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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7e18f3a53eb3da2fc84c24b88957c8bf4d775c1e | [
"if self._units in ('C', 'F'):\n return round(self._state, 1)\nif isinstance(self._state, float):\n return round(self._state, 2)\nreturn self._state",
"if self._units in ['C', 'F']:\n return DEVICE_CLASS_TEMPERATURE\nreturn None",
"if self._units == 'C':\n return TEMP_CELSIUS\nif self._units == 'F':... | <|body_start_0|>
if self._units in ('C', 'F'):
return round(self._state, 1)
if isinstance(self._state, float):
return round(self._state, 2)
return self._state
<|end_body_0|>
<|body_start_1|>
if self._units in ['C', 'F']:
return DEVICE_CLASS_TEMPERATUR... | Representation of a multi level sensor Z-Wave sensor. | ZWaveMultilevelSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZWaveMultilevelSensor:
"""Representation of a multi level sensor Z-Wave sensor."""
def state(self):
"""Return the state of the sensor."""
<|body_0|>
def device_class(self):
"""Return the class of this device."""
<|body_1|>
def unit_of_measurement(sel... | stack_v2_sparse_classes_36k_train_006900 | 3,651 | permissive | [
{
"docstring": "Return the state of the sensor.",
"name": "state",
"signature": "def state(self)"
},
{
"docstring": "Return the class of this device.",
"name": "device_class",
"signature": "def device_class(self)"
},
{
"docstring": "Return the unit the value is expressed in.",
... | 3 | stack_v2_sparse_classes_30k_train_004197 | Implement the Python class `ZWaveMultilevelSensor` described below.
Class description:
Representation of a multi level sensor Z-Wave sensor.
Method signatures and docstrings:
- def state(self): Return the state of the sensor.
- def device_class(self): Return the class of this device.
- def unit_of_measurement(self): ... | Implement the Python class `ZWaveMultilevelSensor` described below.
Class description:
Representation of a multi level sensor Z-Wave sensor.
Method signatures and docstrings:
- def state(self): Return the state of the sensor.
- def device_class(self): Return the class of this device.
- def unit_of_measurement(self): ... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class ZWaveMultilevelSensor:
"""Representation of a multi level sensor Z-Wave sensor."""
def state(self):
"""Return the state of the sensor."""
<|body_0|>
def device_class(self):
"""Return the class of this device."""
<|body_1|>
def unit_of_measurement(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZWaveMultilevelSensor:
"""Representation of a multi level sensor Z-Wave sensor."""
def state(self):
"""Return the state of the sensor."""
if self._units in ('C', 'F'):
return round(self._state, 1)
if isinstance(self._state, float):
return round(self._state,... | the_stack_v2_python_sparse | homeassistant/components/zwave/sensor.py | BenWoodford/home-assistant | train | 11 |
44959a235aff017cba9a1bc0dcf0283f4d22c0a9 | [
"p_current = head\nval_lsit = []\nwhile p_current:\n val_lsit.append(p_current.val)\n p_current = p_current.next\nreturn self.sortedArrayToBST(val_lsit)",
"if nums:\n mid = len(nums) / 2\n node = TreeNode(nums[mid])\n node.left = self.sortedArrayToBST(nums[:mid])\n node.right = self.sortedArrayT... | <|body_start_0|>
p_current = head
val_lsit = []
while p_current:
val_lsit.append(p_current.val)
p_current = p_current.next
return self.sortedArrayToBST(val_lsit)
<|end_body_0|>
<|body_start_1|>
if nums:
mid = len(nums) / 2
node = T... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortedListToBST(self, head):
""":type head: ListNode :rtype: TreeNode"""
<|body_0|>
def sortedArrayToBST(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
p_current = head
va... | stack_v2_sparse_classes_36k_train_006901 | 1,262 | no_license | [
{
"docstring": ":type head: ListNode :rtype: TreeNode",
"name": "sortedListToBST",
"signature": "def sortedListToBST(self, head)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "sortedArrayToBST",
"signature": "def sortedArrayToBST(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedListToBST(self, head): :type head: ListNode :rtype: TreeNode
- def sortedArrayToBST(self, nums): :type nums: List[int] :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedListToBST(self, head): :type head: ListNode :rtype: TreeNode
- def sortedArrayToBST(self, nums): :type nums: List[int] :rtype: TreeNode
<|skeleton|>
class Solution:
... | b7e59ef26a00ebdd3c253ca63f66ea079f9bca54 | <|skeleton|>
class Solution:
def sortedListToBST(self, head):
""":type head: ListNode :rtype: TreeNode"""
<|body_0|>
def sortedArrayToBST(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortedListToBST(self, head):
""":type head: ListNode :rtype: TreeNode"""
p_current = head
val_lsit = []
while p_current:
val_lsit.append(p_current.val)
p_current = p_current.next
return self.sortedArrayToBST(val_lsit)
def sorte... | the_stack_v2_python_sparse | DFS/109_covert_sorted_list_to_BST.py | dodoyuan/leetcode_python | train | 1 | |
1ea721f901acc1e541f1bfeb8ef637e37c2577ff | [
"l = 0\nr = len(List) - 1\nif l > r:\n return None\nif l == r:\n return TreeNode(List[0])\nmid = int((l + r) / 2)\nroot = TreeNode(List[mid])\nroot.left = self.build_tree(List[:mid])\nroot.right = self.build_tree(List[mid + 1:])\nreturn root",
"if not root:\n return []\nqueue = []\nresult = []\nqueue.app... | <|body_start_0|>
l = 0
r = len(List) - 1
if l > r:
return None
if l == r:
return TreeNode(List[0])
mid = int((l + r) / 2)
root = TreeNode(List[mid])
root.left = self.build_tree(List[:mid])
root.right = self.build_tree(List[mid + 1:]... | BinaryTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryTree:
def build_tree(self, List):
"""构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树"""
<|body_0|>
def PrintFromTopToBottom(self, root):
"""层序遍历二叉树：从上到下打印二叉树"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
l = 0
r = len(List) - 1
if l > ... | stack_v2_sparse_classes_36k_train_006902 | 3,791 | no_license | [
{
"docstring": "构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树",
"name": "build_tree",
"signature": "def build_tree(self, List)"
},
{
"docstring": "层序遍历二叉树：从上到下打印二叉树",
"name": "PrintFromTopToBottom",
"signature": "def PrintFromTopToBottom(self, root)"
}
] | 2 | null | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def build_tree(self, List): 构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树
- def PrintFromTopToBottom(self, root): 层序遍历二叉树：从上到下打印二叉树 | Implement the Python class `BinaryTree` described below.
Class description:
Implement the BinaryTree class.
Method signatures and docstrings:
- def build_tree(self, List): 构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树
- def PrintFromTopToBottom(self, root): 层序遍历二叉树：从上到下打印二叉树
<|skeleton|>
class BinaryTree:
def build_tre... | 4e4f739402b95691f6c91411da26d7d3bfe042b6 | <|skeleton|>
class BinaryTree:
def build_tree(self, List):
"""构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树"""
<|body_0|>
def PrintFromTopToBottom(self, root):
"""层序遍历二叉树：从上到下打印二叉树"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryTree:
def build_tree(self, List):
"""构建一棵二叉树，数组必须为中序遍历类型，如果数组排好序，那么得到平衡二叉树"""
l = 0
r = len(List) - 1
if l > r:
return None
if l == r:
return TreeNode(List[0])
mid = int((l + r) / 2)
root = TreeNode(List[mid])
root.l... | the_stack_v2_python_sparse | 剑指offer/57.二叉树的下一个结点.py | hugechuanqi/Algorithms-and-Data-Structures | train | 3 | |
babf78034a9a30fff341ff3da6eb4a6214f9e009 | [
"Target(id=1, user=2, type='standard', latitude=10, longitude=-10, orientation='n', shape='circle', background_color='white', alphanumeric='a', alphanumeric_color='black')\nTarget(type='qrc', latitude=10, longitude=-10, description='http://test.com')\nTarget(type='off_axis', latitude=10, longitude=-10, orientation=... | <|body_start_0|>
Target(id=1, user=2, type='standard', latitude=10, longitude=-10, orientation='n', shape='circle', background_color='white', alphanumeric='a', alphanumeric_color='black')
Target(type='qrc', latitude=10, longitude=-10, description='http://test.com')
Target(type='off_axis', latitu... | Tests the Target model for validation and serialization. | TestTarget | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestTarget:
"""Tests the Target model for validation and serialization."""
def test_valid(self):
"""Test valid inputs."""
<|body_0|>
def test_invalid(self):
"""Test invalid inputs."""
<|body_1|>
def test_serialize(self):
"""Test serialization... | stack_v2_sparse_classes_36k_train_006903 | 14,890 | permissive | [
{
"docstring": "Test valid inputs.",
"name": "test_valid",
"signature": "def test_valid(self)"
},
{
"docstring": "Test invalid inputs.",
"name": "test_invalid",
"signature": "def test_invalid(self)"
},
{
"docstring": "Test serialization.",
"name": "test_serialize",
"signa... | 4 | stack_v2_sparse_classes_30k_val_000505 | Implement the Python class `TestTarget` described below.
Class description:
Tests the Target model for validation and serialization.
Method signatures and docstrings:
- def test_valid(self): Test valid inputs.
- def test_invalid(self): Test invalid inputs.
- def test_serialize(self): Test serialization.
- def test_de... | Implement the Python class `TestTarget` described below.
Class description:
Tests the Target model for validation and serialization.
Method signatures and docstrings:
- def test_valid(self): Test valid inputs.
- def test_invalid(self): Test invalid inputs.
- def test_serialize(self): Test serialization.
- def test_de... | 509f36562fc895433fcd01da755a35dd04581025 | <|skeleton|>
class TestTarget:
"""Tests the Target model for validation and serialization."""
def test_valid(self):
"""Test valid inputs."""
<|body_0|>
def test_invalid(self):
"""Test invalid inputs."""
<|body_1|>
def test_serialize(self):
"""Test serialization... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestTarget:
"""Tests the Target model for validation and serialization."""
def test_valid(self):
"""Test valid inputs."""
Target(id=1, user=2, type='standard', latitude=10, longitude=-10, orientation='n', shape='circle', background_color='white', alphanumeric='a', alphanumeric_color='blac... | the_stack_v2_python_sparse | client/interop/types_test.py | matcheydj/interop | train | 1 |
884b86e1c63265020f9e0eb79cf147ec697ffe39 | [
"self.conditions_dict = conditions_dict\nself.axes_vars = axes_vars\nself.x_axis_label = labels['x_axis']\nself.y_axis_label = labels['y_axis']\nsuper(VegaGraphBarBase, self).__init__(output_path, input_path, config_dir, labels)\nself.graph_type = 'barbase'",
"pandas_df = super(VegaGraphBarBase, self).parse_jsons... | <|body_start_0|>
self.conditions_dict = conditions_dict
self.axes_vars = axes_vars
self.x_axis_label = labels['x_axis']
self.y_axis_label = labels['y_axis']
super(VegaGraphBarBase, self).__init__(output_path, input_path, config_dir, labels)
self.graph_type = 'barbase'
<|e... | Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBar and VegaGraphScatter. Attributes: output_path: the output directory to write the ... | VegaGraphBarBase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VegaGraphBarBase:
"""Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBar and VegaGraphScatter. Attributes: out... | stack_v2_sparse_classes_36k_train_006904 | 16,246 | no_license | [
{
"docstring": "Instantiate the input arguments. References the base class __init__ to instantiate recurring ones.",
"name": "__init__",
"signature": "def __init__(self, output_path, input_path, config_dir, labels, conditions_dict, axes_vars)"
},
{
"docstring": "Parses the input json files using... | 2 | stack_v2_sparse_classes_30k_train_014019 | Implement the Python class `VegaGraphBarBase` described below.
Class description:
Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBa... | Implement the Python class `VegaGraphBarBase` described below.
Class description:
Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBa... | d42ec8e8328117d70fb910f2d1f751ce15862810 | <|skeleton|>
class VegaGraphBarBase:
"""Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBar and VegaGraphScatter. Attributes: out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VegaGraphBarBase:
"""Class for converting json outputs of different algorithms to vega-specific bar or scatter graph json files. This class is a child class of VegaGraphBase and inherits all the methods and variables. It serves as a base class to VegaGraphBar and VegaGraphScatter. Attributes: output_path: the... | the_stack_v2_python_sparse | scripts/json2vega.py | gunrock/io | train | 11 |
2382713acf4aaceb8e09d117e2612d6e6b5bc617 | [
"for i in range(rows):\n for j in range(cols):\n if matrix[i * cols + j] == path[0]:\n if self.find(list(matrix), rows, cols, path[1:], i, j):\n return True",
"if not path:\n return True\nmatrix[i * cols + j] = '0'\nif j + 1 < cols and matrix[i * cols + (j + 1)] == path[0]:\... | <|body_start_0|>
for i in range(rows):
for j in range(cols):
if matrix[i * cols + j] == path[0]:
if self.find(list(matrix), rows, cols, path[1:], i, j):
return True
<|end_body_0|>
<|body_start_1|>
if not path:
return Tr... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPath(self, matrix, rows, cols, path):
"""首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直到路径上的所有字符都在矩阵中找到相应的位置。 由于回朔法的递归特性，路径可以被开成一个栈。当在矩阵中定位了路径中前n个字符的位置之后， 在与第n个字符对应的格子的周围都没有找到第n+1个字符，这... | stack_v2_sparse_classes_36k_train_006905 | 3,558 | no_license | [
{
"docstring": "首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直到路径上的所有字符都在矩阵中找到相应的位置。 由于回朔法的递归特性，路径可以被开成一个栈。当在矩阵中定位了路径中前n个字符的位置之后， 在与第n个字符对应的格子的周围都没有找到第n+1个字符，这个时候只要在路径上回到第n-1个字符，重新定位第n个字符。 由于路径不能重复进入矩阵的格子，还需要定义和字符矩阵大小一样的布尔值矩阵... | 2 | stack_v2_sparse_classes_30k_train_018336 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPath(self, matrix, rows, cols, path): 首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPath(self, matrix, rows, cols, path): 首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直... | c756fe54e8e17e9ba0bfdab5fccc24ac89263d90 | <|skeleton|>
class Solution:
def hasPath(self, matrix, rows, cols, path):
"""首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直到路径上的所有字符都在矩阵中找到相应的位置。 由于回朔法的递归特性，路径可以被开成一个栈。当在矩阵中定位了路径中前n个字符的位置之后， 在与第n个字符对应的格子的周围都没有找到第n+1个字符，这... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPath(self, matrix, rows, cols, path):
"""首先，在矩阵中任选一个格子作为路径的起点。如果路径上的第i个字符不是ch，那么这个格子不可能处在路径上的 第i个位置。如果路径上的第i个字符正好是ch，那么往相邻的格子寻找路径上的第i+1个字符。 除在矩阵边界上的格子之外，其他格子都有4个相邻的格子。重复这个过程直到路径上的所有字符都在矩阵中找到相应的位置。 由于回朔法的递归特性，路径可以被开成一个栈。当在矩阵中定位了路径中前n个字符的位置之后， 在与第n个字符对应的格子的周围都没有找到第n+1个字符，这个时候只要在路径上回到第n-... | the_stack_v2_python_sparse | newcoder_offer/has_path.py | EarthChen/LeetCode_Record | train | 0 | |
2e75b1dfa79a3d7e52dbc65e4ace1a241ffe6ecb | [
"self.url = url\nself.query = query\nself.make_request = make_request\nself.use_get = use_get",
"if rows:\n self.query['rows'] = rows\nif 'rows' not in self.query:\n self.query['rows'] = 10\nself.query['start'] = 0\nend = False\ndocs_retrieved = 0\nwhile not end:\n if self.use_get:\n http_response... | <|body_start_0|>
self.url = url
self.query = query
self.make_request = make_request
self.use_get = use_get
<|end_body_0|>
<|body_start_1|>
if rows:
self.query['rows'] = rows
if 'rows' not in self.query:
self.query['rows'] = 10
self.query['... | Implements the concept of cursor in relational databases | Cursor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cursor:
"""Implements the concept of cursor in relational databases"""
def __init__(self, url, query, make_request=requests, use_get=False):
"""Cursor initialization"""
<|body_0|>
def fetch(self, rows=None):
"""Generator method that grabs all the documents in bul... | stack_v2_sparse_classes_36k_train_006906 | 47,807 | no_license | [
{
"docstring": "Cursor initialization",
"name": "__init__",
"signature": "def __init__(self, url, query, make_request=requests, use_get=False)"
},
{
"docstring": "Generator method that grabs all the documents in bulk sets of 'rows' documents :param rows: number of rows for each request",
"na... | 2 | null | Implement the Python class `Cursor` described below.
Class description:
Implements the concept of cursor in relational databases
Method signatures and docstrings:
- def __init__(self, url, query, make_request=requests, use_get=False): Cursor initialization
- def fetch(self, rows=None): Generator method that grabs all... | Implement the Python class `Cursor` described below.
Class description:
Implements the concept of cursor in relational databases
Method signatures and docstrings:
- def __init__(self, url, query, make_request=requests, use_get=False): Cursor initialization
- def fetch(self, rows=None): Generator method that grabs all... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class Cursor:
"""Implements the concept of cursor in relational databases"""
def __init__(self, url, query, make_request=requests, use_get=False):
"""Cursor initialization"""
<|body_0|>
def fetch(self, rows=None):
"""Generator method that grabs all the documents in bul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cursor:
"""Implements the concept of cursor in relational databases"""
def __init__(self, url, query, make_request=requests, use_get=False):
"""Cursor initialization"""
self.url = url
self.query = query
self.make_request = make_request
self.use_get = use_get
d... | the_stack_v2_python_sparse | repoData/RedTuna-mysolr/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
14b0ec57320083bc44b3a228ac206941b7b9e587 | [
"files = self.files.getlist('file_field')\nfor file in files:\n validators.validate_filename(file.name)\n if not file:\n raise forms.ValidationError('Could not read file: %(file_name)s', params={'file_name': file.name})\nfor file in files:\n if file.size > ActiveProject.INDIVIDUAL_FILE_SIZE_LIMIT:\n... | <|body_start_0|>
files = self.files.getlist('file_field')
for file in files:
validators.validate_filename(file.name)
if not file:
raise forms.ValidationError('Could not read file: %(file_name)s', params={'file_name': file.name})
for file in files:
... | Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root. | UploadFilesForm | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadFilesForm:
"""Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root."""
def clean_file_field(self):
"""Check for file name, size limits and whether they are readable"""
<|body_0|>
def perform_action(self):
... | stack_v2_sparse_classes_36k_train_006907 | 39,361 | permissive | [
{
"docstring": "Check for file name, size limits and whether they are readable",
"name": "clean_file_field",
"signature": "def clean_file_field(self)"
},
{
"docstring": "Upload the files",
"name": "perform_action",
"signature": "def perform_action(self)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000960 | Implement the Python class `UploadFilesForm` described below.
Class description:
Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root.
Method signatures and docstrings:
- def clean_file_field(self): Check for file name, size limits and whether they are readabl... | Implement the Python class `UploadFilesForm` described below.
Class description:
Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root.
Method signatures and docstrings:
- def clean_file_field(self): Check for file name, size limits and whether they are readabl... | e7c8ed0b07a4c9a1b4007f6089f59aafa6a3ac57 | <|skeleton|>
class UploadFilesForm:
"""Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root."""
def clean_file_field(self):
"""Check for file name, size limits and whether they are readable"""
<|body_0|>
def perform_action(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UploadFilesForm:
"""Form for uploading multiple files to a project. `subdir` is the project subdirectory relative to the file root."""
def clean_file_field(self):
"""Check for file name, size limits and whether they are readable"""
files = self.files.getlist('file_field')
for file... | the_stack_v2_python_sparse | physionet-django/project/forms.py | tompollard/physionet-build | train | 0 |
403b4b9ba23ba10354f7848c7a985f2d35c59b54 | [
"details = {}\nselector = 'table > tbody > tr'\nfor resource, unit, used in root.cssselect(selector):\n name = resource.findtext('strong').strip()\n details[name] = (used.text.strip(), unit.text.strip())\nreturn details",
"events = []\nselector = '#ae-billing-logs-table > tbody > tr'\nfor date_elt, event_el... | <|body_start_0|>
details = {}
selector = 'table > tbody > tr'
for resource, unit, used in root.cssselect(selector):
name = resource.findtext('strong').strip()
details[name] = (used.text.strip(), unit.text.strip())
return details
<|end_body_0|>
<|body_start_1|>
... | An API for the contents of /billing/history as structured data. | BillingHistory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BillingHistory:
"""An API for the contents of /billing/history as structured data."""
def _usage_report_dict(self, root):
"""Extract usage report details from the element that contains the table with columns resource, unit, used."""
<|body_0|>
def event_dicts(self):
... | stack_v2_sparse_classes_36k_train_006908 | 15,505 | no_license | [
{
"docstring": "Extract usage report details from the element that contains the table with columns resource, unit, used.",
"name": "_usage_report_dict",
"signature": "def _usage_report_dict(self, root)"
},
{
"docstring": "Information about each row in the billing history table. Entries match the... | 2 | stack_v2_sparse_classes_30k_test_000204 | Implement the Python class `BillingHistory` described below.
Class description:
An API for the contents of /billing/history as structured data.
Method signatures and docstrings:
- def _usage_report_dict(self, root): Extract usage report details from the element that contains the table with columns resource, unit, use... | Implement the Python class `BillingHistory` described below.
Class description:
An API for the contents of /billing/history as structured data.
Method signatures and docstrings:
- def _usage_report_dict(self, root): Extract usage report details from the element that contains the table with columns resource, unit, use... | c4ad2ad67b497ce411a9e5d6d6db407ee304491f | <|skeleton|>
class BillingHistory:
"""An API for the contents of /billing/history as structured data."""
def _usage_report_dict(self, root):
"""Extract usage report details from the element that contains the table with columns resource, unit, used."""
<|body_0|>
def event_dicts(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BillingHistory:
"""An API for the contents of /billing/history as structured data."""
def _usage_report_dict(self, root):
"""Extract usage report details from the element that contains the table with columns resource, unit, used."""
details = {}
selector = 'table > tbody > tr'
... | the_stack_v2_python_sparse | src/gae_dashboard/parsers.py | summer-liu/analytics | train | 1 |
e14f5f493f1270683ae216a11c4bef6faf33476c | [
"exp_last_playthrough = user_domain.ExpUserLastPlaythrough('user_id0', 'exp_id0', 0, 'last_updated', 'state0')\nself.assertEqual(exp_last_playthrough.id, 'user_id0.exp_id0')\nself.assertEqual(exp_last_playthrough.user_id, 'user_id0')\nself.assertEqual(exp_last_playthrough.exploration_id, 'exp_id0')\nself.assertEqua... | <|body_start_0|>
exp_last_playthrough = user_domain.ExpUserLastPlaythrough('user_id0', 'exp_id0', 0, 'last_updated', 'state0')
self.assertEqual(exp_last_playthrough.id, 'user_id0.exp_id0')
self.assertEqual(exp_last_playthrough.user_id, 'user_id0')
self.assertEqual(exp_last_playthrough.ex... | Testing domain object for an exploration last playthrough model. | ExpUserLastPlaythroughTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpUserLastPlaythroughTests:
"""Testing domain object for an exploration last playthrough model."""
def test_initialization(self):
"""Testing init method."""
<|body_0|>
def test_update_last_played_information(self):
"""Testing update_last_played_information."""
... | stack_v2_sparse_classes_36k_train_006909 | 14,816 | permissive | [
{
"docstring": "Testing init method.",
"name": "test_initialization",
"signature": "def test_initialization(self)"
},
{
"docstring": "Testing update_last_played_information.",
"name": "test_update_last_played_information",
"signature": "def test_update_last_played_information(self)"
}
... | 2 | null | Implement the Python class `ExpUserLastPlaythroughTests` described below.
Class description:
Testing domain object for an exploration last playthrough model.
Method signatures and docstrings:
- def test_initialization(self): Testing init method.
- def test_update_last_played_information(self): Testing update_last_pla... | Implement the Python class `ExpUserLastPlaythroughTests` described below.
Class description:
Testing domain object for an exploration last playthrough model.
Method signatures and docstrings:
- def test_initialization(self): Testing init method.
- def test_update_last_played_information(self): Testing update_last_pla... | 899b9755a6b795a8991e596055ac24065a8435e0 | <|skeleton|>
class ExpUserLastPlaythroughTests:
"""Testing domain object for an exploration last playthrough model."""
def test_initialization(self):
"""Testing init method."""
<|body_0|>
def test_update_last_played_information(self):
"""Testing update_last_played_information."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpUserLastPlaythroughTests:
"""Testing domain object for an exploration last playthrough model."""
def test_initialization(self):
"""Testing init method."""
exp_last_playthrough = user_domain.ExpUserLastPlaythrough('user_id0', 'exp_id0', 0, 'last_updated', 'state0')
self.assertEq... | the_stack_v2_python_sparse | core/domain/user_domain_test.py | import-keshav/oppia | train | 4 |
28b89ed7181549671d04e7db1210fffaf1250ab2 | [
"line = data[0]\ntext = line.get('data') or line.get('body')\nif isinstance(text, (bytes, bytearray)):\n text = text.decode('utf-8')\ntext = self._remove_html_tags(text)\ntext = text.lower()\ntext = self._expand_contractions(text)\ntext = self._remove_accented_characters(text)\ntext = self._remove_punctuation(te... | <|body_start_0|>
line = data[0]
text = line.get('data') or line.get('body')
if isinstance(text, (bytes, bytearray)):
text = text.decode('utf-8')
text = self._remove_html_tags(text)
text = text.lower()
text = self._expand_contractions(text)
text = self.... | TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary. | TextClassifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextClassifier:
"""TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary."""
def preprocess(self, data):
"""Normalizes the input text for PyTorch model using following basic cleanup operations :... | stack_v2_sparse_classes_36k_train_006910 | 5,272 | permissive | [
{
"docstring": "Normalizes the input text for PyTorch model using following basic cleanup operations : - remove html tags - lowercase all text - expand contractions [like I'd -> I would, don't -> do not] - remove accented characters - remove punctuations Converts the normalized text to tensor using the source_v... | 4 | null | Implement the Python class `TextClassifier` described below.
Class description:
TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary.
Method signatures and docstrings:
- def preprocess(self, data): Normalizes the input text for... | Implement the Python class `TextClassifier` described below.
Class description:
TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary.
Method signatures and docstrings:
- def preprocess(self, data): Normalizes the input text for... | 242895c6b4596c4119ec09d6139e627c5dd696b6 | <|skeleton|>
class TextClassifier:
"""TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary."""
def preprocess(self, data):
"""Normalizes the input text for PyTorch model using following basic cleanup operations :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextClassifier:
"""TextClassifier handler class. This handler takes a text (string) and as input and returns the classification text based on the model vocabulary."""
def preprocess(self, data):
"""Normalizes the input text for PyTorch model using following basic cleanup operations : - remove htm... | the_stack_v2_python_sparse | ts/torch_handler/text_classifier.py | pytorch/serve | train | 3,689 |
ebb7360a92565566b9eeeb34a054aaf70a7e4b88 | [
"user = users.get_current_user()\nif not utils.IsValidSheriffUser():\n message = 'User \"%s\" not authorized.' % user\n self.response.out.write(json.dumps({'error': message}))\n return\nstep = self.request.get('step')\nif step == 'prefill-info':\n result = _PrefillInfo(self.request.get('test_path'))\nel... | <|body_start_0|>
user = users.get_current_user()
if not utils.IsValidSheriffUser():
message = 'User "%s" not authorized.' % user
self.response.out.write(json.dumps({'error': message}))
return
step = self.request.get('step')
if step == 'prefill-info':
... | URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" parameter: "prefill-info": Returns JSON with some info to fill into the form. "perform-bisec... | StartBisectHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StartBisectHandler:
"""URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" parameter: "prefill-info": Returns JSON with s... | stack_v2_sparse_classes_36k_train_006911 | 32,152 | permissive | [
{
"docstring": "Performs one of several bisect-related actions depending on parameters. The only required parameter is \"step\", which indicates what to do. This end-point should always output valid JSON with different contents depending on the value of \"step\".",
"name": "post",
"signature": "def post... | 3 | stack_v2_sparse_classes_30k_train_000437 | Implement the Python class `StartBisectHandler` described below.
Class description:
URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" paramet... | Implement the Python class `StartBisectHandler` described below.
Class description:
URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" paramet... | 9df8ce98c2a14fb60c2f581853011e32eb4bed0f | <|skeleton|>
class StartBisectHandler:
"""URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" parameter: "prefill-info": Returns JSON with s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StartBisectHandler:
"""URL endpoint for AJAX requests for bisect config handling. Requests are made to this end-point by bisect and trace forms. This handler does several different types of things depending on what is given as the value of the "step" parameter: "prefill-info": Returns JSON with some info to f... | the_stack_v2_python_sparse | third_party/catapult/dashboard/dashboard/start_try_job.py | hanpfei/chromium-net | train | 297 |
ba645af633f7f4a33f2f0a081764ef39cff4b024 | [
"island = 0\nfor row in range(len(grid)):\n for column in range(len(grid[row])):\n if grid[row][column] == '1':\n island += 1\n self.expand_island(grid, row, column)\nreturn island",
"if row < 0 or row >= len(grid) or column < 0 or (column >= len(grid[row])):\n return\nif grid[r... | <|body_start_0|>
island = 0
for row in range(len(grid)):
for column in range(len(grid[row])):
if grid[row][column] == '1':
island += 1
self.expand_island(grid, row, column)
return island
<|end_body_0|>
<|body_start_1|>
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_0|>
def expand_island(self, grid, row, column):
"""Helper function to perform DFS search on the grid"""
<|body_1|>
def area_of_island(self, grid, row, column):
... | stack_v2_sparse_classes_36k_train_006912 | 1,843 | permissive | [
{
"docstring": ":type grid: List[List[str]] :rtype: int",
"name": "numIslands",
"signature": "def numIslands(self, grid)"
},
{
"docstring": "Helper function to perform DFS search on the grid",
"name": "expand_island",
"signature": "def expand_island(self, grid, row, column)"
},
{
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int
- def expand_island(self, grid, row, column): Helper function to perform DFS search on the grid
- def area_of_... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numIslands(self, grid): :type grid: List[List[str]] :rtype: int
- def expand_island(self, grid, row, column): Helper function to perform DFS search on the grid
- def area_of_... | 547c200b627c774535bc22880b16d5390183aeba | <|skeleton|>
class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
<|body_0|>
def expand_island(self, grid, row, column):
"""Helper function to perform DFS search on the grid"""
<|body_1|>
def area_of_island(self, grid, row, column):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numIslands(self, grid):
""":type grid: List[List[str]] :rtype: int"""
island = 0
for row in range(len(grid)):
for column in range(len(grid[row])):
if grid[row][column] == '1':
island += 1
self.expand_isla... | the_stack_v2_python_sparse | medium/200_number_of_islands.py | Sukhrobjon/leetcode | train | 0 | |
bf52cdb366bf2827c2168f9a33a80c59443be497 | [
"super().__init__()\nself._use_condition = use_condition\nself._model = self._get_coupling_layers(num_layers=4, num_channels_hidden=[32, 32], compression_size=compression_size)",
"mask = tf.range(4096, dtype=tf.float32)\nmask = tf.reshape(mask, shape=[64, 64, 1]) % 2\nlayers = []\nfor _ in range(num_layers):\n ... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = self._get_coupling_layers(num_layers=4, num_channels_hidden=[32, 32], compression_size=compression_size)
<|end_body_0|>
<|body_start_1|>
mask = tf.range(4096, dtype=tf.float32)
mask = tf.reshap... | Embedding conditioned flow model. Attributes: _use_condition: | EmbeddingConditionedFlow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, n... | stack_v2_sparse_classes_36k_train_006913 | 12,897 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition: compression_size:",
"name": "__init__",
"signature": "def __init__(self, use_condition, compression_size)"
},
{
"docstring": "Returns a list of convolutional affine coupling layers. Args: num_layers: num_channels_hidden: compression_si... | 3 | stack_v2_sparse_classes_30k_train_007534 | Implement the Python class `EmbeddingConditionedFlow` described below.
Class description:
Embedding conditioned flow model. Attributes: _use_condition:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the object. Args: use_condition: compression_size:
- def _get_cou... | Implement the Python class `EmbeddingConditionedFlow` described below.
Class description:
Embedding conditioned flow model. Attributes: _use_condition:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the object. Args: use_condition: compression_size:
- def _get_cou... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
super().__init__()
self._use_condition = use_condition
se... | the_stack_v2_python_sparse | flow.py | gaotianxiang/text-to-image-synthesis | train | 0 |
942e20fa65f0a304ef68a184de15e6472a24b5c6 | [
"super().__init__(*args, **kwargs)\nself.mode = None\nself.axis = None",
"if isinstance(self.args, dict):\n self.mode = engine.evaluate(self.args.get('mode'), recursive=True)\n self.axis = engine.evaluate(self.args.get('axis'), recursive=True)\nelse:\n self.mode = self.args\n self.axis = Merge.DEFAULT... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.mode = None
self.axis = None
<|end_body_0|>
<|body_start_1|>
if isinstance(self.args, dict):
self.mode = engine.evaluate(self.args.get('mode'), recursive=True)
self.axis = engine.evaluate(self.args.get('axis... | A container for merging inputs from multiple input layers. | Merge | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Merge:
"""A container for merging inputs from multiple input layers."""
def __init__(self, *args, **kwargs):
"""Create a new merge container."""
<|body_0|>
def _parse(self, engine):
"""Parse the child containers"""
<|body_1|>
def _build(self, model):... | stack_v2_sparse_classes_36k_train_006914 | 4,408 | permissive | [
{
"docstring": "Create a new merge container.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Parse the child containers",
"name": "_parse",
"signature": "def _parse(self, engine)"
},
{
"docstring": "Instantiate the container.",
"na... | 4 | stack_v2_sparse_classes_30k_train_006968 | Implement the Python class `Merge` described below.
Class description:
A container for merging inputs from multiple input layers.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a new merge container.
- def _parse(self, engine): Parse the child containers
- def _build(self, model): Ins... | Implement the Python class `Merge` described below.
Class description:
A container for merging inputs from multiple input layers.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Create a new merge container.
- def _parse(self, engine): Parse the child containers
- def _build(self, model): Ins... | fd0c120e50815c1e5be64e5dde964dcd47234556 | <|skeleton|>
class Merge:
"""A container for merging inputs from multiple input layers."""
def __init__(self, *args, **kwargs):
"""Create a new merge container."""
<|body_0|>
def _parse(self, engine):
"""Parse the child containers"""
<|body_1|>
def _build(self, model):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Merge:
"""A container for merging inputs from multiple input layers."""
def __init__(self, *args, **kwargs):
"""Create a new merge container."""
super().__init__(*args, **kwargs)
self.mode = None
self.axis = None
def _parse(self, engine):
"""Parse the child co... | the_stack_v2_python_sparse | kur/containers/layers/merge.py | deepgram/kur | train | 873 |
828834957515fcb5d972577a44c7b92568fd54ec | [
"assert isinstance(reversible_blocks, nn.ModuleList)\nfor block in reversible_blocks:\n assert isinstance(block, ReversibleBlock)\n x = block(x)\nctx.y = x.detach()\nctx.reversible_blocks = reversible_blocks\nctx.eagerly_discard_variables = eagerly_discard_variables\nreturn x",
"y = ctx.y\nif ctx.eagerly_di... | <|body_start_0|>
assert isinstance(reversible_blocks, nn.ModuleList)
for block in reversible_blocks:
assert isinstance(block, ReversibleBlock)
x = block(x)
ctx.y = x.detach()
ctx.reversible_blocks = reversible_blocks
ctx.eagerly_discard_variables = eagerly... | Integrates the reversible sequence into the autograd framework | _ReversibleModuleFunction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ReversibleModuleFunction:
"""Integrates the reversible sequence into the autograd framework"""
def forward(ctx, x, reversible_blocks, eagerly_discard_variables):
"""Performs the forward pass of a reversible sequence within the autograd framework :param ctx: autograd context :param x... | stack_v2_sparse_classes_36k_train_006915 | 8,406 | no_license | [
{
"docstring": "Performs the forward pass of a reversible sequence within the autograd framework :param ctx: autograd context :param x: input tensor :param reversible_blocks: nn.Modulelist of reversible blocks :return: output tensor",
"name": "forward",
"signature": "def forward(ctx, x, reversible_block... | 2 | stack_v2_sparse_classes_30k_train_010074 | Implement the Python class `_ReversibleModuleFunction` described below.
Class description:
Integrates the reversible sequence into the autograd framework
Method signatures and docstrings:
- def forward(ctx, x, reversible_blocks, eagerly_discard_variables): Performs the forward pass of a reversible sequence within the... | Implement the Python class `_ReversibleModuleFunction` described below.
Class description:
Integrates the reversible sequence into the autograd framework
Method signatures and docstrings:
- def forward(ctx, x, reversible_blocks, eagerly_discard_variables): Performs the forward pass of a reversible sequence within the... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class _ReversibleModuleFunction:
"""Integrates the reversible sequence into the autograd framework"""
def forward(ctx, x, reversible_blocks, eagerly_discard_variables):
"""Performs the forward pass of a reversible sequence within the autograd framework :param ctx: autograd context :param x... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ReversibleModuleFunction:
"""Integrates the reversible sequence into the autograd framework"""
def forward(ctx, x, reversible_blocks, eagerly_discard_variables):
"""Performs the forward pass of a reversible sequence within the autograd framework :param ctx: autograd context :param x: input tenso... | the_stack_v2_python_sparse | generated/test_RobinBruegger_RevTorch.py | jansel/pytorch-jit-paritybench | train | 35 |
8f8cc14c49fcc3b32700f45d86938c1e30d241b0 | [
"collections = repo.filter_by(Collection, deleted=False)\niris = True if request.args.get('iris') == '1' else False\ncontainer = {'id': url_for('api.index', _external=True), 'label': 'All collections', 'type': ['AnnotationCollection', 'BasicContainer'], 'total': len(collections), 'items': self._decorate_page_items(... | <|body_start_0|>
collections = repo.filter_by(Collection, deleted=False)
iris = True if request.args.get('iris') == '1' else False
container = {'id': url_for('api.index', _external=True), 'label': 'All collections', 'type': ['AnnotationCollection', 'BasicContainer'], 'total': len(collections), '... | Index API class. | IndexAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IndexAPI:
"""Index API class."""
def get(self):
"""Return a list of all AnnotationCollections."""
<|body_0|>
def post(self):
"""Create an AnnotationCollection."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
collections = repo.filter_by(Collecti... | stack_v2_sparse_classes_36k_train_006916 | 1,290 | permissive | [
{
"docstring": "Return a list of all AnnotationCollections.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create an AnnotationCollection.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017819 | Implement the Python class `IndexAPI` described below.
Class description:
Index API class.
Method signatures and docstrings:
- def get(self): Return a list of all AnnotationCollections.
- def post(self): Create an AnnotationCollection. | Implement the Python class `IndexAPI` described below.
Class description:
Index API class.
Method signatures and docstrings:
- def get(self): Return a list of all AnnotationCollections.
- def post(self): Create an AnnotationCollection.
<|skeleton|>
class IndexAPI:
"""Index API class."""
def get(self):
... | bc504498ef330fab46f2334f96631457d520ec90 | <|skeleton|>
class IndexAPI:
"""Index API class."""
def get(self):
"""Return a list of all AnnotationCollections."""
<|body_0|>
def post(self):
"""Create an AnnotationCollection."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IndexAPI:
"""Index API class."""
def get(self):
"""Return a list of all AnnotationCollections."""
collections = repo.filter_by(Collection, deleted=False)
iris = True if request.args.get('iris') == '1' else False
container = {'id': url_for('api.index', _external=True), 'lab... | the_stack_v2_python_sparse | explicates/api/index.py | alexandermendes/explicates | train | 8 |
a9927bece47be6cfe05ea1b14ab8e40cccc7bb16 | [
"self.splitLine = '/*----------*/'\nself.path = logFilePath\nself.fun = otherFun if otherFun else lambda: ''\nself.printt = printOnCmd\nself.localTime = localTime\nself.format = ' Index :{index}, {time}\\n{timeClass} :{timeStr}\\n Exception :{exceptionName}\\n Message :{message}\\n Args :{args}\\n{otherI... | <|body_start_0|>
self.splitLine = '/*----------*/'
self.path = logFilePath
self.fun = otherFun if otherFun else lambda: ''
self.printt = printOnCmd
self.localTime = localTime
self.format = ' Index :{index}, {time}\n{timeClass} :{timeStr}\n Exception :{exceptionName}\n... | 用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数 | LogException | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogException:
"""用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数"""
def __init__(self, logFilePath=None, otherFun=None, printOnCmd=True, logBegin=False, localTime=False, isOn=True):
"""logF... | stack_v2_sparse_classes_36k_train_006917 | 37,864 | no_license | [
{
"docstring": "logFilePath log文件保存路径,为False时 不写入文件 otherFun 一个返回字符串的函数，每次错误运行一次，结果写入log printOnCmd 时候在屏幕上打印 logBegin 是否记录开始监听事件 localTime 是否为当地时间 默认为GMT时间",
"name": "__init__",
"signature": "def __init__(self, logFilePath=None, otherFun=None, printOnCmd=True, logBegin=False, localTime=False, isOn=True)... | 4 | stack_v2_sparse_classes_30k_val_001105 | Implement the Python class `LogException` described below.
Class description:
用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数
Method signatures and docstrings:
- def __init__(self, logFilePath=None, otherFun=None, printOnCm... | Implement the Python class `LogException` described below.
Class description:
用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数
Method signatures and docstrings:
- def __init__(self, logFilePath=None, otherFun=None, printOnCm... | 69b117ee983d8a9ee3ad176af8b096acc902f3ae | <|skeleton|>
class LogException:
"""用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数"""
def __init__(self, logFilePath=None, otherFun=None, printOnCmd=True, logBegin=False, localTime=False, isOn=True):
"""logF... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogException:
"""用于扑捉和记录函数中的异常错误 usage: loge = LogException(logFilePath,otherFun) # 先实例一个对象 loge.listen(f,*l,**args) # 用 .listen 运行函数 @loge.decorator # 装饰被监听函数"""
def __init__(self, logFilePath=None, otherFun=None, printOnCmd=True, logBegin=False, localTime=False, isOn=True):
"""logFilePath log文件... | the_stack_v2_python_sparse | boxx/tool/toolLog.py | DIYer22/boxx | train | 452 |
cc07f7b69a55cb3e3ccce5a3e9b1eb31b9cebe75 | [
"result = PersonService.get_by_id(id)\nif not result:\n return ({'message': 'The person does not exist'}, 404)\nelse:\n return result[0]",
"data = request.json\nif data['entityID'] != id:\n return ({'message': 'entityID property in the incoming json object and id parameter in the URL path arenot matched'... | <|body_start_0|>
result = PersonService.get_by_id(id)
if not result:
return ({'message': 'The person does not exist'}, 404)
else:
return result[0]
<|end_body_0|>
<|body_start_1|>
data = request.json
if data['entityID'] != id:
return ({'message... | PersonEntity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonEntity:
def get(self, id):
"""Get a specific Person"""
<|body_0|>
def put(self, id):
"""Update a person Use this method to change properties of a person. * Send a JSON object with new properties in the request body. ``` { "name": "New Person Name", "des": "New ... | stack_v2_sparse_classes_36k_train_006918 | 4,600 | no_license | [
{
"docstring": "Get a specific Person",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update a person Use this method to change properties of a person. * Send a JSON object with new properties in the request body. ``` { \"name\": \"New Person Name\", \"des\": \"New Person De... | 3 | stack_v2_sparse_classes_30k_train_017023 | Implement the Python class `PersonEntity` described below.
Class description:
Implement the PersonEntity class.
Method signatures and docstrings:
- def get(self, id): Get a specific Person
- def put(self, id): Update a person Use this method to change properties of a person. * Send a JSON object with new properties i... | Implement the Python class `PersonEntity` described below.
Class description:
Implement the PersonEntity class.
Method signatures and docstrings:
- def get(self, id): Get a specific Person
- def put(self, id): Update a person Use this method to change properties of a person. * Send a JSON object with new properties i... | 05bc527a3738d45263dc8aad23af271b3ea0219c | <|skeleton|>
class PersonEntity:
def get(self, id):
"""Get a specific Person"""
<|body_0|>
def put(self, id):
"""Update a person Use this method to change properties of a person. * Send a JSON object with new properties in the request body. ``` { "name": "New Person Name", "des": "New ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersonEntity:
def get(self, id):
"""Get a specific Person"""
result = PersonService.get_by_id(id)
if not result:
return ({'message': 'The person does not exist'}, 404)
else:
return result[0]
def put(self, id):
"""Update a person Use this met... | the_stack_v2_python_sparse | application/persons/controller.py | dinhphien/api_server | train | 0 | |
673096ab1a035bcc11797b7743218261900df161 | [
"super().__init__()\nself.length = embed_size\nself.model = nn.Sequential()\nlayers_size = [in_channels] + layers_size\niterations = enumerate(zip(layers_size[:-1], layers_size[1:], kernels_size, strides, paddings))\nfor i, (in_c, out_c, k, s, p) in iterations:\n conv2d_i = nn.Conv2d(in_c, out_c, kernel_size=k, ... | <|body_start_0|>
super().__init__()
self.length = embed_size
self.model = nn.Sequential()
layers_size = [in_channels] + layers_size
iterations = enumerate(zip(layers_size[:-1], layers_size[1:], kernels_size, strides, paddings))
for i, (in_c, out_c, k, s, p) in iterations:... | Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer. | ImageInput | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageInput:
"""Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer."""
def __init__(self, embed_size: int, in_channels: int, layers_size: List[int], kernels_size: List[int], strides: List[int], paddings: List[int], pooling: Opt... | stack_v2_sparse_classes_36k_train_006919 | 3,726 | permissive | [
{
"docstring": "Initialize ImageInput. Args: embed_size (int): Size of embedding tensor in_channels (int): Number of channel of inputs layers_size (List[int]): Layers size of CNN kernels_size (List[int]): Kernels size of CNN strides (List[int]): Strides of CNN paddings (List[int]): Paddings of CNN pooling (str,... | 2 | stack_v2_sparse_classes_30k_train_020751 | Implement the Python class `ImageInput` described below.
Class description:
Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer.
Method signatures and docstrings:
- def __init__(self, embed_size: int, in_channels: int, layers_size: List[int], kernels_si... | Implement the Python class `ImageInput` described below.
Class description:
Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer.
Method signatures and docstrings:
- def __init__(self, embed_size: int, in_channels: int, layers_size: List[int], kernels_si... | 751a43b9cd35e951d81c0d9cf46507b1777bb7ff | <|skeleton|>
class ImageInput:
"""Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer."""
def __init__(self, embed_size: int, in_channels: int, layers_size: List[int], kernels_size: List[int], strides: List[int], paddings: List[int], pooling: Opt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageInput:
"""Base Input class for image, which embed image by a stack of convolution neural network (CNN) and fully-connect layer."""
def __init__(self, embed_size: int, in_channels: int, layers_size: List[int], kernels_size: List[int], strides: List[int], paddings: List[int], pooling: Optional[str]='a... | the_stack_v2_python_sparse | torecsys/inputs/base/image_inp.py | p768lwy3/torecsys | train | 98 |
13f9aad7b11cf7da4096f97cbe45c1b44fdff99b | [
"self.followed_graph = {}\nself.news_feed = {}\nself.clock = 0",
"self.clock += 1\nif userId not in self.news_feed:\n self.news_feed[userId] = []\nself.news_feed[userId].append((self.clock, tweetId))",
"self_tweet = self.news_feed.get(userId, [])[-11:]\nfollowee_tweet = []\nfor followee_id in self.followed_g... | <|body_start_0|>
self.followed_graph = {}
self.news_feed = {}
self.clock = 0
<|end_body_0|>
<|body_start_1|>
self.clock += 1
if userId not in self.news_feed:
self.news_feed[userId] = []
self.news_feed[userId].append((self.clock, tweetId))
<|end_body_1|>
<|bo... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k_train_006920 | 2,118 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet. :type userId: int :type tweetId: int :rtype: void",
"name": "postTweet",
"signature": "def postTweet(self, userId, tweetId)"
},
{
"... | 5 | null | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId, tweetId): Compose a new tweet. :type userId: int :type tweetId: int :rtype: void
- def getNew... | 9f6ccf8a8fd8eaaeae2f11557b73be4e5e7adba8 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
<|body_1|>
def getNewsFeed(self, userId):
"""Ret... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.followed_graph = {}
self.news_feed = {}
self.clock = 0
def postTweet(self, userId, tweetId):
"""Compose a new tweet. :type userId: int :type tweetId: int :rtype: void"""
self.clock... | the_stack_v2_python_sparse | python/355.py | MrRabbit0o0/LeetCode | train | 0 | |
37c5f658592de38a14caf7e3bce84f55951dcc6b | [
"user = request.user\nnotifications = user.notifications.unread()\nserializer = self.serializer_class(notifications, many=True)\nreturn Response(serializer.data, status.HTTP_200_OK)",
"user = request.user\nNotification.objects.mark_all_as_unread(user)\nreturn Response({'response': 'All unread'}, status.HTTP_200_O... | <|body_start_0|>
user = request.user
notifications = user.notifications.unread()
serializer = self.serializer_class(notifications, many=True)
return Response(serializer.data, status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1|>
user = request.user
Notification.objects.mar... | Unread notifications Retrieve unread notifications | NotificationListViews | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationListViews:
"""Unread notifications Retrieve unread notifications"""
def get(self, request):
"""retrieves"""
<|body_0|>
def put(self, request, format=None):
"""Mark as unread"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
user = requ... | stack_v2_sparse_classes_36k_train_006921 | 2,497 | permissive | [
{
"docstring": "retrieves",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Mark as unread",
"name": "put",
"signature": "def put(self, request, format=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007711 | Implement the Python class `NotificationListViews` described below.
Class description:
Unread notifications Retrieve unread notifications
Method signatures and docstrings:
- def get(self, request): retrieves
- def put(self, request, format=None): Mark as unread | Implement the Python class `NotificationListViews` described below.
Class description:
Unread notifications Retrieve unread notifications
Method signatures and docstrings:
- def get(self, request): retrieves
- def put(self, request, format=None): Mark as unread
<|skeleton|>
class NotificationListViews:
"""Unread... | b80ad485339dbb02b74d9b2093543bf8173d51de | <|skeleton|>
class NotificationListViews:
"""Unread notifications Retrieve unread notifications"""
def get(self, request):
"""retrieves"""
<|body_0|>
def put(self, request, format=None):
"""Mark as unread"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationListViews:
"""Unread notifications Retrieve unread notifications"""
def get(self, request):
"""retrieves"""
user = request.user
notifications = user.notifications.unread()
serializer = self.serializer_class(notifications, many=True)
return Response(seri... | the_stack_v2_python_sparse | authors/apps/notifications/views.py | deferral/ah-django | train | 1 |
a028872377265846d63fac2fd6d365c5191f4326 | [
"if not root or not root.left:\n return root\nleft, right = (root.left, root.right)\nnew_root = self.upsideDownBinaryTree(left)\nleft.left, left.right = (right, root)\nroot.left, root.right = (None, None)\nreturn new_root",
"p, parent, parent_right = (root, None, None)\nwhile p:\n left = p.left\n p.left ... | <|body_start_0|>
if not root or not root.left:
return root
left, right = (root.left, root.right)
new_root = self.upsideDownBinaryTree(left)
left.left, left.right = (right, root)
root.left, root.right = (None, None)
return new_root
<|end_body_0|>
<|body_start_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def upsideDownBinaryTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def upsideDownBinaryTree_iterative(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not ro... | stack_v2_sparse_classes_36k_train_006922 | 2,305 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "upsideDownBinaryTree",
"signature": "def upsideDownBinaryTree(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "upsideDownBinaryTree_iterative",
"signature": "def upsideDownBinaryTree_iterativ... | 2 | stack_v2_sparse_classes_30k_train_011461 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def upsideDownBinaryTree(self, root): :type root: TreeNode :rtype: TreeNode
- def upsideDownBinaryTree_iterative(self, root): :type root: TreeNode :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def upsideDownBinaryTree(self, root): :type root: TreeNode :rtype: TreeNode
- def upsideDownBinaryTree_iterative(self, root): :type root: TreeNode :rtype: TreeNode
<|skeleton|>
... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def upsideDownBinaryTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def upsideDownBinaryTree_iterative(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def upsideDownBinaryTree(self, root):
""":type root: TreeNode :rtype: TreeNode"""
if not root or not root.left:
return root
left, right = (root.left, root.right)
new_root = self.upsideDownBinaryTree(left)
left.left, left.right = (right, root)
... | the_stack_v2_python_sparse | src/lt_156.py | oxhead/CodingYourWay | train | 0 | |
31fd7437f52594e6d0b30a81e980c4c7fd6bf603 | [
"track_event = TrackEvent.create(**attr)\nif track_event is None:\n raise BusinessError('创建失败')\nreturn True",
"track_event_qs = TrackEvent.query(**search_info)\ntrack_event_qs.order_by('-create_time')\nreturn Splitor(current_page, track_event_qs)",
"track_event_qs = TrackEvent.search(create_time__range=(sal... | <|body_start_0|>
track_event = TrackEvent.create(**attr)
if track_event is None:
raise BusinessError('创建失败')
return True
<|end_body_0|>
<|body_start_1|>
track_event_qs = TrackEvent.query(**search_info)
track_event_qs.order_by('-create_time')
return Splitor(cu... | TrackEventServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrackEventServer:
def generate(cls, **attr):
"""创建跟踪"""
<|body_0|>
def search(cls, current_page, **search_info):
"""查询跟踪列表"""
<|body_1|>
def search_by_sale_chance(cls, sale_chance):
"""根据机会查询跟踪列表"""
<|body_2|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_006923 | 1,190 | no_license | [
{
"docstring": "创建跟踪",
"name": "generate",
"signature": "def generate(cls, **attr)"
},
{
"docstring": "查询跟踪列表",
"name": "search",
"signature": "def search(cls, current_page, **search_info)"
},
{
"docstring": "根据机会查询跟踪列表",
"name": "search_by_sale_chance",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_018221 | Implement the Python class `TrackEventServer` described below.
Class description:
Implement the TrackEventServer class.
Method signatures and docstrings:
- def generate(cls, **attr): 创建跟踪
- def search(cls, current_page, **search_info): 查询跟踪列表
- def search_by_sale_chance(cls, sale_chance): 根据机会查询跟踪列表 | Implement the Python class `TrackEventServer` described below.
Class description:
Implement the TrackEventServer class.
Method signatures and docstrings:
- def generate(cls, **attr): 创建跟踪
- def search(cls, current_page, **search_info): 查询跟踪列表
- def search_by_sale_chance(cls, sale_chance): 根据机会查询跟踪列表
<|skeleton|>
cla... | f572830aa996cfe619fc4dd8279972a2f567c94c | <|skeleton|>
class TrackEventServer:
def generate(cls, **attr):
"""创建跟踪"""
<|body_0|>
def search(cls, current_page, **search_info):
"""查询跟踪列表"""
<|body_1|>
def search_by_sale_chance(cls, sale_chance):
"""根据机会查询跟踪列表"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrackEventServer:
def generate(cls, **attr):
"""创建跟踪"""
track_event = TrackEvent.create(**attr)
if track_event is None:
raise BusinessError('创建失败')
return True
def search(cls, current_page, **search_info):
"""查询跟踪列表"""
track_event_qs = TrackEven... | the_stack_v2_python_sparse | codes/personal_backend/tuoen/abs/service/track/manager.py | MaseraTiGo/4U | train | 0 | |
3aab4cf7eddd55682f2aba650ec0ee52948e5408 | [
"total_dict = {}\nfor b in B:\n for c in b:\n total_dict.setdefault(c, 0)\n total_dict[c] = max(b.count(c), total_dict[c])\n\ndef a_compare_total(a, d):\n for char, count in d.items():\n if a.count(char) < count:\n return False\n return True\nreturn [a for a in A if a_compar... | <|body_start_0|>
total_dict = {}
for b in B:
for c in b:
total_dict.setdefault(c, 0)
total_dict[c] = max(b.count(c), total_dict[c])
def a_compare_total(a, d):
for char, count in d.items():
if a.count(char) < count:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def wordSubsets(self, A, B):
""":type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的時候會比較快 另外也利用了 count function 加速"""
<|body_0|>
def wordSubsetsV1(self, A, B):
... | stack_v2_sparse_classes_36k_train_006924 | 1,753 | no_license | [
{
"docstring": ":type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的時候會比較快 另外也利用了 count function 加速",
"name": "wordSubsets",
"signature": "def wordSubsets(self, A, B)"
},
{
"docstring": ":type A: Lis... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordSubsets(self, A, B): :type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def wordSubsets(self, A, B): :type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def wordSubsets(self, A, B):
""":type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的時候會比較快 另外也利用了 count function 加速"""
<|body_0|>
def wordSubsetsV1(self, A, B):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def wordSubsets(self, A, B):
""":type A: List[str] :type B: List[str] :rtype: List[str] 這邊的解法將 V1 精簡化, 但核心想法還是一樣的 total_dict 就是 B 的要求，但不同於長度為 26 的 list 這邊只記錄了字母數 > 0 的字母，所以後面再檢驗 a 的時候會比較快 另外也利用了 count function 加速"""
total_dict = {}
for b in B:
for c in b:
... | the_stack_v2_python_sparse | cs_notes/string/word_subsets.py | hwc1824/LeetCodeSolution | train | 0 | |
8b7fe54bad51aeb1997abb809802c39a17d75b87 | [
"text = 'Interatomic data.\\n\\n'\ntext += '%-25s%-25s%-25s' % ('Index', 'Spin ID 1', 'Spin ID 2') + '\\n'\nfor i in range(len(self)):\n text += '%-25i%-25s%-25s\\n\\n' % (i, self[i].spin_id1, self[i].spin_id2)\nreturn text",
"cont = InteratomContainer(spin_id1, spin_id2)\nself.append(cont)\nreturn cont",
"i... | <|body_start_0|>
text = 'Interatomic data.\n\n'
text += '%-25s%-25s%-25s' % ('Index', 'Spin ID 1', 'Spin ID 2') + '\n'
for i in range(len(self)):
text += '%-25i%-25s%-25s\n\n' % (i, self[i].spin_id1, self[i].spin_id2)
return text
<|end_body_0|>
<|body_start_1|>
cont ... | List type data container for interatomic specific data. | InteratomList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InteratomList:
"""List type data container for interatomic specific data."""
def __repr__(self):
"""The string representation of the object. Rather than using the standard Python conventions (either the string representation of the value or the "<...desc...>" notation), a rich-format... | stack_v2_sparse_classes_36k_train_006925 | 9,873 | no_license | [
{
"docstring": "The string representation of the object. Rather than using the standard Python conventions (either the string representation of the value or the \"<...desc...>\" notation), a rich-formatted description of the object is given.",
"name": "__repr__",
"signature": "def __repr__(self)"
},
... | 5 | null | Implement the Python class `InteratomList` described below.
Class description:
List type data container for interatomic specific data.
Method signatures and docstrings:
- def __repr__(self): The string representation of the object. Rather than using the standard Python conventions (either the string representation of... | Implement the Python class `InteratomList` described below.
Class description:
List type data container for interatomic specific data.
Method signatures and docstrings:
- def __repr__(self): The string representation of the object. Rather than using the standard Python conventions (either the string representation of... | c317326ddeacd1a1c608128769676899daeae531 | <|skeleton|>
class InteratomList:
"""List type data container for interatomic specific data."""
def __repr__(self):
"""The string representation of the object. Rather than using the standard Python conventions (either the string representation of the value or the "<...desc...>" notation), a rich-format... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InteratomList:
"""List type data container for interatomic specific data."""
def __repr__(self):
"""The string representation of the object. Rather than using the standard Python conventions (either the string representation of the value or the "<...desc...>" notation), a rich-formatted descripti... | the_stack_v2_python_sparse | data_store/interatomic.py | jlec/relax | train | 4 |
8b9d2ddf9b8fd4f964a1efb0e006efcefa4de2f6 | [
"self.radius = size\nself.n = corners\nself.point = None",
"if self.point is not None:\n x, y = self.point.getXY()\n return pyx.box.polygon([(x - self.radius * math.sin(i * 2 * math.pi / self.n), y + self.radius * math.cos(i * 2 * math.pi / self.n)) for i in range(self.n)]).path()\nreturn None"
] | <|body_start_0|>
self.radius = size
self.n = corners
self.point = None
<|end_body_0|>
<|body_start_1|>
if self.point is not None:
x, y = self.point.getXY()
return pyx.box.polygon([(x - self.radius * math.sin(i * 2 * math.pi / self.n), y + self.radius * math.cos(i... | PolygonalMark | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PolygonalMark:
def __init__(self, size=0.075, corners=3):
"""A polygonal mark."""
<|body_0|>
def getPath(self):
"""Return the path for this marker."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.radius = size
self.n = corners
s... | stack_v2_sparse_classes_36k_train_006926 | 12,026 | no_license | [
{
"docstring": "A polygonal mark.",
"name": "__init__",
"signature": "def __init__(self, size=0.075, corners=3)"
},
{
"docstring": "Return the path for this marker.",
"name": "getPath",
"signature": "def getPath(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008197 | Implement the Python class `PolygonalMark` described below.
Class description:
Implement the PolygonalMark class.
Method signatures and docstrings:
- def __init__(self, size=0.075, corners=3): A polygonal mark.
- def getPath(self): Return the path for this marker. | Implement the Python class `PolygonalMark` described below.
Class description:
Implement the PolygonalMark class.
Method signatures and docstrings:
- def __init__(self, size=0.075, corners=3): A polygonal mark.
- def getPath(self): Return the path for this marker.
<|skeleton|>
class PolygonalMark:
def __init__(... | 62f64e33d900280b26a6de5bbd9ee86c38c69cd0 | <|skeleton|>
class PolygonalMark:
def __init__(self, size=0.075, corners=3):
"""A polygonal mark."""
<|body_0|>
def getPath(self):
"""Return the path for this marker."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PolygonalMark:
def __init__(self, size=0.075, corners=3):
"""A polygonal mark."""
self.radius = size
self.n = corners
self.point = None
def getPath(self):
"""Return the path for this marker."""
if self.point is not None:
x, y = self.point.getXY(... | the_stack_v2_python_sparse | pyfeyn/points.py | kpedro88/pyfeyn | train | 0 | |
2fda368ca43c860a7eb63f90972ade3e30a66517 | [
"ana_id = super(hr_department, self).create(vals)\nif self.manager_id.id != False and self.analytic_account_id.id != False:\n self.analytic_account_id.write({'user_id': self.manager_id.user_id.id})\nreturn ana_id",
"ana_id = super(hr_department, self).write(vals)\nif self.manager_id.id != False and self.analyt... | <|body_start_0|>
ana_id = super(hr_department, self).create(vals)
if self.manager_id.id != False and self.analytic_account_id.id != False:
self.analytic_account_id.write({'user_id': self.manager_id.user_id.id})
return ana_id
<|end_body_0|>
<|body_start_1|>
ana_id = super(hr_... | inherit hr.department model | hr_department | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
<|body_0|>
def write(self, vals):
"""override write function to set resposebl... | stack_v2_sparse_classes_36k_train_006927 | 926 | no_license | [
{
"docstring": "override create function to set resposeble of department's analytic account equals to department's manager",
"name": "create",
"signature": "def create(self, vals)"
},
{
"docstring": "override write function to set resposeble of department's analytic account equals to department'... | 2 | null | Implement the Python class `hr_department` described below.
Class description:
inherit hr.department model
Method signatures and docstrings:
- def create(self, vals): override create function to set resposeble of department's analytic account equals to department's manager
- def write(self, vals): override write func... | Implement the Python class `hr_department` described below.
Class description:
inherit hr.department model
Method signatures and docstrings:
- def create(self, vals): override create function to set resposeble of department's analytic account equals to department's manager
- def write(self, vals): override write func... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
<|body_0|>
def write(self, vals):
"""override write function to set resposebl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class hr_department:
"""inherit hr.department model"""
def create(self, vals):
"""override create function to set resposeble of department's analytic account equals to department's manager"""
ana_id = super(hr_department, self).create(vals)
if self.manager_id.id != False and self.analyt... | the_stack_v2_python_sparse | v_11/EBS-SVN/trunk/account_budget_ebs/models/departmentAccount_custom.py | musabahmed/baba | train | 0 |
bf244c8d59f7592201f06cb1c6b38b4b540dd931 | [
"if not request.user.has_perm('Users.users_list'):\n return HttpResponseForbidden()\nnames = [n.lower() for n in user_backend.list()]\nreturn HttpRestAuthResponse(request, names)",
"if not request.user.has_perm('Users.user_create'):\n return HttpResponseForbidden()\nname, password, properties = self._parse_... | <|body_start_0|>
if not request.user.has_perm('Users.users_list'):
return HttpResponseForbidden()
names = [n.lower() for n in user_backend.list()]
return HttpRestAuthResponse(request, names)
<|end_body_0|>
<|body_start_1|>
if not request.user.has_perm('Users.user_create'):
... | Handle requests to ``/users/``. | UsersView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UsersView:
"""Handle requests to ``/users/``."""
def get(self, request, largs, *args, **kwargs):
"""Get all users."""
<|body_0|>
def post(self, request, largs, dry=False):
"""Create a new user."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if ... | stack_v2_sparse_classes_36k_train_006928 | 9,743 | no_license | [
{
"docstring": "Get all users.",
"name": "get",
"signature": "def get(self, request, largs, *args, **kwargs)"
},
{
"docstring": "Create a new user.",
"name": "post",
"signature": "def post(self, request, largs, dry=False)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000695 | Implement the Python class `UsersView` described below.
Class description:
Handle requests to ``/users/``.
Method signatures and docstrings:
- def get(self, request, largs, *args, **kwargs): Get all users.
- def post(self, request, largs, dry=False): Create a new user. | Implement the Python class `UsersView` described below.
Class description:
Handle requests to ``/users/``.
Method signatures and docstrings:
- def get(self, request, largs, *args, **kwargs): Get all users.
- def post(self, request, largs, dry=False): Create a new user.
<|skeleton|>
class UsersView:
"""Handle req... | 60769f6b4965836b2220878cfa2e1bc403d8f8a3 | <|skeleton|>
class UsersView:
"""Handle requests to ``/users/``."""
def get(self, request, largs, *args, **kwargs):
"""Get all users."""
<|body_0|>
def post(self, request, largs, dry=False):
"""Create a new user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UsersView:
"""Handle requests to ``/users/``."""
def get(self, request, largs, *args, **kwargs):
"""Get all users."""
if not request.user.has_perm('Users.users_list'):
return HttpResponseForbidden()
names = [n.lower() for n in user_backend.list()]
return HttpRe... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/RestAuth/Users/views.py | sachinlokesh05/login-registration-forgotpassword-and-resetpassword-using-django-rest-framework- | train | 3 |
3163f2e8699e3fff3f90ce2297d0af3cde3b627e | [
"super(AggregateCell, self).__init__()\nself.pre_transform = pre_transform\nself.concat = concat\nself.agg_size = agg_size\nself.concat = concat\nself.data_format = data_format",
"if self.pre_transform:\n x1 = Conv(self.agg_size, 1, 1, data_format=self.data_format)(x1, training)\n x2 = Conv(self.agg_size, 1... | <|body_start_0|>
super(AggregateCell, self).__init__()
self.pre_transform = pre_transform
self.concat = concat
self.agg_size = agg_size
self.concat = concat
self.data_format = data_format
<|end_body_0|>
<|body_start_1|>
if self.pre_transform:
x1 = Con... | Aggregate two cells and sum or concat them up. | AggregateCell | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AggregateCell:
"""Aggregate two cells and sum or concat them up."""
def __init__(self, agg_size, pre_transform=True, concat=False, data_format='channels_first'):
"""Construct AggregateCell. :param size_1: channel of first input :param size_2: channel of second input :param agg_size: ... | stack_v2_sparse_classes_36k_train_006929 | 12,491 | permissive | [
{
"docstring": "Construct AggregateCell. :param size_1: channel of first input :param size_2: channel of second input :param agg_size: channel of aggregated tensor :param pre_transform: whether to do a transform on two inputs :param concat: concat the result if set to True, otherwise add the result",
"name"... | 2 | stack_v2_sparse_classes_30k_train_017473 | Implement the Python class `AggregateCell` described below.
Class description:
Aggregate two cells and sum or concat them up.
Method signatures and docstrings:
- def __init__(self, agg_size, pre_transform=True, concat=False, data_format='channels_first'): Construct AggregateCell. :param size_1: channel of first input... | Implement the Python class `AggregateCell` described below.
Class description:
Aggregate two cells and sum or concat them up.
Method signatures and docstrings:
- def __init__(self, agg_size, pre_transform=True, concat=False, data_format='channels_first'): Construct AggregateCell. :param size_1: channel of first input... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class AggregateCell:
"""Aggregate two cells and sum or concat them up."""
def __init__(self, agg_size, pre_transform=True, concat=False, data_format='channels_first'):
"""Construct AggregateCell. :param size_1: channel of first input :param size_2: channel of second input :param agg_size: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AggregateCell:
"""Aggregate two cells and sum or concat them up."""
def __init__(self, agg_size, pre_transform=True, concat=False, data_format='channels_first'):
"""Construct AggregateCell. :param size_1: channel of first input :param size_2: channel of second input :param agg_size: channel of ag... | the_stack_v2_python_sparse | built-in/TensorFlow/Official/cv/image_classification/ResnetVariant_for_TensorFlow/automl/vega/search_space/networks/tensorflow/customs/adelaide_nn/micro_decoders.py | Huawei-Ascend/modelzoo | train | 1 |
6cb51966783b07534f0e7b8c31e9ac8c7b4118f7 | [
"args = [*self.pos_only, *self.required, *self.optional]\nif self.varargs:\n args.append(self.varargs)\nargs.extend(self.kw_required.values())\nargs.extend(self.kw_optional.values())\nif self.varkwargs:\n args.append(self.varkwargs)\nreturn Signature(args, return_annotation=return_annotation)",
"out = Decom... | <|body_start_0|>
args = [*self.pos_only, *self.required, *self.optional]
if self.varargs:
args.append(self.varargs)
args.extend(self.kw_required.values())
args.extend(self.kw_optional.values())
if self.varkwargs:
args.append(self.varkwargs)
return ... | DecomposedParams | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecomposedParams:
def signature(self, return_annotation=None) -> Signature:
"""Create a signature object from decomposition."""
<|body_0|>
def replace(self, **kwargs) -> 'DecomposedParams':
"""Replace attribute from decomposed params."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_006930 | 5,048 | permissive | [
{
"docstring": "Create a signature object from decomposition.",
"name": "signature",
"signature": "def signature(self, return_annotation=None) -> Signature"
},
{
"docstring": "Replace attribute from decomposed params.",
"name": "replace",
"signature": "def replace(self, **kwargs) -> 'Dec... | 2 | null | Implement the Python class `DecomposedParams` described below.
Class description:
Implement the DecomposedParams class.
Method signatures and docstrings:
- def signature(self, return_annotation=None) -> Signature: Create a signature object from decomposition.
- def replace(self, **kwargs) -> 'DecomposedParams': Repla... | Implement the Python class `DecomposedParams` described below.
Class description:
Implement the DecomposedParams class.
Method signatures and docstrings:
- def signature(self, return_annotation=None) -> Signature: Create a signature object from decomposition.
- def replace(self, **kwargs) -> 'DecomposedParams': Repla... | 993ae7b8496347ad9720d3ff11e10ab946c3a800 | <|skeleton|>
class DecomposedParams:
def signature(self, return_annotation=None) -> Signature:
"""Create a signature object from decomposition."""
<|body_0|>
def replace(self, **kwargs) -> 'DecomposedParams':
"""Replace attribute from decomposed params."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecomposedParams:
def signature(self, return_annotation=None) -> Signature:
"""Create a signature object from decomposition."""
args = [*self.pos_only, *self.required, *self.optional]
if self.varargs:
args.append(self.varargs)
args.extend(self.kw_required.values())
... | the_stack_v2_python_sparse | sidekick-beta/sidekick/beta/app/function_wrapper.py | fabiommendes/sidekick | train | 32 | |
8d13e9e9517feb63f9e3f69015eab608b2de472c | [
"try:\n if self.id is None:\n return self.query.all()\n if self.id is not None and type(self.id) is int and (self.id >= 0):\n return self.query.get(self.id)\nexcept Exception as e:\n return e.__cause__.args[1]",
"try:\n db.session.add(self)\n return db.session.commit()\nexcept Excepti... | <|body_start_0|>
try:
if self.id is None:
return self.query.all()
if self.id is not None and type(self.id) is int and (self.id >= 0):
return self.query.get(self.id)
except Exception as e:
return e.__cause__.args[1]
<|end_body_0|>
<|bod... | Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id] | ComponentTag | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComponentTag:
"""Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id]"""
def get(self):
"""Using ... | stack_v2_sparse_classes_36k_train_006931 | 10,042 | no_license | [
{
"docstring": "Using get all component tags or get a single component tag. [description] Keyword Arguments: id {[int]} -- [Component group ID] (default: {None}) Returns: [Information about component(s)] -- [When successed] [Message] -- [When failed]",
"name": "get",
"signature": "def get(self)"
},
... | 3 | stack_v2_sparse_classes_30k_train_019737 | Implement the Python class `ComponentTag` described below.
Class description:
Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id]
... | Implement the Python class `ComponentTag` described below.
Class description:
Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id]
... | 052956e5006f7d274d19a43b061c2fe4a6456cc0 | <|skeleton|>
class ComponentTag:
"""Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id]"""
def get(self):
"""Using ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComponentTag:
"""Using to create a component tag [description] Extends: db.Model Variables: __tablename__ {str} -- [table name in database] id {[int]} -- [The id of component tag] component_id {[int]} -- [The id of component] tag_id {[int]} -- [The tag id]"""
def get(self):
"""Using get all compo... | the_stack_v2_python_sparse | models/components.py | BoTranVan/statuspage | train | 0 |
f8bfeadbb0c34abc9530df57e608702dc8c85eec | [
"a = []\nb = []\nt = []\nfor i in A:\n if i % 2 == 0:\n a.append(i)\n else:\n b.append(i)\nfor x in range(len(A) // 2):\n t.append(a[x])\n t.append(b[x])\nreturn t",
"n = len(A)\nresult = [0] * n\neven, odd = (0, 1)\nfor i in A:\n if i % 2 == 0:\n result[even] = i\n even... | <|body_start_0|>
a = []
b = []
t = []
for i in A:
if i % 2 == 0:
a.append(i)
else:
b.append(i)
for x in range(len(A) // 2):
t.append(a[x])
t.append(b[x])
return t
<|end_body_0|>
<|body_start_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortArrayByParityII_1(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParityII_2(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
a = []
b = []
... | stack_v2_sparse_classes_36k_train_006932 | 857 | no_license | [
{
"docstring": ":type A: List[int] :rtype: List[int]",
"name": "sortArrayByParityII_1",
"signature": "def sortArrayByParityII_1(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: List[int]",
"name": "sortArrayByParityII_2",
"signature": "def sortArrayByParityII_2(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII_1(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII_2(self, A): :type A: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortArrayByParityII_1(self, A): :type A: List[int] :rtype: List[int]
- def sortArrayByParityII_2(self, A): :type A: List[int] :rtype: List[int]
<|skeleton|>
class Solution:
... | ec641c43ee481220b3ccdac2d1b6d0826fe379a5 | <|skeleton|>
class Solution:
def sortArrayByParityII_1(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_0|>
def sortArrayByParityII_2(self, A):
""":type A: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortArrayByParityII_1(self, A):
""":type A: List[int] :rtype: List[int]"""
a = []
b = []
t = []
for i in A:
if i % 2 == 0:
a.append(i)
else:
b.append(i)
for x in range(len(A) // 2):
... | the_stack_v2_python_sparse | Leetcode/leetcode922.py | lxh1997zj/-offer_and_LeetCode | train | 0 | |
2185f568dfc58b57aa889ecf6b3751374db57d2f | [
"self.etf_symbol = etfSymbol\nself.universe_settings = universeSettings\nself.universe_filter_function = universeFilterFunc\nself.universe = None",
"if self.universe is None:\n self.universe = algorithm.Universe.ETF(self.etf_symbol, self.universe_settings, self.universe_filter_function)\nreturn [self.universe]... | <|body_start_0|>
self.etf_symbol = etfSymbol
self.universe_settings = universeSettings
self.universe_filter_function = universeFilterFunc
self.universe = None
<|end_body_0|>
<|body_start_1|>
if self.universe is None:
self.universe = algorithm.Universe.ETF(self.etf_sy... | Universe selection model that selects the constituents of an ETF. | ETFConstituentsUniverseSelectionModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ETFConstituentsUniverseSelectionModel:
"""Universe selection model that selects the constituents of an ETF."""
def __init__(self, etfSymbol, universeSettings=None, universeFilterFunc=None):
"""Initializes a new instance of the ETFConstituentsUniverseSelectionModel class Args: etfSymb... | stack_v2_sparse_classes_36k_train_006933 | 2,049 | permissive | [
{
"docstring": "Initializes a new instance of the ETFConstituentsUniverseSelectionModel class Args: etfSymbol: Symbol of the ETF to get constituents for universeSettings: Universe settings universeFilterFunc: Function to filter universe results",
"name": "__init__",
"signature": "def __init__(self, etfS... | 2 | stack_v2_sparse_classes_30k_train_012968 | Implement the Python class `ETFConstituentsUniverseSelectionModel` described below.
Class description:
Universe selection model that selects the constituents of an ETF.
Method signatures and docstrings:
- def __init__(self, etfSymbol, universeSettings=None, universeFilterFunc=None): Initializes a new instance of the ... | Implement the Python class `ETFConstituentsUniverseSelectionModel` described below.
Class description:
Universe selection model that selects the constituents of an ETF.
Method signatures and docstrings:
- def __init__(self, etfSymbol, universeSettings=None, universeFilterFunc=None): Initializes a new instance of the ... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class ETFConstituentsUniverseSelectionModel:
"""Universe selection model that selects the constituents of an ETF."""
def __init__(self, etfSymbol, universeSettings=None, universeFilterFunc=None):
"""Initializes a new instance of the ETFConstituentsUniverseSelectionModel class Args: etfSymb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ETFConstituentsUniverseSelectionModel:
"""Universe selection model that selects the constituents of an ETF."""
def __init__(self, etfSymbol, universeSettings=None, universeFilterFunc=None):
"""Initializes a new instance of the ETFConstituentsUniverseSelectionModel class Args: etfSymbol: Symbol of... | the_stack_v2_python_sparse | Algorithm.Framework/Selection/ETFConstituentsUniverseSelectionModel.py | Capnode/Algoloop | train | 87 |
14a2f55bb0859861c3875689195dfd00246427a4 | [
"conn = sqlite3.connect(path)\nif os.path.exists(path) and os.path.isfile(path):\n return conn\nelse:\n conn = None\n return sqlite3.connect(':memory:')",
"if conn is not None:\n return conn.cursor()\nelse:\n return get_conn('').cursor()",
"if table is not None and table != '':\n sql = 'DROP T... | <|body_start_0|>
conn = sqlite3.connect(path)
if os.path.exists(path) and os.path.isfile(path):
return conn
else:
conn = None
return sqlite3.connect(':memory:')
<|end_body_0|>
<|body_start_1|>
if conn is not None:
return conn.cursor()
... | SQL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SQL:
def get_conn(self, path):
"""获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象"""
<|body_0|>
def get_cursor(self, conn):
"""该方法是获取数据库的游标对象，参数为数据库的连接对象，如果数据库的连接对象不 为None,则返回数据库连接对象所创建的游标对象；否则返回一个游标对象，该对象是内存 中数据库连接对象所创建的游标对象"""
... | stack_v2_sparse_classes_36k_train_006934 | 7,146 | no_license | [
{
"docstring": "获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象",
"name": "get_conn",
"signature": "def get_conn(self, path)"
},
{
"docstring": "该方法是获取数据库的游标对象，参数为数据库的连接对象，如果数据库的连接对象不 为None,则返回数据库连接对象所创建的游标对象；否则返回一个游标对象，该对象是内存 中数据库连接对象所创建的游标对象",
"name": ... | 5 | stack_v2_sparse_classes_30k_train_012386 | Implement the Python class `SQL` described below.
Class description:
Implement the SQL class.
Method signatures and docstrings:
- def get_conn(self, path): 获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象
- def get_cursor(self, conn): 该方法是获取数据库的游标对象，参数为数据库的连接对象，如果数据库的连接对象不 为None,则... | Implement the Python class `SQL` described below.
Class description:
Implement the SQL class.
Method signatures and docstrings:
- def get_conn(self, path): 获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象
- def get_cursor(self, conn): 该方法是获取数据库的游标对象，参数为数据库的连接对象，如果数据库的连接对象不 为None,则... | 04257fd49f05d4b567e234dea4cdf3907aebf0eb | <|skeleton|>
class SQL:
def get_conn(self, path):
"""获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象"""
<|body_0|>
def get_cursor(self, conn):
"""该方法是获取数据库的游标对象，参数为数据库的连接对象，如果数据库的连接对象不 为None,则返回数据库连接对象所创建的游标对象；否则返回一个游标对象，该对象是内存 中数据库连接对象所创建的游标对象"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SQL:
def get_conn(self, path):
"""获取到数据库的连接对象，参数为数据库文件的绝对路径，如果传递的参数是存在，并 且是文件，那么就返回硬盘上面该路径下的数据库文件的连接对象；否则，返回内存中的数 据链接对象"""
conn = sqlite3.connect(path)
if os.path.exists(path) and os.path.isfile(path):
return conn
else:
conn = None
return sql... | the_stack_v2_python_sparse | web/backend/src/mydb.py | erineliu/test-framework | train | 0 | |
cb3734155c0c730f3d201e966eed33c3a665a7a9 | [
"pu = ground_level_m\nlatitude, longitude, _alt = pm.enu2geodetic(pe_m, pn_m, pu, lat0_rad, lon0_rad, ground_level_m, ell=None, deg=False)\necef_x, ecef_y, ecef_z = pm.enu2ecef(pe_m, pn_m, pu, lat0_rad, lon0_rad, ground_level_m, ell=None, deg=False)\nglobal_rotation = Rotation.from_quat(Dubins2DConverter.quaternion... | <|body_start_0|>
pu = ground_level_m
latitude, longitude, _alt = pm.enu2geodetic(pe_m, pn_m, pu, lat0_rad, lon0_rad, ground_level_m, ell=None, deg=False)
ecef_x, ecef_y, ecef_z = pm.enu2ecef(pe_m, pn_m, pu, lat0_rad, lon0_rad, ground_level_m, ell=None, deg=False)
global_rotation = Rotati... | Dubins2DConverter | [
"GPL-3.0-only",
"BSD-3-Clause",
"GPL-1.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dubins2DConverter:
def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list:
"""This method takes in a dictionary of "raw" 2D Dubins log data, as read from the LogReader class, and returns a populated Episode object."""
<|body_0|>
def qua... | stack_v2_sparse_classes_36k_train_006935 | 2,905 | permissive | [
{
"docstring": "This method takes in a dictionary of \"raw\" 2D Dubins log data, as read from the LogReader class, and returns a populated Episode object.",
"name": "convert_data",
"signature": "def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list"
},
{
"... | 2 | stack_v2_sparse_classes_30k_train_000403 | Implement the Python class `Dubins2DConverter` described below.
Class description:
Implement the Dubins2DConverter class.
Method signatures and docstrings:
- def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list: This method takes in a dictionary of "raw" 2D Dubins log data, as... | Implement the Python class `Dubins2DConverter` described below.
Class description:
Implement the Dubins2DConverter class.
Method signatures and docstrings:
- def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list: This method takes in a dictionary of "raw" 2D Dubins log data, as... | c90a7346f3a2a651adda5b6ead47d4989af59dcc | <|skeleton|>
class Dubins2DConverter:
def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list:
"""This method takes in a dictionary of "raw" 2D Dubins log data, as read from the LogReader class, and returns a populated Episode object."""
<|body_0|>
def qua... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dubins2DConverter:
def convert_data(cls, pn_m, pe_m, alt_m, psi_rad, lat0_rad, lon0_rad, ground_level_m) -> list:
"""This method takes in a dictionary of "raw" 2D Dubins log data, as read from the LogReader class, and returns a populated Episode object."""
pu = ground_level_m
latitude,... | the_stack_v2_python_sparse | csaf_f16/fgconverter.py | GaloisInc/csaf | train | 11 | |
a3f7a68156c30a0dbeef317fa5a4aab155c8728a | [
"self.series = series\nself.time_start = time_start\nself.time_end = time_end\nself.time_interval_sec = (time_end - time_start) // NUMBER_OF_BINS\nself.binned_series = []\nself.events_by_key = {}\nself.binned_series, self.events_by_key = self.create_binned_series()\nself.bins_values = list(map(lambda x: self.sum_da... | <|body_start_0|>
self.series = series
self.time_start = time_start
self.time_end = time_end
self.time_interval_sec = (time_end - time_start) // NUMBER_OF_BINS
self.binned_series = []
self.events_by_key = {}
self.binned_series, self.events_by_key = self.create_binn... | Object to calculate time series histograms on data with special format, look at the above get_series methods. | TimeSeries | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeSeries:
"""Object to calculate time series histograms on data with special format, look at the above get_series methods."""
def __init__(self, series, time_start, time_end):
""":param series: data series :type series: list[dict] :param time_start: unix timestamp :type time_start:... | stack_v2_sparse_classes_36k_train_006936 | 14,137 | permissive | [
{
"docstring": ":param series: data series :type series: list[dict] :param time_start: unix timestamp :type time_start: int :param time_end: unix timestamp :type time_end: int",
"name": "__init__",
"signature": "def __init__(self, series, time_start, time_end)"
},
{
"docstring": "Creates the his... | 4 | stack_v2_sparse_classes_30k_train_015852 | Implement the Python class `TimeSeries` described below.
Class description:
Object to calculate time series histograms on data with special format, look at the above get_series methods.
Method signatures and docstrings:
- def __init__(self, series, time_start, time_end): :param series: data series :type series: list[... | Implement the Python class `TimeSeries` described below.
Class description:
Object to calculate time series histograms on data with special format, look at the above get_series methods.
Method signatures and docstrings:
- def __init__(self, series, time_start, time_end): :param series: data series :type series: list[... | 7885f02f13eda3c89fda3d53f76310b6f50960d7 | <|skeleton|>
class TimeSeries:
"""Object to calculate time series histograms on data with special format, look at the above get_series methods."""
def __init__(self, series, time_start, time_end):
""":param series: data series :type series: list[dict] :param time_start: unix timestamp :type time_start:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeSeries:
"""Object to calculate time series histograms on data with special format, look at the above get_series methods."""
def __init__(self, series, time_start, time_end):
""":param series: data series :type series: list[dict] :param time_start: unix timestamp :type time_start: int :param t... | the_stack_v2_python_sparse | lndmanage/lib/report.py | bitromortac/lndmanage | train | 178 |
75439b5f0ac4d753885f08d1c62cf52cbb71ce47 | [
"super(LeamNet, self).__init__()\nself.embed_x = nn.Embedding(opt.n_words, opt.embed_size)\nself.embed_y = nn.Embedding(opt.num_class, opt.embed_size)\nself.att_conv = nn.Conv1d(opt.num_class, opt.num_class, kernel_size=opt.ngram, padding=opt.ngram / 2)\nself.H1_dropout_x = nn.Dropout(opt.dropout)\nself.H1_x = nn.L... | <|body_start_0|>
super(LeamNet, self).__init__()
self.embed_x = nn.Embedding(opt.n_words, opt.embed_size)
self.embed_y = nn.Embedding(opt.num_class, opt.embed_size)
self.att_conv = nn.Conv1d(opt.num_class, opt.num_class, kernel_size=opt.ngram, padding=opt.ngram / 2)
self.H1_dropo... | LeamNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LeamNet:
def __init__(self, opt):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x, x_mask, opt):
"""In the forward function we accept a Tensor of input data and we must return a Tensor ... | stack_v2_sparse_classes_36k_train_006937 | 3,532 | permissive | [
{
"docstring": "In the constructor we instantiate two nn.Linear modules and assign them as member variables.",
"name": "__init__",
"signature": "def __init__(self, opt)"
},
{
"docstring": "In the forward function we accept a Tensor of input data and we must return a Tensor of output data. We can... | 2 | stack_v2_sparse_classes_30k_train_016456 | Implement the Python class `LeamNet` described below.
Class description:
Implement the LeamNet class.
Method signatures and docstrings:
- def __init__(self, opt): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x, x_mask, opt): In the forward function w... | Implement the Python class `LeamNet` described below.
Class description:
Implement the LeamNet class.
Method signatures and docstrings:
- def __init__(self, opt): In the constructor we instantiate two nn.Linear modules and assign them as member variables.
- def forward(self, x, x_mask, opt): In the forward function w... | 08f08cbe3d8afe27a2ad005cf8046a129c42bf78 | <|skeleton|>
class LeamNet:
def __init__(self, opt):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
<|body_0|>
def forward(self, x, x_mask, opt):
"""In the forward function we accept a Tensor of input data and we must return a Tensor ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LeamNet:
def __init__(self, opt):
"""In the constructor we instantiate two nn.Linear modules and assign them as member variables."""
super(LeamNet, self).__init__()
self.embed_x = nn.Embedding(opt.n_words, opt.embed_size)
self.embed_y = nn.Embedding(opt.num_class, opt.embed_siz... | the_stack_v2_python_sparse | MH-Term-Project-master/src/LEAM/model.py | voghoei/DL-Fundation | train | 5 | |
bb751e426205113316c84686120d4d44e02f4b8e | [
"self.visited = {}\nif root is not None:\n self.dfs = [root]\n pointer = self.dfs[-1]\nelse:\n self.dfs = []\n pointer = None\nwhile pointer is not None:\n self.visited[pointer.val] = True\n if pointer.left:\n self.dfs.append(pointer.left)\n pointer = pointer.left",
"if self.dfs[-1].va... | <|body_start_0|>
self.visited = {}
if root is not None:
self.dfs = [root]
pointer = self.dfs[-1]
else:
self.dfs = []
pointer = None
while pointer is not None:
self.visited[pointer.val] = True
if pointer.left:
... | BSTIterator2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTIterator2:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k_train_006938 | 2,715 | no_license | [
{
"docstring": ":type root: TreeNode",
"name": "__init__",
"signature": "def __init__(self, root)"
},
{
"docstring": "@return the next smallest number :rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": "@return whether we have a next smallest number :rt... | 3 | null | Implement the Python class `BSTIterator2` described below.
Class description:
Implement the BSTIterator2 class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest... | Implement the Python class `BSTIterator2` described below.
Class description:
Implement the BSTIterator2 class.
Method signatures and docstrings:
- def __init__(self, root): :type root: TreeNode
- def next(self): @return the next smallest number :rtype: int
- def hasNext(self): @return whether we have a next smallest... | 9387c1cbf1cac2db1aebf5ad196230705ab0fcc7 | <|skeleton|>
class BSTIterator2:
def __init__(self, root):
""":type root: TreeNode"""
<|body_0|>
def next(self):
"""@return the next smallest number :rtype: int"""
<|body_1|>
def hasNext(self):
"""@return whether we have a next smallest number :rtype: bool"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BSTIterator2:
def __init__(self, root):
""":type root: TreeNode"""
self.visited = {}
if root is not None:
self.dfs = [root]
pointer = self.dfs[-1]
else:
self.dfs = []
pointer = None
while pointer is not None:
s... | the_stack_v2_python_sparse | binary_search_tree_iterator.py | lightening0907/algorithm | train | 0 | |
84c5e9a8ec64bb21eb2cde555c100f6149c737e0 | [
"self.list_of_fixes = []\nself.time_threshold = time_threshold * 1000\nself.distance_threshold = distance_threshold\nself.verbose = verbose",
"self.list_of_fixes.append(gps_fix)\nif len(self.list_of_fixes) == 1:\n return (None, None)\nelse:\n return self._process_live()",
"pi = self.list_of_fixes[0]\npj =... | <|body_start_0|>
self.list_of_fixes = []
self.time_threshold = time_threshold * 1000
self.distance_threshold = distance_threshold
self.verbose = verbose
<|end_body_0|>
<|body_start_1|>
self.list_of_fixes.append(gps_fix)
if len(self.list_of_fixes) == 1:
return... | Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_threshold: distance threshold parameter verbose: print internal states-task details | StreamedZhen | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StreamedZhen:
"""Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_threshold: distance threshold parameter verb... | stack_v2_sparse_classes_36k_train_006939 | 3,412 | permissive | [
{
"docstring": "Basic constructor :param time_threshold: Time threshold to employ (in seconds) :param distance_threshold: Distance threshold to employ :param verbose: print task details",
"name": "__init__",
"signature": "def __init__(self, time_threshold, distance_threshold, verbose=False)"
},
{
... | 5 | null | Implement the Python class `StreamedZhen` described below.
Class description:
Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_thres... | Implement the Python class `StreamedZhen` described below.
Class description:
Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_thres... | b058185ca028abd1902edbb35a52d3565b06f8b0 | <|skeleton|>
class StreamedZhen:
"""Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_threshold: distance threshold parameter verb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StreamedZhen:
"""Zhen live algorithm for stay points detection. It works buffering fixes, as the accumulation of coordinates might lead to overflow of values. Attributes: time_threshold: time threshold parameter (value is kept in milliseconds) distance_threshold: distance threshold parameter verbose: print in... | the_stack_v2_python_sparse | pac/stay_point_detectors/StreamedZhen.py | s0lver/stm-creator | train | 0 |
a24c9583d141b85edc2aad239b9119b3e8cf0bcd | [
"nvars = 3\nsuper().__init__(init=(nvars, None, np.dtype('float64')))\nself._makeAttributeAndRegister('nvars', 'duty', 'fsw', 'Vs', 'Rs', 'C1', 'Rp', 'L1', 'C2', 'Rl', localVars=locals(), readOnly=True)\nself.A = np.zeros((nvars, nvars))",
"Tsw = 1 / self.fsw\nf = self.dtype_f(self.init, val=0.0)\nf.impl[:] = sel... | <|body_start_0|>
nvars = 3
super().__init__(init=(nvars, None, np.dtype('float64')))
self._makeAttributeAndRegister('nvars', 'duty', 'fsw', 'Vs', 'Rs', 'C1', 'Rp', 'L1', 'C2', 'Rl', localVars=locals(), readOnly=True)
self.A = np.zeros((nvars, nvars))
<|end_body_0|>
<|body_start_1|>
... | Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equations (ODEs) .. math:: \\frac{d u(t)}{dt} = A_k u(t) + f_k (t) for :math:`k=1,2`. ... | buck_converter | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class buck_converter:
"""Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equations (ODEs) .. math:: \\frac{d u(t)}{dt... | stack_v2_sparse_classes_36k_train_006940 | 6,346 | permissive | [
{
"docstring": "Initialization routine",
"name": "__init__",
"signature": "def __init__(self, duty=0.5, fsw=1000.0, Vs=10.0, Rs=0.5, C1=0.001, Rp=0.01, L1=0.001, C2=0.001, Rl=10)"
},
{
"docstring": "Routine to evaluate the right-hand side of the problem. Parameters ---------- u : dtype_u Current... | 4 | null | Implement the Python class `buck_converter` described below.
Class description:
Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equat... | Implement the Python class `buck_converter` described below.
Class description:
Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equat... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class buck_converter:
"""Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equations (ODEs) .. math:: \\frac{d u(t)}{dt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class buck_converter:
"""Example implementing the model of a buck converter, which is also called a step-down converter. The converter has two different states and each of this state can be expressed as a nonhomogeneous linear system of ordinary differential equations (ODEs) .. math:: \\frac{d u(t)}{dt} = A_k u(t) ... | the_stack_v2_python_sparse | pySDC/implementations/problem_classes/BuckConverter.py | Parallel-in-Time/pySDC | train | 30 |
f019c4222049d7857e9a1f484e0e87656b0ea85c | [
"self.check_type = check_type\nself.result_type = result_type\nself.user_message = user_message",
"if dictionary is None:\n return None\ncheck_type = dictionary.get('checkType')\nresult_type = dictionary.get('resultType')\nuser_message = dictionary.get('userMessage')\nreturn cls(check_type, result_type, user_m... | <|body_start_0|>
self.check_type = check_type
self.result_type = result_type
self.user_message = user_message
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
check_type = dictionary.get('checkType')
result_type = dictionary.get('resultType'... | Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies the type of the host check performed internally. 'kIsAgentPortAccessible' indicates the chec... | HostSettingsCheckResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostSettingsCheckResult:
"""Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies the type of the host check performed inte... | stack_v2_sparse_classes_36k_train_006941 | 3,246 | permissive | [
{
"docstring": "Constructor for the HostSettingsCheckResult class",
"name": "__init__",
"signature": "def __init__(self, check_type=None, result_type=None, user_message=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary repre... | 2 | stack_v2_sparse_classes_30k_train_006164 | Implement the Python class `HostSettingsCheckResult` described below.
Class description:
Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies th... | Implement the Python class `HostSettingsCheckResult` described below.
Class description:
Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies th... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class HostSettingsCheckResult:
"""Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies the type of the host check performed inte... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HostSettingsCheckResult:
"""Implementation of the 'HostSettingsCheckResult' model. Specifies the result of various checks performed internally on host. Attributes: check_type (CheckTypeEnum): Specifies the type of the check internally performed. Specifies the type of the host check performed internally. 'kIsA... | the_stack_v2_python_sparse | cohesity_management_sdk/models/host_settings_check_result.py | cohesity/management-sdk-python | train | 24 |
c3f2d1cddd50989b45fe5f021ddf96f2c01dea2a | [
"cdk_config_file = os.path.join(os.getcwd(), 'cdk.json')\ncdk_language = cfg.CDKLanguage\ncdk_init_cmd = ['cdk', 'init', 'app', '--language', cdk_language]\nif os.path.isfile(cdk_config_file):\n logging.info('CDK application already created.')\nelse:\n logging.info('Creating a new CDK application.')\n run_... | <|body_start_0|>
cdk_config_file = os.path.join(os.getcwd(), 'cdk.json')
cdk_language = cfg.CDKLanguage
cdk_init_cmd = ['cdk', 'init', 'app', '--language', cdk_language]
if os.path.isfile(cdk_config_file):
logging.info('CDK application already created.')
else:
... | Manage CDK dependencies and its versions for the project. | CDKDependencies | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CDKDependencies:
"""Manage CDK dependencies and its versions for the project."""
def init_cdk(cfg=current_config):
"""Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--language typescript` language in which cdk will be built.... | stack_v2_sparse_classes_36k_train_006942 | 3,754 | no_license | [
{
"docstring": "Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--language typescript` language in which cdk will be built. After running CDK init it will read the package.json created and get the CDK version to lock in Windsor config. :param cfg: Confi... | 5 | stack_v2_sparse_classes_30k_train_000838 | Implement the Python class `CDKDependencies` described below.
Class description:
Manage CDK dependencies and its versions for the project.
Method signatures and docstrings:
- def init_cdk(cfg=current_config): Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--... | Implement the Python class `CDKDependencies` described below.
Class description:
Manage CDK dependencies and its versions for the project.
Method signatures and docstrings:
- def init_cdk(cfg=current_config): Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--... | 13cb202fba954d63d728feb0635241d55680a718 | <|skeleton|>
class CDKDependencies:
"""Manage CDK dependencies and its versions for the project."""
def init_cdk(cfg=current_config):
"""Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--language typescript` language in which cdk will be built.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CDKDependencies:
"""Manage CDK dependencies and its versions for the project."""
def init_cdk(cfg=current_config):
"""Run CDK init using the following arguments. `app` the template used to bootstrap the directory structure. `--language typescript` language in which cdk will be built. After runnin... | the_stack_v2_python_sparse | windsor/cdkdependencies.py | westpoint-io/windsor | train | 3 |
cd3ba5abdd2e221f464815bbc9bd5d0f7ea3582f | [
"try:\n import lxml\nexcept ImportError:\n raise ValueError('lxml package not found, please install it with `pip install lxml`')\nsuper().__init__(web_path)\nself.filter_urls = filter_urls\nself.parsing_function = parsing_function or _default_parsing_function",
"els = []\nfor url in soup.find_all('url'):\n ... | <|body_start_0|>
try:
import lxml
except ImportError:
raise ValueError('lxml package not found, please install it with `pip install lxml`')
super().__init__(web_path)
self.filter_urls = filter_urls
self.parsing_function = parsing_function or _default_parsi... | Loader that fetches a sitemap and loads those URLs. | SitemapLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SitemapLoader:
"""Loader that fetches a sitemap and loads those URLs."""
def __init__(self, web_path: str, filter_urls: Optional[List[str]]=None, parsing_function: Optional[Callable]=None):
"""Initialize with webpage path and optional filter URLs. Args: web_path: url of the sitemap f... | stack_v2_sparse_classes_36k_train_006943 | 2,392 | no_license | [
{
"docstring": "Initialize with webpage path and optional filter URLs. Args: web_path: url of the sitemap filter_urls: list of strings or regexes that will be applied to filter the urls that are parsed and loaded parsing_function: Function to parse bs4.Soup output",
"name": "__init__",
"signature": "def... | 3 | null | Implement the Python class `SitemapLoader` described below.
Class description:
Loader that fetches a sitemap and loads those URLs.
Method signatures and docstrings:
- def __init__(self, web_path: str, filter_urls: Optional[List[str]]=None, parsing_function: Optional[Callable]=None): Initialize with webpage path and o... | Implement the Python class `SitemapLoader` described below.
Class description:
Loader that fetches a sitemap and loads those URLs.
Method signatures and docstrings:
- def __init__(self, web_path: str, filter_urls: Optional[List[str]]=None, parsing_function: Optional[Callable]=None): Initialize with webpage path and o... | b7aaa920a52613e3f1f04fa5cd7568ad37302d11 | <|skeleton|>
class SitemapLoader:
"""Loader that fetches a sitemap and loads those URLs."""
def __init__(self, web_path: str, filter_urls: Optional[List[str]]=None, parsing_function: Optional[Callable]=None):
"""Initialize with webpage path and optional filter URLs. Args: web_path: url of the sitemap f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SitemapLoader:
"""Loader that fetches a sitemap and loads those URLs."""
def __init__(self, web_path: str, filter_urls: Optional[List[str]]=None, parsing_function: Optional[Callable]=None):
"""Initialize with webpage path and optional filter URLs. Args: web_path: url of the sitemap filter_urls: l... | the_stack_v2_python_sparse | openai/venv/lib/python3.10/site-packages/langchain/document_loaders/sitemap.py | henrymendez/garage | train | 0 |
41f0d0ad5e971b2d4f0352278ab517ecbcf7767c | [
"shots = 100\ncircuits = ref_measure.multiqubit_measure_circuits_deterministic(allow_sampling=True)\ntargets = ref_measure.multiqubit_measure_counts_deterministic(shots)\nqobj = assemble(circuits, self.SIMULATOR, shots=shots)\nresult = self.SIMULATOR.run(qobj, backend_options=self.BACKEND_OPTS).result()\nself.is_co... | <|body_start_0|>
shots = 100
circuits = ref_measure.multiqubit_measure_circuits_deterministic(allow_sampling=True)
targets = ref_measure.multiqubit_measure_counts_deterministic(shots)
qobj = assemble(circuits, self.SIMULATOR, shots=shots)
result = self.SIMULATOR.run(qobj, backend... | QasmSimulator measure tests. | QasmMultiQubitMeasureTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QasmMultiQubitMeasureTests:
"""QasmSimulator measure tests."""
def test_measure_deterministic_multi_qubit_with_sampling(self):
"""Test QasmSimulator multi-qubit measure with deterministic counts with sampling"""
<|body_0|>
def test_measure_deterministic_multi_qubit_witho... | stack_v2_sparse_classes_36k_train_006944 | 10,352 | permissive | [
{
"docstring": "Test QasmSimulator multi-qubit measure with deterministic counts with sampling",
"name": "test_measure_deterministic_multi_qubit_with_sampling",
"signature": "def test_measure_deterministic_multi_qubit_with_sampling(self)"
},
{
"docstring": "Test QasmSimulator multi-qubit measure... | 4 | null | Implement the Python class `QasmMultiQubitMeasureTests` described below.
Class description:
QasmSimulator measure tests.
Method signatures and docstrings:
- def test_measure_deterministic_multi_qubit_with_sampling(self): Test QasmSimulator multi-qubit measure with deterministic counts with sampling
- def test_measure... | Implement the Python class `QasmMultiQubitMeasureTests` described below.
Class description:
QasmSimulator measure tests.
Method signatures and docstrings:
- def test_measure_deterministic_multi_qubit_with_sampling(self): Test QasmSimulator multi-qubit measure with deterministic counts with sampling
- def test_measure... | 0c1c805fd5dfce465a8955ee3faf81037023a23e | <|skeleton|>
class QasmMultiQubitMeasureTests:
"""QasmSimulator measure tests."""
def test_measure_deterministic_multi_qubit_with_sampling(self):
"""Test QasmSimulator multi-qubit measure with deterministic counts with sampling"""
<|body_0|>
def test_measure_deterministic_multi_qubit_witho... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QasmMultiQubitMeasureTests:
"""QasmSimulator measure tests."""
def test_measure_deterministic_multi_qubit_with_sampling(self):
"""Test QasmSimulator multi-qubit measure with deterministic counts with sampling"""
shots = 100
circuits = ref_measure.multiqubit_measure_circuits_determ... | the_stack_v2_python_sparse | artifacts/old_dataset_versions/original_commits_backup/qiskit-aer/qiskit-aer#322/before/qasm_measure.py | MattePalte/Bugs-Quantum-Computing-Platforms | train | 4 |
2adf3f18e606b193ccaafbf7b02ef642c609fc0e | [
"minNumber = 1000000000.0\nfor i in numbers:\n if i < minNumber:\n minNumber = i\nreturn minNumber",
"i, j = (0, len(numbers) - 1)\nwhile i < j:\n m = (i + j) // 2\n if numbers[m] > numbers[j]:\n i = m + 1\n elif numbers[m] < numbers[j]:\n j = m\n else:\n j -= 1\nreturn ... | <|body_start_0|>
minNumber = 1000000000.0
for i in numbers:
if i < minNumber:
minNumber = i
return minNumber
<|end_body_0|>
<|body_start_1|>
i, j = (0, len(numbers) - 1)
while i < j:
m = (i + j) // 2
if numbers[m] > numbers[j]:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
<... | stack_v2_sparse_classes_36k_train_006945 | 3,169 | no_license | [
{
"docstring": "注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)",
"name": "minArray",
"signature": "def minArray(self, numbers: List[int... | 2 | stack_v2_sparse_classes_30k_train_000421 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minArray(self, numbers: List[int]) -> int: 注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minArray(self, numbers: List[int]) -> int: 注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1... | 51943e2c2c4ec70c7c1d5b53c9fdf0a719428d7a | <|skeleton|>
class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
<... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minArray(self, numbers: List[int]) -> int:
"""注意此题：虽然是递增排序，但是并不排除是包含重复元素的升序数组。 此题会分为三种情况： 第一种情况： 数组[1,2,3,4,5] 1和2旋转后数组尾部， 旋转后为 [3,4,5,1,2] 第二种情况： 数组[1,2,3,4,5] 整体旋转，旋转后不变，仍然为[1,2,3,4,5] 第三种情况： 数组[1,1,1,1,1] 不管怎么旋转，旋转后都为 [1,1,1,1,1] 复杂度分析： 时间复杂度为O(n) 空间复杂度为O(1)"""
minNumber = 100... | the_stack_v2_python_sparse | 剑指offer/PythonVersion/11_旋转数组的最小数字.py | LeBron-Jian/BasicAlgorithmPractice | train | 13 | |
b72494013d0c70a7d2dac223a4b3851734505098 | [
"nonexistent_las = 'nonexistent.las'\nnonexistent_ply = 'nonexistent.ply'\nload(nonexistent_las, nonexistent_ply)\nload_las_mock.assert_called_once_with(nonexistent_las)",
"nonexistent_las = 'nonexistent.las'\nnonexistent_ply = 'nonexistent.ply'\nload(nonexistent_las, nonexistent_ply)\nwrite_ply_mock.assert_calle... | <|body_start_0|>
nonexistent_las = 'nonexistent.las'
nonexistent_ply = 'nonexistent.ply'
load(nonexistent_las, nonexistent_ply)
load_las_mock.assert_called_once_with(nonexistent_las)
<|end_body_0|>
<|body_start_1|>
nonexistent_las = 'nonexistent.las'
nonexistent_ply = 'n... | TestLoad | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLoad:
def test_load(self, load_las_mock, write_ply_mock):
"""Load module should call load_las to get the file."""
<|body_0|>
def test_write(self, load_las_mock, write_ply_mock):
"""Load module should call write_ply to get the file."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_006946 | 1,251 | permissive | [
{
"docstring": "Load module should call load_las to get the file.",
"name": "test_load",
"signature": "def test_load(self, load_las_mock, write_ply_mock)"
},
{
"docstring": "Load module should call write_ply to get the file.",
"name": "test_write",
"signature": "def test_write(self, load... | 2 | stack_v2_sparse_classes_30k_train_011600 | Implement the Python class `TestLoad` described below.
Class description:
Implement the TestLoad class.
Method signatures and docstrings:
- def test_load(self, load_las_mock, write_ply_mock): Load module should call load_las to get the file.
- def test_write(self, load_las_mock, write_ply_mock): Load module should ca... | Implement the Python class `TestLoad` described below.
Class description:
Implement the TestLoad class.
Method signatures and docstrings:
- def test_load(self, load_las_mock, write_ply_mock): Load module should call load_las to get the file.
- def test_write(self, load_las_mock, write_ply_mock): Load module should ca... | 8053cf6f31a7e62b0c4d1d2586284c37da8f13fb | <|skeleton|>
class TestLoad:
def test_load(self, load_las_mock, write_ply_mock):
"""Load module should call load_las to get the file."""
<|body_0|>
def test_write(self, load_las_mock, write_ply_mock):
"""Load module should call write_ply to get the file."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestLoad:
def test_load(self, load_las_mock, write_ply_mock):
"""Load module should call load_las to get the file."""
nonexistent_las = 'nonexistent.las'
nonexistent_ply = 'nonexistent.ply'
load(nonexistent_las, nonexistent_ply)
load_las_mock.assert_called_once_with(non... | the_stack_v2_python_sparse | laserchicken/test_load.py | rubenvalpue/laserchicken | train | 0 | |
1b3154d139398a7f0080a0d763516aa09c3fb181 | [
"if not (probe and typeMapper):\n raise Exception('Argument exception - request classifier must have valid probe and type mapper')\nself.probe = probe\nself.typeMapper = typeMapper",
"counter = txn.getCounterForProbe(self.probe)\nif counter:\n data = counter.data\n if self.typeMapper:\n return sel... | <|body_start_0|>
if not (probe and typeMapper):
raise Exception('Argument exception - request classifier must have valid probe and type mapper')
self.probe = probe
self.typeMapper = typeMapper
<|end_body_0|>
<|body_start_1|>
counter = txn.getCounterForProbe(self.probe)
... | Classifies transactions based on data in a given probe | ProbeDataClassifier | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProbeDataClassifier:
"""Classifies transactions based on data in a given probe"""
def __init__(self, probe, typeMapper):
"""Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the transaction :type probe: xpedite.types.probe.Probe :param type... | stack_v2_sparse_classes_36k_train_006947 | 1,896 | permissive | [
{
"docstring": "Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the transaction :type probe: xpedite.types.probe.Probe :param typeMapper: a callback to map probe data to a category :type typeMapper: bool",
"name": "__init__",
"signature": "def __init__(self,... | 2 | null | Implement the Python class `ProbeDataClassifier` described below.
Class description:
Classifies transactions based on data in a given probe
Method signatures and docstrings:
- def __init__(self, probe, typeMapper): Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the trans... | Implement the Python class `ProbeDataClassifier` described below.
Class description:
Classifies transactions based on data in a given probe
Method signatures and docstrings:
- def __init__(self, probe, typeMapper): Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the trans... | d6b67e98d4b640c98499a373425f1f009e5b9061 | <|skeleton|>
class ProbeDataClassifier:
"""Classifies transactions based on data in a given probe"""
def __init__(self, probe, typeMapper):
"""Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the transaction :type probe: xpedite.types.probe.Probe :param type... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProbeDataClassifier:
"""Classifies transactions based on data in a given probe"""
def __init__(self, probe, typeMapper):
"""Constructs an instance of ProbeDataClassifier :param probe: A probe that is expected to be in the transaction :type probe: xpedite.types.probe.Probe :param typeMapper: a cal... | the_stack_v2_python_sparse | scripts/lib/xpedite/txn/classifier.py | dendisuhubdy/Xpedite | train | 1 |
de87a8bccdaaf69f6bc607b4bfd5a44026af09af | [
"self.region = region\nself.proxy_config = Config()\nif proxy != 'NONE':\n self.proxy_config = Config(proxies={'https': proxy})",
"try:\n return boto3.client(service, region_name=self.region, config=self.proxy_config)\nexcept ClientError as e:\n fail('AWS %s service failed with exception: %s' % (service,... | <|body_start_0|>
self.region = region
self.proxy_config = Config()
if proxy != 'NONE':
self.proxy_config = Config(proxies={'https': proxy})
<|end_body_0|>
<|body_start_1|>
try:
return boto3.client(service, region_name=self.region, config=self.proxy_config)
... | Boto3 configuration object. | Boto3ClientFactory | [
"Python-2.0",
"GPL-1.0-or-later",
"MPL-2.0",
"MIT",
"LicenseRef-scancode-python-cwi",
"BSD-3-Clause",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-free-unknown",
"Apache-2.0",
"MIT-0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
<|body_0|>
def get_client(self, service):
"""Initialize the boto3 client for a given service. :param service: boto3 service. :return: the ... | stack_v2_sparse_classes_36k_train_006948 | 14,826 | permissive | [
{
"docstring": "Initialize the object.",
"name": "__init__",
"signature": "def __init__(self, region, proxy='NONE')"
},
{
"docstring": "Initialize the boto3 client for a given service. :param service: boto3 service. :return: the boto3 client",
"name": "get_client",
"signature": "def get_... | 2 | stack_v2_sparse_classes_30k_val_000191 | Implement the Python class `Boto3ClientFactory` described below.
Class description:
Boto3 configuration object.
Method signatures and docstrings:
- def __init__(self, region, proxy='NONE'): Initialize the object.
- def get_client(self, service): Initialize the boto3 client for a given service. :param service: boto3 s... | Implement the Python class `Boto3ClientFactory` described below.
Class description:
Boto3 configuration object.
Method signatures and docstrings:
- def __init__(self, region, proxy='NONE'): Initialize the object.
- def get_client(self, service): Initialize the boto3 client for a given service. :param service: boto3 s... | a213978a09ea7fc80855bf55c539861ea95259f9 | <|skeleton|>
class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
<|body_0|>
def get_client(self, service):
"""Initialize the boto3 client for a given service. :param service: boto3 service. :return: the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Boto3ClientFactory:
"""Boto3 configuration object."""
def __init__(self, region, proxy='NONE'):
"""Initialize the object."""
self.region = region
self.proxy_config = Config()
if proxy != 'NONE':
self.proxy_config = Config(proxies={'https': proxy})
def get_... | the_stack_v2_python_sparse | awsbatch-cli/src/awsbatch/common.py | aws/aws-parallelcluster | train | 520 |
9f8c4e732c00a0ca3001dd53d42b31f673f30d6c | [
"params = ObjectDict({'contentId': id})\nhost, port = (yield self.get_ip_proxy())\nret = (yield http_fetch(path.PAPER_ADD_VOTE, data=params, proxy_host=host, proxy_port=port))\nraise gen.Return(ret)",
"host, port = (yield self.get_ip_proxy())\nret = (yield http_get(path.PAPER_ARTICLE.format(id), res_json=False, p... | <|body_start_0|>
params = ObjectDict({'contentId': id})
host, port = (yield self.get_ip_proxy())
ret = (yield http_fetch(path.PAPER_ADD_VOTE, data=params, proxy_host=host, proxy_port=port))
raise gen.Return(ret)
<|end_body_0|>
<|body_start_1|>
host, port = (yield self.get_ip_pro... | paper刷榜 | PaperDataService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PaperDataService:
"""paper刷榜"""
def add_vote(self, id):
"""为文章点赞 :param id: 文章 id :return:"""
<|body_0|>
def read_article(self, id):
"""刷文章浏览数 :param id: 文章 id :return:"""
<|body_1|>
def refresh_article(self, id):
"""利用selenium刷新网页 :param id:... | stack_v2_sparse_classes_36k_train_006949 | 1,724 | no_license | [
{
"docstring": "为文章点赞 :param id: 文章 id :return:",
"name": "add_vote",
"signature": "def add_vote(self, id)"
},
{
"docstring": "刷文章浏览数 :param id: 文章 id :return:",
"name": "read_article",
"signature": "def read_article(self, id)"
},
{
"docstring": "利用selenium刷新网页 :param id: :return... | 3 | null | Implement the Python class `PaperDataService` described below.
Class description:
paper刷榜
Method signatures and docstrings:
- def add_vote(self, id): 为文章点赞 :param id: 文章 id :return:
- def read_article(self, id): 刷文章浏览数 :param id: 文章 id :return:
- def refresh_article(self, id): 利用selenium刷新网页 :param id: :return: | Implement the Python class `PaperDataService` described below.
Class description:
paper刷榜
Method signatures and docstrings:
- def add_vote(self, id): 为文章点赞 :param id: 文章 id :return:
- def read_article(self, id): 刷文章浏览数 :param id: 文章 id :return:
- def refresh_article(self, id): 利用selenium刷新网页 :param id: :return:
<|sk... | deced3892333f866525b46fa51ddbe0fa5ff8f58 | <|skeleton|>
class PaperDataService:
"""paper刷榜"""
def add_vote(self, id):
"""为文章点赞 :param id: 文章 id :return:"""
<|body_0|>
def read_article(self, id):
"""刷文章浏览数 :param id: 文章 id :return:"""
<|body_1|>
def refresh_article(self, id):
"""利用selenium刷新网页 :param id:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PaperDataService:
"""paper刷榜"""
def add_vote(self, id):
"""为文章点赞 :param id: 文章 id :return:"""
params = ObjectDict({'contentId': id})
host, port = (yield self.get_ip_proxy())
ret = (yield http_fetch(path.PAPER_ADD_VOTE, data=params, proxy_host=host, proxy_port=port))
... | the_stack_v2_python_sparse | service/data/paper/paper.py | cash2one/DL-BIKE | train | 0 |
e3d089dec2b8dd02dc31386a8128fa400c95e512 | [
"if len(strs) == 0:\n return chr(258)\nreturn chr(257).join((x for x in strs))",
"if s == chr(258):\n return []\nreturn s.split(chr(257))"
] | <|body_start_0|>
if len(strs) == 0:
return chr(258)
return chr(257).join((x for x in strs))
<|end_body_0|>
<|body_start_1|>
if s == chr(258):
return []
return s.split(chr(257))
<|end_body_1|>
| Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(st... | stack_v2_sparse_classes_36k_train_006950 | 744 | no_license | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | d00993a88c6b34fcd79d0a6580fde5c523a2741d | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
if len(strs) == 0:
return chr(258)
return chr(257).join((x for x in strs))
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
... | the_stack_v2_python_sparse | 271_EncodeAndDecodeStrings/271_EncodeAndDecodeStrings.py | H-Cong/LeetCode | train | 0 | |
8e73fe7b8dd0aceaaa4c0739085c488d2649a286 | [
"new_model = CarModel(name=validated_data.get('name'), brand=validated_data.get('brand'))\nnew_model.save()\nreturn new_model",
"instance.name = validated_data.get('name', instance.name)\ninstance.brand = validated_data.get('brand', instance.brand)\ninstance.save()\nreturn instance"
] | <|body_start_0|>
new_model = CarModel(name=validated_data.get('name'), brand=validated_data.get('brand'))
new_model.save()
return new_model
<|end_body_0|>
<|body_start_1|>
instance.name = validated_data.get('name', instance.name)
instance.brand = validated_data.get('brand', inst... | CarModelSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CarModelSerializer:
def create(self, validated_data):
"""create and return new 'CarModel' instance"""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `CarModel` instance"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_006951 | 6,342 | no_license | [
{
"docstring": "create and return new 'CarModel' instance",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update and return an existing `CarModel` instance",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008219 | Implement the Python class `CarModelSerializer` described below.
Class description:
Implement the CarModelSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): create and return new 'CarModel' instance
- def update(self, instance, validated_data): Update and return an existing `CarMo... | Implement the Python class `CarModelSerializer` described below.
Class description:
Implement the CarModelSerializer class.
Method signatures and docstrings:
- def create(self, validated_data): create and return new 'CarModel' instance
- def update(self, instance, validated_data): Update and return an existing `CarMo... | dba8d1fdb96889e41328e792816a4968cbeb1ed4 | <|skeleton|>
class CarModelSerializer:
def create(self, validated_data):
"""create and return new 'CarModel' instance"""
<|body_0|>
def update(self, instance, validated_data):
"""Update and return an existing `CarModel` instance"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CarModelSerializer:
def create(self, validated_data):
"""create and return new 'CarModel' instance"""
new_model = CarModel(name=validated_data.get('name'), brand=validated_data.get('brand'))
new_model.save()
return new_model
def update(self, instance, validated_data):
... | the_stack_v2_python_sparse | cars_web/cars_app/serializers.py | Ignisor/cars_scrapper | train | 0 | |
240ce93ceeaa4bb98148a78a6c2a508d624fcca0 | [
"self.d = {}\nfor i, word in enumerate(words):\n if word not in self.d:\n self.d[word] = [i]\n else:\n self.d[word].append(i)",
"l1 = self.d[word1]\nl2 = self.d[word2]\nminDist = abs(l1[0] - l2[0])\ni, j = (0, 0)\nlen1 = len(l1)\nlen2 = len(l2)\nwhile i < len1 and j < len2:\n minDist = min(... | <|body_start_0|>
self.d = {}
for i, word in enumerate(words):
if word not in self.d:
self.d[word] = [i]
else:
self.d[word].append(i)
<|end_body_0|>
<|body_start_1|>
l1 = self.d[word1]
l2 = self.d[word2]
minDist = abs(l1[0] ... | WordDistance | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
"""Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_006952 | 1,165 | permissive | [
{
"docstring": "initialize your data structure here. :type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": "Adds a word into the data structure. :type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortes... | 2 | null | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word... | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): initialize your data structure here. :type words: List[str]
- def shortest(self, word1, word2): Adds a word into the data structure. :type word... | 975d7e3b8cb9b6be9e80e07febf4bcf6414acd46 | <|skeleton|>
class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
"""Adds a word into the data structure. :type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
"""initialize your data structure here. :type words: List[str]"""
self.d = {}
for i, word in enumerate(words):
if word not in self.d:
self.d[word] = [i]
else:
self.d[word].append(i)
de... | the_stack_v2_python_sparse | Python/leetcode.244.shortest-word-distance-ii.py | tedye/leetcode | train | 4 | |
57265edca835a048f9864b452a080764ad8f3692 | [
"Action.__init__(self, game_state, player)\nassert isinstance(force, (int, float))\nself.force = force\nself.target = target\nself.end_speed = end_speed",
"if self.target is not None:\n ball_position = self.game_state.get_ball_position()\n orientation = (self.target.position - self.player.pose.position).ang... | <|body_start_0|>
Action.__init__(self, game_state, player)
assert isinstance(force, (int, float))
self.force = force
self.target = target
self.end_speed = end_speed
<|end_body_0|>
<|body_start_1|>
if self.target is not None:
ball_position = self.game_state.ge... | Kick | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Kick:
def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1):
""":param game_state: Current state of the game :param player: Instance of the player :param p_force: Kick force [0, 10]"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_006953 | 1,731 | permissive | [
{
"docstring": ":param game_state: Current state of the game :param player: Instance of the player :param p_force: Kick force [0, 10]",
"name": "__init__",
"signature": "def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1)"... | 2 | null | Implement the Python class `Kick` described below.
Class description:
Implement the Kick class.
Method signatures and docstrings:
- def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1): :param game_state: Current state of the game :param... | Implement the Python class `Kick` described below.
Class description:
Implement the Kick class.
Method signatures and docstrings:
- def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1): :param game_state: Current state of the game :param... | ea997cad26e9eaec75e32f7490e2819151937d93 | <|skeleton|>
class Kick:
def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1):
""":param game_state: Current state of the game :param player: Instance of the player :param p_force: Kick force [0, 10]"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Kick:
def __init__(self, game_state: GameState, player: OurPlayer, force: [int, float], target: Pose=Pose(), end_speed=0, cruise_speed=0.1):
""":param game_state: Current state of the game :param player: Instance of the player :param p_force: Kick force [0, 10]"""
Action.__init__(self, game_st... | the_stack_v2_python_sparse | ai/STA/Action/Kick.py | EtienneLavallee/StrategyAI | train | 0 | |
1d89eb0706b8e662d01d2c26a48842bcc75da2e8 | [
"alpha_num = ''\nif type == 'lower':\n case = string.ascii_lowercase\nelif type == 'upper':\n case = string.ascii_uppercase\nelif type == 'digits':\n case = string.digits\nelif type == 'mix':\n case = string.ascii_letters + string.digits\nelse:\n case = string.ascii_letters\nreturn alpha_num.join((ra... | <|body_start_0|>
alpha_num = ''
if type == 'lower':
case = string.ascii_lowercase
elif type == 'upper':
case = string.ascii_uppercase
elif type == 'digits':
case = string.digits
elif type == 'mix':
case = string.ascii_letters + stri... | Test | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test:
def getAlphaNumeric(self, length, type='letters'):
"""Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Parameters: type: Type of characters string should have. Default is letters Provide lower/upper/digi... | stack_v2_sparse_classes_36k_train_006954 | 1,372 | permissive | [
{
"docstring": "Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Parameters: type: Type of characters string should have. Default is letters Provide lower/upper/digits for different types Returns: None",
"name": "getAlphaNumeric"... | 2 | stack_v2_sparse_classes_30k_train_012146 | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def getAlphaNumeric(self, length, type='letters'): Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Paramet... | Implement the Python class `Test` described below.
Class description:
Implement the Test class.
Method signatures and docstrings:
- def getAlphaNumeric(self, length, type='letters'): Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Paramet... | b16143961cee869c7555b449e2a05abeae2dc3b5 | <|skeleton|>
class Test:
def getAlphaNumeric(self, length, type='letters'):
"""Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Parameters: type: Type of characters string should have. Default is letters Provide lower/upper/digi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test:
def getAlphaNumeric(self, length, type='letters'):
"""Get random string of characters Required Parameters: length: Length of string, number of characters string should have Optional Parameters: type: Type of characters string should have. Default is letters Provide lower/upper/digits for differe... | the_stack_v2_python_sparse | selenium_advanced/unittestpackage/test.py | khanhdodang/automation-training-python | train | 0 | |
3f7a9933246792089de82b1856ceb375e3aa7197 | [
"if not isinstance(args, list) and (not isinstance(args, tuple)):\n raise TypeError('In DBNAlert(), the first argument must be a list or tuple of arguments to send to dbn_alert')\nif alert_exe is not None and (not isinstance(alert_exe, str)) and (not isinstance(alert_exe, Runner)):\n raise TypeError('In DBNAl... | <|body_start_0|>
if not isinstance(args, list) and (not isinstance(args, tuple)):
raise TypeError('In DBNAlert(), the first argument must be a list or tuple of arguments to send to dbn_alert')
if alert_exe is not None and (not isinstance(alert_exe, str)) and (not isinstance(alert_exe, Runner... | !This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions. | DBNAlert | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBNAlert:
"""!This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions."""
def __init__(self, args, loglevel=logging... | stack_v2_sparse_classes_36k_train_006955 | 7,985 | permissive | [
{
"docstring": "!Create a new DBNAlert object that can be used to send an alert later on. @param args The arguments to dbn_alert. @param alert_exe The dbn_alert executable name. @param loglevel A Python logging level to log messages before each alert.",
"name": "__init__",
"signature": "def __init__(sel... | 2 | null | Implement the Python class `DBNAlert` described below.
Class description:
!This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions.
Method si... | Implement the Python class `DBNAlert` described below.
Class description:
!This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions.
Method si... | a666ac3b58d19f04249f76c9340f2e4a4a27939b | <|skeleton|>
class DBNAlert:
"""!This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions."""
def __init__(self, args, loglevel=logging... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBNAlert:
"""!This class represents a call to dbn_alert, as a callable Python object. It allows the instructions on how to make the call to be stored for later use by a produtil.datastore.Product object's add_callback and call_callbacks functions."""
def __init__(self, args, loglevel=logging.WARNING, ale... | the_stack_v2_python_sparse | produtil/dbnalert.py | dtcenter/METplus | train | 41 |
b10d3963c8fb2eac58867ca1e1be402822072b2e | [
"if offset is None:\n return default_value\noffset = to_int(offset, 'offset')\nif offset < 0:\n raise ParamValueError(\"'offset' should be greater than or equal to 0.\")\nreturn offset",
"if limit is None:\n return default_value\nlimit = to_int(limit, 'limit')\nif limit < min_value or limit > max_value:\... | <|body_start_0|>
if offset is None:
return default_value
offset = to_int(offset, 'offset')
if offset < 0:
raise ParamValueError("'offset' should be greater than or equal to 0.")
return offset
<|end_body_0|>
<|body_start_1|>
if limit is None:
r... | Validation class, define all check methods. | Validation | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Validation:
"""Validation class, define all check methods."""
def check_offset(cls, offset, default_value=0):
"""Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number or int. default_value (int): Default value for checked of... | stack_v2_sparse_classes_36k_train_006956 | 3,530 | permissive | [
{
"docstring": "Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number or int. default_value (int): Default value for checked offset. Default: 0. Returns: int, offset.",
"name": "check_offset",
"signature": "def check_offset(cls, offset, default... | 4 | stack_v2_sparse_classes_30k_val_000183 | Implement the Python class `Validation` described below.
Class description:
Validation class, define all check methods.
Method signatures and docstrings:
- def check_offset(cls, offset, default_value=0): Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number ... | Implement the Python class `Validation` described below.
Class description:
Validation class, define all check methods.
Method signatures and docstrings:
- def check_offset(cls, offset, default_value=0): Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number ... | a774d893fb2f21dbc3edb5cd89f9e6eec274ebf1 | <|skeleton|>
class Validation:
"""Validation class, define all check methods."""
def check_offset(cls, offset, default_value=0):
"""Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number or int. default_value (int): Default value for checked of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Validation:
"""Validation class, define all check methods."""
def check_offset(cls, offset, default_value=0):
"""Check offset parameter, it must be greater or equal 0. Args: offset (Union[str, int]): Value can be string number or int. default_value (int): Default value for checked offset. Default... | the_stack_v2_python_sparse | mindinsight/datavisual/common/validation.py | mindspore-ai/mindinsight | train | 224 |
2bded521623eeadd44782c60eb6f71cab9a16988 | [
"self.enterTuangou(self.s_name)\nself.swipe_to_down(1)\nsleep(2)\nself.assertTrue(self.check_icon(self.s_name))",
"self.enterTuangou(self.s_name)\nself.swipe_to_down(1)\nself.enter_fist_goods_datil_page(self.s_name)\ns_goods_title = self.setCollected(self.s_name)\nself.press_back_by_keycode()\nself.press_back()\n... | <|body_start_0|>
self.enterTuangou(self.s_name)
self.swipe_to_down(1)
sleep(2)
self.assertTrue(self.check_icon(self.s_name))
<|end_body_0|>
<|body_start_1|>
self.enterTuangou(self.s_name)
self.swipe_to_down(1)
self.enter_fist_goods_datil_page(self.s_name)
... | TChouJiang | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TChouJiang:
def test_goods_icon(self):
"""抽奖团_团购标签验证"""
<|body_0|>
def test_collect(self):
"""抽奖团_收藏功能"""
<|body_1|>
def test_customer_service(self):
"""抽奖团_发送客服消息验证"""
<|body_2|>
def test_t_separately_buy(self):
"""抽奖团_马上抢_单... | stack_v2_sparse_classes_36k_train_006957 | 2,715 | no_license | [
{
"docstring": "抽奖团_团购标签验证",
"name": "test_goods_icon",
"signature": "def test_goods_icon(self)"
},
{
"docstring": "抽奖团_收藏功能",
"name": "test_collect",
"signature": "def test_collect(self)"
},
{
"docstring": "抽奖团_发送客服消息验证",
"name": "test_customer_service",
"signature": "de... | 6 | null | Implement the Python class `TChouJiang` described below.
Class description:
Implement the TChouJiang class.
Method signatures and docstrings:
- def test_goods_icon(self): 抽奖团_团购标签验证
- def test_collect(self): 抽奖团_收藏功能
- def test_customer_service(self): 抽奖团_发送客服消息验证
- def test_t_separately_buy(self): 抽奖团_马上抢_单独购买
- def... | Implement the Python class `TChouJiang` described below.
Class description:
Implement the TChouJiang class.
Method signatures and docstrings:
- def test_goods_icon(self): 抽奖团_团购标签验证
- def test_collect(self): 抽奖团_收藏功能
- def test_customer_service(self): 抽奖团_发送客服消息验证
- def test_t_separately_buy(self): 抽奖团_马上抢_单独购买
- def... | b2066139eb0723eff69d971589b283b4b776c84c | <|skeleton|>
class TChouJiang:
def test_goods_icon(self):
"""抽奖团_团购标签验证"""
<|body_0|>
def test_collect(self):
"""抽奖团_收藏功能"""
<|body_1|>
def test_customer_service(self):
"""抽奖团_发送客服消息验证"""
<|body_2|>
def test_t_separately_buy(self):
"""抽奖团_马上抢_单... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TChouJiang:
def test_goods_icon(self):
"""抽奖团_团购标签验证"""
self.enterTuangou(self.s_name)
self.swipe_to_down(1)
sleep(2)
self.assertTrue(self.check_icon(self.s_name))
def test_collect(self):
"""抽奖团_收藏功能"""
self.enterTuangou(self.s_name)
self.sw... | the_stack_v2_python_sparse | TestCase/4_5/TC_tuan_gou/test_chou_jiang.py | testerSunshine/auto_md | train | 4 | |
377161134525ffa0d72a7e3fcc0b345c66006f9a | [
"setup_metrics = {tuple(m.path): m.id for m in metrics if m.metric in {'SLA | JITTER', 'SLA | UDP RTT'}}\nv = self.cli('show ip sla statistics')\nmetric_map = {'ipsla operation id': 'name', 'latest rtt': 'rtt', 'source to destination jitter min/avg/max': 'sd_jitter', 'destination to source jitter min/avg/max': 'ds_... | <|body_start_0|>
setup_metrics = {tuple(m.path): m.id for m in metrics if m.metric in {'SLA | JITTER', 'SLA | UDP RTT'}}
v = self.cli('show ip sla statistics')
metric_map = {'ipsla operation id': 'name', 'latest rtt': 'rtt', 'source to destination jitter min/avg/max': 'sd_jitter', 'destination t... | Script | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Script:
def get_ip_sla_udp_jitter_metrics_cli(self, metrics):
"""Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:"""
<|body_0|>
def get_ip_sla_icmp_echo_metrics_cli(self, metrics):
"""Returns collected ip sla metrics in form probe... | stack_v2_sparse_classes_36k_train_006958 | 6,963 | permissive | [
{
"docstring": "Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:",
"name": "get_ip_sla_udp_jitter_metrics_cli",
"signature": "def get_ip_sla_udp_jitter_metrics_cli(self, metrics)"
},
{
"docstring": "Returns collected ip sla metrics in form probe id -> { rtt: ... | 3 | stack_v2_sparse_classes_30k_train_015471 | Implement the Python class `Script` described below.
Class description:
Implement the Script class.
Method signatures and docstrings:
- def get_ip_sla_udp_jitter_metrics_cli(self, metrics): Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:
- def get_ip_sla_icmp_echo_metrics_cli(sel... | Implement the Python class `Script` described below.
Class description:
Implement the Script class.
Method signatures and docstrings:
- def get_ip_sla_udp_jitter_metrics_cli(self, metrics): Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:
- def get_ip_sla_icmp_echo_metrics_cli(sel... | aba08dc328296bb0e8e181c2ac9a766e1ec2a0bb | <|skeleton|>
class Script:
def get_ip_sla_udp_jitter_metrics_cli(self, metrics):
"""Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:"""
<|body_0|>
def get_ip_sla_icmp_echo_metrics_cli(self, metrics):
"""Returns collected ip sla metrics in form probe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Script:
def get_ip_sla_udp_jitter_metrics_cli(self, metrics):
"""Returns collected ip sla metrics in form probe id -> { rtt: RTT in seconds } :return:"""
setup_metrics = {tuple(m.path): m.id for m in metrics if m.metric in {'SLA | JITTER', 'SLA | UDP RTT'}}
v = self.cli('show ip sla st... | the_stack_v2_python_sparse | sa/profiles/Cisco/IOS/get_metrics.py | ewwwcha/noc | train | 1 | |
1ded29b013b3c8fc349828d6d63c7b41d569efb8 | [
"super(RandAugmentation, self).__init__(n_level)\nself.n_select = n_select\nself.level = level if type(level) is int and 0 <= level < n_level else None\nself.transforms = transforms",
"chosen_transforms = random.sample(self.transforms, k=self.n_select)\nfor transf in chosen_transforms:\n level = self.level if ... | <|body_start_0|>
super(RandAugmentation, self).__init__(n_level)
self.n_select = n_select
self.level = level if type(level) is int and 0 <= level < n_level else None
self.transforms = transforms
<|end_body_0|>
<|body_start_1|>
chosen_transforms = random.sample(self.transforms, k... | Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719) | RandAugmentation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandAugmentation:
"""Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719)"""
def __init__(self, transforms: List[str], n_select: int=2, level: int=14, n_level: int=31) -> None:
"""Init... | stack_v2_sparse_classes_36k_train_006959 | 5,467 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, transforms: List[str], n_select: int=2, level: int=14, n_level: int=31) -> None"
},
{
"docstring": "Run augmentations.",
"name": "__call__",
"signature": "def __call__(self, img: Image) -> Image"
}
] | 2 | stack_v2_sparse_classes_30k_train_002295 | Implement the Python class `RandAugmentation` described below.
Class description:
Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719)
Method signatures and docstrings:
- def __init__(self, transforms: List[str], n_sel... | Implement the Python class `RandAugmentation` described below.
Class description:
Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719)
Method signatures and docstrings:
- def __init__(self, transforms: List[str], n_sel... | 88bcff70e93dd68058a5cf0dfeac119a57abc6de | <|skeleton|>
class RandAugmentation:
"""Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719)"""
def __init__(self, transforms: List[str], n_select: int=2, level: int=14, n_level: int=31) -> None:
"""Init... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandAugmentation:
"""Random augmentation class. References: RandAugment: Practical automated data augmentation with a reduced search space (https://arxiv.org/abs/1909.13719)"""
def __init__(self, transforms: List[str], n_select: int=2, level: int=14, n_level: int=31) -> None:
"""Initialize."""
... | the_stack_v2_python_sparse | src/augmentation/methods.py | scott-mao/DenseDepth_Pruning | train | 1 |
95f9b969aee21bb81b0eaf331167cfe9bbd34143 | [
"for stack in self.stacks:\n if stack.stack_id == stack_id:\n return stack",
"def should_show_stack(stack):\n \"\"\"\n Determines if a stack should be shown for the list response.\n \"\"\"\n if stack.is_deleted() and (not show_deleted):\n return False\n for tag in t... | <|body_start_0|>
for stack in self.stacks:
if stack.stack_id == stack_id:
return stack
<|end_body_0|>
<|body_start_1|>
def should_show_stack(stack):
"""
Determines if a stack should be shown for the list response.
"""
... | A collection of :obj:`Stack` objects for a region. | RegionalStackCollection | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegionalStackCollection:
"""A collection of :obj:`Stack` objects for a region."""
def stack_by_id(self, stack_id):
"""Retrieves a stack by its ID"""
<|body_0|>
def request_list(self, absolutize_url, show_deleted=False, tags=[]):
"""Tries a stack list operation.""... | stack_v2_sparse_classes_36k_train_006960 | 9,838 | permissive | [
{
"docstring": "Retrieves a stack by its ID",
"name": "stack_by_id",
"signature": "def stack_by_id(self, stack_id)"
},
{
"docstring": "Tries a stack list operation.",
"name": "request_list",
"signature": "def request_list(self, absolutize_url, show_deleted=False, tags=[])"
},
{
"... | 6 | stack_v2_sparse_classes_30k_val_000241 | Implement the Python class `RegionalStackCollection` described below.
Class description:
A collection of :obj:`Stack` objects for a region.
Method signatures and docstrings:
- def stack_by_id(self, stack_id): Retrieves a stack by its ID
- def request_list(self, absolutize_url, show_deleted=False, tags=[]): Tries a st... | Implement the Python class `RegionalStackCollection` described below.
Class description:
A collection of :obj:`Stack` objects for a region.
Method signatures and docstrings:
- def stack_by_id(self, stack_id): Retrieves a stack by its ID
- def request_list(self, absolutize_url, show_deleted=False, tags=[]): Tries a st... | 8e7eeed84ec5ae97863f9330023298845623c639 | <|skeleton|>
class RegionalStackCollection:
"""A collection of :obj:`Stack` objects for a region."""
def stack_by_id(self, stack_id):
"""Retrieves a stack by its ID"""
<|body_0|>
def request_list(self, absolutize_url, show_deleted=False, tags=[]):
"""Tries a stack list operation.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegionalStackCollection:
"""A collection of :obj:`Stack` objects for a region."""
def stack_by_id(self, stack_id):
"""Retrieves a stack by its ID"""
for stack in self.stacks:
if stack.stack_id == stack_id:
return stack
def request_list(self, absolutize_url... | the_stack_v2_python_sparse | mimic/model/heat_objects.py | ranjithpeddi/mimic | train | 1 |
45c4d00461ec47be9a1da524403dc99dcfb9bf8f | [
"if isinstance(pyobj, ExtensionTypeSpec):\n try:\n type_spec_registry.get_name(type(pyobj))\n return True\n except ValueError:\n return False\nreturn False",
"type_spec_class_name = type_spec_registry.get_name(type(extension_type_spec_value))\ntype_state = extension_type_spec_value._ser... | <|body_start_0|>
if isinstance(pyobj, ExtensionTypeSpec):
try:
type_spec_registry.get_name(type(pyobj))
return True
except ValueError:
return False
return False
<|end_body_0|>
<|body_start_1|>
type_spec_class_name = type_sp... | Codec for `tf.ExtensionTypeSpec`. | _ExtensionTypeSpecCodec | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ExtensionTypeSpecCodec:
"""Codec for `tf.ExtensionTypeSpec`."""
def can_encode(self, pyobj):
"""Returns true if `pyobj` can be encoded as an ExtensionTypeSpec."""
<|body_0|>
def do_encode(self, extension_type_spec_value, encode_fn):
"""Returns an encoded proto f... | stack_v2_sparse_classes_36k_train_006961 | 47,654 | permissive | [
{
"docstring": "Returns true if `pyobj` can be encoded as an ExtensionTypeSpec.",
"name": "can_encode",
"signature": "def can_encode(self, pyobj)"
},
{
"docstring": "Returns an encoded proto for the given `tf.ExtensionTypeSpec`.",
"name": "do_encode",
"signature": "def do_encode(self, ex... | 4 | null | Implement the Python class `_ExtensionTypeSpecCodec` described below.
Class description:
Codec for `tf.ExtensionTypeSpec`.
Method signatures and docstrings:
- def can_encode(self, pyobj): Returns true if `pyobj` can be encoded as an ExtensionTypeSpec.
- def do_encode(self, extension_type_spec_value, encode_fn): Retur... | Implement the Python class `_ExtensionTypeSpecCodec` described below.
Class description:
Codec for `tf.ExtensionTypeSpec`.
Method signatures and docstrings:
- def can_encode(self, pyobj): Returns true if `pyobj` can be encoded as an ExtensionTypeSpec.
- def do_encode(self, extension_type_spec_value, encode_fn): Retur... | a7f3934a67900720af3d3b15389551483bee50b8 | <|skeleton|>
class _ExtensionTypeSpecCodec:
"""Codec for `tf.ExtensionTypeSpec`."""
def can_encode(self, pyobj):
"""Returns true if `pyobj` can be encoded as an ExtensionTypeSpec."""
<|body_0|>
def do_encode(self, extension_type_spec_value, encode_fn):
"""Returns an encoded proto f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _ExtensionTypeSpecCodec:
"""Codec for `tf.ExtensionTypeSpec`."""
def can_encode(self, pyobj):
"""Returns true if `pyobj` can be encoded as an ExtensionTypeSpec."""
if isinstance(pyobj, ExtensionTypeSpec):
try:
type_spec_registry.get_name(type(pyobj))
... | the_stack_v2_python_sparse | tensorflow/python/framework/extension_type.py | tensorflow/tensorflow | train | 208,740 |
cbf8502b9e1a3143f2d77e621480380a6ea0e042 | [
"self.call_id = call_id\nself.parent_call_id = parent_call_id\nself.application_id = application_id\nself.account_id = account_id\nself.to = to\nself.mfrom = mfrom\nself.direction = direction\nself.state = state\nself.identity = identity\nself.stir_shaken = stir_shaken\nself.start_time = APIHelper.RFC3339DateTime(s... | <|body_start_0|>
self.call_id = call_id
self.parent_call_id = parent_call_id
self.application_id = application_id
self.account_id = account_id
self.to = to
self.mfrom = mfrom
self.direction = direction
self.state = state
self.identity = identity
... | Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. account_id (string): TODO: type description here. to (string): TODO: type des... | CallState | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CallState:
"""Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. account_id (string): TODO: type descript... | stack_v2_sparse_classes_36k_train_006962 | 6,933 | permissive | [
{
"docstring": "Constructor for the CallState class",
"name": "__init__",
"signature": "def __init__(self, call_id=None, parent_call_id=None, application_id=None, account_id=None, to=None, mfrom=None, direction=None, state=None, identity=None, stir_shaken=None, start_time=None, enqueued_time=None, answe... | 2 | stack_v2_sparse_classes_30k_train_013104 | Implement the Python class `CallState` described below.
Class description:
Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. a... | Implement the Python class `CallState` described below.
Class description:
Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. a... | 447df3cc8cb7acaf3361d842630c432a9c31ce6e | <|skeleton|>
class CallState:
"""Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. account_id (string): TODO: type descript... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CallState:
"""Implementation of the 'CallState' model. TODO: type model description here. Attributes: call_id (string): TODO: type description here. parent_call_id (string): TODO: type description here. application_id (string): TODO: type description here. account_id (string): TODO: type description here. to ... | the_stack_v2_python_sparse | bandwidth/voice/models/call_state.py | Bandwidth/python-sdk | train | 10 |
df31b4139442de6803187c49752cc1f09bca6b39 | [
"inputs = [x.strip('[]\"\\n') for x in sys_stdin]\na = [self.cast(x) for x in inputs[0].split(',')]\no = TreeNode().convert(a)\nx = int(inputs[1])\nreturn (o, x)",
"if x.lower() == 'null':\n return None\nelse:\n return int(x)"
] | <|body_start_0|>
inputs = [x.strip('[]"\n') for x in sys_stdin]
a = [self.cast(x) for x in inputs[0].split(',')]
o = TreeNode().convert(a)
x = int(inputs[1])
return (o, x)
<|end_body_0|>
<|body_start_1|>
if x.lower() == 'null':
return None
else:
... | Input | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Input:
def stdin(self, sys_stdin):
"""Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object"""
<|body_0|>
def cast(self, x):
"""Converts string values to integer or None values. :param str... | stack_v2_sparse_classes_36k_train_006963 | 2,708 | permissive | [
{
"docstring": "Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object",
"name": "stdin",
"signature": "def stdin(self, sys_stdin)"
},
{
"docstring": "Converts string values to integer or None values. :param str x: str... | 2 | stack_v2_sparse_classes_30k_train_013099 | Implement the Python class `Input` described below.
Class description:
Implement the Input class.
Method signatures and docstrings:
- def stdin(self, sys_stdin): Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object
- def cast(self, x): Co... | Implement the Python class `Input` described below.
Class description:
Implement the Input class.
Method signatures and docstrings:
- def stdin(self, sys_stdin): Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object
- def cast(self, x): Co... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Input:
def stdin(self, sys_stdin):
"""Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object"""
<|body_0|>
def cast(self, x):
"""Converts string values to integer or None values. :param str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Input:
def stdin(self, sys_stdin):
"""Imports standard input. :param _io.TextIOWrapper sys_stdin: standard input :return: root node of binary tree :rtype: TreeNode object"""
inputs = [x.strip('[]"\n') for x in sys_stdin]
a = [self.cast(x) for x in inputs[0].split(',')]
o = Tree... | the_stack_v2_python_sparse | 0701_insert_into_binary_search_tree/python_source.py | arthurdysart/LeetCode | train | 0 | |
daaedc4d37aed9872e8e607cea152120df431497 | [
"super(ResBlk, self).__init__()\nself.conv1 = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=stride, padding=1)\nself.bn1 = nn.BatchNorm2d(ch_out)\nself.conv2 = nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1)\nself.bn2 = nn.BatchNorm2d(ch_out)\nself.extra = nn.Sequential()\nif ch_out != ch_in:\n se... | <|body_start_0|>
super(ResBlk, self).__init__()
self.conv1 = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=stride, padding=1)
self.bn1 = nn.BatchNorm2d(ch_out)
self.conv2 = nn.Conv2d(ch_out, ch_out, kernel_size=3, stride=1, padding=1)
self.bn2 = nn.BatchNorm2d(ch_out)
se... | resnet block | ResBlk | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResBlk:
"""resnet block"""
def __init__(self, ch_in, ch_out, stride=1):
""":param ch_in: :param ch_out:"""
<|body_0|>
def forward(self, x):
""":param x: [b, ch, h, w] :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(ResBlk, self)._... | stack_v2_sparse_classes_36k_train_006964 | 12,300 | no_license | [
{
"docstring": ":param ch_in: :param ch_out:",
"name": "__init__",
"signature": "def __init__(self, ch_in, ch_out, stride=1)"
},
{
"docstring": ":param x: [b, ch, h, w] :return:",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009158 | Implement the Python class `ResBlk` described below.
Class description:
resnet block
Method signatures and docstrings:
- def __init__(self, ch_in, ch_out, stride=1): :param ch_in: :param ch_out:
- def forward(self, x): :param x: [b, ch, h, w] :return: | Implement the Python class `ResBlk` described below.
Class description:
resnet block
Method signatures and docstrings:
- def __init__(self, ch_in, ch_out, stride=1): :param ch_in: :param ch_out:
- def forward(self, x): :param x: [b, ch, h, w] :return:
<|skeleton|>
class ResBlk:
"""resnet block"""
def __init... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class ResBlk:
"""resnet block"""
def __init__(self, ch_in, ch_out, stride=1):
""":param ch_in: :param ch_out:"""
<|body_0|>
def forward(self, x):
""":param x: [b, ch, h, w] :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResBlk:
"""resnet block"""
def __init__(self, ch_in, ch_out, stride=1):
""":param ch_in: :param ch_out:"""
super(ResBlk, self).__init__()
self.conv1 = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=stride, padding=1)
self.bn1 = nn.BatchNorm2d(ch_out)
self.conv2 = n... | the_stack_v2_python_sparse | generated/test_dragen1860_Deep_Learning_with_PyTorch_Tutorials.py | jansel/pytorch-jit-paritybench | train | 35 |
310eecd649e9b3909db063c80c7401b7109c2d4c | [
"with self._open(self.app.page_admin_volumes) as page:\n page.label_volume_types.click()\n return page.tab_volume_types",
"volume_type_name = volume_type_name or next(utils.generate_ids('volume-type'))\ntab = self._tab_volume_types()\ntab.button_create_volume_type.click()\nwith tab.form_create_volume_type a... | <|body_start_0|>
with self._open(self.app.page_admin_volumes) as page:
page.label_volume_types.click()
return page.tab_volume_types
<|end_body_0|>
<|body_start_1|>
volume_type_name = volume_type_name or next(utils.generate_ids('volume-type'))
tab = self._tab_volume_types... | Volume types steps. | VolumeTypesSteps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VolumeTypesSteps:
"""Volume types steps."""
def _tab_volume_types(self):
"""Open volume types tab."""
<|body_0|>
def create_volume_type(self, volume_type_name=None, description=None, check=True):
"""Step to create volume type."""
<|body_1|>
def delet... | stack_v2_sparse_classes_36k_train_006965 | 4,174 | no_license | [
{
"docstring": "Open volume types tab.",
"name": "_tab_volume_types",
"signature": "def _tab_volume_types(self)"
},
{
"docstring": "Step to create volume type.",
"name": "create_volume_type",
"signature": "def create_volume_type(self, volume_type_name=None, description=None, check=True)"... | 6 | null | Implement the Python class `VolumeTypesSteps` described below.
Class description:
Volume types steps.
Method signatures and docstrings:
- def _tab_volume_types(self): Open volume types tab.
- def create_volume_type(self, volume_type_name=None, description=None, check=True): Step to create volume type.
- def delete_vo... | Implement the Python class `VolumeTypesSteps` described below.
Class description:
Volume types steps.
Method signatures and docstrings:
- def _tab_volume_types(self): Open volume types tab.
- def create_volume_type(self, volume_type_name=None, description=None, check=True): Step to create volume type.
- def delete_vo... | e7583444cd24893ec6ae237b47db7c605b99b0c5 | <|skeleton|>
class VolumeTypesSteps:
"""Volume types steps."""
def _tab_volume_types(self):
"""Open volume types tab."""
<|body_0|>
def create_volume_type(self, volume_type_name=None, description=None, check=True):
"""Step to create volume type."""
<|body_1|>
def delet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VolumeTypesSteps:
"""Volume types steps."""
def _tab_volume_types(self):
"""Open volume types tab."""
with self._open(self.app.page_admin_volumes) as page:
page.label_volume_types.click()
return page.tab_volume_types
def create_volume_type(self, volume_type_na... | the_stack_v2_python_sparse | stepler/horizon/steps/volume_types.py | Mirantis/stepler | train | 16 |
d5cbcbbe9e3d5bf07c20e2db882169758e3effa3 | [
"super(Receiver, self).__init__()\nself.daemon = False\nself.q_of_samples = multiprocessing.Queue()\nself.server = cb.get_collectd_server(self.q_of_samples)\nself.control = control\nself.pd_dict = pd_dict\nself.collectd_cpu_keys = settings.getValue('COLLECTD_CPU_KEYS')\nself.collectd_processes_keys = settings.getVa... | <|body_start_0|>
super(Receiver, self).__init__()
self.daemon = False
self.q_of_samples = multiprocessing.Queue()
self.server = cb.get_collectd_server(self.q_of_samples)
self.control = control
self.pd_dict = pd_dict
self.collectd_cpu_keys = settings.getValue('COLL... | Wrapper Receiver (of samples) class | Receiver | [
"CC-BY-4.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Receiver:
"""Wrapper Receiver (of samples) class"""
def __init__(self, pd_dict, control):
"""Initialize. A queue will be shared with collectd_bucky"""
<|body_0|>
def run(self):
"""Start receiving the samples."""
<|body_1|>
def handle(self, sample):
... | stack_v2_sparse_classes_36k_train_006966 | 10,808 | permissive | [
{
"docstring": "Initialize. A queue will be shared with collectd_bucky",
"name": "__init__",
"signature": "def __init__(self, pd_dict, control)"
},
{
"docstring": "Start receiving the samples.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Store values and names... | 4 | stack_v2_sparse_classes_30k_train_005533 | Implement the Python class `Receiver` described below.
Class description:
Wrapper Receiver (of samples) class
Method signatures and docstrings:
- def __init__(self, pd_dict, control): Initialize. A queue will be shared with collectd_bucky
- def run(self): Start receiving the samples.
- def handle(self, sample): Store... | Implement the Python class `Receiver` described below.
Class description:
Wrapper Receiver (of samples) class
Method signatures and docstrings:
- def __init__(self, pd_dict, control): Initialize. A queue will be shared with collectd_bucky
- def run(self): Start receiving the samples.
- def handle(self, sample): Store... | d5c0a03054f720da2a5ff9eba74feee57fb0296d | <|skeleton|>
class Receiver:
"""Wrapper Receiver (of samples) class"""
def __init__(self, pd_dict, control):
"""Initialize. A queue will be shared with collectd_bucky"""
<|body_0|>
def run(self):
"""Start receiving the samples."""
<|body_1|>
def handle(self, sample):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Receiver:
"""Wrapper Receiver (of samples) class"""
def __init__(self, pd_dict, control):
"""Initialize. A queue will be shared with collectd_bucky"""
super(Receiver, self).__init__()
self.daemon = False
self.q_of_samples = multiprocessing.Queue()
self.server = cb.... | the_stack_v2_python_sparse | tools/collectors/collectd/collectd.py | shreyagupta30/vineperf | train | 0 |
c6ad1c04d916a201667100e784f85e131198c646 | [
"self.id = id\nself.code = code\nself.url = url\nself.amount = amount\nself.status = status\nself.payment_method = payment_method\nself.created_at = APIHelper.RFC3339DateTime(created_at) if created_at else None\nself.items = items\nself.customer = customer\nself.charge = charge\nself.installments = installments\nse... | <|body_start_0|>
self.id = id
self.code = code
self.url = url
self.amount = amount
self.status = status
self.payment_method = payment_method
self.created_at = APIHelper.RFC3339DateTime(created_at) if created_at else None
self.items = items
self.cus... | Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amount (int): TODO: type description here. status (string): TODO: type description here. p... | GetInvoiceResponse | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetInvoiceResponse:
"""Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amount (int): TODO: type description here. s... | stack_v2_sparse_classes_36k_train_006967 | 8,566 | permissive | [
{
"docstring": "Constructor for the GetInvoiceResponse class",
"name": "__init__",
"signature": "def __init__(self, id=None, code=None, url=None, amount=None, status=None, payment_method=None, created_at=None, items=None, charge=None, installments=None, billing_address=None, subscription=None, shipping=... | 2 | stack_v2_sparse_classes_30k_train_019002 | Implement the Python class `GetInvoiceResponse` described below.
Class description:
Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amoun... | Implement the Python class `GetInvoiceResponse` described below.
Class description:
Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amoun... | 95c80c35dd57bb2a238faeaf30d1e3b4544d2298 | <|skeleton|>
class GetInvoiceResponse:
"""Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amount (int): TODO: type description here. s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetInvoiceResponse:
"""Implementation of the 'GetInvoiceResponse' model. Response object for getting an invoice Attributes: id (string): TODO: type description here. code (string): TODO: type description here. url (string): TODO: type description here. amount (int): TODO: type description here. status (string... | the_stack_v2_python_sparse | mundiapi/models/get_invoice_response.py | mundipagg/MundiAPI-PYTHON | train | 10 |
1ff92a7ab1f22fe13306882ca5f7168607fc4d4b | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | TestServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Get(self, request, context):
"""Returns test by test id."""
<|body_0|>
def Create(self, request, context):
"""Creates test for the specified folder."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_006968 | 6,647 | permissive | [
{
"docstring": "Returns test by test id.",
"name": "Get",
"signature": "def Get(self, request, context)"
},
{
"docstring": "Creates test for the specified folder.",
"name": "Create",
"signature": "def Create(self, request, context)"
},
{
"docstring": "Updates the specified test."... | 3 | null | Implement the Python class `TestServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Get(self, request, context): Returns test by test id.
- def Create(self, request, context): Creates test for the specified folder.
- def... | Implement the Python class `TestServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def Get(self, request, context): Returns test by test id.
- def Create(self, request, context): Creates test for the specified folder.
- def... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class TestServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Get(self, request, context):
"""Returns test by test id."""
<|body_0|>
def Create(self, request, context):
"""Creates test for the specified folder."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestServiceServicer:
"""Missing associated documentation comment in .proto file."""
def Get(self, request, context):
"""Returns test by test id."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Met... | the_stack_v2_python_sparse | yandex/cloud/loadtesting/agent/v1/test_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
2713c7fe674a209ade5ed49a86832860ffe54892 | [
"self.LOGS = settings.logger\nself.dataset = settings.dataset\nself.LOGS.info('DATASET: Instantiating Dataset object')\nmodule = self._load_module(settings, client)\nremote_check = core.get_date(module.url)\nif self.dataset in settings.modules.keys() and remote_check > settings.modules[self.dataset]:\n msg = 'Re... | <|body_start_0|>
self.LOGS = settings.logger
self.dataset = settings.dataset
self.LOGS.info('DATASET: Instantiating Dataset object')
module = self._load_module(settings, client)
remote_check = core.get_date(module.url)
if self.dataset in settings.modules.keys() and remote... | Class to retrieve the required DHTK extension (dataset) module | ExtensionLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client:... | stack_v2_sparse_classes_36k_train_006969 | 3,777 | no_license | [
{
"docstring": "Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client: DHTK Client object Client to use Returns ------- Extension module selected by the user as the .module attribute",
"name": "__init__",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_003919 | Implement the Python class `ExtensionLoader` described below.
Class description:
Class to retrieve the required DHTK extension (dataset) module
Method signatures and docstrings:
- def __init__(self, settings: object, client: object): Method to retrieve the required the DHTK extension module. Parameters ---------- set... | Implement the Python class `ExtensionLoader` described below.
Class description:
Class to retrieve the required DHTK extension (dataset) module
Method signatures and docstrings:
- def __init__(self, settings: object, client: object): Method to retrieve the required the DHTK extension module. Parameters ---------- set... | 54d9104c8b04af0fb368a499372d7ea0337be3d2 | <|skeleton|>
class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExtensionLoader:
"""Class to retrieve the required DHTK extension (dataset) module"""
def __init__(self, settings: object, client: object):
"""Method to retrieve the required the DHTK extension module. Parameters ---------- settings: DHTK Settings object Configurations to use client: DHTK Client ... | the_stack_v2_python_sparse | venv/Lib/site-packages/dhtk/core/loader.py | sorchawalsh/semanticweb | train | 0 |
f89e484418655cc89e679b16aca9507abc8664e7 | [
"if netcdf_filepath[-3:] == '.nc':\n filename_stem = netcdf_filepath[:-3]\nelse:\n filename_stem = netcdf_filepath\nyear = filename_stem.split('_')[-2][:4]\nif subset_name is not None:\n new_filename = f'{year}_{filename_stem}_{subset_name}.nc'\nelse:\n new_filename = f'{year}_{filename_stem}.nc'\nretur... | <|body_start_0|>
if netcdf_filepath[-3:] == '.nc':
filename_stem = netcdf_filepath[:-3]
else:
filename_stem = netcdf_filepath
year = filename_stem.split('_')[-2][:4]
if subset_name is not None:
new_filename = f'{year}_{filename_stem}_{subset_name}.nc'
... | Preprocesses the ESA CCI Landcover data | NDVIPreprocessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NDVIPreprocessor:
"""Preprocesses the ESA CCI Landcover data"""
def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str:
"""AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548_ken... | stack_v2_sparse_classes_36k_train_006970 | 4,147 | no_license | [
{
"docstring": "AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548_kenya.nc",
"name": "create_filename",
"signature": "def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_007154 | Implement the Python class `NDVIPreprocessor` described below.
Class description:
Preprocesses the ESA CCI Landcover data
Method signatures and docstrings:
- def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str: AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVH... | Implement the Python class `NDVIPreprocessor` described below.
Class description:
Preprocesses the ESA CCI Landcover data
Method signatures and docstrings:
- def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str: AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVH... | 2a39c5c20ed50f3194ebb95aba720e48215c0dfd | <|skeleton|>
class NDVIPreprocessor:
"""Preprocesses the ESA CCI Landcover data"""
def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str:
"""AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548_ken... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NDVIPreprocessor:
"""Preprocesses the ESA CCI Landcover data"""
def create_filename(self, netcdf_filepath: str, subset_name: Optional[str]=None) -> str:
"""AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548.nc => 1986_AVHRR-Land_v005_AVH13C1_NOAA-09_19860702_c20170612095548_kenya.nc"""
... | the_stack_v2_python_sparse | ndvi.py | tommylees112/esowc_notes | train | 3 |
2d4abe0f05bd4838b1e6b4b2796ebb2a9dad22ee | [
"if len(nums) == 0:\n return 0\nD = [0 for _ in nums]\nfor index, num in enumerate(nums):\n if index == 0:\n D[index] = num\n elif index == 1:\n D[index] = max(D[index - 1], num)\n else:\n D[index] = max(D[index - 2] + num, D[index - 1])\nreturn D[-1]",
"if not nums:\n return 0... | <|body_start_0|>
if len(nums) == 0:
return 0
D = [0 for _ in nums]
for index, num in enumerate(nums):
if index == 0:
D[index] = num
elif index == 1:
D[index] = max(D[index - 1], num)
else:
D[index] = ... | 同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题"""
def rob2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rt... | stack_v2_sparse_classes_36k_train_006971 | 1,047 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob2",
"signature": "def rob2(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题
Method signatures and docstrings:
- def rob2(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :typ... | Implement the Python class `Solution` described below.
Class description:
同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题
Method signatures and docstrings:
- def rob2(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :typ... | f563dbf35878808491f03281889c9a0800be7d90 | <|skeleton|>
class Solution:
"""同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题"""
def rob2(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""同 HouseRobber，不过这里的数组是环状的，不允许0和n-1同时出现， 分解成0~n-2 和 1~n-1的问题, 如果不偷0， 那么1~n-1可以随便，退化成HouseRobber问题， 如果偷0，那么n-1肯定不能，退化成 0~n-2问题"""
def rob2(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 0:
return 0
D = [0 for _ in nums]
for inde... | the_stack_v2_python_sparse | leetcode/213.HouseRobber2/main.py | lee3164/newcoder | train | 1 |
5e41b29712a08ee5cb90e11b38b2af610e52deed | [
"inputs = tf.keras.Input(shape=(128,) * rank + (16,), batch_size=1)\nnetwork = conv_endec.UNet(scales=scales, base_filters=base_filters, kernel_size=kernel_size, rank=rank, use_deconv=use_deconv, out_channels=out_channels, use_global_residual=use_global_residual)\nfeatures = network(inputs)\nif out_channels is None... | <|body_start_0|>
inputs = tf.keras.Input(shape=(128,) * rank + (16,), batch_size=1)
network = conv_endec.UNet(scales=scales, base_filters=base_filters, kernel_size=kernel_size, rank=rank, use_deconv=use_deconv, out_channels=out_channels, use_global_residual=use_global_residual)
features = networ... | U-Net tests. | UNetTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UNetTest:
"""U-Net tests."""
def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual):
"""Test object creation."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|... | stack_v2_sparse_classes_36k_train_006972 | 3,132 | permissive | [
{
"docstring": "Test object creation.",
"name": "test_unet_creation",
"signature": "def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual)"
},
{
"docstring": "Test de/serialization.",
"name": "test_serialize_deserialize",
"sig... | 2 | null | Implement the Python class `UNetTest` described below.
Class description:
U-Net tests.
Method signatures and docstrings:
- def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual): Test object creation.
- def test_serialize_deserialize(self): Test de/seriali... | Implement the Python class `UNetTest` described below.
Class description:
U-Net tests.
Method signatures and docstrings:
- def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual): Test object creation.
- def test_serialize_deserialize(self): Test de/seriali... | cfd8930ee5281e7f6dceb17c4a5acaf625fd3243 | <|skeleton|>
class UNetTest:
"""U-Net tests."""
def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual):
"""Test object creation."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UNetTest:
"""U-Net tests."""
def test_unet_creation(self, scales, base_filters, kernel_size, rank, out_channels, use_deconv, use_global_residual):
"""Test object creation."""
inputs = tf.keras.Input(shape=(128,) * rank + (16,), batch_size=1)
network = conv_endec.UNet(scales=scales... | the_stack_v2_python_sparse | tensorflow_mri/python/layers/conv_endec_test.py | mrphys/tensorflow-mri | train | 29 |
4eefe3f2214ed67ab0f3433eaf009ee68aeafb9c | [
"sagemaker_session = sagemaker_session or Session()\nbucket, key_prefix = parse_s3_url(url=s3_uri)\nif kms_key is not None:\n extra_args = {'SSECustomerKey': kms_key}\nelse:\n extra_args = None\nreturn sagemaker_session.download_data(path=local_path, bucket=bucket, key_prefix=key_prefix, extra_args=extra_args... | <|body_start_0|>
sagemaker_session = sagemaker_session or Session()
bucket, key_prefix = parse_s3_url(url=s3_uri)
if kms_key is not None:
extra_args = {'SSECustomerKey': kms_key}
else:
extra_args = None
return sagemaker_session.download_data(path=local_pat... | Contains static methods for downloading directories or files from S3. | S3Downloader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class S3Downloader:
"""Contains static methods for downloading directories or files from S3."""
def download(s3_uri, local_path, kms_key=None, sagemaker_session=None):
"""Static method that downloads a given S3 uri to the local machine. Args: s3_uri (str): An S3 uri to download from. local... | stack_v2_sparse_classes_36k_train_006973 | 8,554 | permissive | [
{
"docstring": "Static method that downloads a given S3 uri to the local machine. Args: s3_uri (str): An S3 uri to download from. local_path (str): A local path to download the file(s) to. kms_key (str): The KMS key to use to decrypt the files. sagemaker_session (sagemaker.session.Session): Session object which... | 4 | null | Implement the Python class `S3Downloader` described below.
Class description:
Contains static methods for downloading directories or files from S3.
Method signatures and docstrings:
- def download(s3_uri, local_path, kms_key=None, sagemaker_session=None): Static method that downloads a given S3 uri to the local machi... | Implement the Python class `S3Downloader` described below.
Class description:
Contains static methods for downloading directories or files from S3.
Method signatures and docstrings:
- def download(s3_uri, local_path, kms_key=None, sagemaker_session=None): Static method that downloads a given S3 uri to the local machi... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class S3Downloader:
"""Contains static methods for downloading directories or files from S3."""
def download(s3_uri, local_path, kms_key=None, sagemaker_session=None):
"""Static method that downloads a given S3 uri to the local machine. Args: s3_uri (str): An S3 uri to download from. local... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class S3Downloader:
"""Contains static methods for downloading directories or files from S3."""
def download(s3_uri, local_path, kms_key=None, sagemaker_session=None):
"""Static method that downloads a given S3 uri to the local machine. Args: s3_uri (str): An S3 uri to download from. local_path (str): ... | the_stack_v2_python_sparse | src/sagemaker/s3.py | aws/sagemaker-python-sdk | train | 2,050 |
56d5e0e35200bf6629d652c3bac6fd3f4f6121d5 | [
"self.data_point_vec = data_point_vec\nself.metric_name = metric_name\nself.mtype = mtype",
"if dictionary is None:\n return None\ndata_point_vec = None\nif dictionary.get('dataPointVec') != None:\n data_point_vec = list()\n for structure in dictionary.get('dataPointVec'):\n data_point_vec.append(... | <|body_start_0|>
self.data_point_vec = data_point_vec
self.metric_name = metric_name
self.mtype = mtype
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
data_point_vec = None
if dictionary.get('dataPointVec') != None:
data_point_... | Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time series. metric_name (string): Specifies the name of a metric such as 'kDiskAwaitTimeMse... | MetricDataBlock | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricDataBlock:
"""Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time series. metric_name (string): Specifies the ... | stack_v2_sparse_classes_36k_train_006974 | 2,460 | permissive | [
{
"docstring": "Constructor for the MetricDataBlock class",
"name": "__init__",
"signature": "def __init__(self, data_point_vec=None, metric_name=None, mtype=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation o... | 2 | stack_v2_sparse_classes_30k_train_010111 | Implement the Python class `MetricDataBlock` described below.
Class description:
Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time serie... | Implement the Python class `MetricDataBlock` described below.
Class description:
Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time serie... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class MetricDataBlock:
"""Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time series. metric_name (string): Specifies the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MetricDataBlock:
"""Implementation of the 'MetricDataBlock' model. Specifies a series of metric data points for a time series. Attributes: data_point_vec (list of MetricDataPoint): Array of Data Points. Specifies a list of metric data points for a time series. metric_name (string): Specifies the name of a met... | the_stack_v2_python_sparse | cohesity_management_sdk/models/metric_data_block.py | cohesity/management-sdk-python | train | 24 |
55b2901645c279e53bb670e00116acf907cccd87 | [
"initial_groups = util.setNoneList(initial_groups)\nsuper(self.__class__, self).__init__(initial_groups=initial_groups)\nif is_set_group_label:\n self.setGroupLabels(prefix=prefix)\nself._is_plot = is_plot",
"num_permute = util.nCr(num_isolates, num_occurrences)\ndenom = num_permute ** num_mutations\nreturn 1.... | <|body_start_0|>
initial_groups = util.setNoneList(initial_groups)
super(self.__class__, self).__init__(initial_groups=initial_groups)
if is_set_group_label:
self.setGroupLabels(prefix=prefix)
self._is_plot = is_plot
<|end_body_0|>
<|body_start_1|>
num_permute = util... | MutationCollection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MutationCollection:
def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True):
"""If no mutation_source is specified, then calculates a default MutationDifferential. :param list-Group initial_groups: :param bool is_plot: plots if True"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_006975 | 4,729 | permissive | [
{
"docstring": "If no mutation_source is specified, then calculates a default MutationDifferential. :param list-Group initial_groups: :param bool is_plot: plots if True",
"name": "__init__",
"signature": "def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True)"
},
{... | 5 | stack_v2_sparse_classes_30k_train_012274 | Implement the Python class `MutationCollection` described below.
Class description:
Implement the MutationCollection class.
Method signatures and docstrings:
- def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True): If no mutation_source is specified, then calculates a default Mutat... | Implement the Python class `MutationCollection` described below.
Class description:
Implement the MutationCollection class.
Method signatures and docstrings:
- def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True): If no mutation_source is specified, then calculates a default Mutat... | 704435e66c58677bab24f27820458870092924e2 | <|skeleton|>
class MutationCollection:
def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True):
"""If no mutation_source is specified, then calculates a default MutationDifferential. :param list-Group initial_groups: :param bool is_plot: plots if True"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MutationCollection:
def __init__(self, initial_groups=None, prefix='', is_set_group_label=True, is_plot=True):
"""If no mutation_source is specified, then calculates a default MutationDifferential. :param list-Group initial_groups: :param bool is_plot: plots if True"""
initial_groups = util.se... | the_stack_v2_python_sparse | microbepy/correlation/mutation_collection.py | ScienceStacks/microbepy | train | 1 | |
654903d1365dc7f97bfbe014e96c70493e0cf09f | [
"if not matrix or not path or rows < 1 or (cols < 1):\n return False\nvisited = [0] * (rows * cols)\npathLength = 0\nfor i in range(rows):\n for j in range(cols):\n if self.hasPathCore(matrix, rows, cols, i, j, path, pathLength, visited):\n return True\nreturn False",
"if len(path) == path... | <|body_start_0|>
if not matrix or not path or rows < 1 or (cols < 1):
return False
visited = [0] * (rows * cols)
pathLength = 0
for i in range(rows):
for j in range(cols):
if self.hasPathCore(matrix, rows, cols, i, j, path, pathLength, visited):
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasPath(self, matrix, rows, cols, path):
""":param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径"""
<|body_0|>
def hasPathCore(self, matrix, rows, cols, i, j, path, pathLength, visited):
"""以格子 （i，j） 开始找路径 path 中的字符 path[path... | stack_v2_sparse_classes_36k_train_006976 | 2,879 | permissive | [
{
"docstring": ":param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径",
"name": "hasPath",
"signature": "def hasPath(self, matrix, rows, cols, path)"
},
{
"docstring": "以格子 （i，j） 开始找路径 path 中的字符 path[pathLength]， 若未找到说明以 （i, j）为起点是找不到路径的，直接退出，以下一个格子为起点找。 若找到了路径中的第一个字符，... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPath(self, matrix, rows, cols, path): :param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径
- def hasPathCore(self, matrix, rows, cols, i, j, pa... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasPath(self, matrix, rows, cols, path): :param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径
- def hasPathCore(self, matrix, rows, cols, i, j, pa... | 889d8fa489f1f2719c5a0dafd3ae51df7b4bf978 | <|skeleton|>
class Solution:
def hasPath(self, matrix, rows, cols, path):
""":param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径"""
<|body_0|>
def hasPathCore(self, matrix, rows, cols, i, j, path, pathLength, visited):
"""以格子 （i，j） 开始找路径 path 中的字符 path[path... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hasPath(self, matrix, rows, cols, path):
""":param matrix: 一个一维数组（题目中的二维矩阵） :param rows: 行 :param cols: 列 :param path: 要找的路径"""
if not matrix or not path or rows < 1 or (cols < 1):
return False
visited = [0] * (rows * cols)
pathLength = 0
for i... | the_stack_v2_python_sparse | 剑指offer/12-矩阵中的路径/12 hasPath.py | jinbooooom/coding-for-algorithms | train | 14 | |
1030b9670235ecefde328f82df820232ca97e0f6 | [
"self.battle = battle\nPygameController.__init__(self, screen)\nself.coroutine = self.performEntireRound()",
"self.screen.setBottomView(None)\nPerformEvents(self.battle.eventQueue, self)\nself.coroutine.send(None)\nif self.battle.over:\n self.stopRunning()",
"while not self.battle.over:\n self.performRoun... | <|body_start_0|>
self.battle = battle
PygameController.__init__(self, screen)
self.coroutine = self.performEntireRound()
<|end_body_0|>
<|body_start_1|>
self.screen.setBottomView(None)
PerformEvents(self.battle.eventQueue, self)
self.coroutine.send(None)
if self.... | Controller for Battle Rounds | BattleRoundController | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BattleRoundController:
"""Controller for Battle Rounds"""
def __init__(self, battle, screen):
"""Initialize the Battle Round Controller"""
<|body_0|>
def performGameCycle(self):
"""Tells the battle object what to perform"""
<|body_1|>
def performEnti... | stack_v2_sparse_classes_36k_train_006977 | 2,442 | no_license | [
{
"docstring": "Initialize the Battle Round Controller",
"name": "__init__",
"signature": "def __init__(self, battle, screen)"
},
{
"docstring": "Tells the battle object what to perform",
"name": "performGameCycle",
"signature": "def performGameCycle(self)"
},
{
"docstring": "Per... | 5 | stack_v2_sparse_classes_30k_train_007329 | Implement the Python class `BattleRoundController` described below.
Class description:
Controller for Battle Rounds
Method signatures and docstrings:
- def __init__(self, battle, screen): Initialize the Battle Round Controller
- def performGameCycle(self): Tells the battle object what to perform
- def performEntireRo... | Implement the Python class `BattleRoundController` described below.
Class description:
Controller for Battle Rounds
Method signatures and docstrings:
- def __init__(self, battle, screen): Initialize the Battle Round Controller
- def performGameCycle(self): Tells the battle object what to perform
- def performEntireRo... | 3931eee5fd04e18bb1738a0b27a4c6979dc4db01 | <|skeleton|>
class BattleRoundController:
"""Controller for Battle Rounds"""
def __init__(self, battle, screen):
"""Initialize the Battle Round Controller"""
<|body_0|>
def performGameCycle(self):
"""Tells the battle object what to perform"""
<|body_1|>
def performEnti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BattleRoundController:
"""Controller for Battle Rounds"""
def __init__(self, battle, screen):
"""Initialize the Battle Round Controller"""
self.battle = battle
PygameController.__init__(self, screen)
self.coroutine = self.performEntireRound()
def performGameCycle(self... | the_stack_v2_python_sparse | src/Screen/Pygame/Battle/battle_round_controller.py | sgtnourry/Pokemon-Project | train | 0 |
bd292910056a20d98d07e88d59c6246ec78d3ab8 | [
"args = self.parser.parse_args()\ndata = self.build_data(args=args, collection='task')\nreturn data",
"args = self.parse_args(add_task_fields)\nname = args.pop('name')\ntarget = args.pop('target')\ntry:\n task_data_list = submit_task_task(target=target, name=name, options=args)\nexcept Exception as e:\n log... | <|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='task')
return data
<|end_body_0|>
<|body_start_1|>
args = self.parse_args(add_task_fields)
name = args.pop('name')
target = args.pop('target')
try:
task_dat... | ARLTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARLTask:
def get(self):
"""任务信息查询"""
<|body_0|>
def post(self):
"""任务提交"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = self.parser.parse_args()
data = self.build_data(args=args, collection='task')
return data
<|end_body_0|>
... | stack_v2_sparse_classes_36k_train_006978 | 14,992 | no_license | [
{
"docstring": "任务信息查询",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "任务提交",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021223 | Implement the Python class `ARLTask` described below.
Class description:
Implement the ARLTask class.
Method signatures and docstrings:
- def get(self): 任务信息查询
- def post(self): 任务提交 | Implement the Python class `ARLTask` described below.
Class description:
Implement the ARLTask class.
Method signatures and docstrings:
- def get(self): 任务信息查询
- def post(self): 任务提交
<|skeleton|>
class ARLTask:
def get(self):
"""任务信息查询"""
<|body_0|>
def post(self):
"""任务提交"""
... | 5ca64806252b9e7e6d2b31a6bfaeecbfdc4baf06 | <|skeleton|>
class ARLTask:
def get(self):
"""任务信息查询"""
<|body_0|>
def post(self):
"""任务提交"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ARLTask:
def get(self):
"""任务信息查询"""
args = self.parser.parse_args()
data = self.build_data(args=args, collection='task')
return data
def post(self):
"""任务提交"""
args = self.parse_args(add_task_fields)
name = args.pop('name')
target = args.po... | the_stack_v2_python_sparse | app/routes/task.py | QmF0c3UK/ARL | train | 0 | |
4c5495cf1bb582131de1e5c52b38709eefe0aad0 | [
"self.check_run('deploy_environment_without_toolchain')\nself.env.revert_snapshot('ready_with_5_slaves')\nself.helpers.create_cluster(name=self.__class__.__name__)\nself.helpers.deploy_cluster({'slave-01': ['controller'], 'slave-02': ['compute', 'cinder']})\nself.helpers.run_ostf()\nself.env.make_snapshot('deploy_e... | <|body_start_0|>
self.check_run('deploy_environment_without_toolchain')
self.env.revert_snapshot('ready_with_5_slaves')
self.helpers.create_cluster(name=self.__class__.__name__)
self.helpers.deploy_cluster({'slave-01': ['controller'], 'slave-02': ['compute', 'cinder']})
self.help... | Class for testing that the LMA Toolchain plugins can be installed in an existing environment. | TestToolchainPostInstallation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestToolchainPostInstallation:
"""Class for testing that the LMA Toolchain plugins can be installed in an existing environment."""
def deploy_environment_without_toolchain(self):
"""Deploy a cluster without the LMA Toolchain plugins. Scenario: 1. Create the cluster 2. Add 1 node with... | stack_v2_sparse_classes_36k_train_006979 | 3,993 | no_license | [
{
"docstring": "Deploy a cluster without the LMA Toolchain plugins. Scenario: 1. Create the cluster 2. Add 1 node with the controller role 3. Add 1 node with the compute and cinder roles 4. Deploy the cluster 5. Run OSTF Duration 60m Snapshot deploy_environment_without_toolchain",
"name": "deploy_environmen... | 2 | stack_v2_sparse_classes_30k_train_017847 | Implement the Python class `TestToolchainPostInstallation` described below.
Class description:
Class for testing that the LMA Toolchain plugins can be installed in an existing environment.
Method signatures and docstrings:
- def deploy_environment_without_toolchain(self): Deploy a cluster without the LMA Toolchain pl... | Implement the Python class `TestToolchainPostInstallation` described below.
Class description:
Class for testing that the LMA Toolchain plugins can be installed in an existing environment.
Method signatures and docstrings:
- def deploy_environment_without_toolchain(self): Deploy a cluster without the LMA Toolchain pl... | 179249df2d206eeabb3955c9dc8cb78cac3c36c6 | <|skeleton|>
class TestToolchainPostInstallation:
"""Class for testing that the LMA Toolchain plugins can be installed in an existing environment."""
def deploy_environment_without_toolchain(self):
"""Deploy a cluster without the LMA Toolchain plugins. Scenario: 1. Create the cluster 2. Add 1 node with... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestToolchainPostInstallation:
"""Class for testing that the LMA Toolchain plugins can be installed in an existing environment."""
def deploy_environment_without_toolchain(self):
"""Deploy a cluster without the LMA Toolchain plugins. Scenario: 1. Create the cluster 2. Add 1 node with the controll... | the_stack_v2_python_sparse | stacklight_tests/toolchain/test_post_install.py | rkhozinov/stacklight-integration-tests | train | 1 |
97976139dc89d5f5d252b29d61638a65e5722867 | [
"self.address = self._get_conf('Ec_rest_server_address')\nself.port = self._get_conf('Ec_port_number')\nself.controller_type = 'em'\nself.api_url = 'v1/internal/ec_ctrl/logstatusnotify'\nself.url_format = 'http://{address}:{port}/{api_url}'",
"if self.address and self.port:\n thread = threading.Thread(target=s... | <|body_start_0|>
self.address = self._get_conf('Ec_rest_server_address')
self.port = self._get_conf('Ec_port_number')
self.controller_type = 'em'
self.api_url = 'v1/internal/ec_ctrl/logstatusnotify'
self.url_format = 'http://{address}:{port}/{api_url}'
<|end_body_0|>
<|body_star... | Controller log notification class | ControllerLogNotify | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ControllerLogNotify:
"""Controller log notification class"""
def __init__(self):
"""Constructor"""
<|body_0|>
def notify_logs(self, msg, log_level):
"""Log is notified. Argument: msg : log data (str) log_level : log level (int)"""
<|body_1|>
def send... | stack_v2_sparse_classes_36k_train_006980 | 3,494 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Log is notified. Argument: msg : log data (str) log_level : log level (int)",
"name": "notify_logs",
"signature": "def notify_logs(self, msg, log_level)"
},
{
"docstring": "Requ... | 5 | null | Implement the Python class `ControllerLogNotify` described below.
Class description:
Controller log notification class
Method signatures and docstrings:
- def __init__(self): Constructor
- def notify_logs(self, msg, log_level): Log is notified. Argument: msg : log data (str) log_level : log level (int)
- def send_not... | Implement the Python class `ControllerLogNotify` described below.
Class description:
Controller log notification class
Method signatures and docstrings:
- def __init__(self): Constructor
- def notify_logs(self, msg, log_level): Log is notified. Argument: msg : log data (str) log_level : log level (int)
- def send_not... | e550d1b5ec9419f1fb3eb6e058ce46b57c92ee2f | <|skeleton|>
class ControllerLogNotify:
"""Controller log notification class"""
def __init__(self):
"""Constructor"""
<|body_0|>
def notify_logs(self, msg, log_level):
"""Log is notified. Argument: msg : log data (str) log_level : log level (int)"""
<|body_1|>
def send... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ControllerLogNotify:
"""Controller log notification class"""
def __init__(self):
"""Constructor"""
self.address = self._get_conf('Ec_rest_server_address')
self.port = self._get_conf('Ec_port_number')
self.controller_type = 'em'
self.api_url = 'v1/internal/ec_ctrl/l... | the_stack_v2_python_sparse | lib/ControllerLogNotify/ControllerLogNotify.py | lixiaochun/element-manager | train | 0 |
40018bf78d0e5152a2446aef1b89ac6e8e35b626 | [
"self._resource = resource\nself._pin = pin\nself.data = {}",
"try:\n response = requests.get(f'{self._resource}/digital/{self._pin}', timeout=10)\n self.data = {'state': response.json()['return_value']}\nexcept requests.exceptions.ConnectionError:\n _LOGGER.error(\"No route to device '%s'\", self._resou... | <|body_start_0|>
self._resource = resource
self._pin = pin
self.data = {}
<|end_body_0|>
<|body_start_1|>
try:
response = requests.get(f'{self._resource}/digital/{self._pin}', timeout=10)
self.data = {'state': response.json()['return_value']}
except reque... | Class for handling the data retrieval for pins. | ArestData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArestData:
"""Class for handling the data retrieval for pins."""
def __init__(self, resource, pin):
"""Initialize the aREST data object."""
<|body_0|>
def update(self) -> None:
"""Get the latest data from aREST device."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_006981 | 3,418 | permissive | [
{
"docstring": "Initialize the aREST data object.",
"name": "__init__",
"signature": "def __init__(self, resource, pin)"
},
{
"docstring": "Get the latest data from aREST device.",
"name": "update",
"signature": "def update(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_007244 | Implement the Python class `ArestData` described below.
Class description:
Class for handling the data retrieval for pins.
Method signatures and docstrings:
- def __init__(self, resource, pin): Initialize the aREST data object.
- def update(self) -> None: Get the latest data from aREST device. | Implement the Python class `ArestData` described below.
Class description:
Class for handling the data retrieval for pins.
Method signatures and docstrings:
- def __init__(self, resource, pin): Initialize the aREST data object.
- def update(self) -> None: Get the latest data from aREST device.
<|skeleton|>
class Are... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ArestData:
"""Class for handling the data retrieval for pins."""
def __init__(self, resource, pin):
"""Initialize the aREST data object."""
<|body_0|>
def update(self) -> None:
"""Get the latest data from aREST device."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArestData:
"""Class for handling the data retrieval for pins."""
def __init__(self, resource, pin):
"""Initialize the aREST data object."""
self._resource = resource
self._pin = pin
self.data = {}
def update(self) -> None:
"""Get the latest data from aREST dev... | the_stack_v2_python_sparse | homeassistant/components/arest/binary_sensor.py | home-assistant/core | train | 35,501 |
3f89dae91c71a98247aaf3fc00979abbfdd6931c | [
"input_doc = xml.dom.minidom.parse(filename)\npoint = point.process(input_doc.getElementsByTagName('Parameters')[0])\nrequests = self._handleRequests(input_doc.getElementsByTagName('Requests')[0])\nreturn (point, requests)",
"requests = {}\nfor child in node.childNodes:\n if child.nodeType == node.ELEMENT_NODE... | <|body_start_0|>
input_doc = xml.dom.minidom.parse(filename)
point = point.process(input_doc.getElementsByTagName('Parameters')[0])
requests = self._handleRequests(input_doc.getElementsByTagName('Requests')[0])
return (point, requests)
<|end_body_0|>
<|body_start_1|>
requests = ... | The reader/writer for the COLIN XML IO Formats | ColinXmlIO | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ColinXmlIO:
"""The reader/writer for the COLIN XML IO Formats"""
def read(self, filename, point):
"""Read a point and request information. This method returns a tuple: point, requests"""
<|body_0|>
def _handleRequests(self, node):
"""A function that processes the... | stack_v2_sparse_classes_36k_train_006982 | 2,928 | permissive | [
{
"docstring": "Read a point and request information. This method returns a tuple: point, requests",
"name": "read",
"signature": "def read(self, filename, point)"
},
{
"docstring": "A function that processes the requests",
"name": "_handleRequests",
"signature": "def _handleRequests(sel... | 4 | null | Implement the Python class `ColinXmlIO` described below.
Class description:
The reader/writer for the COLIN XML IO Formats
Method signatures and docstrings:
- def read(self, filename, point): Read a point and request information. This method returns a tuple: point, requests
- def _handleRequests(self, node): A functi... | Implement the Python class `ColinXmlIO` described below.
Class description:
The reader/writer for the COLIN XML IO Formats
Method signatures and docstrings:
- def read(self, filename, point): Read a point and request information. This method returns a tuple: point, requests
- def _handleRequests(self, node): A functi... | ab4ada5a93aed570a6e6ca6161462e970cffe677 | <|skeleton|>
class ColinXmlIO:
"""The reader/writer for the COLIN XML IO Formats"""
def read(self, filename, point):
"""Read a point and request information. This method returns a tuple: point, requests"""
<|body_0|>
def _handleRequests(self, node):
"""A function that processes the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ColinXmlIO:
"""The reader/writer for the COLIN XML IO Formats"""
def read(self, filename, point):
"""Read a point and request information. This method returns a tuple: point, requests"""
input_doc = xml.dom.minidom.parse(filename)
point = point.process(input_doc.getElementsByTagNa... | the_stack_v2_python_sparse | pyomo/opt/plugins/colin_xml_io.py | qtothec/pyomo | train | 3 |
e42279d86caaec807eea2c51576edc1818618277 | [
"if len(s) <= 1:\n return True\nfor i in range(len(s) / 2):\n if s[i] != s[len(s) - i - 1]:\n return False\nreturn True",
"m, n = (len(word1), len(word2))\nif m == 0 or n == 0:\n return 0\ndp = [0] * n\nres = 0\nfor i, a in enumerate(word1):\n cur_max = 1\n for j, b in enumerate(word2):\n ... | <|body_start_0|>
if len(s) <= 1:
return True
for i in range(len(s) / 2):
if s[i] != s[len(s) - i - 1]:
return False
return True
<|end_body_0|>
<|body_start_1|>
m, n = (len(word1), len(word2))
if m == 0 or n == 0:
return 0
... | XString | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XString:
def is_p(self, s):
"""is palindrome type s: string rtype : boolean"""
<|body_0|>
def lcslen(self, word1, word2):
"""longest common substring :type word1: str :type word2: str :rtype: int :return the length of longest common substring, e.g, m('1a2b3c4d', 'a5b... | stack_v2_sparse_classes_36k_train_006983 | 6,377 | no_license | [
{
"docstring": "is palindrome type s: string rtype : boolean",
"name": "is_p",
"signature": "def is_p(self, s)"
},
{
"docstring": "longest common substring :type word1: str :type word2: str :rtype: int :return the length of longest common substring, e.g, m('1a2b3c4d', 'a5b6c777d88') return 4 (le... | 4 | null | Implement the Python class `XString` described below.
Class description:
Implement the XString class.
Method signatures and docstrings:
- def is_p(self, s): is palindrome type s: string rtype : boolean
- def lcslen(self, word1, word2): longest common substring :type word1: str :type word2: str :rtype: int :return the... | Implement the Python class `XString` described below.
Class description:
Implement the XString class.
Method signatures and docstrings:
- def is_p(self, s): is palindrome type s: string rtype : boolean
- def lcslen(self, word1, word2): longest common substring :type word1: str :type word2: str :rtype: int :return the... | 9e4f6f1a2830bd9aab1bba374c98f0464825d435 | <|skeleton|>
class XString:
def is_p(self, s):
"""is palindrome type s: string rtype : boolean"""
<|body_0|>
def lcslen(self, word1, word2):
"""longest common substring :type word1: str :type word2: str :rtype: int :return the length of longest common substring, e.g, m('1a2b3c4d', 'a5b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XString:
def is_p(self, s):
"""is palindrome type s: string rtype : boolean"""
if len(s) <= 1:
return True
for i in range(len(s) / 2):
if s[i] != s[len(s) - i - 1]:
return False
return True
def lcslen(self, word1, word2):
"""... | the_stack_v2_python_sparse | python_solutions/712.minimum-ascii-delete-sum-for-two-strings.py | h4hany/leetcode | train | 0 | |
4c7431e38bed166aac61e4b93caf7764cca6131c | [
"self.image = Image.open(image_data)\nimage_size = self.image.size\nself.image_too_large = False\nif image_size[0] > MAX_ALLOWED_IMAGE_DIM or image_size[1] > MAX_ALLOWED_IMAGE_DIM:\n self.image_too_large = True\nif image_size[0] > MAX_IMAGE_DIM or image_size[1] > MAX_IMAGE_DIM:\n self.image = self.image.resiz... | <|body_start_0|>
self.image = Image.open(image_data)
image_size = self.image.size
self.image_too_large = False
if image_size[0] > MAX_ALLOWED_IMAGE_DIM or image_size[1] > MAX_ALLOWED_IMAGE_DIM:
self.image_too_large = True
if image_size[0] > MAX_IMAGE_DIM or image_size... | Class to check properties of an image and to validate if they are allowed. | ImageProperties | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageProperties:
"""Class to check properties of an image and to validate if they are allowed."""
def __init__(self, image_data):
"""Initializes class variables @param image: Image object (from PIL) @return: None"""
<|body_0|>
def count_colors(self):
"""Counts th... | stack_v2_sparse_classes_36k_train_006984 | 8,366 | no_license | [
{
"docstring": "Initializes class variables @param image: Image object (from PIL) @return: None",
"name": "__init__",
"signature": "def __init__(self, image_data)"
},
{
"docstring": "Counts the number of colors in an image, and matches them to the max allowed @return: boolean true if color count... | 5 | null | Implement the Python class `ImageProperties` described below.
Class description:
Class to check properties of an image and to validate if they are allowed.
Method signatures and docstrings:
- def __init__(self, image_data): Initializes class variables @param image: Image object (from PIL) @return: None
- def count_co... | Implement the Python class `ImageProperties` described below.
Class description:
Class to check properties of an image and to validate if they are allowed.
Method signatures and docstrings:
- def __init__(self, image_data): Initializes class variables @param image: Image object (from PIL) @return: None
- def count_co... | 5fa3a818c3d41bd9c3eb25122e1d376c8910269c | <|skeleton|>
class ImageProperties:
"""Class to check properties of an image and to validate if they are allowed."""
def __init__(self, image_data):
"""Initializes class variables @param image: Image object (from PIL) @return: None"""
<|body_0|>
def count_colors(self):
"""Counts th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageProperties:
"""Class to check properties of an image and to validate if they are allowed."""
def __init__(self, image_data):
"""Initializes class variables @param image: Image object (from PIL) @return: None"""
self.image = Image.open(image_data)
image_size = self.image.size
... | the_stack_v2_python_sparse | ExtractFeatures/Data/pratik98/open_ended_image_submission.py | vivekaxl/LexisNexis | train | 9 |
26dd01fc7464fa5f25199bb74be568bb4abc301a | [
"self.ranges = ranges = [0]\nself.rects = rects\nfor x1, y1, x2, y2 in rects:\n ranges.append(ranges[-1] + (y2 - y1 + 1) * (x2 - x1 + 1))",
"ranges, rects = (self.ranges, self.rects)\nareaPt = random.randint(1, ranges[-1])\nx1, y1, x2, y2 = rects[bisect.bisect_left(ranges, areaPt) - 1]\nreturn [random.randint(... | <|body_start_0|>
self.ranges = ranges = [0]
self.rects = rects
for x1, y1, x2, y2 in rects:
ranges.append(ranges[-1] + (y2 - y1 + 1) * (x2 - x1 + 1))
<|end_body_0|>
<|body_start_1|>
ranges, rects = (self.ranges, self.rects)
areaPt = random.randint(1, ranges[-1])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.ranges = ranges = [0]
self.rects = rects
for x1, y1, x2, y2 ... | stack_v2_sparse_classes_36k_train_006985 | 4,116 | no_license | [
{
"docstring": ":type rects: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, rects)"
},
{
"docstring": ":rtype: List[int]",
"name": "pick",
"signature": "def pick(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014984 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type rects: List[List[int]]
- def pick(self): :rtype: List[int]
<|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: ... | d2037e521a3ee6fdcc14fd5228ea1fd32d57d637 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
<|body_0|>
def pick(self):
""":rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, rects):
""":type rects: List[List[int]]"""
self.ranges = ranges = [0]
self.rects = rects
for x1, y1, x2, y2 in rects:
ranges.append(ranges[-1] + (y2 - y1 + 1) * (x2 - x1 + 1))
def pick(self):
""":rtype: List[int]"""
... | the_stack_v2_python_sparse | monthlyChallenge/2020-08(augustchallenge)/8_22(***)RandNonOverlappedRect.py | phu-n-tran/LeetCode | train | 2 | |
89ff15bbd2be63a50bc35b21850606205f9fee65 | [
"super().__init__()\nself.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)\nself.input_image = self.graph.get_tensor_by_name('input:0')\nself.segmented_tensor = self.graph.get_tensor_by_name('output_prediction:0')",
"img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)\nfeed = {self.i... | <|body_start_0|>
super().__init__()
self.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)
self.input_image = self.graph.get_tensor_by_name('input:0')
self.segmented_tensor = self.graph.get_tensor_by_name('output_prediction:0')
<|end_body_0|>
<|body_start_1... | Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is this true? | DepthPredictor | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DepthPredictor:
"""Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is ... | stack_v2_sparse_classes_36k_train_006986 | 2,142 | permissive | [
{
"docstring": ":param model_bytes: Model file data, likely a loaded *.pb file :param device: The device to run the model on :param session_config: Model configuration options",
"name": "__init__",
"signature": "def __init__(self, model_bytes, device: str=None, session_config: tf.compat.v1.ConfigProto=N... | 2 | stack_v2_sparse_classes_30k_val_000787 | Implement the Python class `DepthPredictor` described below.
Class description:
Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does... | Implement the Python class `DepthPredictor` described below.
Class description:
Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does... | 7412902fed8f91c9c82bd42b0180e07673c38bf1 | <|skeleton|>
class DepthPredictor:
"""Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DepthPredictor:
"""Loads a model and uses it to run depth prediction, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to the pixel's distance from the camera in meters. Does not support batch prediction TODO: Is this true?"""... | the_stack_v2_python_sparse | vcap_utils/vcap_utils/backends/depth.py | opencv/open_vision_capsules | train | 124 |
9e610cef92c3f9a27ce716577bd54232b9871a21 | [
"result = [[]]\nfor num in nums:\n result += [curr_result + [num] for curr_result in result]\nreturn result",
"result = []\n\ndef backtrack(tmp, idx):\n result.append(tmp[:])\n for i in xrange(idx, len(nums)):\n tmp.append(nums[i])\n backtrack(tmp, i + 1)\n tmp.pop()\nbacktrack([], 0... | <|body_start_0|>
result = [[]]
for num in nums:
result += [curr_result + [num] for curr_result in result]
return result
<|end_body_0|>
<|body_start_1|>
result = []
def backtrack(tmp, idx):
result.append(tmp[:])
for i in xrange(idx, len(nums))... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsets_1(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = [[]]
for n... | stack_v2_sparse_classes_36k_train_006987 | 1,481 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsets_1",
"signature": "def subsets_1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsets",
"signature": "def subsets(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000820 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets_1(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets_1(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solution:
... | 5c2473f859da5efec73120256faad06ab8e0e359 | <|skeleton|>
class Solution:
def subsets_1(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def subsets_1(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
result = [[]]
for num in nums:
result += [curr_result + [num] for curr_result in result]
return result
def subsets(self, nums):
""":type nums: List[int] :rtype: Lis... | the_stack_v2_python_sparse | leetcode/subsets.py | chlos/exercises_in_futility | train | 0 | |
c01ac6f0b059d2dd4fe85d2dac1454ca3d6bd08e | [
"if len(values) == 0 or len(weights) == 0:\n return 0\ntable = []\nfor i in range(limit + 1):\n table.append([0] * (len(values) + 1))\nfor max_weights in range(limit + 1):\n for i in range(len(values) + 1):\n if max_weights == 0:\n table[max_weights][i] = 0\n elif i == 0:\n ... | <|body_start_0|>
if len(values) == 0 or len(weights) == 0:
return 0
table = []
for i in range(limit + 1):
table.append([0] * (len(values) + 1))
for max_weights in range(limit + 1):
for i in range(len(values) + 1):
if max_weights == 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_0|>
def knapsack2(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_006988 | 3,832 | no_license | [
{
"docstring": "input: string source, string target return: int",
"name": "knapsack",
"signature": "def knapsack(self, values, weights, limit)"
},
{
"docstring": "input: string source, string target return: int",
"name": "knapsack2",
"signature": "def knapsack2(self, values, weights, lim... | 2 | stack_v2_sparse_classes_30k_val_000022 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knapsack(self, values, weights, limit): input: string source, string target return: int
- def knapsack2(self, values, weights, limit): input: string source, string target ret... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def knapsack(self, values, weights, limit): input: string source, string target return: int
- def knapsack2(self, values, weights, limit): input: string source, string target ret... | 8d9eb98fa5e897602eae9c37b47fd8abae72b1dc | <|skeleton|>
class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_0|>
def knapsack2(self, values, weights, limit):
"""input: string source, string target return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def knapsack(self, values, weights, limit):
"""input: string source, string target return: int"""
if len(values) == 0 or len(weights) == 0:
return 0
table = []
for i in range(limit + 1):
table.append([0] * (len(values) + 1))
for max_wei... | the_stack_v2_python_sparse | misc/knapsack.py | wanlipu/coding-python | train | 0 | |
1684678b68165a0fd8dd055be58b2f53e1faa4ad | [
"fit_params = {}\nmodel_params = {}\nfor k, v in params.items():\n if k in self.independent_vars or k in ['weights', 'method', 'scale_covar', 'iter_cb']:\n fit_params[k] = v\n else:\n model_params[k] = v\np = self.make_params(**model_params)\nfit = lmfit.Model.fit(self, data, params=p, **fit_par... | <|body_start_0|>
fit_params = {}
model_params = {}
for k, v in params.items():
if k in self.independent_vars or k in ['weights', 'method', 'scale_covar', 'iter_cb']:
fit_params[k] = v
else:
model_params[k] = v
p = self.make_params(*... | Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1, 50)) # plot the fit:: fit_curve = fit.eval() plot(time_vals, fit_curve) # ... | FitModel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FitModel:
"""Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1, 50)) # plot the fit:: fit_curve = fit.... | stack_v2_sparse_classes_36k_train_006989 | 6,827 | permissive | [
{
"docstring": "Return a fit of data to this model. Parameters ---------- data : array dependent data to fit interactive : bool If True, show a GUI used for interactively exploring fit parameters Extra keyword arguments are passed to make_params() if they are model parameter names, or passed directly to Model.f... | 3 | stack_v2_sparse_classes_30k_train_008952 | Implement the Python class `FitModel` described below.
Class description:
Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1,... | Implement the Python class `FitModel` described below.
Class description:
Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1,... | ff705f650e765142775f4ae0e3c3159e30af8944 | <|skeleton|>
class FitModel:
"""Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1, 50)) # plot the fit:: fit_curve = fit.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FitModel:
"""Simple extension of lmfit.Model that allows one-line fitting. Example uses: # single exponential fit:: fit = expfitting.Exp1.fit(data, x=time_vals, xoffset=(0, 'fixed'), yoffset=(yoff_guess, -120, 0), amp=(amp_guess, 0, 50), tau=(tau_guess, 0.1, 50)) # plot the fit:: fit_curve = fit.eval() plot(t... | the_stack_v2_python_sparse | cnmodel/util/fitting.py | cnmodel/cnmodel | train | 10 |
b024ce790f1a0c6ce1cc0e1f34202313fcedc8a0 | [
"super().__init__()\nself.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)\nself.label_map = parse_dataset_metadata_bytes(metadata_bytes)\nself.input_image = self.graph.get_tensor_by_name('input')\nself.segmented_tensor = self.graph.get_tensor_by_name('output_prediction')",
"feed = ... | <|body_start_0|>
super().__init__()
self.graph, self.session = parse_tf_model_bytes(model_bytes, device, session_config)
self.label_map = parse_dataset_metadata_bytes(metadata_bytes)
self.input_image = self.graph.get_tensor_by_name('input')
self.segmented_tensor = self.graph.get_... | Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true? | Segmenter | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __ini... | stack_v2_sparse_classes_36k_train_006990 | 2,521 | permissive | [
{
"docstring": ":param model_bytes: Model file data, likely a loaded *.pb file :param metadata_bytes: The dataset metadata file data, likely named \"dataset_metadata.json\" :param device: The device to run the model on :param session_config: Model configuration options",
"name": "__init__",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_016964 | Implement the Python class `Segmenter` described below.
Class description:
Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch predictio... | Implement the Python class `Segmenter` described below.
Class description:
Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch predictio... | 7412902fed8f91c9c82bd42b0180e07673c38bf1 | <|skeleton|>
class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __ini... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Segmenter:
"""Loads a model and uses it to run image segmentation, meaning that it takes an image as input and returns a matrix the size of the input image where the value of each 'pixel' corresponds to an image segment type. Does not support batch prediction TODO: Is this true?"""
def __init__(self, mod... | the_stack_v2_python_sparse | vcap_utils/vcap_utils/backends/segmentation.py | opencv/open_vision_capsules | train | 124 |
757964161dd89c5d39077a62a765398605121c04 | [
"self.filename = os.path.join(write_dir, 'hdf5/data%08d.h5' % i)\nself.iteration = i\nself.zmin_lab = zmin_lab\nself.zmax_lab = zmax_lab\nself.t_lab = t_lab\nself.current_z_lab = 0\nself.current_z_boost = 0\nself.buffered_slices = []\nself.buffer_z_indices = []\ndata_shape = (10, 2 * fld.Nm - 1, Nr_output)\nif fld.... | <|body_start_0|>
self.filename = os.path.join(write_dir, 'hdf5/data%08d.h5' % i)
self.iteration = i
self.zmin_lab = zmin_lab
self.zmax_lab = zmax_lab
self.t_lab = t_lab
self.current_z_lab = 0
self.current_z_boost = 0
self.buffered_slices = []
self.... | Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame) | LabSnapshot | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LabSnapshot:
"""Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame)"""
def __init__(self, t_lab, zmin_lab, zmax_lab, write_dir, i, fld, Nr_output):
"""Initialize a LabSnapshot Parameters ---------- t_lab: float (seconds) Tim... | stack_v2_sparse_classes_36k_train_006991 | 33,919 | permissive | [
{
"docstring": "Initialize a LabSnapshot Parameters ---------- t_lab: float (seconds) Time of this snapshot *in the lab frame* zmin_lab, zmax_lab: floats Longitudinal limits of this snapshot write_dir: string Absolute path to the directory where the data for this snapshot is to be written i: int Number of the f... | 4 | null | Implement the Python class `LabSnapshot` described below.
Class description:
Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame)
Method signatures and docstrings:
- def __init__(self, t_lab, zmin_lab, zmax_lab, write_dir, i, fld, Nr_output): Initialize a Lab... | Implement the Python class `LabSnapshot` described below.
Class description:
Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame)
Method signatures and docstrings:
- def __init__(self, t_lab, zmin_lab, zmax_lab, write_dir, i, fld, Nr_output): Initialize a Lab... | 5744598571eab40c4fb45cc3db21f346b69b1f37 | <|skeleton|>
class LabSnapshot:
"""Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame)"""
def __init__(self, t_lab, zmin_lab, zmax_lab, write_dir, i, fld, Nr_output):
"""Initialize a LabSnapshot Parameters ---------- t_lab: float (seconds) Tim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LabSnapshot:
"""Class that stores data relative to one given snapshot in the lab frame (i.e. one given *time* in the lab frame)"""
def __init__(self, t_lab, zmin_lab, zmax_lab, write_dir, i, fld, Nr_output):
"""Initialize a LabSnapshot Parameters ---------- t_lab: float (seconds) Time of this sna... | the_stack_v2_python_sparse | fbpic/openpmd_diag/boosted_field_diag.py | fbpic/fbpic | train | 163 |
8daa2c680bbf2d7096fe8f99dd40b90b1a609af2 | [
"if os.system('redis-server &') == 0:\n print('redis-server 启动成功')\n try:\n time.sleep(0.5)\n self.__connect = redis.Redis(host=s_host)\n except:\n self.__connect = None\nelse:\n self.__connect = None",
"if self.__connect is not None:\n self.__connect.publish(str_channel, sendM... | <|body_start_0|>
if os.system('redis-server &') == 0:
print('redis-server 启动成功')
try:
time.sleep(0.5)
self.__connect = redis.Redis(host=s_host)
except:
self.__connect = None
else:
self.__connect = None
<|end_... | DataBus | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataBus:
def __init__(self, s_host: str):
""":param s_host: REDIS服务地址"""
<|body_0|>
def publish(self, str_channel: str, sendMsg):
""":param str_channel:消息发布频道 :param sendMsg:对应消息 :return:消息发布状态，成功：TRUE，失败：FALSE"""
<|body_1|>
def get_subscriber(self, list... | stack_v2_sparse_classes_36k_train_006992 | 1,428 | no_license | [
{
"docstring": ":param s_host: REDIS服务地址",
"name": "__init__",
"signature": "def __init__(self, s_host: str)"
},
{
"docstring": ":param str_channel:消息发布频道 :param sendMsg:对应消息 :return:消息发布状态，成功：TRUE，失败：FALSE",
"name": "publish",
"signature": "def publish(self, str_channel: str, sendMsg)"
... | 3 | null | Implement the Python class `DataBus` described below.
Class description:
Implement the DataBus class.
Method signatures and docstrings:
- def __init__(self, s_host: str): :param s_host: REDIS服务地址
- def publish(self, str_channel: str, sendMsg): :param str_channel:消息发布频道 :param sendMsg:对应消息 :return:消息发布状态，成功：TRUE，失败：FA... | Implement the Python class `DataBus` described below.
Class description:
Implement the DataBus class.
Method signatures and docstrings:
- def __init__(self, s_host: str): :param s_host: REDIS服务地址
- def publish(self, str_channel: str, sendMsg): :param str_channel:消息发布频道 :param sendMsg:对应消息 :return:消息发布状态，成功：TRUE，失败：FA... | 31918e28fa3390390c4ea6208132d48164f95f73 | <|skeleton|>
class DataBus:
def __init__(self, s_host: str):
""":param s_host: REDIS服务地址"""
<|body_0|>
def publish(self, str_channel: str, sendMsg):
""":param str_channel:消息发布频道 :param sendMsg:对应消息 :return:消息发布状态，成功：TRUE，失败：FALSE"""
<|body_1|>
def get_subscriber(self, list... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataBus:
def __init__(self, s_host: str):
""":param s_host: REDIS服务地址"""
if os.system('redis-server &') == 0:
print('redis-server 启动成功')
try:
time.sleep(0.5)
self.__connect = redis.Redis(host=s_host)
except:
se... | the_stack_v2_python_sparse | new_soft/Common/Interface/DataBus.py | 841661831/perception | train | 1 | |
e950332936e16fe0704720e81b300c1cdc57962f | [
"if csvfilename is not None:\n attrdata = self.loaddata(mriscan, attrname, csvfilename)\nelse:\n attrdata = self.loaddata(mriscan, attrname)\nattr = netattr.Attr(attrdata, self.atlasobj, mriscan, attrname)\nreturn attr",
"attr_list = []\nfor mriscan in mriscans:\n if csvfilename is not None:\n att... | <|body_start_0|>
if csvfilename is not None:
attrdata = self.loaddata(mriscan, attrname, csvfilename)
else:
attrdata = self.loaddata(mriscan, attrname)
attr = netattr.Attr(attrdata, self.atlasobj, mriscan, attrname)
return attr
<|end_body_0|>
<|body_start_1|>
... | Attribute loader. | AttrLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttrLoader:
"""Attribute loader."""
def loadSingle(self, mriscan, attrname, csvfilename=None):
"""Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - csvfilename: the name of the attr file name. Specify this ... | stack_v2_sparse_classes_36k_train_006993 | 13,309 | no_license | [
{
"docstring": "Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - csvfilename: the name of the attr file name. Specify this parameter to override filename",
"name": "loadSingle",
"signature": "def loadSingle(self, mriscan, att... | 3 | stack_v2_sparse_classes_30k_train_018141 | Implement the Python class `AttrLoader` described below.
Class description:
Attribute loader.
Method signatures and docstrings:
- def loadSingle(self, mriscan, attrname, csvfilename=None): Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - c... | Implement the Python class `AttrLoader` described below.
Class description:
Attribute loader.
Method signatures and docstrings:
- def loadSingle(self, mriscan, attrname, csvfilename=None): Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - c... | dabfabdeb2f922a3dcbdaf3fc46f0c4b40598279 | <|skeleton|>
class AttrLoader:
"""Attribute loader."""
def loadSingle(self, mriscan, attrname, csvfilename=None):
"""Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - csvfilename: the name of the attr file name. Specify this ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttrLoader:
"""Attribute loader."""
def loadSingle(self, mriscan, attrname, csvfilename=None):
"""Load the attribute object, with atlasobj. - mriscan: specify which scan to load from - attrname: the name of the attr to load - csvfilename: the name of the attr file name. Specify this parameter to ... | the_stack_v2_python_sparse | mmdps/proc/loader.py | geyunxiang/mmdps | train | 5 |
393892e2d191c6ead87e8a0e12db2f86e24528d3 | [
"if file is None:\n 'Set client to the default when running on local machine'\n self.file = 'batch1.json'",
"with open(self.file, 'a') as f:\n json.dump(data, f, ensure_ascii=False)\n f.write('\\n')"
] | <|body_start_0|>
if file is None:
'Set client to the default when running on local machine'
self.file = 'batch1.json'
<|end_body_0|>
<|body_start_1|>
with open(self.file, 'a') as f:
json.dump(data, f, ensure_ascii=False)
f.write('\n')
<|end_body_1|>
| FileWriter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileWriter:
def __init__(self, file=None):
""":param file: The path to the wile which this calss will write data."""
<|body_0|>
def send_data(self, data):
"""Writes JSON data to the file. If the file does not exists it will be created."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_006994 | 571 | no_license | [
{
"docstring": ":param file: The path to the wile which this calss will write data.",
"name": "__init__",
"signature": "def __init__(self, file=None)"
},
{
"docstring": "Writes JSON data to the file. If the file does not exists it will be created.",
"name": "send_data",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_014007 | Implement the Python class `FileWriter` described below.
Class description:
Implement the FileWriter class.
Method signatures and docstrings:
- def __init__(self, file=None): :param file: The path to the wile which this calss will write data.
- def send_data(self, data): Writes JSON data to the file. If the file does... | Implement the Python class `FileWriter` described below.
Class description:
Implement the FileWriter class.
Method signatures and docstrings:
- def __init__(self, file=None): :param file: The path to the wile which this calss will write data.
- def send_data(self, data): Writes JSON data to the file. If the file does... | 6530a53f1d901eb418b404f8d705105b08b1ae97 | <|skeleton|>
class FileWriter:
def __init__(self, file=None):
""":param file: The path to the wile which this calss will write data."""
<|body_0|>
def send_data(self, data):
"""Writes JSON data to the file. If the file does not exists it will be created."""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileWriter:
def __init__(self, file=None):
""":param file: The path to the wile which this calss will write data."""
if file is None:
'Set client to the default when running on local machine'
self.file = 'batch1.json'
def send_data(self, data):
"""Writes JS... | the_stack_v2_python_sparse | extraction/file_writer.py | anduinsay/StickComments | train | 0 | |
015e8fe8d59d16818589213af4378bed0b0347b7 | [
"if context is None:\n context = {}\nform = self.read(cr, uid, ids, [])[0]\njournal_ids = form['journal_ids']\njournal_id = form['journal_id'] and form['journal_id'][0]\ncompany_id = form['company_id'] and form['company_id'][0]\ndata_pool = self.pool.get('ir.model.data')\nvoucher_ids = self.get_move(cr, uid, ids... | <|body_start_0|>
if context is None:
context = {}
form = self.read(cr, uid, ids, [])[0]
journal_ids = form['journal_ids']
journal_id = form['journal_id'] and form['journal_id'][0]
company_id = form['company_id'] and form['company_id'][0]
data_pool = self.pool.... | account_cancel_check | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class account_cancel_check:
def get_moves(self, cr, uid, ids, context=None):
"""Method that display all cancelled payment @return: dictionary action details"""
<|body_0|>
def get_move(self, cr, uid, ids=False, journal_ids=False, journal_id=False, company_id=False, account_id=False... | stack_v2_sparse_classes_36k_train_006995 | 5,744 | no_license | [
{
"docstring": "Method that display all cancelled payment @return: dictionary action details",
"name": "get_moves",
"signature": "def get_moves(self, cr, uid, ids, context=None)"
},
{
"docstring": "Method that cancel unreceived & unreconsiled payment vouchers which exceed it's grace period and c... | 2 | null | Implement the Python class `account_cancel_check` described below.
Class description:
Implement the account_cancel_check class.
Method signatures and docstrings:
- def get_moves(self, cr, uid, ids, context=None): Method that display all cancelled payment @return: dictionary action details
- def get_move(self, cr, uid... | Implement the Python class `account_cancel_check` described below.
Class description:
Implement the account_cancel_check class.
Method signatures and docstrings:
- def get_moves(self, cr, uid, ids, context=None): Method that display all cancelled payment @return: dictionary action details
- def get_move(self, cr, uid... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class account_cancel_check:
def get_moves(self, cr, uid, ids, context=None):
"""Method that display all cancelled payment @return: dictionary action details"""
<|body_0|>
def get_move(self, cr, uid, ids=False, journal_ids=False, journal_id=False, company_id=False, account_id=False... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class account_cancel_check:
def get_moves(self, cr, uid, ids, context=None):
"""Method that display all cancelled payment @return: dictionary action details"""
if context is None:
context = {}
form = self.read(cr, uid, ids, [])[0]
journal_ids = form['journal_ids']
... | the_stack_v2_python_sparse | v_7/Dongola/wafi/account_check_writing_wafi/wizard/account_check_cancel.py | musabahmed/baba | train | 0 | |
e27baa3b2d4f703dad99eaac484b1291d27e75bd | [
"completed_process = subprocess.run(command, shell=True, executable='/bin/bash', stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True, timeout=timeout)\nif completed_process.returncode != 0:\n raise Exception(completed_process.stderr)\nsys.stderr.write(completed_process.stderr)",
"process = ... | <|body_start_0|>
completed_process = subprocess.run(command, shell=True, executable='/bin/bash', stdout=subprocess.PIPE, stderr=subprocess.PIPE, universal_newlines=True, timeout=timeout)
if completed_process.returncode != 0:
raise Exception(completed_process.stderr)
sys.stderr.write(... | Subprocess | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Subprocess:
def run(command: str, timeout: int=None) -> None:
"""Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. Returns: str: return stdout of the command."""
<|body_0|>
def interactive_run(command:... | stack_v2_sparse_classes_36k_train_006996 | 19,871 | permissive | [
{
"docstring": "Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. Returns: str: return stdout of the command.",
"name": "run",
"signature": "def run(command: str, timeout: int=None) -> None"
},
{
"docstring": "Run one-time... | 2 | null | Implement the Python class `Subprocess` described below.
Class description:
Implement the Subprocess class.
Method signatures and docstrings:
- def run(command: str, timeout: int=None) -> None: Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. ... | Implement the Python class `Subprocess` described below.
Class description:
Implement the Subprocess class.
Method signatures and docstrings:
- def run(command: str, timeout: int=None) -> None: Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. ... | b3c6a589ad9036b03221e776a6929b2bc1eb4680 | <|skeleton|>
class Subprocess:
def run(command: str, timeout: int=None) -> None:
"""Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. Returns: str: return stdout of the command."""
<|body_0|>
def interactive_run(command:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Subprocess:
def run(command: str, timeout: int=None) -> None:
"""Run one-time command with subprocess.run(). Args: command (str): command to be executed. timeout (int): timeout in seconds. Returns: str: return stdout of the command."""
completed_process = subprocess.run(command, shell=True, ex... | the_stack_v2_python_sparse | maro/cli/grass/lib/scripts/node/join_cluster.py | microsoft/maro | train | 764 | |
9f2ad0541d077cdc022c8560ee1189941ff9936c | [
"super(ConvNet, self).__init__()\nif norm_layer is None:\n norm_layer = nn.BatchNorm1d\nself._norm_layer = norm_layer\nif act_layer is None:\n act_layer = nn.ReLU\nself._act_layer = act_layer\nself.conv1 = conv3x3(1, 16, stride=1)\nself.bn1 = norm_layer(16)\nself.stack1 = self._make_stack(block=block, num_lay... | <|body_start_0|>
super(ConvNet, self).__init__()
if norm_layer is None:
norm_layer = nn.BatchNorm1d
self._norm_layer = norm_layer
if act_layer is None:
act_layer = nn.ReLU
self._act_layer = act_layer
self.conv1 = conv3x3(1, 16, stride=1)
se... | Basic CNN architecture | ConvNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvNet:
"""Basic CNN architecture"""
def __init__(self, block, layers, latent_dim=512, norm_layer=None, act_layer=None):
"""Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of integers specifying number of blocks per stack latent_dim... | stack_v2_sparse_classes_36k_train_006997 | 8,913 | permissive | [
{
"docstring": "Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of integers specifying number of blocks per stack latent_dim: (int) dimension of latent space at network output; default = 512 norm_layer: (nn.Module) normalization layer; default = nn.BatchNorm2d ... | 3 | stack_v2_sparse_classes_30k_train_003622 | Implement the Python class `ConvNet` described below.
Class description:
Basic CNN architecture
Method signatures and docstrings:
- def __init__(self, block, layers, latent_dim=512, norm_layer=None, act_layer=None): Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of ... | Implement the Python class `ConvNet` described below.
Class description:
Basic CNN architecture
Method signatures and docstrings:
- def __init__(self, block, layers, latent_dim=512, norm_layer=None, act_layer=None): Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of ... | 3ad344901c3bb59e0bc16bb70202d2cfd538fd77 | <|skeleton|>
class ConvNet:
"""Basic CNN architecture"""
def __init__(self, block, layers, latent_dim=512, norm_layer=None, act_layer=None):
"""Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of integers specifying number of blocks per stack latent_dim... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvNet:
"""Basic CNN architecture"""
def __init__(self, block, layers, latent_dim=512, norm_layer=None, act_layer=None):
"""Constructor Args: block: (nn.Module) building block; e.g., BasicBlock layers: (list of int) a list of integers specifying number of blocks per stack latent_dim: (int) dimen... | the_stack_v2_python_sparse | baselines/common/networks/cnn.py | baihuaxie/drl-lib | train | 0 |
a8c65985642d78ae4385c6e60a77420651827446 | [
"input_json = request.data\noutput_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))\njson_params = dict(zip(['profile_id'], [input_json['SessionDetails']['Payl... | <|body_start_0|>
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetails', 'SessionDetails', 'Payload'], [input_json['AvailabilityDetails'], input_json['AuthenticationDetails'], input_json['SessionDetails'], None]))
json_params = dict(zip(['profile_id'], [... | This covers the API for checking if the given user is a staff | CheckIfUserIsStaffAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CheckIfUserIsStaffAPI:
"""This covers the API for checking if the given user is a staff"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
<|body_0|>
def check_if_user_is_staff_json(self, request):
"""This function ... | stack_v2_sparse_classes_36k_train_006998 | 2,530 | no_license | [
{
"docstring": "Post Function to fetching common questions based on ticket type.",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "This function checks if the given user is a staff :param request: { 'profile_id': 1, } :return:",
"name": "check_if_user_is_staff_json"... | 2 | null | Implement the Python class `CheckIfUserIsStaffAPI` described below.
Class description:
This covers the API for checking if the given user is a staff
Method signatures and docstrings:
- def post(self, request): Post Function to fetching common questions based on ticket type.
- def check_if_user_is_staff_json(self, req... | Implement the Python class `CheckIfUserIsStaffAPI` described below.
Class description:
This covers the API for checking if the given user is a staff
Method signatures and docstrings:
- def post(self, request): Post Function to fetching common questions based on ticket type.
- def check_if_user_is_staff_json(self, req... | 36eb9931f330e64902354c6fc471be2adf4b7049 | <|skeleton|>
class CheckIfUserIsStaffAPI:
"""This covers the API for checking if the given user is a staff"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
<|body_0|>
def check_if_user_is_staff_json(self, request):
"""This function ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CheckIfUserIsStaffAPI:
"""This covers the API for checking if the given user is a staff"""
def post(self, request):
"""Post Function to fetching common questions based on ticket type."""
input_json = request.data
output_json = dict(zip(['AvailabilityDetails', 'AuthenticationDetail... | the_stack_v2_python_sparse | Generic/common/staffmanagement/staffregister/api/check_if_user_is_staff/views_check_if_user_is_staff.py | archiemb303/common_backend_django | train | 0 |
3223b6213e3c4b993236badffbb571ffe02689c6 | [
"if not l1:\n return l2\nif not l2:\n return l1\nif l1.val < l2.val:\n l1.next = self.mergeTwoLists(l1.next, l2)\n return l1\nelse:\n l2.next = self.mergeTwoLists(l1, l2.next)\n return l2",
"dummy = ListNode(None)\nprev = dummy\nwhile l1 and l2:\n if l1.val < l2.val:\n prev.next = l1\n... | <|body_start_0|>
if not l1:
return l2
if not l2:
return l1
if l1.val < l2.val:
l1.next = self.mergeTwoLists(l1.next, l2)
return l1
else:
l2.next = self.mergeTwoLists(l1, l2.next)
return l2
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""1. 递归："""
<|body_0|>
def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode:
"""2. 迭代 KEY：定义一个辅助的前置节点指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not l... | stack_v2_sparse_classes_36k_train_006999 | 1,949 | no_license | [
{
"docstring": "1. 递归：",
"name": "mergeTwoLists_1",
"signature": "def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode"
},
{
"docstring": "2. 迭代 KEY：定义一个辅助的前置节点指针",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode: 1. 递归：
- def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode: 2. 迭代 KEY：定义一个辅助的前置节点指针 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode: 1. 递归：
- def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode: 2. 迭代 KEY：定义一个辅助的前置节点指针
<|skeleton|>... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""1. 递归："""
<|body_0|>
def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode:
"""2. 迭代 KEY：定义一个辅助的前置节点指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists_1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""1. 递归："""
if not l1:
return l2
if not l2:
return l1
if l1.val < l2.val:
l1.next = self.mergeTwoLists(l1.next, l2)
return l1
else:
... | the_stack_v2_python_sparse | 02-linkedlist/21.合并两个有序链表.py | xiaoruijiang/algorithm | train | 0 |
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