blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8490fd537ed5d3c28cd597e45f54b5668d6934b4 | [
"super().__init__()\nself.lstm = nn.LSTM(dim_in, hidden_dim, batch_first=True, dropout=dropout, bidirectional=bidirectional)\nself.lstm.flatten_parameters()\nself.output_dim = 2 * hidden_dim if bidirectional else hidden_dim\nself.bidirectional = bidirectional",
"assert data.dim() == 3\nb, t = (data.shape[0], data... | <|body_start_0|>
super().__init__()
self.lstm = nn.LSTM(dim_in, hidden_dim, batch_first=True, dropout=dropout, bidirectional=bidirectional)
self.lstm.flatten_parameters()
self.output_dim = 2 * hidden_dim if bidirectional else hidden_dim
self.bidirectional = bidirectional
<|end_bo... | Wrapper for torch.nn.LSTM that handles masked inputs. | LSTM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LSTM:
"""Wrapper for torch.nn.LSTM that handles masked inputs."""
def __init__(self, dim_in: int, hidden_dim: int, dropout: float=0.0, bidirectional: bool=False):
"""Args: dim_in (int): input feature dimension hidden_dim (int): hidden dimesion of lstm layer dropout (float): dropout r... | stack_v2_sparse_classes_36k_train_008500 | 13,032 | permissive | [
{
"docstring": "Args: dim_in (int): input feature dimension hidden_dim (int): hidden dimesion of lstm layer dropout (float): dropout rate - 0.0 if no dropout bidirectional (bool): bidirectional or forward only",
"name": "__init__",
"signature": "def __init__(self, dim_in: int, hidden_dim: int, dropout: ... | 2 | stack_v2_sparse_classes_30k_train_018889 | Implement the Python class `LSTM` described below.
Class description:
Wrapper for torch.nn.LSTM that handles masked inputs.
Method signatures and docstrings:
- def __init__(self, dim_in: int, hidden_dim: int, dropout: float=0.0, bidirectional: bool=False): Args: dim_in (int): input feature dimension hidden_dim (int):... | Implement the Python class `LSTM` described below.
Class description:
Wrapper for torch.nn.LSTM that handles masked inputs.
Method signatures and docstrings:
- def __init__(self, dim_in: int, hidden_dim: int, dropout: float=0.0, bidirectional: bool=False): Args: dim_in (int): input feature dimension hidden_dim (int):... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class LSTM:
"""Wrapper for torch.nn.LSTM that handles masked inputs."""
def __init__(self, dim_in: int, hidden_dim: int, dropout: float=0.0, bidirectional: bool=False):
"""Args: dim_in (int): input feature dimension hidden_dim (int): hidden dimesion of lstm layer dropout (float): dropout r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LSTM:
"""Wrapper for torch.nn.LSTM that handles masked inputs."""
def __init__(self, dim_in: int, hidden_dim: int, dropout: float=0.0, bidirectional: bool=False):
"""Args: dim_in (int): input feature dimension hidden_dim (int): hidden dimesion of lstm layer dropout (float): dropout rate - 0.0 if ... | the_stack_v2_python_sparse | pytorchvideo/models/masked_multistream.py | xchani/pytorchvideo | train | 0 |
674a200c9a860fc2f4141392e3ede2a365799fd7 | [
"fmt = determine_format(request, self._meta.serializer, default_format=self._meta.default_format)\nif fmt == 'text/html' and 'format' not in request:\n fmt = 'application/json'\nreturn fmt",
"for f in mandatory_fields:\n if f not in bundle.data.keys():\n raise ImmediateHttpResponse(HttpBadRequest('%s... | <|body_start_0|>
fmt = determine_format(request, self._meta.serializer, default_format=self._meta.default_format)
if fmt == 'text/html' and 'format' not in request:
fmt = 'application/json'
return fmt
<|end_body_0|>
<|body_start_1|>
for f in mandatory_fields:
if ... | All resourses are inheriting this resource, it have all functions which is commonly using to all classes | CustomBaseResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomBaseResource:
"""All resourses are inheriting this resource, it have all functions which is commonly using to all classes"""
def determine_format(self, request):
"""return application/json as the default format"""
<|body_0|>
def check_mandatory_fields(self, bundle,... | stack_v2_sparse_classes_36k_train_008501 | 4,830 | no_license | [
{
"docstring": "return application/json as the default format",
"name": "determine_format",
"signature": "def determine_format(self, request)"
},
{
"docstring": "For given mandatory fields it will check from bundle. raise error if not present",
"name": "check_mandatory_fields",
"signatur... | 2 | null | Implement the Python class `CustomBaseResource` described below.
Class description:
All resourses are inheriting this resource, it have all functions which is commonly using to all classes
Method signatures and docstrings:
- def determine_format(self, request): return application/json as the default format
- def chec... | Implement the Python class `CustomBaseResource` described below.
Class description:
All resourses are inheriting this resource, it have all functions which is commonly using to all classes
Method signatures and docstrings:
- def determine_format(self, request): return application/json as the default format
- def chec... | ec9e7896f0b005002111cdf26a375813a388cf53 | <|skeleton|>
class CustomBaseResource:
"""All resourses are inheriting this resource, it have all functions which is commonly using to all classes"""
def determine_format(self, request):
"""return application/json as the default format"""
<|body_0|>
def check_mandatory_fields(self, bundle,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomBaseResource:
"""All resourses are inheriting this resource, it have all functions which is commonly using to all classes"""
def determine_format(self, request):
"""return application/json as the default format"""
fmt = determine_format(request, self._meta.serializer, default_format... | the_stack_v2_python_sparse | src/gladminds/core/apis/base_apis.py | ashish-srivastava92/GladmindsAshish | train | 0 |
fbd4f259eb05a05b195ed671144c69d02b491f3e | [
"functions = {'MD5': hashlib.md5, 'SHA1': hashlib.sha1, 'SHA224': hashlib.sha224, 'SHA256': hashlib.sha256, 'SHA384': hashlib.sha384, 'SHA512': hashlib.sha512}\nself.hash_function = functions[selected_hash]\nself.splitter = splitter",
"hash_function = self.hash_function()\nhash_function.update(block)\nreturn hash... | <|body_start_0|>
functions = {'MD5': hashlib.md5, 'SHA1': hashlib.sha1, 'SHA224': hashlib.sha224, 'SHA256': hashlib.sha256, 'SHA384': hashlib.sha384, 'SHA512': hashlib.sha512}
self.hash_function = functions[selected_hash]
self.splitter = splitter
<|end_body_0|>
<|body_start_1|>
hash_fun... | Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty | HashedSplitterDriver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HashedSplitterDriver:
"""Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty"""
def __init__(self, splitter, selected_hash):
"""Consctor of a HashedXorDriver. keyword arguments: n_blocks -- number of blocks to generate selected_hash... | stack_v2_sparse_classes_36k_train_008502 | 2,436 | permissive | [
{
"docstring": "Consctor of a HashedXorDriver. keyword arguments: n_blocks -- number of blocks to generate selected_hash -- hash function used to create a digest of a block.",
"name": "__init__",
"signature": "def __init__(self, splitter, selected_hash)"
},
{
"docstring": "Private function to cr... | 4 | stack_v2_sparse_classes_30k_train_004815 | Implement the Python class `HashedSplitterDriver` described below.
Class description:
Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty
Method signatures and docstrings:
- def __init__(self, splitter, selected_hash): Consctor of a HashedXorDriver. keyword argument... | Implement the Python class `HashedSplitterDriver` described below.
Class description:
Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty
Method signatures and docstrings:
- def __init__(self, splitter, selected_hash): Consctor of a HashedXorDriver. keyword argument... | e9138580594569cbbc7d325e8cd4b1740667edac | <|skeleton|>
class HashedSplitterDriver:
"""Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty"""
def __init__(self, splitter, selected_hash):
"""Consctor of a HashedXorDriver. keyword arguments: n_blocks -- number of blocks to generate selected_hash... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HashedSplitterDriver:
"""Class used to encrypt and genereate digest of a block. This Encryption guarantess privacy and integraty"""
def __init__(self, splitter, selected_hash):
"""Consctor of a HashedXorDriver. keyword arguments: n_blocks -- number of blocks to generate selected_hash -- hash func... | the_stack_v2_python_sparse | pyproxy/pyproxy/coder/safestore/hashed_splitter_driver.py | safecloud-project/recast | train | 0 |
f43647b1fd412382b395f84bb9b2fc91df018883 | [
"if not nums or len(nums) == 0:\n return\nself.total_sum = [0 for _ in range(len(nums))]\nself.total_sum[0] = nums[0]\nif len(self.total_sum) == 1:\n return\nfor idx in range(1, len(nums)):\n self.total_sum[idx] = self.total_sum[idx - 1] + nums[idx]",
"if i == 0:\n return self.total_sum[j]\nelse:\n ... | <|body_start_0|>
if not nums or len(nums) == 0:
return
self.total_sum = [0 for _ in range(len(nums))]
self.total_sum[0] = nums[0]
if len(self.total_sum) == 1:
return
for idx in range(1, len(nums)):
self.total_sum[idx] = self.total_sum[idx - 1] ... | NumArray | [
"MIT"
] | 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 not nums or len(nums) == 0:
return
s... | stack_v2_sparse_classes_36k_train_008503 | 1,218 | permissive | [
{
"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 | null | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def 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):
... | 5097f69bb0050d963c784d6bc0e88a7e871568ed | <|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_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
if not nums or len(nums) == 0:
return
self.total_sum = [0 for _ in range(len(nums))]
self.total_sum[0] = nums[0]
if len(self.total_sum) == 1:
return
for idx in range(1, len(n... | the_stack_v2_python_sparse | 300-/303.py | yshshadow/Leetcode | train | 0 | |
de5bdcf5a8363ba879073aee8e66ce7485141306 | [
"prefix = nums[:]\nfor i in range(1, len(prefix)):\n prefix[i] += prefix[i - 1]\nself.prefix = prefix",
"if i == 0:\n return self.prefix[j]\nelse:\n return self.prefix[j] - self.prefix[i - 1]"
] | <|body_start_0|>
prefix = nums[:]
for i in range(1, len(prefix)):
prefix[i] += prefix[i - 1]
self.prefix = prefix
<|end_body_0|>
<|body_start_1|>
if i == 0:
return self.prefix[j]
else:
return self.prefix[j] - self.prefix[i - 1]
<|end_body_1|>
| 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|>
prefix = nums[:]
for i in range(1, len(prefix)):
... | stack_v2_sparse_classes_36k_train_008504 | 586 | 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_012214 | 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):
... | 0e35e4cc87bd41144b8e34302aafe776fec1b356 | <|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_36k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
prefix = nums[:]
for i in range(1, len(prefix)):
prefix[i] += prefix[i - 1]
self.prefix = prefix
def sumRange(self, i, j):
""":type i: int :type j: int :rtype: int"""
if i == 0:
... | the_stack_v2_python_sparse | LeetCode/303-range_sum_query_immutable.py | davll/practical-algorithms | train | 0 | |
d7eeb73e4b61324a3ce88c5b7c42284923b15b2d | [
"login_page.LoginPage(self.driver).login()\nsleep(3)\nlandlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()\nsleep(3)\nlandlord_nav_page.LandlordNavPage(self.driver).close_weiChat()\nsleep(3)\nlandlord_nav_page.LandlordNavPage(self.driver).roommanager()\nsleep(3)\npo = landlord_read_page.LandlordReadPage(sel... | <|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(3)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(3)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
sleep(3)
landlord_nav_page.LandlordNavPage(self.driver).roomman... | 房源管理-房东必读 | TestLandlordRead | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLandlordRead:
"""房源管理-房东必读"""
def test_agreement(self):
"""服务协议"""
<|body_0|>
def test_landlord_read(self):
"""房东规则"""
<|body_1|>
def test_tenant_rule(self):
"""房客规则"""
<|body_2|>
def test_roomauditrule(self):
"""房间审核... | stack_v2_sparse_classes_36k_train_008505 | 4,003 | permissive | [
{
"docstring": "服务协议",
"name": "test_agreement",
"signature": "def test_agreement(self)"
},
{
"docstring": "房东规则",
"name": "test_landlord_read",
"signature": "def test_landlord_read(self)"
},
{
"docstring": "房客规则",
"name": "test_tenant_rule",
"signature": "def test_tenant... | 6 | stack_v2_sparse_classes_30k_train_011707 | Implement the Python class `TestLandlordRead` described below.
Class description:
房源管理-房东必读
Method signatures and docstrings:
- def test_agreement(self): 服务协议
- def test_landlord_read(self): 房东规则
- def test_tenant_rule(self): 房客规则
- def test_roomauditrule(self): 房间审核规范
- def test_privacypolicy(self): 隐私条款
- def test_... | Implement the Python class `TestLandlordRead` described below.
Class description:
房源管理-房东必读
Method signatures and docstrings:
- def test_agreement(self): 服务协议
- def test_landlord_read(self): 房东规则
- def test_tenant_rule(self): 房客规则
- def test_roomauditrule(self): 房间审核规范
- def test_privacypolicy(self): 隐私条款
- def test_... | 192c70c49a8e9e072b9d0d0136f02c653c589410 | <|skeleton|>
class TestLandlordRead:
"""房源管理-房东必读"""
def test_agreement(self):
"""服务协议"""
<|body_0|>
def test_landlord_read(self):
"""房东规则"""
<|body_1|>
def test_tenant_rule(self):
"""房客规则"""
<|body_2|>
def test_roomauditrule(self):
"""房间审核... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLandlordRead:
"""房源管理-房东必读"""
def test_agreement(self):
"""服务协议"""
login_page.LoginPage(self.driver).login()
sleep(3)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(3)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
... | the_stack_v2_python_sparse | mayi/test_case/test_landlord_read.py | 18701016443/mayi | train | 0 |
ac53cfcd3a64493e0ae54c879ed11c122106dcc9 | [
"if self.memory:\n return str(self.data)\nwith helpers.ensure_open(self):\n return self.text_stream.read(size)",
"resource = target\nif not isinstance(resource, Resource):\n resource = TextResource(**options)\nif not isinstance(resource, TextResource):\n raise FrictionlessException('target must be a t... | <|body_start_0|>
if self.memory:
return str(self.data)
with helpers.ensure_open(self):
return self.text_stream.read(size)
<|end_body_0|>
<|body_start_1|>
resource = target
if not isinstance(resource, Resource):
resource = TextResource(**options)
... | TextResource | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextResource:
def read_text(self, *, size: Optional[int]=None) -> str:
"""Read text into memory Returns: str: resource text"""
<|body_0|>
def write_text(self, target: Optional[Union[TextResource, Any]]=None, **options: Any):
"""Write text data to the target"""
... | stack_v2_sparse_classes_36k_train_008506 | 1,414 | permissive | [
{
"docstring": "Read text into memory Returns: str: resource text",
"name": "read_text",
"signature": "def read_text(self, *, size: Optional[int]=None) -> str"
},
{
"docstring": "Write text data to the target",
"name": "write_text",
"signature": "def write_text(self, target: Optional[Uni... | 2 | stack_v2_sparse_classes_30k_train_011764 | Implement the Python class `TextResource` described below.
Class description:
Implement the TextResource class.
Method signatures and docstrings:
- def read_text(self, *, size: Optional[int]=None) -> str: Read text into memory Returns: str: resource text
- def write_text(self, target: Optional[Union[TextResource, Any... | Implement the Python class `TextResource` described below.
Class description:
Implement the TextResource class.
Method signatures and docstrings:
- def read_text(self, *, size: Optional[int]=None) -> str: Read text into memory Returns: str: resource text
- def write_text(self, target: Optional[Union[TextResource, Any... | 740319edeee58f12cc6956a53356f3065ff18cbb | <|skeleton|>
class TextResource:
def read_text(self, *, size: Optional[int]=None) -> str:
"""Read text into memory Returns: str: resource text"""
<|body_0|>
def write_text(self, target: Optional[Union[TextResource, Any]]=None, **options: Any):
"""Write text data to the target"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextResource:
def read_text(self, *, size: Optional[int]=None) -> str:
"""Read text into memory Returns: str: resource text"""
if self.memory:
return str(self.data)
with helpers.ensure_open(self):
return self.text_stream.read(size)
def write_text(self, targ... | the_stack_v2_python_sparse | frictionless/resources/text.py | frictionlessdata/frictionless-py | train | 295 | |
6d893bdd9c23dae4a8e214c517b4a1d2764e53f7 | [
"self.foods = []\nfor fx, fy in food:\n self.foods.append((fx, fy))\nself.food_index = 0\nself.width = width\nself.height = height\nself.body = [[0, 0]]",
"head_x, head_y = self.body[0]\nnext_x = head_x\nnext_y = head_y\nif direction == 'U':\n next_x -= 1\nelif direction == 'L':\n next_y -= 1\nelif direc... | <|body_start_0|>
self.foods = []
for fx, fy in food:
self.foods.append((fx, fy))
self.food_index = 0
self.width = width
self.height = height
self.body = [[0, 0]]
<|end_body_0|>
<|body_start_1|>
head_x, head_y = self.body[0]
next_x = head_x
... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k_train_008507 | 1,998 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | null | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | 696a25f8597e2a5bc5ab788924418d6423160af1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | 353_design_snake_game.py | tooyoungtoosimplesometimesnaive/probable-octo-potato | train | 0 | |
dbf772f49fad5a963043fb4b09419134b64eda40 | [
"coord = torch.stack(data_samples.metainfo['coord']).to(inputs)\ncell = torch.stack(data_samples.metainfo['cell']).to(inputs)\nfeats = self.generator(inputs, coord, cell, **kwargs)\nreturn feats",
"feats = self.forward_tensor(inputs, data_samples, test_mode=True)\nih, iw = inputs.shape[-2:]\ncoord_count = data_sa... | <|body_start_0|>
coord = torch.stack(data_samples.metainfo['coord']).to(inputs)
cell = torch.stack(data_samples.metainfo['cell']).to(inputs)
feats = self.generator(inputs, coord, cell, **kwargs)
return feats
<|end_body_0|>
<|body_start_1|>
feats = self.forward_tensor(inputs, dat... | LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path for pretrained model. Default: None. data_preprocessor (dict, optional):... | LIIF | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LIIF:
"""LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path for pretrained model. Default: None. dat... | stack_v2_sparse_classes_36k_train_008508 | 2,572 | permissive | [
{
"docstring": "Forward tensor. Returns result of simple forward. Args: inputs (torch.Tensor): batch input tensor collated by :attr:`data_preprocessor`. data_samples (List[BaseDataElement], optional): data samples collated by :attr:`data_preprocessor`. Returns: Tensor: result of simple forward.",
"name": "f... | 2 | null | Implement the Python class `LIIF` described below.
Class description:
LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path f... | Implement the Python class `LIIF` described below.
Class description:
LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path f... | a382f143c0fd20d227e1e5524831ba26a568190d | <|skeleton|>
class LIIF:
"""LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path for pretrained model. Default: None. dat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LIIF:
"""LIIF model for single image super-resolution. Paper: Learning Continuous Image Representation with Local Implicit Image Function Args: generator (dict): Config for the generator. pixel_loss (dict): Config for the pixel loss. pretrained (str): Path for pretrained model. Default: None. data_preprocesso... | the_stack_v2_python_sparse | mmagic/models/editors/liif/liif.py | open-mmlab/mmagic | train | 1,370 |
ac80d0fb8db7912b1ab79e8838a1b257a2b8ac03 | [
"m1, m2 = (sys.maxsize, sys.maxsize)\nfor i in nums:\n if m1 >= i:\n m1 = i\n elif m2 >= i:\n m2 = i\n else:\n return True\nreturn False",
"n = len(nums)\nif n < 3:\n return False\nf = [nums[0]] * n\nb = [nums[-1]] * n\nfor i in range(1, n):\n f[i] = min(f[i - 1], nums[i])\nfor... | <|body_start_0|>
m1, m2 = (sys.maxsize, sys.maxsize)
for i in nums:
if m1 >= i:
m1 = i
elif m2 >= i:
m2 = i
else:
return True
return False
<|end_body_0|>
<|body_start_1|>
n = len(nums)
if n < 3:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def increasingTripletO1Space(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m1, m2 = (sys.maxsize, s... | stack_v2_sparse_classes_36k_train_008509 | 1,715 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "increasingTriplet",
"signature": "def increasingTriplet(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "increasingTripletO1Space",
"signature": "def increasingTripletO1Space(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013697 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool
- def increasingTripletO1Space(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def increasingTriplet(self, nums): :type nums: List[int] :rtype: bool
- def increasingTripletO1Space(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def increasingTripletO1Space(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def increasingTriplet(self, nums):
""":type nums: List[int] :rtype: bool"""
m1, m2 = (sys.maxsize, sys.maxsize)
for i in nums:
if m1 >= i:
m1 = i
elif m2 >= i:
m2 = i
else:
return True
... | the_stack_v2_python_sparse | I/IncreasingTripletSubsequence.py | bssrdf/pyleet | train | 2 | |
d3afad4242879ffdf9cbb34934755f24a0b54f99 | [
"self.open(base_url + '/logout')\nself.open(base_url + '/login')\nself.type('#password', generate_password_hash('test_password'))\nself.click('input[type=\"submit\"]')\nself.assert_element('#message')\nself.assert_text('Email format incorrect: Cannot be empty', '#message')",
"self.open(base_url + '/logout')\nself... | <|body_start_0|>
self.open(base_url + '/logout')
self.open(base_url + '/login')
self.type('#password', generate_password_hash('test_password'))
self.click('input[type="submit"]')
self.assert_element('#message')
self.assert_text('Email format incorrect: Cannot be empty', '... | FrontEndLoginR1 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrontEndLoginR1:
def test_loginFormEmailEmpty(self, *_):
"""This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message"""
<|body_0|>
def test_loginFormPassEmpty(self, *_):
"""This function tests that the... | stack_v2_sparse_classes_36k_train_008510 | 1,752 | permissive | [
{
"docstring": "This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message",
"name": "test_loginFormEmailEmpty",
"signature": "def test_loginFormEmailEmpty(self, *_)"
},
{
"docstring": "This function tests that the user form cannot ... | 2 | stack_v2_sparse_classes_30k_train_007934 | Implement the Python class `FrontEndLoginR1` described below.
Class description:
Implement the FrontEndLoginR1 class.
Method signatures and docstrings:
- def test_loginFormEmailEmpty(self, *_): This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message
-... | Implement the Python class `FrontEndLoginR1` described below.
Class description:
Implement the FrontEndLoginR1 class.
Method signatures and docstrings:
- def test_loginFormEmailEmpty(self, *_): This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message
-... | 582e00a4c16016e545fedcbb14a745d125db94e0 | <|skeleton|>
class FrontEndLoginR1:
def test_loginFormEmailEmpty(self, *_):
"""This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message"""
<|body_0|>
def test_loginFormPassEmpty(self, *_):
"""This function tests that the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrontEndLoginR1:
def test_loginFormEmailEmpty(self, *_):
"""This function tests that the user form cannot be empty, if email is empty the message warns the user with an error message"""
self.open(base_url + '/logout')
self.open(base_url + '/login')
self.type('#password', genera... | the_stack_v2_python_sparse | qa327_test/frontend/login/test_R1_6.py | GraemeBadley/QA-Project | train | 0 | |
6e89f90a25df44a9580d8a73c8b9d2592759872d | [
"department = get_department(id_dept)\nif department:\n resp = jsonify(department)\n resp.status_code = 200\n return resp\nelse:\n resp = jsonify({'message': f'department #{id_dept} does not exist'})\n return resp",
"deleted = del_department(id_dept)\nif deleted:\n resp = jsonify({'message': f'd... | <|body_start_0|>
department = get_department(id_dept)
if department:
resp = jsonify(department)
resp.status_code = 200
return resp
else:
resp = jsonify({'message': f'department #{id_dept} does not exist'})
return resp
<|end_body_0|>
<|... | DepartmentItem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepartmentItem:
def get(self, id_dept):
"""Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if not -> message': department with id does not exist"""
<|body_0|>
def delete(self, id_dept):... | stack_v2_sparse_classes_36k_train_008511 | 3,115 | no_license | [
{
"docstring": "Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if not -> message': department with id does not exist",
"name": "get",
"signature": "def get(self, id_dept)"
},
{
"docstring": "Method get dep... | 3 | stack_v2_sparse_classes_30k_train_021687 | Implement the Python class `DepartmentItem` described below.
Class description:
Implement the DepartmentItem class.
Method signatures and docstrings:
- def get(self, id_dept): Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if n... | Implement the Python class `DepartmentItem` described below.
Class description:
Implement the DepartmentItem class.
Method signatures and docstrings:
- def get(self, id_dept): Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if n... | 8452b3671afce50b733379f278d1adf89e6e2ec9 | <|skeleton|>
class DepartmentItem:
def get(self, id_dept):
"""Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if not -> message': department with id does not exist"""
<|body_0|>
def delete(self, id_dept):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DepartmentItem:
def get(self, id_dept):
"""Method get department id from url and gets corresponding department :param dept_id: department id :return: if success -> department info, if not -> message': department with id does not exist"""
department = get_department(id_dept)
if departme... | the_stack_v2_python_sparse | department-app/rest/rest_departments.py | dgiart/final05_python_2021 | train | 0 | |
2903cc2bb853e9170eb33c9b9d040dadc0381b0a | [
"super().__init__()\nself.rel_pos_emb = torch.nn.Parameter(torch.randn(2 * seq_len - 1, int(dim_head)))\nself.rel_pos = calc_rel_pos(seq_len)",
"content_lambda = torch.einsum('bnk,bnv->bkv', torch.softmax(k, dim=-1), v)\ncontent_output = torch.einsum('bnk,bkv->bnv', q, content_lambda)\nrel_pos_emb = self.rel_pos_... | <|body_start_0|>
super().__init__()
self.rel_pos_emb = torch.nn.Parameter(torch.randn(2 * seq_len - 1, int(dim_head)))
self.rel_pos = calc_rel_pos(seq_len)
<|end_body_0|>
<|body_start_1|>
content_lambda = torch.einsum('bnk,bnv->bkv', torch.softmax(k, dim=-1), v)
content_output =... | LambdaLayer | [
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LambdaLayer:
def __init__(self, seq_len: int, dim_head: int, *_, **__):
"""Attention approximation using Lambda layers, from "Lambda networks: modeling long-range interactions without attention.", Bello, I. (2021)."""
<|body_0|>
def forward(self, q: torch.Tensor, k: torch.Te... | stack_v2_sparse_classes_36k_train_008512 | 2,479 | permissive | [
{
"docstring": "Attention approximation using Lambda layers, from \"Lambda networks: modeling long-range interactions without attention.\", Bello, I. (2021).",
"name": "__init__",
"signature": "def __init__(self, seq_len: int, dim_head: int, *_, **__)"
},
{
"docstring": "..NOTE: We're reusing th... | 2 | stack_v2_sparse_classes_30k_train_009314 | Implement the Python class `LambdaLayer` described below.
Class description:
Implement the LambdaLayer class.
Method signatures and docstrings:
- def __init__(self, seq_len: int, dim_head: int, *_, **__): Attention approximation using Lambda layers, from "Lambda networks: modeling long-range interactions without atte... | Implement the Python class `LambdaLayer` described below.
Class description:
Implement the LambdaLayer class.
Method signatures and docstrings:
- def __init__(self, seq_len: int, dim_head: int, *_, **__): Attention approximation using Lambda layers, from "Lambda networks: modeling long-range interactions without atte... | 71bab94cb954e6e291ca93d3bce5dffadab4286d | <|skeleton|>
class LambdaLayer:
def __init__(self, seq_len: int, dim_head: int, *_, **__):
"""Attention approximation using Lambda layers, from "Lambda networks: modeling long-range interactions without attention.", Bello, I. (2021)."""
<|body_0|>
def forward(self, q: torch.Tensor, k: torch.Te... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LambdaLayer:
def __init__(self, seq_len: int, dim_head: int, *_, **__):
"""Attention approximation using Lambda layers, from "Lambda networks: modeling long-range interactions without attention.", Bello, I. (2021)."""
super().__init__()
self.rel_pos_emb = torch.nn.Parameter(torch.randn... | the_stack_v2_python_sparse | xformers/components/attention/lambda_layer.py | hercules261188/xformers | train | 1 | |
12fc61b52c2bc0b426d2172e3d70c5d27fe95d99 | [
"if per_channel:\n return np.array(list(self.samples())).mean(axis=(0, 1, 2))\nreturn np.array(list(self.samples())).mean()",
"if per_channel:\n return np.array(list(self.samples())).std(axis=(0, 1, 2))\nreturn np.array(list(self.samples())).std()"
] | <|body_start_0|>
if per_channel:
return np.array(list(self.samples())).mean(axis=(0, 1, 2))
return np.array(list(self.samples())).mean()
<|end_body_0|>
<|body_start_1|>
if per_channel:
return np.array(list(self.samples())).std(axis=(0, 1, 2))
return np.array(list... | A dataset, consisting of multiple samples/images and corresponding class labels. | ImageDataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageDataset:
"""A dataset, consisting of multiple samples/images and corresponding class labels."""
def get_mean(self, per_channel=False):
"""Get the global mean of this dataset. The result value is cached."""
<|body_0|>
def get_stddev(self, per_channel=False):
... | stack_v2_sparse_classes_36k_train_008513 | 818 | no_license | [
{
"docstring": "Get the global mean of this dataset. The result value is cached.",
"name": "get_mean",
"signature": "def get_mean(self, per_channel=False)"
},
{
"docstring": "Get the global stddev of this dataset. The result value is cached.",
"name": "get_stddev",
"signature": "def get_... | 2 | stack_v2_sparse_classes_30k_train_001162 | Implement the Python class `ImageDataset` described below.
Class description:
A dataset, consisting of multiple samples/images and corresponding class labels.
Method signatures and docstrings:
- def get_mean(self, per_channel=False): Get the global mean of this dataset. The result value is cached.
- def get_stddev(se... | Implement the Python class `ImageDataset` described below.
Class description:
A dataset, consisting of multiple samples/images and corresponding class labels.
Method signatures and docstrings:
- def get_mean(self, per_channel=False): Get the global mean of this dataset. The result value is cached.
- def get_stddev(se... | bed2b189340be52723aa4d53b4d51ad289a4a265 | <|skeleton|>
class ImageDataset:
"""A dataset, consisting of multiple samples/images and corresponding class labels."""
def get_mean(self, per_channel=False):
"""Get the global mean of this dataset. The result value is cached."""
<|body_0|>
def get_stddev(self, per_channel=False):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageDataset:
"""A dataset, consisting of multiple samples/images and corresponding class labels."""
def get_mean(self, per_channel=False):
"""Get the global mean of this dataset. The result value is cached."""
if per_channel:
return np.array(list(self.samples())).mean(axis=(0... | the_stack_v2_python_sparse | cnn-keras/dataset/ImageDataset.py | chaosmail/cvsp-age-gender-classification-16 | train | 2 |
f58aaa66a860ff7b50683f7d8ec80a8e9b9ae155 | [
"\"\"\":field\n The object ID.\n \"\"\"\nself.object_id: int = object_id\nself._solver_id: int = solver_id\nself._object_index: int = object_index\n':field\\n The positions of each particle as a numpy array.\\n '\nself.positions: np.ndarray = np.array([], dtype=np.float32)\n':field\\n ... | <|body_start_0|>
""":field
The object ID.
"""
self.object_id: int = object_id
self._solver_id: int = solver_id
self._object_index: int = object_index
':field\n The positions of each particle as a numpy array.\n '
self.position... | Data for an Obi actor. | ObiActor | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObiActor:
"""Data for an Obi actor."""
def __init__(self, object_id: int, solver_id: int, object_index: int):
""":param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The index of the object in the `ObiParticles` output data."""
... | stack_v2_sparse_classes_36k_train_008514 | 1,831 | permissive | [
{
"docstring": ":param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The index of the object in the `ObiParticles` output data.",
"name": "__init__",
"signature": "def __init__(self, object_id: int, solver_id: int, object_index: int)"
},
{
"d... | 2 | stack_v2_sparse_classes_30k_train_009295 | Implement the Python class `ObiActor` described below.
Class description:
Data for an Obi actor.
Method signatures and docstrings:
- def __init__(self, object_id: int, solver_id: int, object_index: int): :param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The ind... | Implement the Python class `ObiActor` described below.
Class description:
Data for an Obi actor.
Method signatures and docstrings:
- def __init__(self, object_id: int, solver_id: int, object_index: int): :param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The ind... | 9df96fba455b327bb360d8dd5886d8754046c690 | <|skeleton|>
class ObiActor:
"""Data for an Obi actor."""
def __init__(self, object_id: int, solver_id: int, object_index: int):
""":param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The index of the object in the `ObiParticles` output data."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObiActor:
"""Data for an Obi actor."""
def __init__(self, object_id: int, solver_id: int, object_index: int):
""":param object_id: The object ID. :param solver_id: The ID of the object's Obi solver. :param object_index: The index of the object in the `ObiParticles` output data."""
""":fie... | the_stack_v2_python_sparse | Python/tdw/obi_data/obi_actor.py | threedworld-mit/tdw | train | 427 |
9cbfd96b4dc7501a093b5abc5eb58486428739cf | [
"print('student__iter__')\nself.value = 5\nreturn self",
"print('student__next__')\nif self.value >= 0:\n self.value -= 1\n return self.value\nelse:\n raise StopIteration"
] | <|body_start_0|>
print('student__iter__')
self.value = 5
return self
<|end_body_0|>
<|body_start_1|>
print('student__next__')
if self.value >= 0:
self.value -= 1
return self.value
else:
raise StopIteration
<|end_body_1|>
| Color | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Color:
def __iter__(self):
"""遍历对象开始时，先调用这个函数"""
<|body_0|>
def __next__(self):
"""每循环一次，便调用一次，一直到发生了StopIteration异常为"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print('student__iter__')
self.value = 5
return self
<|end_body_0|>
... | stack_v2_sparse_classes_36k_train_008515 | 761 | no_license | [
{
"docstring": "遍历对象开始时，先调用这个函数",
"name": "__iter__",
"signature": "def __iter__(self)"
},
{
"docstring": "每循环一次，便调用一次，一直到发生了StopIteration异常为",
"name": "__next__",
"signature": "def __next__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000388 | Implement the Python class `Color` described below.
Class description:
Implement the Color class.
Method signatures and docstrings:
- def __iter__(self): 遍历对象开始时，先调用这个函数
- def __next__(self): 每循环一次，便调用一次，一直到发生了StopIteration异常为 | Implement the Python class `Color` described below.
Class description:
Implement the Color class.
Method signatures and docstrings:
- def __iter__(self): 遍历对象开始时，先调用这个函数
- def __next__(self): 每循环一次，便调用一次，一直到发生了StopIteration异常为
<|skeleton|>
class Color:
def __iter__(self):
"""遍历对象开始时，先调用这个函数"""
<... | 5e404417289ffd7fa564425c9d34513a0c08b860 | <|skeleton|>
class Color:
def __iter__(self):
"""遍历对象开始时，先调用这个函数"""
<|body_0|>
def __next__(self):
"""每循环一次，便调用一次，一直到发生了StopIteration异常为"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Color:
def __iter__(self):
"""遍历对象开始时，先调用这个函数"""
print('student__iter__')
self.value = 5
return self
def __next__(self):
"""每循环一次，便调用一次，一直到发生了StopIteration异常为"""
print('student__next__')
if self.value >= 0:
self.value -= 1
re... | the_stack_v2_python_sparse | day002/07_魔法函数_e_遍历.py | miaoshihu/learn_python | train | 0 | |
cb9b2dcfc5fc879ca9be2761faae15f1cf69b628 | [
"book = get_object_or_404(models.Edition, id=book_id)\nform = forms.ReadThroughForm()\ndata = {'form': form, 'book': book}\nif readthrough_id:\n data['readthrough'] = get_object_or_404(models.ReadThrough, id=readthrough_id)\nreturn TemplateResponse(request, 'readthrough/readthrough.html', data)",
"book_id = re... | <|body_start_0|>
book = get_object_or_404(models.Edition, id=book_id)
form = forms.ReadThroughForm()
data = {'form': form, 'book': book}
if readthrough_id:
data['readthrough'] = get_object_or_404(models.ReadThrough, id=readthrough_id)
return TemplateResponse(request, ... | Add new read dates | ReadThrough | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadThrough:
"""Add new read dates"""
def get(self, request, book_id, readthrough_id=None):
"""standalone form in case of errors"""
<|body_0|>
def post(self, request):
"""can't use the form normally because the dates are too finnicky"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_008516 | 8,188 | no_license | [
{
"docstring": "standalone form in case of errors",
"name": "get",
"signature": "def get(self, request, book_id, readthrough_id=None)"
},
{
"docstring": "can't use the form normally because the dates are too finnicky",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | null | Implement the Python class `ReadThrough` described below.
Class description:
Add new read dates
Method signatures and docstrings:
- def get(self, request, book_id, readthrough_id=None): standalone form in case of errors
- def post(self, request): can't use the form normally because the dates are too finnicky | Implement the Python class `ReadThrough` described below.
Class description:
Add new read dates
Method signatures and docstrings:
- def get(self, request, book_id, readthrough_id=None): standalone form in case of errors
- def post(self, request): can't use the form normally because the dates are too finnicky
<|skele... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class ReadThrough:
"""Add new read dates"""
def get(self, request, book_id, readthrough_id=None):
"""standalone form in case of errors"""
<|body_0|>
def post(self, request):
"""can't use the form normally because the dates are too finnicky"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadThrough:
"""Add new read dates"""
def get(self, request, book_id, readthrough_id=None):
"""standalone form in case of errors"""
book = get_object_or_404(models.Edition, id=book_id)
form = forms.ReadThroughForm()
data = {'form': form, 'book': book}
if readthroug... | the_stack_v2_python_sparse | bookwyrm/views/reading.py | bookwyrm-social/bookwyrm | train | 1,398 |
3fdb029283a1a664f8a6e0d3a973069fb07cc16e | [
"l, r = (0, len(nums) - 1)\nif nums[l] < nums[r] or len(nums) == 1:\n return nums[l]\nif len(nums) == 2:\n return min(nums[0], nums[1])\nwhile l < r:\n m = (l + r) // 2\n if m + 1 < len(nums) and nums[m] > nums[m + 1]:\n return nums[m + 1]\n if m - 1 >= 0 and nums[m - 1] > nums[m]:\n re... | <|body_start_0|>
l, r = (0, len(nums) - 1)
if nums[l] < nums[r] or len(nums) == 1:
return nums[l]
if len(nums) == 2:
return min(nums[0], nums[1])
while l < r:
m = (l + r) // 2
if m + 1 < len(nums) and nums[m] > nums[m + 1]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]"""
<|body_0|>
def findMin2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<... | stack_v2_sparse_classes_36k_train_008517 | 2,046 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]",
"name": "findMin",
"signature": "def findMin(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findMin2",
"signature": "def findMin2(... | 2 | stack_v2_sparse_classes_30k_train_002938 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMin(self, nums): :type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]
- def findMin2(self, nums): :type nums: Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMin(self, nums): :type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]
- def findMin2(self, nums): :type nums: Lis... | 85128e7d26157b3c36eb43868269de42ea2fcb98 | <|skeleton|>
class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]"""
<|body_0|>
def findMin2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMin(self, nums):
""":type nums: List[int] :rtype: int [3,4,5,5,5,6,6,1,1,2,3,3] [3,3,3,1] [1] [1,1] [2,2,2,0,1,2] [10,1,10,10,10]"""
l, r = (0, len(nums) - 1)
if nums[l] < nums[r] or len(nums) == 1:
return nums[l]
if len(nums) == 2:
ret... | the_stack_v2_python_sparse | src/Find Minimum in Rotated Sorted Array II.py | jsdiuf/leetcode | train | 1 | |
89fda9895a6eca166b978d46ec7ff15cc158b24b | [
"self.shards = shards\nself.id_col = schema['id_col']\nself.dt_col = schema['dt_col']\nself.feature_col = schema['feature_col'].copy()\nself.target_col = schema['target_col'].copy()\nself.numpy_shards = None\nself._id_list = list(shards[self.id_col].unique())",
"_check_type(shards, 'shards', SparkXShards)\ntarget... | <|body_start_0|>
self.shards = shards
self.id_col = schema['id_col']
self.dt_col = schema['dt_col']
self.feature_col = schema['feature_col'].copy()
self.target_col = schema['target_col'].copy()
self.numpy_shards = None
self._id_list = list(shards[self.id_col].uniq... | XShardsTSDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XShardsTSDataset:
def __init__(self, shards, **schema):
"""XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the transform methods. XShardTSDataset will partition the dataset by id_col, which is experimental."""
... | stack_v2_sparse_classes_36k_train_008518 | 8,833 | permissive | [
{
"docstring": "XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the transform methods. XShardTSDataset will partition the dataset by id_col, which is experimental.",
"name": "__init__",
"signature": "def __init__(self, shards, **schem... | 4 | stack_v2_sparse_classes_30k_train_014263 | Implement the Python class `XShardsTSDataset` described below.
Class description:
Implement the XShardsTSDataset class.
Method signatures and docstrings:
- def __init__(self, shards, **schema): XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the tr... | Implement the Python class `XShardsTSDataset` described below.
Class description:
Implement the XShardsTSDataset class.
Method signatures and docstrings:
- def __init__(self, shards, **schema): XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the tr... | 7cc3e2849057d6429d03b1af0db13caae57960a5 | <|skeleton|>
class XShardsTSDataset:
def __init__(self, shards, **schema):
"""XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the transform methods. XShardTSDataset will partition the dataset by id_col, which is experimental."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XShardsTSDataset:
def __init__(self, shards, **schema):
"""XShardTSDataset is an abstract of time series dataset with distributed fashion. Cascade call is supported for most of the transform methods. XShardTSDataset will partition the dataset by id_col, which is experimental."""
self.shards = ... | the_stack_v2_python_sparse | pyzoo/zoo/chronos/data/experimental/xshards_tsdataset.py | intel-analytics/analytics-zoo | train | 3,104 | |
8af36d333b5e6d20ca9350e733056ffe0f295f9d | [
"n = len(arr)\nfor i in range(n - 2):\n if all((j % 2 == 1 for j in arr[i:i + 3])):\n return True\nreturn False",
"n = len(arr)\nfor i in range(n - 2):\n if arr[i] & 1 and arr[i + 1] & 1 and arr[i + 2] & 1:\n return True\nreturn False"
] | <|body_start_0|>
n = len(arr)
for i in range(n - 2):
if all((j % 2 == 1 for j in arr[i:i + 3])):
return True
return False
<|end_body_0|>
<|body_start_1|>
n = len(arr)
for i in range(n - 2):
if arr[i] & 1 and arr[i + 1] & 1 and arr[i + 2] &... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeConsecutiveOdds(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_0|>
def threeConsecutiveOdds(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(arr)
for i in... | stack_v2_sparse_classes_36k_train_008519 | 628 | no_license | [
{
"docstring": ":type arr: List[int] :rtype: bool",
"name": "threeConsecutiveOdds",
"signature": "def threeConsecutiveOdds(self, arr)"
},
{
"docstring": ":type arr: List[int] :rtype: bool",
"name": "threeConsecutiveOdds",
"signature": "def threeConsecutiveOdds(self, arr)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeConsecutiveOdds(self, arr): :type arr: List[int] :rtype: bool
- def threeConsecutiveOdds(self, arr): :type arr: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeConsecutiveOdds(self, arr): :type arr: List[int] :rtype: bool
- def threeConsecutiveOdds(self, arr): :type arr: List[int] :rtype: bool
<|skeleton|>
class Solution:
... | a509b383a42f54313970168d9faa11f088f18708 | <|skeleton|>
class Solution:
def threeConsecutiveOdds(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_0|>
def threeConsecutiveOdds(self, arr):
""":type arr: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeConsecutiveOdds(self, arr):
""":type arr: List[int] :rtype: bool"""
n = len(arr)
for i in range(n - 2):
if all((j % 2 == 1 for j in arr[i:i + 3])):
return True
return False
def threeConsecutiveOdds(self, arr):
""":type... | the_stack_v2_python_sparse | 1550_Three_Consecutive_Odds.py | bingli8802/leetcode | train | 0 | |
61f61444cc0309097ced00faefc503d3a7bd51c2 | [
"self.vehtype = vehtype\nself.speed = speed\nself.acce = acce\nself.weight = weight\nself.space = space\nself.datetime = datetime\nif lane == 1:\n self.x = 90\n self.y = 720\nelse:\n self.x = 960 - 90 - 345\n self.y = -100\nself.color = (255, 255, 255)",
"self.str1 = u'车型: {0}轴车 时间: {1}'.format(self.v... | <|body_start_0|>
self.vehtype = vehtype
self.speed = speed
self.acce = acce
self.weight = weight
self.space = space
self.datetime = datetime
if lane == 1:
self.x = 90
self.y = 720
else:
self.x = 960 - 90 - 345
... | Veh class, each will print a veh's info | Veh | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a... | stack_v2_sparse_classes_36k_train_008520 | 3,873 | no_license | [
{
"docstring": "Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a standard datetime object)",
"name": "__init__",
"signature": "def __init__(self, vehtype, speed, acce, lane, weight, space, dateti... | 5 | stack_v2_sparse_classes_30k_train_003698 | Implement the Python class `Veh` described below.
Class description:
Veh class, each will print a veh's info
Method signatures and docstrings:
- def __init__(self, vehtype, speed, acce, lane, weight, space, datetime): Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight:... | Implement the Python class `Veh` described below.
Class description:
Veh class, each will print a veh's info
Method signatures and docstrings:
- def __init__(self, vehtype, speed, acce, lane, weight, space, datetime): Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight:... | 038497eb9b2119769ecb85e023156eeff375d0e3 | <|skeleton|>
class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a standard dat... | the_stack_v2_python_sparse | Veh.py | MatheMatrix/realtimewatcher | train | 1 |
b75166d9eb907de085925242fdeab40c0b0a4a8a | [
"super().__init__()\nself.feat_channels = feat_channels\nself.gate_channels = gate_channels\nself.int_channels = int_channels\nself.gate_conv = nn.Conv2d(gate_channels, int_channels, kernel_size=1, bias=False)\nself.gate_bn = nn.BatchNorm2d(int_channels)\nself.feat_conv = nn.Conv2d(feat_channels, int_channels, kern... | <|body_start_0|>
super().__init__()
self.feat_channels = feat_channels
self.gate_channels = gate_channels
self.int_channels = int_channels
self.gate_conv = nn.Conv2d(gate_channels, int_channels, kernel_size=1, bias=False)
self.gate_bn = nn.BatchNorm2d(int_channels)
... | Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf | AttentionGate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttentionGate:
"""Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf"""
def __init__(self, gate_channels, feat_channels, int_channels):
"""Paramete... | stack_v2_sparse_classes_36k_train_008521 | 9,610 | no_license | [
{
"docstring": "Parameters ---------- gate_channels : int No. of feature-maps in gate vector. feat_channels : int No. of feature-maps in lower-level feature vector (e.g. skip connection). int_channels : int No. of intermediate channels for the attention module.",
"name": "__init__",
"signature": "def __... | 2 | stack_v2_sparse_classes_30k_train_019000 | Implement the Python class `AttentionGate` described below.
Class description:
Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf
Method signatures and docstrings:
- def __init__(se... | Implement the Python class `AttentionGate` described below.
Class description:
Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf
Method signatures and docstrings:
- def __init__(se... | 6fe259cd15ca31b4a238f700d3993b48e44a73fe | <|skeleton|>
class AttentionGate:
"""Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf"""
def __init__(self, gate_channels, feat_channels, int_channels):
"""Paramete... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttentionGate:
"""Attention gate for (skip) connections. Produces the attention coefficient :math:`alpha`. See "Attention U-Net:Learning Where to Look for the Pancreas" https://arxiv.org/pdf/1804.03999.pdf"""
def __init__(self, gate_channels, feat_channels, int_channels):
"""Parameters ----------... | the_stack_v2_python_sparse | nets/unet.py | medical-projects/dlmi-project | train | 0 |
679c21bc3ef9abc4d2078782b050e4be1419fabe | [
"self.seq = []\nself.count = []\ni = 0\nwhile i < len(A):\n self.seq.append(A[i + 1])\n self.count.append(A[i])\n i += 2",
"while len(self.count) > 0 and self.count[0] < n:\n self.seq.pop(0)\n count = self.count.pop(0)\n n -= count\nif len(self.count) == 0:\n return -1\nif self.count[0] == n:... | <|body_start_0|>
self.seq = []
self.count = []
i = 0
while i < len(A):
self.seq.append(A[i + 1])
self.count.append(A[i])
i += 2
<|end_body_0|>
<|body_start_1|>
while len(self.count) > 0 and self.count[0] < n:
self.seq.pop(0)
... | RLEIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.seq = []
self.count = []
i = 0
while i < len(A):
... | stack_v2_sparse_classes_36k_train_008522 | 3,178 | no_license | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | null | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | 7a459e9742958e63be8886874904e5ab2489411a | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.seq = []
self.count = []
i = 0
while i < len(A):
self.seq.append(A[i + 1])
self.count.append(A[i])
i += 2
def next(self, n):
""":type n: int :rtype: int"""... | the_stack_v2_python_sparse | Medium/900.py | Hellofafar/Leetcode | train | 6 | |
403be96503a385caaa78bd3a4ca276ca7332e01d | [
"self.name = kwargs.get('name')\nself.active = kwargs.get('active', True)\nself.created_by = kwargs.get('created_by')\nself.updated_by = kwargs.get('updated_by')",
"db.session.add(self)\nif commit is True:\n db.session.commit()",
"self.permissions.append(permission)\ndb.session.add(self)\nif commit is True:\... | <|body_start_0|>
self.name = kwargs.get('name')
self.active = kwargs.get('active', True)
self.created_by = kwargs.get('created_by')
self.updated_by = kwargs.get('updated_by')
<|end_body_0|>
<|body_start_1|>
db.session.add(self)
if commit is True:
db.session.c... | Description for role model | Role | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Role:
"""Description for role model"""
def __init__(self, **kwargs):
"""Initialization for role model"""
<|body_0|>
def save(self, commit=True):
"""Save data for role model"""
<|body_1|>
def save_role_permission(self, permission, commit=True):
... | stack_v2_sparse_classes_36k_train_008523 | 4,260 | no_license | [
{
"docstring": "Initialization for role model",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Save data for role model",
"name": "save",
"signature": "def save(self, commit=True)"
},
{
"docstring": "Relationship between role and permission",
... | 5 | stack_v2_sparse_classes_30k_train_008131 | Implement the Python class `Role` described below.
Class description:
Description for role model
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialization for role model
- def save(self, commit=True): Save data for role model
- def save_role_permission(self, permission, commit=True): Relationsh... | Implement the Python class `Role` described below.
Class description:
Description for role model
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialization for role model
- def save(self, commit=True): Save data for role model
- def save_role_permission(self, permission, commit=True): Relationsh... | 4dc5f5e816e3c461b8a60c5f61c7eafc08050579 | <|skeleton|>
class Role:
"""Description for role model"""
def __init__(self, **kwargs):
"""Initialization for role model"""
<|body_0|>
def save(self, commit=True):
"""Save data for role model"""
<|body_1|>
def save_role_permission(self, permission, commit=True):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Role:
"""Description for role model"""
def __init__(self, **kwargs):
"""Initialization for role model"""
self.name = kwargs.get('name')
self.active = kwargs.get('active', True)
self.created_by = kwargs.get('created_by')
self.updated_by = kwargs.get('updated_by')
... | the_stack_v2_python_sparse | app/models/role.py | ekramulmostafa/ms-auth | train | 0 |
0659a6fb0933cb63584222011d3e7ee28f055f2f | [
"self._GC_TAG = 'GC'\nself._WORKFLOW_TAG = 'WORKFLOW'\nif not ctx or not hasattr(ctx, self._GC_TAG):\n self.ctx = DataContext(None, self._GC_TAG)\n self.ctx.update_context(None, self._WORKFLOW_TAG)\nself.wf_context = getattr(self.ctx, self._WORKFLOW_TAG)\nself.gc_context = getattr(self.ctx, self._GC_TAG)",
... | <|body_start_0|>
self._GC_TAG = 'GC'
self._WORKFLOW_TAG = 'WORKFLOW'
if not ctx or not hasattr(ctx, self._GC_TAG):
self.ctx = DataContext(None, self._GC_TAG)
self.ctx.update_context(None, self._WORKFLOW_TAG)
self.wf_context = getattr(self.ctx, self._WORKFLOW_TAG)
... | In this class we are defining all procedures that can be commonly used for all services | BaseWorkflowRunSaltStateNVerify | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseWorkflowRunSaltStateNVerify:
"""In this class we are defining all procedures that can be commonly used for all services"""
def __init__(self, ctx=None):
"""Step 1: Create variables for both global and local yaml files to store data Step 2: Passes the variables names to DataContex... | stack_v2_sparse_classes_36k_train_008524 | 2,236 | no_license | [
{
"docstring": "Step 1: Create variables for both global and local yaml files to store data Step 2: Passes the variables names to DataContext process to assign values Args: :param ctx:",
"name": "__init__",
"signature": "def __init__(self, ctx=None)"
},
{
"docstring": "Description: At the end of... | 3 | null | Implement the Python class `BaseWorkflowRunSaltStateNVerify` described below.
Class description:
In this class we are defining all procedures that can be commonly used for all services
Method signatures and docstrings:
- def __init__(self, ctx=None): Step 1: Create variables for both global and local yaml files to st... | Implement the Python class `BaseWorkflowRunSaltStateNVerify` described below.
Class description:
In this class we are defining all procedures that can be commonly used for all services
Method signatures and docstrings:
- def __init__(self, ctx=None): Step 1: Create variables for both global and local yaml files to st... | 93dd6d14ae4b0856aa7c6f059904cc1f13800e5f | <|skeleton|>
class BaseWorkflowRunSaltStateNVerify:
"""In this class we are defining all procedures that can be commonly used for all services"""
def __init__(self, ctx=None):
"""Step 1: Create variables for both global and local yaml files to store data Step 2: Passes the variables names to DataContex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseWorkflowRunSaltStateNVerify:
"""In this class we are defining all procedures that can be commonly used for all services"""
def __init__(self, ctx=None):
"""Step 1: Create variables for both global and local yaml files to store data Step 2: Passes the variables names to DataContext process to ... | the_stack_v2_python_sparse | automation_framework/workflow/baseworkflow_run_salt_state_n_verify.py | vijaymaddukuri/python_repo | train | 0 |
18f251e5f82ae248088262ae8e08940622db4918 | [
"self.spi = spi\nself.cs_pin = cs_pin\nself.buf4 = bytearray(4)",
"try:\n retry = 0\n while True:\n retry += 1\n self.cs_pin.value(0)\n try:\n self.spi.readinto(self.buf4)\n except:\n pass\n self.cs_pin.value(1)\n val = self.buf4[0] << 8 | self... | <|body_start_0|>
self.spi = spi
self.cs_pin = cs_pin
self.buf4 = bytearray(4)
<|end_body_0|>
<|body_start_1|>
try:
retry = 0
while True:
retry += 1
self.cs_pin.value(0)
try:
self.spi.readinto(sel... | Read the data from MAX31855 thermocouple amplifier | MAX31855 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MAX31855:
"""Read the data from MAX31855 thermocouple amplifier"""
def __init__(self, spi, cs_pin):
"""constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: output pin for SPI transaction. Must be initialized HIGH. :... | stack_v2_sparse_classes_36k_train_008525 | 2,358 | no_license | [
{
"docstring": "constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: output pin for SPI transaction. Must be initialized HIGH. :param mclk freq: freq of the source clock (eg: 25000000 for 25 Mhz).",
"name": "__init__",
"signature": "de... | 2 | null | Implement the Python class `MAX31855` described below.
Class description:
Read the data from MAX31855 thermocouple amplifier
Method signatures and docstrings:
- def __init__(self, spi, cs_pin): constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: ou... | Implement the Python class `MAX31855` described below.
Class description:
Read the data from MAX31855 thermocouple amplifier
Method signatures and docstrings:
- def __init__(self, spi, cs_pin): constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: ou... | 75184da49e8578315a26bc42d9c3816ae5d5afe8 | <|skeleton|>
class MAX31855:
"""Read the data from MAX31855 thermocouple amplifier"""
def __init__(self, spi, cs_pin):
"""constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: output pin for SPI transaction. Must be initialized HIGH. :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MAX31855:
"""Read the data from MAX31855 thermocouple amplifier"""
def __init__(self, spi, cs_pin):
"""constructor. :param spi: must be initialized (in SPI in mode0 -> polarity=0, phase=0) and baudrate=5000000 :param cs_pin: output pin for SPI transaction. Must be initialized HIGH. :param mclk fr... | the_stack_v2_python_sparse | max31855/lib/max31855.py | mchobby/esp8266-upy | train | 47 |
20e621f8f2aff42e89d3868eb5afcdaa5f840ebd | [
"if not email:\n raise ValueError('Users must have an email address')\nuser = self.model(email=self.normalize_email(email), name=name, avatar=kwargs.get('avatar'))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(email, password=password, name=name)\nuser.is_admin... | <|body_start_0|>
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=self.normalize_email(email), name=name, avatar=kwargs.get('avatar'))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_st... | 这里是管网处复制修改的 | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
"""这里是管网处复制修改的"""
def create_user(self, email, name, password=None, **kwargs):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, name, password):
"""Creates and saves a sup... | stack_v2_sparse_classes_36k_train_008526 | 5,562 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, email, name, password=None, **kwargs)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
... | 2 | stack_v2_sparse_classes_30k_train_003218 | Implement the Python class `MyUserManager` described below.
Class description:
这里是管网处复制修改的
Method signatures and docstrings:
- def create_user(self, email, name, password=None, **kwargs): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, name, password): Cr... | Implement the Python class `MyUserManager` described below.
Class description:
这里是管网处复制修改的
Method signatures and docstrings:
- def create_user(self, email, name, password=None, **kwargs): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, email, name, password): Cr... | 8017a63631b994e67d3aaa342a7ea6e60fe6fe9c | <|skeleton|>
class MyUserManager:
"""这里是管网处复制修改的"""
def create_user(self, email, name, password=None, **kwargs):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, name, password):
"""Creates and saves a sup... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
"""这里是管网处复制修改的"""
def create_user(self, email, name, password=None, **kwargs):
"""Creates and saves a User with the given email, date of birth and password."""
if not email:
raise ValueError('Users must have an email address')
user = self.model(email=sel... | the_stack_v2_python_sparse | CMDB/web/models.py | Mrs-wang1/python-test | train | 0 |
58d8c2271fb423f8309143ccf3d44b10f145e02b | [
"print(data)\nmin_date = timezone.now() + timedelta(minutes=10)\nif data <= min_date:\n raise serializers.ValidationError('Departure time must be at least pass the next 20 minutes window')\nreturn data",
"if self.context['request'].user != data['offered_by']:\n raise serializer.ValidationError('Ride offered... | <|body_start_0|>
print(data)
min_date = timezone.now() + timedelta(minutes=10)
if data <= min_date:
raise serializers.ValidationError('Departure time must be at least pass the next 20 minutes window')
return data
<|end_body_0|>
<|body_start_1|>
if self.context['reque... | Create ride serializer | CreateRideSerialier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateRideSerialier:
"""Create ride serializer"""
def validate_departure_date(self, data):
"""Verify date is not in the past"""
<|body_0|>
def validate(self, data):
"""Validate Verify that the person who offers the ride is member and also the same user making the... | stack_v2_sparse_classes_36k_train_008527 | 7,953 | no_license | [
{
"docstring": "Verify date is not in the past",
"name": "validate_departure_date",
"signature": "def validate_departure_date(self, data)"
},
{
"docstring": "Validate Verify that the person who offers the ride is member and also the same user making the request",
"name": "validate",
"sig... | 3 | stack_v2_sparse_classes_30k_train_008124 | Implement the Python class `CreateRideSerialier` described below.
Class description:
Create ride serializer
Method signatures and docstrings:
- def validate_departure_date(self, data): Verify date is not in the past
- def validate(self, data): Validate Verify that the person who offers the ride is member and also the... | Implement the Python class `CreateRideSerialier` described below.
Class description:
Create ride serializer
Method signatures and docstrings:
- def validate_departure_date(self, data): Verify date is not in the past
- def validate(self, data): Validate Verify that the person who offers the ride is member and also the... | 0cede53169041667bd40bbce3c4774af84ffc2fa | <|skeleton|>
class CreateRideSerialier:
"""Create ride serializer"""
def validate_departure_date(self, data):
"""Verify date is not in the past"""
<|body_0|>
def validate(self, data):
"""Validate Verify that the person who offers the ride is member and also the same user making the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateRideSerialier:
"""Create ride serializer"""
def validate_departure_date(self, data):
"""Verify date is not in the past"""
print(data)
min_date = timezone.now() + timedelta(minutes=10)
if data <= min_date:
raise serializers.ValidationError('Departure time ... | the_stack_v2_python_sparse | rides/serializers/rides.py | KrystellCR/DjangoRF | train | 0 |
984d4a8105560eb8aef5cd6f922c3c2ac02e3dea | [
"self.funcs = funcs\nself.argmax = argmax\nself.maxval = maxval\nself.argmin = argmin\nself.minval = minval\nexperiment_caller = self._get_experiment_caller()\nsuper(MultiFunctionCaller, self).__init__(experiment_caller, domain, descr, *args, noise_type=noise_type, noise_scale=noise_scale, fidel_space=fidel_space, ... | <|body_start_0|>
self.funcs = funcs
self.argmax = argmax
self.maxval = maxval
self.argmin = argmin
self.minval = minval
experiment_caller = self._get_experiment_caller()
super(MultiFunctionCaller, self).__init__(experiment_caller, domain, descr, *args, noise_type=... | An Experiment Caller specifically for evaluating a collection of functions. | MultiFunctionCaller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiFunctionCaller:
"""An Experiment Caller specifically for evaluating a collection of functions."""
def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', noise_scale=None, fidel_space=None, fidel_cost_func=None, fidel_to_opt... | stack_v2_sparse_classes_36k_train_008528 | 28,947 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', noise_scale=None, fidel_space=None, fidel_cost_func=None, fidel_to_opt=None, *args, **kwargs)"
},
{
"docstring":... | 4 | stack_v2_sparse_classes_30k_train_021224 | Implement the Python class `MultiFunctionCaller` described below.
Class description:
An Experiment Caller specifically for evaluating a collection of functions.
Method signatures and docstrings:
- def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', no... | Implement the Python class `MultiFunctionCaller` described below.
Class description:
An Experiment Caller specifically for evaluating a collection of functions.
Method signatures and docstrings:
- def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', no... | 3eef7d30bcc2e56f2221a624bd8ec7f933f81e40 | <|skeleton|>
class MultiFunctionCaller:
"""An Experiment Caller specifically for evaluating a collection of functions."""
def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', noise_scale=None, fidel_space=None, fidel_cost_func=None, fidel_to_opt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiFunctionCaller:
"""An Experiment Caller specifically for evaluating a collection of functions."""
def __init__(self, funcs, domain, descr='', argmax=None, maxval=None, argmin=None, minval=None, noise_type='no_noise', noise_scale=None, fidel_space=None, fidel_cost_func=None, fidel_to_opt=None, *args,... | the_stack_v2_python_sparse | dragonfly/exd/experiment_caller.py | dragonfly/dragonfly | train | 868 |
e72364f2b5e48f2fbe13ad14984cce83583f5013 | [
"\"\"\" use a `default dictionary` to map each node to its child nodes.\n https://docs.python.org/3/library/collections.html#collections.defaultdict\n\n defaulting to a `list` makes it easier to iterate over\n child nodes in later stages of the algorithm\n \"\"\"\nroutes = co... | <|body_start_0|>
""" use a `default dictionary` to map each node to its child nodes.
https://docs.python.org/3/library/collections.html#collections.defaultdict
defaulting to a `list` makes it easier to iterate over
child nodes in later stages of the a... | BinaryTree | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTree:
def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int:
"""below solution assumes a specific order of the nodes --> [parent, child]. it fails when a node is represented as [child, parent]."""
<|body_0|>
def minTimeGraph(self, n: int, e... | stack_v2_sparse_classes_36k_train_008529 | 3,051 | permissive | [
{
"docstring": "below solution assumes a specific order of the nodes --> [parent, child]. it fails when a node is represented as [child, parent].",
"name": "minTimeTree",
"signature": "def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int"
},
{
"docstring": "works fo... | 2 | null | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int: below solution assumes a specific order of the nodes --> [parent, child]. it fails when a ... | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int: below solution assumes a specific order of the nodes --> [parent, child]. it fails when a ... | 14356c6adb1946417482eaaf6f42dde4b8351d2f | <|skeleton|>
class BinaryTree:
def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int:
"""below solution assumes a specific order of the nodes --> [parent, child]. it fails when a node is represented as [child, parent]."""
<|body_0|>
def minTimeGraph(self, n: int, e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTree:
def minTimeTree(self, n: int, edges: List[List[int]], hasApple: List[bool]) -> int:
"""below solution assumes a specific order of the nodes --> [parent, child]. it fails when a node is represented as [child, parent]."""
""" use a `default dictionary` to map each node to its child n... | the_stack_v2_python_sparse | binary_tree/m_min_time_apple.py | dhrubach/python-code-recipes | train | 1 | |
84b9a5c876ad3590cd4cb6e91908d2c2655861d5 | [
"self.printTag = 'MOOSE_PARSER'\nself.inputFile = inputFile\nself.roots = self.loadInput(inputFile)",
"if not os.path.exists(inputFile):\n raise IOError('MOOSE input file not found: \"{}\"'.format(inputFile))\nwith open(inputFile, 'r') as f:\n roots = MooseInputParser.getpotToInputTree(f)\nreturn roots",
... | <|body_start_0|>
self.printTag = 'MOOSE_PARSER'
self.inputFile = inputFile
self.roots = self.loadInput(inputFile)
<|end_body_0|>
<|body_start_1|>
if not os.path.exists(inputFile):
raise IOError('MOOSE input file not found: "{}"'.format(inputFile))
with open(inputFile... | Import the MOOSE input as xml tree, provide methods to add/change entries and print it back | MOOSEparser | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MOOSEparser:
"""Import the MOOSE input as xml tree, provide methods to add/change entries and print it back"""
def __init__(self, inputFile):
"""Constructor @ In, inputFile, string, input file name @ Out, None"""
<|body_0|>
def loadInput(self, inputFile):
"""Read... | stack_v2_sparse_classes_36k_train_008530 | 5,231 | permissive | [
{
"docstring": "Constructor @ In, inputFile, string, input file name @ Out, None",
"name": "__init__",
"signature": "def __init__(self, inputFile)"
},
{
"docstring": "Reads the input to class members. @ In, inputFile, string, name of input file @ Out, roots, list, root nodes of input file as uti... | 6 | null | Implement the Python class `MOOSEparser` described below.
Class description:
Import the MOOSE input as xml tree, provide methods to add/change entries and print it back
Method signatures and docstrings:
- def __init__(self, inputFile): Constructor @ In, inputFile, string, input file name @ Out, None
- def loadInput(s... | Implement the Python class `MOOSEparser` described below.
Class description:
Import the MOOSE input as xml tree, provide methods to add/change entries and print it back
Method signatures and docstrings:
- def __init__(self, inputFile): Constructor @ In, inputFile, string, input file name @ Out, None
- def loadInput(s... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class MOOSEparser:
"""Import the MOOSE input as xml tree, provide methods to add/change entries and print it back"""
def __init__(self, inputFile):
"""Constructor @ In, inputFile, string, input file name @ Out, None"""
<|body_0|>
def loadInput(self, inputFile):
"""Read... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MOOSEparser:
"""Import the MOOSE input as xml tree, provide methods to add/change entries and print it back"""
def __init__(self, inputFile):
"""Constructor @ In, inputFile, string, input file name @ Out, None"""
self.printTag = 'MOOSE_PARSER'
self.inputFile = inputFile
se... | the_stack_v2_python_sparse | ravenframework/CodeInterfaceClasses/MooseBasedApp/MOOSEparser.py | idaholab/raven | train | 201 |
75b58288cdf1656448282d23ab7466480cd104a9 | [
"super().__init__()\nself.x = x\nself.y = y\nself.width = width\nself.height = height\nassert self.x >= 0\nassert self.y >= 0\nassert self.width > 0\nassert self.height > 0",
"if len(inputs.shape) >= 4:\n return inputs[:, self.y:self.y + self.height, self.x:self.x + self.width]\nelse:\n return inputs[self.y... | <|body_start_0|>
super().__init__()
self.x = x
self.y = y
self.width = width
self.height = height
assert self.x >= 0
assert self.y >= 0
assert self.width > 0
assert self.height > 0
<|end_body_0|>
<|body_start_1|>
if len(inputs.shape) >= 4:... | Crops one or more images to a new size without touching the color channel. | ImageCrop | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageCrop:
"""Crops one or more images to a new size without touching the color channel."""
def __init__(self, x=0, y=0, width=0, height=0):
"""Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width of resulting image. height (int): Height of resulting ima... | stack_v2_sparse_classes_36k_train_008531 | 1,949 | permissive | [
{
"docstring": "Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width of resulting image. height (int): Height of resulting image.",
"name": "__init__",
"signature": "def __init__(self, x=0, y=0, width=0, height=0)"
},
{
"docstring": "Images come in with either a bat... | 2 | stack_v2_sparse_classes_30k_train_009246 | Implement the Python class `ImageCrop` described below.
Class description:
Crops one or more images to a new size without touching the color channel.
Method signatures and docstrings:
- def __init__(self, x=0, y=0, width=0, height=0): Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width ... | Implement the Python class `ImageCrop` described below.
Class description:
Crops one or more images to a new size without touching the color channel.
Method signatures and docstrings:
- def __init__(self, x=0, y=0, width=0, height=0): Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width ... | 8abfb18538340d50146c9c44f5ecb8a1e7d89ac3 | <|skeleton|>
class ImageCrop:
"""Crops one or more images to a new size without touching the color channel."""
def __init__(self, x=0, y=0, width=0, height=0):
"""Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width of resulting image. height (int): Height of resulting ima... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageCrop:
"""Crops one or more images to a new size without touching the color channel."""
def __init__(self, x=0, y=0, width=0, height=0):
"""Args: x (int): Start x coordinate. y (int): Start y coordinate. width (int): Width of resulting image. height (int): Height of resulting image."""
... | the_stack_v2_python_sparse | surreal/components/preprocessors/image_crop.py | ducandu/surreal | train | 6 |
7ff8e097472b962a5b4b417aadf93881b30ef9eb | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | DropboxStorageServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DropboxStorageServiceServicer:
"""Missing associated documentation comment in .proto file."""
def listDropboxStorage(self, request, context):
"""Storage"""
<|body_0|>
def getDropboxStorage(self, request, context):
"""Missing associated documentation comment in .p... | stack_v2_sparse_classes_36k_train_008532 | 10,219 | permissive | [
{
"docstring": "Storage",
"name": "listDropboxStorage",
"signature": "def listDropboxStorage(self, request, context)"
},
{
"docstring": "Missing associated documentation comment in .proto file.",
"name": "getDropboxStorage",
"signature": "def getDropboxStorage(self, request, context)"
... | 5 | stack_v2_sparse_classes_30k_train_001588 | Implement the Python class `DropboxStorageServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def listDropboxStorage(self, request, context): Storage
- def getDropboxStorage(self, request, context): Missing associated docume... | Implement the Python class `DropboxStorageServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def listDropboxStorage(self, request, context): Storage
- def getDropboxStorage(self, request, context): Missing associated docume... | c69e14b409add099d151434b9add711e41f41b20 | <|skeleton|>
class DropboxStorageServiceServicer:
"""Missing associated documentation comment in .proto file."""
def listDropboxStorage(self, request, context):
"""Storage"""
<|body_0|>
def getDropboxStorage(self, request, context):
"""Missing associated documentation comment in .p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DropboxStorageServiceServicer:
"""Missing associated documentation comment in .proto file."""
def listDropboxStorage(self, request, context):
"""Storage"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedEr... | the_stack_v2_python_sparse | python-sdk/src/airavata_mft_sdk/dropbox/DropboxStorageService_pb2_grpc.py | apache/airavata-mft | train | 23 |
18d146c8b8dbbf07705a148a40d56ea3cff14151 | [
"dic = {}\ntimes = len(nums) // 2\nprint('times:', times)\nfor index, item in enumerate(nums):\n if item in dic:\n dic[item] += 1\n if dic[item] > times:\n return item\n else:\n dic[item] = 1\nprint(dic)\nreturn max(dic, key=dic.get)",
"if not nums:\n return None\nif len(n... | <|body_start_0|>
dic = {}
times = len(nums) // 2
print('times:', times)
for index, item in enumerate(nums):
if item in dic:
dic[item] += 1
if dic[item] > times:
return item
else:
dic[item] = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def majorityElement2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dic = {}
times = len(nums) /... | stack_v2_sparse_classes_36k_train_008533 | 1,379 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "majorityElement",
"signature": "def majorityElement(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "majorityElement2",
"signature": "def majorityElement2(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): :type nums: List[int] :rtype: int
- def majorityElement2(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def majorityElement(self, nums): :type nums: List[int] :rtype: int
- def majorityElement2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def ma... | 6be4e77f659e80c853e58dceec88990c4065f9de | <|skeleton|>
class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def majorityElement2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def majorityElement(self, nums):
""":type nums: List[int] :rtype: int"""
dic = {}
times = len(nums) // 2
print('times:', times)
for index, item in enumerate(nums):
if item in dic:
dic[item] += 1
if dic[item] > times:... | the_stack_v2_python_sparse | 169_Majority_Element.py | Lobo2008/LeetCode | train | 0 | |
0cc31e4d001e8ca87d2950a65047dce6fef1ac7a | [
"label_map = LabelMap.create_label_map(app_path, train_pattern)\nresource_loader = ResourceLoader.create_resource_loader(app_path)\ntrain_query_list = resource_loader.get_flattened_label_set(label_set=train_pattern)\nif TuneLevel.ENTITY.value in tuning_level:\n label_map.entity2id = LabelMap._get_entity_mappings... | <|body_start_0|>
label_map = LabelMap.create_label_map(app_path, train_pattern)
resource_loader = ResourceLoader.create_resource_loader(app_path)
train_query_list = resource_loader.get_flattened_label_set(label_set=train_pattern)
if TuneLevel.ENTITY.value in tuning_level:
lab... | Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details. | DataBucketFactory | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBucketFactory:
"""Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details."""
def get_data_bucket_for_strategy_tuning(app_path: str, tuning_level: list, train_patter... | stack_v2_sparse_classes_36k_train_008534 | 20,702 | permissive | [
{
"docstring": "Creates a DataBucket to be used for strategy tuning. Args: app_path (str): Path to MindMeld application tuning_level (list): The hierarchy levels to tune (\"domain\", \"intent\" or \"entity\") train_pattern (str): Regex pattern to match train files. (\".*train.*.txt\") test_pattern (str): Regex ... | 2 | stack_v2_sparse_classes_30k_train_005173 | Implement the Python class `DataBucketFactory` described below.
Class description:
Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details.
Method signatures and docstrings:
- def get_data_bucket... | Implement the Python class `DataBucketFactory` described below.
Class description:
Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details.
Method signatures and docstrings:
- def get_data_bucket... | bd3547d5c1bd092dbd4a64a90528dfc2e2b3844a | <|skeleton|>
class DataBucketFactory:
"""Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details."""
def get_data_bucket_for_strategy_tuning(app_path: str, tuning_level: list, train_patter... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBucketFactory:
"""Class to generate the initial data for experimentation. (Seed Queries, Remaining Queries, and Test Queries). Handles initial sampling and data split based on configuation details."""
def get_data_bucket_for_strategy_tuning(app_path: str, tuning_level: list, train_pattern: str, test_... | the_stack_v2_python_sparse | mindmeld/active_learning/data_loading.py | cisco/mindmeld | train | 671 |
78972ff408306570ac5e4a6af7fa578c5d420361 | [
"batch_size = 100\npred_illum_rgb = np.random.rand(batch_size, 3)\ntrue_illum_rgb = np.random.rand(batch_size, 3)\nexpected_angle = 180.0 / math.pi * np.arccos(np.sum(_normalized(true_illum_rgb / pred_illum_rgb) * _normalized(np.ones(shape=(1, 3))), axis=1))\nself.assertAllClose(losses.reproduction_error(tf.constan... | <|body_start_0|>
batch_size = 100
pred_illum_rgb = np.random.rand(batch_size, 3)
true_illum_rgb = np.random.rand(batch_size, 3)
expected_angle = 180.0 / math.pi * np.arccos(np.sum(_normalized(true_illum_rgb / pred_illum_rgb) * _normalized(np.ones(shape=(1, 3))), axis=1))
self.ass... | Tests losses.reproduction_error. | ReproductionErrorTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReproductionErrorTest:
"""Tests losses.reproduction_error."""
def testAgainstRefImpl(self):
"""Tests against reference implementation."""
<|body_0|>
def testWhiteIlluminant(self):
"""Tests against white (neutral gray) illuminants."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k_train_008535 | 17,094 | permissive | [
{
"docstring": "Tests against reference implementation.",
"name": "testAgainstRefImpl",
"signature": "def testAgainstRefImpl(self)"
},
{
"docstring": "Tests against white (neutral gray) illuminants.",
"name": "testWhiteIlluminant",
"signature": "def testWhiteIlluminant(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_021067 | Implement the Python class `ReproductionErrorTest` described below.
Class description:
Tests losses.reproduction_error.
Method signatures and docstrings:
- def testAgainstRefImpl(self): Tests against reference implementation.
- def testWhiteIlluminant(self): Tests against white (neutral gray) illuminants.
- def testT... | Implement the Python class `ReproductionErrorTest` described below.
Class description:
Tests losses.reproduction_error.
Method signatures and docstrings:
- def testAgainstRefImpl(self): Tests against reference implementation.
- def testWhiteIlluminant(self): Tests against white (neutral gray) illuminants.
- def testT... | c52b225082327ea34bed80357dbff004fc9926ba | <|skeleton|>
class ReproductionErrorTest:
"""Tests losses.reproduction_error."""
def testAgainstRefImpl(self):
"""Tests against reference implementation."""
<|body_0|>
def testWhiteIlluminant(self):
"""Tests against white (neutral gray) illuminants."""
<|body_1|>
def t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReproductionErrorTest:
"""Tests losses.reproduction_error."""
def testAgainstRefImpl(self):
"""Tests against reference implementation."""
batch_size = 100
pred_illum_rgb = np.random.rand(batch_size, 3)
true_illum_rgb = np.random.rand(batch_size, 3)
expected_angle =... | the_stack_v2_python_sparse | python/losses_test.py | mahmoudnafifi/ffcc | train | 1 |
1ecba3b803f18e740eb13291702c6f5237f01ab5 | [
"super().__init__(name=name, verbose=verbose)\nassert 0 <= clip_fraction <= 1\nself.levels_path = levels_path\nself.mip = int(mip)\nself.clip_fraction = float(clip_fraction)\nself.minval = minval\nself.maxval = maxval",
"assert chunk.ndim == 3\nimage = np.transpose(chunk).astype(np.float32)\noffset = Vec(*chunk.g... | <|body_start_0|>
super().__init__(name=name, verbose=verbose)
assert 0 <= clip_fraction <= 1
self.levels_path = levels_path
self.mip = int(mip)
self.clip_fraction = float(clip_fraction)
self.minval = minval
self.maxval = maxval
<|end_body_0|>
<|body_start_1|>
... | Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735 | NormalizeSectionContrastOperator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalizeSectionContrastOperator:
"""Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735"""
def __init__(self, levels_path: str, ... | stack_v2_sparse_classes_36k_train_008536 | 4,858 | permissive | [
{
"docstring": "levels_path: (str) path of section histogram files. mip: (int) the mip level of section histogram. clip_fraction: (float) the fraction of intensity to be clamped. minval: (float)",
"name": "__init__",
"signature": "def __init__(self, levels_path: str, mip: int, clip_fraction: float, minv... | 4 | stack_v2_sparse_classes_30k_train_009567 | Implement the Python class `NormalizeSectionContrastOperator` described below.
Class description:
Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735
Metho... | Implement the Python class `NormalizeSectionContrastOperator` described below.
Class description:
Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735
Metho... | c7e78eb9798e88e398e6f56469a00ff26cff9232 | <|skeleton|>
class NormalizeSectionContrastOperator:
"""Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735"""
def __init__(self, levels_path: str, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NormalizeSectionContrastOperator:
"""Contrast Correction based on LuminanceLevelsTask output. Note that this operator was modified from Will's ContrastNormalizationTask in igneous: https://github.com/seung-lab/igneous/blob/master/igneous/tasks.py#L735"""
def __init__(self, levels_path: str, mip: int, cli... | the_stack_v2_python_sparse | chunkflow/flow/normalize_section_contrast.py | aixioma/chunkflow | train | 0 |
ccd76485925a4b693b312575c44683f60bcafc01 | [
"future_seq = self.image_group_future_seq(image_seq, **kwargs)\nindex_group_seq = self.future_result_seq(future_seq)\nfor _, group in sorted(index_group_seq):\n for image in group:\n yield image",
"future_list = list(future_seq)\nfuture_seq = as_completed(future_list)\nfor future in future_seq:\n yie... | <|body_start_0|>
future_seq = self.image_group_future_seq(image_seq, **kwargs)
index_group_seq = self.future_result_seq(future_seq)
for _, group in sorted(index_group_seq):
for image in group:
yield image
<|end_body_0|>
<|body_start_1|>
future_list = list(fut... | It helps only with long videos WARNING: remember that sending data from process to another has its own costs! | ParallelExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParallelExtractor:
"""It helps only with long videos WARNING: remember that sending data from process to another has its own costs!"""
def transform_frame_images(self, image_seq, **kwargs):
""":param image_seq: :param kwargs: :return:"""
<|body_0|>
def future_result_seq(... | stack_v2_sparse_classes_36k_train_008537 | 3,728 | permissive | [
{
"docstring": ":param image_seq: :param kwargs: :return:",
"name": "transform_frame_images",
"signature": "def transform_frame_images(self, image_seq, **kwargs)"
},
{
"docstring": ":param future_seq: :return:",
"name": "future_result_seq",
"signature": "def future_result_seq(future_seq)... | 5 | stack_v2_sparse_classes_30k_train_001188 | Implement the Python class `ParallelExtractor` described below.
Class description:
It helps only with long videos WARNING: remember that sending data from process to another has its own costs!
Method signatures and docstrings:
- def transform_frame_images(self, image_seq, **kwargs): :param image_seq: :param kwargs: :... | Implement the Python class `ParallelExtractor` described below.
Class description:
It helps only with long videos WARNING: remember that sending data from process to another has its own costs!
Method signatures and docstrings:
- def transform_frame_images(self, image_seq, **kwargs): :param image_seq: :param kwargs: :... | 617ff45c9c3c96bbd9a975aef15f1b2697282b9c | <|skeleton|>
class ParallelExtractor:
"""It helps only with long videos WARNING: remember that sending data from process to another has its own costs!"""
def transform_frame_images(self, image_seq, **kwargs):
""":param image_seq: :param kwargs: :return:"""
<|body_0|>
def future_result_seq(... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParallelExtractor:
"""It helps only with long videos WARNING: remember that sending data from process to another has its own costs!"""
def transform_frame_images(self, image_seq, **kwargs):
""":param image_seq: :param kwargs: :return:"""
future_seq = self.image_group_future_seq(image_seq,... | the_stack_v2_python_sparse | shot_detector/features/extractors/parallel_extractor.py | w495/python-video-shot-detector | train | 20 |
20fa88941344e2835fa8e175a61cf16ba8c14d00 | [
"self.porosity = 0.92\nself.k_matrix = 0.0058\nself.PPI = 10.0\nself.K = 2e-07\nself.Nu_D",
"self.Re_K = self.velocity * self.K ** 0.5 / self.nu\nself.f = 1.0 / self.Re_K + 0.55\nself.k = self.k_matrix\nself.deltaP = self.f * self.perimeter * self.node_length / self.flow_area * (0.5 * self.rho * self.velocity ** ... | <|body_start_0|>
self.porosity = 0.92
self.k_matrix = 0.0058
self.PPI = 10.0
self.K = 2e-07
self.Nu_D
<|end_body_0|>
<|body_start_1|>
self.Re_K = self.velocity * self.K ** 0.5 / self.nu
self.f = 1.0 / self.Re_K + 0.55
self.k = self.k_matrix
self.d... | Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init__ solve_enh | BejanPorous | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BejanPorous:
"""Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init__ solve_enh"""
def __init__(self)... | stack_v2_sparse_classes_36k_train_008538 | 15,856 | no_license | [
{
"docstring": "Initializes a bunch of constants.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Solves for convection parameters with enhancement.",
"name": "solve_enh",
"signature": "def solve_enh(self)"
}
] | 2 | null | Implement the Python class `BejanPorous` described below.
Class description:
Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init... | Implement the Python class `BejanPorous` described below.
Class description:
Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init... | d619b66b1f16557e06c94eee1c16d4ee2a9e896a | <|skeleton|>
class BejanPorous:
"""Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init__ solve_enh"""
def __init__(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BejanPorous:
"""Class for porous media according to the book of Bejan. Bejan, A. “Designed Porous Media: Maximal Heat Transfer Density at Decreasing Length Scales.” International Journal of Heat and Mass Transfer 47, no. 14 (2004): 3073–3083. Methods: __init__ solve_enh"""
def __init__(self):
"""... | the_stack_v2_python_sparse | Modules/enhancement.py | hfateh/TE_Model-1 | train | 0 |
473092687bcdd4c502a6e854288b87750ed91b34 | [
"self.intersection_meter = AverageMeter()\nself.union_meter = AverageMeter()\nself.target_meter = AverageMeter()\nself.accuracy = 0",
"intersection, union, target = iou_utils.intersectionAndUnion(pred, target, num_classes)\nself.intersection_meter.update(intersection)\nself.union_meter.update(union)\nself.target_... | <|body_start_0|>
self.intersection_meter = AverageMeter()
self.union_meter = AverageMeter()
self.target_meter = AverageMeter()
self.accuracy = 0
<|end_body_0|>
<|body_start_1|>
intersection, union, target = iou_utils.intersectionAndUnion(pred, target, num_classes)
self.i... | An AverageMeter designed specifically for evaluating segmentation results. | SegmentationAverageMeter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentationAverageMeter:
"""An AverageMeter designed specifically for evaluating segmentation results."""
def __init__(self) -> None:
"""Initialize object."""
<|body_0|>
def update_metrics_cpu(self, pred: np.ndarray, target: np.ndarray, num_classes: int) -> None:
... | stack_v2_sparse_classes_36k_train_008539 | 3,630 | permissive | [
{
"docstring": "Initialize object.",
"name": "__init__",
"signature": "def __init__(self) -> None"
},
{
"docstring": "Args: pred target classes",
"name": "update_metrics_cpu",
"signature": "def update_metrics_cpu(self, pred: np.ndarray, target: np.ndarray, num_classes: int) -> None"
},... | 4 | stack_v2_sparse_classes_30k_train_005209 | Implement the Python class `SegmentationAverageMeter` described below.
Class description:
An AverageMeter designed specifically for evaluating segmentation results.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize object.
- def update_metrics_cpu(self, pred: np.ndarray, target: np.ndarray, n... | Implement the Python class `SegmentationAverageMeter` described below.
Class description:
An AverageMeter designed specifically for evaluating segmentation results.
Method signatures and docstrings:
- def __init__(self) -> None: Initialize object.
- def update_metrics_cpu(self, pred: np.ndarray, target: np.ndarray, n... | e078ae6ee33ca34dc07f3900b9ded5295c29d9c8 | <|skeleton|>
class SegmentationAverageMeter:
"""An AverageMeter designed specifically for evaluating segmentation results."""
def __init__(self) -> None:
"""Initialize object."""
<|body_0|>
def update_metrics_cpu(self, pred: np.ndarray, target: np.ndarray, num_classes: int) -> None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SegmentationAverageMeter:
"""An AverageMeter designed specifically for evaluating segmentation results."""
def __init__(self) -> None:
"""Initialize object."""
self.intersection_meter = AverageMeter()
self.union_meter = AverageMeter()
self.target_meter = AverageMeter()
... | the_stack_v2_python_sparse | mseg_semantic/utils/avg_meter.py | mseg-dataset/mseg-semantic | train | 461 |
23552b6bd9a0076dff9fb1bde82366f6f0bf6595 | [
"while get_current_window_id() == 10101:\n xbmc.sleep(100)\nsuper(progress_dialog, self).__init__()",
"if kodi_version_major() < 19:\n lines = message.split('\\n', 2)\n line1, line2, line3 = lines + [None] * (3 - len(lines))\n return super(progress_dialog, self).create(heading, line1=line1, line2=line... | <|body_start_0|>
while get_current_window_id() == 10101:
xbmc.sleep(100)
super(progress_dialog, self).__init__()
<|end_body_0|>
<|body_start_1|>
if kodi_version_major() < 19:
lines = message.split('\n', 2)
line1, line2, line3 = lines + [None] * (3 - len(lines... | Show Kodi's Progress dialog | progress_dialog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class progress_dialog:
"""Show Kodi's Progress dialog"""
def __init__(self):
"""Initialize a new progress dialog"""
<|body_0|>
def create(self, heading, message=''):
"""Create and show a progress dialog"""
<|body_1|>
def update(self, percent, message=''):
... | stack_v2_sparse_classes_36k_train_008540 | 14,153 | permissive | [
{
"docstring": "Initialize a new progress dialog",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create and show a progress dialog",
"name": "create",
"signature": "def create(self, heading, message='')"
},
{
"docstring": "Update the progress dialog",
... | 3 | stack_v2_sparse_classes_30k_train_012365 | Implement the Python class `progress_dialog` described below.
Class description:
Show Kodi's Progress dialog
Method signatures and docstrings:
- def __init__(self): Initialize a new progress dialog
- def create(self, heading, message=''): Create and show a progress dialog
- def update(self, percent, message=''): Upda... | Implement the Python class `progress_dialog` described below.
Class description:
Show Kodi's Progress dialog
Method signatures and docstrings:
- def __init__(self): Initialize a new progress dialog
- def create(self, heading, message=''): Create and show a progress dialog
- def update(self, percent, message=''): Upda... | 9b7cab3656c2497c812ab101a56ed661dd8cf4a7 | <|skeleton|>
class progress_dialog:
"""Show Kodi's Progress dialog"""
def __init__(self):
"""Initialize a new progress dialog"""
<|body_0|>
def create(self, heading, message=''):
"""Create and show a progress dialog"""
<|body_1|>
def update(self, percent, message=''):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class progress_dialog:
"""Show Kodi's Progress dialog"""
def __init__(self):
"""Initialize a new progress dialog"""
while get_current_window_id() == 10101:
xbmc.sleep(100)
super(progress_dialog, self).__init__()
def create(self, heading, message=''):
"""Create a... | the_stack_v2_python_sparse | repo/script.module.inputstreamhelper/lib/inputstreamhelper/kodiutils.py | irmu/arda | train | 7 |
c7746f5fdc97129331ce8be711368b5a9bff62c1 | [
"env = EpisodeInfo(gym.make('CartPole-v1'))\n\ndef actor(ob):\n ac = torch.from_numpy(np.array(env.action_space.sample()))[None]\n return namedtuple('test', ['action', 'state_out'])(action=ac, state_out=None)\nstats = rl_evaluate(env, actor, 10, outfile='./out.pt', save_info=True)\nassert len(stats['episode_l... | <|body_start_0|>
env = EpisodeInfo(gym.make('CartPole-v1'))
def actor(ob):
ac = torch.from_numpy(np.array(env.action_space.sample()))[None]
return namedtuple('test', ['action', 'state_out'])(action=ac, state_out=None)
stats = rl_evaluate(env, actor, 10, outfile='./out.pt... | Test. | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
"""Test."""
def test_eval(self):
"""Test."""
<|body_0|>
def test_record(self):
"""Test record."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
env = EpisodeInfo(gym.make('CartPole-v1'))
def actor(ob):
ac = torch.from_n... | stack_v2_sparse_classes_36k_train_008541 | 7,046 | no_license | [
{
"docstring": "Test.",
"name": "test_eval",
"signature": "def test_eval(self)"
},
{
"docstring": "Test record.",
"name": "test_record",
"signature": "def test_record(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015911 | Implement the Python class `Test` described below.
Class description:
Test.
Method signatures and docstrings:
- def test_eval(self): Test.
- def test_record(self): Test record. | Implement the Python class `Test` described below.
Class description:
Test.
Method signatures and docstrings:
- def test_eval(self): Test.
- def test_record(self): Test record.
<|skeleton|>
class Test:
"""Test."""
def test_eval(self):
"""Test."""
<|body_0|>
def test_record(self):
... | e71c4b12955b01bfb907aa31c91ded6bcd8aaec8 | <|skeleton|>
class Test:
"""Test."""
def test_eval(self):
"""Test."""
<|body_0|>
def test_record(self):
"""Test record."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test:
"""Test."""
def test_eval(self):
"""Test."""
env = EpisodeInfo(gym.make('CartPole-v1'))
def actor(ob):
ac = torch.from_numpy(np.array(env.action_space.sample()))[None]
return namedtuple('test', ['action', 'state_out'])(action=ac, state_out=None)
... | the_stack_v2_python_sparse | dl/rl/util/eval.py | cbschaff/dl | train | 1 |
2984dbcad5c98d03efd32a90951b1c7fa4d7768f | [
"if not Arr:\n return None\nhead = ListNode(Arr[0])\np = head\nfor i in range(1, len(Arr)):\n p.next = ListNode(Arr[i])\n p = p.next\nreturn head",
"if not head:\n return None\nresult = []\np = head\nwhile p:\n result.append(p.val)\n p = p.next\nreturn result"
] | <|body_start_0|>
if not Arr:
return None
head = ListNode(Arr[0])
p = head
for i in range(1, len(Arr)):
p.next = ListNode(Arr[i])
p = p.next
return head
<|end_body_0|>
<|body_start_1|>
if not head:
return None
result... | LinkList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinkList:
def buildList(self, Arr):
"""建立链表"""
<|body_0|>
def printLinkList(self, head):
"""打印链表"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not Arr:
return None
head = ListNode(Arr[0])
p = head
for i in ra... | stack_v2_sparse_classes_36k_train_008542 | 2,459 | no_license | [
{
"docstring": "建立链表",
"name": "buildList",
"signature": "def buildList(self, Arr)"
},
{
"docstring": "打印链表",
"name": "printLinkList",
"signature": "def printLinkList(self, head)"
}
] | 2 | null | Implement the Python class `LinkList` described below.
Class description:
Implement the LinkList class.
Method signatures and docstrings:
- def buildList(self, Arr): 建立链表
- def printLinkList(self, head): 打印链表 | Implement the Python class `LinkList` described below.
Class description:
Implement the LinkList class.
Method signatures and docstrings:
- def buildList(self, Arr): 建立链表
- def printLinkList(self, head): 打印链表
<|skeleton|>
class LinkList:
def buildList(self, Arr):
"""建立链表"""
<|body_0|>
def p... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class LinkList:
def buildList(self, Arr):
"""建立链表"""
<|body_0|>
def printLinkList(self, head):
"""打印链表"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinkList:
def buildList(self, Arr):
"""建立链表"""
if not Arr:
return None
head = ListNode(Arr[0])
p = head
for i in range(1, len(Arr)):
p.next = ListNode(Arr[i])
p = p.next
return head
def printLinkList(self, head):
... | the_stack_v2_python_sparse | Big大话数据结构/linklist链表/1、相交链表的交点.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 | |
a9feae6f37a759eeb6f33b95ea92c7aa66d8432c | [
"self.url = '/ydtp-backend-service/api/web_hand_over_duty'\ndata = {'user_id': handUser, 'password': pwd}\nre = self.post(url=self.zby_api, data=data, headers=form_headers)\nreturn re.text",
"self.url = '/ydtp-backend-service/api/offduty'\nre = self.post(url=self.zby_api, headers=form_headers)\nreturn re.text",
... | <|body_start_0|>
self.url = '/ydtp-backend-service/api/web_hand_over_duty'
data = {'user_id': handUser, 'password': pwd}
re = self.post(url=self.zby_api, data=data, headers=form_headers)
return re.text
<|end_body_0|>
<|body_start_1|>
self.url = '/ydtp-backend-service/api/offduty... | 个人中心 | PersonalInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonalInfo:
"""个人中心"""
def webHandOverDuty(self, handUser, pwd):
"""交接班"""
<|body_0|>
def offduty(self):
"""退出登录"""
<|body_1|>
def dutyInfo(self):
"""个人信息"""
<|body_2|>
def __shiftRecords(self):
"""收费汇总列表"""
<|b... | stack_v2_sparse_classes_36k_train_008543 | 1,626 | no_license | [
{
"docstring": "交接班",
"name": "webHandOverDuty",
"signature": "def webHandOverDuty(self, handUser, pwd)"
},
{
"docstring": "退出登录",
"name": "offduty",
"signature": "def offduty(self)"
},
{
"docstring": "个人信息",
"name": "dutyInfo",
"signature": "def dutyInfo(self)"
},
{
... | 5 | null | Implement the Python class `PersonalInfo` described below.
Class description:
个人中心
Method signatures and docstrings:
- def webHandOverDuty(self, handUser, pwd): 交接班
- def offduty(self): 退出登录
- def dutyInfo(self): 个人信息
- def __shiftRecords(self): 收费汇总列表
- def shiftMoneys(self): 查看收费流水清单 | Implement the Python class `PersonalInfo` described below.
Class description:
个人中心
Method signatures and docstrings:
- def webHandOverDuty(self, handUser, pwd): 交接班
- def offduty(self): 退出登录
- def dutyInfo(self): 个人信息
- def __shiftRecords(self): 收费汇总列表
- def shiftMoneys(self): 查看收费流水清单
<|skeleton|>
class PersonalInf... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class PersonalInfo:
"""个人中心"""
def webHandOverDuty(self, handUser, pwd):
"""交接班"""
<|body_0|>
def offduty(self):
"""退出登录"""
<|body_1|>
def dutyInfo(self):
"""个人信息"""
<|body_2|>
def __shiftRecords(self):
"""收费汇总列表"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersonalInfo:
"""个人中心"""
def webHandOverDuty(self, handUser, pwd):
"""交接班"""
self.url = '/ydtp-backend-service/api/web_hand_over_duty'
data = {'user_id': handUser, 'password': pwd}
re = self.post(url=self.zby_api, data=data, headers=form_headers)
return re.text
... | the_stack_v2_python_sparse | Api/sentry_service/personalInfo.py | oyebino/pomp_api | train | 1 |
71a09f56391825e8356cf44bef808b34970e9728 | [
"if self.action == 'create':\n return [IsAuthenticated()]\nif self.action in ['update', 'partial_update', 'destroy']:\n return [IsAdminUser()]\nreturn []",
"if self.request.user.is_superuser:\n return Order.objects.prefetch_related('orders_in').all()\nif self.request.user.is_authenticated:\n return Or... | <|body_start_0|>
if self.action == 'create':
return [IsAuthenticated()]
if self.action in ['update', 'partial_update', 'destroy']:
return [IsAdminUser()]
return []
<|end_body_0|>
<|body_start_1|>
if self.request.user.is_superuser:
return Order.objects... | OrderViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderViewSet:
def get_permissions(self):
"""Получение прав для действий."""
<|body_0|>
def get_queryset(self):
"""Получение списка заказов."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.action == 'create':
return [IsAuthenticat... | stack_v2_sparse_classes_36k_train_008544 | 1,309 | no_license | [
{
"docstring": "Получение прав для действий.",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "Получение списка заказов.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020546 | Implement the Python class `OrderViewSet` described below.
Class description:
Implement the OrderViewSet class.
Method signatures and docstrings:
- def get_permissions(self): Получение прав для действий.
- def get_queryset(self): Получение списка заказов. | Implement the Python class `OrderViewSet` described below.
Class description:
Implement the OrderViewSet class.
Method signatures and docstrings:
- def get_permissions(self): Получение прав для действий.
- def get_queryset(self): Получение списка заказов.
<|skeleton|>
class OrderViewSet:
def get_permissions(sel... | 1edce1a74e1fef43c4cdc9fe39a0b4d2fbec77b2 | <|skeleton|>
class OrderViewSet:
def get_permissions(self):
"""Получение прав для действий."""
<|body_0|>
def get_queryset(self):
"""Получение списка заказов."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderViewSet:
def get_permissions(self):
"""Получение прав для действий."""
if self.action == 'create':
return [IsAuthenticated()]
if self.action in ['update', 'partial_update', 'destroy']:
return [IsAdminUser()]
return []
def get_queryset(self):
... | the_stack_v2_python_sparse | order/views.py | LiliyaVerchenko/dj_diplom | train | 0 | |
9468d4724c762ae62f7aebece6a1ef51dfd29736 | [
"if self is NativeOrForeign.Foreign:\n return pair.foreign\nelif self is NativeOrForeign.Native:\n return pair.native",
"if self is NativeOrForeign.Foreign:\n return NativeOrForeign.Native\nelif self is NativeOrForeign.Native:\n return NativeOrForeign.Foreign"
] | <|body_start_0|>
if self is NativeOrForeign.Foreign:
return pair.foreign
elif self is NativeOrForeign.Native:
return pair.native
<|end_body_0|>
<|body_start_1|>
if self is NativeOrForeign.Foreign:
return NativeOrForeign.Native
elif self is NativeOrFor... | Helper class to dynamically get the proper Form from a Concpet Pair | NativeOrForeign | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NativeOrForeign:
"""Helper class to dynamically get the proper Form from a Concpet Pair"""
def __call__(self, pair):
"""Return the proepr Form from the given Concept Pair"""
<|body_0|>
def other(self):
"""Return the other Type of Native or Foreign"""
<|bo... | stack_v2_sparse_classes_36k_train_008545 | 717 | no_license | [
{
"docstring": "Return the proepr Form from the given Concept Pair",
"name": "__call__",
"signature": "def __call__(self, pair)"
},
{
"docstring": "Return the other Type of Native or Foreign",
"name": "other",
"signature": "def other(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004061 | Implement the Python class `NativeOrForeign` described below.
Class description:
Helper class to dynamically get the proper Form from a Concpet Pair
Method signatures and docstrings:
- def __call__(self, pair): Return the proepr Form from the given Concept Pair
- def other(self): Return the other Type of Native or Fo... | Implement the Python class `NativeOrForeign` described below.
Class description:
Helper class to dynamically get the proper Form from a Concpet Pair
Method signatures and docstrings:
- def __call__(self, pair): Return the proepr Form from the given Concept Pair
- def other(self): Return the other Type of Native or Fo... | f08dc4465b7e4fb32235e1647c46edd4472f9093 | <|skeleton|>
class NativeOrForeign:
"""Helper class to dynamically get the proper Form from a Concpet Pair"""
def __call__(self, pair):
"""Return the proepr Form from the given Concept Pair"""
<|body_0|>
def other(self):
"""Return the other Type of Native or Foreign"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NativeOrForeign:
"""Helper class to dynamically get the proper Form from a Concpet Pair"""
def __call__(self, pair):
"""Return the proepr Form from the given Concept Pair"""
if self is NativeOrForeign.Foreign:
return pair.foreign
elif self is NativeOrForeign.Native:
... | the_stack_v2_python_sparse | src/Data/Concept/native_or_foreign.py | cloew/VocabTester | train | 0 |
a7669150fc762245c8fb0d68f8df6901ff0b2d8d | [
"storage = get_storage()\nsites = storage.list_sites()\nreturn jsonify(SiteResponseSchema(many=True).dump(sites))",
"data = request.get_json()\ntry:\n site = SiteSchema().load(data)\nexcept ValidationError as err:\n return (jsonify({'errors': err.messages}), 400)\nstorage = get_storage()\nsite_id = storage.... | <|body_start_0|>
storage = get_storage()
sites = storage.list_sites()
return jsonify(SiteResponseSchema(many=True).dump(sites))
<|end_body_0|>
<|body_start_1|>
data = request.get_json()
try:
site = SiteSchema().load(data)
except ValidationError as err:
... | AllSitesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AllSitesView:
def get(self, *args):
"""--- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content: application/json: schema: type: array items: $ref: '#/components/schemas/SiteMetadata' 401: $ref: '#... | stack_v2_sparse_classes_36k_train_008546 | 10,882 | permissive | [
{
"docstring": "--- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content: application/json: schema: type: array items: $ref: '#/components/schemas/SiteMetadata' 401: $ref: '#/components/responses/401-Unauthorized'",
"... | 2 | stack_v2_sparse_classes_30k_train_018939 | Implement the Python class `AllSitesView` described below.
Class description:
Implement the AllSitesView class.
Method signatures and docstrings:
- def get(self, *args): --- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content:... | Implement the Python class `AllSitesView` described below.
Class description:
Implement the AllSitesView class.
Method signatures and docstrings:
- def get(self, *args): --- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content:... | 280800c73eb7cfd49029462b352887e78f1ff91b | <|skeleton|>
class AllSitesView:
def get(self, *args):
"""--- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content: application/json: schema: type: array items: $ref: '#/components/schemas/SiteMetadata' 401: $ref: '#... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AllSitesView:
def get(self, *args):
"""--- summary: List sites description: List all sites that the user has access to. tags: - Sites responses: 200: description: A list of sites content: application/json: schema: type: array items: $ref: '#/components/schemas/SiteMetadata' 401: $ref: '#/components/re... | the_stack_v2_python_sparse | sfa_api/sites.py | SolarArbiter/solarforecastarbiter-api | train | 9 | |
0a0e8ca954e11fa02ce577db60c945c42932fb3e | [
"self.w = w\nself.arr = [w[0]]\nfor n in w[1:]:\n self.arr.append(self.arr[-1] + n)",
"rnd = random.random() * self.arr[-1]\ni = bisect.bisect_left(self.arr, rnd)\nreturn i"
] | <|body_start_0|>
self.w = w
self.arr = [w[0]]
for n in w[1:]:
self.arr.append(self.arr[-1] + n)
<|end_body_0|>
<|body_start_1|>
rnd = random.random() * self.arr[-1]
i = bisect.bisect_left(self.arr, rnd)
return i
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.w = w
self.arr = [w[0]]
for n in w[1:]:
self.arr.append(self.ar... | stack_v2_sparse_classes_36k_train_008547 | 542 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | b4da922c4e8406c486760639b71e3ec50283ca43 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.w = w
self.arr = [w[0]]
for n in w[1:]:
self.arr.append(self.arr[-1] + n)
def pickIndex(self):
""":rtype: int"""
rnd = random.random() * self.arr[-1]
i = bisect.bisect_left(s... | the_stack_v2_python_sparse | current_session/python/528_redo2.py | YJL33/LeetCode | train | 3 | |
a164b4fa59a69e1154a25238695a2d4c0fc69a16 | [
"self.__domain = domainName\nself.__kdcHost = serverIP\nself.__domainUsers = domainusers\nself.__sprayPassword = sprayPassword\nself.DomainUserRequest()",
"domain = '@' + self.__domain\nfor user in self.__domainUsers:\n targetuser = user + domain\n self.AttackToTarget(targetuser)",
"self.__sprayusers = []... | <|body_start_0|>
self.__domain = domainName
self.__kdcHost = serverIP
self.__domainUsers = domainusers
self.__sprayPassword = sprayPassword
self.DomainUserRequest()
<|end_body_0|>
<|body_start_1|>
domain = '@' + self.__domain
for user in self.__domainUsers:
... | PasswordSPRAY | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
<|body_0|>
def DomainUserRequest(self):
"""Pars to Domain"""
<|body_1|>
def AttackToTarget(self, username):
"""Attack Part"""... | stack_v2_sparse_classes_36k_train_008548 | 1,067 | permissive | [
{
"docstring": "Spray Attack Arguments",
"name": "AttackArguments",
"signature": "def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName)"
},
{
"docstring": "Pars to Domain",
"name": "DomainUserRequest",
"signature": "def DomainUserRequest(self)"
},
{
"docstri... | 3 | stack_v2_sparse_classes_30k_train_017093 | Implement the Python class `PasswordSPRAY` described below.
Class description:
Implement the PasswordSPRAY class.
Method signatures and docstrings:
- def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName): Spray Attack Arguments
- def DomainUserRequest(self): Pars to Domain
- def AttackToTarget(s... | Implement the Python class `PasswordSPRAY` described below.
Class description:
Implement the PasswordSPRAY class.
Method signatures and docstrings:
- def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName): Spray Attack Arguments
- def DomainUserRequest(self): Pars to Domain
- def AttackToTarget(s... | 92263ea73bd2eaa2081fb277c76aa229103a1d54 | <|skeleton|>
class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
<|body_0|>
def DomainUserRequest(self):
"""Pars to Domain"""
<|body_1|>
def AttackToTarget(self, username):
"""Attack Part"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordSPRAY:
def AttackArguments(self, serverIP, domainusers, sprayPassword, domainName):
"""Spray Attack Arguments"""
self.__domain = domainName
self.__kdcHost = serverIP
self.__domainUsers = domainusers
self.__sprayPassword = sprayPassword
self.DomainUserReq... | the_stack_v2_python_sparse | pentestui/pentest_api/enumeration/ldap/spray/sprayattack.py | mustgundogdu/PentestUI | train | 31 | |
3119ec891683e72a49046e7cff5463760b8e7a7e | [
"profiles = Profile.objects.all()\nserializer = ProfileCreateSerializer(profiles, many=True)\nreturn Response(serializer.data)",
"serializer = ProfileCreateSerializer(data=request.data)\nif serializer.is_valid(raise_exception=ValueError):\n serializer.save()\n return Response(serializer.data, status=status.... | <|body_start_0|>
profiles = Profile.objects.all()
serializer = ProfileCreateSerializer(profiles, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = ProfileCreateSerializer(data=request.data)
if serializer.is_valid(raise_exception=ValueError)... | A class based view for creating and fetching student records | ProfileCreateAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfileCreateAPIView:
"""A class based view for creating and fetching student records"""
def get(self, format: object=None) -> object:
"""Get all the student records :param format: Format of the student records to return to :return: Returns a list of student records"""
<|body... | stack_v2_sparse_classes_36k_train_008549 | 8,136 | no_license | [
{
"docstring": "Get all the student records :param format: Format of the student records to return to :return: Returns a list of student records",
"name": "get",
"signature": "def get(self, format: object=None) -> object"
},
{
"docstring": "Create a student record :param format: Format of the st... | 2 | null | Implement the Python class `ProfileCreateAPIView` described below.
Class description:
A class based view for creating and fetching student records
Method signatures and docstrings:
- def get(self, format: object=None) -> object: Get all the student records :param format: Format of the student records to return to :re... | Implement the Python class `ProfileCreateAPIView` described below.
Class description:
A class based view for creating and fetching student records
Method signatures and docstrings:
- def get(self, format: object=None) -> object: Get all the student records :param format: Format of the student records to return to :re... | 42e42cbd9b7dbcaed38109b7373735ff110900a3 | <|skeleton|>
class ProfileCreateAPIView:
"""A class based view for creating and fetching student records"""
def get(self, format: object=None) -> object:
"""Get all the student records :param format: Format of the student records to return to :return: Returns a list of student records"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfileCreateAPIView:
"""A class based view for creating and fetching student records"""
def get(self, format: object=None) -> object:
"""Get all the student records :param format: Format of the student records to return to :return: Returns a list of student records"""
profiles = Profile.... | the_stack_v2_python_sparse | UserRegistrationApp/views.py | HishamDigitalHub/SportActivities | train | 0 |
4f89da3cd0a34cb113e61d9694ff10fc4519053d | [
"EventHandler.__init__(self)\nself._pegHand = pegHandler\nself._color = colorNum",
"if event.getDescription() == 'mouse click':\n gui = self._pegHand._gui\n gui._guess.setPegColor(self._pegHand._peg, self._color)\n hole = gui._holes[gui._currentTurnNum][self._pegHand._peg]\n hole.setRadius(gui._pegRad... | <|body_start_0|>
EventHandler.__init__(self)
self._pegHand = pegHandler
self._color = colorNum
<|end_body_0|>
<|body_start_1|>
if event.getDescription() == 'mouse click':
gui = self._pegHand._gui
gui._guess.setPegColor(self._pegHand._peg, self._color)
... | Handler class for the selection of a colored peg. | ChoiceHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChoiceHandler:
"""Handler class for the selection of a colored peg."""
def __init__(self, pegHandler, colorNum):
"""Create a new instance."""
<|body_0|>
def handle(self, event):
"""Set the choice of color and close the popup."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_008550 | 6,736 | no_license | [
{
"docstring": "Create a new instance.",
"name": "__init__",
"signature": "def __init__(self, pegHandler, colorNum)"
},
{
"docstring": "Set the choice of color and close the popup.",
"name": "handle",
"signature": "def handle(self, event)"
}
] | 2 | null | Implement the Python class `ChoiceHandler` described below.
Class description:
Handler class for the selection of a colored peg.
Method signatures and docstrings:
- def __init__(self, pegHandler, colorNum): Create a new instance.
- def handle(self, event): Set the choice of color and close the popup. | Implement the Python class `ChoiceHandler` described below.
Class description:
Handler class for the selection of a colored peg.
Method signatures and docstrings:
- def __init__(self, pegHandler, colorNum): Create a new instance.
- def handle(self, event): Set the choice of color and close the popup.
<|skeleton|>
cl... | 2d008e9cedc33d9e24420bef14b73b28ff54cdbf | <|skeleton|>
class ChoiceHandler:
"""Handler class for the selection of a colored peg."""
def __init__(self, pegHandler, colorNum):
"""Create a new instance."""
<|body_0|>
def handle(self, event):
"""Set the choice of color and close the popup."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChoiceHandler:
"""Handler class for the selection of a colored peg."""
def __init__(self, pegHandler, colorNum):
"""Create a new instance."""
EventHandler.__init__(self)
self._pegHand = pegHandler
self._color = colorNum
def handle(self, event):
"""Set the choi... | the_stack_v2_python_sparse | C152/sourcecode/ch15/MastermindGUI.py | nrichgels/ClassCode | train | 2 |
ee13ea769fd21ec674b0316d052d7a3838685764 | [
"url = host + '/api/goods/find'\ndata = {'sku': sku, 'gid': goods_id}\nr = requests.post(url=url, data=data).json()\nout_format('获取单品:', r)",
"url = host + '/api/goods/line'\ndata = {'sku': sku, 'gid': goods_id}\nr = requests.post(url=url, data=data).json()\nout_format('获取单品价格和属性:', r)\nreturn r",
"url = host +... | <|body_start_0|>
url = host + '/api/goods/find'
data = {'sku': sku, 'gid': goods_id}
r = requests.post(url=url, data=data).json()
out_format('获取单品:', r)
<|end_body_0|>
<|body_start_1|>
url = host + '/api/goods/line'
data = {'sku': sku, 'gid': goods_id}
r = reques... | goods | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class goods:
def get_goods(self):
"""获取单品 :return: gid"""
<|body_0|>
def get_price(self):
"""获取单品价格和属性 :return:"""
<|body_1|>
def get_comment(self):
"""获取评论列表 gid:产品id size:记录条数 page:页码 :return:"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_008551 | 1,426 | no_license | [
{
"docstring": "获取单品 :return: gid",
"name": "get_goods",
"signature": "def get_goods(self)"
},
{
"docstring": "获取单品价格和属性 :return:",
"name": "get_price",
"signature": "def get_price(self)"
},
{
"docstring": "获取评论列表 gid:产品id size:记录条数 page:页码 :return:",
"name": "get_comment",
... | 3 | stack_v2_sparse_classes_30k_train_005459 | Implement the Python class `goods` described below.
Class description:
Implement the goods class.
Method signatures and docstrings:
- def get_goods(self): 获取单品 :return: gid
- def get_price(self): 获取单品价格和属性 :return:
- def get_comment(self): 获取评论列表 gid:产品id size:记录条数 page:页码 :return: | Implement the Python class `goods` described below.
Class description:
Implement the goods class.
Method signatures and docstrings:
- def get_goods(self): 获取单品 :return: gid
- def get_price(self): 获取单品价格和属性 :return:
- def get_comment(self): 获取评论列表 gid:产品id size:记录条数 page:页码 :return:
<|skeleton|>
class goods:
def... | 0ebaae335de2f1633e31c4fc3f60e556220a8bfb | <|skeleton|>
class goods:
def get_goods(self):
"""获取单品 :return: gid"""
<|body_0|>
def get_price(self):
"""获取单品价格和属性 :return:"""
<|body_1|>
def get_comment(self):
"""获取评论列表 gid:产品id size:记录条数 page:页码 :return:"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class goods:
def get_goods(self):
"""获取单品 :return: gid"""
url = host + '/api/goods/find'
data = {'sku': sku, 'gid': goods_id}
r = requests.post(url=url, data=data).json()
out_format('获取单品:', r)
def get_price(self):
"""获取单品价格和属性 :return:"""
url = host + '/... | the_stack_v2_python_sparse | Atle/interface/framework/base/aGoods.py | shiqi0128/My_scripts | train | 0 | |
b40d56eabe8d6e3f1f5875a2ba77b5222ec40314 | [
"self.user = user\npipelines = kwargs.pop('pipelines', None)\nsuper(ProjectCreateForm, self).__init__(*args, **kwargs)\nchoices = []\nif pipelines is not None:\n for pipeline in pipelines:\n choices.append((pipeline.id, pipeline.name))\n self.fields['pipeline'].choices = choices",
"project_name = sel... | <|body_start_0|>
self.user = user
pipelines = kwargs.pop('pipelines', None)
super(ProjectCreateForm, self).__init__(*args, **kwargs)
choices = []
if pipelines is not None:
for pipeline in pipelines:
choices.append((pipeline.id, pipeline.name))
... | Form for project creation. | ProjectCreateForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectCreateForm:
"""Form for project creation."""
def __init__(self, user, *args, **kwargs):
"""Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable with Script objects"""
<|body_0|>
def clean_pro... | stack_v2_sparse_classes_36k_train_008552 | 2,111 | no_license | [
{
"docstring": "Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable with Script objects",
"name": "__init__",
"signature": "def __init__(self, user, *args, **kwargs)"
},
{
"docstring": "Clean the project name in this form.... | 3 | stack_v2_sparse_classes_30k_train_019192 | Implement the Python class `ProjectCreateForm` described below.
Class description:
Form for project creation.
Method signatures and docstrings:
- def __init__(self, user, *args, **kwargs): Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable wit... | Implement the Python class `ProjectCreateForm` described below.
Class description:
Form for project creation.
Method signatures and docstrings:
- def __init__(self, user, *args, **kwargs): Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable wit... | dfa60c9a812e52fa44f0d3cf1c201943574976df | <|skeleton|>
class ProjectCreateForm:
"""Form for project creation."""
def __init__(self, user, *args, **kwargs):
"""Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable with Script objects"""
<|body_0|>
def clean_pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectCreateForm:
"""Form for project creation."""
def __init__(self, user, *args, **kwargs):
"""Initialise method for ProjectCreateForm. :param args: argument :param kwargs: keyword arguments containing a scripts variable with Script objects"""
self.user = user
pipelines = kwarg... | the_stack_v2_python_sparse | equestria/projects/forms.py | KiOui/CLST-2020 | train | 0 |
c8123c33139ade40cee1c22d58ef0279d1d914ab | [
"super().__init__(model_path, device, core, num_requests, 'Action Recognition')\n_, _, t, h, w = self.input_size\nself.input_height = h\nself.input_width = w\nself.input_length = t\nself.img_scale = img_scale\nself.num_test_classes = num_classes",
"src_roi_height, src_roi_width = (src_roi[3] - src_roi[1], src_roi... | <|body_start_0|>
super().__init__(model_path, device, core, num_requests, 'Action Recognition')
_, _, t, h, w = self.input_size
self.input_height = h
self.input_width = w
self.input_length = t
self.img_scale = img_scale
self.num_test_classes = num_classes
<|end_bo... | Class that is used to work with action recognition model. | ActionRecognizer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionRecognizer:
"""Class that is used to work with action recognition model."""
def __init__(self, model_path, device, core, num_requests, img_scale, num_classes):
"""Constructor"""
<|body_0|>
def _convert_to_central_roi(src_roi, input_height, input_width, img_scale):
... | stack_v2_sparse_classes_36k_train_008553 | 3,426 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, model_path, device, core, num_requests, img_scale, num_classes)"
},
{
"docstring": "Extracts from the input ROI the central square part with specified side size",
"name": "_convert_to_central_roi",
"signat... | 5 | null | Implement the Python class `ActionRecognizer` described below.
Class description:
Class that is used to work with action recognition model.
Method signatures and docstrings:
- def __init__(self, model_path, device, core, num_requests, img_scale, num_classes): Constructor
- def _convert_to_central_roi(src_roi, input_h... | Implement the Python class `ActionRecognizer` described below.
Class description:
Class that is used to work with action recognition model.
Method signatures and docstrings:
- def __init__(self, model_path, device, core, num_requests, img_scale, num_classes): Constructor
- def _convert_to_central_roi(src_roi, input_h... | 7929adbe91e9cfe8dc5dc1daad5ae7392f9719a0 | <|skeleton|>
class ActionRecognizer:
"""Class that is used to work with action recognition model."""
def __init__(self, model_path, device, core, num_requests, img_scale, num_classes):
"""Constructor"""
<|body_0|>
def _convert_to_central_roi(src_roi, input_height, input_width, img_scale):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionRecognizer:
"""Class that is used to work with action recognition model."""
def __init__(self, model_path, device, core, num_requests, img_scale, num_classes):
"""Constructor"""
super().__init__(model_path, device, core, num_requests, 'Action Recognition')
_, _, t, h, w = se... | the_stack_v2_python_sparse | demos/gesture_recognition_demo/python/gesture_recognition_demo/action_recognizer.py | openvinotoolkit/open_model_zoo | train | 1,712 |
f17eac5a734194eba918cb8a2185f3505e4f5e9f | [
"if self.auto:\n try:\n application.pyre_mpi(*args, **kwds)\n except AttributeError:\n pass\n return self.spawn(*args, application=application, **kwds)\nreturn self.parallel(*args, application=application, **kwds)",
"import mpi\nif mpi.init():\n self.world = mpi.world\n return super()... | <|body_start_0|>
if self.auto:
try:
application.pyre_mpi(*args, **kwds)
except AttributeError:
pass
return self.spawn(*args, application=application, **kwds)
return self.parallel(*args, application=application, **kwds)
<|end_body_0|>
<... | Encapsulation of launching an MPI job using {mpirun} | Launcher | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Launcher:
"""Encapsulation of launching an MPI job using {mpirun}"""
def launch(self, application, *args, **kwds):
"""Launch {application} as a collection of mpi tasks"""
<|body_0|>
def parallel(self, *args, **kwds):
"""Called after the parallel machine has been ... | stack_v2_sparse_classes_36k_train_008554 | 5,102 | permissive | [
{
"docstring": "Launch {application} as a collection of mpi tasks",
"name": "launch",
"signature": "def launch(self, application, *args, **kwds)"
},
{
"docstring": "Called after the parallel machine has been built and it is time to invoke the user's code in every node",
"name": "parallel",
... | 4 | stack_v2_sparse_classes_30k_train_006701 | Implement the Python class `Launcher` described below.
Class description:
Encapsulation of launching an MPI job using {mpirun}
Method signatures and docstrings:
- def launch(self, application, *args, **kwds): Launch {application} as a collection of mpi tasks
- def parallel(self, *args, **kwds): Called after the paral... | Implement the Python class `Launcher` described below.
Class description:
Encapsulation of launching an MPI job using {mpirun}
Method signatures and docstrings:
- def launch(self, application, *args, **kwds): Launch {application} as a collection of mpi tasks
- def parallel(self, *args, **kwds): Called after the paral... | d741c44ffb3e9e1f726bf492202ac8738bb4aa1c | <|skeleton|>
class Launcher:
"""Encapsulation of launching an MPI job using {mpirun}"""
def launch(self, application, *args, **kwds):
"""Launch {application} as a collection of mpi tasks"""
<|body_0|>
def parallel(self, *args, **kwds):
"""Called after the parallel machine has been ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Launcher:
"""Encapsulation of launching an MPI job using {mpirun}"""
def launch(self, application, *args, **kwds):
"""Launch {application} as a collection of mpi tasks"""
if self.auto:
try:
application.pyre_mpi(*args, **kwds)
except AttributeError:
... | the_stack_v2_python_sparse | packages/mpi/Launcher.py | pyre/pyre | train | 27 |
4eaf959e6e238a9044869b45cd495ded070f94fa | [
"if r >= N or r < 0 or c < 0 or (c >= N):\n return 0\nif K == 0:\n return 1\nelse:\n explore = [[-2, -1], [-1, -2], [-2, 1], [-1, 2], [2, -1], [1, -2], [2, 1], [1, 2]]\n tot_prob = 0\n for xd, yd in explore:\n v = self.knightProbability(N, K - 1, r + xd, c + yd)\n tot_prob += v\n ret... | <|body_start_0|>
if r >= N or r < 0 or c < 0 or (c >= N):
return 0
if K == 0:
return 1
else:
explore = [[-2, -1], [-1, -2], [-2, 1], [-1, 2], [2, -1], [1, -2], [2, 1], [1, 2]]
tot_prob = 0
for xd, yd in explore:
v = self... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def knightProbability_bf(self, N, K, r, c):
""":type N: int :type K: int :type r: int :type c: int :rtype: float"""
<|body_0|>
def knightProbability(self, N, K, r, c):
""":type N: int :type K: int :type r: int :type c: int :rtype: float"""
<|body_1|... | stack_v2_sparse_classes_36k_train_008555 | 1,548 | no_license | [
{
"docstring": ":type N: int :type K: int :type r: int :type c: int :rtype: float",
"name": "knightProbability_bf",
"signature": "def knightProbability_bf(self, N, K, r, c)"
},
{
"docstring": ":type N: int :type K: int :type r: int :type c: int :rtype: float",
"name": "knightProbability",
... | 2 | stack_v2_sparse_classes_30k_train_019398 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knightProbability_bf(self, N, K, r, c): :type N: int :type K: int :type r: int :type c: int :rtype: float
- def knightProbability(self, N, K, r, c): :type N: int :type K: int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knightProbability_bf(self, N, K, r, c): :type N: int :type K: int :type r: int :type c: int :rtype: float
- def knightProbability(self, N, K, r, c): :type N: int :type K: int... | b3a8a4db43f1d8620b70d54dd032e37b1eae7947 | <|skeleton|>
class Solution:
def knightProbability_bf(self, N, K, r, c):
""":type N: int :type K: int :type r: int :type c: int :rtype: float"""
<|body_0|>
def knightProbability(self, N, K, r, c):
""":type N: int :type K: int :type r: int :type c: int :rtype: float"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def knightProbability_bf(self, N, K, r, c):
""":type N: int :type K: int :type r: int :type c: int :rtype: float"""
if r >= N or r < 0 or c < 0 or (c >= N):
return 0
if K == 0:
return 1
else:
explore = [[-2, -1], [-1, -2], [-2, 1], ... | the_stack_v2_python_sparse | Leetcode/Medium/knight_prob.py | rajaditya-m/Interview-Prep | train | 0 | |
4d733c4aefc460de5b36fbc0fb046509e030af71 | [
"alloy_type_set = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False)\nalloy = alloy_model.Alloy.objects.only('id', 'name').filter(is_delete=False, id=alloy_id)\nif alloy:\n data = {'alloy_type_set': alloy_type_set, 'alloy': alloy}\n return render(request, 'admin/alloy/alloy_edit.html', c... | <|body_start_0|>
alloy_type_set = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False)
alloy = alloy_model.Alloy.objects.only('id', 'name').filter(is_delete=False, id=alloy_id)
if alloy:
data = {'alloy_type_set': alloy_type_set, 'alloy': alloy}
return ... | 合金修改 | AlloyEdit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlloyEdit:
"""合金修改"""
def get(self, request, alloy_id):
"""指定合金查询展示 :param request: :param alloy_id: :return:"""
<|body_0|>
def put(self, request, alloy_id):
"""指定合金修改 :param request: :param alloy_id: :return:"""
<|body_1|>
def delete(self, request, ... | stack_v2_sparse_classes_36k_train_008556 | 11,849 | no_license | [
{
"docstring": "指定合金查询展示 :param request: :param alloy_id: :return:",
"name": "get",
"signature": "def get(self, request, alloy_id)"
},
{
"docstring": "指定合金修改 :param request: :param alloy_id: :return:",
"name": "put",
"signature": "def put(self, request, alloy_id)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_009375 | Implement the Python class `AlloyEdit` described below.
Class description:
合金修改
Method signatures and docstrings:
- def get(self, request, alloy_id): 指定合金查询展示 :param request: :param alloy_id: :return:
- def put(self, request, alloy_id): 指定合金修改 :param request: :param alloy_id: :return:
- def delete(self, request, allo... | Implement the Python class `AlloyEdit` described below.
Class description:
合金修改
Method signatures and docstrings:
- def get(self, request, alloy_id): 指定合金查询展示 :param request: :param alloy_id: :return:
- def put(self, request, alloy_id): 指定合金修改 :param request: :param alloy_id: :return:
- def delete(self, request, allo... | 063332d2a5e2ddabf800817f02074b4f5c162ade | <|skeleton|>
class AlloyEdit:
"""合金修改"""
def get(self, request, alloy_id):
"""指定合金查询展示 :param request: :param alloy_id: :return:"""
<|body_0|>
def put(self, request, alloy_id):
"""指定合金修改 :param request: :param alloy_id: :return:"""
<|body_1|>
def delete(self, request, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlloyEdit:
"""合金修改"""
def get(self, request, alloy_id):
"""指定合金查询展示 :param request: :param alloy_id: :return:"""
alloy_type_set = alloy_model.AlloyType.objects.only('id', 'type').filter(is_delete=False)
alloy = alloy_model.Alloy.objects.only('id', 'name').filter(is_delete=False, i... | the_stack_v2_python_sparse | sfs/apps/alloy/views.py | Hx-someone/sfs-1 | train | 0 |
1486af3848f9ce74c1c9ad17c7fc0fe6a6c3b2bb | [
"if self.action in ['login', 'signup', 'verify']:\n permissions = [AllowAny]\nelif self.action in ['profile', 'retrieve', 'update', 'partial_update']:\n permissions = [IsAuthenticated, IsAccountOwner]\nelse:\n permissions = [IsAuthenticated]\nreturn [p() for p in permissions]",
"serializer = UserLoginSer... | <|body_start_0|>
if self.action in ['login', 'signup', 'verify']:
permissions = [AllowAny]
elif self.action in ['profile', 'retrieve', 'update', 'partial_update']:
permissions = [IsAuthenticated, IsAccountOwner]
else:
permissions = [IsAuthenticated]
re... | User view set. Handle sign up, login and account verification. | UserViewSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserViewSet:
"""User view set. Handle sign up, login and account verification."""
def get_permissions(self):
"""Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same User can be edited and viewed"""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_008557 | 3,563 | permissive | [
{
"docstring": "Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same User can be edited and viewed",
"name": "get_permissions",
"signature": "def get_permissions(self)"
},
{
"docstring": "User sign in.",
"name": "login",
"signatu... | 5 | stack_v2_sparse_classes_30k_train_009513 | Implement the Python class `UserViewSet` described below.
Class description:
User view set. Handle sign up, login and account verification.
Method signatures and docstrings:
- def get_permissions(self): Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same Use... | Implement the Python class `UserViewSet` described below.
Class description:
User view set. Handle sign up, login and account verification.
Method signatures and docstrings:
- def get_permissions(self): Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same Use... | 9693e95ca723f1846666838a24c60d0715224e36 | <|skeleton|>
class UserViewSet:
"""User view set. Handle sign up, login and account verification."""
def get_permissions(self):
"""Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same User can be edited and viewed"""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserViewSet:
"""User view set. Handle sign up, login and account verification."""
def get_permissions(self):
"""Assign permissions based on action. If the action is retrieve, custom permission is added so that only the same User can be edited and viewed"""
if self.action in ['login', 'sig... | the_stack_v2_python_sparse | root/users/api/views/users.py | macknilan/Post-prueba-tecnica-desarrollador-python | train | 1 |
ec26c73f2ab189b55b53dbdfcf44d4b890a40935 | [
"self.kekule_smiles = kekule_smiles\nself.all_bonds_explicit = all_bonds_explicit\nself.all_hs_explicit = all_hs_explicit\nself.sanitize = sanitize\nself.seed = seed\nif self.seed > -1:\n np.random.seed(self.seed)",
"molecule = Chem.MolFromSmiles(smiles, sanitize=self.sanitize)\nif molecule is None:\n logge... | <|body_start_0|>
self.kekule_smiles = kekule_smiles
self.all_bonds_explicit = all_bonds_explicit
self.all_hs_explicit = all_hs_explicit
self.sanitize = sanitize
self.seed = seed
if self.seed > -1:
np.random.seed(self.seed)
<|end_body_0|>
<|body_start_1|>
... | Augment a SMILES string, according to Bjerrum (2017). | Augment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Augment:
"""Augment a SMILES string, according to Bjerrum (2017)."""
def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None:
"""NOTE: These parameter need to be passed down to the enumerato... | stack_v2_sparse_classes_36k_train_008558 | 22,008 | permissive | [
{
"docstring": "NOTE: These parameter need to be passed down to the enumerator.",
"name": "__init__",
"signature": "def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None"
},
{
"docstring": "Apply the ... | 2 | stack_v2_sparse_classes_30k_train_004030 | Implement the Python class `Augment` described below.
Class description:
Augment a SMILES string, according to Bjerrum (2017).
Method signatures and docstrings:
- def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None: NOTE... | Implement the Python class `Augment` described below.
Class description:
Augment a SMILES string, according to Bjerrum (2017).
Method signatures and docstrings:
- def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None: NOTE... | 27ca3f8c5b5463cd081be5abdea04f5bfa076f39 | <|skeleton|>
class Augment:
"""Augment a SMILES string, according to Bjerrum (2017)."""
def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None:
"""NOTE: These parameter need to be passed down to the enumerato... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Augment:
"""Augment a SMILES string, according to Bjerrum (2017)."""
def __init__(self, kekule_smiles: bool=False, all_bonds_explicit: bool=False, all_hs_explicit: bool=False, sanitize: bool=True, seed: int=-1) -> None:
"""NOTE: These parameter need to be passed down to the enumerator."""
... | the_stack_v2_python_sparse | pytoda/smiles/transforms.py | PaccMann/paccmann_datasets | train | 22 |
a14a608257c4d48d58e96b617e3b1ba286c6296a | [
"try:\n attr_name = attr_name.lower()\n self.__getattribute__(attr_name)\nexcept AttributeError:\n try:\n attr_name = self.Attribute[attr_name.upper()].value\n self.__getattribute__(attr_name)\n except KeyError:\n raise AttributeError(f'No attribute \"{attr_name}\"')\nfor field in d... | <|body_start_0|>
try:
attr_name = attr_name.lower()
self.__getattribute__(attr_name)
except AttributeError:
try:
attr_name = self.Attribute[attr_name.upper()].value
self.__getattribute__(attr_name)
except KeyError:
... | Learner specific parameters | LearnerParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LearnerParams:
"""Learner specific parameters"""
def set_attr(self, attr_name: str, value: Union[int, float]) -> None:
"""Enhanced set attribute method that has enhanced checking"""
<|body_0|>
def get_attr(self, attr_name: str) -> Optional[Union[int, float]]:
"""... | stack_v2_sparse_classes_36k_train_008559 | 6,052 | permissive | [
{
"docstring": "Enhanced set attribute method that has enhanced checking",
"name": "set_attr",
"signature": "def set_attr(self, attr_name: str, value: Union[int, float]) -> None"
},
{
"docstring": "Attribute accessor with more robust handling of attribute name",
"name": "get_attr",
"sign... | 2 | stack_v2_sparse_classes_30k_train_005971 | Implement the Python class `LearnerParams` described below.
Class description:
Learner specific parameters
Method signatures and docstrings:
- def set_attr(self, attr_name: str, value: Union[int, float]) -> None: Enhanced set attribute method that has enhanced checking
- def get_attr(self, attr_name: str) -> Optional... | Implement the Python class `LearnerParams` described below.
Class description:
Learner specific parameters
Method signatures and docstrings:
- def set_attr(self, attr_name: str, value: Union[int, float]) -> None: Enhanced set attribute method that has enhanced checking
- def get_attr(self, attr_name: str) -> Optional... | bb11e9fceb2bcb22621ed1bd743858bfa5c2475e | <|skeleton|>
class LearnerParams:
"""Learner specific parameters"""
def set_attr(self, attr_name: str, value: Union[int, float]) -> None:
"""Enhanced set attribute method that has enhanced checking"""
<|body_0|>
def get_attr(self, attr_name: str) -> Optional[Union[int, float]]:
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LearnerParams:
"""Learner specific parameters"""
def set_attr(self, attr_name: str, value: Union[int, float]) -> None:
"""Enhanced set attribute method that has enhanced checking"""
try:
attr_name = attr_name.lower()
self.__getattribute__(attr_name)
except ... | the_stack_v2_python_sparse | src/apu/types.py | zhbfy/arbitrary_pu | train | 0 |
27438849b800c9fa65cba43b03818eb13c7d7d86 | [
"self._vectorizer = TfidfVectorizer(ngram_range=ngram_range, min_df=min_df, max_df=max_df, analyzer=analyzer.value)\nself._documents = documents\nself._index = self._vectorizer.fit_transform(map(text_getter, self._documents))",
"query_vector = self._vectorizer.transform([query])\nscores = zip(self._documents, sel... | <|body_start_0|>
self._vectorizer = TfidfVectorizer(ngram_range=ngram_range, min_df=min_df, max_df=max_df, analyzer=analyzer.value)
self._documents = documents
self._index = self._vectorizer.fit_transform(map(text_getter, self._documents))
<|end_body_0|>
<|body_start_1|>
query_vector = ... | A simple text index from a corpus of text using tf-idf similarity. | TextIndex | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and r... | stack_v2_sparse_classes_36k_train_008560 | 4,223 | permissive | [
{
"docstring": "Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and retrieved. text_getter: Function to extract text from documents. ngram_range: tuple (min_n, max_n), default=(1, 2) The lower and upper boundary of the range of n-values for different n-grams to be extracted. Al... | 2 | stack_v2_sparse_classes_30k_train_007763 | Implement the Python class `TextIndex` described below.
Class description:
A simple text index from a corpus of text using tf-idf similarity.
Method signatures and docstrings:
- def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9): Init parameters for TextIndex.... | Implement the Python class `TextIndex` described below.
Class description:
A simple text index from a corpus of text using tf-idf similarity.
Method signatures and docstrings:
- def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9): Init parameters for TextIndex.... | 569a3c31451d941165bd10783f73f494406b3906 | <|skeleton|>
class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextIndex:
"""A simple text index from a corpus of text using tf-idf similarity."""
def __init__(self, documents, text_getter, ngram_range=(1, 2), analyzer=Analyzer.WORD, min_df=1, max_df=0.9):
"""Init parameters for TextIndex. Args: documents: Corpus of documents to be indexed and retrieved. tex... | the_stack_v2_python_sparse | tapas/utils/text_index.py | google-research/tapas | train | 1,043 |
4ea8d5f89063d53d94eae68df1e35943c20ac8f4 | [
"if np.isscalar(times):\n t = np.asarray([times])\nelse:\n t = np.asarray(times)\nif np.isscalar(data):\n d = data * np.ones((t.size,))\nelse:\n d = np.asarray(data)\nreturn (d, t)",
"if len(data.shape) != 1:\n raise EquationException('{}: Invalid number of dimensions in prescribed scalar data. Exp... | <|body_start_0|>
if np.isscalar(times):
t = np.asarray([times])
else:
t = np.asarray(times)
if np.isscalar(data):
d = data * np.ones((t.size,))
else:
d = np.asarray(data)
return (d, t)
<|end_body_0|>
<|body_start_1|>
if len... | PrescribedScalarParameter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrescribedScalarParameter:
def _setScalarData(self, data, times=0):
"""Set prescribed scalar data appropriately."""
<|body_0|>
def _verifySettingsPrescribedScalarData(self, name, data, times):
"""Verify the structure of the prescribed data."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_008561 | 1,257 | permissive | [
{
"docstring": "Set prescribed scalar data appropriately.",
"name": "_setScalarData",
"signature": "def _setScalarData(self, data, times=0)"
},
{
"docstring": "Verify the structure of the prescribed data.",
"name": "_verifySettingsPrescribedScalarData",
"signature": "def _verifySettingsP... | 2 | stack_v2_sparse_classes_30k_train_010390 | Implement the Python class `PrescribedScalarParameter` described below.
Class description:
Implement the PrescribedScalarParameter class.
Method signatures and docstrings:
- def _setScalarData(self, data, times=0): Set prescribed scalar data appropriately.
- def _verifySettingsPrescribedScalarData(self, name, data, t... | Implement the Python class `PrescribedScalarParameter` described below.
Class description:
Implement the PrescribedScalarParameter class.
Method signatures and docstrings:
- def _setScalarData(self, data, times=0): Set prescribed scalar data appropriately.
- def _verifySettingsPrescribedScalarData(self, name, data, t... | eba9fabddfa4ef439737807ef30978a52ab55afb | <|skeleton|>
class PrescribedScalarParameter:
def _setScalarData(self, data, times=0):
"""Set prescribed scalar data appropriately."""
<|body_0|>
def _verifySettingsPrescribedScalarData(self, name, data, times):
"""Verify the structure of the prescribed data."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrescribedScalarParameter:
def _setScalarData(self, data, times=0):
"""Set prescribed scalar data appropriately."""
if np.isscalar(times):
t = np.asarray([times])
else:
t = np.asarray(times)
if np.isscalar(data):
d = data * np.ones((t.size,))... | the_stack_v2_python_sparse | py/DREAM/Settings/Equations/PrescribedScalarParameter.py | anymodel/DREAM-1 | train | 0 | |
8363b2b01ff97527f83427f0d277719d2a8ded3f | [
"super().__init__(productcode, description, marketprice, rentalprice)\nself.productcode = productcode\nself.description = description\nself.marketprice = marketprice\nself.rentalprice = rentalprice\nself.material = material\nself.size = size",
"outputdict = {}\noutputdict['productcode'] = self.productcode\noutput... | <|body_start_0|>
super().__init__(productcode, description, marketprice, rentalprice)
self.productcode = productcode
self.description = description
self.marketprice = marketprice
self.rentalprice = rentalprice
self.material = material
self.size = size
<|end_body_0... | Class for inventory | Furniture | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Furniture:
"""Class for inventory"""
def __init__(self, productcode, description, marketprice, rentalprice, material, size):
"""initializing variables"""
<|body_0|>
def returnasdictionary(self):
"""return as dictionary"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_008562 | 1,114 | no_license | [
{
"docstring": "initializing variables",
"name": "__init__",
"signature": "def __init__(self, productcode, description, marketprice, rentalprice, material, size)"
},
{
"docstring": "return as dictionary",
"name": "returnasdictionary",
"signature": "def returnasdictionary(self)"
}
] | 2 | null | Implement the Python class `Furniture` described below.
Class description:
Class for inventory
Method signatures and docstrings:
- def __init__(self, productcode, description, marketprice, rentalprice, material, size): initializing variables
- def returnasdictionary(self): return as dictionary | Implement the Python class `Furniture` described below.
Class description:
Class for inventory
Method signatures and docstrings:
- def __init__(self, productcode, description, marketprice, rentalprice, material, size): initializing variables
- def returnasdictionary(self): return as dictionary
<|skeleton|>
class Fur... | ac12beeae8aa57135bbcd03ac7a4f977fa3bdb56 | <|skeleton|>
class Furniture:
"""Class for inventory"""
def __init__(self, productcode, description, marketprice, rentalprice, material, size):
"""initializing variables"""
<|body_0|>
def returnasdictionary(self):
"""return as dictionary"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Furniture:
"""Class for inventory"""
def __init__(self, productcode, description, marketprice, rentalprice, material, size):
"""initializing variables"""
super().__init__(productcode, description, marketprice, rentalprice)
self.productcode = productcode
self.description = ... | the_stack_v2_python_sparse | students/Daniel_Carrasco/lesson01/assignment/inventory_management/furnitureClass.py | UWPCE-PythonCert-ClassRepos/py220-online-201904-V2 | train | 1 |
c50eb8e053f5134c8eb92a4d910d5fde5f459e8f | [
"Algorithm.__init__(self)\nself.name = 'Keep only largest connected component'\nself.parent = 'Graph filtering'",
"image, graph = args\nlargest = max(nx.connected_component_subgraphs(graph), key=len)\nself.result['img'] = largest\ntmp = self.draw_edges(image, largest)\ndrawn = self.draw_nodes(tmp, largest)\nself.... | <|body_start_0|>
Algorithm.__init__(self)
self.name = 'Keep only largest connected component'
self.parent = 'Graph filtering'
<|end_body_0|>
<|body_start_1|>
image, graph = args
largest = max(nx.connected_component_subgraphs(graph), key=len)
self.result['img'] = largest
... | Largest component filter implementation. | AlgBody | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlgBody:
"""Largest component filter implementation."""
def __init__(self):
"""Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category"""
<|body_0|>
def process(self, args):
"""Keep only largest connected component from nefi1... | stack_v2_sparse_classes_36k_train_008563 | 2,726 | no_license | [
{
"docstring": "Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Keep only largest connected component from nefi1. Args: | *args* : a list containing image array and Graph obje... | 4 | stack_v2_sparse_classes_30k_train_020758 | Implement the Python class `AlgBody` described below.
Class description:
Largest component filter implementation.
Method signatures and docstrings:
- def __init__(self): Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category
- def process(self, args): Keep only largest connected... | Implement the Python class `AlgBody` described below.
Class description:
Largest component filter implementation.
Method signatures and docstrings:
- def __init__(self): Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category
- def process(self, args): Keep only largest connected... | 0dc9becc09da22af3edac90b81b1dd9b1f44fd5b | <|skeleton|>
class AlgBody:
"""Largest component filter implementation."""
def __init__(self):
"""Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category"""
<|body_0|>
def process(self, args):
"""Keep only largest connected component from nefi1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlgBody:
"""Largest component filter implementation."""
def __init__(self):
"""Instance vars: | *name* : name of the algorithm | *parent* : name of the appropriate category"""
Algorithm.__init__(self)
self.name = 'Keep only largest connected component'
self.parent = 'Graph... | the_stack_v2_python_sparse | Andreas_Algorithms_Prototype/largest.py | andreasfirczynski/NetworkExtractionFromImages | train | 0 |
87169dbebcb456678f87a682a1488d299cf21901 | [
"self.pool_size = pool_size\nif self.pool_size > 0:\n self.num_imgs = 0\n self.images = []",
"if isinstance(images, Tensor):\n images = images.asnumpy()\nif self.pool_size == 0:\n return Tensor(images)\nreturn_images = []\nfor image in images:\n if self.num_imgs < self.pool_size:\n self.num_... | <|body_start_0|>
self.pool_size = pool_size
if self.pool_size > 0:
self.num_imgs = 0
self.images = []
<|end_body_0|>
<|body_start_1|>
if isinstance(images, Tensor):
images = images.asnumpy()
if self.pool_size == 0:
return Tensor(images)
... | This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators. | ImagePool | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImagePool:
"""This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators."""
def __init__(self, pool_size):
"""Initialize the... | stack_v2_sparse_classes_36k_train_008564 | 5,554 | permissive | [
{
"docstring": "Initialize the ImagePool class Args: pool_size (int): the size of image buffer, if pool_size=0, no buffer will be created.",
"name": "__init__",
"signature": "def __init__(self, pool_size)"
},
{
"docstring": "Return an image from the pool. Args: images: the latest generated image... | 2 | stack_v2_sparse_classes_30k_train_006591 | Implement the Python class `ImagePool` described below.
Class description:
This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators.
Method signatures and do... | Implement the Python class `ImagePool` described below.
Class description:
This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators.
Method signatures and do... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class ImagePool:
"""This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators."""
def __init__(self, pool_size):
"""Initialize the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImagePool:
"""This class implements an image buffer that stores previously generated images. This buffer enables us to update discriminators using a history of generated images rather than the ones produced by the latest generators."""
def __init__(self, pool_size):
"""Initialize the ImagePool cl... | the_stack_v2_python_sparse | official/cv/CycleGAN/src/utils/tools.py | mindspore-ai/models | train | 301 |
162369d9f0693db5465a5698f63851fb7f331427 | [
"self.idf_dict = idf_dict\nself.default_idf = default_idf\nself.word_list = word_list\nself.keyword_num = keyword_num\nself.tf_dict = self.get_tf_dict()",
"tf_dict = {}\nfor word in self.word_list:\n tf_dict[word] = tf_dict.get(word, 0.0) + 1.0\ntt_count = len(self.word_list)\nfor key, value in tf_dict.items()... | <|body_start_0|>
self.idf_dict = idf_dict
self.default_idf = default_idf
self.word_list = word_list
self.keyword_num = keyword_num
self.tf_dict = self.get_tf_dict()
<|end_body_0|>
<|body_start_1|>
tf_dict = {}
for word in self.word_list:
tf_dict[word]... | TfIdfModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TfIdfModel:
def __init__(self, idf_dict, default_idf, word_list, keyword_num):
"""[summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 keyword_num ([type]): 关键词数量"""
<|body_0|>
def get_tf_dict(self):
"""统计 TF 值 Retur... | stack_v2_sparse_classes_36k_train_008565 | 12,729 | no_license | [
{
"docstring": "[summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 keyword_num ([type]): 关键词数量",
"name": "__init__",
"signature": "def __init__(self, idf_dict, default_idf, word_list, keyword_num)"
},
{
"docstring": "统计 TF 值 Returns: [type]: [... | 3 | null | Implement the Python class `TfIdfModel` described below.
Class description:
Implement the TfIdfModel class.
Method signatures and docstrings:
- def __init__(self, idf_dict, default_idf, word_list, keyword_num): [summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 key... | Implement the Python class `TfIdfModel` described below.
Class description:
Implement the TfIdfModel class.
Method signatures and docstrings:
- def __init__(self, idf_dict, default_idf, word_list, keyword_num): [summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 key... | b1690cc6e487aff70e4c1fe9a98cd4d5b6557ce8 | <|skeleton|>
class TfIdfModel:
def __init__(self, idf_dict, default_idf, word_list, keyword_num):
"""[summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 keyword_num ([type]): 关键词数量"""
<|body_0|>
def get_tf_dict(self):
"""统计 TF 值 Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TfIdfModel:
def __init__(self, idf_dict, default_idf, word_list, keyword_num):
"""[summary] Args: idf_dict ([type]): 训练好的idf字典 default_idf ([type]): 默认idf值 word_list ([type]): 处理后的待提取文本 keyword_num ([type]): 关键词数量"""
self.idf_dict = idf_dict
self.default_idf = default_idf
self.... | the_stack_v2_python_sparse | src/src_nlp/keyword_extract/keyword_extract_demo.py | YanyiPU/deeplearning | train | 0 | |
87da29dba6340ec4955cc8c858e6108d0a19d6ed | [
"super(Summarization, self).__init__(**kwargs)\nself.d_model = d_model\nself.n_head = n_head\nself.d_head = d_head\nself.initializer = initializer\nself.dropout = dropout\nself.dropout_att = dropout_att\nself.use_proj = use_proj\nself.summary_type = summary_type",
"if self.use_proj:\n self.proj_layer = tf.kera... | <|body_start_0|>
super(Summarization, self).__init__(**kwargs)
self.d_model = d_model
self.n_head = n_head
self.d_head = d_head
self.initializer = initializer
self.dropout = dropout
self.dropout_att = dropout_att
self.use_proj = use_proj
self.summa... | The layer to pool the output from XLNet model into a vector. | Summarization | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Summarization:
"""The layer to pool the output from XLNet model into a vector."""
def __init__(self, d_model, n_head, d_head, dropout, dropout_att, initializer, use_proj=True, summary_type='last', **kwargs):
"""Constructs Summarization layer. Args: d_model: int, the dimension of mode... | stack_v2_sparse_classes_36k_train_008566 | 46,062 | permissive | [
{
"docstring": "Constructs Summarization layer. Args: d_model: int, the dimension of model hidden state. n_head: int, the number of attention heads. d_head: int, the dimension size of each attention head. dropout: float, dropout rate. dropout_att: float, dropout rate on attention probabilities. initializer: Ini... | 3 | stack_v2_sparse_classes_30k_train_017394 | Implement the Python class `Summarization` described below.
Class description:
The layer to pool the output from XLNet model into a vector.
Method signatures and docstrings:
- def __init__(self, d_model, n_head, d_head, dropout, dropout_att, initializer, use_proj=True, summary_type='last', **kwargs): Constructs Summa... | Implement the Python class `Summarization` described below.
Class description:
The layer to pool the output from XLNet model into a vector.
Method signatures and docstrings:
- def __init__(self, d_model, n_head, d_head, dropout, dropout_att, initializer, use_proj=True, summary_type='last', **kwargs): Constructs Summa... | a115d918f6894a69586174653172be0b5d1de952 | <|skeleton|>
class Summarization:
"""The layer to pool the output from XLNet model into a vector."""
def __init__(self, d_model, n_head, d_head, dropout, dropout_att, initializer, use_proj=True, summary_type='last', **kwargs):
"""Constructs Summarization layer. Args: d_model: int, the dimension of mode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Summarization:
"""The layer to pool the output from XLNet model into a vector."""
def __init__(self, d_model, n_head, d_head, dropout, dropout_att, initializer, use_proj=True, summary_type='last', **kwargs):
"""Constructs Summarization layer. Args: d_model: int, the dimension of model hidden stat... | the_stack_v2_python_sparse | models/official/nlp/xlnet/xlnet_modeling.py | finnickniu/tensorflow_object_detection_tflite | train | 60 |
3b29838a84dd7a58ad4eff9f29b9e99e1358b71f | [
"super().__init__()\nif nonlinear_activation:\n nonlinear_activation = nonlinear_activation.lower()\ninitialize(self, init_type)\nself.layers = nn.LayerList()\nassert len(kernel_sizes) == 2\nassert kernel_sizes[0] % 2 == 1\nassert kernel_sizes[1] % 2 == 1\nself.layers.append(nn.Sequential(getattr(nn, pad)((np.pr... | <|body_start_0|>
super().__init__()
if nonlinear_activation:
nonlinear_activation = nonlinear_activation.lower()
initialize(self, init_type)
self.layers = nn.LayerList()
assert len(kernel_sizes) == 2
assert kernel_sizes[0] % 2 == 1
assert kernel_sizes[... | MelGAN discriminator module. | MelGANDiscriminator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MelGANDiscriminator:
"""MelGAN discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, kernel_sizes: List[int]=[5, 3], channels: int=16, max_downsample_channels: int=1024, bias: bool=True, downsample_scales: List[int]=[4, 4, 4, 4], nonlinear_activation: str='leak... | stack_v2_sparse_classes_36k_train_008567 | 20,745 | permissive | [
{
"docstring": "Initilize MelGAN discriminator module. Args: in_channels (int): Number of input channels. out_channels (int): Number of output channels. kernel_sizes (List[int]): List of two kernel sizes. The prod will be used for the first conv layer, and the first and the second kernel sizes will be used for ... | 2 | null | Implement the Python class `MelGANDiscriminator` described below.
Class description:
MelGAN discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, kernel_sizes: List[int]=[5, 3], channels: int=16, max_downsample_channels: int=1024, bias: bool=True, downsa... | Implement the Python class `MelGANDiscriminator` described below.
Class description:
MelGAN discriminator module.
Method signatures and docstrings:
- def __init__(self, in_channels: int=1, out_channels: int=1, kernel_sizes: List[int]=[5, 3], channels: int=16, max_downsample_channels: int=1024, bias: bool=True, downsa... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class MelGANDiscriminator:
"""MelGAN discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, kernel_sizes: List[int]=[5, 3], channels: int=16, max_downsample_channels: int=1024, bias: bool=True, downsample_scales: List[int]=[4, 4, 4, 4], nonlinear_activation: str='leak... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MelGANDiscriminator:
"""MelGAN discriminator module."""
def __init__(self, in_channels: int=1, out_channels: int=1, kernel_sizes: List[int]=[5, 3], channels: int=16, max_downsample_channels: int=1024, bias: bool=True, downsample_scales: List[int]=[4, 4, 4, 4], nonlinear_activation: str='leakyrelu', nonli... | the_stack_v2_python_sparse | paddlespeech/t2s/models/melgan/melgan.py | anniyanvr/DeepSpeech-1 | train | 0 |
15ed22f7fffd066270fb8d0534cc859287a9c769 | [
"self.main_window = QtGui.QWidget()\nself.gui = Gui()\nself.gui.setupUi(self.main_window)\nself.gui.drawing_widget.mousePressEvent = self.mouse_press\nself.gui.drawing_widget.paintEvent = self.paint_event\nself.birds = []\nself.birds.append(Cardinal(random.randint(20, 600), random.randint(60, 400)))\nself.birds.app... | <|body_start_0|>
self.main_window = QtGui.QWidget()
self.gui = Gui()
self.gui.setupUi(self.main_window)
self.gui.drawing_widget.mousePressEvent = self.mouse_press
self.gui.drawing_widget.paintEvent = self.paint_event
self.birds = []
self.birds.append(Cardinal(rand... | Application class to create and control the gui. | App | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class App:
"""Application class to create and control the gui."""
def __init__(self):
"""Initialize the gui."""
<|body_0|>
def mouse_press(self, event):
"""Called automatically when the user presses the mouse button on the drawing widget. :param PyQt.QtGui.QMouseEvent ... | stack_v2_sparse_classes_36k_train_008568 | 13,878 | no_license | [
{
"docstring": "Initialize the gui.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Called automatically when the user presses the mouse button on the drawing widget. :param PyQt.QtGui.QMouseEvent event: The event object from PyQt. :return: None",
"name": "mouse_pr... | 4 | stack_v2_sparse_classes_30k_train_020914 | Implement the Python class `App` described below.
Class description:
Application class to create and control the gui.
Method signatures and docstrings:
- def __init__(self): Initialize the gui.
- def mouse_press(self, event): Called automatically when the user presses the mouse button on the drawing widget. :param Py... | Implement the Python class `App` described below.
Class description:
Application class to create and control the gui.
Method signatures and docstrings:
- def __init__(self): Initialize the gui.
- def mouse_press(self, event): Called automatically when the user presses the mouse button on the drawing widget. :param Py... | 0e3470085083012f893adb22aa46d46039016965 | <|skeleton|>
class App:
"""Application class to create and control the gui."""
def __init__(self):
"""Initialize the gui."""
<|body_0|>
def mouse_press(self, event):
"""Called automatically when the user presses the mouse button on the drawing widget. :param PyQt.QtGui.QMouseEvent ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class App:
"""Application class to create and control the gui."""
def __init__(self):
"""Initialize the gui."""
self.main_window = QtGui.QWidget()
self.gui = Gui()
self.gui.setupUi(self.main_window)
self.gui.drawing_widget.mousePressEvent = self.mouse_press
self.... | the_stack_v2_python_sparse | CS_210 (Introduction to Programming)/Labs/Lab34_AviaryApp.py | JacobOrner/USAFA | train | 0 |
c3f2afb1cec4f1fb11ad16ba472ebddf50d73508 | [
"self.key = 'sys_session_check'\nself.desc = _('Checks sessions so they are live.')\nself.interval = 60\nself.persistent = True",
"global _SESSIONS\nif not _SESSIONS:\n from src.server.sessionhandler import SESSIONS as _SESSIONS\n_SESSIONS.validate_sessions()"
] | <|body_start_0|>
self.key = 'sys_session_check'
self.desc = _('Checks sessions so they are live.')
self.interval = 60
self.persistent = True
<|end_body_0|>
<|body_start_1|>
global _SESSIONS
if not _SESSIONS:
from src.server.sessionhandler import SESSIONS as _... | Check sessions regularly. | CheckSessions | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckSessions:
"""Check sessions regularly."""
def at_script_creation(self):
"""Setup the script"""
<|body_0|>
def at_repeat(self):
"""called every 60 seconds"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.key = 'sys_session_check'
... | stack_v2_sparse_classes_36k_train_008569 | 17,327 | permissive | [
{
"docstring": "Setup the script",
"name": "at_script_creation",
"signature": "def at_script_creation(self)"
},
{
"docstring": "called every 60 seconds",
"name": "at_repeat",
"signature": "def at_repeat(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017350 | Implement the Python class `CheckSessions` described below.
Class description:
Check sessions regularly.
Method signatures and docstrings:
- def at_script_creation(self): Setup the script
- def at_repeat(self): called every 60 seconds | Implement the Python class `CheckSessions` described below.
Class description:
Check sessions regularly.
Method signatures and docstrings:
- def at_script_creation(self): Setup the script
- def at_repeat(self): called every 60 seconds
<|skeleton|>
class CheckSessions:
"""Check sessions regularly."""
def at_... | e8025abd5345b95fe7bee458d4dcf3a91e24602c | <|skeleton|>
class CheckSessions:
"""Check sessions regularly."""
def at_script_creation(self):
"""Setup the script"""
<|body_0|>
def at_repeat(self):
"""called every 60 seconds"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckSessions:
"""Check sessions regularly."""
def at_script_creation(self):
"""Setup the script"""
self.key = 'sys_session_check'
self.desc = _('Checks sessions so they are live.')
self.interval = 60
self.persistent = True
def at_repeat(self):
"""call... | the_stack_v2_python_sparse | src/scripts/scripts.py | Aumnren/evennia | train | 0 |
06a787cdda25d2773af420a6677b67dfd701745d | [
"self.data = data\nself.left = None\nself.right = None",
"if val < self.data:\n if self.left is None:\n self.left = Node(val)\n else:\n self.left.insert(val)\nif val > self.data:\n if self.right is None:\n self.right = Node(val)\n else:\n self.right.insert(val)",
"tree = ... | <|body_start_0|>
self.data = data
self.left = None
self.right = None
<|end_body_0|>
<|body_start_1|>
if val < self.data:
if self.left is None:
self.left = Node(val)
else:
self.left.insert(val)
if val > self.data:
... | Node | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Node:
def __init__(self, data):
"""Initialize Node data attributes."""
<|body_0|>
def insert(self, val):
"""Insert values to tree accordingly."""
<|body_1|>
def preorderTraversal(self, val):
"""Performs NLR traversal algorithm using recursion."""... | stack_v2_sparse_classes_36k_train_008570 | 1,606 | no_license | [
{
"docstring": "Initialize Node data attributes.",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Insert values to tree accordingly.",
"name": "insert",
"signature": "def insert(self, val)"
},
{
"docstring": "Performs NLR traversal algorithm using ... | 3 | stack_v2_sparse_classes_30k_train_001676 | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, data): Initialize Node data attributes.
- def insert(self, val): Insert values to tree accordingly.
- def preorderTraversal(self, val): Performs NLR traversal algorith... | Implement the Python class `Node` described below.
Class description:
Implement the Node class.
Method signatures and docstrings:
- def __init__(self, data): Initialize Node data attributes.
- def insert(self, val): Insert values to tree accordingly.
- def preorderTraversal(self, val): Performs NLR traversal algorith... | 9ad4b2ab8b6e1bf643534f61fe030ca56b094bde | <|skeleton|>
class Node:
def __init__(self, data):
"""Initialize Node data attributes."""
<|body_0|>
def insert(self, val):
"""Insert values to tree accordingly."""
<|body_1|>
def preorderTraversal(self, val):
"""Performs NLR traversal algorithm using recursion."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Node:
def __init__(self, data):
"""Initialize Node data attributes."""
self.data = data
self.left = None
self.right = None
def insert(self, val):
"""Insert values to tree accordingly."""
if val < self.data:
if self.left is None:
... | the_stack_v2_python_sparse | trees/tree traversals/preorder.py | gabrielleevaristo/algo-practice | train | 0 | |
5b04c9575c93733eae442c8a81cead6129515b36 | [
"if Database.__instance is None:\n Database()\nreturn Database.__instance",
"if Database.__instance is not None:\n raise Exception('This class is a singleton!')\nelse:\n Database.__instance = self\n self.connection = init_connection_engine()"
] | <|body_start_0|>
if Database.__instance is None:
Database()
return Database.__instance
<|end_body_0|>
<|body_start_1|>
if Database.__instance is not None:
raise Exception('This class is a singleton!')
else:
Database.__instance = self
self.... | Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance. | Database | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Database:
"""Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance."""
def get_instance():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private construct... | stack_v2_sparse_classes_36k_train_008571 | 5,624 | permissive | [
{
"docstring": "Static access method.",
"name": "get_instance",
"signature": "def get_instance()"
},
{
"docstring": "Virtually private constructor.",
"name": "__init__",
"signature": "def __init__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000812 | Implement the Python class `Database` described below.
Class description:
Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance.
Method signatures and docstrings:
- def get_instance(): Static access method.
- def __init__(self): Virtua... | Implement the Python class `Database` described below.
Class description:
Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance.
Method signatures and docstrings:
- def get_instance(): Static access method.
- def __init__(self): Virtua... | f47c6cce471d97104074d403ab9ec39a08276213 | <|skeleton|>
class Database:
"""Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance."""
def get_instance():
"""Static access method."""
<|body_0|>
def __init__(self):
"""Virtually private construct... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Database:
"""Singleton Database class to connect SQLServer. Database provides a connection to a remote SQLServer. Attributes: connection: db instance."""
def get_instance():
"""Static access method."""
if Database.__instance is None:
Database()
return Database.__instan... | the_stack_v2_python_sparse | util/database.py | ReadMoa/web-service | train | 0 |
fe8af5173828e5f2ba3eec3accdcd3de4d5ac61f | [
"self.filename = filename\nself.__outputFieldsCsv = copy.deepcopy(outputFieldsCsv)\nself.__headerFiedlNames = None\nself.__boolAddShapeFields = boolAddShapeFields\nself.__userFieldShapeMap = userFieldShapeMap\ntry:\n self.__log = log\n if self.__outputFieldsCsv is not None:\n with open(self.filename, '... | <|body_start_0|>
self.filename = filename
self.__outputFieldsCsv = copy.deepcopy(outputFieldsCsv)
self.__headerFiedlNames = None
self.__boolAddShapeFields = boolAddShapeFields
self.__userFieldShapeMap = userFieldShapeMap
try:
self.__log = log
if se... | API for write output CSV files write data output files | CSV_Writer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSV_Writer:
"""API for write output CSV files write data output files"""
def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None):
"""Constructor :param log: logger object :param filename: Work file name :param inputFields: Column header na... | stack_v2_sparse_classes_36k_train_008572 | 8,314 | permissive | [
{
"docstring": "Constructor :param log: logger object :param filename: Work file name :param inputFields: Column header names list for output file",
"name": "__init__",
"signature": "def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None)"
},
{
"docst... | 4 | stack_v2_sparse_classes_30k_train_011035 | Implement the Python class `CSV_Writer` described below.
Class description:
API for write output CSV files write data output files
Method signatures and docstrings:
- def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None): Constructor :param log: logger object :param file... | Implement the Python class `CSV_Writer` described below.
Class description:
API for write output CSV files write data output files
Method signatures and docstrings:
- def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None): Constructor :param log: logger object :param file... | 9764fcb86d3898b232c4cc333dab75ebe41cd421 | <|skeleton|>
class CSV_Writer:
"""API for write output CSV files write data output files"""
def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None):
"""Constructor :param log: logger object :param filename: Work file name :param inputFields: Column header na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSV_Writer:
"""API for write output CSV files write data output files"""
def __init__(self, log, filename, outputFieldsCsv, boolAddShapeFields=False, userFieldShapeMap=None):
"""Constructor :param log: logger object :param filename: Work file name :param inputFields: Column header names list for ... | the_stack_v2_python_sparse | PlanheatMappingModule/PlanHeatDMM/manageCsv/csv_writer.py | Planheat/Planheat-Tool | train | 2 |
a4d9f9fc3acf8095df6ead79c1c8113adc09d09b | [
"line = 'hello world, this is some téśt data!'\nmember = chrome_app.apis.api_member_used(line)\nself.assertIsNone(member)\nline = 'hello world, this is some téśt data!'\nmember = chrome_app.apis.api_member_used(line)\nself.assertIsNone(member)",
"line = 'hello world, this test data uses chrome.tts.speak, test tes... | <|body_start_0|>
line = 'hello world, this is some téśt data!'
member = chrome_app.apis.api_member_used(line)
self.assertIsNone(member)
line = 'hello world, this is some téśt data!'
member = chrome_app.apis.api_member_used(line)
self.assertIsNone(member)
<|end_body_0|>
<... | Tests api_member_used. | TestApiMemberUsed | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestApiMemberUsed:
"""Tests api_member_used."""
def test_no_member(self):
"""Tests that if there is no member, None is returned."""
<|body_0|>
def test_api_member(self):
"""Tests that a member is picked up in the input string."""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k_train_008573 | 3,679 | permissive | [
{
"docstring": "Tests that if there is no member, None is returned.",
"name": "test_no_member",
"signature": "def test_no_member(self)"
},
{
"docstring": "Tests that a member is picked up in the input string.",
"name": "test_api_member",
"signature": "def test_api_member(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_017365 | Implement the Python class `TestApiMemberUsed` described below.
Class description:
Tests api_member_used.
Method signatures and docstrings:
- def test_no_member(self): Tests that if there is no member, None is returned.
- def test_api_member(self): Tests that a member is picked up in the input string.
- def test_chro... | Implement the Python class `TestApiMemberUsed` described below.
Class description:
Tests api_member_used.
Method signatures and docstrings:
- def test_no_member(self): Tests that if there is no member, None is returned.
- def test_api_member(self): Tests that a member is picked up in the input string.
- def test_chro... | 985419af32f9bbd3abc934db3edc09523477118a | <|skeleton|>
class TestApiMemberUsed:
"""Tests api_member_used."""
def test_no_member(self):
"""Tests that if there is no member, None is returned."""
<|body_0|>
def test_api_member(self):
"""Tests that a member is picked up in the input string."""
<|body_1|>
def test_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestApiMemberUsed:
"""Tests api_member_used."""
def test_no_member(self):
"""Tests that if there is no member, None is returned."""
line = 'hello world, this is some téśt data!'
member = chrome_app.apis.api_member_used(line)
self.assertIsNone(member)
line = 'hello ... | the_stack_v2_python_sparse | src/chrome_app/apis_test.py | HoeDetector/caterpillar | train | 0 |
8711cacd47e4ec61718a1afe5a736b487d2e7a1d | [
"self.host = host\nif user:\n self._auth = HTTPBasicAuth(user, password)\nelse:\n self._auth = None\nself.dam = Assets(self)",
"try:\n url = self.host + path\n logging.debug('URL - ' + url)\n result = requests.get(url, auth=self._auth)\n logging.debug('Response from the URL : ' + str(result))\n ... | <|body_start_0|>
self.host = host
if user:
self._auth = HTTPBasicAuth(user, password)
else:
self._auth = None
self.dam = Assets(self)
<|end_body_0|>
<|body_start_1|>
try:
url = self.host + path
logging.debug('URL - ' + url)
... | Connects to and performs the get and post operations on the connected AEM instance | Connector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Connector:
"""Connects to and performs the get and post operations on the connected AEM instance"""
def __init__(self, host, user, password):
"""Initialize connection to the host with given user and password"""
<|body_0|>
def rawget(self, path):
"""Performs a get... | stack_v2_sparse_classes_36k_train_008574 | 3,242 | permissive | [
{
"docstring": "Initialize connection to the host with given user and password",
"name": "__init__",
"signature": "def __init__(self, host, user, password)"
},
{
"docstring": "Performs a get operation to the path and returns the raw response as-is",
"name": "rawget",
"signature": "def ra... | 5 | stack_v2_sparse_classes_30k_train_000507 | Implement the Python class `Connector` described below.
Class description:
Connects to and performs the get and post operations on the connected AEM instance
Method signatures and docstrings:
- def __init__(self, host, user, password): Initialize connection to the host with given user and password
- def rawget(self, ... | Implement the Python class `Connector` described below.
Class description:
Connects to and performs the get and post operations on the connected AEM instance
Method signatures and docstrings:
- def __init__(self, host, user, password): Initialize connection to the host with given user and password
- def rawget(self, ... | 432d802f62da95eaa630cae651dabba56d50029c | <|skeleton|>
class Connector:
"""Connects to and performs the get and post operations on the connected AEM instance"""
def __init__(self, host, user, password):
"""Initialize connection to the host with given user and password"""
<|body_0|>
def rawget(self, path):
"""Performs a get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Connector:
"""Connects to and performs the get and post operations on the connected AEM instance"""
def __init__(self, host, user, password):
"""Initialize connection to the host with given user and password"""
self.host = host
if user:
self._auth = HTTPBasicAuth(user,... | the_stack_v2_python_sparse | dampy/lib/Connector.py | moonraker46/dampy | train | 0 |
10259174f6d2eae2f4d8eb8747ba893fdca27cc0 | [
"self.is_lambda_based_g_c_enabled = is_lambda_based_g_c_enabled\nself.access_key_id = access_key_id\nself.auth_method = auth_method\nself.c_2_s_access_portal = c_2_s_access_portal\nself.credential_blob = credential_blob\nself.credential_endpoint = credential_endpoint\nself.iam_role_arn = iam_role_arn\nself.read_onl... | <|body_start_0|>
self.is_lambda_based_g_c_enabled = is_lambda_based_g_c_enabled
self.access_key_id = access_key_id
self.auth_method = auth_method
self.c_2_s_access_portal = c_2_s_access_portal
self.credential_blob = credential_blob
self.credential_endpoint = credential_en... | Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled (bool): Specifies whether this vault supports AWS Lambda based GC. A Lambda function need... | AmazonCloudCredentials | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AmazonCloudCredentials:
"""Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled (bool): Specifies whether this vault su... | stack_v2_sparse_classes_36k_train_008575 | 9,393 | permissive | [
{
"docstring": "Constructor for the AmazonCloudCredentials class",
"name": "__init__",
"signature": "def __init__(self, is_lambda_based_g_c_enabled=None, access_key_id=None, auth_method=None, c_2_s_access_portal=None, credential_blob=None, credential_endpoint=None, iam_role_arn=None, read_only_iam_role_... | 2 | null | Implement the Python class `AmazonCloudCredentials` described below.
Class description:
Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled ... | Implement the Python class `AmazonCloudCredentials` described below.
Class description:
Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class AmazonCloudCredentials:
"""Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled (bool): Specifies whether this vault su... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AmazonCloudCredentials:
"""Implementation of the 'AmazonCloudCredentials' model. Specifies the cloud credentials to connect to a Amazon service account. Glacier, S3, and S3-compatible clouds all use these credentials. Attributes: is_lambda_based_g_c_enabled (bool): Specifies whether this vault supports AWS La... | the_stack_v2_python_sparse | cohesity_management_sdk/models/amazon_cloud_credentials.py | cohesity/management-sdk-python | train | 24 |
1a16784ef4c043c8cd21240f66dae8ecb512ebc3 | [
"client = Client.objects.filter(pk=self.kwargs.get('client_pk')).filter(organization=self.request.user.organization).first()\nif client is None:\n raise NotFound()\nreturn client",
"campaign = client.campaign_set.filter(pk=self.kwargs['campaign_pk']).first()\nif campaign is None:\n raise NotFound()\nreturn ... | <|body_start_0|>
client = Client.objects.filter(pk=self.kwargs.get('client_pk')).filter(organization=self.request.user.organization).first()
if client is None:
raise NotFound()
return client
<|end_body_0|>
<|body_start_1|>
campaign = client.campaign_set.filter(pk=self.kwargs... | Checks that user has access to client for viewsets that depend on client_pk url | ClientAccessMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClientAccessMixin:
"""Checks that user has access to client for viewsets that depend on client_pk url"""
def _check_client_access(self):
"""Make sure client exists and belongs to the same organization"""
<|body_0|>
def _check_campaign_access(self, client):
"""Mak... | stack_v2_sparse_classes_36k_train_008576 | 6,187 | no_license | [
{
"docstring": "Make sure client exists and belongs to the same organization",
"name": "_check_client_access",
"signature": "def _check_client_access(self)"
},
{
"docstring": "Make sure campaign belongs to client",
"name": "_check_campaign_access",
"signature": "def _check_campaign_acces... | 3 | stack_v2_sparse_classes_30k_train_020268 | Implement the Python class `ClientAccessMixin` described below.
Class description:
Checks that user has access to client for viewsets that depend on client_pk url
Method signatures and docstrings:
- def _check_client_access(self): Make sure client exists and belongs to the same organization
- def _check_campaign_acce... | Implement the Python class `ClientAccessMixin` described below.
Class description:
Checks that user has access to client for viewsets that depend on client_pk url
Method signatures and docstrings:
- def _check_client_access(self): Make sure client exists and belongs to the same organization
- def _check_campaign_acce... | 4a66bc3d516f8116c20aa11399f25e618e74f06e | <|skeleton|>
class ClientAccessMixin:
"""Checks that user has access to client for viewsets that depend on client_pk url"""
def _check_client_access(self):
"""Make sure client exists and belongs to the same organization"""
<|body_0|>
def _check_campaign_access(self, client):
"""Mak... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClientAccessMixin:
"""Checks that user has access to client for viewsets that depend on client_pk url"""
def _check_client_access(self):
"""Make sure client exists and belongs to the same organization"""
client = Client.objects.filter(pk=self.kwargs.get('client_pk')).filter(organization=s... | the_stack_v2_python_sparse | clients/views.py | magloirend/budget_tracker | train | 0 |
3498d556b10af91a07b7551e2c2947717e1eac27 | [
"self.reward = reward\nself.nb_arms = nb_arms\nself.pattern = pattern\nself.terminate_on_win = terminate_on_win\nassert len(self.pattern) > 0, 'Pattern cannot be empty.'\nassert min(self.pattern) >= 0, 'Negative values in patterns not allowed.'\nassert max(self.pattern) < self.nb_arms, 'Values greater than the numb... | <|body_start_0|>
self.reward = reward
self.nb_arms = nb_arms
self.pattern = pattern
self.terminate_on_win = terminate_on_win
assert len(self.pattern) > 0, 'Pattern cannot be empty.'
assert min(self.pattern) >= 0, 'Negative values in patterns not allowed.'
assert m... | A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic. | CheatMAB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheatMAB:
"""A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic."""
def __init__(self, nb_arms: int... | stack_v2_sparse_classes_36k_train_008577 | 3,255 | no_license | [
{
"docstring": "Initialize a sequential MAB. :param nb_arms: the number of arms. :param pattern: the pattern to perform in order to give a reward. :param reward: the reward. :param terminate_on_win: whether the episode should terminate when the pattern is matched.",
"name": "__init__",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_014064 | Implement the Python class `CheatMAB` described below.
Class description:
A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic.
... | Implement the Python class `CheatMAB` described below.
Class description:
A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic.
... | b516ffa46e9df6a67fbda7546f9128c23920c460 | <|skeleton|>
class CheatMAB:
"""A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic."""
def __init__(self, nb_arms: int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheatMAB:
"""A variant of the classic MAB. There exists a sequence of actions s.t. after performing that sequence, all actions lead to a reward with probability 1 from that point on. E.g. pull arm 1 three times, then pull arm 3. The reward is deterministic."""
def __init__(self, nb_arms: int, pattern: Se... | the_stack_v2_python_sparse | src/envs/cheat_mab.py | marcofavorito/PAC-RDPs-code | train | 2 |
bd471540f6e90add42c640a93b189e88990f311a | [
"to_datetime = lambda x: {'dateTime': self.__class__.strftime(x)}\nto_visibility = lambda x: 'public' if x == 'public' else 'private'\nto_source = lambda x: {'url': get_base_url() + x()}\nto_attendees = lambda x: [dict(email=a.email, displayName=a.nickname) for a in x.iterator()]\ntranslation_table = (('summary', '... | <|body_start_0|>
to_datetime = lambda x: {'dateTime': self.__class__.strftime(x)}
to_visibility = lambda x: 'public' if x == 'public' else 'private'
to_source = lambda x: {'url': get_base_url() + x()}
to_attendees = lambda x: [dict(email=a.email, displayName=a.nickname) for a in x.iterat... | KawazGoogleCalendarBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KawazGoogleCalendarBackend:
def translate(self, event):
"""Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] パラメーター"""
<|body_0|>
def is_valid(self, event, raise_exception=False):
"""Kawaz3のEventモデルインスタン... | stack_v2_sparse_classes_36k_train_008578 | 2,550 | no_license | [
{
"docstring": "Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] パラメーター",
"name": "translate",
"signature": "def translate(self, event)"
},
{
"docstring": "Kawaz3のEventモデルインスタンスが、Google Calendar API Version3の Bodyパラメーターと適合しているかをチェッ... | 2 | null | Implement the Python class `KawazGoogleCalendarBackend` described below.
Class description:
Implement the KawazGoogleCalendarBackend class.
Method signatures and docstrings:
- def translate(self, event): Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] ... | Implement the Python class `KawazGoogleCalendarBackend` described below.
Class description:
Implement the KawazGoogleCalendarBackend class.
Method signatures and docstrings:
- def translate(self, event): Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] ... | 8f9a850c4df41b0fc1da5b73189772552d5cd531 | <|skeleton|>
class KawazGoogleCalendarBackend:
def translate(self, event):
"""Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] パラメーター"""
<|body_0|>
def is_valid(self, event, raise_exception=False):
"""Kawaz3のEventモデルインスタン... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KawazGoogleCalendarBackend:
def translate(self, event):
"""Kawaz3のEventモデルをGoogle Calendar API Version3のBodyパラメーターに変換します Params: event [Event] Eventモデルインスタンス Return: [dict] パラメーター"""
to_datetime = lambda x: {'dateTime': self.__class__.strftime(x)}
to_visibility = lambda x: 'public' if ... | the_stack_v2_python_sparse | src/kawaz/apps/events/gcal.py | kawazrepos/Kawaz3rd | train | 7 | |
89f67c60f1b50e0e4a876628b0231090c038f511 | [
"if n == 0 or n == 1:\n return 1\nelse:\n return self.climbStairs(n - 1) + self.climbStairs(n - 2)",
"if n == 0 or n == 1:\n return 1\nelse:\n dp = [0] * (n + 1)\n dp[0] = 1\n dp[1] = 1\n for i in range(2, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2]\n return dp[-1]",
"if n == 0 or n =... | <|body_start_0|>
if n == 0 or n == 1:
return 1
else:
return self.climbStairs(n - 1) + self.climbStairs(n - 2)
<|end_body_0|>
<|body_start_1|>
if n == 0 or n == 1:
return 1
else:
dp = [0] * (n + 1)
dp[0] = 1
dp[1] = ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""Time: N/A Time limit exceeded Mem: N/A ^"""
<|body_0|>
def climbStairs(self, n):
"""Time: 24ms (96.94%) Mem: 12.7 MB (100%)"""
<|body_1|>
def climbStairs(self, n):
"""Time: 28ms (90.99%) Mem: 12.... | stack_v2_sparse_classes_36k_train_008579 | 1,874 | no_license | [
{
"docstring": "Time: N/A Time limit exceeded Mem: N/A ^",
"name": "climbStairs",
"signature": "def climbStairs(self, n: int) -> int"
},
{
"docstring": "Time: 24ms (96.94%) Mem: 12.7 MB (100%)",
"name": "climbStairs",
"signature": "def climbStairs(self, n)"
},
{
"docstring": "Tim... | 3 | stack_v2_sparse_classes_30k_train_018791 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: Time: N/A Time limit exceeded Mem: N/A ^
- def climbStairs(self, n): Time: 24ms (96.94%) Mem: 12.7 MB (100%)
- def climbStairs(self, n): Tim... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def climbStairs(self, n: int) -> int: Time: N/A Time limit exceeded Mem: N/A ^
- def climbStairs(self, n): Time: 24ms (96.94%) Mem: 12.7 MB (100%)
- def climbStairs(self, n): Tim... | 5a40f53602d3a5f4d5478ac6ea2b41f3272420db | <|skeleton|>
class Solution:
def climbStairs(self, n: int) -> int:
"""Time: N/A Time limit exceeded Mem: N/A ^"""
<|body_0|>
def climbStairs(self, n):
"""Time: 24ms (96.94%) Mem: 12.7 MB (100%)"""
<|body_1|>
def climbStairs(self, n):
"""Time: 28ms (90.99%) Mem: 12.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def climbStairs(self, n: int) -> int:
"""Time: N/A Time limit exceeded Mem: N/A ^"""
if n == 0 or n == 1:
return 1
else:
return self.climbStairs(n - 1) + self.climbStairs(n - 2)
def climbStairs(self, n):
"""Time: 24ms (96.94%) Mem: 12.7 MB... | the_stack_v2_python_sparse | coding-problems/leetcode/recursion/climb_stairs.py | BaoAdrian/interview-prep | train | 0 | |
4847c9905587193f73d90e010c479bfac08bafff | [
"try:\n session = async_get_clientsession(hass)\n cloud_api_client = cloud_loqed.CloudAPIClient(session, data[CONF_API_TOKEN])\n cloud_client = cloud_loqed.LoqedCloudAPI(cloud_api_client)\n lock_data = await cloud_client.async_get_locks()\nexcept aiohttp.ClientError as err:\n _LOGGER.error('HTTP Conn... | <|body_start_0|>
try:
session = async_get_clientsession(hass)
cloud_api_client = cloud_loqed.CloudAPIClient(session, data[CONF_API_TOKEN])
cloud_client = cloud_loqed.LoqedCloudAPI(cloud_api_client)
lock_data = await cloud_client.async_get_locks()
except ai... | Handle a config flow for Loqed. | ConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Loqed."""
async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]:
"""Validate the user input allows us to connect."""
<|body_0|>
async def async_step_zeroconf(self, discovery_info: ZeroconfServi... | stack_v2_sparse_classes_36k_train_008580 | 5,680 | permissive | [
{
"docstring": "Validate the user input allows us to connect.",
"name": "validate_input",
"signature": "async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]"
},
{
"docstring": "Handle zeroconf discovery.",
"name": "async_step_zeroconf",
"signature":... | 3 | null | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Loqed.
Method signatures and docstrings:
- async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]: Validate the user input allows us to connect.
- async def async_step_zeroconf(sel... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Loqed.
Method signatures and docstrings:
- async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]: Validate the user input allows us to connect.
- async def async_step_zeroconf(sel... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Loqed."""
async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]:
"""Validate the user input allows us to connect."""
<|body_0|>
async def async_step_zeroconf(self, discovery_info: ZeroconfServi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfigFlow:
"""Handle a config flow for Loqed."""
async def validate_input(self, hass: HomeAssistant, data: dict[str, Any]) -> dict[str, Any]:
"""Validate the user input allows us to connect."""
try:
session = async_get_clientsession(hass)
cloud_api_client = cloud_... | the_stack_v2_python_sparse | homeassistant/components/loqed/config_flow.py | home-assistant/core | train | 35,501 |
476a3243b4d74a3f3b22c5def18ee7ee96910301 | [
"self.x_procedure_created = True\nfor line in self.order_line:\n print(line.product_id)\n if line.product_id.is_procedure():\n product_product = line.product_id\n pl_creates.create_procedure(treatment, product_product)",
"print()\nprint('order - proc_is_not_created_and_state_is_sale')\nreturn ... | <|body_start_0|>
self.x_procedure_created = True
for line in self.order_line:
print(line.product_id)
if line.product_id.is_procedure():
product_product = line.product_id
pl_creates.create_procedure(treatment, product_product)
<|end_body_0|>
<|body... | Order controller. Directs flow between Order and other models (Treatment). | OrderBl | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderBl:
"""Order controller. Directs flow between Order and other models (Treatment)."""
def create_procedure_man(self, treatment):
"""Create Procedure Man - In prog Used by: Treatment"""
<|body_0|>
def proc_is_not_created_and_state_is_sale(self):
"""Used by: Tr... | stack_v2_sparse_classes_36k_train_008581 | 2,116 | no_license | [
{
"docstring": "Create Procedure Man - In prog Used by: Treatment",
"name": "create_procedure_man",
"signature": "def create_procedure_man(self, treatment)"
},
{
"docstring": "Used by: Treatment",
"name": "proc_is_not_created_and_state_is_sale",
"signature": "def proc_is_not_created_and_... | 5 | null | Implement the Python class `OrderBl` described below.
Class description:
Order controller. Directs flow between Order and other models (Treatment).
Method signatures and docstrings:
- def create_procedure_man(self, treatment): Create Procedure Man - In prog Used by: Treatment
- def proc_is_not_created_and_state_is_sa... | Implement the Python class `OrderBl` described below.
Class description:
Order controller. Directs flow between Order and other models (Treatment).
Method signatures and docstrings:
- def create_procedure_man(self, treatment): Create Procedure Man - In prog Used by: Treatment
- def proc_is_not_created_and_state_is_sa... | c15f8b146392d47a9040404a4ac8e45a1b062198 | <|skeleton|>
class OrderBl:
"""Order controller. Directs flow between Order and other models (Treatment)."""
def create_procedure_man(self, treatment):
"""Create Procedure Man - In prog Used by: Treatment"""
<|body_0|>
def proc_is_not_created_and_state_is_sale(self):
"""Used by: Tr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderBl:
"""Order controller. Directs flow between Order and other models (Treatment)."""
def create_procedure_man(self, treatment):
"""Create Procedure Man - In prog Used by: Treatment"""
self.x_procedure_created = True
for line in self.order_line:
print(line.product_... | the_stack_v2_python_sparse | models/order/order_controller.py | gibil5/openhealth | train | 1 |
d208ca4db22c8cf8466a505e4ff0d86271a9748e | [
"location_node = xml_root.find(INPUT)\nnames = [OBJ_NAME, REG_SIZE]\nxml_nodes = self.node_dict(names, location_node)\nself._dust_nodes = [CoordNode(xml_nodes[OBJ_NAME], col_names=['RA', 'Dec', 'coord sys']), NumberNode(xml_nodes[REG_SIZE], REG_SIZE, units=u.deg)]\nself.create_columns()",
"base_string = BaseResul... | <|body_start_0|>
location_node = xml_root.find(INPUT)
names = [OBJ_NAME, REG_SIZE]
xml_nodes = self.node_dict(names, location_node)
self._dust_nodes = [CoordNode(xml_nodes[OBJ_NAME], col_names=['RA', 'Dec', 'coord sys']), NumberNode(xml_nodes[REG_SIZE], REG_SIZE, units=u.deg)]
se... | The location section of the DustResults object. | LocationSection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocationSection:
"""The location section of the DustResults object."""
def __init__(self, xml_root):
"""Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides"""
<|body_0|>
def __str__(self):
"""Return a stri... | stack_v2_sparse_classes_36k_train_008582 | 41,056 | permissive | [
{
"docstring": "Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides",
"name": "__init__",
"signature": "def __init__(self, xml_root)"
},
{
"docstring": "Return a string representation of the section.",
"name": "__str__",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_008949 | Implement the Python class `LocationSection` described below.
Class description:
The location section of the DustResults object.
Method signatures and docstrings:
- def __init__(self, xml_root): Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides
- def __str__... | Implement the Python class `LocationSection` described below.
Class description:
The location section of the DustResults object.
Method signatures and docstrings:
- def __init__(self, xml_root): Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides
- def __str__... | 51316d7417d7daf01a8b29d1df99037b9227c2bc | <|skeleton|>
class LocationSection:
"""The location section of the DustResults object."""
def __init__(self, xml_root):
"""Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides"""
<|body_0|>
def __str__(self):
"""Return a stri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocationSection:
"""The location section of the DustResults object."""
def __init__(self, xml_root):
"""Parameters ---------- xml_root : `xml.etree.ElementTree` the xml tree where the data for this section resides"""
location_node = xml_root.find(INPUT)
names = [OBJ_NAME, REG_SIZE... | the_stack_v2_python_sparse | astroquery/ipac/irsa/irsa_dust/core.py | astropy/astroquery | train | 636 |
99f6b8338f9990d97be47923bae154e1bdd79abf | [
"self.__vc = virtual_coach.VirtualCoach('local', storage_username='demo', storage_password='demo')\nself.__experiments_list = {}\nself.__last_status = [None]\nself.__launched = False\nself.__sim = None\nexperiments_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'experiments_list.json')\nif not os.... | <|body_start_0|>
self.__vc = virtual_coach.VirtualCoach('local', storage_username='demo', storage_password='demo')
self.__experiments_list = {}
self.__last_status = [None]
self.__launched = False
self.__sim = None
experiments_path = os.path.join(os.path.dirname(os.path.re... | This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json | ExperimentsLauncher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExperimentsLauncher:
"""This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json"""
def __init__(self):
"""In the constructor we instantiate a VC, and read the list of experi... | stack_v2_sparse_classes_36k_train_008583 | 5,296 | no_license | [
{
"docstring": "In the constructor we instantiate a VC, and read the list of experiments from the experiments_list.json",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "\" Helper method that is specified as the callback function whenever we have a status change. By defa... | 4 | null | Implement the Python class `ExperimentsLauncher` described below.
Class description:
This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json
Method signatures and docstrings:
- def __init__(self): In the con... | Implement the Python class `ExperimentsLauncher` described below.
Class description:
This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json
Method signatures and docstrings:
- def __init__(self): In the con... | e4d22da4488aacd727d9f520b40fba2230bea113 | <|skeleton|>
class ExperimentsLauncher:
"""This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json"""
def __init__(self):
"""In the constructor we instantiate a VC, and read the list of experi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExperimentsLauncher:
"""This class contains an instance of the virtual coach, and exposes a single function to run continuously the list of experiments contained in the experiments_list.json"""
def __init__(self):
"""In the constructor we instantiate a VC, and read the list of experiments from th... | the_stack_v2_python_sparse | demo_carousel/experiments_launcher.py | HBPNeurorobotics/Experiments | train | 1 |
8e9154c5b89ffbcfef759af6b028819fee440ae3 | [
"self.mNormal = normal.normalized()\nself.mDistance = dvalue\nself.mColor = color",
"if self.mNormal.dot(ray.mDirection) == 0:\n return None\nt = (self.mDistance - ray.mOrigin.dot(self.mNormal)) / self.mNormal.dot(ray.mDirection)\nif t < 0:\n return None\nelse:\n return rayHit(t, self.mNormal, ray, self)... | <|body_start_0|>
self.mNormal = normal.normalized()
self.mDistance = dvalue
self.mColor = color
<|end_body_0|>
<|body_start_1|>
if self.mNormal.dot(ray.mDirection) == 0:
return None
t = (self.mDistance - ray.mOrigin.dot(self.mNormal)) / self.mNormal.dot(ray.mDirectio... | Creates a plane object | Plane | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Plane:
"""Creates a plane object"""
def __init__(self, normal, dvalue, color):
"""creates the plane"""
<|body_0|>
def rayIntersection(self, ray):
"""Returns the distance from the intersection of the ray and the object"""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_008584 | 7,372 | no_license | [
{
"docstring": "creates the plane",
"name": "__init__",
"signature": "def __init__(self, normal, dvalue, color)"
},
{
"docstring": "Returns the distance from the intersection of the ray and the object",
"name": "rayIntersection",
"signature": "def rayIntersection(self, ray)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004863 | Implement the Python class `Plane` described below.
Class description:
Creates a plane object
Method signatures and docstrings:
- def __init__(self, normal, dvalue, color): creates the plane
- def rayIntersection(self, ray): Returns the distance from the intersection of the ray and the object | Implement the Python class `Plane` described below.
Class description:
Creates a plane object
Method signatures and docstrings:
- def __init__(self, normal, dvalue, color): creates the plane
- def rayIntersection(self, ray): Returns the distance from the intersection of the ray and the object
<|skeleton|>
class Plan... | 95fc6bcdad6e61abb469c5025b9b3c9edafab8fc | <|skeleton|>
class Plane:
"""Creates a plane object"""
def __init__(self, normal, dvalue, color):
"""creates the plane"""
<|body_0|>
def rayIntersection(self, ray):
"""Returns the distance from the intersection of the ray and the object"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Plane:
"""Creates a plane object"""
def __init__(self, normal, dvalue, color):
"""creates the plane"""
self.mNormal = normal.normalized()
self.mDistance = dvalue
self.mColor = color
def rayIntersection(self, ray):
"""Returns the distance from the intersection ... | the_stack_v2_python_sparse | Raytracer/objects3d.py | TylermEvans/Portfolio | train | 1 |
2bde7d6856a12976001b0a381f406e072370b56e | [
"Parametre.__init__(self, 'supprimer', 'del')\nself.schema = '<groupe1:groupe_existant> <groupe2:groupe_existant>'\nself.aide_courte = 'supprime un groupe inclus'\nself.aide_longue = 'Cette commande permet de supprimer un groupe inclus. Le premier groupe à entrer est celui dans lequel on doit supprimer le second gr... | <|body_start_0|>
Parametre.__init__(self, 'supprimer', 'del')
self.schema = '<groupe1:groupe_existant> <groupe2:groupe_existant>'
self.aide_courte = 'supprime un groupe inclus'
self.aide_longue = 'Cette commande permet de supprimer un groupe inclus. Le premier groupe à entrer est celui d... | Commande 'groupe inclus ajouter'. | PrmInclusSupprimer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmInclusSupprimer:
"""Commande 'groupe inclus ajouter'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008585 | 3,321 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmInclusSupprimer` described below.
Class description:
Commande 'groupe inclus ajouter'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmInclusSupprimer` described below.
Class description:
Commande 'groupe inclus ajouter'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmInclusSupprimer:
... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmInclusSupprimer:
"""Commande 'groupe inclus ajouter'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmInclusSupprimer:
"""Commande 'groupe inclus ajouter'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'supprimer', 'del')
self.schema = '<groupe1:groupe_existant> <groupe2:groupe_existant>'
self.aide_courte = 'supprime un groupe inclus'
... | the_stack_v2_python_sparse | src/primaires/joueur/commandes/groupe/inclus_supprimer.py | vincent-lg/tsunami | train | 5 |
bc94add4f8676af81e87e1f15f5efc53de58a542 | [
"if data is None:\n if lambtha < 1:\n raise ValueError('lambtha must be a positive value')\n else:\n self.lambtha = float(lambtha)\nelif type(data) is not list:\n raise TypeError('data must be a list')\nelif len(data) < 2:\n raise ValueError('data must contain multiple values')\nelse:\n ... | <|body_start_0|>
if data is None:
if lambtha < 1:
raise ValueError('lambtha must be a positive value')
else:
self.lambtha = float(lambtha)
elif type(data) is not list:
raise TypeError('data must be a list')
elif len(data) < 2:
... | class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for given number of successes def cdf(self, k): calculates CDF for given numb... | Poisson | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Poisson:
"""class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for given number of successes def cdf(self... | stack_v2_sparse_classes_36k_train_008586 | 2,830 | no_license | [
{
"docstring": "class constructor parameters: data [list]: data to be used to estimate the distibution lambtha [float]: the expected number of occurances on a given time Sets the instance attribute lambtha as a float If data is not given: Use the given lambtha or raise ValueError if lambtha is not positive valu... | 3 | stack_v2_sparse_classes_30k_train_008905 | Implement the Python class `Poisson` described below.
Class description:
class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for... | Implement the Python class `Poisson` described below.
Class description:
class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for... | 8834b201ca84937365e4dcc0fac978656cdf5293 | <|skeleton|>
class Poisson:
"""class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for given number of successes def cdf(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Poisson:
"""class that represents Poisson distribution class constructor: def __init__(self, data=None, lambtha=1.) instance attributes: lambtha [float]: the expected number of occurances in a given time instance methods: def pmf(self, k): calculates PMF for given number of successes def cdf(self, k): calcula... | the_stack_v2_python_sparse | math/0x03-probability/poisson.py | ejonakodra/holbertonschool-machine_learning-1 | train | 0 |
75d5a64caf8b6175ffedde32d4f3f5868be5fb05 | [
"try:\n if create_if_missing:\n site_profile, is_new = self.get_or_create(user=user, profile=profile, local_site=local_site)\n else:\n site_profile = self.get(user=user, profile=profile, local_site=local_site)\n is_new = False\nexcept MultipleObjectsReturned:\n site_profile = self._fix... | <|body_start_0|>
try:
if create_if_missing:
site_profile, is_new = self.get_or_create(user=user, profile=profile, local_site=local_site)
else:
site_profile = self.get(user=user, profile=profile, local_site=local_site)
is_new = False
... | Manager for Local Site profiles. | LocalSiteProfileManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalSiteProfileManager:
"""Manager for Local Site profiles."""
def for_user(self, user, profile, local_site, create_if_missing=False):
"""Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user (django.contrib.auth.models.User): The user to get the p... | stack_v2_sparse_classes_36k_train_008587 | 9,061 | permissive | [
{
"docstring": "Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user (django.contrib.auth.models.User): The user to get the profile for. profile (reviewboard.accounts.models.Profile): The user's global profile. local_site (reviewboard.site.models.LocalSite): The Local Site to... | 2 | null | Implement the Python class `LocalSiteProfileManager` described below.
Class description:
Manager for Local Site profiles.
Method signatures and docstrings:
- def for_user(self, user, profile, local_site, create_if_missing=False): Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user... | Implement the Python class `LocalSiteProfileManager` described below.
Class description:
Manager for Local Site profiles.
Method signatures and docstrings:
- def for_user(self, user, profile, local_site, create_if_missing=False): Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class LocalSiteProfileManager:
"""Manager for Local Site profiles."""
def for_user(self, user, profile, local_site, create_if_missing=False):
"""Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user (django.contrib.auth.models.User): The user to get the p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocalSiteProfileManager:
"""Manager for Local Site profiles."""
def for_user(self, user, profile, local_site, create_if_missing=False):
"""Return the Local Site profile for the given user and site. Version Added: 5.0 Args: user (django.contrib.auth.models.User): The user to get the profile for. p... | the_stack_v2_python_sparse | reviewboard/accounts/managers.py | reviewboard/reviewboard | train | 1,141 |
feada690bdbf32241921ed938f937eaaa5ed25ee | [
"assert isinstance(converter, Converter), 'Invalid converter %s' % converter\nassert isinstance(baseTimeZone, tzinfo), 'Invalid base time zone %s' % baseTimeZone\nassert isinstance(timeZoneStr, tzinfo), 'Invalid time zone %s' % timeZoneStr\nassert isinstance(timeZoneVal, tzinfo), 'Invalid time zone %s' % timeZoneVa... | <|body_start_0|>
assert isinstance(converter, Converter), 'Invalid converter %s' % converter
assert isinstance(baseTimeZone, tzinfo), 'Invalid base time zone %s' % baseTimeZone
assert isinstance(timeZoneStr, tzinfo), 'Invalid time zone %s' % timeZoneStr
assert isinstance(timeZoneVal, tzi... | Provides the converter time zone support. | ConverterTimeZone | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConverterTimeZone:
"""Provides the converter time zone support."""
def __init__(self, converter, baseTimeZone, timeZoneStr, timeZoneVal):
"""Construct the GMT converter. @param converter: Converter The wrapped converter. @param baseTimeZone: tzinfo The time zone of the dates to be co... | stack_v2_sparse_classes_36k_train_008588 | 5,482 | no_license | [
{
"docstring": "Construct the GMT converter. @param converter: Converter The wrapped converter. @param baseTimeZone: tzinfo The time zone of the dates to be converted. @param timeZoneStr: tzinfo The time zone to convert to string values. @param timeZoneVal: tzinfo The time zone to convert the string values.",
... | 3 | stack_v2_sparse_classes_30k_train_016596 | Implement the Python class `ConverterTimeZone` described below.
Class description:
Provides the converter time zone support.
Method signatures and docstrings:
- def __init__(self, converter, baseTimeZone, timeZoneStr, timeZoneVal): Construct the GMT converter. @param converter: Converter The wrapped converter. @param... | Implement the Python class `ConverterTimeZone` described below.
Class description:
Provides the converter time zone support.
Method signatures and docstrings:
- def __init__(self, converter, baseTimeZone, timeZoneStr, timeZoneVal): Construct the GMT converter. @param converter: Converter The wrapped converter. @param... | e0b3466b34d31548996d57be4a9dac134d904380 | <|skeleton|>
class ConverterTimeZone:
"""Provides the converter time zone support."""
def __init__(self, converter, baseTimeZone, timeZoneStr, timeZoneVal):
"""Construct the GMT converter. @param converter: Converter The wrapped converter. @param baseTimeZone: tzinfo The time zone of the dates to be co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConverterTimeZone:
"""Provides the converter time zone support."""
def __init__(self, converter, baseTimeZone, timeZoneStr, timeZoneVal):
"""Construct the GMT converter. @param converter: Converter The wrapped converter. @param baseTimeZone: tzinfo The time zone of the dates to be converted. @par... | the_stack_v2_python_sparse | components/ally-core-http/ally/core/http/impl/processor/time_zone.py | cristidomsa/Ally-Py | train | 0 |
feba19c3e280bbd99bc8ce19a4fc58ffaac612d6 | [
"self.dic = {}\ni = 0\nfor n in list(nx.traversal.bfs_tree(self.tree, 'Thing')):\n self.dic[n] = i\n i += 1\nself.inv_dic = {str(v): k for k, v in self.dic.items()}",
"ordered_edgelist = {n: list(self.tree.successors(n)) for n in self.tree.nodes()}\nedgelist = defaultdict(list)\nfor k, v in ordered_edgelist... | <|body_start_0|>
self.dic = {}
i = 0
for n in list(nx.traversal.bfs_tree(self.tree, 'Thing')):
self.dic[n] = i
i += 1
self.inv_dic = {str(v): k for k, v in self.dic.items()}
<|end_body_0|>
<|body_start_1|>
ordered_edgelist = {n: list(self.tree.successors(... | HyperEEmbeddingManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HyperEEmbeddingManager:
def create_dictionary(self):
"""create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants an edgelist in which node names are number, (with the root which is the O (zero) value)"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_008589 | 11,182 | no_license | [
{
"docstring": "create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants an edgelist in which node names are number, (with the root which is the O (zero) value)",
"name": "create_dictionary",
"signature": "def create_dictionary(self)"
},... | 4 | stack_v2_sparse_classes_30k_train_012448 | Implement the Python class `HyperEEmbeddingManager` described below.
Class description:
Implement the HyperEEmbeddingManager class.
Method signatures and docstrings:
- def create_dictionary(self): create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants... | Implement the Python class `HyperEEmbeddingManager` described below.
Class description:
Implement the HyperEEmbeddingManager class.
Method signatures and docstrings:
- def create_dictionary(self): create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants... | 14fcc9081ecd27e042de0be2d6b9c53914506fb8 | <|skeleton|>
class HyperEEmbeddingManager:
def create_dictionary(self):
"""create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants an edgelist in which node names are number, (with the root which is the O (zero) value)"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HyperEEmbeddingManager:
def create_dictionary(self):
"""create a dictionary which is {node: value} and the inverse dictionary which is {value: node} this is because HyperE wants an edgelist in which node names are number, (with the root which is the O (zero) value)"""
self.dic = {}
i =... | the_stack_v2_python_sparse | preprocessing/ConceptEmbeddingManager.py | NooneBug/MTNCI | train | 0 | |
56d4948c9dedbe24f9707be0f76742caba6b6a1a | [
"self.uid = uid or str(uuid.uuid4())\nself.battlearea = battlearea\nself.target_missile_locs = target_missile_locs",
"target = None\nif len(self.target_missile_locs) > 0:\n target = self.target_missile_locs.pop(0)\nreturn target"
] | <|body_start_0|>
self.uid = uid or str(uuid.uuid4())
self.battlearea = battlearea
self.target_missile_locs = target_missile_locs
<|end_body_0|>
<|body_start_1|>
target = None
if len(self.target_missile_locs) > 0:
target = self.target_missile_locs.pop(0)
retur... | An instance of this class represents a player. | Player | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Player:
"""An instance of this class represents a player."""
def __init__(self, battlearea, target_missile_locs, uid=None):
""":param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. [A1, B2, C6, D2] :param uid Unique id of player."""
... | stack_v2_sparse_classes_36k_train_008590 | 808 | permissive | [
{
"docstring": ":param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. [A1, B2, C6, D2] :param uid Unique id of player.",
"name": "__init__",
"signature": "def __init__(self, battlearea, target_missile_locs, uid=None)"
},
{
"docstring": "Get and remov... | 2 | null | Implement the Python class `Player` described below.
Class description:
An instance of this class represents a player.
Method signatures and docstrings:
- def __init__(self, battlearea, target_missile_locs, uid=None): :param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. ... | Implement the Python class `Player` described below.
Class description:
An instance of this class represents a player.
Method signatures and docstrings:
- def __init__(self, battlearea, target_missile_locs, uid=None): :param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. ... | 1ca9470c33236016cbb88a38b2f19db41535e457 | <|skeleton|>
class Player:
"""An instance of this class represents a player."""
def __init__(self, battlearea, target_missile_locs, uid=None):
""":param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. [A1, B2, C6, D2] :param uid Unique id of player."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Player:
"""An instance of this class represents a player."""
def __init__(self, battlearea, target_missile_locs, uid=None):
""":param battlearea: Underlying player's battlearea :param target_missile_locs: Missile targets. e.e. [A1, B2, C6, D2] :param uid Unique id of player."""
self.uid =... | the_stack_v2_python_sparse | Misc/battleshipGame/src/entity/player/player.py | suyash248/ds_algo | train | 8 |
a012293ade129d98d8c85dc89b94c564b4280007 | [
"try:\n post_data = request.data\n bk_username = request.user.username\n if create_topic(post_data, bk_username):\n return JsonResponse({'result': True, 'code': 0, 'data': [], 'message': 'topic创建成功'})\n else:\n return JsonResponse({'result': False, 'code': 1, 'data': [], 'message': 'topic创... | <|body_start_0|>
try:
post_data = request.data
bk_username = request.user.username
if create_topic(post_data, bk_username):
return JsonResponse({'result': True, 'code': 0, 'data': [], 'message': 'topic创建成功'})
else:
return JsonRespon... | kafka topic信息表视图 | KafkaTopicViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KafkaTopicViewSet:
"""kafka topic信息表视图"""
def create_topic(self, request, *args, **kwargs):
"""/kafka/create_topic 创建kafka topic信息"""
<|body_0|>
def check_topic(self, request, *args, **kwargs):
"""/kafka/check_topic 后台查询kafka topic状态信息"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_008591 | 12,453 | no_license | [
{
"docstring": "/kafka/create_topic 创建kafka topic信息",
"name": "create_topic",
"signature": "def create_topic(self, request, *args, **kwargs)"
},
{
"docstring": "/kafka/check_topic 后台查询kafka topic状态信息",
"name": "check_topic",
"signature": "def check_topic(self, request, *args, **kwargs)"
... | 2 | stack_v2_sparse_classes_30k_train_016977 | Implement the Python class `KafkaTopicViewSet` described below.
Class description:
kafka topic信息表视图
Method signatures and docstrings:
- def create_topic(self, request, *args, **kwargs): /kafka/create_topic 创建kafka topic信息
- def check_topic(self, request, *args, **kwargs): /kafka/check_topic 后台查询kafka topic状态信息 | Implement the Python class `KafkaTopicViewSet` described below.
Class description:
kafka topic信息表视图
Method signatures and docstrings:
- def create_topic(self, request, *args, **kwargs): /kafka/create_topic 创建kafka topic信息
- def check_topic(self, request, *args, **kwargs): /kafka/check_topic 后台查询kafka topic状态信息
<|ske... | 97cfac2ba94d67980d837f0b541caae70b68a595 | <|skeleton|>
class KafkaTopicViewSet:
"""kafka topic信息表视图"""
def create_topic(self, request, *args, **kwargs):
"""/kafka/create_topic 创建kafka topic信息"""
<|body_0|>
def check_topic(self, request, *args, **kwargs):
"""/kafka/check_topic 后台查询kafka topic状态信息"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KafkaTopicViewSet:
"""kafka topic信息表视图"""
def create_topic(self, request, *args, **kwargs):
"""/kafka/create_topic 创建kafka topic信息"""
try:
post_data = request.data
bk_username = request.user.username
if create_topic(post_data, bk_username):
... | the_stack_v2_python_sparse | apps/kafka/views.py | sdgdsffdsfff/bk-dop | train | 0 |
79f1f9403e408b557a41330ebb7d2d08d8b3f800 | [
"try:\n self.assertEqual(add(17, 23), 40)\nexcept Exception as error:\n print(error)",
"try:\n self.assertEqual(add(-7, -11), -18)\nexcept Exception as error:\n print(error)",
"try:\n self.assertEqual(add(0, 15), 15)\nexcept Exception as error:\n print(error)"
] | <|body_start_0|>
try:
self.assertEqual(add(17, 23), 40)
except Exception as error:
print(error)
<|end_body_0|>
<|body_start_1|>
try:
self.assertEqual(add(-7, -11), -18)
except Exception as error:
print(error)
<|end_body_1|>
<|body_start_2... | Test add function from calculation.py module. | TestAddFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAddFunction:
"""Test add function from calculation.py module."""
def test_add_all_args_greater_zero(self):
"""Test add function if all arguments are greater than zero."""
<|body_0|>
def test_add_all_args_less_zero(self):
"""Test add function if all arguments ... | stack_v2_sparse_classes_36k_train_008592 | 1,838 | no_license | [
{
"docstring": "Test add function if all arguments are greater than zero.",
"name": "test_add_all_args_greater_zero",
"signature": "def test_add_all_args_greater_zero(self)"
},
{
"docstring": "Test add function if all arguments are less than zero.",
"name": "test_add_all_args_less_zero",
... | 3 | stack_v2_sparse_classes_30k_train_017366 | Implement the Python class `TestAddFunction` described below.
Class description:
Test add function from calculation.py module.
Method signatures and docstrings:
- def test_add_all_args_greater_zero(self): Test add function if all arguments are greater than zero.
- def test_add_all_args_less_zero(self): Test add funct... | Implement the Python class `TestAddFunction` described below.
Class description:
Test add function from calculation.py module.
Method signatures and docstrings:
- def test_add_all_args_greater_zero(self): Test add function if all arguments are greater than zero.
- def test_add_all_args_less_zero(self): Test add funct... | 3a500c9d55fecf4032b5faf59a1cbecf64592e9a | <|skeleton|>
class TestAddFunction:
"""Test add function from calculation.py module."""
def test_add_all_args_greater_zero(self):
"""Test add function if all arguments are greater than zero."""
<|body_0|>
def test_add_all_args_less_zero(self):
"""Test add function if all arguments ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAddFunction:
"""Test add function from calculation.py module."""
def test_add_all_args_greater_zero(self):
"""Test add function if all arguments are greater than zero."""
try:
self.assertEqual(add(17, 23), 40)
except Exception as error:
print(error)
... | the_stack_v2_python_sparse | python10/test_calculation.py | maksimok93/Dp-189 | train | 0 |
9d0e47607b8d7f3e9acfc65962522eafd5a94fda | [
"logger.info('【获取微信全局唯一票据access_token】>>>执行定时器任务')\ntornado.ioloop.IOLoop.instance().call_later(0, self.get_access_token)\ntornado.ioloop.PeriodicCallback(self.get_access_token, self._expire_time_access_token).start()",
"url = WxConfig.config_get_access_token_url\nr = requests.get(url)\nif r.status_code == 200:\n... | <|body_start_0|>
logger.info('【获取微信全局唯一票据access_token】>>>执行定时器任务')
tornado.ioloop.IOLoop.instance().call_later(0, self.get_access_token)
tornado.ioloop.PeriodicCallback(self.get_access_token, self._expire_time_access_token).start()
<|end_body_0|>
<|body_start_1|>
url = WxConfig.config_g... | 定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket | WxShedule | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WxShedule:
"""定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket"""
def excute(self):
"""执行定时器任务"""
<|body_0|>
def get_access_token(self):
"""获取微信全局唯一票据access_token"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_008593 | 1,897 | no_license | [
{
"docstring": "执行定时器任务",
"name": "excute",
"signature": "def excute(self)"
},
{
"docstring": "获取微信全局唯一票据access_token",
"name": "get_access_token",
"signature": "def get_access_token(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015317 | Implement the Python class `WxShedule` described below.
Class description:
定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket
Method signatures and docstrings:
- def excute(self): 执行定时器任务
- def get_access_token(self): 获取微信全局唯一票据access_token | Implement the Python class `WxShedule` described below.
Class description:
定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket
Method signatures and docstrings:
- def excute(self): 执行定时器任务
- def get_access_token(self): 获取微信全局唯一票据access_token
<|skeleton|>
class Wx... | b4b60a33028ae1c638b8051304576f2b9e4630aa | <|skeleton|>
class WxShedule:
"""定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket"""
def excute(self):
"""执行定时器任务"""
<|body_0|>
def get_access_token(self):
"""获取微信全局唯一票据access_token"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WxShedule:
"""定时任务调度器 excute 执行定时器任务 get_access_token 获取微信全局唯一票据access_token get_jsapi_ticket 获取JS_SDK权限签名的jsapi_ticket"""
def excute(self):
"""执行定时器任务"""
logger.info('【获取微信全局唯一票据access_token】>>>执行定时器任务')
tornado.ioloop.IOLoop.instance().call_later(0, self.get_access_token)
... | the_stack_v2_python_sparse | prize_server/weixinback/core/server/wxshedule.py | XTAYJGDUFVF/prize_server | train | 0 |
e261ee90ac21f193058a3a9581da3dc8b8eef0ec | [
"for group in self:\n if group.match(environments):\n return group\nreturn None",
"ret = set()\nfor group in self:\n for env in group.environments:\n ret.add(HashableEnvironment(name=env.name, typename=env.environmentType.name))\nreturn sorted(ret, key=lambda e: e.typename)"
] | <|body_start_0|>
for group in self:
if group.match(environments):
return group
return None
<|end_body_0|>
<|body_start_1|>
ret = set()
for group in self:
for env in group.environments:
ret.add(HashableEnvironment(name=env.name, typ... | BaseEnvironmentGroupList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseEnvironmentGroupList:
def match(self, environments):
"""If the given set of ``environments`` match any environment group in this environment group list, return that environment group. Else return None."""
<|body_0|>
def environments(self):
"""Return a list of all... | stack_v2_sparse_classes_36k_train_008594 | 8,477 | no_license | [
{
"docstring": "If the given set of ``environments`` match any environment group in this environment group list, return that environment group. Else return None.",
"name": "match",
"signature": "def match(self, environments)"
},
{
"docstring": "Return a list of all unique environments in this en... | 2 | stack_v2_sparse_classes_30k_train_002495 | Implement the Python class `BaseEnvironmentGroupList` described below.
Class description:
Implement the BaseEnvironmentGroupList class.
Method signatures and docstrings:
- def match(self, environments): If the given set of ``environments`` match any environment group in this environment group list, return that enviro... | Implement the Python class `BaseEnvironmentGroupList` described below.
Class description:
Implement the BaseEnvironmentGroupList class.
Method signatures and docstrings:
- def match(self, environments): If the given set of ``environments`` match any environment group in this environment group list, return that enviro... | deb6b22ed417740bf947e86938710bd5fa2ee2e7 | <|skeleton|>
class BaseEnvironmentGroupList:
def match(self, environments):
"""If the given set of ``environments`` match any environment group in this environment group list, return that environment group. Else return None."""
<|body_0|>
def environments(self):
"""Return a list of all... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseEnvironmentGroupList:
def match(self, environments):
"""If the given set of ``environments`` match any environment group in this environment group list, return that environment group. Else return None."""
for group in self:
if group.match(environments):
return g... | the_stack_v2_python_sparse | ccui/environments/models.py | camd/caseconductor-ui | train | 0 | |
c55f1e260e27665a32fea9d7d8a92c8ed12268af | [
"logger.info('%s initialization' % obj.name)\nsuper(self.__class__, self).__init__(obj, parent)\nself.ppx = 0.0\nself.ppy = 0.0\nself.ppz = 0.0\nself.pvx = 0.0\nself.pvy = 0.0\nself.pvz = 0.0\nself.p = self.blender_obj.position\nself.v = [0.0, 0.0, 0.0]\nself.pv = [0.0, 0.0, 0.0]\nself.a = [0.0, 0.0, 0.0]\nself.tic... | <|body_start_0|>
logger.info('%s initialization' % obj.name)
super(self.__class__, self).__init__(obj, parent)
self.ppx = 0.0
self.ppy = 0.0
self.ppz = 0.0
self.pvx = 0.0
self.pvy = 0.0
self.pvz = 0.0
self.p = self.blender_obj.position
self... | Accelerometer sensor | AccelerometerClass | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccelerometerClass:
"""Accelerometer sensor"""
def __init__(self, obj, parent=None):
"""Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent."""
<|body_0|>
def default_action(self):
"""Co... | stack_v2_sparse_classes_36k_train_008595 | 3,250 | permissive | [
{
"docstring": "Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent.",
"name": "__init__",
"signature": "def __init__(self, obj, parent=None)"
},
{
"docstring": "Compute the speed and accleration of the robot The speed ... | 2 | null | Implement the Python class `AccelerometerClass` described below.
Class description:
Accelerometer sensor
Method signatures and docstrings:
- def __init__(self, obj, parent=None): Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent.
- def def... | Implement the Python class `AccelerometerClass` described below.
Class description:
Accelerometer sensor
Method signatures and docstrings:
- def __init__(self, obj, parent=None): Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent.
- def def... | 07fcb64fea3b58b258e917eb1aed0a585f863418 | <|skeleton|>
class AccelerometerClass:
"""Accelerometer sensor"""
def __init__(self, obj, parent=None):
"""Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent."""
<|body_0|>
def default_action(self):
"""Co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccelerometerClass:
"""Accelerometer sensor"""
def __init__(self, obj, parent=None):
"""Constructor method. Receives the reference to the Blender object. The second parameter should be the name of the object's parent."""
logger.info('%s initialization' % obj.name)
super(self.__cla... | the_stack_v2_python_sparse | src/morse/sensors/accelerometer.py | DefaultUser/morse | train | 2 |
3723b140e34e94025c6f6a8400bbe3361c257f7a | [
"for name, hook in what.iteritems():\n func = getattr(target, name)\n if not isinstance(func, HookedMethod):\n func = HookedMethod(func)\n setattr(target, name, func)\n func.pending.append(hook)",
"for name, hook in what.iteritems():\n hooked = getattr(target, name)\n if hook in hooke... | <|body_start_0|>
for name, hook in what.iteritems():
func = getattr(target, name)
if not isinstance(func, HookedMethod):
func = HookedMethod(func)
setattr(target, name, func)
func.pending.append(hook)
<|end_body_0|>
<|body_start_1|>
fo... | HookSet | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HookSet:
def install_hooks(target, **what):
""":param target: :param what: :return:"""
<|body_0|>
def remove_hooks(target, **what):
""":param target: :param what: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for name, hook in what.iterit... | stack_v2_sparse_classes_36k_train_008596 | 1,672 | permissive | [
{
"docstring": ":param target: :param what: :return:",
"name": "install_hooks",
"signature": "def install_hooks(target, **what)"
},
{
"docstring": ":param target: :param what: :return:",
"name": "remove_hooks",
"signature": "def remove_hooks(target, **what)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000579 | Implement the Python class `HookSet` described below.
Class description:
Implement the HookSet class.
Method signatures and docstrings:
- def install_hooks(target, **what): :param target: :param what: :return:
- def remove_hooks(target, **what): :param target: :param what: :return: | Implement the Python class `HookSet` described below.
Class description:
Implement the HookSet class.
Method signatures and docstrings:
- def install_hooks(target, **what): :param target: :param what: :return:
- def remove_hooks(target, **what): :param target: :param what: :return:
<|skeleton|>
class HookSet:
d... | 18b77c72bd12de2e3c510a5792434386a79ccfa8 | <|skeleton|>
class HookSet:
def install_hooks(target, **what):
""":param target: :param what: :return:"""
<|body_0|>
def remove_hooks(target, **what):
""":param target: :param what: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HookSet:
def install_hooks(target, **what):
""":param target: :param what: :return:"""
for name, hook in what.iteritems():
func = getattr(target, name)
if not isinstance(func, HookedMethod):
func = HookedMethod(func)
setattr(target, name,... | the_stack_v2_python_sparse | angr/misc/hookset.py | ercoppa/angr | train | 1 | |
dd219f4b1e819975173334a422d9b7ea0cd460e1 | [
"name = self.cleaned_data.get('name')\nif name[-1] == '.':\n raise ValidationError(_('Name may not end with dot.'), code='invalid')\nreturn name",
"data = self.cleaned_data.get('content')\n_type = self.cleaned_data.get('type')\nif _type == 'A':\n validate_ipv4_address(data)\nelif _type == 'AAAA':\n valid... | <|body_start_0|>
name = self.cleaned_data.get('name')
if name[-1] == '.':
raise ValidationError(_('Name may not end with dot.'), code='invalid')
return name
<|end_body_0|>
<|body_start_1|>
data = self.cleaned_data.get('content')
_type = self.cleaned_data.get('type')
... | Create/edit DataRecord | DataRecordForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataRecordForm:
"""Create/edit DataRecord"""
def clean_name(self):
"""Make sure name doesn't end with `.`"""
<|body_0|>
def clean_content(self):
"""Clean content based on selected type"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
name = self.... | stack_v2_sparse_classes_36k_train_008597 | 2,285 | permissive | [
{
"docstring": "Make sure name doesn't end with `.`",
"name": "clean_name",
"signature": "def clean_name(self)"
},
{
"docstring": "Clean content based on selected type",
"name": "clean_content",
"signature": "def clean_content(self)"
}
] | 2 | null | Implement the Python class `DataRecordForm` described below.
Class description:
Create/edit DataRecord
Method signatures and docstrings:
- def clean_name(self): Make sure name doesn't end with `.`
- def clean_content(self): Clean content based on selected type | Implement the Python class `DataRecordForm` described below.
Class description:
Create/edit DataRecord
Method signatures and docstrings:
- def clean_name(self): Make sure name doesn't end with `.`
- def clean_content(self): Clean content based on selected type
<|skeleton|>
class DataRecordForm:
"""Create/edit Da... | 2305b1e27abb0bfe9fcee93b79e012c62cba712e | <|skeleton|>
class DataRecordForm:
"""Create/edit DataRecord"""
def clean_name(self):
"""Make sure name doesn't end with `.`"""
<|body_0|>
def clean_content(self):
"""Clean content based on selected type"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataRecordForm:
"""Create/edit DataRecord"""
def clean_name(self):
"""Make sure name doesn't end with `.`"""
name = self.cleaned_data.get('name')
if name[-1] == '.':
raise ValidationError(_('Name may not end with dot.'), code='invalid')
return name
def cle... | the_stack_v2_python_sparse | supervisr/dns/forms/records.py | BeryJu/supervisr | train | 1 |
b36f1ae0209c72dc7b6ef426920d4eed12026f69 | [
"import sys\nimport os\nnew_path = os.path.join(sys.prefix, 'Lib', 'site-packages')\nif os.path.exists(new_path) and new_path not in sys.path:\n sys.path += [new_path]",
"action_handler_t_name = ida_kernwin.action_handler_t.__name__\nif action_handler_t_name == 'action_handler_t_objprotect':\n return\nif is... | <|body_start_0|>
import sys
import os
new_path = os.path.join(sys.prefix, 'Lib', 'site-packages')
if os.path.exists(new_path) and new_path not in sys.path:
sys.path += [new_path]
<|end_body_0|>
<|body_start_1|>
action_handler_t_name = ida_kernwin.action_handler_t.__n... | Fix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Fix:
def packagespath():
"""Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the machine's installed python instead of a packaged version, but that version was running withou... | stack_v2_sparse_classes_36k_train_008598 | 6,068 | no_license | [
{
"docstring": "Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the machine's installed python instead of a packaged version, but that version was running without using site-packages. This made a u... | 3 | stack_v2_sparse_classes_30k_test_000877 | Implement the Python class `Fix` described below.
Class description:
Implement the Fix class.
Method signatures and docstrings:
- def packagespath(): Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the m... | Implement the Python class `Fix` described below.
Class description:
Implement the Fix class.
Method signatures and docstrings:
- def packagespath(): Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the m... | 149c210576ab77f930a7592d99203cf9e8819675 | <|skeleton|>
class Fix:
def packagespath():
"""Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the machine's installed python instead of a packaged version, but that version was running withou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Fix:
def packagespath():
"""Hack required in relatively old IDA linux/osx versions (around 6.4/5) to successfully load python packages installed in site-packages. IDA for linux/osx was using the machine's installed python instead of a packaged version, but that version was running without using site-p... | the_stack_v2_python_sparse | ida_plugins/rematch/rematch/idasix.py | Trietptm-on-Coding-Algorithms/stuff | train | 0 | |
c55d654ea716533d197236fde7525488d396d215 | [
"FlatReader.__init__(self, underlying_array, formatted_dtype=formatted_dtype, formatted_shape=formatted_shape, reverse_axes=reverse_axes, transpose_axes=transpose_axes, format_function=format_function, close_segments=close_segments)\nSICDTypeReader.__init__(self, None, sicd_meta)\nself._check_sizes()",
"if not is... | <|body_start_0|>
FlatReader.__init__(self, underlying_array, formatted_dtype=formatted_dtype, formatted_shape=formatted_shape, reverse_axes=reverse_axes, transpose_axes=transpose_axes, format_function=format_function, close_segments=close_segments)
SICDTypeReader.__init__(self, None, sicd_meta)
... | Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes. | FlatSICDReader | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlatSICDReader:
"""Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes."""
def __init__(self, sicd_meta, underlying_array, formatted_dtype: Union[None, str, numpy.dtype]=None, formatted_shape: Union[None, Tuple[int, ...]]=None, reverse_axes: Uni... | stack_v2_sparse_classes_36k_train_008599 | 9,108 | permissive | [
{
"docstring": "Parameters ---------- sicd_meta : None|SICDType `None`, or the SICD metadata object underlying_array : numpy.ndarray formatted_dtype : None|str|numpy.dtype formatted_shape : None|Tuple[int, ...] reverse_axes : None|Sequence[int] transpose_axes : None|Tuple[int, ...] format_function : None|Format... | 2 | stack_v2_sparse_classes_30k_test_000696 | Implement the Python class `FlatSICDReader` described below.
Class description:
Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes.
Method signatures and docstrings:
- def __init__(self, sicd_meta, underlying_array, formatted_dtype: Union[None, str, numpy.dtype]=None, f... | Implement the Python class `FlatSICDReader` described below.
Class description:
Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes.
Method signatures and docstrings:
- def __init__(self, sicd_meta, underlying_array, formatted_dtype: Union[None, str, numpy.dtype]=None, f... | de1b1886f161a83b6c89aadc7a2c7cfc4892ef81 | <|skeleton|>
class FlatSICDReader:
"""Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes."""
def __init__(self, sicd_meta, underlying_array, formatted_dtype: Union[None, str, numpy.dtype]=None, formatted_shape: Union[None, Tuple[int, ...]]=None, reverse_axes: Uni... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlatSICDReader:
"""Create a sicd type reader directly from an array. **Changed in version 1.3.0** for reading changes."""
def __init__(self, sicd_meta, underlying_array, formatted_dtype: Union[None, str, numpy.dtype]=None, formatted_shape: Union[None, Tuple[int, ...]]=None, reverse_axes: Union[None, int,... | the_stack_v2_python_sparse | sarpy/io/complex/base.py | ngageoint/sarpy | train | 192 |
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