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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ab8730795161ecb89426f9f0db37c162c2c1f894 | [
"self.dic = {}\nfor word in set(dictionary):\n if word:\n if len(word) <= 2:\n if word not in self.dic:\n self.dic[word] = set()\n self.dic[word].add(word)\n else:\n abb = word[0] + str(len(word) - 2) + word[-1]\n if abb in self.dic:\n ... | <|body_start_0|>
self.dic = {}
for word in set(dictionary):
if word:
if len(word) <= 2:
if word not in self.dic:
self.dic[word] = set()
self.dic[word].add(word)
else:
abb =... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
"""check if a word is unique. :type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_026200 | 1,496 | no_license | [
{
"docstring": "initialize your data structure here. :type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": "check if a word is unique. :type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
... | 2 | stack_v2_sparse_classes_30k_train_019204 | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str]
- def isUnique(self, word): check if a word is unique. :type word: str ... | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): initialize your data structure here. :type dictionary: List[str]
- def isUnique(self, word): check if a word is unique. :type word: str ... | f1b85a2bfee024ef3afdf2ca0b223842c2d2d3f3 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
"""check if a word is unique. :type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
"""initialize your data structure here. :type dictionary: List[str]"""
self.dic = {}
for word in set(dictionary):
if word:
if len(word) <= 2:
if word not in self.dic:
... | the_stack_v2_python_sparse | 288-Unique-Word-Abbreviation/solution.py | Xochitlxie/Leetcode | train | 0 | |
52c41950217afca0b46e5a7f0ac7c8af355aa293 | [
"self.array = array\nself.tree = [0 for _ in range(len(self.array) * 4)]\nself.init(self.tree, 0, len(self.array) - 1, 1)\nself.last_index = len(array) - 1",
"if start == end:\n tree[node] = start\n return tree[node]\nmid = (start + end) // 2\nleft = self.init(tree, start, mid, node * 2)\nright = self.init(... | <|body_start_0|>
self.array = array
self.tree = [0 for _ in range(len(self.array) * 4)]
self.init(self.tree, 0, len(self.array) - 1, 1)
self.last_index = len(array) - 1
<|end_body_0|>
<|body_start_1|>
if start == end:
tree[node] = start
return tree[node]
... | A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method directly. min(left, right, node=1, start=0, end=-1) return the partial min of the a... | Segment_Min_Tree | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Segment_Min_Tree:
"""A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method directly. min(left, right, node=1, star... | stack_v2_sparse_classes_36k_train_026201 | 4,003 | permissive | [
{
"docstring": "Parameters ---------- array : list the array that you want to make tree",
"name": "__init__",
"signature": "def __init__(self, array)"
},
{
"docstring": "Don't Call This Method Directly",
"name": "init",
"signature": "def init(self, tree, start, end, node)"
},
{
"... | 3 | null | Implement the Python class `Segment_Min_Tree` described below.
Class description:
A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method ... | Implement the Python class `Segment_Min_Tree` described below.
Class description:
A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method ... | 3efa96710e97c8740d6fef69e4afe7a23bfca05f | <|skeleton|>
class Segment_Min_Tree:
"""A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method directly. min(left, right, node=1, star... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Segment_Min_Tree:
"""A Class used to get partial min of an array and update data ... Attributes ---------- array : list a list which to make a segment tree Methods ------- init(tree, start, end, node) make segment tree from the array. don't call this method directly. min(left, right, node=1, start=0, end=-1) ... | the_stack_v2_python_sparse | libs/segment_tree_min.py | yskang/AlgorithmPractice | train | 0 |
ff92132657b857349b01daa1f5bf7aeb1bb7fb1d | [
"i = 0\nres = []\nwhile i < len(nums):\n if nums[i] != i + 1 and nums[i] != nums[nums[i] - 1]:\n tmp = nums[i]\n nums[i] = nums[tmp - 1]\n nums[tmp - 1] = tmp\n else:\n i += 1\nfor i in range(len(nums)):\n if nums[i] != i + 1:\n res.append(i + 1)\nreturn res",
"myset = ... | <|body_start_0|>
i = 0
res = []
while i < len(nums):
if nums[i] != i + 1 and nums[i] != nums[nums[i] - 1]:
tmp = nums[i]
nums[i] = nums[tmp - 1]
nums[tmp - 1] = tmp
else:
i += 1
for i in range(len(num... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDisappearedNumbers2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i = 0
... | stack_v2_sparse_classes_36k_train_026202 | 1,144 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDisappearedNumbers",
"signature": "def findDisappearedNumbers(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDisappearedNumbers2",
"signature": "def findDisappearedNumbers2(self... | 2 | stack_v2_sparse_classes_30k_train_021577 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDisappearedNumbers(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers2(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDisappearedNumbers(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers2(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
c... | ab49373ff3fc306a03a90de02e1801b8cbe520d7 | <|skeleton|>
class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDisappearedNumbers2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
i = 0
res = []
while i < len(nums):
if nums[i] != i + 1 and nums[i] != nums[nums[i] - 1]:
tmp = nums[i]
nums[i] = nums[tmp - 1]
... | the_stack_v2_python_sparse | explore/array/448.py | yiguid/LeetCodePractise | train | 0 | |
fb03652a4ac48127d705619db5ccefde52b63d40 | [
"super(TransformerDecoderLayer, self).__init__()\nself.self_attn = NonLocalSelfAttention(channels)\nself.dropout1 = nn.Dropout(dropout)\nout_c = int(channels / 2)\nself.mutate = nn.Sequential(ConvolutionalTransposeBlock(in_c=channels, out_c=out_c, padded=True, kernel_size=kernel_size), ConvolutionalTransposeBlock(i... | <|body_start_0|>
super(TransformerDecoderLayer, self).__init__()
self.self_attn = NonLocalSelfAttention(channels)
self.dropout1 = nn.Dropout(dropout)
out_c = int(channels / 2)
self.mutate = nn.Sequential(ConvolutionalTransposeBlock(in_c=channels, out_c=out_c, padded=True, kernel_... | TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advance... | TransformerDecoderLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerDecoderLayer:
"""TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polo... | stack_v2_sparse_classes_36k_train_026203 | 9,975 | no_license | [
{
"docstring": ":param channels: :param dropout: :param kernel_size:",
"name": "__init__",
"signature": "def __init__(self, channels, dropout=0.1, kernel_size=1)"
},
{
"docstring": "Pass the input through the encoder layer. Args: src: the sequence to the encoder layer (required). Shape: see the ... | 2 | stack_v2_sparse_classes_30k_train_017471 | Implement the Python class `TransformerDecoderLayer` described below.
Class description:
TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan... | Implement the Python class `TransformerDecoderLayer` described below.
Class description:
TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan... | be76715676dc1652e80ff5f95003220d8002c4d9 | <|skeleton|>
class TransformerDecoderLayer:
"""TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerDecoderLayer:
"""TransformerEncoderLayer is made up of self-attn and feedforward network. This standard encoder layer is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017.... | the_stack_v2_python_sparse | models/transformer_convolutional_vae.py | flawnson/AA_VAE | train | 0 |
7109acb5fcc67928fcc899ea32bda20a0df3f7a3 | [
"def preorder_traversal(root):\n if not root:\n return 'None'\n return ','.join([str(root.val), preorder_traversal(root.left), preorder_traversal(root.right)])\nreturn preorder_traversal(root)",
"from collections import deque\ndata = deque(data.split(','))\n\ndef build_tree_from_inorder(data):\n n... | <|body_start_0|>
def preorder_traversal(root):
if not root:
return 'None'
return ','.join([str(root.val), preorder_traversal(root.left), preorder_traversal(root.right)])
return preorder_traversal(root)
<|end_body_0|>
<|body_start_1|>
from collections impo... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_026204 | 1,331 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | fd4cf122cfd4920f3bd8dce40ba7487a170a1b57 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def preorder_traversal(root):
if not root:
return 'None'
return ','.join([str(root.val), preorder_traversal(root.left), preorder_traversal(root.ri... | the_stack_v2_python_sparse | 0297_Serialize_and_Deserialize_Binary_Tree.py | coldmanck/leetcode-python | train | 6 | |
c1aa2c79ec02ea2569d041088936be373b090142 | [
"s.dingding = dingding\ns.match_pattern = d.get('MatchPattern', None)\ns.xmlrpc_recv_url = d['XmlRpcRecvUrl']\ns.recv_password = d.get('RecvPassword', None)",
"if s.xmlrpc_recv_url != subs.xmlrpc_recv_url:\n return False\nif s.recv_password != subs.recv_password:\n return False\nif not s.match_pattern:\n ... | <|body_start_0|>
s.dingding = dingding
s.match_pattern = d.get('MatchPattern', None)
s.xmlrpc_recv_url = d['XmlRpcRecvUrl']
s.recv_password = d.get('RecvPassword', None)
<|end_body_0|>
<|body_start_1|>
if s.xmlrpc_recv_url != subs.xmlrpc_recv_url:
return False
... | Unsubscription - augment an unsubscription dictionary | Unsubscription | [
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Unsubscription:
"""Unsubscription - augment an unsubscription dictionary"""
def __init__(s, d, dingding):
"""unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL of unsubscribing interfac... | stack_v2_sparse_classes_36k_train_026205 | 25,098 | permissive | [
{
"docstring": "unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL of unsubscribing interface * RecvPassword (OPTIONAL) - if there is a password associated with the receiver, put it here nothing else",
"name":... | 2 | stack_v2_sparse_classes_30k_train_009903 | Implement the Python class `Unsubscription` described below.
Class description:
Unsubscription - augment an unsubscription dictionary
Method signatures and docstrings:
- def __init__(s, d, dingding): unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcR... | Implement the Python class `Unsubscription` described below.
Class description:
Unsubscription - augment an unsubscription dictionary
Method signatures and docstrings:
- def __init__(s, d, dingding): unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcR... | da65d948b346d3f455e79168a8753b2b16d8fc5f | <|skeleton|>
class Unsubscription:
"""Unsubscription - augment an unsubscription dictionary"""
def __init__(s, d, dingding):
"""unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL of unsubscribing interfac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Unsubscription:
"""Unsubscription - augment an unsubscription dictionary"""
def __init__(s, d, dingding):
"""unsubscribe dict: * MatchPattern (*OPTIONAL*) - pattern to unsubscribe; if missing, unsubscribe ALL patterns * XmlRpcRecvUrl (REQUIRED) - XML-RPC URL of unsubscribing interface * RecvPassw... | the_stack_v2_python_sparse | ancient/src/dingding/dingding.py | BackupTheBerlios/onebigsoup-svn | train | 0 |
c054df0ab52c3e6ab864b948a4bb8061e9dff15d | [
"self.src = src_pattern\nself.dst = dst_pattern\nself.dayu_object = DayuPath(self.src)",
"scan_gen = self.dayu_object.scan()\nscan_list = list(scan_gen)\nif scan_list:\n return scan_list[0].frames\nreturn []",
"scan_gen = self.dayu_object.scan()\nscan_list = list(scan_gen)\nif scan_list:\n scan_object = s... | <|body_start_0|>
self.src = src_pattern
self.dst = dst_pattern
self.dayu_object = DayuPath(self.src)
<|end_body_0|>
<|body_start_1|>
scan_gen = self.dayu_object.scan()
scan_list = list(scan_gen)
if scan_list:
return scan_list[0].frames
return []
<|end... | SequenceConverter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SequenceConverter:
def __init__(self, src_pattern, dst_pattern):
"""序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext"""
<|body_0|>
def frames(self):
"""获取序列的帧数 :return: <list>"""
<|body_1|>
def file_list(self):
"""这种情况，sel... | stack_v2_sparse_classes_36k_train_026206 | 1,692 | no_license | [
{
"docstring": "序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext",
"name": "__init__",
"signature": "def __init__(self, src_pattern, dst_pattern)"
},
{
"docstring": "获取序列的帧数 :return: <list>",
"name": "frames",
"signature": "def frames(self)"
},
{
"docstrin... | 4 | null | Implement the Python class `SequenceConverter` described below.
Class description:
Implement the SequenceConverter class.
Method signatures and docstrings:
- def __init__(self, src_pattern, dst_pattern): 序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext
- def frames(self): 获取序列的帧数 :return: <lis... | Implement the Python class `SequenceConverter` described below.
Class description:
Implement the SequenceConverter class.
Method signatures and docstrings:
- def __init__(self, src_pattern, dst_pattern): 序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext
- def frames(self): 获取序列的帧数 :return: <lis... | 5fdc4e308191345149b902c5913e2698336630ea | <|skeleton|>
class SequenceConverter:
def __init__(self, src_pattern, dst_pattern):
"""序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext"""
<|body_0|>
def frames(self):
"""获取序列的帧数 :return: <list>"""
<|body_1|>
def file_list(self):
"""这种情况，sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SequenceConverter:
def __init__(self, src_pattern, dst_pattern):
"""序列转换 :param src_pattern: name.####.ext :param dst_pattern: name.####.ext"""
self.src = src_pattern
self.dst = dst_pattern
self.dayu_object = DayuPath(self.src)
def frames(self):
"""获取序列的帧数 :return:... | the_stack_v2_python_sparse | mliber_libs/python_libs/sequence_converter/sequence_converter.py | githeshuai/mliber | train | 2 | |
a3f701106cf559711e47350e1d107303c6eac275 | [
"self.struct_format = '=h'\nself.prefix_length = struct.calcsize(self.struct_format)\nself._unprocessed = ''\nself.PACKET_MAX_LENGTH = 99999",
"all_data = self._unprocessed + data\ncurrent_offset = 0\nfmt = self.struct_format\nself._unprocessed = all_data\npacket, result = (None, None)\nwhile len(all_data) >= cur... | <|body_start_0|>
self.struct_format = '=h'
self.prefix_length = struct.calcsize(self.struct_format)
self._unprocessed = ''
self.PACKET_MAX_LENGTH = 99999
<|end_body_0|>
<|body_start_1|>
all_data = self._unprocessed + data
current_offset = 0
fmt = self.struct_form... | class docs | NetData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetData:
"""class docs"""
def __init__(self):
"""Constructor"""
<|body_0|>
def net_wok(self, data):
"""work 长度取前2个字节"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.struct_format = '=h'
self.prefix_length = struct.calcsize(self.stru... | stack_v2_sparse_classes_36k_train_026207 | 1,438 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "work 长度取前2个字节",
"name": "net_wok",
"signature": "def net_wok(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008286 | Implement the Python class `NetData` described below.
Class description:
class docs
Method signatures and docstrings:
- def __init__(self): Constructor
- def net_wok(self, data): work 长度取前2个字节 | Implement the Python class `NetData` described below.
Class description:
class docs
Method signatures and docstrings:
- def __init__(self): Constructor
- def net_wok(self, data): work 长度取前2个字节
<|skeleton|>
class NetData:
"""class docs"""
def __init__(self):
"""Constructor"""
<|body_0|>
... | fd5dff2607164f4d8a3fa1c328f72ac540c844ca | <|skeleton|>
class NetData:
"""class docs"""
def __init__(self):
"""Constructor"""
<|body_0|>
def net_wok(self, data):
"""work 长度取前2个字节"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetData:
"""class docs"""
def __init__(self):
"""Constructor"""
self.struct_format = '=h'
self.prefix_length = struct.calcsize(self.struct_format)
self._unprocessed = ''
self.PACKET_MAX_LENGTH = 99999
def net_wok(self, data):
"""work 长度取前2个字节"""
... | the_stack_v2_python_sparse | client/analysis/netsvc/resolve.py | flaght/mcrawler | train | 0 |
97164383dc7930d4674c89ae1a3ef19f2e886f69 | [
"homedir = pwd.getpwnam(user)[5]\nsshdir = os.path.join(homedir, '.ssh')\nkeyfile = os.path.join(sshdir, 'id_dsa.pub')\nif os.path.exists(keyfile):\n return keyfile\nelse:\n keyfile = os.path.join(sshdir, 'id_rsa.pub')\n if os.path.exists(keyfile):\n return keyfile\nreturn False",
"homedir = pwd.g... | <|body_start_0|>
homedir = pwd.getpwnam(user)[5]
sshdir = os.path.join(homedir, '.ssh')
keyfile = os.path.join(sshdir, 'id_dsa.pub')
if os.path.exists(keyfile):
return keyfile
else:
keyfile = os.path.join(sshdir, 'id_rsa.pub')
if os.path.exists... | Generic system administration stuff | SysADM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SysADM:
"""Generic system administration stuff"""
def findSSHKeyFile(self, user):
"""return ssh key file if it exists, or False"""
<|body_0|>
def genSSHKey(self, user):
"""generate a user SSH key, assuming it's not already created. returns full path to public key... | stack_v2_sparse_classes_36k_train_026208 | 7,200 | permissive | [
{
"docstring": "return ssh key file if it exists, or False",
"name": "findSSHKeyFile",
"signature": "def findSSHKeyFile(self, user)"
},
{
"docstring": "generate a user SSH key, assuming it's not already created. returns full path to public key file.",
"name": "genSSHKey",
"signature": "d... | 3 | stack_v2_sparse_classes_30k_train_013987 | Implement the Python class `SysADM` described below.
Class description:
Generic system administration stuff
Method signatures and docstrings:
- def findSSHKeyFile(self, user): return ssh key file if it exists, or False
- def genSSHKey(self, user): generate a user SSH key, assuming it's not already created. returns fu... | Implement the Python class `SysADM` described below.
Class description:
Generic system administration stuff
Method signatures and docstrings:
- def findSSHKeyFile(self, user): return ssh key file if it exists, or False
- def genSSHKey(self, user): generate a user SSH key, assuming it's not already created. returns fu... | 14812dfbc7bac1d76c4d9e5be2cdf83fc1c391a1 | <|skeleton|>
class SysADM:
"""Generic system administration stuff"""
def findSSHKeyFile(self, user):
"""return ssh key file if it exists, or False"""
<|body_0|>
def genSSHKey(self, user):
"""generate a user SSH key, assuming it's not already created. returns full path to public key... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SysADM:
"""Generic system administration stuff"""
def findSSHKeyFile(self, user):
"""return ssh key file if it exists, or False"""
homedir = pwd.getpwnam(user)[5]
sshdir = os.path.join(homedir, '.ssh')
keyfile = os.path.join(sshdir, 'id_dsa.pub')
if os.path.exists(... | the_stack_v2_python_sparse | data/python/be83e963dd5f3631631f7c1497f0afdf_appadm.py | maxim5/code-inspector | train | 5 |
5aeaf528d92c7d3d7ac0d98ac36bafe81b1dd06a | [
"if not list_of_files:\n return {}\n_dict = file_handler.retrieve_time_stamp(list_of_files, label=label)\n_time_metadata_dict = MetadataHandler._reformat_dict(dictionary=_dict)\n_beamline_metadata_dict = MetadataHandler.retrieve_beamline_metadata(list_of_files)\n_metadata_dict = combine_dictionaries(master_dicti... | <|body_start_0|>
if not list_of_files:
return {}
_dict = file_handler.retrieve_time_stamp(list_of_files, label=label)
_time_metadata_dict = MetadataHandler._reformat_dict(dictionary=_dict)
_beamline_metadata_dict = MetadataHandler.retrieve_beamline_metadata(list_of_files)
... | MetadataHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetadataHandler:
def retrieve_metadata(list_of_files=None, display_infos=False, label=''):
"""dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'value': value, 'name': name}, 'metadata3_key': {'value': value, 'name': name}, ... }, ... }"""
<|bod... | stack_v2_sparse_classes_36k_train_026209 | 5,100 | permissive | [
{
"docstring": "dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'value': value, 'name': name}, 'metadata3_key': {'value': value, 'name': name}, ... }, ... }",
"name": "retrieve_metadata",
"signature": "def retrieve_metadata(list_of_files=None, display_infos=False, la... | 3 | stack_v2_sparse_classes_30k_train_005433 | Implement the Python class `MetadataHandler` described below.
Class description:
Implement the MetadataHandler class.
Method signatures and docstrings:
- def retrieve_metadata(list_of_files=None, display_infos=False, label=''): dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'valu... | Implement the Python class `MetadataHandler` described below.
Class description:
Implement the MetadataHandler class.
Method signatures and docstrings:
- def retrieve_metadata(list_of_files=None, display_infos=False, label=''): dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'valu... | 70a43a76eaf08f4ac63db3df7fbfb2e5cdb1216e | <|skeleton|>
class MetadataHandler:
def retrieve_metadata(list_of_files=None, display_infos=False, label=''):
"""dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'value': value, 'name': name}, 'metadata3_key': {'value': value, 'name': name}, ... }, ... }"""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetadataHandler:
def retrieve_metadata(list_of_files=None, display_infos=False, label=''):
"""dict = {'file1': {'metadata1_key': {'value': value, 'name': name}, 'metadata2_key': {'value': value, 'name': name}, 'metadata3_key': {'value': value, 'name': name}, ... }, ... }"""
if not list_of_file... | the_stack_v2_python_sparse | notebooks/__code/normalization/metadata_handler.py | neutronimaging/python_notebooks | train | 8 | |
8cd8d517e5f6b5fce4b6888148192fc295cb9545 | [
"if n == 1 or n == 0 or n == -1:\n return x ** n\nhalf = self.myPow(x, n // 2)\nmod = n % 2\nreturn half * half * x ** mod",
"if x == 0:\n return 0\nif n < 0:\n x, n = (1 / x, -n)\nres = 1\nwhile n:\n if n & 1:\n res *= x\n x *= x\n n >>= 1\nreturn res"
] | <|body_start_0|>
if n == 1 or n == 0 or n == -1:
return x ** n
half = self.myPow(x, n // 2)
mod = n % 2
return half * half * x ** mod
<|end_body_0|>
<|body_start_1|>
if x == 0:
return 0
if n < 0:
x, n = (1 / x, -n)
res = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def myPow(self, x: float, n: int) -> float:
"""二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:"""
<|body_0|>
def myPow1(self, x: float, n: int) -> float:
""":param x: -100 < x < 100 注意分析 x=0 情况 :param n: 注意分析 负指数情况 :return:"""
<|body... | stack_v2_sparse_classes_36k_train_026210 | 1,071 | no_license | [
{
"docstring": "二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:",
"name": "myPow",
"signature": "def myPow(self, x: float, n: int) -> float"
},
{
"docstring": ":param x: -100 < x < 100 注意分析 x=0 情况 :param n: 注意分析 负指数情况 :return:",
"name": "myPow1",
"signature": "def myPow1(... | 2 | stack_v2_sparse_classes_30k_train_013859 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x: float, n: int) -> float: 二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:
- def myPow1(self, x: float, n: int) -> float: :param x: -100 < x < 10... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def myPow(self, x: float, n: int) -> float: 二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:
- def myPow1(self, x: float, n: int) -> float: :param x: -100 < x < 10... | 4ca0ec2ab9510b12b7e8c65af52dee719f099ea6 | <|skeleton|>
class Solution:
def myPow(self, x: float, n: int) -> float:
"""二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:"""
<|body_0|>
def myPow1(self, x: float, n: int) -> float:
""":param x: -100 < x < 100 注意分析 x=0 情况 :param n: 注意分析 负指数情况 :return:"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def myPow(self, x: float, n: int) -> float:
"""二分递归相乘，不过仍然有大量重复运算 :param x: :param n: 指数；注意考虑 指数为负的情况 :return:"""
if n == 1 or n == 0 or n == -1:
return x ** n
half = self.myPow(x, n // 2)
mod = n % 2
return half * half * x ** mod
def myPow1(s... | the_stack_v2_python_sparse | offer/16-数值的整数次方.py | JDer-liuodngkai/LeetCode | train | 0 | |
27497175e67a23b396b5523e6ddffdfe17ca787a | [
"if hypothesis == '' or references == '':\n if self.metric.__name__ == 'wip':\n max_val = 0.0\n min_val = 1.0\n else:\n max_val = 1.0\n min_val = 0.0\n return _empty_values_score(hypothesis, references, min_val=max_val, max_val=min_val)\nscore = self.metric(truth=references, hyp... | <|body_start_0|>
if hypothesis == '' or references == '':
if self.metric.__name__ == 'wip':
max_val = 0.0
min_val = 1.0
else:
max_val = 1.0
min_val = 0.0
return _empty_values_score(hypothesis, references, min_val... | JIWERScore template metric class | JIWERScore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JIWERScore:
"""JIWERScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute JIWERScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hy... | stack_v2_sparse_classes_36k_train_026211 | 7,252 | permissive | [
{
"docstring": "Compute JIWERScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypothesis sentences reference (str): a reference sentence or a list of reference sentences kwargs: see complete list at: https://github.com/jitsi/jiwer/blob/1fd2a161fd21296640c... | 2 | stack_v2_sparse_classes_30k_train_006187 | Implement the Python class `JIWERScore` described below.
Class description:
JIWERScore template metric class
Method signatures and docstrings:
- def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float: Compute JIWERScore score of a hypothesis and a reference. Params... | Implement the Python class `JIWERScore` described below.
Class description:
JIWERScore template metric class
Method signatures and docstrings:
- def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float: Compute JIWERScore score of a hypothesis and a reference. Params... | bef8033d9b9d7ea9797b5a0fdc7558d388bb0bfd | <|skeleton|>
class JIWERScore:
"""JIWERScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute JIWERScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hy... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JIWERScore:
"""JIWERScore template metric class"""
def __call__(self, hypothesis: Union[str, List[str]], references: Union[str, List[str]], **kwargs) -> float:
"""Compute JIWERScore score of a hypothesis and a reference. Params: hypothesis (str): a hypothesis sentence or a list of hypothesis sent... | the_stack_v2_python_sparse | platiagro/metrics_nlp/base.py | platiagro/sdk | train | 1 |
2ec081459688116921fdaf8fccab8274c26377bd | [
"self.root = Node()\nfor word in words:\n insert(self.root, word)\nself.node_list = []",
"complete_found = False\nfor i in range(len(self.node_list) - 1, -1, -1):\n if letter in self.node_list[i].d:\n self.node_list[i] = self.node_list[i].d[letter]\n if self.node_list[i].complete:\n ... | <|body_start_0|>
self.root = Node()
for word in words:
insert(self.root, word)
self.node_list = []
<|end_body_0|>
<|body_start_1|>
complete_found = False
for i in range(len(self.node_list) - 1, -1, -1):
if letter in self.node_list[i].d:
se... | StreamChecker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.root = Node()
for word in words:
in... | stack_v2_sparse_classes_36k_train_026212 | 5,756 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type letter: str :rtype: bool",
"name": "query",
"signature": "def query(self, letter)"
}
] | 2 | null | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool | Implement the Python class `StreamChecker` described below.
Class description:
Implement the StreamChecker class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def query(self, letter): :type letter: str :rtype: bool
<|skeleton|>
class StreamChecker:
def __init__(self, w... | 3a2e75238a333843987c6413ab674a7e985c8c01 | <|skeleton|>
class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def query(self, letter):
""":type letter: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StreamChecker:
def __init__(self, words):
""":type words: List[str]"""
self.root = Node()
for word in words:
insert(self.root, word)
self.node_list = []
def query(self, letter):
""":type letter: str :rtype: bool"""
complete_found = False
... | the_stack_v2_python_sparse | coding_practice/tries/stream_of_characters.py | daveboat/interview_prep | train | 2 | |
0fbb2829d370ad36e4ee4d5a5ff212c23e4a335a | [
"super(MLP, self).__init__()\nself.hidden_sizes = configs.hidden_sizes\nself.input_size = configs.input_size\nself.output_size = configs.output_size\nself.hidden_activation = getattr(helper_functions, configs.hidden_activation) if 'hidden_activation' in configs.keys() else hidden_activation\nself.output_activation ... | <|body_start_0|>
super(MLP, self).__init__()
self.hidden_sizes = configs.hidden_sizes
self.input_size = configs.input_size
self.output_size = configs.output_size
self.hidden_activation = getattr(helper_functions, configs.hidden_activation) if 'hidden_activation' in configs.keys()... | Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (function): activation function of output layer hidden_layers (list): li... | MLP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLP:
"""Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (function): activation function of output... | stack_v2_sparse_classes_36k_train_026213 | 7,663 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, configs: ConfigDict, hidden_activation: Callable=F.relu, linear_layer: nn.Module=nn.Linear, use_output_layer: bool=True, n_category: int=-1, init_fn: Callable=init_layer_uniform)"
},
{
"docstring": "Forward method... | 2 | stack_v2_sparse_classes_30k_train_002632 | Implement the Python class `MLP` described below.
Class description:
Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (f... | Implement the Python class `MLP` described below.
Class description:
Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (f... | fdfac4e7056ee5a9d5b48b7b9653ce844a03ca22 | <|skeleton|>
class MLP:
"""Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (function): activation function of output... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLP:
"""Baseline of Multilayer perceptron. Attributes: input_size (int): size of input output_size (int): size of output layer hidden_sizes (list): sizes of hidden layers hidden_activation (function): activation function of hidden layers output_activation (function): activation function of output layer hidden... | the_stack_v2_python_sparse | rl_algorithms/common/networks/heads.py | medipixel/rl_algorithms | train | 525 |
cd009a2c2dd786937e4193a1038d2ff40d81b372 | [
"self.server_endpoint = server_endpoint\nself.treq_client = treq_client\nif self.treq_client is None:\n import treq\n self.treq_client = treq",
"payload = {'alarmTemplate': alarm_template, 'checkTemplate': check_template, 'policyId': policy_id}\nd = self.treq_client.post(append_segments(self.server_endpoint... | <|body_start_0|>
self.server_endpoint = server_endpoint
self.treq_client = treq_client
if self.treq_client is None:
import treq
self.treq_client = treq
<|end_body_0|>
<|body_start_1|>
payload = {'alarmTemplate': alarm_template, 'checkTemplate': check_template, 'p... | Client for Bobby | BobbyClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BobbyClient:
"""Client for Bobby"""
def __init__(self, server_endpoint, treq_client=None):
"""Create a Bobby Client :param server_endpoint: Endpoint to use"""
<|body_0|>
def create_policy(self, tenant_id, group_id, policy_id, check_template, alarm_template):
"""C... | stack_v2_sparse_classes_36k_train_026214 | 4,855 | permissive | [
{
"docstring": "Create a Bobby Client :param server_endpoint: Endpoint to use",
"name": "__init__",
"signature": "def __init__(self, server_endpoint, treq_client=None)"
},
{
"docstring": "Create a policy in Bobby. This means that Bobby will start to roll out alarms and checks across all of the s... | 4 | null | Implement the Python class `BobbyClient` described below.
Class description:
Client for Bobby
Method signatures and docstrings:
- def __init__(self, server_endpoint, treq_client=None): Create a Bobby Client :param server_endpoint: Endpoint to use
- def create_policy(self, tenant_id, group_id, policy_id, check_templat... | Implement the Python class `BobbyClient` described below.
Class description:
Client for Bobby
Method signatures and docstrings:
- def __init__(self, server_endpoint, treq_client=None): Create a Bobby Client :param server_endpoint: Endpoint to use
- def create_policy(self, tenant_id, group_id, policy_id, check_templat... | 7199cdd67255fe116dbcbedea660c13453671134 | <|skeleton|>
class BobbyClient:
"""Client for Bobby"""
def __init__(self, server_endpoint, treq_client=None):
"""Create a Bobby Client :param server_endpoint: Endpoint to use"""
<|body_0|>
def create_policy(self, tenant_id, group_id, policy_id, check_template, alarm_template):
"""C... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BobbyClient:
"""Client for Bobby"""
def __init__(self, server_endpoint, treq_client=None):
"""Create a Bobby Client :param server_endpoint: Endpoint to use"""
self.server_endpoint = server_endpoint
self.treq_client = treq_client
if self.treq_client is None:
imp... | the_stack_v2_python_sparse | otter/bobby.py | rackerlabs/otter | train | 20 |
ce64b155e92bbc5a4a0aa16c7ad6c746a4842352 | [
"self.get_model = get_model\nassert callable(get_model), get_model\nself.input_signature = input_signature\nself.target_signature = target_signature\nif trainer is None:\n nr_gpu = get_nr_gpu()\n if nr_gpu <= 1:\n trainer = SimpleTrainer()\n else:\n trainer = SyncMultiGPUTrainerParameterServe... | <|body_start_0|>
self.get_model = get_model
assert callable(get_model), get_model
self.input_signature = input_signature
self.target_signature = target_signature
if trainer is None:
nr_gpu = get_nr_gpu()
if nr_gpu <= 1:
trainer = SimpleTrai... | KerasModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KerasModel:
def __init__(self, get_model, input_signature=None, target_signature=None, input=None, trainer=None):
"""Args: get_model (input1, input2, ... -> keras.Model): A function which takes tensors, builds and returns a Keras model. It will be part of the tower function. input_signat... | stack_v2_sparse_classes_36k_train_026215 | 12,196 | permissive | [
{
"docstring": "Args: get_model (input1, input2, ... -> keras.Model): A function which takes tensors, builds and returns a Keras model. It will be part of the tower function. input_signature ([tf.TensorSpec]): required. The signature for inputs. target_signature ([tf.TensorSpec]): required. The signature for th... | 3 | null | Implement the Python class `KerasModel` described below.
Class description:
Implement the KerasModel class.
Method signatures and docstrings:
- def __init__(self, get_model, input_signature=None, target_signature=None, input=None, trainer=None): Args: get_model (input1, input2, ... -> keras.Model): A function which t... | Implement the Python class `KerasModel` described below.
Class description:
Implement the KerasModel class.
Method signatures and docstrings:
- def __init__(self, get_model, input_signature=None, target_signature=None, input=None, trainer=None): Args: get_model (input1, input2, ... -> keras.Model): A function which t... | 1547a54e8546494614ca31c984a1bfd1d0e24b77 | <|skeleton|>
class KerasModel:
def __init__(self, get_model, input_signature=None, target_signature=None, input=None, trainer=None):
"""Args: get_model (input1, input2, ... -> keras.Model): A function which takes tensors, builds and returns a Keras model. It will be part of the tower function. input_signat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KerasModel:
def __init__(self, get_model, input_signature=None, target_signature=None, input=None, trainer=None):
"""Args: get_model (input1, input2, ... -> keras.Model): A function which takes tensors, builds and returns a Keras model. It will be part of the tower function. input_signature ([tf.Tenso... | the_stack_v2_python_sparse | tensorpack/contrib/keras.py | tensorpack/tensorpack | train | 4,600 | |
63f29c22e7ae287a6a7d55727880a80d53550f8d | [
"users = models.CmAlarmUser.objects.all()\nserializer = serializers.CmAlarmUserSerializer(users, many=True)\nreturn Response(serializer.data)",
"serializer = serializers.CmAlarmUserSerializer(data=request.DATA)\nif serializer.is_valid():\n d_user_count = models.CmAlarmUser.objects.filter(phone=serializer.data[... | <|body_start_0|>
users = models.CmAlarmUser.objects.all()
serializer = serializers.CmAlarmUserSerializer(users, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = serializers.CmAlarmUserSerializer(data=request.DATA)
if serializer.is_valid():... | UserList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserList:
def get(self, request):
"""action : 9.6 get users list :param request: :return:"""
<|body_0|>
def post(self, request):
"""acrtion: 9.7 create a new alarm user :param request: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
users =... | stack_v2_sparse_classes_36k_train_026216 | 10,115 | no_license | [
{
"docstring": "action : 9.6 get users list :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "acrtion: 9.7 create a new alarm user :param request: :return:",
"name": "post",
"signature": "def post(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013030 | Implement the Python class `UserList` described below.
Class description:
Implement the UserList class.
Method signatures and docstrings:
- def get(self, request): action : 9.6 get users list :param request: :return:
- def post(self, request): acrtion: 9.7 create a new alarm user :param request: :return: | Implement the Python class `UserList` described below.
Class description:
Implement the UserList class.
Method signatures and docstrings:
- def get(self, request): action : 9.6 get users list :param request: :return:
- def post(self, request): acrtion: 9.7 create a new alarm user :param request: :return:
<|skeleton|... | 44bc38c2c04fcaa928f58aeb8165fc1fff64bbcd | <|skeleton|>
class UserList:
def get(self, request):
"""action : 9.6 get users list :param request: :return:"""
<|body_0|>
def post(self, request):
"""acrtion: 9.7 create a new alarm user :param request: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserList:
def get(self, request):
"""action : 9.6 get users list :param request: :return:"""
users = models.CmAlarmUser.objects.all()
serializer = serializers.CmAlarmUserSerializer(users, many=True)
return Response(serializer.data)
def post(self, request):
"""acrti... | the_stack_v2_python_sparse | trunk/monitor_web/cm_alarm/group_user_views.py | wuhongyang/iass-web | train | 0 | |
3a190a21cd5d7bf18adb6f16b73d18c3546493da | [
"assert cloud_name in equation.field_names, f'Field {cloud_name} does not exist in the equation set'\nassert rain_name in equation.field_names, f'Field {rain_name} does not exist in the equation set'\nself.cloud_idx = equation.field_names.index(cloud_name)\nself.rain_idx = equation.field_names.index(rain_name)\nVcl... | <|body_start_0|>
assert cloud_name in equation.field_names, f'Field {cloud_name} does not exist in the equation set'
assert rain_name in equation.field_names, f'Field {rain_name} does not exist in the equation set'
self.cloud_idx = equation.field_names.index(cloud_name)
self.rain_idx = e... | Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain concentration, and auto-accumulation, which is accelerated by the existence of rain... | Coalescence | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Coalescence:
"""Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain concentration, and auto-accumulation, which ... | stack_v2_sparse_classes_36k_train_026217 | 46,841 | permissive | [
{
"docstring": "Args: equation (:class:`PrognosticEquationSet`): the model's equation. cloud_name (str, optional): name of the cloud variable. Defaults to 'cloud_water'. rain_name (str, optional): name of the rain variable. Defaults to 'rain'. accretion (bool, optional): whether to include the accretion process... | 2 | stack_v2_sparse_classes_30k_train_012594 | Implement the Python class `Coalescence` described below.
Class description:
Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain conce... | Implement the Python class `Coalescence` described below.
Class description:
Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain conce... | ab93672a84d4a71019abad4249529403e4b0c8d7 | <|skeleton|>
class Coalescence:
"""Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain concentration, and auto-accumulation, which ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Coalescence:
"""Represents the coalescence of cloud droplets to form rain droplets. Coalescence is the process of forming rain droplets from cloud droplets. This scheme performs that process, using two parts: accretion, which is independent of the rain concentration, and auto-accumulation, which is accelerate... | the_stack_v2_python_sparse | gusto/physics.py | firedrakeproject/gusto | train | 10 |
aa320c154fbed1082647fa73b0e87b802b993cb9 | [
"lhs_match = lhs_match or Match.IGNORED\nrhs_match = rhs_match or Match.IGNORED\nif lhs_match == Match.IGNORED:\n return rhs_match\nif rhs_match == Match.IGNORED:\n return lhs_match\nif lhs_match == Match.FAIL:\n return Match.FAIL\nif rhs_match == Match.FAIL:\n return Match.FAIL\nreturn Match.PASS",
"... | <|body_start_0|>
lhs_match = lhs_match or Match.IGNORED
rhs_match = rhs_match or Match.IGNORED
if lhs_match == Match.IGNORED:
return rhs_match
if rhs_match == Match.IGNORED:
return lhs_match
if lhs_match == Match.FAIL:
return Match.FAIL
... | Internal enum. Represents the result of a match. | Match | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Match:
"""Internal enum. Represents the result of a match."""
def combine(lhs_match, rhs_match):
"""Combines to match levels into a single match level"""
<|body_0|>
def from_bool(passed):
"""Constructs a match description from a boolean value"""
<|body_1|... | stack_v2_sparse_classes_36k_train_026218 | 42,043 | permissive | [
{
"docstring": "Combines to match levels into a single match level",
"name": "combine",
"signature": "def combine(lhs_match, rhs_match)"
},
{
"docstring": "Constructs a match description from a boolean value",
"name": "from_bool",
"signature": "def from_bool(passed)"
},
{
"docstr... | 3 | null | Implement the Python class `Match` described below.
Class description:
Internal enum. Represents the result of a match.
Method signatures and docstrings:
- def combine(lhs_match, rhs_match): Combines to match levels into a single match level
- def from_bool(passed): Constructs a match description from a boolean value... | Implement the Python class `Match` described below.
Class description:
Internal enum. Represents the result of a match.
Method signatures and docstrings:
- def combine(lhs_match, rhs_match): Combines to match levels into a single match level
- def from_bool(passed): Constructs a match description from a boolean value... | 69c082d2bf9b9985db77d1d25a3f423ecf016e00 | <|skeleton|>
class Match:
"""Internal enum. Represents the result of a match."""
def combine(lhs_match, rhs_match):
"""Combines to match levels into a single match level"""
<|body_0|>
def from_bool(passed):
"""Constructs a match description from a boolean value"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Match:
"""Internal enum. Represents the result of a match."""
def combine(lhs_match, rhs_match):
"""Combines to match levels into a single match level"""
lhs_match = lhs_match or Match.IGNORED
rhs_match = rhs_match or Match.IGNORED
if lhs_match == Match.IGNORED:
... | the_stack_v2_python_sparse | testplan/common/utils/comparison.py | morganstanley/testplan | train | 78 |
00cff3ed654eb303c0b8ab1bb1f53329d98f1710 | [
"super(SqueezeNomenclature, self).build_from_string(name)\nif len(self.tokens) > 1:\n self.tokens = self.tokens[:-1]",
"new_tokens = []\nfor token in tokens:\n if len(token) > 1:\n new_token = token[0].upper() + token[1:]\n else:\n new_token = token.upper()\n new_tokens.append(new_token)... | <|body_start_0|>
super(SqueezeNomenclature, self).build_from_string(name)
if len(self.tokens) > 1:
self.tokens = self.tokens[:-1]
<|end_body_0|>
<|body_start_1|>
new_tokens = []
for token in tokens:
if len(token) > 1:
new_token = token[0].upper() ... | SqueezeNomenclature | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqueezeNomenclature:
def build_from_string(self, name):
"""In Squeeze nomenclature, the last token is always the type of the object."""
<|body_0|>
def _join_tokens(self, tokens):
"""In Squeeze nomenclature, the first letter of each token is always in uppercase."""
... | stack_v2_sparse_classes_36k_train_026219 | 6,903 | permissive | [
{
"docstring": "In Squeeze nomenclature, the last token is always the type of the object.",
"name": "build_from_string",
"signature": "def build_from_string(self, name)"
},
{
"docstring": "In Squeeze nomenclature, the first letter of each token is always in uppercase.",
"name": "_join_tokens... | 2 | stack_v2_sparse_classes_30k_train_021115 | Implement the Python class `SqueezeNomenclature` described below.
Class description:
Implement the SqueezeNomenclature class.
Method signatures and docstrings:
- def build_from_string(self, name): In Squeeze nomenclature, the last token is always the type of the object.
- def _join_tokens(self, tokens): In Squeeze no... | Implement the Python class `SqueezeNomenclature` described below.
Class description:
Implement the SqueezeNomenclature class.
Method signatures and docstrings:
- def build_from_string(self, name): In Squeeze nomenclature, the last token is always the type of the object.
- def _join_tokens(self, tokens): In Squeeze no... | 132911d908ebc8eebe7a29923936ce03d513c112 | <|skeleton|>
class SqueezeNomenclature:
def build_from_string(self, name):
"""In Squeeze nomenclature, the last token is always the type of the object."""
<|body_0|>
def _join_tokens(self, tokens):
"""In Squeeze nomenclature, the first letter of each token is always in uppercase."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SqueezeNomenclature:
def build_from_string(self, name):
"""In Squeeze nomenclature, the last token is always the type of the object."""
super(SqueezeNomenclature, self).build_from_string(name)
if len(self.tokens) > 1:
self.tokens = self.tokens[:-1]
def _join_tokens(sel... | the_stack_v2_python_sparse | omtk/rigs/rigSqueeze.py | fsanges/omtk | train | 2 | |
ecc7c70f5f32e53034797b5c49abba77c7892873 | [
"ref_counts, alt_counts = AD\ntotal_counts = ref_counts + alt_counts\nif not total_counts:\n return 0.0\nreturn alt_counts / total_counts",
"self.name = name\nself.record = record\ntarget_sample = [self.record.samples[index] for index in range(len(self.record.samples)) if self.record.samples[index].name == sel... | <|body_start_0|>
ref_counts, alt_counts = AD
total_counts = ref_counts + alt_counts
if not total_counts:
return 0.0
return alt_counts / total_counts
<|end_body_0|>
<|body_start_1|>
self.name = name
self.record = record
target_sample = [self.record.sam... | Object to calculate and store FORMAT information for samples associated with a VCF record (Variant) | Sample | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sample:
"""Object to calculate and store FORMAT information for samples associated with a VCF record (Variant)"""
def AF_from_AD(AD):
"""Calculate allele frequency from AD FORMAT field value"""
<|body_0|>
def __init__(self, name, record, caller):
"""Initialize th... | stack_v2_sparse_classes_36k_train_026220 | 25,776 | no_license | [
{
"docstring": "Calculate allele frequency from AD FORMAT field value",
"name": "AF_from_AD",
"signature": "def AF_from_AD(AD)"
},
{
"docstring": "Initialize this object and calculate Args: name (str): the name of the sample from the VCF record (pysam.VariantRecord): record with which this sampl... | 6 | stack_v2_sparse_classes_30k_train_003024 | Implement the Python class `Sample` described below.
Class description:
Object to calculate and store FORMAT information for samples associated with a VCF record (Variant)
Method signatures and docstrings:
- def AF_from_AD(AD): Calculate allele frequency from AD FORMAT field value
- def __init__(self, name, record, c... | Implement the Python class `Sample` described below.
Class description:
Object to calculate and store FORMAT information for samples associated with a VCF record (Variant)
Method signatures and docstrings:
- def AF_from_AD(AD): Calculate allele frequency from AD FORMAT field value
- def __init__(self, name, record, c... | 4d7989c5e83cdf6fd19ef50df4563a03b326c0c0 | <|skeleton|>
class Sample:
"""Object to calculate and store FORMAT information for samples associated with a VCF record (Variant)"""
def AF_from_AD(AD):
"""Calculate allele frequency from AD FORMAT field value"""
<|body_0|>
def __init__(self, name, record, caller):
"""Initialize th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sample:
"""Object to calculate and store FORMAT information for samples associated with a VCF record (Variant)"""
def AF_from_AD(AD):
"""Calculate allele frequency from AD FORMAT field value"""
ref_counts, alt_counts = AD
total_counts = ref_counts + alt_counts
if not total... | the_stack_v2_python_sparse | scripts/consensus_merge.py | kids-first/kf-somatic-workflow | train | 13 |
65cde5a8b5950a4d4eaaa10a448481b427392782 | [
"count = 0\nresult = []\nfor i in S[::-1]:\n if i != '-':\n count += 1\n result.append(i.upper())\n if count == K:\n result.append('-')\n count = 0\nresult.reverse()\nreturn ''.join(result).lstrip('-')",
"S = S.replace('-', '').upper()\nn = len(S)\nnumDash = n // K\nl... | <|body_start_0|>
count = 0
result = []
for i in S[::-1]:
if i != '-':
count += 1
result.append(i.upper())
if count == K:
result.append('-')
count = 0
result.reverse()
return ''.joi... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def licenseKeyFormatting(self, S, K):
""":type S: str :type K: int :rtype: str 75ms"""
<|body_0|>
def licenseKeyFormatting_1(self, S, K):
""":type S: str :type K: int :rtype: str 32ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
count =... | stack_v2_sparse_classes_36k_train_026221 | 2,695 | no_license | [
{
"docstring": ":type S: str :type K: int :rtype: str 75ms",
"name": "licenseKeyFormatting",
"signature": "def licenseKeyFormatting(self, S, K)"
},
{
"docstring": ":type S: str :type K: int :rtype: str 32ms",
"name": "licenseKeyFormatting_1",
"signature": "def licenseKeyFormatting_1(self... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def licenseKeyFormatting(self, S, K): :type S: str :type K: int :rtype: str 75ms
- def licenseKeyFormatting_1(self, S, K): :type S: str :type K: int :rtype: str 32ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def licenseKeyFormatting(self, S, K): :type S: str :type K: int :rtype: str 75ms
- def licenseKeyFormatting_1(self, S, K): :type S: str :type K: int :rtype: str 32ms
<|skeleton|... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def licenseKeyFormatting(self, S, K):
""":type S: str :type K: int :rtype: str 75ms"""
<|body_0|>
def licenseKeyFormatting_1(self, S, K):
""":type S: str :type K: int :rtype: str 32ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def licenseKeyFormatting(self, S, K):
""":type S: str :type K: int :rtype: str 75ms"""
count = 0
result = []
for i in S[::-1]:
if i != '-':
count += 1
result.append(i.upper())
if count == K:
... | the_stack_v2_python_sparse | LicenseKeyFormatting_MID_482.py | 953250587/leetcode-python | train | 2 | |
3e56e0bc6a88cfed99a3b9a024311f14daa90b10 | [
"super(Group_RDB, self).__init__()\nself.InChan = InChannel\nself.OutChan = OutChannel\nself.G = growRate\nself.C = nConvLayers\nif self.InChan != self.G:\n self.InConv = nn.Conv2d(self.InChan, self.G, 1, padding=0, stride=1)\nif self.OutChan != self.G and self.OutChan != self.InChan:\n self.OutConv = nn.Conv... | <|body_start_0|>
super(Group_RDB, self).__init__()
self.InChan = InChannel
self.OutChan = OutChannel
self.G = growRate
self.C = nConvLayers
if self.InChan != self.G:
self.InConv = nn.Conv2d(self.InChan, self.G, 1, padding=0, stride=1)
if self.OutChan !... | Group residual dense block. | Group_RDB | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRat... | stack_v2_sparse_classes_36k_train_026222 | 13,650 | permissive | [
{
"docstring": "Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRate: growth rate of block :type growRate: int :param nConvLayers: the number of convlution layer :type nConvLayers: int :param kSize: ker... | 2 | stack_v2_sparse_classes_30k_train_003825 | Implement the Python class `Group_RDB` described below.
Class description:
Group residual dense block.
Method signatures and docstrings:
- def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: chan... | Implement the Python class `Group_RDB` described below.
Class description:
Group residual dense block.
Method signatures and docstrings:
- def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3): Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: chan... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Group_RDB:
"""Group residual dense block."""
def __init__(self, InChannel, OutChannel, growRate, nConvLayers, kSize=3):
"""Initialize Block. :param InChannel: channel number of input :type InChannel: int :param OutChannel: channel number of output :type OutChannel: int :param growRate: growth rat... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/esrbodys/erdb_esr.py | Huawei-Ascend/modelzoo | train | 1 |
e5077a26d041cc9bbed47296fc66fa74cea5ead3 | [
"super().__init__(input_tensor_spec=input_tensor_spec, name=name)\nif kernel_initializer is None:\n kernel_initializer = functools.partial(variance_scaling_init, mode='fan_in', distribution='truncated_normal', nonlinearity=activation)\nself._param_length = None\nself._conv_net = None\nif conv_layer_params:\n ... | <|body_start_0|>
super().__init__(input_tensor_spec=input_tensor_spec, name=name)
if kernel_initializer is None:
kernel_initializer = functools.partial(variance_scaling_init, mode='fan_in', distribution='truncated_normal', nonlinearity=activation)
self._param_length = None
se... | ParamNetwork | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParamNetwork:
def __init__(self, input_tensor_spec, conv_layer_params=None, fc_layer_params=None, use_conv_bias=False, use_conv_ln=False, use_fc_bias=True, use_fc_ln=False, n_groups=None, activation=torch.relu_, kernel_initializer=None, last_layer_size=None, last_activation=None, last_use_bias=T... | stack_v2_sparse_classes_36k_train_026223 | 14,523 | permissive | [
{
"docstring": "A network with Fc and conv2D layers that does not maintain its own network parameters, but accepts them from users. If the given parameter tensor has an extra batch dimension (first dimension), it performs parallel operations. Args: input_tensor_spec (nested TensorSpec): the (nested) tensor spec... | 4 | stack_v2_sparse_classes_30k_train_000404 | Implement the Python class `ParamNetwork` described below.
Class description:
Implement the ParamNetwork class.
Method signatures and docstrings:
- def __init__(self, input_tensor_spec, conv_layer_params=None, fc_layer_params=None, use_conv_bias=False, use_conv_ln=False, use_fc_bias=True, use_fc_ln=False, n_groups=No... | Implement the Python class `ParamNetwork` described below.
Class description:
Implement the ParamNetwork class.
Method signatures and docstrings:
- def __init__(self, input_tensor_spec, conv_layer_params=None, fc_layer_params=None, use_conv_bias=False, use_conv_ln=False, use_fc_bias=True, use_fc_ln=False, n_groups=No... | b00ff2fa5e660de31020338ba340263183fbeaa4 | <|skeleton|>
class ParamNetwork:
def __init__(self, input_tensor_spec, conv_layer_params=None, fc_layer_params=None, use_conv_bias=False, use_conv_ln=False, use_fc_bias=True, use_fc_ln=False, n_groups=None, activation=torch.relu_, kernel_initializer=None, last_layer_size=None, last_activation=None, last_use_bias=T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParamNetwork:
def __init__(self, input_tensor_spec, conv_layer_params=None, fc_layer_params=None, use_conv_bias=False, use_conv_ln=False, use_fc_bias=True, use_fc_ln=False, n_groups=None, activation=torch.relu_, kernel_initializer=None, last_layer_size=None, last_activation=None, last_use_bias=True, last_use_... | the_stack_v2_python_sparse | alf/networks/param_networks.py | HorizonRobotics/alf | train | 288 | |
10164d4fee1539138eb78fa575966d63b226c8e1 | [
"self.name = name\nself.protocol = protocol\nself.public_port = public_port\nself.local_ip = local_ip\nself.local_port = local_port\nself.allowed_ips = allowed_ips",
"if dictionary is None:\n return None\nname = dictionary.get('name')\nprotocol = dictionary.get('protocol')\npublic_port = dictionary.get('public... | <|body_start_0|>
self.name = name
self.protocol = protocol
self.public_port = public_port
self.local_ip = local_ip
self.local_port = local_port
self.allowed_ips = allowed_ips
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
n... | Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving on the WAN local_ip (string): Local IP address to which traffic will be forwarde... | PortRuleModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortRuleModel:
"""Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving on the WAN local_ip (string): Local IP ... | stack_v2_sparse_classes_36k_train_026224 | 3,031 | permissive | [
{
"docstring": "Constructor for the PortRuleModel class",
"name": "__init__",
"signature": "def __init__(self, name=None, protocol=None, public_port=None, local_ip=None, local_port=None, allowed_ips=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (d... | 2 | null | Implement the Python class `PortRuleModel` described below.
Class description:
Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving ... | Implement the Python class `PortRuleModel` described below.
Class description:
Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving ... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class PortRuleModel:
"""Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving on the WAN local_ip (string): Local IP ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PortRuleModel:
"""Implementation of the 'PortRule' model. TODO: type model description here. Attributes: name (string): A description of the rule protocol (Protocol3Enum): 'tcp' or 'udp' public_port (string): Destination port of the traffic that is arriving on the WAN local_ip (string): Local IP address to wh... | the_stack_v2_python_sparse | meraki_sdk/models/port_rule_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
5ad93cb5d267f0bfd68bc11e8230f81b97927e97 | [
"n = len(nums)\nif n < 3:\n return False\nleft_min = nums[0]\nrights = SortedList(nums[2:])\nfor j in range(1, n - 1):\n if left_min < nums[j]:\n idx = rights.bisect_right(left_min)\n if idx != len(rights) and rights[idx] < nums[j]:\n return True\n left_min = min(left_min, nums[j])... | <|body_start_0|>
n = len(nums)
if n < 3:
return False
left_min = nums[0]
rights = SortedList(nums[2:])
for j in range(1, n - 1):
if left_min < nums[j]:
idx = rights.bisect_right(left_min)
if idx != len(rights) and rights[idx... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find132pattern(self, nums: List[int]) -> bool:
"""O(nlogn)"""
<|body_0|>
def find132pattern(self, nums: List[int]) -> bool:
"""O(n) 单调栈"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums)
if n < 3:
return ... | stack_v2_sparse_classes_36k_train_026225 | 1,107 | no_license | [
{
"docstring": "O(nlogn)",
"name": "find132pattern",
"signature": "def find132pattern(self, nums: List[int]) -> bool"
},
{
"docstring": "O(n) 单调栈",
"name": "find132pattern",
"signature": "def find132pattern(self, nums: List[int]) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find132pattern(self, nums: List[int]) -> bool: O(nlogn)
- def find132pattern(self, nums: List[int]) -> bool: O(n) 单调栈 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find132pattern(self, nums: List[int]) -> bool: O(nlogn)
- def find132pattern(self, nums: List[int]) -> bool: O(n) 单调栈
<|skeleton|>
class Solution:
def find132pattern(se... | 26a467dfe8acd8ae4be0cd2784d79eebf09c06ce | <|skeleton|>
class Solution:
def find132pattern(self, nums: List[int]) -> bool:
"""O(nlogn)"""
<|body_0|>
def find132pattern(self, nums: List[int]) -> bool:
"""O(n) 单调栈"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def find132pattern(self, nums: List[int]) -> bool:
"""O(nlogn)"""
n = len(nums)
if n < 3:
return False
left_min = nums[0]
rights = SortedList(nums[2:])
for j in range(1, n - 1):
if left_min < nums[j]:
idx = right... | the_stack_v2_python_sparse | FuckLeetcode/456.132 模式.py | Alex-Beng/ojs | train | 0 | |
d0b3d3db9aab6110be1759054cc99c17449711d2 | [
"super(SemanticLidar, self).__init__(carla_actor=carla_actor, parent=parent, node=node, synchronous_mode=synchronous_mode, prefix='semantic_lidar/' + carla_actor.attributes.get('role_name'))\nself.semantic_lidar_publisher = rospy.Publisher(self.get_topic_prefix() + '/point_cloud', PointCloud2, queue_size=10)\nself.... | <|body_start_0|>
super(SemanticLidar, self).__init__(carla_actor=carla_actor, parent=parent, node=node, synchronous_mode=synchronous_mode, prefix='semantic_lidar/' + carla_actor.attributes.get('role_name'))
self.semantic_lidar_publisher = rospy.Publisher(self.get_topic_prefix() + '/point_cloud', PointCl... | Actor implementation details for semantic lidars | SemanticLidar | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SemanticLidar:
"""Actor implementation details for semantic lidars"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge... | stack_v2_sparse_classes_36k_train_026226 | 5,360 | permissive | [
{
"docstring": "Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent :param node: node-handle :type node: carla_ros_bridge.CarlaRosBridge",
"name": "__init__",
"signature": "def __init__(self, carla_acto... | 2 | stack_v2_sparse_classes_30k_train_018951 | Implement the Python class `SemanticLidar` described below.
Class description:
Actor implementation details for semantic lidars
Method signatures and docstrings:
- def __init__(self, carla_actor, parent, node, synchronous_mode): Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param ... | Implement the Python class `SemanticLidar` described below.
Class description:
Actor implementation details for semantic lidars
Method signatures and docstrings:
- def __init__(self, carla_actor, parent, node, synchronous_mode): Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param ... | 65ba2fdb2ca24907083bc277ec333294ab174fa6 | <|skeleton|>
class SemanticLidar:
"""Actor implementation details for semantic lidars"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SemanticLidar:
"""Actor implementation details for semantic lidars"""
def __init__(self, carla_actor, parent, node, synchronous_mode):
"""Constructor :param carla_actor: carla actor object :type carla_actor: carla.Actor :param parent: the parent of this :type parent: carla_ros_bridge.Parent :para... | the_stack_v2_python_sparse | ros/ros-bridge/carla_ros_bridge/src/carla_ros_bridge/lidar.py | Essentia-Laboratory/intelligent-embedded-systems | train | 3 |
3d6cb4a82092bed82b0b7818f2f697f3293a3073 | [
"for pair in self.non_infinite_loop_pairs:\n self.assertFalse(results_in_infinite_loop(pair[0], pair[1]))\n self.assertTrue(is_power_of_two(pair[0] + pair[1]))",
"for pair in self.infinite_loop_pairs:\n self.assertTrue(results_in_infinite_loop(pair[0], pair[1]))\n self.assertFalse(is_power_of_two(pair... | <|body_start_0|>
for pair in self.non_infinite_loop_pairs:
self.assertFalse(results_in_infinite_loop(pair[0], pair[1]))
self.assertTrue(is_power_of_two(pair[0] + pair[1]))
<|end_body_0|>
<|body_start_1|>
for pair in self.infinite_loop_pairs:
self.assertTrue(results_i... | LoopTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoopTests:
def test_no_loop_if_sum_is_power_of_two(self):
"""Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the sum of the pairs are powers of 2"""
<|body_0|>
def test_loop_if_sum_is_not_power_of_... | stack_v2_sparse_classes_36k_train_026227 | 23,320 | no_license | [
{
"docstring": "Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the sum of the pairs are powers of 2",
"name": "test_no_loop_if_sum_is_power_of_two",
"signature": "def test_no_loop_if_sum_is_power_of_two(self)"
},
{
"d... | 2 | stack_v2_sparse_classes_30k_train_019731 | Implement the Python class `LoopTests` described below.
Class description:
Implement the LoopTests class.
Method signatures and docstrings:
- def test_no_loop_if_sum_is_power_of_two(self): Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the... | Implement the Python class `LoopTests` described below.
Class description:
Implement the LoopTests class.
Method signatures and docstrings:
- def test_no_loop_if_sum_is_power_of_two(self): Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the... | d8b9bb69f9ca12565200e99efb575988de10185e | <|skeleton|>
class LoopTests:
def test_no_loop_if_sum_is_power_of_two(self):
"""Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the sum of the pairs are powers of 2"""
<|body_0|>
def test_loop_if_sum_is_not_power_of_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoopTests:
def test_no_loop_if_sum_is_power_of_two(self):
"""Do not loop when the sum of the pair of numbers IS a power of 2 i.e., if the pair of numbers will NOT enter an infinite loop, the sum of the pairs are powers of 2"""
for pair in self.non_infinite_loop_pairs:
self.assertFa... | the_stack_v2_python_sparse | Level_4/7_DistractTheTrainers/solution.py | ken-power/Foobar_Challenge | train | 5 | |
f0680e6efd13e740ed9c035196b21bbc77487efe | [
"if not Path('state.dump').exists():\n logger.info('CHECK: dump file does not exist, creating a new one')\n engine_data = os.environ.get('postgres')\n psql = create_engine(engine_data, connect_args={'options': '-csearch_path=content'})\n tables_states = {}\n which_time_to_get = {'film_work': 'min', '... | <|body_start_0|>
if not Path('state.dump').exists():
logger.info('CHECK: dump file does not exist, creating a new one')
engine_data = os.environ.get('postgres')
psql = create_engine(engine_data, connect_args={'options': '-csearch_path=content'})
tables_states = {}... | BaseStorage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseStorage:
def get_initial_data(self):
"""If not yet exist creates dump file with initial update dates in psql :return: None"""
<|body_0|>
def save_state(self, updated_at: str) -> None:
"""Saves key:value of a state. All states are in one file if form: table_name: ... | stack_v2_sparse_classes_36k_train_026228 | 2,737 | no_license | [
{
"docstring": "If not yet exist creates dump file with initial update dates in psql :return: None",
"name": "get_initial_data",
"signature": "def get_initial_data(self)"
},
{
"docstring": "Saves key:value of a state. All states are in one file if form: table_name: updated_at If file with state ... | 3 | stack_v2_sparse_classes_30k_train_008107 | Implement the Python class `BaseStorage` described below.
Class description:
Implement the BaseStorage class.
Method signatures and docstrings:
- def get_initial_data(self): If not yet exist creates dump file with initial update dates in psql :return: None
- def save_state(self, updated_at: str) -> None: Saves key:va... | Implement the Python class `BaseStorage` described below.
Class description:
Implement the BaseStorage class.
Method signatures and docstrings:
- def get_initial_data(self): If not yet exist creates dump file with initial update dates in psql :return: None
- def save_state(self, updated_at: str) -> None: Saves key:va... | 4ddc8a77e5a9e9bc2a900c7bb6ffbcf5999e8c89 | <|skeleton|>
class BaseStorage:
def get_initial_data(self):
"""If not yet exist creates dump file with initial update dates in psql :return: None"""
<|body_0|>
def save_state(self, updated_at: str) -> None:
"""Saves key:value of a state. All states are in one file if form: table_name: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseStorage:
def get_initial_data(self):
"""If not yet exist creates dump file with initial update dates in psql :return: None"""
if not Path('state.dump').exists():
logger.info('CHECK: dump file does not exist, creating a new one')
engine_data = os.environ.get('postgre... | the_stack_v2_python_sparse | postgres_to_es/state_tracking.py | maffka123/Admin_panel_sprint_2 | train | 0 | |
0d7435c9c3f78fea8212d02288beb662458c31ff | [
"message = get_object_or_404(Message, pk=message_id)\nserializer = MessageSerializer(message)\nreturn Response(serializer.data)",
"message = get_object_or_404(Event, pk=message_id)\nmessage.delete()\nreturn Response(status=status.HTTP_204_NO_CONTENT)"
] | <|body_start_0|>
message = get_object_or_404(Message, pk=message_id)
serializer = MessageSerializer(message)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
message = get_object_or_404(Event, pk=message_id)
message.delete()
return Response(status=status.... | MessageDetail | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageDetail:
def get(self, request, message_id, format=None):
"""Get message detail --- serializer: administrator.serializers.MessageSerializer"""
<|body_0|>
def delete(self, request, message_id, format=None):
"""Delete message (you cannot revert this change) --- s... | stack_v2_sparse_classes_36k_train_026229 | 30,608 | permissive | [
{
"docstring": "Get message detail --- serializer: administrator.serializers.MessageSerializer",
"name": "get",
"signature": "def get(self, request, message_id, format=None)"
},
{
"docstring": "Delete message (you cannot revert this change) --- serializer: administrator.serializers.MessageSerial... | 2 | stack_v2_sparse_classes_30k_train_008332 | Implement the Python class `MessageDetail` described below.
Class description:
Implement the MessageDetail class.
Method signatures and docstrings:
- def get(self, request, message_id, format=None): Get message detail --- serializer: administrator.serializers.MessageSerializer
- def delete(self, request, message_id, ... | Implement the Python class `MessageDetail` described below.
Class description:
Implement the MessageDetail class.
Method signatures and docstrings:
- def get(self, request, message_id, format=None): Get message detail --- serializer: administrator.serializers.MessageSerializer
- def delete(self, request, message_id, ... | 73728463badb3bfd4413aa0f7aeb44a9606fdfea | <|skeleton|>
class MessageDetail:
def get(self, request, message_id, format=None):
"""Get message detail --- serializer: administrator.serializers.MessageSerializer"""
<|body_0|>
def delete(self, request, message_id, format=None):
"""Delete message (you cannot revert this change) --- s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessageDetail:
def get(self, request, message_id, format=None):
"""Get message detail --- serializer: administrator.serializers.MessageSerializer"""
message = get_object_or_404(Message, pk=message_id)
serializer = MessageSerializer(message)
return Response(serializer.data)
... | the_stack_v2_python_sparse | administrator/views.py | belatrix/BackendAllStars | train | 5 | |
fff124458b642f6f1196eccbc6244b29d9a0c547 | [
"self.input = input_object\nself.output = output_object\nreturn self.handle()",
"self.output = PyStratumStyle(self.input, self.output)\ncommand = self.get_application().find('constants')\nret = command.execute(self.input, self.output)\nif ret:\n return ret\ncommand = self.get_application().find('loader')\nret ... | <|body_start_0|>
self.input = input_object
self.output = output_object
return self.handle()
<|end_body_0|>
<|body_start_1|>
self.output = PyStratumStyle(self.input, self.output)
command = self.get_application().find('constants')
ret = command.execute(self.input, self.out... | Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines} | PyStratumCommand | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PyStratumCommand:
"""Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines}"""
def execute(self, input_object: Input, output_object: Output) -> int:
"""Executes this command."""
... | stack_v2_sparse_classes_36k_train_026230 | 1,572 | permissive | [
{
"docstring": "Executes this command.",
"name": "execute",
"signature": "def execute(self, input_object: Input, output_object: Output) -> int"
},
{
"docstring": "Executes the actual Stratum program.",
"name": "handle",
"signature": "def handle(self) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_004828 | Implement the Python class `PyStratumCommand` described below.
Class description:
Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines}
Method signatures and docstrings:
- def execute(self, input_object: Input, output_o... | Implement the Python class `PyStratumCommand` described below.
Class description:
Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines}
Method signatures and docstrings:
- def execute(self, input_object: Input, output_o... | 52484003b431f2c42c1c29959fe7a2ba3bd38515 | <|skeleton|>
class PyStratumCommand:
"""Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines}"""
def execute(self, input_object: Input, output_object: Output) -> int:
"""Executes this command."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PyStratumCommand:
"""Loads stored routines and generates a wrapper class stratum {config_file : The stratum configuration file} {file_names?* : Sources with stored routines}"""
def execute(self, input_object: Input, output_object: Output) -> int:
"""Executes this command."""
self.input = ... | the_stack_v2_python_sparse | pystratum/command/PyStratumCommand.py | cryptobuks1/py-stratum | train | 0 |
571decb2462cdbde483836a9cc776f31c84606d3 | [
"dp = [-100 for _ in range(len(nums))]\ndp[0] = nums[0]\nfor i in range(1, len(nums)):\n for j in range(i + 1):\n dp[i] = max([dp[i], sum(nums[j:i + 1])])\nreturn max(dp)",
"dp = [-100 for _ in range(len(nums))]\ndp[0] = nums[0]\nfor i in range(1, len(nums)):\n dp[i] = dp[i - 1] + max(nums[i - 1], 0)... | <|body_start_0|>
dp = [-100 for _ in range(len(nums))]
dp[0] = nums[0]
for i in range(1, len(nums)):
for j in range(i + 1):
dp[i] = max([dp[i], sum(nums[j:i + 1])])
return max(dp)
<|end_body_0|>
<|body_start_1|>
dp = [-100 for _ in range(len(nums))]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray_fail(self, nums):
"""暴力法 :param nums: :return:"""
<|body_0|>
def maxSubArray_self(self, nums):
"""暴力法 :param nums: :return:"""
<|body_1|>
def maxSubArray(self, nums):
"""f(n+1) 只与 f(n) 与 nums[n+1]有关 只要nums[n+1]>0 则f(n)必然... | stack_v2_sparse_classes_36k_train_026231 | 2,523 | no_license | [
{
"docstring": "暴力法 :param nums: :return:",
"name": "maxSubArray_fail",
"signature": "def maxSubArray_fail(self, nums)"
},
{
"docstring": "暴力法 :param nums: :return:",
"name": "maxSubArray_self",
"signature": "def maxSubArray_self(self, nums)"
},
{
"docstring": "f(n+1) 只与 f(n) 与 n... | 3 | stack_v2_sparse_classes_30k_val_000628 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray_fail(self, nums): 暴力法 :param nums: :return:
- def maxSubArray_self(self, nums): 暴力法 :param nums: :return:
- def maxSubArray(self, nums): f(n+1) 只与 f(n) 与 nums[n+1... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray_fail(self, nums): 暴力法 :param nums: :return:
- def maxSubArray_self(self, nums): 暴力法 :param nums: :return:
- def maxSubArray(self, nums): f(n+1) 只与 f(n) 与 nums[n+1... | e12ead66d28175d34b51eac4ccdd6de06eb4d92d | <|skeleton|>
class Solution:
def maxSubArray_fail(self, nums):
"""暴力法 :param nums: :return:"""
<|body_0|>
def maxSubArray_self(self, nums):
"""暴力法 :param nums: :return:"""
<|body_1|>
def maxSubArray(self, nums):
"""f(n+1) 只与 f(n) 与 nums[n+1]有关 只要nums[n+1]>0 则f(n)必然... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray_fail(self, nums):
"""暴力法 :param nums: :return:"""
dp = [-100 for _ in range(len(nums))]
dp[0] = nums[0]
for i in range(1, len(nums)):
for j in range(i + 1):
dp[i] = max([dp[i], sum(nums[j:i + 1])])
return max(dp)
... | the_stack_v2_python_sparse | df_42_maxSubArray.py | zhenglinghan/leetcode_jianzhi_Offer | train | 2 | |
89d9756f78aab8677e4c58945eb4814f305a3da6 | [
"l1 = len(word1)\nl2 = len(word2)\ndp = [[0 for i in range(l1 + 1)] for i in range(l2 + 1)]\nfor i in range(1, l1 + 1):\n dp[0][i] = i\nfor i in range(1, l2 + 1):\n dp[i][0] = i\nfor i in range(1, l2 + 1):\n for j in range(1, l1 + 1):\n if word2[i - 1] == word1[j - 1]:\n dp[i][j] = dp[i -... | <|body_start_0|>
l1 = len(word1)
l2 = len(word2)
dp = [[0 for i in range(l1 + 1)] for i in range(l2 + 1)]
for i in range(1, l1 + 1):
dp[0][i] = i
for i in range(1, l2 + 1):
dp[i][0] = i
for i in range(1, l2 + 1):
for j in range(1, l1 + ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance_self(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_026232 | 1,819 | no_license | [
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance",
"signature": "def minDistance(self, word1, word2)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance_self",
"signature": "def minDistance_self(self, word1, word2)"... | 2 | stack_v2_sparse_classes_30k_train_014924 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance_self(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance_self(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|sk... | ea492ec864b50547214ecbbb2cdeeac21e70229b | <|skeleton|>
class Solution:
def minDistance(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance_self(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minDistance(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
l1 = len(word1)
l2 = len(word2)
dp = [[0 for i in range(l1 + 1)] for i in range(l2 + 1)]
for i in range(1, l1 + 1):
dp[0][i] = i
for i in range(1, l2 +... | the_stack_v2_python_sparse | 72_edit_distance/sol.py | lianke123321/leetcode_sol | train | 0 | |
0f031c0b23b317cda83cbecb0005207764d961e5 | [
"outZipFile = zipfile.ZipFile(zipname, 'w', zipfile.ZIP_DEFLATED)\nfor idx, dir in enumerate(directory_list):\n if not os.path.exists(dir):\n print(f'Error, directory {dir} does not exist')\n continue\n rootdir = os.path.basename(dir)\n try:\n os.listdir(dir)\n for dirpath, dirn... | <|body_start_0|>
outZipFile = zipfile.ZipFile(zipname, 'w', zipfile.ZIP_DEFLATED)
for idx, dir in enumerate(directory_list):
if not os.path.exists(dir):
print(f'Error, directory {dir} does not exist')
continue
rootdir = os.path.basename(dir)
... | Functions for accessing local files. | Local | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Local:
"""Functions for accessing local files."""
def zip_dir(cls, directory_list, zipname):
"""Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name of zip file to compress files into. :return: Zip file cont... | stack_v2_sparse_classes_36k_train_026233 | 12,445 | permissive | [
{
"docstring": "Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name of zip file to compress files into. :return: Zip file containing files.",
"name": "zip_dir",
"signature": "def zip_dir(cls, directory_list, zipname)"
},
{... | 6 | stack_v2_sparse_classes_30k_train_019838 | Implement the Python class `Local` described below.
Class description:
Functions for accessing local files.
Method signatures and docstrings:
- def zip_dir(cls, directory_list, zipname): Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name o... | Implement the Python class `Local` described below.
Class description:
Functions for accessing local files.
Method signatures and docstrings:
- def zip_dir(cls, directory_list, zipname): Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name o... | f200ccd224170761ed6a73ae8adf84972af2213d | <|skeleton|>
class Local:
"""Functions for accessing local files."""
def zip_dir(cls, directory_list, zipname):
"""Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name of zip file to compress files into. :return: Zip file cont... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Local:
"""Functions for accessing local files."""
def zip_dir(cls, directory_list, zipname):
"""Compress a directory into a single ZIP file. :param directory_list: List of files to compress into zip file. :param zipname: Name of zip file to compress files into. :return: Zip file containing files.... | the_stack_v2_python_sparse | fusetools/transfer_tools.py | TrendingTechnology/fusetools | train | 0 |
ea86e129cb5a2ab072541b7dfca40534645a92c4 | [
"Menu.__init__(self, master)\nroot.configure(menu=self)\nself.menuFichier = Menu(self, tearoff=0)\nself.menuEdition = Menu(self, tearoff=0)\nself.menuAffichage = Menu(self, tearoff=0)\nself.add_cascade(label='Fichier', menu=self.menuFichier)\nself.add_cascade(label='Edition', menu=self.menuEdition)\nself.add_cascad... | <|body_start_0|>
Menu.__init__(self, master)
root.configure(menu=self)
self.menuFichier = Menu(self, tearoff=0)
self.menuEdition = Menu(self, tearoff=0)
self.menuAffichage = Menu(self, tearoff=0)
self.add_cascade(label='Fichier', menu=self.menuFichier)
self.add_ca... | Classe de la barre de menus. | MenuBar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MenuBar:
"""Classe de la barre de menus."""
def __init__(self, root, master):
"""Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme."""
<|body_0|>
def __getBindingOf(self, bindingVir... | stack_v2_sparse_classes_36k_train_026234 | 2,550 | no_license | [
{
"docstring": "Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme.",
"name": "__init__",
"signature": "def __init__(self, root, master)"
},
{
"docstring": "@param bindingVirtuel : <str> nom du bindings dont... | 2 | stack_v2_sparse_classes_30k_train_008563 | Implement the Python class `MenuBar` described below.
Class description:
Classe de la barre de menus.
Method signatures and docstrings:
- def __init__(self, root, master): Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme.
- def... | Implement the Python class `MenuBar` described below.
Class description:
Classe de la barre de menus.
Method signatures and docstrings:
- def __init__(self, root, master): Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme.
- def... | f59e9d491fe1d60654fad5357474763e4755f13a | <|skeleton|>
class MenuBar:
"""Classe de la barre de menus."""
def __init__(self, root, master):
"""Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme."""
<|body_0|>
def __getBindingOf(self, bindingVir... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MenuBar:
"""Classe de la barre de menus."""
def __init__(self, root, master):
"""Constructeur de la barre de menus. @param root: fenêtre sur laquelle mettre cette barre de menus. @param master: l'Application du programme."""
Menu.__init__(self, master)
root.configure(menu=self)
... | the_stack_v2_python_sparse | TaskManager/MenuBar.py | Zetrypio/TaskManager | train | 2 |
0960020f36e83c50446ef6ea1006b6c5531c6f8d | [
"e = std.runtime_error('runtime pb!!')\nself.assertTrue(e)\nself.assertEqual(e.what(), 'runtime pb!!')",
"ROOT.gInterpreter.Declare('\\n namespace test2Exception {\\n template <typename T>\\n class Handle;\\n\\n class Exception : public std::exception {};\\n }\\n\\n template... | <|body_start_0|>
e = std.runtime_error('runtime pb!!')
self.assertTrue(e)
self.assertEqual(e.what(), 'runtime pb!!')
<|end_body_0|>
<|body_start_1|>
ROOT.gInterpreter.Declare('\n namespace test2Exception {\n template <typename T>\n class Handle;\n\n class Ex... | Cpp10StandardExceptions | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cpp10StandardExceptions:
def test1StandardExceptionsAccessFromPython(self):
"""Access C++ standard exception objects from python"""
<|body_0|>
def test2ExceptionBoolValue(self):
"""Test boolean value of exception object"""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_026235 | 30,462 | no_license | [
{
"docstring": "Access C++ standard exception objects from python",
"name": "test1StandardExceptionsAccessFromPython",
"signature": "def test1StandardExceptionsAccessFromPython(self)"
},
{
"docstring": "Test boolean value of exception object",
"name": "test2ExceptionBoolValue",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_004845 | Implement the Python class `Cpp10StandardExceptions` described below.
Class description:
Implement the Cpp10StandardExceptions class.
Method signatures and docstrings:
- def test1StandardExceptionsAccessFromPython(self): Access C++ standard exception objects from python
- def test2ExceptionBoolValue(self): Test boole... | Implement the Python class `Cpp10StandardExceptions` described below.
Class description:
Implement the Cpp10StandardExceptions class.
Method signatures and docstrings:
- def test1StandardExceptionsAccessFromPython(self): Access C++ standard exception objects from python
- def test2ExceptionBoolValue(self): Test boole... | 134508460915282a5d82d6cbbb6e6afa14653413 | <|skeleton|>
class Cpp10StandardExceptions:
def test1StandardExceptionsAccessFromPython(self):
"""Access C++ standard exception objects from python"""
<|body_0|>
def test2ExceptionBoolValue(self):
"""Test boolean value of exception object"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cpp10StandardExceptions:
def test1StandardExceptionsAccessFromPython(self):
"""Access C++ standard exception objects from python"""
e = std.runtime_error('runtime pb!!')
self.assertTrue(e)
self.assertEqual(e.what(), 'runtime pb!!')
def test2ExceptionBoolValue(self):
... | the_stack_v2_python_sparse | python/cpp/PyROOT_advancedtests.py | root-project/roottest | train | 41 | |
19a785c2d6f7f5842701b16f7ea7213b45d5a5d9 | [
"if head is None:\n return None\nif head.next is None:\n return head\nif head.next.next is None:\n if head.val < head.next.val:\n return head\n else:\n head.next.next = head\n tmp = head.next\n head.next = None\n return tmp\nf = ListNode()\nf.next = head\nfast = f\nslo... | <|body_start_0|>
if head is None:
return None
if head.next is None:
return head
if head.next.next is None:
if head.val < head.next.val:
return head
else:
head.next.next = head
tmp = head.next
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(self, list1, list2):
""":type list1: Optional[ListNode] :type list2: Optional[ListNode] :rtype: Optional[ListNode]"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_026236 | 1,578 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "sortList",
"signature": "def sortList(self, head)"
},
{
"docstring": ":type list1: Optional[ListNode] :type list2: Optional[ListNode] :rtype: Optional[ListNode]",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(sel... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def mergeTwoLists(self, list1, list2): :type list1: Optional[ListNode] :type list2: Optional[ListNode] :rtype: O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortList(self, head): :type head: ListNode :rtype: ListNode
- def mergeTwoLists(self, list1, list2): :type list1: Optional[ListNode] :type list2: Optional[ListNode] :rtype: O... | ca8b2662330776d14962532ed8994dfeedadef70 | <|skeleton|>
class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def mergeTwoLists(self, list1, list2):
""":type list1: Optional[ListNode] :type list2: Optional[ListNode] :rtype: Optional[ListNode]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortList(self, head):
""":type head: ListNode :rtype: ListNode"""
if head is None:
return None
if head.next is None:
return head
if head.next.next is None:
if head.val < head.next.val:
return head
els... | the_stack_v2_python_sparse | Algo/Leetcode/148SortList.py | lawy623/Algorithm_Interview_Prep | train | 2 | |
d765bd4196eb3ca05265a641e83201eae7c2af77 | [
"server = g.db.query(Server).get(server_id)\nif not server:\n log.warning('Requested a non-existant battleserver: %s', server_id)\n abort(http_client.NOT_FOUND, description='Server not found')\nmachine_id = server.machine_id\nrecord = server.as_dict()\nrecord['url'] = url_for('servers.entry', server_id=server... | <|body_start_0|>
server = g.db.query(Server).get(server_id)
if not server:
log.warning('Requested a non-existant battleserver: %s', server_id)
abort(http_client.NOT_FOUND, description='Server not found')
machine_id = server.machine_id
record = server.as_dict()
... | Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource. | ServerAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServerAPI:
"""Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource."""
def get(self, server_id):
... | stack_v2_sparse_classes_36k_train_026237 | 16,872 | permissive | [
{
"docstring": "Get information about a single battle server instance. Returns information from the machine and the associated battle if found.",
"name": "get",
"signature": "def get(self, server_id)"
},
{
"docstring": "The battleserver management (celery) process calls this to update the status... | 2 | stack_v2_sparse_classes_30k_val_000123 | Implement the Python class `ServerAPI` described below.
Class description:
Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource.
... | Implement the Python class `ServerAPI` described below.
Class description:
Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource.
... | 9825cb22b26b577b715f2ce95453363bf90ecc7e | <|skeleton|>
class ServerAPI:
"""Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource."""
def get(self, server_id):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServerAPI:
"""Interface to battle servers instances. A battleserver instance is a single run of a battleserver executable. The battleserver will have a single battle on it. You should never have a battle resource without an associated battleserver resource."""
def get(self, server_id):
"""Get inf... | the_stack_v2_python_sparse | driftbase/api/servers.py | dgnorth/drift-base | train | 1 |
6602bba6449ae7c6078c48f4ab703167d7e8e0dd | [
"self._metadata = metadata\nif not rest_prefix.endswith('/'):\n self._rest_prefix = '%s/' % rest_prefix\nelse:\n self._rest_prefix = rest_prefix\nself._mapping_rules = [CustomRequestMappingRule(self._rest_prefix), VerbMappingRule(self._rest_prefix), ListMappingRule(self._rest_prefix), PostMappingRule(self._re... | <|body_start_0|>
self._metadata = metadata
if not rest_prefix.endswith('/'):
self._rest_prefix = '%s/' % rest_prefix
else:
self._rest_prefix = rest_prefix
self._mapping_rules = [CustomRequestMappingRule(self._rest_prefix), VerbMappingRule(self._rest_prefix), ListM... | Generate the routing rules based on vAPI metamodel metadata. | RoutingRuleGenerator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoutingRuleGenerator:
"""Generate the routing rules based on vAPI metamodel metadata."""
def __init__(self, metadata, rest_prefix):
"""Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.MetadataStore` :param metadata: Object that contains the rele... | stack_v2_sparse_classes_36k_train_026238 | 37,981 | permissive | [
{
"docstring": "Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.MetadataStore` :param metadata: Object that contains the relevant metamodel metadata of all the services. :type rest_prefix: :class:`str` :param rest_prefix: REST URL prefix",
"name": "__init__",
"sig... | 3 | null | Implement the Python class `RoutingRuleGenerator` described below.
Class description:
Generate the routing rules based on vAPI metamodel metadata.
Method signatures and docstrings:
- def __init__(self, metadata, rest_prefix): Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.Meta... | Implement the Python class `RoutingRuleGenerator` described below.
Class description:
Generate the routing rules based on vAPI metamodel metadata.
Method signatures and docstrings:
- def __init__(self, metadata, rest_prefix): Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.Meta... | c07e1be98615201139b26c28db3aa584c4254b66 | <|skeleton|>
class RoutingRuleGenerator:
"""Generate the routing rules based on vAPI metamodel metadata."""
def __init__(self, metadata, rest_prefix):
"""Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.MetadataStore` :param metadata: Object that contains the rele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoutingRuleGenerator:
"""Generate the routing rules based on vAPI metamodel metadata."""
def __init__(self, metadata, rest_prefix):
"""Initialize RoutingRuleGenerator :type metadata: :class:`vmware.vapi.server.rest_handler.MetadataStore` :param metadata: Object that contains the relevant metamode... | the_stack_v2_python_sparse | vmware/vapi/rest/rules.py | adammillerio/vsphere-automation-sdk-python | train | 0 |
bd050bda65ec61070a21596eec0b1c1e09df51b6 | [
"self.rotating_right = False\nself.rotating_left = True\nself.stop_front_dist = 0.6\nself.min_front_dist = 0.8\nsuper().__init__('tw02_navigation')\nself.create_subscription(LaserScan, '/robot_0/base_scan', self.laserCallback, 1)\nself.vel_pub = self.create_publisher(Twist, '/robot_0/cmd_vel', 1)",
"\"\"\" Right ... | <|body_start_0|>
self.rotating_right = False
self.rotating_left = True
self.stop_front_dist = 0.6
self.min_front_dist = 0.8
super().__init__('tw02_navigation')
self.create_subscription(LaserScan, '/robot_0/base_scan', self.laserCallback, 1)
self.vel_pub = self.cre... | Random navigation avoiding laser-based detected obstacles. | BasicNavigation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicNavigation:
"""Random navigation avoiding laser-based detected obstacles."""
def __init__(self):
"""Initializes the class instance."""
<|body_0|>
def laserCallback(self, msg: LaserScan):
"""Update distance to closest obstacles and controll the robot bsed on ... | stack_v2_sparse_classes_36k_train_026239 | 5,606 | no_license | [
{
"docstring": "Initializes the class instance.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Update distance to closest obstacles and controll the robot bsed on those detected obstacles",
"name": "laserCallback",
"signature": "def laserCallback(self, msg: La... | 2 | stack_v2_sparse_classes_30k_train_000925 | Implement the Python class `BasicNavigation` described below.
Class description:
Random navigation avoiding laser-based detected obstacles.
Method signatures and docstrings:
- def __init__(self): Initializes the class instance.
- def laserCallback(self, msg: LaserScan): Update distance to closest obstacles and contro... | Implement the Python class `BasicNavigation` described below.
Class description:
Random navigation avoiding laser-based detected obstacles.
Method signatures and docstrings:
- def __init__(self): Initializes the class instance.
- def laserCallback(self, msg: LaserScan): Update distance to closest obstacles and contro... | a8f2541c60f36cd5c1af417a6fef7c80b163cd01 | <|skeleton|>
class BasicNavigation:
"""Random navigation avoiding laser-based detected obstacles."""
def __init__(self):
"""Initializes the class instance."""
<|body_0|>
def laserCallback(self, msg: LaserScan):
"""Update distance to closest obstacles and controll the robot bsed on ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicNavigation:
"""Random navigation avoiding laser-based detected obstacles."""
def __init__(self):
"""Initializes the class instance."""
self.rotating_right = False
self.rotating_left = True
self.stop_front_dist = 0.6
self.min_front_dist = 0.8
super().__... | the_stack_v2_python_sparse | src/tw02/tw02/navigation.py | ipleiria-robotics/adv_robotics | train | 0 |
296b09bf3bc7e476538bb530f54b2ca888f4f602 | [
"self.obj = obj\nself.attrGetter = xobj_attrgetter(varName)\nself.previousValue = self.attrGetter(self.obj)\nself.callback = callback",
"value = self.attrGetter(self.obj)\nif value != self.previousValue:\n self.previousValue = value\n self.callback(value)"
] | <|body_start_0|>
self.obj = obj
self.attrGetter = xobj_attrgetter(varName)
self.previousValue = self.attrGetter(self.obj)
self.callback = callback
<|end_body_0|>
<|body_start_1|>
value = self.attrGetter(self.obj)
if value != self.previousValue:
self.previousV... | Represents a watch placed on a particular variable of an object | VarWatch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VarWatch:
"""Represents a watch placed on a particular variable of an object"""
def __init__(self, obj, varName, callback):
"""Initialize the Watch with the object and its variable to watch and the callback to fire"""
<|body_0|>
def checkChange(self):
"""Check if... | stack_v2_sparse_classes_36k_train_026240 | 702 | no_license | [
{
"docstring": "Initialize the Watch with the object and its variable to watch and the callback to fire",
"name": "__init__",
"signature": "def __init__(self, obj, varName, callback)"
},
{
"docstring": "Check if the value has changed",
"name": "checkChange",
"signature": "def checkChange... | 2 | null | Implement the Python class `VarWatch` described below.
Class description:
Represents a watch placed on a particular variable of an object
Method signatures and docstrings:
- def __init__(self, obj, varName, callback): Initialize the Watch with the object and its variable to watch and the callback to fire
- def checkC... | Implement the Python class `VarWatch` described below.
Class description:
Represents a watch placed on a particular variable of an object
Method signatures and docstrings:
- def __init__(self, obj, varName, callback): Initialize the Watch with the object and its variable to watch and the callback to fire
- def checkC... | 19b7bf08658ce329c7b076ce2014bae9f5f09268 | <|skeleton|>
class VarWatch:
"""Represents a watch placed on a particular variable of an object"""
def __init__(self, obj, varName, callback):
"""Initialize the Watch with the object and its variable to watch and the callback to fire"""
<|body_0|>
def checkChange(self):
"""Check if... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VarWatch:
"""Represents a watch placed on a particular variable of an object"""
def __init__(self, obj, varName, callback):
"""Initialize the Watch with the object and its variable to watch and the callback to fire"""
self.obj = obj
self.attrGetter = xobj_attrgetter(varName)
... | the_stack_v2_python_sparse | src/knot/watches/var_watch.py | cloew/Knot | train | 1 |
eea8de42a84217c39b5874ee4708cb5ecb435be6 | [
"\"\"\"\n 大致步骤：\n 1-获取传入date以及code\n 2-根据code以及date获取geostationtidedata中的一个 StationTideData（model）\n 3-从realdata中获取过程中的极值出现时间以及值\n \"\"\"\ncode = request.GET.get('code', settings.DEFAULT_TYPHOON_CODE_BYSTATION)\nself.code = code\ndate_str = request.GET.... | <|body_start_0|>
"""
大致步骤：
1-获取传入date以及code
2-根据code以及date获取geostationtidedata中的一个 StationTideData（model）
3-从realdata中获取过程中的极值出现时间以及值
"""
code = request.GET.get('code', settings.DEFAULT_TYPHOON_CO... | StationTideDataListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StationTideDataListView:
def get(self, request):
""":param request: :return:"""
<|body_0|>
def getStationTargetRealData(self, targetdatetime: datetime, code: str) -> []:
"""根据时间获取该时间该台风的测站数据 :param date: :return:"""
<|body_1|>
def dataListMax(self, data:... | stack_v2_sparse_classes_36k_train_026241 | 46,325 | no_license | [
{
"docstring": ":param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "根据时间获取该时间该台风的测站数据 :param date: :return:",
"name": "getStationTargetRealData",
"signature": "def getStationTargetRealData(self, targetdatetime: datetime, code: str) -> []"
... | 4 | stack_v2_sparse_classes_30k_test_000258 | Implement the Python class `StationTideDataListView` described below.
Class description:
Implement the StationTideDataListView class.
Method signatures and docstrings:
- def get(self, request): :param request: :return:
- def getStationTargetRealData(self, targetdatetime: datetime, code: str) -> []: 根据时间获取该时间该台风的测站数据 ... | Implement the Python class `StationTideDataListView` described below.
Class description:
Implement the StationTideDataListView class.
Method signatures and docstrings:
- def get(self, request): :param request: :return:
- def getStationTargetRealData(self, targetdatetime: datetime, code: str) -> []: 根据时间获取该时间该台风的测站数据 ... | 53289e9583e52531346031921fb8f8b7026e399d | <|skeleton|>
class StationTideDataListView:
def get(self, request):
""":param request: :return:"""
<|body_0|>
def getStationTargetRealData(self, targetdatetime: datetime, code: str) -> []:
"""根据时间获取该时间该台风的测站数据 :param date: :return:"""
<|body_1|>
def dataListMax(self, data:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StationTideDataListView:
def get(self, request):
""":param request: :return:"""
"""
大致步骤：
1-获取传入date以及code
2-根据code以及date获取geostationtidedata中的一个 StationTideData（model）
3-从realdata中获取过程中的极值出现时间以及值
... | the_stack_v2_python_sparse | docker/pull-code/210724/code/apps/Typhoon/views.py | evaseemefly/TyphoonSearchSys | train | 20 | |
ea593a3f0a5e147e667cabf307ff543913229fde | [
"super(ResizeImageTask, self).__init__(*args, **kwargs)\nself.setOption('convertToRGBA', self.__defaultConvertToRGBA)\nself.setMetadata('dispatch.split', True)",
"import OpenImageIO as oiio\nfor crawler in self.crawlers():\n width = self.option('width')\n height = self.option('height')\n if isinstance(wi... | <|body_start_0|>
super(ResizeImageTask, self).__init__(*args, **kwargs)
self.setOption('convertToRGBA', self.__defaultConvertToRGBA)
self.setMetadata('dispatch.split', True)
<|end_body_0|>
<|body_start_1|>
import OpenImageIO as oiio
for crawler in self.crawlers():
wi... | Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes. | ResizeImageTask | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResizeImageTask:
"""Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes."""
def __init__(self, *args, **kwargs):
"""Create a resize image task."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_026242 | 3,190 | permissive | [
{
"docstring": "Create a resize image task.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Perform the task.",
"name": "_perform",
"signature": "def _perform(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020675 | Implement the Python class `ResizeImageTask` described below.
Class description:
Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes.
Method signatures and docstrings:
- def __init__(self, *args, **kw... | Implement the Python class `ResizeImageTask` described below.
Class description:
Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes.
Method signatures and docstrings:
- def __init__(self, *args, **kw... | 046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4 | <|skeleton|>
class ResizeImageTask:
"""Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes."""
def __init__(self, *args, **kwargs):
"""Create a resize image task."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResizeImageTask:
"""Image resize task. Options: - Optional: "convertToRGBA" - Required: "width" and "height" (both support templates) TODO: missing to kombi metadata/source image attributes."""
def __init__(self, *args, **kwargs):
"""Create a resize image task."""
super(ResizeImageTask, s... | the_stack_v2_python_sparse | src/lib/kombi/Task/Image/ResizeImageTask.py | kombiHQ/kombi | train | 2 |
4f2d71c4097ff2a0b9d9fed3bb43d80e6dd33c6f | [
"self.included = self._get_plugins_by_type('included')\nself.custom = self._get_plugins_by_type('custom')\nfor plugin in list(self.custom):\n if plugin in self.included:\n del self.custom[plugin]\n warn('Custom plugin \"{plugin_name}\" is invalid, as there is already an included plugin of the same ... | <|body_start_0|>
self.included = self._get_plugins_by_type('included')
self.custom = self._get_plugins_by_type('custom')
for plugin in list(self.custom):
if plugin in self.included:
del self.custom[plugin]
warn('Custom plugin "{plugin_name}" is invalid... | Class used to store valid included and custom plugins. | _ValidPlugins | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ValidPlugins:
"""Class used to store valid included and custom plugins."""
def __init__(self):
"""Store all plugins by their type."""
<|body_0|>
def get_plugin_type(self, plugin_name):
"""Return the type (included or custom) for the given plugin."""
<|bo... | stack_v2_sparse_classes_36k_train_026243 | 5,248 | no_license | [
{
"docstring": "Store all plugins by their type.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Return the type (included or custom) for the given plugin.",
"name": "get_plugin_type",
"signature": "def get_plugin_type(self, plugin_name)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_011842 | Implement the Python class `_ValidPlugins` described below.
Class description:
Class used to store valid included and custom plugins.
Method signatures and docstrings:
- def __init__(self): Store all plugins by their type.
- def get_plugin_type(self, plugin_name): Return the type (included or custom) for the given pl... | Implement the Python class `_ValidPlugins` described below.
Class description:
Class used to store valid included and custom plugins.
Method signatures and docstrings:
- def __init__(self): Store all plugins by their type.
- def get_plugin_type(self, plugin_name): Return the type (included or custom) for the given pl... | cead3639bab2acce9da55a4e7f196c750160b27f | <|skeleton|>
class _ValidPlugins:
"""Class used to store valid included and custom plugins."""
def __init__(self):
"""Store all plugins by their type."""
<|body_0|>
def get_plugin_type(self, plugin_name):
"""Return the type (included or custom) for the given plugin."""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ValidPlugins:
"""Class used to store valid included and custom plugins."""
def __init__(self):
"""Store all plugins by their type."""
self.included = self._get_plugins_by_type('included')
self.custom = self._get_plugins_by_type('custom')
for plugin in list(self.custom):
... | the_stack_v2_python_sparse | srcds/addons/source-python/plugins/admin/core/plugins/valid.py | Source-Python-Dev-Team/Source.Python.Admin | train | 8 |
55b273f55322caf5218b488e63f32a7db2a3f3a0 | [
"self.item = item\nif emoji is None:\n if item.hasEmoji:\n emoji = item.emoji\n else:\n raise ValueError('Attempted to create a ReactionInventoryPickerOption without providing an emoji, and the provided item has no emoji')\nif name is None:\n name = item.name\n if item.hasEmoji and emoji !... | <|body_start_0|>
self.item = item
if emoji is None:
if item.hasEmoji:
emoji = item.emoji
else:
raise ValueError('Attempted to create a ReactionInventoryPickerOption without providing an emoji, and the provided item has no emoji')
if name is... | A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item: bbItem | ReactionInventoryPickerOption | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReactionInventoryPickerOption:
"""A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item: bbItem"""
def __init__(self, ite... | stack_v2_sparse_classes_36k_train_026244 | 9,225 | permissive | [
{
"docstring": ":param bbItem item: The bbItem that this option represents :param ReactionMenu menu: The ReactionMenu where this option is active :param lib.emojis.dumbEmoji emoji: The emoji that a user must react with in order to trigger this menu option (Default item.emoji) :param str name: The name of this o... | 2 | null | Implement the Python class `ReactionInventoryPickerOption` described below.
Class description:
A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item... | Implement the Python class `ReactionInventoryPickerOption` described below.
Class description:
A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item... | b4fe3d765b764ab169284ce0869a810825013389 | <|skeleton|>
class ReactionInventoryPickerOption:
"""A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item: bbItem"""
def __init__(self, ite... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReactionInventoryPickerOption:
"""A reaction menu option that represents a bbItem instance. Unless configured otherwise, the option's name and emoji will correspond to the item's name and emoji. :var item: The bbItem that this option represents :vartype item: bbItem"""
def __init__(self, item: bbItem.bbI... | the_stack_v2_python_sparse | BB/reactionMenus/ReactionInventoryPicker.py | Trimatix/GOF2BountyBot | train | 7 |
e6651aaa82c284e68825ed7e24f1ef0f41a4bd60 | [
"subtotal = 0\nfor item in self.items:\n subtotal += item.total_cost\nreturn subtotal",
"if self.shipping_handling:\n return self.subtotal + self.shipping_handling\nreturn self.subtotal"
] | <|body_start_0|>
subtotal = 0
for item in self.items:
subtotal += item.total_cost
return subtotal
<|end_body_0|>
<|body_start_1|>
if self.shipping_handling:
return self.subtotal + self.shipping_handling
return self.subtotal
<|end_body_1|>
| The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and handling that will be applied total: Float value of the total cost | PurchaseOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PurchaseOrder:
"""The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and handling that will be applied total: Fl... | stack_v2_sparse_classes_36k_train_026245 | 19,591 | no_license | [
{
"docstring": "Calculate the subtotal of the item. Returns: subtotal (float)",
"name": "subtotal",
"signature": "def subtotal(self)"
},
{
"docstring": "Calculate the actual total of the item. This is done by add shipping and handling to the subtotal. If there is no shipping and handling just re... | 2 | stack_v2_sparse_classes_30k_train_015654 | Implement the Python class `PurchaseOrder` described below.
Class description:
The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and ... | Implement the Python class `PurchaseOrder` described below.
Class description:
The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and ... | b4774f3e3616ccde6b02086811b82627f6614498 | <|skeleton|>
class PurchaseOrder:
"""The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and handling that will be applied total: Fl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PurchaseOrder:
"""The PurchaseOrder object contains purchase order properties Attributes: po_id: Integer value that uniquely identifies the purchase order status: Integer of the status of the purchase order shipping_handling: Float value of the shipping and handling that will be applied total: Float value of ... | the_stack_v2_python_sparse | models.py | cyberjedi22/TCMS | train | 0 |
b016d2423a2003fdb0536c3ae3bd2f8fef212ee6 | [
"self.start = [0, 0]\nself.current = [0, 0]\nself.start_facing = 'E'\nself.current_facing = self.start_facing",
"result = self.current\nstep = 0\nstep_dir = re.match('^(\\\\D)', instr).group()\nstep_size = int(re.search('(\\\\d+)', instr).group())\ndirection_map = {'N': operator.add(self.current[1], step_size), '... | <|body_start_0|>
self.start = [0, 0]
self.current = [0, 0]
self.start_facing = 'E'
self.current_facing = self.start_facing
<|end_body_0|>
<|body_start_1|>
result = self.current
step = 0
step_dir = re.match('^(\\D)', instr).group()
step_size = int(re.searc... | Ship | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ship:
def __init__(self):
""":param facing: direction the ship is facing right now"""
<|body_0|>
def move_ship(self, instr: str) -> list:
"""Assuming a coordinate system of (-inf, inf) on the x and (-inf, inf) on the y :param instr: looks like NSEW, LR, or F (forward... | stack_v2_sparse_classes_36k_train_026246 | 4,032 | no_license | [
{
"docstring": ":param facing: direction the ship is facing right now",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Assuming a coordinate system of (-inf, inf) on the x and (-inf, inf) on the y :param instr: looks like NSEW, LR, or F (forward), plus a number :return:... | 5 | stack_v2_sparse_classes_30k_train_007941 | Implement the Python class `Ship` described below.
Class description:
Implement the Ship class.
Method signatures and docstrings:
- def __init__(self): :param facing: direction the ship is facing right now
- def move_ship(self, instr: str) -> list: Assuming a coordinate system of (-inf, inf) on the x and (-inf, inf) ... | Implement the Python class `Ship` described below.
Class description:
Implement the Ship class.
Method signatures and docstrings:
- def __init__(self): :param facing: direction the ship is facing right now
- def move_ship(self, instr: str) -> list: Assuming a coordinate system of (-inf, inf) on the x and (-inf, inf) ... | aa7e5daec4226bd96020db66bf38009463960f6b | <|skeleton|>
class Ship:
def __init__(self):
""":param facing: direction the ship is facing right now"""
<|body_0|>
def move_ship(self, instr: str) -> list:
"""Assuming a coordinate system of (-inf, inf) on the x and (-inf, inf) on the y :param instr: looks like NSEW, LR, or F (forward... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ship:
def __init__(self):
""":param facing: direction the ship is facing right now"""
self.start = [0, 0]
self.current = [0, 0]
self.start_facing = 'E'
self.current_facing = self.start_facing
def move_ship(self, instr: str) -> list:
"""Assuming a coordinate... | the_stack_v2_python_sparse | day_12.py | szeitlin/advent_of_code | train | 0 | |
2144115a128b85ae0eab9db409c4b863ce7af8b3 | [
"if not matrix:\n return []\nm = len(matrix)\nn = len(matrix[0])\ni, j = (0, n - 1)\nspiral = matrix[0]\ndirection = 1\nk = 1\nfor _ in range((m - 1) * n):\n if direction == 0:\n j += 1\n if j == n - k:\n direction = 1\n elif direction == 1:\n i += 1\n if i == m - k:\... | <|body_start_0|>
if not matrix:
return []
m = len(matrix)
n = len(matrix[0])
i, j = (0, n - 1)
spiral = matrix[0]
direction = 1
k = 1
for _ in range((m - 1) * n):
if direction == 0:
j += 1
if j == n -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def spiralOrder1(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not matri... | stack_v2_sparse_classes_36k_train_026247 | 1,687 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: List[int]",
"name": "spiralOrder",
"signature": "def spiralOrder(self, matrix)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: List[int]",
"name": "spiralOrder1",
"signature": "def spiralOrder1(self, matrix)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def spiralOrder1(self, matrix): :type matrix: List[List[int]] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def spiralOrder1(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
<|skeleton|>
cla... | 863b89be674a82eef60c0f33d726ac08d43f2e01 | <|skeleton|>
class Solution:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def spiralOrder1(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
if not matrix:
return []
m = len(matrix)
n = len(matrix[0])
i, j = (0, n - 1)
spiral = matrix[0]
direction = 1
k = 1
for _ in range... | the_stack_v2_python_sparse | q54_Spiral_Matrix.py | Ryuya1995/leetcode | train | 0 | |
a0fa4b89d7ec0f39289f3fb3a800450e009967ab | [
"super().__init__(app, id=id, config=config)\nself.Username = self.Config.get('username')\nself.Password = self.Config.get('password')\nself.Hostname = self.Config.get('hostname')\nself.Port = self.Config.get('port')",
"client = aioftp.Client()\nawait client.connect(self.Hostname, 21)\nawait client.login(self.Use... | <|body_start_0|>
super().__init__(app, id=id, config=config)
self.Username = self.Config.get('username')
self.Password = self.Config.get('password')
self.Hostname = self.Config.get('hostname')
self.Port = self.Config.get('port')
<|end_body_0|>
<|body_start_1|>
client = a... | Description: | | FTPConnection | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FTPConnection:
"""Description: |"""
def __init__(self, app, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None"""
<|body_0|>
async def connect(self):
"""Description... | stack_v2_sparse_classes_36k_train_026248 | 887 | permissive | [
{
"docstring": "Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None",
"name": "__init__",
"signature": "def __init__(self, app, id=None, config=None)"
},
{
"docstring": "Description: :return: client |",
"name": "connect"... | 2 | null | Implement the Python class `FTPConnection` described below.
Class description:
Description: |
Method signatures and docstrings:
- def __init__(self, app, id=None, config=None): Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None
- async def conne... | Implement the Python class `FTPConnection` described below.
Class description:
Description: |
Method signatures and docstrings:
- def __init__(self, app, id=None, config=None): Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None
- async def conne... | 11ee3689d0ff6e9b662deeb3fc5e18bb0aabc8f2 | <|skeleton|>
class FTPConnection:
"""Description: |"""
def __init__(self, app, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None"""
<|body_0|>
async def connect(self):
"""Description... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FTPConnection:
"""Description: |"""
def __init__(self, app, id=None, config=None):
"""Description: **Parameters** app : Application Name of the Application id : ID, default = None config : JSON, default = None"""
super().__init__(app, id=id, config=config)
self.Username = self.Con... | the_stack_v2_python_sparse | bspump/ftp/connection.py | LibertyAces/BitSwanPump | train | 24 |
87ae9a44f57c448574c79c961c32b747b8bfac5e | [
"xy = points.data[..., :2]\nz = points.z\nuv = (xy.T @ diag(z).inverse()).T if len(z.shape) else xy.T * 1 / z\nreturn Vector2(uv)",
"if isinstance(depth, (float, int)):\n depth = Tensor([depth])\nreturn Vector3.from_coords(points.x * depth, points.y * depth, depth)"
] | <|body_start_0|>
xy = points.data[..., :2]
z = points.z
uv = (xy.T @ diag(z).inverse()).T if len(z.shape) else xy.T * 1 / z
return Vector2(uv)
<|end_body_0|>
<|body_start_1|>
if isinstance(depth, (float, int)):
depth = Tensor([depth])
return Vector3.from_coor... | Z1Projection | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Z1Projection:
def project(self, points: Vector3) -> Vector2:
"""Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: Vector3 representing the points to project. Returns: Vector2 representing the projected points. Examp... | stack_v2_sparse_classes_36k_train_026249 | 1,838 | permissive | [
{
"docstring": "Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: Vector3 representing the points to project. Returns: Vector2 representing the projected points. Example: >>> points = Vector3.from_coords(1., 2., 3.) >>> Z1Projection().proj... | 2 | null | Implement the Python class `Z1Projection` described below.
Class description:
Implement the Z1Projection class.
Method signatures and docstrings:
- def project(self, points: Vector3) -> Vector2: Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: ... | Implement the Python class `Z1Projection` described below.
Class description:
Implement the Z1Projection class.
Method signatures and docstrings:
- def project(self, points: Vector3) -> Vector2: Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: ... | 1e0f8baa7318c05b17ea6dbb48605691bca8972f | <|skeleton|>
class Z1Projection:
def project(self, points: Vector3) -> Vector2:
"""Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: Vector3 representing the points to project. Returns: Vector2 representing the projected points. Examp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Z1Projection:
def project(self, points: Vector3) -> Vector2:
"""Project one or more Vector3 from the camera frame into the canonical z=1 plane through perspective division. Args: points: Vector3 representing the points to project. Returns: Vector2 representing the projected points. Example: >>> points... | the_stack_v2_python_sparse | kornia/sensors/camera/projection_model.py | kornia/kornia | train | 7,351 | |
9c5ead501ba0f152d92c322dd718a60ca9a9f95d | [
"def serializeRecur(node, level):\n if node == None:\n return '#'\n next_level = chr(ord(level) + 1)\n return serializeRecur(node.left, next_level) + level + str(node.val) + level + serializeRecur(node.right, next_level)\nreturn serializeRecur(root, 'A')",
"def deserializeRecur(code, level):\n ... | <|body_start_0|>
def serializeRecur(node, level):
if node == None:
return '#'
next_level = chr(ord(level) + 1)
return serializeRecur(node.left, next_level) + level + str(node.val) + level + serializeRecur(node.right, next_level)
return serializeRecur(r... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_026250 | 2,916 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 8cda0518440488992d7e2c70cb8555ec7b34083f | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def serializeRecur(node, level):
if node == None:
return '#'
next_level = chr(ord(level) + 1)
return serializeRecur(node.left, next_le... | the_stack_v2_python_sparse | 449/main.py | szhongren/leetcode | train | 0 | |
faac29f81eed167eff719c30e413bea06098fe85 | [
"ans = []\nself.removeHelper(s, 0, 0, '(', ')', ans)\nreturn ans",
"sum = 0\nfor i in range(last_i, len(s)):\n if s[i] == char1:\n sum += 1\n if s[i] == char2:\n sum -= 1\n if sum >= 0:\n continue\n for j in range(last_j, i + 1):\n if s[j] == char2 and (j == last_j or s[j] ... | <|body_start_0|>
ans = []
self.removeHelper(s, 0, 0, '(', ')', ans)
return ans
<|end_body_0|>
<|body_start_1|>
sum = 0
for i in range(last_i, len(s)):
if s[i] == char1:
sum += 1
if s[i] == char2:
sum -= 1
if sum... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def removeHelper(self, s, last_i, last_j, char1, char2, ans):
"""Remove invalid parentheses in two rounds: 1st round: detect ')' appears more times then '(' 2nd round: de... | stack_v2_sparse_classes_36k_train_026251 | 1,373 | no_license | [
{
"docstring": ":type s: str :rtype: List[str]",
"name": "removeInvalidParentheses",
"signature": "def removeInvalidParentheses(self, s)"
},
{
"docstring": "Remove invalid parentheses in two rounds: 1st round: detect ')' appears more times then '(' 2nd round: detect '(' appears more times then '... | 2 | stack_v2_sparse_classes_30k_train_021328 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeInvalidParentheses(self, s): :type s: str :rtype: List[str]
- def removeHelper(self, s, last_i, last_j, char1, char2, ans): Remove invalid parentheses in two rounds: 1s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeInvalidParentheses(self, s): :type s: str :rtype: List[str]
- def removeHelper(self, s, last_i, last_j, char1, char2, ans): Remove invalid parentheses in two rounds: 1s... | 83f95caa3f7a487e8561e69133772d5add4484e1 | <|skeleton|>
class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def removeHelper(self, s, last_i, last_j, char1, char2, ans):
"""Remove invalid parentheses in two rounds: 1st round: detect ')' appears more times then '(' 2nd round: de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeInvalidParentheses(self, s):
""":type s: str :rtype: List[str]"""
ans = []
self.removeHelper(s, 0, 0, '(', ')', ans)
return ans
def removeHelper(self, s, last_i, last_j, char1, char2, ans):
"""Remove invalid parentheses in two rounds: 1st round:... | the_stack_v2_python_sparse | algorithms.master/invalid paranthesis.py | apk2129/_personal | train | 0 | |
387e927070389bbbebded9641a55d59a8283f1aa | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn Domain()",
"from .directory_object import DirectoryObject\nfrom .domain_dns_record import DomainDnsRecord\nfrom .domain_state import DomainState\nfrom .entity import Entity\nfrom .internal_domain_federation import InternalDomainFederat... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return Domain()
<|end_body_0|>
<|body_start_1|>
from .directory_object import DirectoryObject
from .domain_dns_record import DomainDnsRecord
from .domain_state import DomainState
... | Domain | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Domain:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Domain:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Domain"""
... | stack_v2_sparse_classes_36k_train_026252 | 9,421 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Domain",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(parse_... | 3 | stack_v2_sparse_classes_30k_train_001890 | Implement the Python class `Domain` described below.
Class description:
Implement the Domain class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Domain: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: Th... | Implement the Python class `Domain` described below.
Class description:
Implement the Domain class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Domain: Creates a new instance of the appropriate class based on discriminator value Args: parse_node: Th... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class Domain:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Domain:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Domain"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Domain:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> Domain:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Domain"""
if not p... | the_stack_v2_python_sparse | msgraph/generated/models/domain.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
5eb5529630d1a899d08b74c5c4ae06524cca194b | [
"name_base = self.specs['dsn_basename']\nsuffix = ''\nfor var, val in zip(self.swp_var_list, combo_list):\n if isinstance(val, str):\n val = os.path.splitext(os.path.basename(val))[0]\n suffix += '_%s_%s' % (var, val)\n elif isinstance(val, int):\n suffix += '_%s_%d' % (var, val)\n eli... | <|body_start_0|>
name_base = self.specs['dsn_basename']
suffix = ''
for var, val in zip(self.swp_var_list, combo_list):
if isinstance(val, str):
val = os.path.splitext(os.path.basename(val))[0]
suffix += '_%s_%s' % (var, val)
elif isinstanc... | CustomDesignManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomDesignManager:
def get_design_name(self, combo_list):
"""Generate cell names based on sweep parameter values."""
<|body_0|>
def get_layout_params(self, val_list):
"""Returns the layout dictionary from the given sweep parameter values. Overwritten to incorporate... | stack_v2_sparse_classes_36k_train_026253 | 19,150 | permissive | [
{
"docstring": "Generate cell names based on sweep parameter values.",
"name": "get_design_name",
"signature": "def get_design_name(self, combo_list)"
},
{
"docstring": "Returns the layout dictionary from the given sweep parameter values. Overwritten to incorporate the discrete evaluation proble... | 2 | stack_v2_sparse_classes_30k_val_001132 | Implement the Python class `CustomDesignManager` described below.
Class description:
Implement the CustomDesignManager class.
Method signatures and docstrings:
- def get_design_name(self, combo_list): Generate cell names based on sweep parameter values.
- def get_layout_params(self, val_list): Returns the layout dict... | Implement the Python class `CustomDesignManager` described below.
Class description:
Implement the CustomDesignManager class.
Method signatures and docstrings:
- def get_design_name(self, combo_list): Generate cell names based on sweep parameter values.
- def get_layout_params(self, val_list): Returns the layout dict... | 2ce6da8665d944bab8508a83bc4d3d07fd5afb35 | <|skeleton|>
class CustomDesignManager:
def get_design_name(self, combo_list):
"""Generate cell names based on sweep parameter values."""
<|body_0|>
def get_layout_params(self, val_list):
"""Returns the layout dictionary from the given sweep parameter values. Overwritten to incorporate... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomDesignManager:
def get_design_name(self, combo_list):
"""Generate cell names based on sweep parameter values."""
name_base = self.specs['dsn_basename']
suffix = ''
for var, val in zip(self.swp_var_list, combo_list):
if isinstance(val, str):
val... | the_stack_v2_python_sparse | eval_engines/bag/AFE_CMP_eval.py | kouroshHakha/bag_deep_ckt | train | 19 | |
0d8d1c3e6819939ebb050b24b2c5ae2596a89539 | [
"def structure2list(list):\n if list == []:\n return None\n max_1 = list[0]\n max_item = 0\n for i, val in enumerate(list):\n if val >= max_1:\n max_1 = val\n max_item = i\n root = TreeNode(max_1)\n root.left = structure2list(list[0:max_item])\n root.right = ... | <|body_start_0|>
def structure2list(list):
if list == []:
return None
max_1 = list[0]
max_item = 0
for i, val in enumerate(list):
if val >= max_1:
max_1 = val
max_item = i
root = T... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode 282ms"""
<|body_0|>
def constructMaximumBinaryTree_1(self, nums):
""":type nums: List[int] :rtype: TreeNode 192ms"""
<|body_1|>
def constructMaximumBinaryTree... | stack_v2_sparse_classes_36k_train_026254 | 2,893 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: TreeNode 282ms",
"name": "constructMaximumBinaryTree",
"signature": "def constructMaximumBinaryTree(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode 192ms",
"name": "constructMaximumBinaryTree_1",
"signature": "def const... | 3 | stack_v2_sparse_classes_30k_train_012064 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode 282ms
- def constructMaximumBinaryTree_1(self, nums): :type nums: List[int] :rtype: TreeNode 19... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode 282ms
- def constructMaximumBinaryTree_1(self, nums): :type nums: List[int] :rtype: TreeNode 19... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode 282ms"""
<|body_0|>
def constructMaximumBinaryTree_1(self, nums):
""":type nums: List[int] :rtype: TreeNode 192ms"""
<|body_1|>
def constructMaximumBinaryTree... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode 282ms"""
def structure2list(list):
if list == []:
return None
max_1 = list[0]
max_item = 0
for i, val in enumerate(list):
... | the_stack_v2_python_sparse | MaximumBinaryTree_MID_654.py | 953250587/leetcode-python | train | 2 | |
f32f4d669853ce1068b6b4af3abe5fc22e4eb52d | [
"params = kwarg['params']\ncmd = 'tc qdisc {} '.format(command)\nreturn cmd",
"params = kwarg['params']\ncmd = 'tc qdisc {} '.format(command)\nreturn cmd"
] | <|body_start_0|>
params = kwarg['params']
cmd = 'tc qdisc {} '.format(command)
return cmd
<|end_body_0|>
<|body_start_1|>
params = kwarg['params']
cmd = 'tc qdisc {} '.format(command)
return cmd
<|end_body_1|>
| tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT ] qdisc show [ dev DEV ] | LinuxTcQdiscImpl | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LinuxTcQdiscImpl:
"""tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT ] qdisc show [ dev DEV ]"""
def f... | stack_v2_sparse_classes_36k_train_026255 | 1,163 | permissive | [
{
"docstring": "tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ]",
"name": "format_modify",
"signature": "def format_modify(self, command, ... | 2 | null | Implement the Python class `LinuxTcQdiscImpl` described below.
Class description:
tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT... | Implement the Python class `LinuxTcQdiscImpl` described below.
Class description:
tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT... | e4c8221e18cd94e7424c30e12eb0fb82f7767267 | <|skeleton|>
class LinuxTcQdiscImpl:
"""tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT ] qdisc show [ dev DEV ]"""
def f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LinuxTcQdiscImpl:
"""tc [ OPTIONS ] qdisc [ add | change | replace | link | delete ] dev DEV [ parent qdisc-id | root ] [ handle qdisc-id ] [ ingress_block BLOCK_INDEX ] [ egress_block BLOCK_INDEX ] qdisc [ qdisc specific parameters ] tc [ OPTIONS ] [ FORMAT ] qdisc show [ dev DEV ]"""
def format_modify(... | the_stack_v2_python_sparse | Amazon_Framework/DentOsTestbedLib/src/dent_os_testbed/lib/tc/linux/linux_tc_qdisc_impl.py | tld3daniel/testing | train | 0 |
8fe6190044b8d9d00330b58afb087f6e4f16282c | [
"srv = service_url[8:20]\nlast = WEBQuery.T[srv] if srv in WEBQuery.T else 0.0\nwait = 0 if timestamp() - last > throttling else throttling\nsleep(wait)\nself.url = service_url\nself.data = webservice.query(service_url, ua)\nWEBQuery.T[srv] = timestamp()",
"if data_checker:\n return data_checker(self.data)\nif... | <|body_start_0|>
srv = service_url[8:20]
last = WEBQuery.T[srv] if srv in WEBQuery.T else 0.0
wait = 0 if timestamp() - last > throttling else throttling
sleep(wait)
self.url = service_url
self.data = webservice.query(service_url, ua)
WEBQuery.T[srv] = timestamp()... | Base class to query a webservice and parse the result to py objects. | WEBQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WEBQuery:
"""Base class to query a webservice and parse the result to py objects."""
def __init__(self, service_url, ua=UA, throttling=THROTTLING):
"""Initialize & call webservice."""
<|body_0|>
def check_data(self, data_checker=None):
"""Check the data & handle ... | stack_v2_sparse_classes_36k_train_026256 | 2,294 | permissive | [
{
"docstring": "Initialize & call webservice.",
"name": "__init__",
"signature": "def __init__(self, service_url, ua=UA, throttling=THROTTLING)"
},
{
"docstring": "Check the data & handle errors.",
"name": "check_data",
"signature": "def check_data(self, data_checker=None)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_020807 | Implement the Python class `WEBQuery` described below.
Class description:
Base class to query a webservice and parse the result to py objects.
Method signatures and docstrings:
- def __init__(self, service_url, ua=UA, throttling=THROTTLING): Initialize & call webservice.
- def check_data(self, data_checker=None): Che... | Implement the Python class `WEBQuery` described below.
Class description:
Base class to query a webservice and parse the result to py objects.
Method signatures and docstrings:
- def __init__(self, service_url, ua=UA, throttling=THROTTLING): Initialize & call webservice.
- def check_data(self, data_checker=None): Che... | 973fd05ddcee1c5c3cd9bf88353c6623dd69f57a | <|skeleton|>
class WEBQuery:
"""Base class to query a webservice and parse the result to py objects."""
def __init__(self, service_url, ua=UA, throttling=THROTTLING):
"""Initialize & call webservice."""
<|body_0|>
def check_data(self, data_checker=None):
"""Check the data & handle ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WEBQuery:
"""Base class to query a webservice and parse the result to py objects."""
def __init__(self, service_url, ua=UA, throttling=THROTTLING):
"""Initialize & call webservice."""
srv = service_url[8:20]
last = WEBQuery.T[srv] if srv in WEBQuery.T else 0.0
wait = 0 if ... | the_stack_v2_python_sparse | lib/python3.6/site-packages/isbnlib/dev/webquery.py | sanjaymaniam/OpenKindlerWeb | train | 1 |
32aa3e77edd63b76826e226d0ff1d79cb09caa39 | [
"super().__init__()\nself.mid_planes = mid_planes = out_planes // 1\nself.out_planes = out_planes\nself.share_planes = share_planes\nself.nsample = nsample\nself.linear_q = layers.Dense(mid_planes)\nself.linear_k = layers.Dense(mid_planes)\nself.linear_v = layers.Dense(out_planes)\nself.linear_p = tf.keras.models.S... | <|body_start_0|>
super().__init__()
self.mid_planes = mid_planes = out_planes // 1
self.out_planes = out_planes
self.share_planes = share_planes
self.nsample = nsample
self.linear_q = layers.Dense(mid_planes)
self.linear_k = layers.Dense(mid_planes)
self.l... | Transformer layer of the model, uses self attention. | Transformer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""Transformer layer of the model, uses self attention."""
def __init__(self, in_planes, out_planes, share_planes=8, nsample=16):
"""Constructor for Transformer Layer. Args: in_planes (int): Number of input planes. out_planes (int): Number of output planes. share_planes ... | stack_v2_sparse_classes_36k_train_026257 | 29,888 | permissive | [
{
"docstring": "Constructor for Transformer Layer. Args: in_planes (int): Number of input planes. out_planes (int): Number of output planes. share_planes (int): Number of shared planes. nsample (int): Number of neighbours.",
"name": "__init__",
"signature": "def __init__(self, in_planes, out_planes, sha... | 2 | stack_v2_sparse_classes_30k_train_016011 | Implement the Python class `Transformer` described below.
Class description:
Transformer layer of the model, uses self attention.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, share_planes=8, nsample=16): Constructor for Transformer Layer. Args: in_planes (int): Number of input planes.... | Implement the Python class `Transformer` described below.
Class description:
Transformer layer of the model, uses self attention.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, share_planes=8, nsample=16): Constructor for Transformer Layer. Args: in_planes (int): Number of input planes.... | 51482281dc180786e7563c73c12ac5df89289748 | <|skeleton|>
class Transformer:
"""Transformer layer of the model, uses self attention."""
def __init__(self, in_planes, out_planes, share_planes=8, nsample=16):
"""Constructor for Transformer Layer. Args: in_planes (int): Number of input planes. out_planes (int): Number of output planes. share_planes ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Transformer:
"""Transformer layer of the model, uses self attention."""
def __init__(self, in_planes, out_planes, share_planes=8, nsample=16):
"""Constructor for Transformer Layer. Args: in_planes (int): Number of input planes. out_planes (int): Number of output planes. share_planes (int): Number... | the_stack_v2_python_sparse | ml3d/tf/models/point_transformer.py | CosmosHua/Open3D-ML | train | 0 |
5de109650ffc20d48dfb983592cfd637f0ebbb61 | [
"self.c0 = c0\nself.cm = cm\nself.z_src = z_src\nself.c_src = c0 + self.z_src * cm\nself.launch_angles = np.linspace(pi / 2 - 0.001, theta_min, num_rays)\nself.px = None\nself.rho = None\nself.travel_time = None\nself.q = None\nself._rays_to_z0()",
"surface_rays = np.zeros((self.launch_angles.size, 4))\npx = np.e... | <|body_start_0|>
self.c0 = c0
self.cm = cm
self.z_src = z_src
self.c_src = c0 + self.z_src * cm
self.launch_angles = np.linspace(pi / 2 - 0.001, theta_min, num_rays)
self.px = None
self.rho = None
self.travel_time = None
self.q = None
self.... | Shoot a fan of rays to the surface, create an interpolator | CLinearFan | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CLinearFan:
"""Shoot a fan of rays to the surface, create an interpolator"""
def __init__(self, c0, cm, z_src, num_rays, theta_min):
"""Initilize rays"""
<|body_0|>
def _rays_to_z0(self):
"""propagate rays untill they hit z=0"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_026258 | 2,352 | permissive | [
{
"docstring": "Initilize rays",
"name": "__init__",
"signature": "def __init__(self, c0, cm, z_src, num_rays, theta_min)"
},
{
"docstring": "propagate rays untill they hit z=0",
"name": "_rays_to_z0",
"signature": "def _rays_to_z0(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000342 | Implement the Python class `CLinearFan` described below.
Class description:
Shoot a fan of rays to the surface, create an interpolator
Method signatures and docstrings:
- def __init__(self, c0, cm, z_src, num_rays, theta_min): Initilize rays
- def _rays_to_z0(self): propagate rays untill they hit z=0 | Implement the Python class `CLinearFan` described below.
Class description:
Shoot a fan of rays to the surface, create an interpolator
Method signatures and docstrings:
- def __init__(self, c0, cm, z_src, num_rays, theta_min): Initilize rays
- def _rays_to_z0(self): propagate rays untill they hit z=0
<|skeleton|>
cl... | 23038da6ee14ad8861938f7307e33b65e3835626 | <|skeleton|>
class CLinearFan:
"""Shoot a fan of rays to the surface, create an interpolator"""
def __init__(self, c0, cm, z_src, num_rays, theta_min):
"""Initilize rays"""
<|body_0|>
def _rays_to_z0(self):
"""propagate rays untill they hit z=0"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CLinearFan:
"""Shoot a fan of rays to the surface, create an interpolator"""
def __init__(self, c0, cm, z_src, num_rays, theta_min):
"""Initilize rays"""
self.c0 = c0
self.cm = cm
self.z_src = z_src
self.c_src = c0 + self.z_src * cm
self.launch_angles = np.... | the_stack_v2_python_sparse | novice_stakes/refraction/clin_greens.py | nedlrichards/novice_stakes | train | 0 |
659eb6fadc32229d48a9e1f09215e699ca037b36 | [
"if layer_specs is None:\n layer_specs = [[3, 128, 1, 1], [3, 128, 1, 1], [3, 96, 1, 1], [3, 64, 1, 1], [3, 32, 1, 1], [3, 2, 1, 1]]\nsuper().__init__(name=name, layer_specs=layer_specs, activation_fn=activation_fn, last_activation_fn=None, regularizer=regularizer, padding='SAME', dense_net=dense_net)\nself.sear... | <|body_start_0|>
if layer_specs is None:
layer_specs = [[3, 128, 1, 1], [3, 128, 1, 1], [3, 96, 1, 1], [3, 64, 1, 1], [3, 32, 1, 1], [3, 2, 1, 1]]
super().__init__(name=name, layer_specs=layer_specs, activation_fn=activation_fn, last_activation_fn=None, regularizer=regularizer, padding='SAME... | EstimatorNetwork | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EstimatorNetwork:
def __init__(self, name='estimator_network', layer_specs=None, activation_fn=leaky_relu, regularizer=None, search_range=4, dense_net=True, cost_volume_activation=True):
""":param name: Str. For variable scoping. :param layer_specs: See parent class. :param activation_fn... | stack_v2_sparse_classes_36k_train_026259 | 4,188 | no_license | [
{
"docstring": ":param name: Str. For variable scoping. :param layer_specs: See parent class. :param activation_fn: Tensorflow activation function. :param regularizer: Tf regularizer such as tf.contrib.layers.l2_regularizer. :param dense_net: Bool. Default for PWC-Net is true. :param cost_volume_activation: Boo... | 2 | stack_v2_sparse_classes_30k_train_016698 | Implement the Python class `EstimatorNetwork` described below.
Class description:
Implement the EstimatorNetwork class.
Method signatures and docstrings:
- def __init__(self, name='estimator_network', layer_specs=None, activation_fn=leaky_relu, regularizer=None, search_range=4, dense_net=True, cost_volume_activation=... | Implement the Python class `EstimatorNetwork` described below.
Class description:
Implement the EstimatorNetwork class.
Method signatures and docstrings:
- def __init__(self, name='estimator_network', layer_specs=None, activation_fn=leaky_relu, regularizer=None, search_range=4, dense_net=True, cost_volume_activation=... | 494d503c729ba018614fc742f1aee1e48d37127e | <|skeleton|>
class EstimatorNetwork:
def __init__(self, name='estimator_network', layer_specs=None, activation_fn=leaky_relu, regularizer=None, search_range=4, dense_net=True, cost_volume_activation=True):
""":param name: Str. For variable scoping. :param layer_specs: See parent class. :param activation_fn... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EstimatorNetwork:
def __init__(self, name='estimator_network', layer_specs=None, activation_fn=leaky_relu, regularizer=None, search_range=4, dense_net=True, cost_volume_activation=True):
""":param name: Str. For variable scoping. :param layer_specs: See parent class. :param activation_fn: Tensorflow a... | the_stack_v2_python_sparse | pwcnet/estimator_network/model.py | NeedsMorePie/interpolator | train | 2 | |
f363efa9af9881501129cc3336798bf47f20b12b | [
"conv_data = Bech32BaseUtils.ConvertBits(data, 8, 5)\nif conv_data is None:\n raise ValueError('Invalid data, cannot perform conversion to base32')\nreturn conv_data",
"conv_data = Bech32BaseUtils.ConvertBits(data, 5, 8, False)\nif conv_data is None:\n raise ValueError('Invalid data, cannot perform conversi... | <|body_start_0|>
conv_data = Bech32BaseUtils.ConvertBits(data, 8, 5)
if conv_data is None:
raise ValueError('Invalid data, cannot perform conversion to base32')
return conv_data
<|end_body_0|>
<|body_start_1|>
conv_data = Bech32BaseUtils.ConvertBits(data, 5, 8, False)
... | Class container for Bech32 utility functions. | Bech32BaseUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bech32BaseUtils:
"""Class container for Bech32 utility functions."""
def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]:
"""Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: list[int]: Converted data Raises: ValueError: If the string ... | stack_v2_sparse_classes_36k_train_026260 | 8,003 | permissive | [
{
"docstring": "Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: list[int]: Converted data Raises: ValueError: If the string is not valid",
"name": "ConvertToBase32",
"signature": "def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]"
},
{
"docstr... | 3 | stack_v2_sparse_classes_30k_train_011422 | Implement the Python class `Bech32BaseUtils` described below.
Class description:
Class container for Bech32 utility functions.
Method signatures and docstrings:
- def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]: Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: lis... | Implement the Python class `Bech32BaseUtils` described below.
Class description:
Class container for Bech32 utility functions.
Method signatures and docstrings:
- def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]: Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: lis... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class Bech32BaseUtils:
"""Class container for Bech32 utility functions."""
def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]:
"""Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: list[int]: Converted data Raises: ValueError: If the string ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bech32BaseUtils:
"""Class container for Bech32 utility functions."""
def ConvertToBase32(data: Union[List[int], bytes]) -> List[int]:
"""Convert data to base32. Args: data (list[int] or bytes): Data to be converted Returns: list[int]: Converted data Raises: ValueError: If the string is not valid"... | the_stack_v2_python_sparse | bip_utils/bech32/bech32_base.py | ebellocchia/bip_utils | train | 244 |
ad2cf5ed5bf84c172cb0aa1eaac2f3cd983f6298 | [
"super().__init__()\nself.self_attn = nn.MultiheadAttention(d_model, nhead, dropout=dropout)\nself.sru = SRUCell(d_model, dim_feedforward, dropout, sru_dropout or dropout, bidirectional=bidirectional, has_skip_term=False, **kwargs)\nself.linear2 = nn.Linear(dim_feedforward, d_model)\nself.norm1 = nn.LayerNorm(d_mod... | <|body_start_0|>
super().__init__()
self.self_attn = nn.MultiheadAttention(d_model, nhead, dropout=dropout)
self.sru = SRUCell(d_model, dim_feedforward, dropout, sru_dropout or dropout, bidirectional=bidirectional, has_skip_term=False, **kwargs)
self.linear2 = nn.Linear(dim_feedforward, ... | A TransformerSRUEncoderLayer with an SRU replacing the FFN. | TransformerSRUEncoderLayer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformerSRUEncoderLayer:
"""A TransformerSRUEncoderLayer with an SRU replacing the FFN."""
def __init__(self, d_model: int, nhead: int, dim_feedforward: int=2048, dropout: float=0.1, sru_dropout: Optional[float]=None, bidirectional: bool=False, **kwargs: Dict[str, Any]) -> None:
"... | stack_v2_sparse_classes_36k_train_026261 | 23,050 | permissive | [
{
"docstring": "Initialize a TransformerSRUEncoderLayer. Parameters ---------- d_model : int The number of expected features in the input. n_head : int The number of heads in the multiheadattention models. dim_feedforward : int, optional The dimension of the feedforward network (default=2048). dropout : float, ... | 2 | null | Implement the Python class `TransformerSRUEncoderLayer` described below.
Class description:
A TransformerSRUEncoderLayer with an SRU replacing the FFN.
Method signatures and docstrings:
- def __init__(self, d_model: int, nhead: int, dim_feedforward: int=2048, dropout: float=0.1, sru_dropout: Optional[float]=None, bid... | Implement the Python class `TransformerSRUEncoderLayer` described below.
Class description:
A TransformerSRUEncoderLayer with an SRU replacing the FFN.
Method signatures and docstrings:
- def __init__(self, d_model: int, nhead: int, dim_feedforward: int=2048, dropout: float=0.1, sru_dropout: Optional[float]=None, bid... | 0dc2f5b2b286694defe8abf450fe5be9ae12c097 | <|skeleton|>
class TransformerSRUEncoderLayer:
"""A TransformerSRUEncoderLayer with an SRU replacing the FFN."""
def __init__(self, d_model: int, nhead: int, dim_feedforward: int=2048, dropout: float=0.1, sru_dropout: Optional[float]=None, bidirectional: bool=False, **kwargs: Dict[str, Any]) -> None:
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformerSRUEncoderLayer:
"""A TransformerSRUEncoderLayer with an SRU replacing the FFN."""
def __init__(self, d_model: int, nhead: int, dim_feedforward: int=2048, dropout: float=0.1, sru_dropout: Optional[float]=None, bidirectional: bool=False, **kwargs: Dict[str, Any]) -> None:
"""Initialize ... | the_stack_v2_python_sparse | flambe/nn/transformer_sru.py | cle-ros/flambe | train | 1 |
2c592bf4954ce95a840a657b7b9e04c3be0e6cfe | [
"self.backend_tiering = backend_tiering\nself.frontend_tiering = frontend_tiering\nself.max_retention = max_retention",
"if dictionary is None:\n return None\nbackend_tiering = dictionary.get('backendTiering')\nfrontend_tiering = dictionary.get('frontendTiering')\nmax_retention = dictionary.get('maxRetention')... | <|body_start_0|>
self.backend_tiering = backend_tiering
self.frontend_tiering = frontend_tiering
self.max_retention = max_retention
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
backend_tiering = dictionary.get('backendTiering')
frontend_... | Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (long|int): Specified the max retention for backup policy creation. | TieringInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TieringInfo:
"""Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (long|int): Specified the max retention for... | stack_v2_sparse_classes_36k_train_026262 | 1,968 | permissive | [
{
"docstring": "Constructor for the TieringInfo class",
"name": "__init__",
"signature": "def __init__(self, backend_tiering=None, frontend_tiering=None, max_retention=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary repres... | 2 | null | Implement the Python class `TieringInfo` described below.
Class description:
Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (lon... | Implement the Python class `TieringInfo` described below.
Class description:
Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (lon... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class TieringInfo:
"""Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (long|int): Specified the max retention for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TieringInfo:
"""Implementation of the 'TieringInfo' model. TODO: type description here. Attributes: backend_tiering (bool): Specifies whether back-end tiering is enabled. frontend_tiering (bool): Specifies whether Front End Tiering Enabled max_retention (long|int): Specified the max retention for backup polic... | the_stack_v2_python_sparse | cohesity_management_sdk/models/tiering_info.py | cohesity/management-sdk-python | train | 24 |
c9a51ff94bd984e34c43853f9e2b64e18a2493f3 | [
"C = 1\nfor i in range(0, n):\n C = C * 2 * (2 * i + 1) / (i + 2)\nreturn int(C)",
"G = [0] * (n + 1)\nG[0] = G[1] = 1\nfor i in range(2, n + 1):\n for j in range(1, i + 1):\n G[i] += G[j - 1] * G[i - j]\nreturn G[-1]"
] | <|body_start_0|>
C = 1
for i in range(0, n):
C = C * 2 * (2 * i + 1) / (i + 2)
return int(C)
<|end_body_0|>
<|body_start_1|>
G = [0] * (n + 1)
G[0] = G[1] = 1
for i in range(2, n + 1):
for j in range(1, i + 1):
G[i] += G[j - 1] * G... | BST | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BST:
def get_unique_bst_count(self, n: int) -> int:
"""Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:"""
<|body_0|>
def get_unique_bst_count_(self, n: int) -> int:
"""Approach: DP Ti... | stack_v2_sparse_classes_36k_train_026263 | 969 | no_license | [
{
"docstring": "Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:",
"name": "get_unique_bst_count",
"signature": "def get_unique_bst_count(self, n: int) -> int"
},
{
"docstring": "Approach: DP Time Complexity: O(N^... | 2 | null | Implement the Python class `BST` described below.
Class description:
Implement the BST class.
Method signatures and docstrings:
- def get_unique_bst_count(self, n: int) -> int: Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:
- def get... | Implement the Python class `BST` described below.
Class description:
Implement the BST class.
Method signatures and docstrings:
- def get_unique_bst_count(self, n: int) -> int: Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:
- def get... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class BST:
def get_unique_bst_count(self, n: int) -> int:
"""Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:"""
<|body_0|>
def get_unique_bst_count_(self, n: int) -> int:
"""Approach: DP Ti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BST:
def get_unique_bst_count(self, n: int) -> int:
"""Approach: Mathematical Deduction Time Complexity: O(N) Space Complexity: O(1) Formulae: Cn = 2(2n + 1)Cn / n + 2 :param n: :return:"""
C = 1
for i in range(0, n):
C = C * 2 * (2 * i + 1) / (i + 2)
return int(C)
... | the_stack_v2_python_sparse | revisited/trees/unique_binary_search_tree_ii.py | Shiv2157k/leet_code | train | 1 | |
ffbcf06dfb4ca6f267808f4235baf87d86dcaf11 | [
"E0 = a0 * m_e * c ** 2 * k0 / e\nzr = 0.5 * k0 * waist ** 2\nself.k0 = k0\nself.inv_zr = 1.0 / zr\nself.inv_waist2 = 1.0 / waist ** 2\nself.inv_tau2 = 1 / tau ** 2\nself.focal_length = focal_length\nself.t_peak = t_peak\nself.v_antenna = source_v\nself.E0 = E0\nself.beta = beta\nself.zeta = zeta\nself.phi2 = phi2\... | <|body_start_0|>
E0 = a0 * m_e * c ** 2 * k0 / e
zr = 0.5 * k0 * waist ** 2
self.k0 = k0
self.inv_zr = 1.0 / zr
self.inv_waist2 = 1.0 / waist ** 2
self.inv_tau2 = 1 / tau ** 2
self.focal_length = focal_length
self.t_peak = t_peak
self.v_antenna = s... | Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp) | GaussianSTCProfile | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianSTCProfile:
"""Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp)"""
def __init__(self, k0, waist, tau, t_peak, a0, zeta, beta, phi2, dim, focal_length=0, boost=None, source_v=0):
"""Defin... | stack_v2_sparse_classes_36k_train_026264 | 34,589 | permissive | [
{
"docstring": "Define a Gaussian laser profile with spatio-temporal correlations (i.e. with spatial chirp, angular dispersion and temporal chirp) This object can then be passed to the `EM3D` class, as the argument `laser_func`, in order to have a Gaussian with spatio-temporal correlations laser emitted by the ... | 2 | null | Implement the Python class `GaussianSTCProfile` described below.
Class description:
Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp)
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_peak, a0, zeta, beta, ... | Implement the Python class `GaussianSTCProfile` described below.
Class description:
Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp)
Method signatures and docstrings:
- def __init__(self, k0, waist, tau, t_peak, a0, zeta, beta, ... | 091c982f82788209017315e13eb7d0e743687d46 | <|skeleton|>
class GaussianSTCProfile:
"""Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp)"""
def __init__(self, k0, waist, tau, t_peak, a0, zeta, beta, phi2, dim, focal_length=0, boost=None, source_v=0):
"""Defin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianSTCProfile:
"""Class that calculates a Gaussian laser pulse with spatio-temporal correlations (i.e. spatial chirp, angular dispersion and temporal chirp)"""
def __init__(self, k0, waist, tau, t_peak, a0, zeta, beta, phi2, dim, focal_length=0, boost=None, source_v=0):
"""Define a Gaussian ... | the_stack_v2_python_sparse | scripts/field_solvers/laser/laser_profiles.py | giadarol/warp | train | 0 |
25385a28f0f74829106862d6042db499eda90493 | [
"self._has_been_validated: bool = False\nself._source_names: Set[SourceName] = {GITHUB, GITLAB, BITBUCKET}\nself.protocol_override: Optional[Protocol] = None\nself._sources: Dict[SourceName, Source] = {GITHUB: Source(GITHUB, GITHUB_YAML), GITLAB: Source(GITLAB, GITLAB_YAML), BITBUCKET: Source(BITBUCKET, BITBUCKET_Y... | <|body_start_0|>
self._has_been_validated: bool = False
self._source_names: Set[SourceName] = {GITHUB, GITLAB, BITBUCKET}
self.protocol_override: Optional[Protocol] = None
self._sources: Dict[SourceName, Source] = {GITHUB: Source(GITHUB, GITHUB_YAML), GITLAB: Source(GITLAB, GITLAB_YAML),... | Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol | SourceController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SourceController:
"""Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol"""
def __init__(self):
"""SourceController __init__"""
<|body... | stack_v2_sparse_classes_36k_train_026265 | 3,873 | permissive | [
{
"docstring": "SourceController __init__",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Register source with controller :param Optional[Union[Source, SourceName]] source: Source to add :raise SourcesValidatedError: :raise UnknownTypeError:",
"name": "add_source",... | 5 | stack_v2_sparse_classes_30k_train_014296 | Implement the Python class `SourceController` described below.
Class description:
Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol
Method signatures and docstrings:
- def __... | Implement the Python class `SourceController` described below.
Class description:
Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol
Method signatures and docstrings:
- def __... | 1438fc8b1bb7379de66142ffcb0e20b459b59159 | <|skeleton|>
class SourceController:
"""Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol"""
def __init__(self):
"""SourceController __init__"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SourceController:
"""Class encapsulating project information from clowder yaml for controlling clowder :ivar Optional[str] protocol_override: The protocol to override sources without an explicitly specified protcol"""
def __init__(self):
"""SourceController __init__"""
self._has_been_vali... | the_stack_v2_python_sparse | clowder/controller/source_controller.py | JrGoodle/clowder | train | 17 |
7aa8431b6d51e95eb8346bd4493b33ac4f1bee52 | [
"if root is None:\n return ''\nleft = self.serialize(root.left)\nright = self.serialize(root.right)\nreturn str(root.val) + '-' + str(len(left)) + '#' + left + '#' + right",
"if data == '':\n return None\nindex = data.find('#')\nnode = data[:index].split('-')\nroot = TreeNode(int(node[0]))\nlength = int(nod... | <|body_start_0|>
if root is None:
return ''
left = self.serialize(root.left)
right = self.serialize(root.right)
return str(root.val) + '-' + str(len(left)) + '#' + left + '#' + right
<|end_body_0|>
<|body_start_1|>
if data == '':
return None
index... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is Non... | stack_v2_sparse_classes_36k_train_026266 | 2,405 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 752ac00bea40be1e3794d80aa7b2be58c0a548f6 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if root is None:
return ''
left = self.serialize(root.left)
right = self.serialize(root.right)
return str(root.val) + '-' + str(len(left)) + '#' + left + '#' + right
... | the_stack_v2_python_sparse | Code/Serialize and Deserialize BST.py | mws19901118/Leetcode | train | 0 | |
b63161d220b2066182b0baf591d11e67affa1bae | [
"adj_list = {0: [1, 2], 1: [2], 2: [0], 3: []}\nresult = find_friend_groups(adj_list)\nself.assertEqual(result, 2)",
"adj_list = {0: [1, 2], 1: [0, 5], 2: [0], 3: [6], 4: [], 5: [1], 6: [3]}\nresult = find_friend_groups(adj_list)\nself.assertEqual(result, 3)"
] | <|body_start_0|>
adj_list = {0: [1, 2], 1: [2], 2: [0], 3: []}
result = find_friend_groups(adj_list)
self.assertEqual(result, 2)
<|end_body_0|>
<|body_start_1|>
adj_list = {0: [1, 2], 1: [0, 5], 2: [0], 3: [6], 4: [], 5: [1], 6: [3]}
result = find_friend_groups(adj_list)
... | TestFindFriendGroups | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFindFriendGroups:
def test_returns_two_groups(self):
"""Takes in an adjacency list of friends and returns 2"""
<|body_0|>
def test_returns_three_groups(self):
"""Takes in an adjacency list of friends and returns 3"""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_026267 | 674 | permissive | [
{
"docstring": "Takes in an adjacency list of friends and returns 2",
"name": "test_returns_two_groups",
"signature": "def test_returns_two_groups(self)"
},
{
"docstring": "Takes in an adjacency list of friends and returns 3",
"name": "test_returns_three_groups",
"signature": "def test_r... | 2 | stack_v2_sparse_classes_30k_train_006364 | Implement the Python class `TestFindFriendGroups` described below.
Class description:
Implement the TestFindFriendGroups class.
Method signatures and docstrings:
- def test_returns_two_groups(self): Takes in an adjacency list of friends and returns 2
- def test_returns_three_groups(self): Takes in an adjacency list o... | Implement the Python class `TestFindFriendGroups` described below.
Class description:
Implement the TestFindFriendGroups class.
Method signatures and docstrings:
- def test_returns_two_groups(self): Takes in an adjacency list of friends and returns 2
- def test_returns_three_groups(self): Takes in an adjacency list o... | 27ffb6b32d6d18d279c51cfa45bf305a409be5c2 | <|skeleton|>
class TestFindFriendGroups:
def test_returns_two_groups(self):
"""Takes in an adjacency list of friends and returns 2"""
<|body_0|>
def test_returns_three_groups(self):
"""Takes in an adjacency list of friends and returns 3"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestFindFriendGroups:
def test_returns_two_groups(self):
"""Takes in an adjacency list of friends and returns 2"""
adj_list = {0: [1, 2], 1: [2], 2: [0], 3: []}
result = find_friend_groups(adj_list)
self.assertEqual(result, 2)
def test_returns_three_groups(self):
"... | the_stack_v2_python_sparse | src/daily-coding-problem/easy/find-friend-groups/test_find_friend_group.py | nwthomas/code-challenges | train | 2 | |
d0fb03163a22b6906f8d653163f6ac4fab4bc9c7 | [
"langs = hnd.request.headers.get('Accept-Language', '').split(',')\nlangs = get_languages(langs)\nformencode.api.set_stdtranslation(domain='FormEncode', languages=langs)\nself.translate = get_gettextobject('aha', langs).ugettext\nself._ = self.translate\nsuper(ModelCRUDController, self).__init__(hnd, params)",
"q... | <|body_start_0|>
langs = hnd.request.headers.get('Accept-Language', '').split(',')
langs = get_languages(langs)
formencode.api.set_stdtranslation(domain='FormEncode', languages=langs)
self.translate = get_gettextobject('aha', langs).ugettext
self._ = self.translate
super(... | A controller that handles CRUD form of particular model. | ModelCRUDController | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelCRUDController:
"""A controller that handles CRUD form of particular model."""
def __init__(self, hnd, params={}):
"""Initialize method."""
<|body_0|>
def get_index_object(self, start, end):
"""A method to generate query, that gets bunch of object to show in... | stack_v2_sparse_classes_36k_train_026268 | 11,935 | permissive | [
{
"docstring": "Initialize method.",
"name": "__init__",
"signature": "def __init__(self, hnd, params={})"
},
{
"docstring": "A method to generate query, that gets bunch of object to show in the list",
"name": "get_index_object",
"signature": "def get_index_object(self, start, end)"
},... | 3 | null | Implement the Python class `ModelCRUDController` described below.
Class description:
A controller that handles CRUD form of particular model.
Method signatures and docstrings:
- def __init__(self, hnd, params={}): Initialize method.
- def get_index_object(self, start, end): A method to generate query, that gets bunch... | Implement the Python class `ModelCRUDController` described below.
Class description:
A controller that handles CRUD form of particular model.
Method signatures and docstrings:
- def __init__(self, hnd, params={}): Initialize method.
- def get_index_object(self, start, end): A method to generate query, that gets bunch... | e1209f7d44d1c59ff9d373b7d89d414f31a9c28b | <|skeleton|>
class ModelCRUDController:
"""A controller that handles CRUD form of particular model."""
def __init__(self, hnd, params={}):
"""Initialize method."""
<|body_0|>
def get_index_object(self, start, end):
"""A method to generate query, that gets bunch of object to show in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelCRUDController:
"""A controller that handles CRUD form of particular model."""
def __init__(self, hnd, params={}):
"""Initialize method."""
langs = hnd.request.headers.get('Accept-Language', '').split(',')
langs = get_languages(langs)
formencode.api.set_stdtranslation... | the_stack_v2_python_sparse | aha/modelcontroller/crudcontroller.py | Letractively/aha-gae | train | 0 |
7d260fc3f3b9de7d635f8b1acfd65fbd72ca8f14 | [
"super().__init__(d_model, q, v, h, attention_size, **kwargs)\nself._window_size = window_size\nself._padding = padding\nself._q = q\nself._v = v\nself._step = self._window_size - 2 * self._padding\nself._future_mask = nn.Parameter(torch.triu(torch.ones((self._window_size, self._window_size)), diagonal=1).bool(), r... | <|body_start_0|>
super().__init__(d_model, q, v, h, attention_size, **kwargs)
self._window_size = window_size
self._padding = padding
self._q = q
self._v = v
self._step = self._window_size - 2 * self._padding
self._future_mask = nn.Parameter(torch.triu(torch.ones(... | Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, keys and values are divided in chunks using a moving window. Parameters ---------- d_model: ... | MultiHeadAttentionWindow | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadAttentionWindow:
"""Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, keys and values are divided in chunks us... | stack_v2_sparse_classes_36k_train_026269 | 13,552 | permissive | [
{
"docstring": "Initialize the Multi Head Block.",
"name": "__init__",
"signature": "def __init__(self, d_model: int, q: int, v: int, h: int, attention_size: int=None, window_size: Optional[int]=168, padding: Optional[int]=168 // 4, **kwargs)"
},
{
"docstring": "Propagate forward the input throu... | 2 | null | Implement the Python class `MultiHeadAttentionWindow` described below.
Class description:
Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, k... | Implement the Python class `MultiHeadAttentionWindow` described below.
Class description:
Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, k... | 0b801d2d2e828ac480d1097cb3bdd82b1e25c15b | <|skeleton|>
class MultiHeadAttentionWindow:
"""Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, keys and values are divided in chunks us... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadAttentionWindow:
"""Multi Head Attention block with moving window. Given 3 inputs of shape (batch_size, K, d_model), that will be used to compute query, keys and values, we output a self attention tensor of shape (batch_size, K, d_model). Queries, keys and values are divided in chunks using a moving ... | the_stack_v2_python_sparse | code/deep/adarnn/tst/multiHeadAttention.py | jindongwang/transferlearning | train | 12,773 |
548cd1060439ddb42d912ed288abda3fc3dbe3ea | [
"self.names = names\nif len(names) == 0:\n self.leader = None\nelse:\n self.leader = Person(names[0])\n current_person = self.leader\n for name in names[1:]:\n current_person.next = Person(name)\n current_person = current_person.next",
"count = len(self.names)\ntemp = []\nif count > 0:\n... | <|body_start_0|>
self.names = names
if len(names) == 0:
self.leader = None
else:
self.leader = Person(names[0])
current_person = self.leader
for name in names[1:]:
current_person.next = Person(name)
current_person = ... | PeopleChain | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeopleChain:
def __init__(self, names):
"""(Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first person in names."""
<|body_0|>
def get_leader(self):
"""(Person) -> str Return ... | stack_v2_sparse_classes_36k_train_026270 | 3,971 | permissive | [
{
"docstring": "(Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first person in names.",
"name": "__init__",
"signature": "def __init__(self, names)"
},
{
"docstring": "(Person) -> str Return the name of t... | 5 | null | Implement the Python class `PeopleChain` described below.
Class description:
Implement the PeopleChain class.
Method signatures and docstrings:
- def __init__(self, names): (Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first ... | Implement the Python class `PeopleChain` described below.
Class description:
Implement the PeopleChain class.
Method signatures and docstrings:
- def __init__(self, names): (Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first ... | 37009dfdbef9a15c2851bcca2a4e029267e6a02d | <|skeleton|>
class PeopleChain:
def __init__(self, names):
"""(Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first person in names."""
<|body_0|>
def get_leader(self):
"""(Person) -> str Return ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PeopleChain:
def __init__(self, names):
"""(Person, list of str) -> NoneType Create Person objects linked together in the order provided in names. Set the leader of the chain as the first person in names."""
self.names = names
if len(names) == 0:
self.leader = None
... | the_stack_v2_python_sparse | uoft/CSC148H1F Intro to Comp Sci/@week3_stacks/@@Exercise3/chain.py | Reginald-Lee/biji-ben | train | 0 | |
12d669248364c84b34be73e12e34a5be160a9069 | [
"if isinstance(num, str):\n _n = int(num)\nelse:\n _n = num\nif _n < 0 or _n >= MAX_VALUE_LIMIT:\n raise ValueError('Out of range')\nnum_str = str(num)\ncapital_str = ''.join([LOWER_DIGITS[int(i)] for i in num_str])\ns_units = LOWER_UNITS[len(LOWER_UNITS) - len(num_str):]\no = ''.join((f'{u}{d}' for u, d i... | <|body_start_0|>
if isinstance(num, str):
_n = int(num)
else:
_n = num
if _n < 0 or _n >= MAX_VALUE_LIMIT:
raise ValueError('Out of range')
num_str = str(num)
capital_str = ''.join([LOWER_DIGITS[int(i)] for i in num_str])
s_units = LOWE... | ChineseNumbers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChineseNumbers:
def measure_number(num: Union[int, str], upper: bool=False) -> str:
"""将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.measure_number(204, True) '贰佰零肆'"""
<|body_0|>
def order_number(num: Union[int, str], upper: b... | stack_v2_sparse_classes_36k_train_026271 | 4,068 | permissive | [
{
"docstring": "将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.measure_number(204, True) '贰佰零肆'",
"name": "measure_number",
"signature": "def measure_number(num: Union[int, str], upper: bool=False) -> str"
},
{
"docstring": "将数字转化为编号大/小写的中文数字，数字0的中文... | 3 | stack_v2_sparse_classes_30k_train_004078 | Implement the Python class `ChineseNumbers` described below.
Class description:
Implement the ChineseNumbers class.
Method signatures and docstrings:
- def measure_number(num: Union[int, str], upper: bool=False) -> str: 将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.meas... | Implement the Python class `ChineseNumbers` described below.
Class description:
Implement the ChineseNumbers class.
Method signatures and docstrings:
- def measure_number(num: Union[int, str], upper: bool=False) -> str: 将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.meas... | 06407958a6ba3115d783ed6457c2e7355a3f237c | <|skeleton|>
class ChineseNumbers:
def measure_number(num: Union[int, str], upper: bool=False) -> str:
"""将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.measure_number(204, True) '贰佰零肆'"""
<|body_0|>
def order_number(num: Union[int, str], upper: b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChineseNumbers:
def measure_number(num: Union[int, str], upper: bool=False) -> str:
"""将数字转化为计量大/小写的中文数字，数字0的中文形式为“零”。 >>> ChineseNumbers.measure_number(11) '十一' >>> ChineseNumbers.measure_number(204, True) '贰佰零肆'"""
if isinstance(num, str):
_n = int(num)
else:
... | the_stack_v2_python_sparse | borax/numbers.py | kinegratii/borax | train | 67 | |
ceeff7b250ac1858f1286342b799ac0c9968b8ec | [
"if not matrix:\n self.M, self.N = (0, -1)\n return\nself.M, self.N = (len(matrix), len(matrix[0]))\nfor i in xrange(1, self.M):\n matrix[i][0] += matrix[i - 1][0]\nfor j in xrange(1, self.N):\n matrix[0][j] += matrix[0][j - 1]\nfor i in xrange(1, self.M):\n for j in xrange(1, self.N):\n matri... | <|body_start_0|>
if not matrix:
self.M, self.N = (0, -1)
return
self.M, self.N = (len(matrix), len(matrix[0]))
for i in xrange(1, self.M):
matrix[i][0] += matrix[i - 1][0]
for j in xrange(1, self.N):
matrix[0][j] += matrix[0][j - 1]
... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_026272 | 1,750 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | stack_v2_sparse_classes_30k_train_001272 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 00196f836d4bc226ddcb745b17e247c2ed4e9b4b | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if not matrix:
self.M, self.N = (0, -1)
return
self.M, self.N = (len(matrix), len(matrix[0]))
for i in xrange(1, self.M):
matrix[i][0] += matrix[i - 1][0]
for ... | the_stack_v2_python_sparse | Facebook习题/面经/304. Range Sum Query 2D - Immutable.py | signalwolf/Leetcode_by_type | train | 0 | |
80afb49f56f742d7d0d5d04ef6ba5d6c89f73510 | [
"force = req.get_param_as_bool(name='force') or False\ndryrun = req.get_param_as_bool(name='dryrun') or False\nhelper = ConfigdocsHelper(req.context)\nvalidations = self.commit_configdocs(helper, force, dryrun)\nresp.body = self.to_json(validations)\nresp.status = validations.get('code', falcon.HTTP_200)",
"if he... | <|body_start_0|>
force = req.get_param_as_bool(name='force') or False
dryrun = req.get_param_as_bool(name='dryrun') or False
helper = ConfigdocsHelper(req.context)
validations = self.commit_configdocs(helper, force, dryrun)
resp.body = self.to_json(validations)
resp.statu... | Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations. | CommitConfigDocsResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommitConfigDocsResource:
"""Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations."""
def on_post(self, req, resp):
"""Get validations from all UCP components Functionality does not exist yet"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_026273 | 9,265 | permissive | [
{
"docstring": "Get validations from all UCP components Functionality does not exist yet",
"name": "on_post",
"signature": "def on_post(self, req, resp)"
},
{
"docstring": "Attempts to commit the configdocs",
"name": "commit_configdocs",
"signature": "def commit_configdocs(self, helper, ... | 2 | stack_v2_sparse_classes_30k_train_013395 | Implement the Python class `CommitConfigDocsResource` described below.
Class description:
Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations.
Method signatures and docstrings:
- def on_post(self, req, resp): Get validations from all UCP componen... | Implement the Python class `CommitConfigDocsResource` described below.
Class description:
Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations.
Method signatures and docstrings:
- def on_post(self, req, resp): Get validations from all UCP componen... | 14d66afb012025a5289818d8e8d2092ccce19ffa | <|skeleton|>
class CommitConfigDocsResource:
"""Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations."""
def on_post(self, req, resp):
"""Get validations from all UCP components Functionality does not exist yet"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommitConfigDocsResource:
"""Commits the buffered configdocs, if the validations pass (or are overridden (force = true)) Returns the list of validations."""
def on_post(self, req, resp):
"""Get validations from all UCP components Functionality does not exist yet"""
force = req.get_param_a... | the_stack_v2_python_sparse | src/bin/shipyard_airflow/shipyard_airflow/control/configdocs/configdocs_api.py | att-comdev/shipyard | train | 14 |
58acc77c9d1a57ae5ed1fecd150e700e475007bf | [
"for i in range(len(nums)):\n while nums[i] != i + 1 and nums[nums[i] - 1] != nums[i]:\n nums[nums[i] - 1], nums[i] = (nums[i], nums[nums[i] - 1])\nreturn [i + 1 for i, num in enumerate(nums) if num != i + 1]",
"for i in range(len(nums)):\n index = abs(nums[i]) - 1\n nums[index] = -abs(nums[index]... | <|body_start_0|>
for i in range(len(nums)):
while nums[i] != i + 1 and nums[nums[i] - 1] != nums[i]:
nums[nums[i] - 1], nums[i] = (nums[i], nums[nums[i] - 1])
return [i + 1 for i, num in enumerate(nums) if num != i + 1]
<|end_body_0|>
<|body_start_1|>
for i in range(... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDisappearedNumbers2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for i in r... | stack_v2_sparse_classes_36k_train_026274 | 895 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDisappearedNumbers",
"signature": "def findDisappearedNumbers(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "findDisappearedNumbers2",
"signature": "def findDisappearedNumbers2(self... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDisappearedNumbers(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers2(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDisappearedNumbers(self, nums): :type nums: List[int] :rtype: List[int]
- def findDisappearedNumbers2(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
c... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def findDisappearedNumbers2(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDisappearedNumbers(self, nums):
""":type nums: List[int] :rtype: List[int]"""
for i in range(len(nums)):
while nums[i] != i + 1 and nums[nums[i] - 1] != nums[i]:
nums[nums[i] - 1], nums[i] = (nums[i], nums[nums[i] - 1])
return [i + 1 for i,... | the_stack_v2_python_sparse | 401-500/441-450/448-findAllNumbersDisappearedInArray/findAllNumbersDisappearedInArray.py | xuychen/Leetcode | train | 0 | |
13066b6179d3ad277d4f3bbcdc494fd56ff5debe | [
"endpoint = self.base_url + '/authorize'\nbody = {'user_auth': {'client_id': base.getid(consumer), 'scopes': scopes}}\nresponse, body = self.client.post(endpoint, body=body, redirect=redirect)\nredirect_uri = response.headers.get('Location')\nparsed = urlparse.urlparse(redirect_uri)\nquery = dict(urlparse.parse_qsl... | <|body_start_0|>
endpoint = self.base_url + '/authorize'
body = {'user_auth': {'client_id': base.getid(consumer), 'scopes': scopes}}
response, body = self.client.post(endpoint, body=body, redirect=redirect)
redirect_uri = response.headers.get('Location')
parsed = urlparse.urlpars... | Manager class for manipulating identity OAuth authorization codes. | AuthorizationCodeManager | [
"Apache-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthorizationCodeManager:
"""Manager class for manipulating identity OAuth authorization codes."""
def authorize(self, consumer, scopes, redirect=False):
"""Authorize a Consumer for certain scopes, getting an authorization code. The way the provider (Keystone) will return the code is... | stack_v2_sparse_classes_36k_train_026275 | 4,893 | permissive | [
{
"docstring": "Authorize a Consumer for certain scopes, getting an authorization code. The way the provider (Keystone) will return the code is in the header, as an HTTP redirection: 'Location': 'https://foo.com/welcome_back?code=somerandomstring&state=xyz' Utilize Identity API operation: POST /OS-OAUTH2/author... | 2 | stack_v2_sparse_classes_30k_train_019277 | Implement the Python class `AuthorizationCodeManager` described below.
Class description:
Manager class for manipulating identity OAuth authorization codes.
Method signatures and docstrings:
- def authorize(self, consumer, scopes, redirect=False): Authorize a Consumer for certain scopes, getting an authorization code... | Implement the Python class `AuthorizationCodeManager` described below.
Class description:
Manager class for manipulating identity OAuth authorization codes.
Method signatures and docstrings:
- def authorize(self, consumer, scopes, redirect=False): Authorize a Consumer for certain scopes, getting an authorization code... | e1c18ffc181de3a28dccae3bd4f3a08a3ed3d090 | <|skeleton|>
class AuthorizationCodeManager:
"""Manager class for manipulating identity OAuth authorization codes."""
def authorize(self, consumer, scopes, redirect=False):
"""Authorize a Consumer for certain scopes, getting an authorization code. The way the provider (Keystone) will return the code is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthorizationCodeManager:
"""Manager class for manipulating identity OAuth authorization codes."""
def authorize(self, consumer, scopes, redirect=False):
"""Authorize a Consumer for certain scopes, getting an authorization code. The way the provider (Keystone) will return the code is in the heade... | the_stack_v2_python_sparse | keystoneclient/v3/contrib/oauth2/authorization_codes.py | hmunfru/python-keystoneclient | train | 0 |
79b48d5be97a16f98ed183dd40b13a7b71c2f5f8 | [
"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... | * 登录相关接口 | AuthServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthServiceServicer:
"""* 登录相关接口"""
def sendVerificationCode(self, request, context):
"""* 发送验证码 @NoAuth"""
<|body_0|>
def login(self, request, context):
"""* 登录 @NoAuth"""
<|body_1|>
def refreshToken(self, request, context):
"""* 刷新token"""
... | stack_v2_sparse_classes_36k_train_026276 | 5,205 | no_license | [
{
"docstring": "* 发送验证码 @NoAuth",
"name": "sendVerificationCode",
"signature": "def sendVerificationCode(self, request, context)"
},
{
"docstring": "* 登录 @NoAuth",
"name": "login",
"signature": "def login(self, request, context)"
},
{
"docstring": "* 刷新token",
"name": "refres... | 3 | stack_v2_sparse_classes_30k_train_021005 | Implement the Python class `AuthServiceServicer` described below.
Class description:
* 登录相关接口
Method signatures and docstrings:
- def sendVerificationCode(self, request, context): * 发送验证码 @NoAuth
- def login(self, request, context): * 登录 @NoAuth
- def refreshToken(self, request, context): * 刷新token | Implement the Python class `AuthServiceServicer` described below.
Class description:
* 登录相关接口
Method signatures and docstrings:
- def sendVerificationCode(self, request, context): * 发送验证码 @NoAuth
- def login(self, request, context): * 登录 @NoAuth
- def refreshToken(self, request, context): * 刷新token
<|skeleton|>
clas... | 3c8eb4b870087a0baab2a749e2876594b83044ea | <|skeleton|>
class AuthServiceServicer:
"""* 登录相关接口"""
def sendVerificationCode(self, request, context):
"""* 发送验证码 @NoAuth"""
<|body_0|>
def login(self, request, context):
"""* 登录 @NoAuth"""
<|body_1|>
def refreshToken(self, request, context):
"""* 刷新token"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthServiceServicer:
"""* 登录相关接口"""
def sendVerificationCode(self, request, context):
"""* 发送验证码 @NoAuth"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def login(se... | the_stack_v2_python_sparse | buf_grpc/Auth_pb2_grpc.py | heyeping/grpc_auto_project | train | 0 |
2389facaa4178096d6f98d80815317be2d66febc | [
"self.count = 0\nself.size = size\nself.array = []",
"if self.count == self.size:\n return False\nself.array.append(value)\nself.count += 1\nreturn True",
"if self.count == 0:\n return False\ndata = self.array[self.count - 1]\nself.count -= 1\nreturn data"
] | <|body_start_0|>
self.count = 0
self.size = size
self.array = []
<|end_body_0|>
<|body_start_1|>
if self.count == self.size:
return False
self.array.append(value)
self.count += 1
return True
<|end_body_1|>
<|body_start_2|>
if self.count == 0:... | stack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stack:
def __init__(self, size):
"""栈结构 :param size: 栈大小"""
<|body_0|>
def push(self, value):
"""入栈 入栈判满 :param value:"""
<|body_1|>
def pop(self):
"""出栈 出栈判空 :return:"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
self.count =... | stack_v2_sparse_classes_36k_train_026277 | 856 | no_license | [
{
"docstring": "栈结构 :param size: 栈大小",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": "入栈 入栈判满 :param value:",
"name": "push",
"signature": "def push(self, value)"
},
{
"docstring": "出栈 出栈判空 :return:",
"name": "pop",
"signature": "def pop(se... | 3 | stack_v2_sparse_classes_30k_train_010086 | Implement the Python class `stack` described below.
Class description:
Implement the stack class.
Method signatures and docstrings:
- def __init__(self, size): 栈结构 :param size: 栈大小
- def push(self, value): 入栈 入栈判满 :param value:
- def pop(self): 出栈 出栈判空 :return: | Implement the Python class `stack` described below.
Class description:
Implement the stack class.
Method signatures and docstrings:
- def __init__(self, size): 栈结构 :param size: 栈大小
- def push(self, value): 入栈 入栈判满 :param value:
- def pop(self): 出栈 出栈判空 :return:
<|skeleton|>
class stack:
def __init__(self, size)... | 7543af3cf09cc225626af78a44b185ecad52ac24 | <|skeleton|>
class stack:
def __init__(self, size):
"""栈结构 :param size: 栈大小"""
<|body_0|>
def push(self, value):
"""入栈 入栈判满 :param value:"""
<|body_1|>
def pop(self):
"""出栈 出栈判空 :return:"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stack:
def __init__(self, size):
"""栈结构 :param size: 栈大小"""
self.count = 0
self.size = size
self.array = []
def push(self, value):
"""入栈 入栈判满 :param value:"""
if self.count == self.size:
return False
self.array.append(value)
self... | the_stack_v2_python_sparse | stack/array_stack.py | cpeixin/leetcode-bbbbrent | train | 0 | |
9d1a434935dc92f34a1a78f4b3f8b0efdf9596c4 | [
"self.basename = addon\nself.addon_type = ValidAddons.get_addon_type(self.basename)\nself.module = 'gungame51.scripts.%s.%s.%s' % (self.addon_type, self.basename, self.basename)\ninstance = __import__(self.module, globals(), locals(), [''])\nreload(instance)\nself.globals = instance.__dict__\nself.info = self._get_... | <|body_start_0|>
self.basename = addon
self.addon_type = ValidAddons.get_addon_type(self.basename)
self.module = 'gungame51.scripts.%s.%s.%s' % (self.addon_type, self.basename, self.basename)
instance = __import__(self.module, globals(), locals(), [''])
reload(instance)
s... | Class that stores the instance of an included/custom addon | _AddonInstance | [
"Artistic-1.0",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _AddonInstance:
"""Class that stores the instance of an included/custom addon"""
def __init__(self, addon):
"""Called when the addon is first imported"""
<|body_0|>
def _get_addon_info(self):
"""Returns the AddonInfo instance for the addon"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_026278 | 2,595 | permissive | [
{
"docstring": "Called when the addon is first imported",
"name": "__init__",
"signature": "def __init__(self, addon)"
},
{
"docstring": "Returns the AddonInfo instance for the addon",
"name": "_get_addon_info",
"signature": "def _get_addon_info(self)"
}
] | 2 | null | Implement the Python class `_AddonInstance` described below.
Class description:
Class that stores the instance of an included/custom addon
Method signatures and docstrings:
- def __init__(self, addon): Called when the addon is first imported
- def _get_addon_info(self): Returns the AddonInfo instance for the addon | Implement the Python class `_AddonInstance` described below.
Class description:
Class that stores the instance of an included/custom addon
Method signatures and docstrings:
- def __init__(self, addon): Called when the addon is first imported
- def _get_addon_info(self): Returns the AddonInfo instance for the addon
<... | ebf4624626266f552189a32612b8d09cd5b4c5a3 | <|skeleton|>
class _AddonInstance:
"""Class that stores the instance of an included/custom addon"""
def __init__(self, addon):
"""Called when the addon is first imported"""
<|body_0|>
def _get_addon_info(self):
"""Returns the AddonInfo instance for the addon"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _AddonInstance:
"""Class that stores the instance of an included/custom addon"""
def __init__(self, addon):
"""Called when the addon is first imported"""
self.basename = addon
self.addon_type = ValidAddons.get_addon_type(self.basename)
self.module = 'gungame51.scripts.%s.%... | the_stack_v2_python_sparse | cstrike/addons/eventscripts/gungame51/core/addons/instance.py | GunGame-Dev-Team/GunGame51 | train | 0 |
1bd8a79b187fbde38cebe26939079f961c83d336 | [
"super(QDesignatorSortModel, self).__init__(parent)\nself.comparator = QDesignatorComparator()\nself.column = designatorColumn",
"try:\n a = left.data().split(',')[0]\n b = right.data().split(',')[0]\n desigs = list(map(self.comparator.getNormalisedDesignator, [a, b]))\nexcept IndexError:\n desigs = [... | <|body_start_0|>
super(QDesignatorSortModel, self).__init__(parent)
self.comparator = QDesignatorComparator()
self.column = designatorColumn
<|end_body_0|>
<|body_start_1|>
try:
a = left.data().split(',')[0]
b = right.data().split(',')[0]
desigs = lis... | Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default. | QDesignatorSortModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy a... | stack_v2_sparse_classes_36k_train_026279 | 2,928 | no_license | [
{
"docstring": "sorting proxy assures that designators are correctly sorted. For this give a column number, which contains designators. This is to identify whether ordinary sorting or string sorting has to be done",
"name": "__init__",
"signature": "def __init__(self, designatorColumn=0, parent=None)"
... | 2 | stack_v2_sparse_classes_30k_train_012584 | Implement the Python class `QDesignatorSortModel` described below.
Class description:
Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default.
Method signatures and docstrings:
- def __init_... | Implement the Python class `QDesignatorSortModel` described below.
Class description:
Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default.
Method signatures and docstrings:
- def __init_... | 013a5859fc64aa4b43dfe5b493c058fba6dfdcee | <|skeleton|>
class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QDesignatorSortModel:
"""Reimplements sorting of the treeview such, that designator and values numbers are properly sorted according to 'normal' perception. Hence U1, U2, U3 and not U1, U10, U11 as by default."""
def __init__(self, designatorColumn=0, parent=None):
"""sorting proxy assures that d... | the_stack_v2_python_sparse | BOMizator/qdesignatorsortmodel.py | dejfson/BOMizator | train | 1 |
3f2d00cf00e3aa45fd91f013b68b468344bc1925 | [
"email = self.cleaned_data['email']\nself.users_cache = User.objects.filter(email__iexact=email)\nif len(self.users_cache) == 0:\n raise forms.ValidationError(_(\"That e-mail address doesn't have an associated user account. Are you sure you've registered?\"))\nreturn email",
"from utils.emails import send_emai... | <|body_start_0|>
email = self.cleaned_data['email']
self.users_cache = User.objects.filter(email__iexact=email)
if len(self.users_cache) == 0:
raise forms.ValidationError(_("That e-mail address doesn't have an associated user account. Are you sure you've registered?"))
return... | PasswordResetForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetForm:
def clean_email(self):
"""Validates that a user exists with the given e-mail address."""
<|body_0|>
def save(self, domain_override=None, email_template_name='registration/password_reset_email.html', use_https=False, token_generator=default_token_generator,... | stack_v2_sparse_classes_36k_train_026280 | 7,310 | no_license | [
{
"docstring": "Validates that a user exists with the given e-mail address.",
"name": "clean_email",
"signature": "def clean_email(self)"
},
{
"docstring": "Generates a one-use only link for resetting password and sends to the user",
"name": "save",
"signature": "def save(self, domain_ov... | 2 | null | Implement the Python class `PasswordResetForm` described below.
Class description:
Implement the PasswordResetForm class.
Method signatures and docstrings:
- def clean_email(self): Validates that a user exists with the given e-mail address.
- def save(self, domain_override=None, email_template_name='registration/pass... | Implement the Python class `PasswordResetForm` described below.
Class description:
Implement the PasswordResetForm class.
Method signatures and docstrings:
- def clean_email(self): Validates that a user exists with the given e-mail address.
- def save(self, domain_override=None, email_template_name='registration/pass... | 7d0d58afb96b5ba57c5fe5517027555b36d47448 | <|skeleton|>
class PasswordResetForm:
def clean_email(self):
"""Validates that a user exists with the given e-mail address."""
<|body_0|>
def save(self, domain_override=None, email_template_name='registration/password_reset_email.html', use_https=False, token_generator=default_token_generator,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordResetForm:
def clean_email(self):
"""Validates that a user exists with the given e-mail address."""
email = self.cleaned_data['email']
self.users_cache = User.objects.filter(email__iexact=email)
if len(self.users_cache) == 0:
raise forms.ValidationError(_("T... | the_stack_v2_python_sparse | source/frontoffice/forms.py | openstate/Wiekiesjij | train | 0 | |
4e2ed3a6116697bba605177a0604edffdd610b56 | [
"loc = [(i - 1, j - 1), (i - 1, j), (i - 1, j + 1), (i, j - 1), (i, j), (i, j + 1), (i + 1, j - 1), (i + 1, j), (i + 1, j + 1)]\nsum_i = 0\ncnt_i = 0\nfor k in loc:\n if new_arr[k[0]][k[1]] != add_i:\n cnt_i += 1\n sum_i += new_arr[k[0]][k[1]]\nM[i - 1][j - 1] = math.floor(sum_i / cnt_i)",
"new_a... | <|body_start_0|>
loc = [(i - 1, j - 1), (i - 1, j), (i - 1, j + 1), (i, j - 1), (i, j), (i, j + 1), (i + 1, j - 1), (i + 1, j), (i + 1, j + 1)]
sum_i = 0
cnt_i = 0
for k in loc:
if new_arr[k[0]][k[1]] != add_i:
cnt_i += 1
sum_i += new_arr[k[0]]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def add_square(self, i, j, new_arr, M):
"""遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值"""
<|body_0|>
def imageSmoother(self, M):
""":type M: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
loc = [(i ... | stack_v2_sparse_classes_36k_train_026281 | 1,288 | no_license | [
{
"docstring": "遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值",
"name": "add_square",
"signature": "def add_square(self, i, j, new_arr, M)"
},
{
"docstring": ":type M: List[List[int]] :rtype: List[List[int]]",
"name": "imageSmoother",
"signature": "def imageSmoother(self, M)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def add_square(self, i, j, new_arr, M): 遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值
- def imageSmoother(self, M): :type M: List[List[int]] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def add_square(self, i, j, new_arr, M): 遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值
- def imageSmoother(self, M): :type M: List[List[int]] :rtype: List[List[int]]
<|skeleton|>
c... | c37f44f71a0e266aa8078c95506e6aa54ce4660c | <|skeleton|>
class Solution:
def add_square(self, i, j, new_arr, M):
"""遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值"""
<|body_0|>
def imageSmoother(self, M):
""":type M: List[List[int]] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def add_square(self, i, j, new_arr, M):
"""遍历 new_arr 元素，将对应的 M 中元素 M[i-1][j-1] 修改为平均值"""
loc = [(i - 1, j - 1), (i - 1, j), (i - 1, j + 1), (i, j - 1), (i, j), (i, j + 1), (i + 1, j - 1), (i + 1, j), (i + 1, j + 1)]
sum_i = 0
cnt_i = 0
for k in loc:
... | the_stack_v2_python_sparse | 661. Image Smoother/661.py | hotheat/LeetCode | train | 2 | |
5b27cf5c7b5a6a62cd7ee99412bd0dcb6cdb13db | [
"super().__init__()\nself.W = tf.keras.layers.Dense(units)\nself.U = tf.keras.layers.Dense(units)\nself.V = tf.keras.layers.Dense(1)",
"query = s_prev\nvalues = hidden_states\nnewaxis_query = tf.expand_dims(query, 1)\na = self.W(newaxis_query)\nb = self.U(values)\nscore = self.V(tf.nn.tanh(a + b))\nscore = tf.nn.... | <|body_start_0|>
super().__init__()
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1)
<|end_body_0|>
<|body_start_1|>
query = s_prev
values = hidden_states
newaxis_query = tf.expand_dims(query, 1)
... | calculate the attention for machine translation | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""calculate the attention for machine translation"""
def __init__(self, units):
"""ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder hidden state *U - {Dense} units units: the encoder hidde... | stack_v2_sparse_classes_36k_train_026282 | 1,923 | no_license | [
{
"docstring": "ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder hidden state *U - {Dense} units units: the encoder hidden states *V - {Dense} 1 units: the tanh of the sum of the outputs of W and U",
"name": "__init__",
"sig... | 2 | null | Implement the Python class `SelfAttention` described below.
Class description:
calculate the attention for machine translation
Method signatures and docstrings:
- def __init__(self, units): ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder... | Implement the Python class `SelfAttention` described below.
Class description:
calculate the attention for machine translation
Method signatures and docstrings:
- def __init__(self, units): ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder... | 7dafc37d306fcf2ea0f5af5bd97dfd78d388100c | <|skeleton|>
class SelfAttention:
"""calculate the attention for machine translation"""
def __init__(self, units):
"""ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder hidden state *U - {Dense} units units: the encoder hidde... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""calculate the attention for machine translation"""
def __init__(self, units):
"""ARGS: *units :{integer}: the number of hidden units in the alignment model Sets : *W - {Dense} units units: the previous decoder hidden state *U - {Dense} units units: the encoder hidden states *V -... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | AndresSern/holbertonschool-machine_learning-1 | train | 0 |
948ff0c7f12e269d2431db353c5ac4b3fd7ce052 | [
"result = await _booru(ctx.bot.session, BASE_URLS['safebooru']['api'], f'maid {tags}')\nif isinstance(result, str):\n await ctx.send(result)\nelse:\n embed = _process_post(result, BASE_URLS['safebooru']['post'])\n await ctx.send(embed=embed)",
"result = await _booru(ctx.bot.session, BASE_URLS['safebooru'... | <|body_start_0|>
result = await _booru(ctx.bot.session, BASE_URLS['safebooru']['api'], f'maid {tags}')
if isinstance(result, str):
await ctx.send(result)
else:
embed = _process_post(result, BASE_URLS['safebooru']['post'])
await ctx.send(embed=embed)
<|end_body... | Imageboard lookup commands. | Booru | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Booru:
"""Imageboard lookup commands."""
async def maid(self, ctx, *, tags=''):
"""Find a random maid. Optional tags."""
<|body_0|>
async def animeme(self, ctx, *, tags=''):
"""Find a random anime meme. Optional tags."""
<|body_1|>
async def colonles... | stack_v2_sparse_classes_36k_train_026283 | 4,323 | permissive | [
{
"docstring": "Find a random maid. Optional tags.",
"name": "maid",
"signature": "async def maid(self, ctx, *, tags='')"
},
{
"docstring": "Find a random anime meme. Optional tags.",
"name": "animeme",
"signature": "async def animeme(self, ctx, *, tags='')"
},
{
"docstring": ":<... | 4 | stack_v2_sparse_classes_30k_train_013625 | Implement the Python class `Booru` described below.
Class description:
Imageboard lookup commands.
Method signatures and docstrings:
- async def maid(self, ctx, *, tags=''): Find a random maid. Optional tags.
- async def animeme(self, ctx, *, tags=''): Find a random anime meme. Optional tags.
- async def colonlesstha... | Implement the Python class `Booru` described below.
Class description:
Imageboard lookup commands.
Method signatures and docstrings:
- async def maid(self, ctx, *, tags=''): Find a random maid. Optional tags.
- async def animeme(self, ctx, *, tags=''): Find a random anime meme. Optional tags.
- async def colonlesstha... | 9bf3f2125939b66bd1894e509c1b1fa1ab413a6a | <|skeleton|>
class Booru:
"""Imageboard lookup commands."""
async def maid(self, ctx, *, tags=''):
"""Find a random maid. Optional tags."""
<|body_0|>
async def animeme(self, ctx, *, tags=''):
"""Find a random anime meme. Optional tags."""
<|body_1|>
async def colonles... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Booru:
"""Imageboard lookup commands."""
async def maid(self, ctx, *, tags=''):
"""Find a random maid. Optional tags."""
result = await _booru(ctx.bot.session, BASE_URLS['safebooru']['api'], f'maid {tags}')
if isinstance(result, str):
await ctx.send(result)
els... | the_stack_v2_python_sparse | cogs/imgboards/booru.py | DasWolke/kitsuchan-2 | train | 1 |
2b7b2833cfe463367e53354102656bbdf9e10cec | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn WorkbookTable()",
"from .entity import Entity\nfrom .workbook_table_column import WorkbookTableColumn\nfrom .workbook_table_row import WorkbookTableRow\nfrom .workbook_table_sort import WorkbookTableSort\nfrom .workbook_worksheet impor... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return WorkbookTable()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .workbook_table_column import WorkbookTableColumn
from .workbook_table_row import WorkbookTableRow... | WorkbookTable | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkbookTable:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTable:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_36k_train_026284 | 6,969 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: WorkbookTable",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value... | 3 | null | Implement the Python class `WorkbookTable` described below.
Class description:
Implement the WorkbookTable class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTable: Creates a new instance of the appropriate class based on discriminator value... | Implement the Python class `WorkbookTable` described below.
Class description:
Implement the WorkbookTable class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTable: Creates a new instance of the appropriate class based on discriminator value... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class WorkbookTable:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTable:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkbookTable:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> WorkbookTable:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: WorkbookTabl... | the_stack_v2_python_sparse | msgraph/generated/models/workbook_table.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
aa3da683a2b93dcec2afbefb352ff374eebfd878 | [
"super(RLEnvConfiguration, self).__init__(**kwargs)\nself.num = 1\nself.gamma = 0.99\nself.max_episode_steps = 100\nself.set_necessary_configs(**kwargs)\nself.set_unnecessary_configs(**kwargs)",
"try:\n self.env_name = kwargs['env_name']\nexcept Exception as e:\n raise Exception('necessary configs error in ... | <|body_start_0|>
super(RLEnvConfiguration, self).__init__(**kwargs)
self.num = 1
self.gamma = 0.99
self.max_episode_steps = 100
self.set_necessary_configs(**kwargs)
self.set_unnecessary_configs(**kwargs)
<|end_body_0|>
<|body_start_1|>
try:
self.env_n... | class stores the env for rl configuration | RLEnvConfiguration | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEnvConfiguration:
"""class stores the env for rl configuration"""
def __init__(self, **kwargs):
"""initialize settings"""
<|body_0|>
def set_necessary_configs(self, **kwargs):
"""set rl env configs that necessarily provided by user"""
<|body_1|>
de... | stack_v2_sparse_classes_36k_train_026285 | 5,332 | no_license | [
{
"docstring": "initialize settings",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "set rl env configs that necessarily provided by user",
"name": "set_necessary_configs",
"signature": "def set_necessary_configs(self, **kwargs)"
},
{
"docstrin... | 3 | null | Implement the Python class `RLEnvConfiguration` described below.
Class description:
class stores the env for rl configuration
Method signatures and docstrings:
- def __init__(self, **kwargs): initialize settings
- def set_necessary_configs(self, **kwargs): set rl env configs that necessarily provided by user
- def se... | Implement the Python class `RLEnvConfiguration` described below.
Class description:
class stores the env for rl configuration
Method signatures and docstrings:
- def __init__(self, **kwargs): initialize settings
- def set_necessary_configs(self, **kwargs): set rl env configs that necessarily provided by user
- def se... | b0e8f66b3ade742445a41d3d5667032a931d94d2 | <|skeleton|>
class RLEnvConfiguration:
"""class stores the env for rl configuration"""
def __init__(self, **kwargs):
"""initialize settings"""
<|body_0|>
def set_necessary_configs(self, **kwargs):
"""set rl env configs that necessarily provided by user"""
<|body_1|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RLEnvConfiguration:
"""class stores the env for rl configuration"""
def __init__(self, **kwargs):
"""initialize settings"""
super(RLEnvConfiguration, self).__init__(**kwargs)
self.num = 1
self.gamma = 0.99
self.max_episode_steps = 100
self.set_necessary_con... | the_stack_v2_python_sparse | config/rl_config.py | wz139704646/MBRL_on_VAEs | train | 1 |
43fb7e2734c8263ef4e6301bd3d67021ded81e96 | [
"super(ProcessActionHandler, self).initialize(*args, **kwargs)\nself.actions = action_loader.load_actions()\nlogging.info('ProcessActionHandler loaded %d async actions: %s', len(self.actions['async']), str(sorted(self.actions['async'].keys())))",
"payload = pickle.loads(self.request.body)\nasync_actions = payload... | <|body_start_0|>
super(ProcessActionHandler, self).initialize(*args, **kwargs)
self.actions = action_loader.load_actions()
logging.info('ProcessActionHandler loaded %d async actions: %s', len(self.actions['async']), str(sorted(self.actions['async'].keys())))
<|end_body_0|>
<|body_start_1|>
... | Handler for processing Actions. | ProcessActionHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessActionHandler:
"""Handler for processing Actions."""
def initialize(self, *args, **kwargs):
"""Overridden initializer that imports all available Actions."""
<|body_0|>
def post(self):
"""Process an async Action task with the correct Action class."""
... | stack_v2_sparse_classes_36k_train_026286 | 2,558 | permissive | [
{
"docstring": "Overridden initializer that imports all available Actions.",
"name": "initialize",
"signature": "def initialize(self, *args, **kwargs)"
},
{
"docstring": "Process an async Action task with the correct Action class.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `ProcessActionHandler` described below.
Class description:
Handler for processing Actions.
Method signatures and docstrings:
- def initialize(self, *args, **kwargs): Overridden initializer that imports all available Actions.
- def post(self): Process an async Action task with the correct Ac... | Implement the Python class `ProcessActionHandler` described below.
Class description:
Handler for processing Actions.
Method signatures and docstrings:
- def initialize(self, *args, **kwargs): Overridden initializer that imports all available Actions.
- def post(self): Process an async Action task with the correct Ac... | 91753e47aff26d78978ebe7aca70f4a7cbf6a3d4 | <|skeleton|>
class ProcessActionHandler:
"""Handler for processing Actions."""
def initialize(self, *args, **kwargs):
"""Overridden initializer that imports all available Actions."""
<|body_0|>
def post(self):
"""Process an async Action task with the correct Action class."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessActionHandler:
"""Handler for processing Actions."""
def initialize(self, *args, **kwargs):
"""Overridden initializer that imports all available Actions."""
super(ProcessActionHandler, self).initialize(*args, **kwargs)
self.actions = action_loader.load_actions()
log... | the_stack_v2_python_sparse | loaner/web_app/backend/handlers/task/process_action.py | ryangugcloudca/loaner | train | 0 |
9ed2f6621a79b8041965c44e73f378c79502681f | [
"if dry_run:\n return\nthemes = get_themes()\nfor theme in themes:\n css_packages = self.get_themed_packages(theme.theme_dir_name, settings.PIPELINE['STYLESHEETS'])\n from pipeline.packager import Packager\n packager = Packager(storage=self, css_packages=css_packages)\n for package_name in packager.p... | <|body_start_0|>
if dry_run:
return
themes = get_themes()
for theme in themes:
css_packages = self.get_themed_packages(theme.theme_dir_name, settings.PIPELINE['STYLESHEETS'])
from pipeline.packager import Packager
packager = Packager(storage=self, ... | Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'style-vendor': { 'source_filenames': [ 'js/vendor/afontgarde/afontgarde.css', 'css/vendor... | ThemePipelineMixin | [
"AGPL-3.0-only",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThemePipelineMixin:
"""Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'style-vendor': { 'source_filenames': [ 'js/... | stack_v2_sparse_classes_36k_train_026287 | 13,343 | permissive | [
{
"docstring": "This post_process hook is used to package all themed assets.",
"name": "post_process",
"signature": "def post_process(self, paths, dry_run=False, **options)"
},
{
"docstring": "Update paths with the themed assets, Args: prefix: theme prefix for which to update asset paths e.g. 'r... | 2 | null | Implement the Python class `ThemePipelineMixin` described below.
Class description:
Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'styl... | Implement the Python class `ThemePipelineMixin` described below.
Class description:
Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'styl... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class ThemePipelineMixin:
"""Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'style-vendor': { 'source_filenames': [ 'js/... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThemePipelineMixin:
"""Mixin to make sure themed assets are also packaged and used along with non themed assets. if a source asset for a particular package is not present then the default asset is used. e.g. in the following package and for 'red-theme' 'style-vendor': { 'source_filenames': [ 'js/vendor/afontg... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/openedx/core/djangoapps/theming/storage.py | luque/better-ways-of-thinking-about-software | train | 3 |
6325ed7b11217df22ab00563334555430f291120 | [
"rmNum = []\nfor i, val in enumerate(nums):\n if i > 0 and nums[i] == nums[i - 1]:\n rmNum.append(nums[i - 1])\nfor val in rmNum:\n nums.remove(val)\nreturn len(nums)",
"if len(nums) <= 1:\n return len(nums)\nslow = 0\nfor i in range(1, len(nums)):\n if nums[i] != nums[slow]:\n slow += 1... | <|body_start_0|>
rmNum = []
for i, val in enumerate(nums):
if i > 0 and nums[i] == nums[i - 1]:
rmNum.append(nums[i - 1])
for val in rmNum:
nums.remove(val)
return len(nums)
<|end_body_0|>
<|body_start_1|>
if len(nums) <= 1:
re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
rmNum = []
for i, val in e... | stack_v2_sparse_classes_36k_train_026288 | 724 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates",
"signature": "def removeDuplicates(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "removeDuplicates2",
"signature": "def removeDuplicates2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001038 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates2(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 removeDuplicates(self, nums): :type nums: List[int] :rtype: int
- def removeDuplicates2(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def ... | 49d607a66890f3f419c3f0032a57cbd1365edbb7 | <|skeleton|>
class Solution:
def removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def removeDuplicates2(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 removeDuplicates(self, nums):
""":type nums: List[int] :rtype: int"""
rmNum = []
for i, val in enumerate(nums):
if i > 0 and nums[i] == nums[i - 1]:
rmNum.append(nums[i - 1])
for val in rmNum:
nums.remove(val)
return... | the_stack_v2_python_sparse | Easy/026.remove-duplicates-from-sorted-array/remove-duplicates-from-sorted-array.py | henryji96/LeetCode-Solutions | train | 1 | |
81d95e1c461584bec81e29048dae92835a151c10 | [
"super(MACNNClassifier, self).__init__(model_name=model_name, model_save_directory=model_save_directory)\nself.verbose = verbose\nself._is_fitted = False\nself.classes_ = None\nself.nb_classes = -1\nself.input_shape = None\nself.model = None\nself.history = None\nself.kernel_sizes = kernel_sizes\nself.filters = fil... | <|body_start_0|>
super(MACNNClassifier, self).__init__(model_name=model_name, model_save_directory=model_save_directory)
self.verbose = verbose
self._is_fitted = False
self.classes_ = None
self.nb_classes = -1
self.input_shape = None
self.model = None
self... | Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max pooling layer. The final section contains two blocks and a mean reduction followed by... | MACNNClassifier | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MACNNClassifier:
"""Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max pooling layer. The final section contains ... | stack_v2_sparse_classes_36k_train_026289 | 8,060 | permissive | [
{
"docstring": ":param nb_epochs: int, the number of epochs to train the model :param batch_size: int, the number of samples per gradient update. :param rnn_layer: int, filter size for rnn layer :param filters: int, array of shape 2, filter sizes for two convolutional layers :param kernel_sizes: int,array of sh... | 3 | stack_v2_sparse_classes_30k_train_016406 | Implement the Python class `MACNNClassifier` described below.
Class description:
Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max poo... | Implement the Python class `MACNNClassifier` described below.
Class description:
Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max poo... | b565b7499f58f43da7314f1bf26eccce94e88134 | <|skeleton|>
class MACNNClassifier:
"""Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max pooling layer. The final section contains ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MACNNClassifier:
"""Implementation of MACNNClassifier from Chen (2021). [1]_ Overview: Neural Network made of multiple convolutional attention blocks. The block is separated into three sections. Section 1 and 2 are made up of two blocks followed by a max pooling layer. The final section contains two blocks an... | the_stack_v2_python_sparse | sktime_dl/classification/_macnn.py | sktime/sktime-dl | train | 586 |
e03bb58b24774d695efaaa1e9efd72944748a01d | [
"if environment is not None and utils.version_lt(self._version, '1.25'):\n raise errors.InvalidVersion('Setting environment for exec is not supported in API < 1.25')\nif isinstance(cmd, str):\n cmd = utils.split_command(cmd)\nif isinstance(environment, dict):\n environment = utils.utils.format_environment(... | <|body_start_0|>
if environment is not None and utils.version_lt(self._version, '1.25'):
raise errors.InvalidVersion('Setting environment for exec is not supported in API < 1.25')
if isinstance(cmd, str):
cmd = utils.split_command(cmd)
if isinstance(environment, dict):
... | ExecApiMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec insta... | stack_v2_sparse_classes_36k_train_026290 | 6,224 | permissive | [
{
"docstring": "Sets up an exec instance in a running container. Args: container (str): Target container where exec instance will be created cmd (str or list): Command to be executed stdout (bool): Attach to stdout. Default: ``True`` stderr (bool): Attach to stderr. Default: ``True`` stdin (bool): Attach to std... | 4 | stack_v2_sparse_classes_30k_train_000420 | Implement the Python class `ExecApiMixin` described below.
Class description:
Implement the ExecApiMixin class.
Method signatures and docstrings:
- def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None): Sets... | Implement the Python class `ExecApiMixin` described below.
Class description:
Implement the ExecApiMixin class.
Method signatures and docstrings:
- def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None): Sets... | c38656dc7894363f32317affecc3e4279e1163f8 | <|skeleton|>
class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec insta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExecApiMixin:
def exec_create(self, container, cmd, stdout=True, stderr=True, stdin=False, tty=False, privileged=False, user='', environment=None, workdir=None, detach_keys=None):
"""Sets up an exec instance in a running container. Args: container (str): Target container where exec instance will be cr... | the_stack_v2_python_sparse | docker/api/exec_api.py | docker/docker-py | train | 6,473 | |
19010bc22c79b4716d5467797d05bf2d7327b74e | [
"if db_dir is None:\n db_dir = OnChainSQLite3.DEFAULT_PAYMENT_DB_DIR\nif db is None:\n db = OnChainSQLite3.DEFAULT_PAYMENT_DB_PATH\nif db_dir and (not os.path.exists(db_dir)):\n os.makedirs(db_dir)\nself.connection = sqlite3.connect(os.path.join(db_dir, db), check_same_thread=False)\nself.c = self.connecti... | <|body_start_0|>
if db_dir is None:
db_dir = OnChainSQLite3.DEFAULT_PAYMENT_DB_DIR
if db is None:
db = OnChainSQLite3.DEFAULT_PAYMENT_DB_PATH
if db_dir and (not os.path.exists(db_dir)):
os.makedirs(db_dir)
self.connection = sqlite3.connect(os.path.join... | SQLite3 binding for the on-chain transaction model. | OnChainSQLite3 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnChainSQLite3:
"""SQLite3 binding for the on-chain transaction model."""
def __init__(self, db=None, db_dir=None):
"""Instantiate SQLite3 for storing on chain transaction data."""
<|body_0|>
def create(self, txid, amount):
"""Create a transaction entry."""
... | stack_v2_sparse_classes_36k_train_026291 | 16,798 | permissive | [
{
"docstring": "Instantiate SQLite3 for storing on chain transaction data.",
"name": "__init__",
"signature": "def __init__(self, db=None, db_dir=None)"
},
{
"docstring": "Create a transaction entry.",
"name": "create",
"signature": "def create(self, txid, amount)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_train_000136 | Implement the Python class `OnChainSQLite3` described below.
Class description:
SQLite3 binding for the on-chain transaction model.
Method signatures and docstrings:
- def __init__(self, db=None, db_dir=None): Instantiate SQLite3 for storing on chain transaction data.
- def create(self, txid, amount): Create a transa... | Implement the Python class `OnChainSQLite3` described below.
Class description:
SQLite3 binding for the on-chain transaction model.
Method signatures and docstrings:
- def __init__(self, db=None, db_dir=None): Instantiate SQLite3 for storing on chain transaction data.
- def create(self, txid, amount): Create a transa... | a5e99fccf11ed75420775ae3e924c9ce94f2e86d | <|skeleton|>
class OnChainSQLite3:
"""SQLite3 binding for the on-chain transaction model."""
def __init__(self, db=None, db_dir=None):
"""Instantiate SQLite3 for storing on chain transaction data."""
<|body_0|>
def create(self, txid, amount):
"""Create a transaction entry."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OnChainSQLite3:
"""SQLite3 binding for the on-chain transaction model."""
def __init__(self, db=None, db_dir=None):
"""Instantiate SQLite3 for storing on chain transaction data."""
if db_dir is None:
db_dir = OnChainSQLite3.DEFAULT_PAYMENT_DB_DIR
if db is None:
... | the_stack_v2_python_sparse | two1/bitserv/models.py | shayanb/two1 | train | 4 |
c4e849864d94b8b94dc15c79409964e27fd5d805 | [
"test_info = db.get_test(item_id)\nif not test_info:\n pecan.abort(404)\ntest_list = db.get_test_results(item_id)\ntest_name_list = [test_dict[0] for test_dict in test_list]\nreturn {'cpid': test_info.cpid, 'created_at': test_info.created_at, 'duration_seconds': test_info.duration_seconds, 'results': test_name_l... | <|body_start_0|>
test_info = db.get_test(item_id)
if not test_info:
pecan.abort(404)
test_list = db.get_test_results(item_id)
test_name_list = [test_dict[0] for test_dict in test_list]
return {'cpid': test_info.cpid, 'created_at': test_info.created_at, 'duration_secon... | /v1/results handler. | ResultsController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResultsController:
"""/v1/results handler."""
def get_item(self, item_id):
"""Handler for getting item"""
<|body_0|>
def store_item(self, item_in_json):
"""Handler for storing item. Should return new item id"""
<|body_1|>
def get(self):
"""Ge... | stack_v2_sparse_classes_36k_train_026292 | 8,563 | permissive | [
{
"docstring": "Handler for getting item",
"name": "get_item",
"signature": "def get_item(self, item_id)"
},
{
"docstring": "Handler for storing item. Should return new item id",
"name": "store_item",
"signature": "def store_item(self, item_in_json)"
},
{
"docstring": "Get inform... | 3 | stack_v2_sparse_classes_30k_train_006213 | Implement the Python class `ResultsController` described below.
Class description:
/v1/results handler.
Method signatures and docstrings:
- def get_item(self, item_id): Handler for getting item
- def store_item(self, item_in_json): Handler for storing item. Should return new item id
- def get(self): Get information o... | Implement the Python class `ResultsController` described below.
Class description:
/v1/results handler.
Method signatures and docstrings:
- def get_item(self, item_id): Handler for getting item
- def store_item(self, item_in_json): Handler for storing item. Should return new item id
- def get(self): Get information o... | 711f7527c430873edbed72e4f85af916b2088014 | <|skeleton|>
class ResultsController:
"""/v1/results handler."""
def get_item(self, item_id):
"""Handler for getting item"""
<|body_0|>
def store_item(self, item_in_json):
"""Handler for storing item. Should return new item id"""
<|body_1|>
def get(self):
"""Ge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResultsController:
"""/v1/results handler."""
def get_item(self, item_id):
"""Handler for getting item"""
test_info = db.get_test(item_id)
if not test_info:
pecan.abort(404)
test_list = db.get_test_results(item_id)
test_name_list = [test_dict[0] for tes... | the_stack_v2_python_sparse | refstack/api/controllers/v1.py | russell/refstack | train | 0 |
c89969d2dc917bef875f0ea8d6aacb561278d585 | [
"self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)\nself.currently = None\nself.hourly = {}\nself.update = Throttle(MIN_TIME_BETWEEN_UPDATES)(self._update)",
"try:\n forecasts = self._msw.get_future()\n self.currently = forecasts.data[0]\n for forecast in forecasts.data[:8]:\n h... | <|body_start_0|>
self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)
self.currently = None
self.hourly = {}
self.update = Throttle(MIN_TIME_BETWEEN_UPDATES)(self._update)
<|end_body_0|>
<|body_start_1|>
try:
forecasts = self._msw.get_future()
... | Get the latest data from MagicSeaweed. | MagicSeaweedData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
<|body_0|>
def _update(self):
"""Get the latest data from MagicSeaweed."""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_36k_train_026293 | 6,249 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, api_key, spot_id, units)"
},
{
"docstring": "Get the latest data from MagicSeaweed.",
"name": "_update",
"signature": "def _update(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005070 | Implement the Python class `MagicSeaweedData` described below.
Class description:
Get the latest data from MagicSeaweed.
Method signatures and docstrings:
- def __init__(self, api_key, spot_id, units): Initialize the data object.
- def _update(self): Get the latest data from MagicSeaweed. | Implement the Python class `MagicSeaweedData` described below.
Class description:
Get the latest data from MagicSeaweed.
Method signatures and docstrings:
- def __init__(self, api_key, spot_id, units): Initialize the data object.
- def _update(self): Get the latest data from MagicSeaweed.
<|skeleton|>
class MagicSea... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
<|body_0|>
def _update(self):
"""Get the latest data from MagicSeaweed."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)
self.currently = None
self.hourly = {}
self.update = T... | the_stack_v2_python_sparse | homeassistant/components/magicseaweed/sensor.py | BenWoodford/home-assistant | train | 11 |
a7b25973013730ad3e99ad9bc22ef843e64cb1c7 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn IosVppEBook()",
"from .managed_e_book import ManagedEBook\nfrom .managed_e_book import ManagedEBook\nfields: Dict[str, Callable[[Any], None]] = {'appleId': lambda n: setattr(self, 'apple_id', n.get_str_value()), 'genres': lambda n: set... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return IosVppEBook()
<|end_body_0|>
<|body_start_1|>
from .managed_e_book import ManagedEBook
from .managed_e_book import ManagedEBook
fields: Dict[str, Callable[[Any], None]] = {'apple... | A class containing the properties for iOS Vpp eBook. | IosVppEBook | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IosVppEBook:
"""A class containing the properties for iOS Vpp eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosVppEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to... | stack_v2_sparse_classes_36k_train_026294 | 3,718 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: IosVppEBook",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(p... | 3 | null | Implement the Python class `IosVppEBook` described below.
Class description:
A class containing the properties for iOS Vpp eBook.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosVppEBook: Creates a new instance of the appropriate class based on discr... | Implement the Python class `IosVppEBook` described below.
Class description:
A class containing the properties for iOS Vpp eBook.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosVppEBook: Creates a new instance of the appropriate class based on discr... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class IosVppEBook:
"""A class containing the properties for iOS Vpp eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosVppEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IosVppEBook:
"""A class containing the properties for iOS Vpp eBook."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> IosVppEBook:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the dis... | the_stack_v2_python_sparse | msgraph/generated/models/ios_vpp_e_book.py | microsoftgraph/msgraph-sdk-python | train | 135 |
161198a83d588b799819b6e33daa5dcfd821913c | [
"node = node_cache.setdefault(self.resource_id, URIRef(self.resource_id))\ngraph.add((node, RDF.type, getattr(namespace, self.type)))\ngraph.add((node, getattr(namespace, 'id'), Literal(self.resource_id)))\nself.link_collection.to_rdf(subj=node, namespace=namespace, graph=graph, node_cache=node_cache)",
"vertex =... | <|body_start_0|>
node = node_cache.setdefault(self.resource_id, URIRef(self.resource_id))
graph.add((node, RDF.type, getattr(namespace, self.type)))
graph.add((node, getattr(namespace, 'id'), Literal(self.resource_id)))
self.link_collection.to_rdf(subj=node, namespace=namespace, graph=gr... | A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollection representing links from this resource | Resource | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resource:
"""A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollection representing links from this resource... | stack_v2_sparse_classes_36k_train_026295 | 2,016 | permissive | [
{
"docstring": "Graph this Resource as a URIRef on a Graph. Args: namespace: RDF namespace to use for predicates and objects when graphing this resource's links graph: RDF graph node_cache: NodeCache to use for any cached URIRef lookups",
"name": "to_rdf",
"signature": "def to_rdf(self, namespace: Names... | 2 | null | Implement the Python class `Resource` described below.
Class description:
A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollectio... | Implement the Python class `Resource` described below.
Class description:
A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollectio... | eb7d5d18f3d177973c4105c21be9d251250ca8d6 | <|skeleton|>
class Resource:
"""A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollection representing links from this resource... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Resource:
"""A Resource defines a single scanned resource which is directly translatable to a graph node. It contains an id, type name and list of Links. Args: resource_id: id of this resource type: type name of this resource link_collection: a LinkCollection representing links from this resource"""
def ... | the_stack_v2_python_sparse | altimeter/core/resource/resource.py | tableau/altimeter | train | 75 |
e9344b06ef250b4c62c7b61d823cea2600f87fc0 | [
"meeting_user = MeetingUser()\nmeeting_user.is_accepted = is_accepted\nmeeting_user.is_response = may_join\nmeeting_user.is_coordinator = is_coordinator\nmeeting_user.user_id = user_id\nreturn meeting_user",
"meeting_user = MeetingUser()\nmeeting_user.is_coordinator = True\nmeeting_user.is_accepted = 1\nmeeting_u... | <|body_start_0|>
meeting_user = MeetingUser()
meeting_user.is_accepted = is_accepted
meeting_user.is_response = may_join
meeting_user.is_coordinator = is_coordinator
meeting_user.user_id = user_id
return meeting_user
<|end_body_0|>
<|body_start_1|>
meeting_user =... | CreateMeetingAttendees | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateMeetingAttendees:
def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinator=False):
"""For create Meeting, create MeetingUser models. :param user_id: :param is_accepted: :param may_join: :param is_coordinator: :return: List of MeetingUser models."""
... | stack_v2_sparse_classes_36k_train_026296 | 1,133 | no_license | [
{
"docstring": "For create Meeting, create MeetingUser models. :param user_id: :param is_accepted: :param may_join: :param is_coordinator: :return: List of MeetingUser models.",
"name": "_form_attendee",
"signature": "def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinat... | 2 | null | Implement the Python class `CreateMeetingAttendees` described below.
Class description:
Implement the CreateMeetingAttendees class.
Method signatures and docstrings:
- def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinator=False): For create Meeting, create MeetingUser models. :param... | Implement the Python class `CreateMeetingAttendees` described below.
Class description:
Implement the CreateMeetingAttendees class.
Method signatures and docstrings:
- def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinator=False): For create Meeting, create MeetingUser models. :param... | 214cb14eb23f3aa1e32616d666c14d041a2c7dc7 | <|skeleton|>
class CreateMeetingAttendees:
def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinator=False):
"""For create Meeting, create MeetingUser models. :param user_id: :param is_accepted: :param may_join: :param is_coordinator: :return: List of MeetingUser models."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateMeetingAttendees:
def _form_attendee(self, user_id: int, is_accepted=False, may_join=False, is_coordinator=False):
"""For create Meeting, create MeetingUser models. :param user_id: :param is_accepted: :param may_join: :param is_coordinator: :return: List of MeetingUser models."""
meeting... | the_stack_v2_python_sparse | backend/src/api/pool/decorators/meeting_decorators/libs_meeting_decorator/meeting_attendee_libs/attendee_create.py | enixdark/meeting-training-app | train | 0 | |
faaabaeb71d1e73aed74372579eb77123fce9c8d | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('bohorqux_peterg04_rocksdan_yfchen', 'bohorqux_peterg04_rocksdan_yfchen')\nurl = 'http://datamechanics.io/data/eileenli_yidingou/Restaurant.json'\nresponse = urllib.request.urlopen(url).read().decode('utf... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bohorqux_peterg04_rocksdan_yfchen', 'bohorqux_peterg04_rocksdan_yfchen')
url = 'http://datamechanics.io/data/eileenli_yidingou/Restaurant.json'
re... | getRestaurants | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_36k_train_026297 | 4,123 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_004477 | Implement the Python class `getRestaurants` described below.
Class description:
Implement the getRestaurants class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | Implement the Python class `getRestaurants` described below.
Class description:
Implement the getRestaurants class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bohorqux_peterg04_rocksdan_yfchen', ... | the_stack_v2_python_sparse | bohorqux_peterg04_rocksdan_yfchen/getRestaurants.py | ROODAY/course-2017-fal-proj | train | 3 | |
1c502a7a980e08d8ceb7b3a23fef094e82f18e77 | [
"with open(path) as f:\n text = f.read()\nif preamble in text:\n with open(path, 'wt') as f:\n f.write(text.replace(preamble, '', 1))",
"for directory in self.directories:\n python_files = files_with_extension('.py', directory)\n c_files = files_with_extension('.c', directory) + files_with_exte... | <|body_start_0|>
with open(path) as f:
text = f.read()
if preamble in text:
with open(path, 'wt') as f:
f.write(text.replace(preamble, '', 1))
<|end_body_0|>
<|body_start_1|>
for directory in self.directories:
python_files = files_with_extensi... | RemoveCopyrightCommand | [
"MIT",
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoveCopyrightCommand:
def _remove_copyright(self, path, preamble):
"""Remove the copyright if present in the given file."""
<|body_0|>
def run(self):
"""Execution of the command action."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
with open(pat... | stack_v2_sparse_classes_36k_train_026298 | 14,165 | permissive | [
{
"docstring": "Remove the copyright if present in the given file.",
"name": "_remove_copyright",
"signature": "def _remove_copyright(self, path, preamble)"
},
{
"docstring": "Execution of the command action.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010919 | Implement the Python class `RemoveCopyrightCommand` described below.
Class description:
Implement the RemoveCopyrightCommand class.
Method signatures and docstrings:
- def _remove_copyright(self, path, preamble): Remove the copyright if present in the given file.
- def run(self): Execution of the command action. | Implement the Python class `RemoveCopyrightCommand` described below.
Class description:
Implement the RemoveCopyrightCommand class.
Method signatures and docstrings:
- def _remove_copyright(self, path, preamble): Remove the copyright if present in the given file.
- def run(self): Execution of the command action.
<|s... | fa6808a6ca8063751da92f683f2b810a0690a462 | <|skeleton|>
class RemoveCopyrightCommand:
def _remove_copyright(self, path, preamble):
"""Remove the copyright if present in the given file."""
<|body_0|>
def run(self):
"""Execution of the command action."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoveCopyrightCommand:
def _remove_copyright(self, path, preamble):
"""Remove the copyright if present in the given file."""
with open(path) as f:
text = f.read()
if preamble in text:
with open(path, 'wt') as f:
f.write(text.replace(preamble, ''... | the_stack_v2_python_sparse | setup.py | mramospe/minkit | train | 0 | |
d5b4d11dedf2138bffd1c08e7f3cb0ff528c2f91 | [
"self.p0 = p0\nself.p1 = p1\nself.p2 = p2\nself.p3 = p3",
"\"\"\"\n Caso en que la coordenada \"y\" es igual a cero. \n \"\"\"\nif self.y == 0:\n '\\n Caso en que la coordenada \"x\" es mayor que cero. \\n '\n if checkSign(self.x) == 2:\n return 0\n '\\n ... | <|body_start_0|>
self.p0 = p0
self.p1 = p1
self.p2 = p2
self.p3 = p3
<|end_body_0|>
<|body_start_1|>
"""
Caso en que la coordenada "y" es igual a cero.
"""
if self.y == 0:
'\n Caso en que la coordenada "x" es mayor ... | Face3d | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Face3d:
def __init__(self, p0, p1, p2, p3):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d"""
<|body_0|>
def Triangulate(self):
"""Metodo que se encarga de triangular una cara en el e... | stack_v2_sparse_classes_36k_train_026299 | 3,592 | no_license | [
{
"docstring": "@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d",
"name": "__init__",
"signature": "def __init__(self, p0, p1, p2, p3)"
},
{
"docstring": "Metodo que se encarga de triangular una cara en el espacio 3D... | 3 | stack_v2_sparse_classes_30k_train_002357 | Implement the Python class `Face3d` described below.
Class description:
Implement the Face3d class.
Method signatures and docstrings:
- def __init__(self, p0, p1, p2, p3): @param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d
- def Triangulate(... | Implement the Python class `Face3d` described below.
Class description:
Implement the Face3d class.
Method signatures and docstrings:
- def __init__(self, p0, p1, p2, p3): @param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d
- def Triangulate(... | a93de278ea92ad8d57d66fcb76744d394400bd11 | <|skeleton|>
class Face3d:
def __init__(self, p0, p1, p2, p3):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d"""
<|body_0|>
def Triangulate(self):
"""Metodo que se encarga de triangular una cara en el e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Face3d:
def __init__(self, p0, p1, p2, p3):
"""@param p0: instancia de Point3d @param p1: instancia de Point3d @param p2: instancia de Point3d @param p3: instancia de Point3d"""
self.p0 = p0
self.p1 = p1
self.p2 = p2
self.p3 = p3
def Triangulate(self):
"""M... | the_stack_v2_python_sparse | geometry/controller/geometry_3d/face_3d.py | nvergarayi/Cubicador | train | 0 |
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