING') as log_cm:\n stdout, stderr = self.redirect_streams(lambda: show.show_files([]))\n self.assertEqual(len(log_cm.output), 1)\n self.assertIn('No items to show', log_cm.output[0])\nself.assertEqual(stdout, '')\nself.assertEqual(stderr, '')",
"with self.assertLogs(level... | <|body_start_0|>
with self.assertLogs(level='WARNING') as log_cm:
stdout, stderr = self.redirect_streams(lambda: show.show_files([]))
self.assertEqual(len(log_cm.output), 1)
self.assertIn('No items to show', log_cm.output[0])
self.assertEqual(stdout, '')
self.... | Basic tests of show_files | TestShowFiles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestShowFiles:
"""Basic tests of show_files"""
def test_show_files_empty_list(self):
"""An empty list in should show nothing"""
<|body_0|>
def test_show_files_empty_string(self):
"""An empty string in should show nothing"""
<|body_1|>
def test_show_f... | stack_v2_sparse_classes_75kplus_train_067471 | 5,423 | no_license | [
{
"docstring": "An empty list in should show nothing",
"name": "test_show_files_empty_list",
"signature": "def test_show_files_empty_list(self)"
},
{
"docstring": "An empty string in should show nothing",
"name": "test_show_files_empty_string",
"signature": "def test_show_files_empty_str... | 4 | stack_v2_sparse_classes_30k_train_023537 | Implement the Python class `TestShowFiles` described below.
Class description:
Basic tests of show_files
Method signatures and docstrings:
- def test_show_files_empty_list(self): An empty list in should show nothing
- def test_show_files_empty_string(self): An empty string in should show nothing
- def test_show_files... | Implement the Python class `TestShowFiles` described below.
Class description:
Basic tests of show_files
Method signatures and docstrings:
- def test_show_files_empty_list(self): An empty list in should show nothing
- def test_show_files_empty_string(self): An empty string in should show nothing
- def test_show_files... | 539868dab2041b7694c0d53e8e74cf1b5b033653 | <|skeleton|>
class TestShowFiles:
"""Basic tests of show_files"""
def test_show_files_empty_list(self):
"""An empty list in should show nothing"""
<|body_0|>
def test_show_files_empty_string(self):
"""An empty string in should show nothing"""
<|body_1|>
def test_show_f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestShowFiles:
"""Basic tests of show_files"""
def test_show_files_empty_list(self):
"""An empty list in should show nothing"""
with self.assertLogs(level='WARNING') as log_cm:
stdout, stderr = self.redirect_streams(lambda: show.show_files([]))
self.assertEqual(len... | the_stack_v2_python_sparse | test_igseq/test_show.py | ShawHahnLab/igseq | train | 1 |
6d3a95a0160ff8b7166a9b4013fc7c57c508e172 | [
"super(MLLM, self).__init__()\nself.device = opt.device\nself.max_sequence_len = opt.max_sequence_length\nsentiment_lexicon = opt.sentiment_dic\nif sentiment_lexicon is not None:\n sentiment_lexicon = torch.tensor(sentiment_lexicon, dtype=torch.float)\nself.num_hidden_layers = len(str(opt.ngram_value).split(',')... | <|body_start_0|>
super(MLLM, self).__init__()
self.device = opt.device
self.max_sequence_len = opt.max_sequence_length
sentiment_lexicon = opt.sentiment_dic
if sentiment_lexicon is not None:
sentiment_lexicon = torch.tensor(sentiment_lexicon, dtype=torch.float)
... | MLLM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLLM:
def __init__(self, opt):
"""max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension"""
<|body_0|>
def forward(self, input_seq):
"""In the forward function we accept a Variab... | stack_v2_sparse_classes_75kplus_train_067472 | 4,295 | no_license | [
{
"docstring": "max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension",
"name": "__init__",
"signature": "def __init__(self, opt)"
},
{
"docstring": "In the forward function we accept a Variable of input da... | 2 | stack_v2_sparse_classes_30k_train_032654 | Implement the Python class `MLLM` described below.
Class description:
Implement the MLLM class.
Method signatures and docstrings:
- def __init__(self, opt): max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension
- def forward(sel... | Implement the Python class `MLLM` described below.
Class description:
Implement the MLLM class.
Method signatures and docstrings:
- def __init__(self, opt): max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension
- def forward(sel... | de9a632fd2895d7341b03d6ef8149e7670bd78db | <|skeleton|>
class MLLM:
def __init__(self, opt):
"""max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension"""
<|body_0|>
def forward(self, input_seq):
"""In the forward function we accept a Variab... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MLLM:
def __init__(self, opt):
"""max_sequence_len: input sentence length embedding_dim: input dimension num_measurements: number of measurement units, also the output dimension"""
super(MLLM, self).__init__()
self.device = opt.device
self.max_sequence_len = opt.max_sequence_le... | the_stack_v2_python_sparse | models/classification/MLLM.py | qiuchili/qnn_torch | train | 17 | |
367d3c25983cd2edb62cf274faa55796a342a6ed | [
"m, n = (len(heights), len(heights[0]))\npos = [(0, 1), (0, -1), (1, 0), (-1, 0)]\n\ndef dfs(x, y):\n if (x, y) in memo:\n return memo[x, y]\n visited.add((x, y))\n ans = 0\n if x == 0 or y == 0:\n ans |= 2\n if x == m - 1 or y == n - 1:\n ans |= 1\n print(x, y, ans)\n for ... | <|body_start_0|>
m, n = (len(heights), len(heights[0]))
pos = [(0, 1), (0, -1), (1, 0), (-1, 0)]
def dfs(x, y):
if (x, y) in memo:
return memo[x, y]
visited.add((x, y))
ans = 0
if x == 0 or y == 0:
ans |= 2
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pacificAtlantic(self, heights: List[List[int]]) -> List[List[int]]:
"""思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能流向太平洋 4. 11：能流向太平洋和大西洋 2. 当某个点对应的ans=3时，说明既能流向太平洋也能流向大西洋 @param heights: @return:"""
<|bo... | stack_v2_sparse_classes_75kplus_train_067473 | 3,937 | no_license | [
{
"docstring": "思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能流向太平洋 4. 11：能流向太平洋和大西洋 2. 当某个点对应的ans=3时，说明既能流向太平洋也能流向大西洋 @param heights: @return:",
"name": "pacificAtlantic",
"signature": "def pacificAtlantic(self, heights: List[List[int]]) -> Li... | 2 | stack_v2_sparse_classes_30k_train_054401 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pacificAtlantic(self, heights: List[List[int]]) -> List[List[int]]: 思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pacificAtlantic(self, heights: List[List[int]]) -> List[List[int]]: 思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能... | e43ee86c5a8cdb808da09b4b6138e10275abadb5 | <|skeleton|>
class Solution:
def pacificAtlantic(self, heights: List[List[int]]) -> List[List[int]]:
"""思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能流向太平洋 4. 11：能流向太平洋和大西洋 2. 当某个点对应的ans=3时，说明既能流向太平洋也能流向大西洋 @param heights: @return:"""
<|bo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def pacificAtlantic(self, heights: List[List[int]]) -> List[List[int]]:
"""思路：顺流而下 1. 从大陆开始流向太平洋和大西洋，通过两位二进制记录最终流向，如果能流向太平洋，ans |=2,如果能流向大西洋，ans |=1 1. 00：都不能流入 2. 01：能流向大西洋 3. 10：能流向太平洋 4. 11：能流向太平洋和大西洋 2. 当某个点对应的ans=3时，说明既能流向太平洋也能流向大西洋 @param heights: @return:"""
m, n = (len(height... | the_stack_v2_python_sparse | LeetCode/深度优先搜索(dfs)/岛屿问题/417. 太平洋大西洋水流问题.py | yiming1012/MyLeetCode | train | 2 | |
9e3b840c54734cffbcb4fa7481f0ee433f2b74f0 | [
"super(BinaryFocalLoss, self).__init__(name=name)\nself.gamma = gamma\nself.alpha = alpha",
"y_true = tf.cast(y_true, tf.float32)\nepsilon = K.epsilon()\ny_pred = K.clip(y_pred, epsilon, 1.0 - epsilon)\np_t = tf.where(K.equal(y_true, 1), y_pred, 1 - y_pred)\nalpha_factor = K.ones_like(y_true) * self.alpha\nalpha_... | <|body_start_0|>
super(BinaryFocalLoss, self).__init__(name=name)
self.gamma = gamma
self.alpha = alpha
<|end_body_0|>
<|body_start_1|>
y_true = tf.cast(y_true, tf.float32)
epsilon = K.epsilon()
y_pred = K.clip(y_pred, epsilon, 1.0 - epsilon)
p_t = tf.where(K.equ... | Implementation of simple binary focal loss. | BinaryFocalLoss | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryFocalLoss:
"""Implementation of simple binary focal loss."""
def __init__(self, name=None, gamma=2.0, alpha=0.25):
""":param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > 0 reduces the relative loss for well-classified examples ... | stack_v2_sparse_classes_75kplus_train_067474 | 3,619 | permissive | [
{
"docstring": ":param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > 0 reduces the relative loss for well-classified examples (p>0.5) putting more focus on hard misclassified example :param alpha: alpha constant used in focal loss equation. scalar factor to redu... | 2 | stack_v2_sparse_classes_30k_train_022954 | Implement the Python class `BinaryFocalLoss` described below.
Class description:
Implementation of simple binary focal loss.
Method signatures and docstrings:
- def __init__(self, name=None, gamma=2.0, alpha=0.25): :param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > ... | Implement the Python class `BinaryFocalLoss` described below.
Class description:
Implementation of simple binary focal loss.
Method signatures and docstrings:
- def __init__(self, name=None, gamma=2.0, alpha=0.25): :param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > ... | 391b4d84c9994e9abda64c6e48f2eac6b374b052 | <|skeleton|>
class BinaryFocalLoss:
"""Implementation of simple binary focal loss."""
def __init__(self, name=None, gamma=2.0, alpha=0.25):
""":param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > 0 reduces the relative loss for well-classified examples ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BinaryFocalLoss:
"""Implementation of simple binary focal loss."""
def __init__(self, name=None, gamma=2.0, alpha=0.25):
""":param name: displayed name for loss function :param gamma: gamma constant used in focal loss. gamma > 0 reduces the relative loss for well-classified examples (p>0.5) putti... | the_stack_v2_python_sparse | losses/focal_loss.py | Barchid/Indoor_Segmentation | train | 2 |
06ea7904436cf2143621688f92fe768fb6d18a75 | [
"user = User.objects.create_user(username='username', email='myemail@test.com', password='password', first_name='first', last_name='last')\ndata = {'username': 'changed', 'first_name': 'changed', 'last_name': 'changed', 'email': 'changed@change.ie'}\nform = EditProfileForm(data, instance=user)\nself.assertTrue(form... | <|body_start_0|>
user = User.objects.create_user(username='username', email='myemail@test.com', password='password', first_name='first', last_name='last')
data = {'username': 'changed', 'first_name': 'changed', 'last_name': 'changed', 'email': 'changed@change.ie'}
form = EditProfileForm(data, in... | test the edit profile form | Test_Edit_Profile_Form | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_Edit_Profile_Form:
"""test the edit profile form"""
def test_Edit_Profile_Form(self):
"""Test that the Edit Profile Form returns valid when there is valid changes"""
<|body_0|>
def test_correct_message_for_no_username_input(self):
"""Test that the error mess... | stack_v2_sparse_classes_75kplus_train_067475 | 9,772 | no_license | [
{
"docstring": "Test that the Edit Profile Form returns valid when there is valid changes",
"name": "test_Edit_Profile_Form",
"signature": "def test_Edit_Profile_Form(self)"
},
{
"docstring": "Test that the error message 'This field is required' occurs when there is no username inputted in the f... | 3 | stack_v2_sparse_classes_30k_train_051260 | Implement the Python class `Test_Edit_Profile_Form` described below.
Class description:
test the edit profile form
Method signatures and docstrings:
- def test_Edit_Profile_Form(self): Test that the Edit Profile Form returns valid when there is valid changes
- def test_correct_message_for_no_username_input(self): Tes... | Implement the Python class `Test_Edit_Profile_Form` described below.
Class description:
test the edit profile form
Method signatures and docstrings:
- def test_Edit_Profile_Form(self): Test that the Edit Profile Form returns valid when there is valid changes
- def test_correct_message_for_no_username_input(self): Tes... | a80148cb642cb09dac57cff18483be14fed67dfd | <|skeleton|>
class Test_Edit_Profile_Form:
"""test the edit profile form"""
def test_Edit_Profile_Form(self):
"""Test that the Edit Profile Form returns valid when there is valid changes"""
<|body_0|>
def test_correct_message_for_no_username_input(self):
"""Test that the error mess... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_Edit_Profile_Form:
"""test the edit profile form"""
def test_Edit_Profile_Form(self):
"""Test that the Edit Profile Form returns valid when there is valid changes"""
user = User.objects.create_user(username='username', email='myemail@test.com', password='password', first_name='first'... | the_stack_v2_python_sparse | accounts/tests_forms.py | sarahbarron/Stream-3-Project | train | 1 |
ccfa549c203e6aaa51d5e12d24543cdf770eefdf | [
"def check_supported_spec(spec):\n if tensor_spec.is_discrete(spec):\n assert len(spec.shape) == 0 or (len(spec.shape) == 1 and spec.shape[0] == 1)\n else:\n assert len(spec.shape) == 1\ntf.nest.map_structure(check_supported_spec, action_spec)\nself._action_spec = action_spec",
"tf.nest.assert... | <|body_start_0|>
def check_supported_spec(spec):
if tensor_spec.is_discrete(spec):
assert len(spec.shape) == 0 or (len(spec.shape) == 1 and spec.shape[0] == 1)
else:
assert len(spec.shape) == 1
tf.nest.map_structure(check_supported_spec, action_spe... | A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them | SimpleActionEncoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SimpleActionEncoder:
"""A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them"""
def __init__(self, action_spec):
"""Create Simpl... | stack_v2_sparse_classes_75kplus_train_067476 | 2,438 | permissive | [
{
"docstring": "Create SimpleActionEncoder. Args: action_spec (nested BoundedTensorSpec): spec for actions",
"name": "__init__",
"signature": "def __init__(self, action_spec)"
},
{
"docstring": "Generate encoded actions. Args: inputs (nested Tensor): action tensors. Returns: nested Tensor with t... | 2 | stack_v2_sparse_classes_30k_train_038987 | Implement the Python class `SimpleActionEncoder` described below.
Class description:
A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them
Method signatures and do... | Implement the Python class `SimpleActionEncoder` described below.
Class description:
A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them
Method signatures and do... | 38a3621337a030f74bb3944d7695e7642e777e10 | <|skeleton|>
class SimpleActionEncoder:
"""A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them"""
def __init__(self, action_spec):
"""Create Simpl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SimpleActionEncoder:
"""A simple encoder for action. Only supports one action (discrete or continuous). If encode discrete action to one hot representation and use the original continous actions. And output the concat of all of them"""
def __init__(self, action_spec):
"""Create SimpleActionEncode... | the_stack_v2_python_sparse | alf/utils/action_encoder.py | Haichao-Zhang/alf | train | 1 |
d1ac638651d2a219ce26c5098f97aa5f7f890535 | [
"if isinstance(model, str):\n name = model\nelif isinstance(model, type):\n name = model.__name__\nelse:\n name = model.__class__.__name__\nreturn '__%s_%s__' % (name, id_)",
"res = DBSession.query(cls.value).filter(cls.key == cls.replacement_key(model, id_)).first()\nif res:\n return res[0]",
"sess... | <|body_start_0|>
if isinstance(model, str):
name = model
elif isinstance(model, type):
name = model.__name__
else:
name = model.__class__.__name__
return '__%s_%s__' % (name, id_)
<|end_body_0|>
<|body_start_1|>
res = DBSession.query(cls.value... | Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects, where referred objects may become obsolete themselves. | Config | [
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Config:
"""Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects, where referred objects may become obs... | stack_v2_sparse_classes_75kplus_train_067477 | 2,241 | permissive | [
{
"docstring": "Determine the replacement key for an object. :param model: Model class or instance. :param id_: Identifier of a class instance. :return: ``str`` representation identifying a database object.",
"name": "replacement_key",
"signature": "def replacement_key(model, id_)"
},
{
"docstri... | 3 | null | Implement the Python class `Config` described below.
Class description:
Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects... | Implement the Python class `Config` described below.
Class description:
Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects... | a4901e2e1c90eb62b5f855608863df556677df06 | <|skeleton|>
class Config:
"""Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects, where referred objects may become obs... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Config:
"""Model class to allow storage of key-value pairs of configuration data. This model is also (ab-)used to implement a mechanism linking database objects of all types without enforcing referential intagrity, e.g. to model chains of superseding objects, where referred objects may become obsolete themsel... | the_stack_v2_python_sparse | src/clld/db/models/config.py | clld/clld | train | 44 |
ff3e713bda33fe18287774cf6e4c22000bc7b201 | [
"def dfs(root, curMax):\n if not root:\n return 0\n if root.val >= curMax:\n cur = 1\n curMax = max(curMax, root.val)\n else:\n cur = 0\n return cur + dfs(root.left, curMax) + dfs(root.right, curMax)\nres = dfs(root, root.val)\nreturn res",
"self.count = 0\n\ndef dfs(root, ... | <|body_start_0|>
def dfs(root, curMax):
if not root:
return 0
if root.val >= curMax:
cur = 1
curMax = max(curMax, root.val)
else:
cur = 0
return cur + dfs(root.left, curMax) + dfs(root.right, curMax)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def goodNodes1(self, root):
""":type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax"""
<|body_0|>
def goodNodes2(self, root):
""":type root: TreeNode :rtype: int... | stack_v2_sparse_classes_75kplus_train_067478 | 1,298 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax",
"name": "goodNodes1",
"signature": "def goodNodes1(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name":... | 2 | stack_v2_sparse_classes_30k_test_002003 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def goodNodes1(self, root): :type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax
-... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def goodNodes1(self, root): :type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax
-... | 813235789ce422a3bab198317aafc46fbc61625e | <|skeleton|>
class Solution:
def goodNodes1(self, root):
""":type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax"""
<|body_0|>
def goodNodes2(self, root):
""":type root: TreeNode :rtype: int... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def goodNodes1(self, root):
""":type root: TreeNode :rtype: int my own solution: pass curMax value down to the subtrees if current is good node, ie curcount += 1 and update curMax"""
def dfs(root, curMax):
if not root:
return 0
if root.val >= c... | the_stack_v2_python_sparse | 7.BINARY TREE and BST/1448_count_good_nodes/solution.py | kimmyoo/python_leetcode | train | 1 | |
890e2f587a9c4ec1e03642011f9ad5371be7d0db | [
"DocketGenerator.__init__(self)\nself.n_stimuli = n_stimuli\nself.n_reference = np.int32(n_reference)\nself.n_select = np.int32(n_select)\nself.is_ranked = True",
"n_reference = self.n_reference\nn_select = np.repeat(self.n_select, n_trial)\nis_ranked = np.repeat(self.is_ranked, n_trial)\nidx_eligable = np.arange... | <|body_start_0|>
DocketGenerator.__init__(self)
self.n_stimuli = n_stimuli
self.n_reference = np.int32(n_reference)
self.n_select = np.int32(n_select)
self.is_ranked = True
<|end_body_0|>
<|body_start_1|>
n_reference = self.n_reference
n_select = np.repeat(self.n... | A trial generator that blindly samples trials. | RandomRank | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomRank:
"""A trial generator that blindly samples trials."""
def __init__(self, n_stimuli, n_reference=2, n_select=1):
"""Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference (optional): A scalar indicating the number of references... | stack_v2_sparse_classes_75kplus_train_067479 | 2,605 | permissive | [
{
"docstring": "Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference (optional): A scalar indicating the number of references for each trial. n_select (optional): A scalar indicating the number of selections an agent must make.",
"name": "__init__",
"sign... | 2 | stack_v2_sparse_classes_30k_train_037737 | Implement the Python class `RandomRank` described below.
Class description:
A trial generator that blindly samples trials.
Method signatures and docstrings:
- def __init__(self, n_stimuli, n_reference=2, n_select=1): Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference... | Implement the Python class `RandomRank` described below.
Class description:
A trial generator that blindly samples trials.
Method signatures and docstrings:
- def __init__(self, n_stimuli, n_reference=2, n_select=1): Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference... | 4f05348cf43d2d53ff9cc6dee633de385df883e3 | <|skeleton|>
class RandomRank:
"""A trial generator that blindly samples trials."""
def __init__(self, n_stimuli, n_reference=2, n_select=1):
"""Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference (optional): A scalar indicating the number of references... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RandomRank:
"""A trial generator that blindly samples trials."""
def __init__(self, n_stimuli, n_reference=2, n_select=1):
"""Initialize. Arguments: n_stimuli: A scalar indicating the total number of unique stimuli. n_reference (optional): A scalar indicating the number of references for each tri... | the_stack_v2_python_sparse | psiz/generators/similarity/rank/random_rank.py | asuiconlab/psiz | train | 0 |
3bc9ed7fac8464e9d9f14df0ea35c50e38380ede | [
"argument_and_expected_result = {'a': 'a', 'aa': 'a', 'aaa': 'a', 'aba': 'ab', 'bba': 'ba', 'aab': 'ab', 'TechCity': 'Techiy'}\nfor word, expected_result in argument_and_expected_result.items():\n result = task1.remove_all_except_first(word)\n self.assertEqual(result, expected_result)",
"argument_and_expect... | <|body_start_0|>
argument_and_expected_result = {'a': 'a', 'aa': 'a', 'aaa': 'a', 'aba': 'ab', 'bba': 'ba', 'aab': 'ab', 'TechCity': 'Techiy'}
for word, expected_result in argument_and_expected_result.items():
result = task1.remove_all_except_first(word)
self.assertEqual(result, ... | Tests for string manipulation task. | StringManipulationTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StringManipulationTest:
"""Tests for string manipulation task."""
def test_remove_all_except_first(self):
"""Test that all character in a strings are removed except first character"""
<|body_0|>
def test_remove_first_occurrence(self):
"""Test that first occurrenc... | stack_v2_sparse_classes_75kplus_train_067480 | 1,369 | no_license | [
{
"docstring": "Test that all character in a strings are removed except first character",
"name": "test_remove_all_except_first",
"signature": "def test_remove_all_except_first(self)"
},
{
"docstring": "Test that first occurrence of character is removed in a string",
"name": "test_remove_fir... | 2 | stack_v2_sparse_classes_30k_train_011941 | Implement the Python class `StringManipulationTest` described below.
Class description:
Tests for string manipulation task.
Method signatures and docstrings:
- def test_remove_all_except_first(self): Test that all character in a strings are removed except first character
- def test_remove_first_occurrence(self): Test... | Implement the Python class `StringManipulationTest` described below.
Class description:
Tests for string manipulation task.
Method signatures and docstrings:
- def test_remove_all_except_first(self): Test that all character in a strings are removed except first character
- def test_remove_first_occurrence(self): Test... | 4c5044a4e9085cc09d8eee223c89217cae408166 | <|skeleton|>
class StringManipulationTest:
"""Tests for string manipulation task."""
def test_remove_all_except_first(self):
"""Test that all character in a strings are removed except first character"""
<|body_0|>
def test_remove_first_occurrence(self):
"""Test that first occurrenc... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class StringManipulationTest:
"""Tests for string manipulation task."""
def test_remove_all_except_first(self):
"""Test that all character in a strings are removed except first character"""
argument_and_expected_result = {'a': 'a', 'aa': 'a', 'aaa': 'a', 'aba': 'ab', 'bba': 'ba', 'aab': 'ab', '... | the_stack_v2_python_sparse | unit_test/test_task1.py | monofal/Full-Stack-Training | train | 0 |
e50b5fba8e02c08bc0d94bc143e22793c8752d4e | [
"super(FeatureSlice, self).__init__(**kwargs)\nself.slicing_indices = s_inds\nself.n_feats = len(s_inds)\nself.n_dims = n_dims\nself.return_last_seq = return_last_seq\nif n_dims == 2:\n raise NotImplementedError('Not implemented for 2D tensors!')",
"s = -1 if self.return_last_seq else slice(None)\nfeature_tens... | <|body_start_0|>
super(FeatureSlice, self).__init__(**kwargs)
self.slicing_indices = s_inds
self.n_feats = len(s_inds)
self.n_dims = n_dims
self.return_last_seq = return_last_seq
if n_dims == 2:
raise NotImplementedError('Not implemented for 2D tensors!')
<|en... | Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones. | FeatureSlice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureSlice:
"""Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones."""
def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq: bool=True, **kwargs):
"""Initialize layer. Args: s_inds: Th... | stack_v2_sparse_classes_75kplus_train_067481 | 13,797 | no_license | [
{
"docstring": "Initialize layer. Args: s_inds: The array with the indices. n_dims: The number of dimensions of the input tensor. **kwargs: The kwargs for super(), e.g. `name`.",
"name": "__init__",
"signature": "def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq: bool=True, **kwargs)... | 3 | stack_v2_sparse_classes_30k_train_005122 | Implement the Python class `FeatureSlice` described below.
Class description:
Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones.
Method signatures and docstrings:
- def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq:... | Implement the Python class `FeatureSlice` described below.
Class description:
Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones.
Method signatures and docstrings:
- def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq:... | 76bb37bf2d23f7d047602bbdbcc4b2607df53a2b | <|skeleton|>
class FeatureSlice:
"""Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones."""
def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq: bool=True, **kwargs):
"""Initialize layer. Args: s_inds: Th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FeatureSlice:
"""Extracts specified features from tensor. TODO: Make it more efficient by considering not single slices but multiple consecutive ones."""
def __init__(self, s_inds: np.ndarray, n_dims: int=3, return_last_seq: bool=True, **kwargs):
"""Initialize layer. Args: s_inds: The array with ... | the_stack_v2_python_sparse | BatchRL/ml/keras_layers.py | chbauman/MasterThesis | train | 0 |
f2e52a6d9a71753b882c449c9fbad3af436d7c6a | [
"msg_id = None\nmsg_len = 0\nraw_msg_id = np.fromfile(file_hdl, np.int16, 1)\nraw_msg_len = np.fromfile(file_hdl, np.int32, 1)\ntry:\n if raw_msg_id is not None:\n msg_id = raw_msg_id[0]\n if raw_msg_len is not None:\n msg_len = raw_msg_len[0]\nexcept IndexError:\n pass\nreturn (msg_id, msg_l... | <|body_start_0|>
msg_id = None
msg_len = 0
raw_msg_id = np.fromfile(file_hdl, np.int16, 1)
raw_msg_len = np.fromfile(file_hdl, np.int32, 1)
try:
if raw_msg_id is not None:
msg_id = raw_msg_id[0]
if raw_msg_len is not None:
m... | Handles reading UTWin CScan (.csc) files | UTWinCscanReader | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UTWinCscanReader:
"""Handles reading UTWin CScan (.csc) files"""
def msg_info(cls, file_hdl):
"""Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found."""
<|body_0|>
def find_message(cls, file_name, message... | stack_v2_sparse_classes_75kplus_train_067482 | 49,665 | permissive | [
{
"docstring": "Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found.",
"name": "msg_info",
"signature": "def msg_info(cls, file_hdl)"
},
{
"docstring": "Returns the position in the UTWin file corresponding to the specified messag... | 5 | null | Implement the Python class `UTWinCscanReader` described below.
Class description:
Handles reading UTWin CScan (.csc) files
Method signatures and docstrings:
- def msg_info(cls, file_hdl): Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found.
- def find... | Implement the Python class `UTWinCscanReader` described below.
Class description:
Handles reading UTWin CScan (.csc) files
Method signatures and docstrings:
- def msg_info(cls, file_hdl): Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found.
- def find... | 33f4ec11cfc3befbe52f0985b8ab8ff39901d0c9 | <|skeleton|>
class UTWinCscanReader:
"""Handles reading UTWin CScan (.csc) files"""
def msg_info(cls, file_hdl):
"""Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found."""
<|body_0|>
def find_message(cls, file_name, message... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UTWinCscanReader:
"""Handles reading UTWin CScan (.csc) files"""
def msg_info(cls, file_hdl):
"""Returns a tuple of message ID and message length read from the file. Returns (None, 0) if ID and length were not found."""
msg_id = None
msg_len = 0
raw_msg_id = np.fromfile(fi... | the_stack_v2_python_sparse | models/dataio.py | ccoughlin/nditoolbox-labs | train | 0 |
89fecd54bc1f885c366fe4130658e60b7039fa96 | [
"with self.assertRaises(EOFError) as e:\n fileio.GetAtomsFromXyzq([])\nself.assertEqual(str(e.exception), 'XYZQ file is empty.')",
"with self.assertRaises(IndexError) as e:\n fileio.GetAtomsFromXyzq([[], ['X', '0.0', '0.0', '0.0', '0.0']])\nself.assertEqual(str(e.exception), 'First line of XYZQ file must be... | <|body_start_0|>
with self.assertRaises(EOFError) as e:
fileio.GetAtomsFromXyzq([])
self.assertEqual(str(e.exception), 'XYZQ file is empty.')
<|end_body_0|>
<|body_start_1|>
with self.assertRaises(IndexError) as e:
fileio.GetAtomsFromXyzq([[], ['X', '0.0', '0.0', '0.0', ... | Unit tests for mmlib.fileio.GetAtomsFromXyzq method. | TestGetAtomsFromXyzq | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGetAtomsFromXyzq:
"""Unit tests for mmlib.fileio.GetAtomsFromXyzq method."""
def testEmptyArray(self):
"""Asserts error raise for empty input."""
<|body_0|>
def testEmptyFirstRow(self):
"""Asserts error raise for empty first row of input."""
<|body_1|... | stack_v2_sparse_classes_75kplus_train_067483 | 20,144 | no_license | [
{
"docstring": "Asserts error raise for empty input.",
"name": "testEmptyArray",
"signature": "def testEmptyArray(self)"
},
{
"docstring": "Asserts error raise for empty first row of input.",
"name": "testEmptyFirstRow",
"signature": "def testEmptyFirstRow(self)"
},
{
"docstring"... | 6 | stack_v2_sparse_classes_30k_test_002513 | Implement the Python class `TestGetAtomsFromXyzq` described below.
Class description:
Unit tests for mmlib.fileio.GetAtomsFromXyzq method.
Method signatures and docstrings:
- def testEmptyArray(self): Asserts error raise for empty input.
- def testEmptyFirstRow(self): Asserts error raise for empty first row of input.... | Implement the Python class `TestGetAtomsFromXyzq` described below.
Class description:
Unit tests for mmlib.fileio.GetAtomsFromXyzq method.
Method signatures and docstrings:
- def testEmptyArray(self): Asserts error raise for empty input.
- def testEmptyFirstRow(self): Asserts error raise for empty first row of input.... | 0ac31aac3070bba17e91c9922a2e32c569479e4d | <|skeleton|>
class TestGetAtomsFromXyzq:
"""Unit tests for mmlib.fileio.GetAtomsFromXyzq method."""
def testEmptyArray(self):
"""Asserts error raise for empty input."""
<|body_0|>
def testEmptyFirstRow(self):
"""Asserts error raise for empty first row of input."""
<|body_1|... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestGetAtomsFromXyzq:
"""Unit tests for mmlib.fileio.GetAtomsFromXyzq method."""
def testEmptyArray(self):
"""Asserts error raise for empty input."""
with self.assertRaises(EOFError) as e:
fileio.GetAtomsFromXyzq([])
self.assertEqual(str(e.exception), 'XYZQ file is emp... | the_stack_v2_python_sparse | scripts/molecular_mechanics/mmlib/fileio_test.py | aledzib/Computational-Chemistry | train | 1 |
a856e9c098632e4e753cbae27d0b50362a4f2ee1 | [
"super().__init__()\nself._commands = []\nself._allocated_qubit_ids = set()\nself._deallocated_qubit_ids = set()",
"if self._deallocated_qubit_ids != self._allocated_qubit_ids:\n raise QubitManagementError(\"\\n Error. Qubits have been allocated in 'with \" + \"Dagger(eng)' context,\\n which have not explicitl... | <|body_start_0|>
super().__init__()
self._commands = []
self._allocated_qubit_ids = set()
self._deallocated_qubit_ids = set()
<|end_body_0|>
<|body_start_1|>
if self._deallocated_qubit_ids != self._allocated_qubit_ids:
raise QubitManagementError("\n Error. Qubits hav... | Store all commands and, when done, inverts the circuit & runs it. | DaggerEngine | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DaggerEngine:
"""Store all commands and, when done, inverts the circuit & runs it."""
def __init__(self):
"""Initialize a DaggerEngine object."""
<|body_0|>
def run(self):
"""Run the stored circuit in reverse and check that local qubits have been deallocated."""
... | stack_v2_sparse_classes_75kplus_train_067484 | 4,460 | permissive | [
{
"docstring": "Initialize a DaggerEngine object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run the stored circuit in reverse and check that local qubits have been deallocated.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Recei... | 3 | null | Implement the Python class `DaggerEngine` described below.
Class description:
Store all commands and, when done, inverts the circuit & runs it.
Method signatures and docstrings:
- def __init__(self): Initialize a DaggerEngine object.
- def run(self): Run the stored circuit in reverse and check that local qubits have ... | Implement the Python class `DaggerEngine` described below.
Class description:
Store all commands and, when done, inverts the circuit & runs it.
Method signatures and docstrings:
- def __init__(self): Initialize a DaggerEngine object.
- def run(self): Run the stored circuit in reverse and check that local qubits have ... | 67c660ca18725d23ab0b261a45e34873b6a58d03 | <|skeleton|>
class DaggerEngine:
"""Store all commands and, when done, inverts the circuit & runs it."""
def __init__(self):
"""Initialize a DaggerEngine object."""
<|body_0|>
def run(self):
"""Run the stored circuit in reverse and check that local qubits have been deallocated."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DaggerEngine:
"""Store all commands and, when done, inverts the circuit & runs it."""
def __init__(self):
"""Initialize a DaggerEngine object."""
super().__init__()
self._commands = []
self._allocated_qubit_ids = set()
self._deallocated_qubit_ids = set()
def r... | the_stack_v2_python_sparse | projectq/meta/_dagger.py | ProjectQ-Framework/ProjectQ | train | 886 |
92ccc251ace9030607e5deef492bceea069bddb8 | [
"self.X = X\nself.input_dim = input_dim\nself.batch_input = batch_input",
"if self.batch_input is True:\n return tf.expand_dims(self.X, 0)[0, :, :, :]\nelse:\n return tf.expand_dims(self.X, 0)"
] | <|body_start_0|>
self.X = X
self.input_dim = input_dim
self.batch_input = batch_input
<|end_body_0|>
<|body_start_1|>
if self.batch_input is True:
return tf.expand_dims(self.X, 0)[0, :, :, :]
else:
return tf.expand_dims(self.X, 0)
<|end_body_1|>
| This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions) | InputLSTMLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputLSTMLayer:
"""This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions)"""
def __init__(self, X, input_dim, batch_input=False):
"""Initialize ... | stack_v2_sparse_classes_75kplus_train_067485 | 1,119 | permissive | [
{
"docstring": "Initialize InputLSTMLayer class Parameters ---------- X : tf.Tensor Input tensor to be transformed input_dim : integer Input dimensions batch_input : boolean (default False) If input is batch",
"name": "__init__",
"signature": "def __init__(self, X, input_dim, batch_input=False)"
},
... | 2 | stack_v2_sparse_classes_30k_train_043108 | Implement the Python class `InputLSTMLayer` described below.
Class description:
This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions)
Method signatures and docstrings:
- def __i... | Implement the Python class `InputLSTMLayer` described below.
Class description:
This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions)
Method signatures and docstrings:
- def __i... | d129172b064d9e73e9118ac7164eb826a1263100 | <|skeleton|>
class InputLSTMLayer:
"""This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions)"""
def __init__(self, X, input_dim, batch_input=False):
"""Initialize ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InputLSTMLayer:
"""This layer expands dimensions inorder for the LSTM to function. The input data has a shape of (?,input_dimensions) and the output for this layer is a tensor of the shape (1, ?, input_dimensions)"""
def __init__(self, X, input_dim, batch_input=False):
"""Initialize InputLSTMLaye... | the_stack_v2_python_sparse | timeflow/layers/input_lstm_layer.py | genesiscrew/TensorFlow-Predictor | train | 1 |
41fa99d6de5ae139cacd40bb2788d0d5a93a4391 | [
"if not root:\n return True\nreturn self.is_symmetric_recursive(root)",
"def recursion(node1, node2):\n if not node1 and (not node2):\n return True\n return bool(node1) and bool(node2) and (node1.val == node2.val) and recursion(node1.left, node2.right) and recursion(node1.right, node2.left)\nretur... | <|body_start_0|>
if not root:
return True
return self.is_symmetric_recursive(root)
<|end_body_0|>
<|body_start_1|>
def recursion(node1, node2):
if not node1 and (not node2):
return True
return bool(node1) and bool(node2) and (node1.val == node... | Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right sym... | stack_v2_sparse_classes_75kplus_train_067486 | 3,129 | no_license | [
{
"docstring": "Determine whether a given binary tree is left-right symmetric. :type root: TreeNode :rtype: bool",
"name": "is_symmetric",
"signature": "def is_symmetric(self, root)"
},
{
"docstring": "Symmetric tree: recursive solution.",
"name": "is_symmetric_recursive",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_032353 | Implement the Python class `Solution` described below.
Class description:
Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None
Method signatures and docstrings:
- def is_symmetric(self, root)... | Implement the Python class `Solution` described below.
Class description:
Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None
Method signatures and docstrings:
- def is_symmetric(self, root)... | e11bfc454789e716055b80873af0817ec8588aea | <|skeleton|>
class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right sym... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""Solution to Leetcode problem 101: Symmetric Tree. Definition for a binary tree node. class TreeNode(object): def __init__(self, x): self.val = x self.left = None self.right = None"""
def is_symmetric(self, root):
"""Determine whether a given binary tree is left-right symmetric. :type... | the_stack_v2_python_sparse | p101/problem101.py | stanl3y/leetcode | train | 0 |
d56b20c9c038f2a636de9aee5cc0d98868d217e3 | [
"super(FunctionComponent, self).__init__(opts)\nself.fn_options = opts.get(PACKAGE_NAME, {})\nself.opts = opts\nvalidate_fields(config.REQUIRED_CONFIG_SETTINGS, self.fn_options)",
"self.fn_options = opts.get(PACKAGE_NAME, {})\nself.opts = opts\nvalidate_fields(config.REQUIRED_CONFIG_SETTINGS, self.fn_options)",
... | <|body_start_0|>
super(FunctionComponent, self).__init__(opts)
self.fn_options = opts.get(PACKAGE_NAME, {})
self.opts = opts
validate_fields(config.REQUIRED_CONFIG_SETTINGS, self.fn_options)
<|end_body_0|>
<|body_start_1|>
self.fn_options = opts.get(PACKAGE_NAME, {})
sel... | Component that implements Resilient function 'funct_zia_remove_from_url_category'' | FunctionComponent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionComponent:
"""Component that implements Resilient function 'funct_zia_remove_from_url_category''"""
def __init__(self, opts):
"""Constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration option... | stack_v2_sparse_classes_75kplus_train_067487 | 3,635 | permissive | [
{
"docstring": "Constructor provides access to the configuration options",
"name": "__init__",
"signature": "def __init__(self, opts)"
},
{
"docstring": "Configuration options have changed, save new values",
"name": "_reload",
"signature": "def _reload(self, event, opts)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_052328 | Implement the Python class `FunctionComponent` described below.
Class description:
Component that implements Resilient function 'funct_zia_remove_from_url_category''
Method signatures and docstrings:
- def __init__(self, opts): Constructor provides access to the configuration options
- def _reload(self, event, opts):... | Implement the Python class `FunctionComponent` described below.
Class description:
Component that implements Resilient function 'funct_zia_remove_from_url_category''
Method signatures and docstrings:
- def __init__(self, opts): Constructor provides access to the configuration options
- def _reload(self, event, opts):... | 6878c78b94eeca407998a41ce8db2cc00f2b6758 | <|skeleton|>
class FunctionComponent:
"""Component that implements Resilient function 'funct_zia_remove_from_url_category''"""
def __init__(self, opts):
"""Constructor provides access to the configuration options"""
<|body_0|>
def _reload(self, event, opts):
"""Configuration option... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FunctionComponent:
"""Component that implements Resilient function 'funct_zia_remove_from_url_category''"""
def __init__(self, opts):
"""Constructor provides access to the configuration options"""
super(FunctionComponent, self).__init__(opts)
self.fn_options = opts.get(PACKAGE_NAM... | the_stack_v2_python_sparse | fn_zia/fn_zia/components/funct_zia_remove_from_url_category.py | ibmresilient/resilient-community-apps | train | 81 |
dc3d247bb1098d297aad529bf34ae5dfd0af6d33 | [
"new_prop = 'user_prop'\nnew_prop_value = rand_name('new_prop_value')\nimage = self.images_behavior.create_image_via_task()\nresponse = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})\nself.assertEqual(response.status_code, 200)\nupdated_image = response.entity\nself.assertIn(new_prop, up... | <|body_start_0|>
new_prop = 'user_prop'
new_prop_value = rand_name('new_prop_value')
image = self.images_behavior.create_image_via_task()
response = self.images_client.update_image(image.id_, add={new_prop: new_prop_value})
self.assertEqual(response.status_code, 200)
upda... | TestUpdateImagePositive | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_75kplus_train_067488 | 6,204 | permissive | [
{
"docstring": "@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new property's value is correct",
"name": "test_update_image_add_additional_prope... | 4 | stack_v2_sparse_classes_30k_train_008384 | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | Implement the Python class `TestUpdateImagePositive` described below.
Class description:
Implement the TestUpdateImagePositive class.
Method signatures and docstrings:
- def test_update_image_add_additional_property(self): @summary: Update image add additional property 1) Create image 2) Update image adding a new pro... | 30f0e64672676c3f90b4a582fe90fac6621475b3 | <|skeleton|>
class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestUpdateImagePositive:
def test_update_image_add_additional_property(self):
"""@summary: Update image add additional property 1) Create image 2) Update image adding a new property 3) Verify that the response code is 200 4) Verify that the new property is in the response 5) Verify that the new proper... | the_stack_v2_python_sparse | cloudroast/images/v2/functional/test_update_image_positive.py | RULCSoft/cloudroast | train | 1 | |
0d329c74abd1b6cf79b45535999e320f2f8eb5c8 | [
"response = get_and_check_page(self, 'huntserver:create_account', 200)\npost_context = {'user-first_name': 'first', 'user-last_name': 'last', 'user-username': 'user7', 'user-email': 'user7@example.com', 'person-phone': '777-777-7777', 'person-allergies': 'something', 'user-password': 'password', 'user-confirm_passw... | <|body_start_0|>
response = get_and_check_page(self, 'huntserver:create_account', 200)
post_context = {'user-first_name': 'first', 'user-last_name': 'last', 'user-username': 'user7', 'user-email': 'user7@example.com', 'person-phone': '777-777-7777', 'person-allergies': 'something', 'user-password': 'pas... | AuthTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthTests:
def test_create_account(self):
"""Test the account creation view"""
<|body_0|>
def test_login_selection(self):
"""Test the login selection view"""
<|body_1|>
def test_account_logout(self):
"""Test the account logout view"""
<|b... | stack_v2_sparse_classes_75kplus_train_067489 | 33,380 | permissive | [
{
"docstring": "Test the account creation view",
"name": "test_create_account",
"signature": "def test_create_account(self)"
},
{
"docstring": "Test the login selection view",
"name": "test_login_selection",
"signature": "def test_login_selection(self)"
},
{
"docstring": "Test th... | 4 | stack_v2_sparse_classes_30k_test_000616 | Implement the Python class `AuthTests` described below.
Class description:
Implement the AuthTests class.
Method signatures and docstrings:
- def test_create_account(self): Test the account creation view
- def test_login_selection(self): Test the login selection view
- def test_account_logout(self): Test the account ... | Implement the Python class `AuthTests` described below.
Class description:
Implement the AuthTests class.
Method signatures and docstrings:
- def test_create_account(self): Test the account creation view
- def test_login_selection(self): Test the login selection view
- def test_account_logout(self): Test the account ... | 44f87cc5cfe8bb23a8e04fddee187b9056407741 | <|skeleton|>
class AuthTests:
def test_create_account(self):
"""Test the account creation view"""
<|body_0|>
def test_login_selection(self):
"""Test the login selection view"""
<|body_1|>
def test_account_logout(self):
"""Test the account logout view"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthTests:
def test_create_account(self):
"""Test the account creation view"""
response = get_and_check_page(self, 'huntserver:create_account', 200)
post_context = {'user-first_name': 'first', 'user-last_name': 'last', 'user-username': 'user7', 'user-email': 'user7@example.com', 'perso... | the_stack_v2_python_sparse | huntserver/tests.py | dlareau/puzzlehunt_server | train | 20 | |
4ccd406ad7014e7578048084f424dacd39d2692e | [
"rs = [S]\n\ndef flip(ch):\n if ch in ascii_lowercase:\n return ch.upper()\n else:\n return ch.lower()\nfor i in range(len(S)):\n if S[i].lower() not in ascii_lowercase:\n continue\n else:\n ans = []\n for cur_s in rs:\n tmp = cur_s[:i] + flip(cur_s[i]) + cu... | <|body_start_0|>
rs = [S]
def flip(ch):
if ch in ascii_lowercase:
return ch.upper()
else:
return ch.lower()
for i in range(len(S)):
if S[i].lower() not in ascii_lowercase:
continue
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str]"""
<|body_0|>
def letterCasePermutation1(self, S):
""":type S: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
rs = [S]
def flip(ch):
... | stack_v2_sparse_classes_75kplus_train_067490 | 1,812 | no_license | [
{
"docstring": ":type S: str :rtype: List[str]",
"name": "letterCasePermutation",
"signature": "def letterCasePermutation(self, S)"
},
{
"docstring": ":type S: str :rtype: List[str]",
"name": "letterCasePermutation1",
"signature": "def letterCasePermutation1(self, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018702 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCasePermutation(self, S): :type S: str :rtype: List[str]
- def letterCasePermutation1(self, S): :type S: str :rtype: List[str] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCasePermutation(self, S): :type S: str :rtype: List[str]
- def letterCasePermutation1(self, S): :type S: str :rtype: List[str]
<|skeleton|>
class Solution:
def le... | 56730ff8cf432dda08bb56a0e783400d0375af69 | <|skeleton|>
class Solution:
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str]"""
<|body_0|>
def letterCasePermutation1(self, S):
""":type S: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def letterCasePermutation(self, S):
""":type S: str :rtype: List[str]"""
rs = [S]
def flip(ch):
if ch in ascii_lowercase:
return ch.upper()
else:
return ch.lower()
for i in range(len(S)):
if S[i].low... | the_stack_v2_python_sparse | 784-字母大小写全排列.py | kt8506/Leetcode | train | 0 | |
72b10bcb2bc85c6862d110b6299aa2ea2fdae35d | [
"args = get_retro_args()\nassert torch.distributed.get_rank() == 0\nfaiss.omp_set_num_threads(64)\nempty_index_path = self.get_empty_index_path()\nif os.path.isfile(empty_index_path):\n return\nmerged_path = get_training_data_merged_path()\ninp = np.memmap(merged_path, dtype='f4', mode='r').reshape((-1, args.hid... | <|body_start_0|>
args = get_retro_args()
assert torch.distributed.get_rank() == 0
faiss.omp_set_num_threads(64)
empty_index_path = self.get_empty_index_path()
if os.path.isfile(empty_index_path):
return
merged_path = get_training_data_merged_path()
inp... | FaissBaseIndex | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaissBaseIndex:
def _train(self):
"""Train index (rank 0's method)."""
<|body_0|>
def train(self):
"""Train index."""
<|body_1|>
def _add(self, text_dataset):
"""Add to index (rank 0's method)."""
<|body_2|>
def add(self, text_datase... | stack_v2_sparse_classes_75kplus_train_067491 | 4,030 | permissive | [
{
"docstring": "Train index (rank 0's method).",
"name": "_train",
"signature": "def _train(self)"
},
{
"docstring": "Train index.",
"name": "train",
"signature": "def train(self)"
},
{
"docstring": "Add to index (rank 0's method).",
"name": "_add",
"signature": "def _add... | 4 | stack_v2_sparse_classes_30k_train_000975 | Implement the Python class `FaissBaseIndex` described below.
Class description:
Implement the FaissBaseIndex class.
Method signatures and docstrings:
- def _train(self): Train index (rank 0's method).
- def train(self): Train index.
- def _add(self, text_dataset): Add to index (rank 0's method).
- def add(self, text_... | Implement the Python class `FaissBaseIndex` described below.
Class description:
Implement the FaissBaseIndex class.
Method signatures and docstrings:
- def _train(self): Train index (rank 0's method).
- def train(self): Train index.
- def _add(self, text_dataset): Add to index (rank 0's method).
- def add(self, text_... | 99b044bff07f8e5d48b45223ed4bb11bd4e884e6 | <|skeleton|>
class FaissBaseIndex:
def _train(self):
"""Train index (rank 0's method)."""
<|body_0|>
def train(self):
"""Train index."""
<|body_1|>
def _add(self, text_dataset):
"""Add to index (rank 0's method)."""
<|body_2|>
def add(self, text_datase... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FaissBaseIndex:
def _train(self):
"""Train index (rank 0's method)."""
args = get_retro_args()
assert torch.distributed.get_rank() == 0
faiss.omp_set_num_threads(64)
empty_index_path = self.get_empty_index_path()
if os.path.isfile(empty_index_path):
... | the_stack_v2_python_sparse | tools/retro/index/indexes/faiss_base.py | NVIDIA/Megatron-LM | train | 6,315 | |
fb7f952c7f01b52a0cb0b2f3f0e5893d08421183 | [
"try:\n registry = oai_registry_api.get_by_id(registry_id)\n all_errors = oai_registry_api.harvest_registry(registry)\n if len(all_errors) > 0:\n raise exceptions_oai.OAIAPISerializeLabelledException(errors=all_errors, status_code=status.HTTP_400_BAD_REQUEST)\n content = OaiPmhMessage.get_message... | <|body_start_0|>
try:
registry = oai_registry_api.get_by_id(registry_id)
all_errors = oai_registry_api.harvest_registry(registry)
if len(all_errors) > 0:
raise exceptions_oai.OAIAPISerializeLabelledException(errors=all_errors, status_code=status.HTTP_400_BAD_R... | Harvest | Harvest | [
"NIST-Software",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Harvest:
"""Harvest"""
def patch(self, request, registry_id):
"""Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Object was not found - code: 500 content: Internal server err... | stack_v2_sparse_classes_75kplus_train_067492 | 17,640 | permissive | [
{
"docstring": "Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Object was not found - code: 500 content: Internal server error",
"name": "patch",
"signature": "def patch(self, request, registry... | 2 | stack_v2_sparse_classes_30k_train_026437 | Implement the Python class `Harvest` described below.
Class description:
Harvest
Method signatures and docstrings:
- def patch(self, request, registry_id): Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Obje... | Implement the Python class `Harvest` described below.
Class description:
Harvest
Method signatures and docstrings:
- def patch(self, request, registry_id): Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Obje... | bc5e31a9d7e5f66e34340230ae17a3cc2d08e7e7 | <|skeleton|>
class Harvest:
"""Harvest"""
def patch(self, request, registry_id):
"""Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Object was not found - code: 500 content: Internal server err... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Harvest:
"""Harvest"""
def patch(self, request, registry_id):
"""Harvest a given registry (Data provider) Args: request: HTTP request registry_id: ObjectId Returns: - code: 200 content: Success message - code: 404 content: Object was not found - code: 500 content: Internal server error"""
... | the_stack_v2_python_sparse | core_oaipmh_harvester_app/rest/oai_registry/views.py | usnistgov/core_oaipmh_harvester_app | train | 1 |
b4d80942c203d4d2c2267610f6dce8f059be9bc5 | [
"self.key = generate_random_aes_key()\nself.keysize = len(self.key)\nself.iv = b'0' * len(self.key)\nself.prefix = 'comment1=cooking%20MCs;userdata='\nself.suffix = ';comment2=%20like%20a%20pound%20of%20bacon'",
"print_line(f'{BOLD_START}CBC bitflipping attacks{BOLD_END}', color=BLUE)\nprint_line('Generate a rand... | <|body_start_0|>
self.key = generate_random_aes_key()
self.keysize = len(self.key)
self.iv = b'0' * len(self.key)
self.prefix = 'comment1=cooking%20MCs;userdata='
self.suffix = ';comment2=%20like%20a%20pound%20of%20bacon'
<|end_body_0|>
<|body_start_1|>
print_line(f'{BOL... | Challenge16 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Challenge16:
def __init__(self):
"""Init"""
<|body_0|>
def display(self):
"""Display challenge info :return:"""
<|body_1|>
def run(self):
"""The idea is we are filling the prefix up to full block size as usual Then we inject a dummy block with kn... | stack_v2_sparse_classes_75kplus_train_067493 | 5,228 | no_license | [
{
"docstring": "Init",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Display challenge info :return:",
"name": "display",
"signature": "def display(self)"
},
{
"docstring": "The idea is we are filling the prefix up to full block size as usual Then we in... | 5 | stack_v2_sparse_classes_30k_train_036102 | Implement the Python class `Challenge16` described below.
Class description:
Implement the Challenge16 class.
Method signatures and docstrings:
- def __init__(self): Init
- def display(self): Display challenge info :return:
- def run(self): The idea is we are filling the prefix up to full block size as usual Then we ... | Implement the Python class `Challenge16` described below.
Class description:
Implement the Challenge16 class.
Method signatures and docstrings:
- def __init__(self): Init
- def display(self): Display challenge info :return:
- def run(self): The idea is we are filling the prefix up to full block size as usual Then we ... | 8e5a5b8216b3ee91b72a7388289bb5658721d375 | <|skeleton|>
class Challenge16:
def __init__(self):
"""Init"""
<|body_0|>
def display(self):
"""Display challenge info :return:"""
<|body_1|>
def run(self):
"""The idea is we are filling the prefix up to full block size as usual Then we inject a dummy block with kn... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Challenge16:
def __init__(self):
"""Init"""
self.key = generate_random_aes_key()
self.keysize = len(self.key)
self.iv = b'0' * len(self.key)
self.prefix = 'comment1=cooking%20MCs;userdata='
self.suffix = ';comment2=%20like%20a%20pound%20of%20bacon'
def disp... | the_stack_v2_python_sparse | challenges/set_02_block_crypto/challenge_16_cbc_bit_flipping_attack.py | matei/cryptopals | train | 0 | |
d2512f3e345335fbbeea4df9aef0c3124adbd787 | [
"q_data = request.query_params\nser = GetPortfolioSerializer(data=q_data)\nif ser.is_valid(raise_exception=False):\n return send_200(data=ser.data, message='portfolios retrieved successfully')\nreturn send_400(status='FAILED', data={'errors': ser.errors}, message=ser.extract_error_msg())",
"data = dict(request... | <|body_start_0|>
q_data = request.query_params
ser = GetPortfolioSerializer(data=q_data)
if ser.is_valid(raise_exception=False):
return send_200(data=ser.data, message='portfolios retrieved successfully')
return send_400(status='FAILED', data={'errors': ser.errors}, message=s... | PortfolioInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortfolioInfo:
def get(self, request):
"""Get protflios of an user"""
<|body_0|>
def post(self, request):
"""Register a new portfolio for user"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
q_data = request.query_params
ser = GetPortfolioSe... | stack_v2_sparse_classes_75kplus_train_067494 | 4,414 | no_license | [
{
"docstring": "Get protflios of an user",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Register a new portfolio for user",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_test_002350 | Implement the Python class `PortfolioInfo` described below.
Class description:
Implement the PortfolioInfo class.
Method signatures and docstrings:
- def get(self, request): Get protflios of an user
- def post(self, request): Register a new portfolio for user | Implement the Python class `PortfolioInfo` described below.
Class description:
Implement the PortfolioInfo class.
Method signatures and docstrings:
- def get(self, request): Get protflios of an user
- def post(self, request): Register a new portfolio for user
<|skeleton|>
class PortfolioInfo:
def get(self, requ... | 3a64de39af7c51f6702c0e84a9c034055d72780e | <|skeleton|>
class PortfolioInfo:
def get(self, request):
"""Get protflios of an user"""
<|body_0|>
def post(self, request):
"""Register a new portfolio for user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PortfolioInfo:
def get(self, request):
"""Get protflios of an user"""
q_data = request.query_params
ser = GetPortfolioSerializer(data=q_data)
if ser.is_valid(raise_exception=False):
return send_200(data=ser.data, message='portfolios retrieved successfully')
... | the_stack_v2_python_sparse | stashaway/api/portfolio.py | ritzvik/sample-portfolio-manager | train | 0 | |
b83e0c4f970a56257e8f2ea5e5d60644e2d35492 | [
"\"\"\"\n Explanation: Using a set, we can see what values already exist in\n the array as we iterate through wih O(1) retrieval. If the set already contains\n the value we're at, we return True to denote that a duplicate is found. Otherwise,\n we return False at the end after we've made... | <|body_start_0|>
"""
Explanation: Using a set, we can see what values already exist in
the array as we iterate through wih O(1) retrieval. If the set already contains
the value we're at, we return True to denote that a duplicate is found. Otherwise,
... | Duplicates | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Duplicates:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def findDisappearedNumbers(self, nums):
""":type nums: Lis... | stack_v2_sparse_classes_75kplus_train_067495 | 2,726 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "containsDuplicate",
"signature": "def containsDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDuplicates",
"signature": "def findDuplicates(self, nums)"
},
{
"docstring"... | 3 | null | Implement the Python class `Duplicates` described below.
Class description:
Implement the Duplicates class.
Method signatures and docstrings:
- def containsDuplicate(self, nums): :type nums: List[int] :rtype: bool
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers(s... | Implement the Python class `Duplicates` described below.
Class description:
Implement the Duplicates class.
Method signatures and docstrings:
- def containsDuplicate(self, nums): :type nums: List[int] :rtype: bool
- def findDuplicates(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers(s... | 6f62fa7449f4e6f76a68068ec36587fe426734be | <|skeleton|>
class Duplicates:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def findDuplicates(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def findDisappearedNumbers(self, nums):
""":type nums: Lis... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Duplicates:
def containsDuplicate(self, nums):
""":type nums: List[int] :rtype: bool"""
"""
Explanation: Using a set, we can see what values already exist in
the array as we iterate through wih O(1) retrieval. If the set already contains
the valu... | the_stack_v2_python_sparse | Questions/Duplicates.py | yojoecool/InterviewPrep | train | 1 | |
caf27bafdc9196e64def7d6b5d06a88acadd507d | [
"service_id = request.args.get('service_id')\nstart_date = request.args.get('start_date')\nend_date = request.args.get('end_date')\ntry:\n return (get_all_orders(service_id, start_date, end_date), 200)\nexcept Exception:\n orders_namespace.abort(400, 'An error occured')",
"post_data = request.get_json()\nse... | <|body_start_0|>
service_id = request.args.get('service_id')
start_date = request.args.get('start_date')
end_date = request.args.get('end_date')
try:
return (get_all_orders(service_id, start_date, end_date), 200)
except Exception:
orders_namespace.abort(40... | OrdersList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrdersList:
def get(self):
"""Returns all orders"""
<|body_0|>
def post(self):
"""Creates a new service request."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
service_id = request.args.get('service_id')
start_date = request.args.get('start... | stack_v2_sparse_classes_75kplus_train_067496 | 4,484 | no_license | [
{
"docstring": "Returns all orders",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Creates a new service request.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_026604 | Implement the Python class `OrdersList` described below.
Class description:
Implement the OrdersList class.
Method signatures and docstrings:
- def get(self): Returns all orders
- def post(self): Creates a new service request. | Implement the Python class `OrdersList` described below.
Class description:
Implement the OrdersList class.
Method signatures and docstrings:
- def get(self): Returns all orders
- def post(self): Creates a new service request.
<|skeleton|>
class OrdersList:
def get(self):
"""Returns all orders"""
... | f96bf6b151cea0905080a4b3d1d55f23c31c64b3 | <|skeleton|>
class OrdersList:
def get(self):
"""Returns all orders"""
<|body_0|>
def post(self):
"""Creates a new service request."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OrdersList:
def get(self):
"""Returns all orders"""
service_id = request.args.get('service_id')
start_date = request.args.get('start_date')
end_date = request.args.get('end_date')
try:
return (get_all_orders(service_id, start_date, end_date), 200)
ex... | the_stack_v2_python_sparse | src/api/orders/views.py | tonyguesswho/quick-service | train | 0 | |
0a58edd96c5aee7ec583d1e6ff427d66cc62abbc | [
"super(InceptionModule, self).__init__()\nself.conv_1x1 = torch.nn.Sequential(DefaultConvolutionModule(in_channels=in_channels, out_channels=num1x1, kernel=1))\nself.conv_3x3 = torch.nn.Sequential(DefaultConvolutionModule(in_channels=in_channels, out_channels=num3x3reduce, kernel=1), DefaultConvolutionModule(in_cha... | <|body_start_0|>
super(InceptionModule, self).__init__()
self.conv_1x1 = torch.nn.Sequential(DefaultConvolutionModule(in_channels=in_channels, out_channels=num1x1, kernel=1))
self.conv_3x3 = torch.nn.Sequential(DefaultConvolutionModule(in_channels=in_channels, out_channels=num3x3reduce, kernel=1... | This class defines the Inception Module for the GoogLeNet Architecture. | InceptionModule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InceptionModule:
"""This class defines the Inception Module for the GoogLeNet Architecture."""
def __init__(self, in_channels, num1x1, num3x3reduce, num3x3, num5x5reduce, num5x5, num1x1reduce):
"""The constructor of the InceptionModule class. :param in_channels: number of input chann... | stack_v2_sparse_classes_75kplus_train_067497 | 7,584 | no_license | [
{
"docstring": "The constructor of the InceptionModule class. :param in_channels: number of input channel :param num1x1: channel size of 1x1 convolution :param num3x3reduce: bottleneck channel size of 3x3 convolution :param num3x3: channel size of 3x3 convolution :param num5x5reduce: bottleneck channel size of ... | 2 | stack_v2_sparse_classes_30k_train_040673 | Implement the Python class `InceptionModule` described below.
Class description:
This class defines the Inception Module for the GoogLeNet Architecture.
Method signatures and docstrings:
- def __init__(self, in_channels, num1x1, num3x3reduce, num3x3, num5x5reduce, num5x5, num1x1reduce): The constructor of the Incepti... | Implement the Python class `InceptionModule` described below.
Class description:
This class defines the Inception Module for the GoogLeNet Architecture.
Method signatures and docstrings:
- def __init__(self, in_channels, num1x1, num3x3reduce, num3x3, num5x5reduce, num5x5, num1x1reduce): The constructor of the Incepti... | e5560febfbf0f6e2d275f1147576d43411b1f182 | <|skeleton|>
class InceptionModule:
"""This class defines the Inception Module for the GoogLeNet Architecture."""
def __init__(self, in_channels, num1x1, num3x3reduce, num3x3, num5x5reduce, num5x5, num1x1reduce):
"""The constructor of the InceptionModule class. :param in_channels: number of input chann... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InceptionModule:
"""This class defines the Inception Module for the GoogLeNet Architecture."""
def __init__(self, in_channels, num1x1, num3x3reduce, num3x3, num5x5reduce, num5x5, num1x1reduce):
"""The constructor of the InceptionModule class. :param in_channels: number of input channel :param num... | the_stack_v2_python_sparse | GoogLeNet/model.py | ldmichel/DeepLearning_MiniProjects | train | 0 |
e2a24c4e7c8e369d2f4267652c1940486e416620 | [
"if len(nums) == 0:\n return None\nself.sums = [0 for _ in range(len(nums))]\nself.sums[0] = nums[0]\nfor i in range(1, len(nums)):\n self.sums[i] = self.sums[i - 1] + nums[i]",
"if i > 0 and j > 0:\n return self.sums[j] - self.sums[i - 1]\nelse:\n return self.sums[j]"
] | <|body_start_0|>
if len(nums) == 0:
return None
self.sums = [0 for _ in range(len(nums))]
self.sums[0] = nums[0]
for i in range(1, len(nums)):
self.sums[i] = self.sums[i - 1] + nums[i]
<|end_body_0|>
<|body_start_1|>
if i > 0 and j > 0:
return... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) == 0:
return None
self.sum... | stack_v2_sparse_classes_75kplus_train_067498 | 1,117 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type i: int :type j: int :rtype: int",
"name": "sumRange",
"signature": "def sumRange(self, i, j)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020811 | 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 sumRange(self, i, j): :type i: int :type j: int :rtype: int | 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 sumRange(self, i, j): :type i: int :type j: int :rtype: int
<|skeleton|>
class NumArray:
def __init__(self, nums):
... | 7fa160362ebb58e7286b490012542baa2d51e5c9 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
if len(nums) == 0:
return None
self.sums = [0 for _ in range(len(nums))]
self.sums[0] = nums[0]
for i in range(1, len(nums)):
self.sums[i] = self.sums[i - 1] + nums[i]
def sumRa... | the_stack_v2_python_sparse | sum/range_sum_query.py | gerrycfchang/leetcode-python | train | 2 | |
87f201cdb85ffd756c31bc68a2b50350d81d37ed | [
"if request.user and request.user.is_staff:\n return True\nelif request.user and request.user.role_id == 4:\n return True\nreturn False",
"if request.method == 'POST' or request.method == 'PUT':\n is_seller_assigned = hasattr(obj, 'seller_assigned') and request.user.id == obj.seller_assigned.id\n is_s... | <|body_start_0|>
if request.user and request.user.is_staff:
return True
elif request.user and request.user.role_id == 4:
return True
return False
<|end_body_0|>
<|body_start_1|>
if request.method == 'POST' or request.method == 'PUT':
is_seller_assigne... | Solo Administradores o Vendedores. | IsAdminOrSeller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsAdminOrSeller:
"""Solo Administradores o Vendedores."""
def has_permission(self, request, view):
"""Permiso General."""
<|body_0|>
def has_object_permission(self, request, view, obj):
"""Permiso de nivel objeto. PAara saber si se trata del vendedor del obj o un... | stack_v2_sparse_classes_75kplus_train_067499 | 7,085 | no_license | [
{
"docstring": "Permiso General.",
"name": "has_permission",
"signature": "def has_permission(self, request, view)"
},
{
"docstring": "Permiso de nivel objeto. PAara saber si se trata del vendedor del obj o un admin",
"name": "has_object_permission",
"signature": "def has_object_permissi... | 2 | null | Implement the Python class `IsAdminOrSeller` described below.
Class description:
Solo Administradores o Vendedores.
Method signatures and docstrings:
- def has_permission(self, request, view): Permiso General.
- def has_object_permission(self, request, view, obj): Permiso de nivel objeto. PAara saber si se trata del ... | Implement the Python class `IsAdminOrSeller` described below.
Class description:
Solo Administradores o Vendedores.
Method signatures and docstrings:
- def has_permission(self, request, view): Permiso General.
- def has_object_permission(self, request, view, obj): Permiso de nivel objeto. PAara saber si se trata del ... | 3135a4142c38f367a152e1fc79fee8af8fca4bcc | <|skeleton|>
class IsAdminOrSeller:
"""Solo Administradores o Vendedores."""
def has_permission(self, request, view):
"""Permiso General."""
<|body_0|>
def has_object_permission(self, request, view, obj):
"""Permiso de nivel objeto. PAara saber si se trata del vendedor del obj o un... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IsAdminOrSeller:
"""Solo Administradores o Vendedores."""
def has_permission(self, request, view):
"""Permiso General."""
if request.user and request.user.is_staff:
return True
elif request.user and request.user.role_id == 4:
return True
return Fals... | the_stack_v2_python_sparse | api/permissions.py | darwinv/api-chat-lnk | train | 0 |
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