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
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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
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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a1dc0b4495f5c42e902b569b99aa5c776bcb9290 | [
"self = cls()\nfor value in values:\n self.add(value)\nreturn self",
"path = value if isinstance(value, Path) else Path(str(value))\nsubtree = self\nfor part in path.parts:\n try:\n subtree = subtree[part]\n except KeyError:\n return default\nreturn subtree",
"path = value if isinstance(v... | <|body_start_0|>
self = cls()
for value in values:
self.add(value)
return self
<|end_body_0|>
<|body_start_1|>
path = value if isinstance(value, Path) else Path(str(value))
subtree = self
for part in path.parts:
try:
subtree = subt... | Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) a/b/c/d x/y/z x/y/zz >>> print('\\n'.join(sorted(directory.get('x/y')))) z zz | DirectoryTree | [
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DirectoryTree:
"""Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) a/b/c/d x/y/z x/y/zz >>> print('\\n'.jo... | stack_v2_sparse_classes_36k_train_008900 | 2,754 | permissive | [
{
"docstring": "Construct a tree from a list with paths.",
"name": "from_list",
"signature": "def from_list(cls, values)"
},
{
"docstring": "Return a subtree if exists.",
"name": "get",
"signature": "def get(self, value, default=None)"
},
{
"docstring": "Create a safe directory f... | 4 | null | Implement the Python class `DirectoryTree` described below.
Class description:
Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) ... | Implement the Python class `DirectoryTree` described below.
Class description:
Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) ... | e0ff587f507d049eeeb873e8488ba8bb10ac1a15 | <|skeleton|>
class DirectoryTree:
"""Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) a/b/c/d x/y/z x/y/zz >>> print('\\n'.jo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DirectoryTree:
"""Create a safe directory tree from paths. Example usage: >>> directory = DirectoryTree() >>> directory.add('a/b/c') >>> directory.add('a/b/c/d') >>> directory.add('x/y/z') >>> directory.add('x/y/zz') >>> print('\\n'.join(sorted(directory))) a/b/c/d x/y/z x/y/zz >>> print('\\n'.join(sorted(dir... | the_stack_v2_python_sparse | renku/domain_model/datastructures.py | SwissDataScienceCenter/renku-python | train | 30 |
709b7a281bac1f3d1f7541e5bddaa9a7e7cf4786 | [
"super(FourierFineCoattention, self).__init__()\nwith self.init_scope():\n self.energy_layer = links.Bilinear(hidden_dim, hidden_dim, 1)\n self.attention_layer_1 = GraphLinear(head, 1, nobias=True)\n self.attention_layer_2 = GraphLinear(head, 1, nobias=True)\n self.lt_layer_1 = GraphLinear(hidden_dim, h... | <|body_start_0|>
super(FourierFineCoattention, self).__init__()
with self.init_scope():
self.energy_layer = links.Bilinear(hidden_dim, hidden_dim, 1)
self.attention_layer_1 = GraphLinear(head, 1, nobias=True)
self.attention_layer_2 = GraphLinear(head, 1, nobias=True)
... | TODO | FourierFineCoattention | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FourierFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
... | stack_v2_sparse_classes_36k_train_008901 | 25,561 | permissive | [
{
"docstring": ":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism",
"name": "__init__",
"signature": "def __init__(self, hidden_dim, out_dim, head, activation=functions.identity)"
},
{
"do... | 4 | stack_v2_sparse_classes_30k_train_011129 | Implement the Python class `FourierFineCoattention` described below.
Class description:
TODO
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, activation=functions.identity): :param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :para... | Implement the Python class `FourierFineCoattention` described below.
Class description:
TODO
Method signatures and docstrings:
- def __init__(self, hidden_dim, out_dim, head, activation=functions.identity): :param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :para... | 21b64a3c8cc9bc33718ae09c65aa917e575132eb | <|skeleton|>
class FourierFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FourierFineCoattention:
"""TODO"""
def __init__(self, hidden_dim, out_dim, head, activation=functions.identity):
""":param hidden_dim: dimension of atom representation :param out_dim: dimension of molecular representation :param head: number of heads in attention mechanism"""
super(Fourie... | the_stack_v2_python_sparse | models/coattention/nie_coattention.py | Minys233/GCN-BMP | train | 1 |
f0bdc18bbdc65c9e968d24215b8e50bef2352cc7 | [
"super(Conv2dSubsampling1, self).__init__()\nself.conv = torch.nn.Sequential(torch.nn.Conv2d(1, odim, 3, 1), torch.nn.ReLU(), torch.nn.Conv2d(odim, odim, 3, 1), torch.nn.ReLU())\nself.out = torch.nn.Sequential(torch.nn.Linear(odim * (idim - 4), odim), pos_enc if pos_enc is not None else PositionalEncoding(odim, dro... | <|body_start_0|>
super(Conv2dSubsampling1, self).__init__()
self.conv = torch.nn.Sequential(torch.nn.Conv2d(1, odim, 3, 1), torch.nn.ReLU(), torch.nn.Conv2d(odim, odim, 3, 1), torch.nn.ReLU())
self.out = torch.nn.Sequential(torch.nn.Linear(odim * (idim - 4), odim), pos_enc if pos_enc is not None... | Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer. | Conv2dSubsampling1 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv2dSubsampling1:
"""Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim,... | stack_v2_sparse_classes_36k_train_008902 | 14,351 | permissive | [
{
"docstring": "Construct an Conv2dSubsampling1 object.",
"name": "__init__",
"signature": "def __init__(self, idim, odim, dropout_rate, pos_enc=None)"
},
{
"docstring": "Pass x through 2 Conv2d layers without subsampling. Args: x (torch.Tensor): Input tensor (#batch, time, idim). x_mask (torch.... | 3 | null | Implement the Python class `Conv2dSubsampling1` described below.
Class description:
Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.... | Implement the Python class `Conv2dSubsampling1` described below.
Class description:
Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class Conv2dSubsampling1:
"""Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv2dSubsampling1:
"""Similar to Conv2dSubsampling module, but without any subsampling performed. Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/transformer/subsampling.py | espnet/espnet | train | 7,242 |
c450d5fab34c11f348247928e4c22920bcaf43cf | [
"rows = len(matrix)\ncols = len(matrix[0])\nlens = [[-1] * cols for _ in range(rows)]\nmax_path = 0\nfor row in range(rows):\n for col in range(cols):\n max_path = max(max_path, self.longest_increasing_path_core(matrix, rows, cols, row, col, lens))\nreturn max_path + 1",
"if lens[row][col] != -1:\n r... | <|body_start_0|>
rows = len(matrix)
cols = len(matrix[0])
lens = [[-1] * cols for _ in range(rows)]
max_path = 0
for row in range(rows):
for col in range(cols):
max_path = max(max_path, self.longest_increasing_path_core(matrix, rows, cols, row, col, le... | 给定一个整数矩阵,找到增加最长路径的长度。 | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""给定一个整数矩阵,找到增加最长路径的长度。"""
def longest_increasing_path(self, matrix):
"""对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度"""
<|body_0|>
def longest_increasing_path_core(self, matrix, rows, cols, row, col, lens):
"""寻找四个方向上的最大路径 :param matrix: 整数矩阵... | stack_v2_sparse_classes_36k_train_008903 | 3,070 | no_license | [
{
"docstring": "对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度",
"name": "longest_increasing_path",
"signature": "def longest_increasing_path(self, matrix)"
},
{
"docstring": "寻找四个方向上的最大路径 :param matrix: 整数矩阵 :param rows: 行数 :param cols: 列数 :param row: 当前行 :param col: 当前列 :param lens: 动态规... | 2 | null | Implement the Python class `Solution` described below.
Class description:
给定一个整数矩阵,找到增加最长路径的长度。
Method signatures and docstrings:
- def longest_increasing_path(self, matrix): 对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度
- def longest_increasing_path_core(self, matrix, rows, cols, row, col, lens): 寻找四个方向上的最大路... | Implement the Python class `Solution` described below.
Class description:
给定一个整数矩阵,找到增加最长路径的长度。
Method signatures and docstrings:
- def longest_increasing_path(self, matrix): 对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度
- def longest_increasing_path_core(self, matrix, rows, cols, row, col, lens): 寻找四个方向上的最大路... | 9fdc4b1a2b59b7aed22ddfe92aade487b4c19b71 | <|skeleton|>
class Solution:
"""给定一个整数矩阵,找到增加最长路径的长度。"""
def longest_increasing_path(self, matrix):
"""对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度"""
<|body_0|>
def longest_increasing_path_core(self, matrix, rows, cols, row, col, lens):
"""寻找四个方向上的最大路径 :param matrix: 整数矩阵... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""给定一个整数矩阵,找到增加最长路径的长度。"""
def longest_increasing_path(self, matrix):
"""对矩阵中的每一个坐标计算最远距离 :param matrix: 整数矩阵 :return: 最长路径的长度"""
rows = len(matrix)
cols = len(matrix[0])
lens = [[-1] * cols for _ in range(rows)]
max_path = 0
for row in range(row... | the_stack_v2_python_sparse | interview_coding/longest_increasing_path.py | MemoryForSky/Data-Structures-and-Algorithms | train | 0 |
78d5677e32e6b588b32f33b38158759f6a2a96bf | [
"if dispositivo_id:\n dispositivo = Dispositivo.objects.get(pk=dispositivo_id)\n form = FormDispositivo(instance=dispositivo)\nelse:\n form = FormDispositivo()\nreturn render(request, self.template, {'form': form})",
"if dispositivo_id:\n dispositivo = Dispositivo.objects.get(pk=dispositivo_id)\n f... | <|body_start_0|>
if dispositivo_id:
dispositivo = Dispositivo.objects.get(pk=dispositivo_id)
form = FormDispositivo(instance=dispositivo)
else:
form = FormDispositivo()
return render(request, self.template, {'form': form})
<|end_body_0|>
<|body_start_1|>
... | Cadastra os dispositivos | CadastroDispositivoView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CadastroDispositivoView:
"""Cadastra os dispositivos"""
def get(self, request, dispositivo_id=None):
"""Cria um formulário para cadastrar o dispositivo"""
<|body_0|>
def post(self, request, dispositivo_id=None):
"""Envia para o servidor os dispositivos cadastrado... | stack_v2_sparse_classes_36k_train_008904 | 5,983 | no_license | [
{
"docstring": "Cria um formulário para cadastrar o dispositivo",
"name": "get",
"signature": "def get(self, request, dispositivo_id=None)"
},
{
"docstring": "Envia para o servidor os dispositivos cadastrados",
"name": "post",
"signature": "def post(self, request, dispositivo_id=None)"
... | 2 | null | Implement the Python class `CadastroDispositivoView` described below.
Class description:
Cadastra os dispositivos
Method signatures and docstrings:
- def get(self, request, dispositivo_id=None): Cria um formulário para cadastrar o dispositivo
- def post(self, request, dispositivo_id=None): Envia para o servidor os di... | Implement the Python class `CadastroDispositivoView` described below.
Class description:
Cadastra os dispositivos
Method signatures and docstrings:
- def get(self, request, dispositivo_id=None): Cria um formulário para cadastrar o dispositivo
- def post(self, request, dispositivo_id=None): Envia para o servidor os di... | 7b799a71380aca342e879c5556cc24fcebdac1ca | <|skeleton|>
class CadastroDispositivoView:
"""Cadastra os dispositivos"""
def get(self, request, dispositivo_id=None):
"""Cria um formulário para cadastrar o dispositivo"""
<|body_0|>
def post(self, request, dispositivo_id=None):
"""Envia para o servidor os dispositivos cadastrado... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CadastroDispositivoView:
"""Cadastra os dispositivos"""
def get(self, request, dispositivo_id=None):
"""Cria um formulário para cadastrar o dispositivo"""
if dispositivo_id:
dispositivo = Dispositivo.objects.get(pk=dispositivo_id)
form = FormDispositivo(instance=di... | the_stack_v2_python_sparse | detransapp/views/dispositivo.py | brunowber/transnote2 | train | 0 |
3d354a435b6c318cfdcc7ee2be0ccc91f1e7aba6 | [
"self.user = kwargs.pop('user', None)\nself.question = kwargs.pop('question', None)\nsuper(KitsuneBaseForumForm, self).__init__(*args, **kwargs)",
"cdata = self.cleaned_data.get('content')\nif not cdata:\n return super(KitsuneBaseForumForm, self).clean(*args, **kwargs)\nif not self.user:\n raise forms.Valid... | <|body_start_0|>
self.user = kwargs.pop('user', None)
self.question = kwargs.pop('question', None)
super(KitsuneBaseForumForm, self).__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
cdata = self.cleaned_data.get('content')
if not cdata:
return super(KitsuneB... | Base form suitable for all the project. Mainly adds a common clean method to deal with spam. | KitsuneBaseForumForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KitsuneBaseForumForm:
"""Base form suitable for all the project. Mainly adds a common clean method to deal with spam."""
def __init__(self, *args, **kwargs):
"""Override init method to get the user if possible."""
<|body_0|>
def clean(self, *args, **kwargs):
"""G... | stack_v2_sparse_classes_36k_train_008905 | 1,419 | permissive | [
{
"docstring": "Override init method to get the user if possible.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Generic clean method used by all forms in the question app. Parse content for suspicious content. - Toll free numbers - NANP numbers - Lin... | 2 | stack_v2_sparse_classes_30k_train_010313 | Implement the Python class `KitsuneBaseForumForm` described below.
Class description:
Base form suitable for all the project. Mainly adds a common clean method to deal with spam.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Override init method to get the user if possible.
- def clean(self... | Implement the Python class `KitsuneBaseForumForm` described below.
Class description:
Base form suitable for all the project. Mainly adds a common clean method to deal with spam.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Override init method to get the user if possible.
- def clean(self... | 67ec527bfc32c715bf9f29d5e01362c4903aebd2 | <|skeleton|>
class KitsuneBaseForumForm:
"""Base form suitable for all the project. Mainly adds a common clean method to deal with spam."""
def __init__(self, *args, **kwargs):
"""Override init method to get the user if possible."""
<|body_0|>
def clean(self, *args, **kwargs):
"""G... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KitsuneBaseForumForm:
"""Base form suitable for all the project. Mainly adds a common clean method to deal with spam."""
def __init__(self, *args, **kwargs):
"""Override init method to get the user if possible."""
self.user = kwargs.pop('user', None)
self.question = kwargs.pop('qu... | the_stack_v2_python_sparse | kitsune/sumo/forms.py | mozilla/kitsune | train | 1,218 |
5f45935372d3cb33d0e21d88a390bcc90e986189 | [
"super(Darknet, self).__init__()\nself.in_channels = in_ch\nself.batch_norm = batch_norm\nself.filters = filters\nself.stride_out_1 = 32\nself.stride_out_2 = 16\nself.stride_out_3 = 8\nindex = 0\nself.first_index = 0\nself.conv0 = DarknetConvBlock(self.in_channels, self.filters, kernel_size=3, stride=1, padding=1, ... | <|body_start_0|>
super(Darknet, self).__init__()
self.in_channels = in_ch
self.batch_norm = batch_norm
self.filters = filters
self.stride_out_1 = 32
self.stride_out_2 = 16
self.stride_out_3 = 8
index = 0
self.first_index = 0
self.conv0 = Da... | Darknet body class | Darknet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Darknet:
"""Darknet body class"""
def __init__(self, in_ch, filters=32, batch_norm=True):
"""Constructor"""
<|body_0|>
def forward(self, x):
"""Foward method"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(Darknet, self).__init__()
... | stack_v2_sparse_classes_36k_train_008906 | 28,014 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, in_ch, filters=32, batch_norm=True)"
},
{
"docstring": "Foward method",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000835 | Implement the Python class `Darknet` described below.
Class description:
Darknet body class
Method signatures and docstrings:
- def __init__(self, in_ch, filters=32, batch_norm=True): Constructor
- def forward(self, x): Foward method | Implement the Python class `Darknet` described below.
Class description:
Darknet body class
Method signatures and docstrings:
- def __init__(self, in_ch, filters=32, batch_norm=True): Constructor
- def forward(self, x): Foward method
<|skeleton|>
class Darknet:
"""Darknet body class"""
def __init__(self, in... | 69edb5ecd569395086cf610df9c8aa345284259a | <|skeleton|>
class Darknet:
"""Darknet body class"""
def __init__(self, in_ch, filters=32, batch_norm=True):
"""Constructor"""
<|body_0|>
def forward(self, x):
"""Foward method"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Darknet:
"""Darknet body class"""
def __init__(self, in_ch, filters=32, batch_norm=True):
"""Constructor"""
super(Darknet, self).__init__()
self.in_channels = in_ch
self.batch_norm = batch_norm
self.filters = filters
self.stride_out_1 = 32
self.stri... | the_stack_v2_python_sparse | python/models/modules.py | dswanderley/detntorch | train | 2 |
bdda34ac8938f7fc69fa465bf05ff900881b795e | [
"Parametre.__init__(self, 'info', 'info')\nself.schema = '<cle>'\nself.aide_courte = \"affiche des informations sur l'étendue\"\nself.aide_longue = \"Affiche des informations sur l'étendue d'eau précisée en paramètre, comme ses obstacles, côtes et liens. Les obstacles sont des points neutres de l'étendue, pouvant r... | <|body_start_0|>
Parametre.__init__(self, 'info', 'info')
self.schema = '<cle>'
self.aide_courte = "affiche des informations sur l'étendue"
self.aide_longue = "Affiche des informations sur l'étendue d'eau précisée en paramètre, comme ses obstacles, côtes et liens. Les obstacles sont des ... | Commande 'etendue info'. | PrmInfo | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrmInfo:
"""Commande 'etendue info'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Parametre.__ini... | stack_v2_sparse_classes_36k_train_008907 | 4,018 | permissive | [
{
"docstring": "Constructeur du paramètre",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Interprétation du paramètre",
"name": "interpreter",
"signature": "def interpreter(self, personnage, dic_masques)"
}
] | 2 | null | Implement the Python class `PrmInfo` described below.
Class description:
Commande 'etendue info'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre | Implement the Python class `PrmInfo` described below.
Class description:
Commande 'etendue info'.
Method signatures and docstrings:
- def __init__(self): Constructeur du paramètre
- def interpreter(self, personnage, dic_masques): Interprétation du paramètre
<|skeleton|>
class PrmInfo:
"""Commande 'etendue info'.... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class PrmInfo:
"""Commande 'etendue info'."""
def __init__(self):
"""Constructeur du paramètre"""
<|body_0|>
def interpreter(self, personnage, dic_masques):
"""Interprétation du paramètre"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrmInfo:
"""Commande 'etendue info'."""
def __init__(self):
"""Constructeur du paramètre"""
Parametre.__init__(self, 'info', 'info')
self.schema = '<cle>'
self.aide_courte = "affiche des informations sur l'étendue"
self.aide_longue = "Affiche des informations sur l... | the_stack_v2_python_sparse | src/primaires/salle/commandes/etendue/info.py | vincent-lg/tsunami | train | 5 |
752fee9382a1ce1515fe484109a916e1d8964cd3 | [
"if hasattr(measurement_model, 'inverse_covar'):\n inv_measurement_covar = measurement_model.inverse_covar(**kwargs)\nelse:\n inv_measurement_covar = np.linalg.inv(measurement_model.covar(**kwargs))\nreturn inv_measurement_covar",
"measurement_model = self._check_measurement_model(measurement_model)\nhh = s... | <|body_start_0|>
if hasattr(measurement_model, 'inverse_covar'):
inv_measurement_covar = measurement_model.inverse_covar(**kwargs)
else:
inv_measurement_covar = np.linalg.inv(measurement_model.covar(**kwargs))
return inv_measurement_covar
<|end_body_0|>
<|body_start_1|>
... | A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} + H^{T}_k R^{-1}_k \\mathbf{z}_{k} where :math:`\\mathbf{y}_{k|k-1}` is the predicted infor... | InformationKalmanUpdater | [
"LicenseRef-scancode-proprietary-license",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"Python-2.0",
"LicenseRef-scancode-secret-labs-2011"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InformationKalmanUpdater:
"""A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} + H^{T}_k R^{-1}_k \\mathbf{z}_{k} wher... | stack_v2_sparse_classes_36k_train_008908 | 6,014 | permissive | [
{
"docstring": "Return the inverse of the measurement covariance (or calculate it) Parameters ---------- measurement_model The measurement model to be queried **kwargs : various, optional These are passed to :meth:`~.LinearGaussian.covar()` Returns ------- : :class:`numpy.ndarray` The inverse of the measurement... | 3 | stack_v2_sparse_classes_30k_train_008338 | Implement the Python class `InformationKalmanUpdater` described below.
Class description:
A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} ... | Implement the Python class `InformationKalmanUpdater` described below.
Class description:
A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} ... | f24090cc919b3b590b84f965a3884ed1293d181d | <|skeleton|>
class InformationKalmanUpdater:
"""A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} + H^{T}_k R^{-1}_k \\mathbf{z}_{k} wher... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InformationKalmanUpdater:
"""A class which implements the update of information form of the Kalman filter. This is conceptually very simple. The update proceeds as: .. math:: Y_{k|k} = Y_{k|k-1} + H^{T}_k R^{-1}_k H_k \\mathbf{y}_{k|k} = \\mathbf{y}_{k|k-1} + H^{T}_k R^{-1}_k \\mathbf{z}_{k} where :math:`\\ma... | the_stack_v2_python_sparse | stonesoup/updater/information.py | dstl/Stone-Soup | train | 315 |
9e4048e89c0a57b3e4d57720b05b91fb7846363f | [
"super(MultiHeadedAttention, self).__init__()\nassert n_feat % n_head == 0\nself.d_k = n_feat // n_head\nself.h = n_head\nself.linear_q = torch.nn.Linear(q_dim, n_feat)\nself.linear_k = torch.nn.Linear(k_dim, n_feat)\nself.linear_v = torch.nn.Linear(v_dim, n_feat)\nself.linear_out = torch.nn.Linear(n_feat, n_feat)\... | <|body_start_0|>
super(MultiHeadedAttention, self).__init__()
assert n_feat % n_head == 0
self.d_k = n_feat // n_head
self.h = n_head
self.linear_q = torch.nn.Linear(q_dim, n_feat)
self.linear_k = torch.nn.Linear(k_dim, n_feat)
self.linear_v = torch.nn.Linear(v_di... | Multi head attention module with different input dimension. | MultiHeadedAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiHeadedAttention:
"""Multi head attention module with different input dimension."""
def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0):
"""Initialize multi head attention module."""
<|body_0|>
def forward_qkv(self, query, key, value):
"... | stack_v2_sparse_classes_36k_train_008909 | 6,388 | no_license | [
{
"docstring": "Initialize multi head attention module.",
"name": "__init__",
"signature": "def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0)"
},
{
"docstring": "Transform query, key and value. Args: query (torch.Tensor): Query tensor (#batch, time1, size). key (torch.Ten... | 4 | null | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Multi head attention module with different input dimension.
Method signatures and docstrings:
- def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0): Initialize multi head attention module.
- def forward_qkv(sel... | Implement the Python class `MultiHeadedAttention` described below.
Class description:
Multi head attention module with different input dimension.
Method signatures and docstrings:
- def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0): Initialize multi head attention module.
- def forward_qkv(sel... | b8365ea023e75cb69d84466319dd682726908320 | <|skeleton|>
class MultiHeadedAttention:
"""Multi head attention module with different input dimension."""
def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0):
"""Initialize multi head attention module."""
<|body_0|>
def forward_qkv(self, query, key, value):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiHeadedAttention:
"""Multi head attention module with different input dimension."""
def __init__(self, q_dim, k_dim, v_dim, n_head, n_feat, dropout_rate=0.0):
"""Initialize multi head attention module."""
super(MultiHeadedAttention, self).__init__()
assert n_feat % n_head == 0... | the_stack_v2_python_sparse | vae_npvc/model/layers_gst.py | Sinica-SLAM/vae_npvc | train | 1 |
bd3ffce8f8f65094804a0236b96ac7d1da1d6cfe | [
"self.config = config_\nself.logger = logging.getLogger('cuda_logger')\nself.radius = self.config['RL_parameters']['neighborhood_radius']",
"self.logger.info('Starting job: NeighborhoodDataExportJob\\n')\ndata_provider = DataProvider(self.config)\ndata_exporter = DataExporter(self.config)\nhex_attr_df = data_prov... | <|body_start_0|>
self.config = config_
self.logger = logging.getLogger('cuda_logger')
self.radius = self.config['RL_parameters']['neighborhood_radius']
<|end_body_0|>
<|body_start_1|>
self.logger.info('Starting job: NeighborhoodDataExportJob\n')
data_provider = DataProvider(self... | This class implements a job to export the neighborhood data | NeighborhoodDataExportJob | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeighborhoodDataExportJob:
"""This class implements a job to export the neighborhood data"""
def __init__(self, config_):
"""Constructor :param config_: :param viz_name: :return:"""
<|body_0|>
def run(self):
"""This method executes the job :param: :return:"""
... | stack_v2_sparse_classes_36k_train_008910 | 1,581 | no_license | [
{
"docstring": "Constructor :param config_: :param viz_name: :return:",
"name": "__init__",
"signature": "def __init__(self, config_)"
},
{
"docstring": "This method executes the job :param: :return:",
"name": "run",
"signature": "def run(self)"
}
] | 2 | null | Implement the Python class `NeighborhoodDataExportJob` described below.
Class description:
This class implements a job to export the neighborhood data
Method signatures and docstrings:
- def __init__(self, config_): Constructor :param config_: :param viz_name: :return:
- def run(self): This method executes the job :p... | Implement the Python class `NeighborhoodDataExportJob` described below.
Class description:
This class implements a job to export the neighborhood data
Method signatures and docstrings:
- def __init__(self, config_): Constructor :param config_: :param viz_name: :return:
- def run(self): This method executes the job :p... | f7fcd2cc1d6ba18b199d176d4d39193f025ee281 | <|skeleton|>
class NeighborhoodDataExportJob:
"""This class implements a job to export the neighborhood data"""
def __init__(self, config_):
"""Constructor :param config_: :param viz_name: :return:"""
<|body_0|>
def run(self):
"""This method executes the job :param: :return:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeighborhoodDataExportJob:
"""This class implements a job to export the neighborhood data"""
def __init__(self, config_):
"""Constructor :param config_: :param viz_name: :return:"""
self.config = config_
self.logger = logging.getLogger('cuda_logger')
self.radius = self.con... | the_stack_v2_python_sparse | learn_to_earn_framework/jobs/export_neighborhood_data.py | transparent-framework/optimize-ride-sharing-earnings | train | 7 |
8bb32698a54f8e26798bc59451899e77a7dfe995 | [
"Thread.__init__(self)\nself.IP = IP\nself.scan_type = scan_type\nself.file = file\nself.connstr = ''\nself.scanresult = ''",
"try:\n cd = pyclamd.ClamdNetworkSocket(self.IP, 3310)\n if cd.ping():\n self.connstr = self.IP + ' Connection [OK]'\n cd.reload()\n if self.scan_type == 'contsc... | <|body_start_0|>
Thread.__init__(self)
self.IP = IP
self.scan_type = scan_type
self.file = file
self.connstr = ''
self.scanresult = ''
<|end_body_0|>
<|body_start_1|>
try:
cd = pyclamd.ClamdNetworkSocket(self.IP, 3310)
if cd.ping():
... | Scan | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Scan:
def __init__(self, IP, scan_type, file):
"""构造方法，参数初始化"""
<|body_0|>
def run(self):
"""多进程run方法"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Thread.__init__(self)
self.IP = IP
self.scan_type = scan_type
self.file = f... | stack_v2_sparse_classes_36k_train_008911 | 2,394 | no_license | [
{
"docstring": "构造方法，参数初始化",
"name": "__init__",
"signature": "def __init__(self, IP, scan_type, file)"
},
{
"docstring": "多进程run方法",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012783 | Implement the Python class `Scan` described below.
Class description:
Implement the Scan class.
Method signatures and docstrings:
- def __init__(self, IP, scan_type, file): 构造方法，参数初始化
- def run(self): 多进程run方法 | Implement the Python class `Scan` described below.
Class description:
Implement the Scan class.
Method signatures and docstrings:
- def __init__(self, IP, scan_type, file): 构造方法，参数初始化
- def run(self): 多进程run方法
<|skeleton|>
class Scan:
def __init__(self, IP, scan_type, file):
"""构造方法，参数初始化"""
<|b... | c77e518f8faaa832fda83f86d2ed594667bebe47 | <|skeleton|>
class Scan:
def __init__(self, IP, scan_type, file):
"""构造方法，参数初始化"""
<|body_0|>
def run(self):
"""多进程run方法"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Scan:
def __init__(self, IP, scan_type, file):
"""构造方法，参数初始化"""
Thread.__init__(self)
self.IP = IP
self.scan_type = scan_type
self.file = file
self.connstr = ''
self.scanresult = ''
def run(self):
"""多进程run方法"""
try:
cd =... | the_stack_v2_python_sparse | Python自动化运维/Chapter Four/pyClamad/sample.py | qq412607705/Python_test | train | 0 | |
cf63158ab3652d28bce03bdaf20dd7d8d59e90b9 | [
"super(ErrorWindow, self).__init__()\nmovieName = name\nerrorMessage = msg",
"size = getSize()\nfm = g.getFontMetrics()\ng.setColor(Color.WHITE)\ng.fillRect(0, 0, size.width, size.height)\ng.setColor(Color.BLACK)\nx = (size.width - fm.stringWidth(movieName)) / 2\ny = size.height / 2 - fm.getHeight()\ng.drawString... | <|body_start_0|>
super(ErrorWindow, self).__init__()
movieName = name
errorMessage = msg
<|end_body_0|>
<|body_start_1|>
size = getSize()
fm = g.getFontMetrics()
g.setColor(Color.WHITE)
g.fillRect(0, 0, size.width, size.height)
g.setColor(Color.BLACK)
... | generated source for class ErrorWindow | ErrorWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ErrorWindow:
"""generated source for class ErrorWindow"""
def __init__(self, name, msg):
"""generated source for method __init__"""
<|body_0|>
def paint(self, g):
"""generated source for method paint"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008912 | 28,432 | no_license | [
{
"docstring": "generated source for method __init__",
"name": "__init__",
"signature": "def __init__(self, name, msg)"
},
{
"docstring": "generated source for method paint",
"name": "paint",
"signature": "def paint(self, g)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000242 | Implement the Python class `ErrorWindow` described below.
Class description:
generated source for class ErrorWindow
Method signatures and docstrings:
- def __init__(self, name, msg): generated source for method __init__
- def paint(self, g): generated source for method paint | Implement the Python class `ErrorWindow` described below.
Class description:
generated source for class ErrorWindow
Method signatures and docstrings:
- def __init__(self, name, msg): generated source for method __init__
- def paint(self, g): generated source for method paint
<|skeleton|>
class ErrorWindow:
"""ge... | 5de73ee6d6945974083767c7bcbb650de08356de | <|skeleton|>
class ErrorWindow:
"""generated source for class ErrorWindow"""
def __init__(self, name, msg):
"""generated source for method __init__"""
<|body_0|>
def paint(self, g):
"""generated source for method paint"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ErrorWindow:
"""generated source for class ErrorWindow"""
def __init__(self, name, msg):
"""generated source for method __init__"""
super(ErrorWindow, self).__init__()
movieName = name
errorMessage = msg
def paint(self, g):
"""generated source for method paint... | the_stack_v2_python_sparse | ACM-Test/out/production/acm/out/production/acm/MovieClip.java.py | nrnoble/masterdirectory | train | 0 |
2fff010753645435909604d84fa60de82e44b05c | [
"layer.Layer.__init__(self, inputs, inputs, alpha)\nself.hiddens = hiddens\nself.previoushidden = None\nself.parameters['weightsin'] = numpy.random.normal(0.0, 1.0 / numpy.sqrt(self.inputs), (self.hiddens, self.inputs))\nself.parameters['weightsout'] = numpy.random.normal(0.0, 1.0 / numpy.sqrt(self.hiddens), (self.... | <|body_start_0|>
layer.Layer.__init__(self, inputs, inputs, alpha)
self.hiddens = hiddens
self.previoushidden = None
self.parameters['weightsin'] = numpy.random.normal(0.0, 1.0 / numpy.sqrt(self.inputs), (self.hiddens, self.inputs))
self.parameters['weightsout'] = numpy.random.no... | Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1 | AutoEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutoEncoder:
"""Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1"""
def __init__(self, inputs, hiddens, alpha=None, nonlinearity=None):
"""Constructor : param inputs : dimension of input (and reconstructed output) feature s... | stack_v2_sparse_classes_36k_train_008913 | 4,788 | no_license | [
{
"docstring": "Constructor : param inputs : dimension of input (and reconstructed output) feature space : param hiddens : dimension of compressed output feature space : param alpha : learning rate constant hyperparameter : param nonlinearity : transfer function applied after linear transformation of inputs",
... | 4 | stack_v2_sparse_classes_30k_val_000582 | Implement the Python class `AutoEncoder` described below.
Class description:
Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1
Method signatures and docstrings:
- def __init__(self, inputs, hiddens, alpha=None, nonlinearity=None): Constructor : param inputs ... | Implement the Python class `AutoEncoder` described below.
Class description:
Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1
Method signatures and docstrings:
- def __init__(self, inputs, hiddens, alpha=None, nonlinearity=None): Constructor : param inputs ... | 10ee6e2297b7a2e01165ef983ae34097d7178122 | <|skeleton|>
class AutoEncoder:
"""Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1"""
def __init__(self, inputs, hiddens, alpha=None, nonlinearity=None):
"""Constructor : param inputs : dimension of input (and reconstructed output) feature s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AutoEncoder:
"""Auto Encoder Layer Mathematically, f(x) = W2 * g(x) + b2 g(x)(i) = 1 / (1 + exp(-h(x)(i))) h(x) = W1 * x + b1"""
def __init__(self, inputs, hiddens, alpha=None, nonlinearity=None):
"""Constructor : param inputs : dimension of input (and reconstructed output) feature space : param ... | the_stack_v2_python_sparse | net/autoencoder.py | sunilmallya-work/NET | train | 0 |
3c4a028f08dfa7bbe5f28c94f95c77a77a16cd99 | [
"super(MultiheadAttentionContainer, self).__init__()\nself.nhead = nhead\nself.in_proj_container = in_proj_container\nself.attention_layer = attention_layer\nself.out_proj = out_proj\nself.attn_map = 0",
"tgt_len, src_len, bsz, embed_dim = (query.size(-3), key.size(-3), query.size(-2), query.size(-1))\nq, k, v = ... | <|body_start_0|>
super(MultiheadAttentionContainer, self).__init__()
self.nhead = nhead
self.in_proj_container = in_proj_container
self.attention_layer = attention_layer
self.out_proj = out_proj
self.attn_map = 0
<|end_body_0|>
<|body_start_1|>
tgt_len, src_len, ... | MultiheadAttentionContainer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiheadAttentionContainer:
def __init__(self, nhead, in_proj_container, attention_layer, out_proj):
"""A multi-head attention container Args: nhead: the number of heads in the multiheadattention model in_proj_container: A container of multi-head in-projection linear layers (a.k.a nn.Li... | stack_v2_sparse_classes_36k_train_008914 | 38,400 | permissive | [
{
"docstring": "A multi-head attention container Args: nhead: the number of heads in the multiheadattention model in_proj_container: A container of multi-head in-projection linear layers (a.k.a nn.Linear). attention_layer: The attention layer. out_proj: The multi-head out-projection layer (a.k.a nn.Linear). Exa... | 2 | null | Implement the Python class `MultiheadAttentionContainer` described below.
Class description:
Implement the MultiheadAttentionContainer class.
Method signatures and docstrings:
- def __init__(self, nhead, in_proj_container, attention_layer, out_proj): A multi-head attention container Args: nhead: the number of heads i... | Implement the Python class `MultiheadAttentionContainer` described below.
Class description:
Implement the MultiheadAttentionContainer class.
Method signatures and docstrings:
- def __init__(self, nhead, in_proj_container, attention_layer, out_proj): A multi-head attention container Args: nhead: the number of heads i... | feeab742e9c737c8e2b8b0e44d3efff4049f5847 | <|skeleton|>
class MultiheadAttentionContainer:
def __init__(self, nhead, in_proj_container, attention_layer, out_proj):
"""A multi-head attention container Args: nhead: the number of heads in the multiheadattention model in_proj_container: A container of multi-head in-projection linear layers (a.k.a nn.Li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiheadAttentionContainer:
def __init__(self, nhead, in_proj_container, attention_layer, out_proj):
"""A multi-head attention container Args: nhead: the number of heads in the multiheadattention model in_proj_container: A container of multi-head in-projection linear layers (a.k.a nn.Linear). attenti... | the_stack_v2_python_sparse | src/models/baselines/transformer.py | ColinAvrech/state-spaces | train | 0 | |
ed62a18590d04c2e0abd79169cc74f77220acd95 | [
"self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]\nself.weights = [2.5, 3.0, 3.5]\nfor i in range(0, 3):\n self.assertEqual(self.nuts[i]._Coconut__weight, self.weights[i], 'The weight is wrong')",
"varieties = [Coconut(variety) for variety in ['middle eastern', 'south... | <|body_start_0|>
self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]
self.weights = [2.5, 3.0, 3.5]
for i in range(0, 3):
self.assertEqual(self.nuts[i]._Coconut__weight, self.weights[i], 'The weight is wrong')
<|end_body_0|>
<|body_start_1|>
... | TestCoconuts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
<|body_0|>
def test_total_weight(self):
"""Tests that the sum of a specified number of coconuts of each type returned matches the expected total"""
<|bo... | stack_v2_sparse_classes_36k_train_008915 | 2,241 | no_license | [
{
"docstring": "Tests that different coconut types each have a different weight",
"name": "test_weight",
"signature": "def test_weight(self)"
},
{
"docstring": "Tests that the sum of a specified number of coconuts of each type returned matches the expected total",
"name": "test_total_weight"... | 3 | stack_v2_sparse_classes_30k_train_013812 | Implement the Python class `TestCoconuts` described below.
Class description:
Implement the TestCoconuts class.
Method signatures and docstrings:
- def test_weight(self): Tests that different coconut types each have a different weight
- def test_total_weight(self): Tests that the sum of a specified number of coconuts... | Implement the Python class `TestCoconuts` described below.
Class description:
Implement the TestCoconuts class.
Method signatures and docstrings:
- def test_weight(self): Tests that different coconut types each have a different weight
- def test_total_weight(self): Tests that the sum of a specified number of coconuts... | 4ca74dd054be17e7a57da891c5d239e3f915d3f1 | <|skeleton|>
class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
<|body_0|>
def test_total_weight(self):
"""Tests that the sum of a specified number of coconuts of each type returned matches the expected total"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCoconuts:
def test_weight(self):
"""Tests that different coconut types each have a different weight"""
self.nuts = [Coconut(variety) for variety in ['middle eastern', 'south asian', 'american']]
self.weights = [2.5, 3.0, 3.5]
for i in range(0, 3):
self.assertEqu... | the_stack_v2_python_sparse | Lesson 2 - Converting Data Into Structured Objects/project/attempt_1/test_coconuts.py | jmwoloso/Python_3 | train | 0 | |
8d87a8ca8530345d20eed9587cbdd4bf71b542d5 | [
"self.pipe = pipe\nself.event = event\nself.schema = event[3:]\nself.table = data[0]\nself.cmd = data[1]\nself.args = data[2]\nthreading.Thread.__init__(self)",
"dictdb = get_db(self.schema)\nassert hasattr(dictdb, self.cmd), \"'%(cmd)s' not a valid method of <type 'dict'>\" % self\nfunc = getattr(dictdb, self.cm... | <|body_start_0|>
self.pipe = pipe
self.event = event
self.schema = event[3:]
self.table = data[0]
self.cmd = data[1]
self.args = data[2]
threading.Thread.__init__(self)
<|end_body_0|>
<|body_start_1|>
dictdb = get_db(self.schema)
assert hasattr(di... | This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name. | DBHandler | [
"MIT",
"ISC",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBHandler:
"""This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name."""
def __init__(self, pipe, event, data):
"""Arguments: pipe: parent end of multiprocessin... | stack_v2_sparse_classes_36k_train_008916 | 2,757 | permissive | [
{
"docstring": "Arguments: pipe: parent end of multiprocessing.Pipe() event: database schema in form of string 'db-schema' or 'db=schema'. When '-' is used, the result is returned as a single transfer. When '=', an iterable is yielded and the data is transfered via the IPC pipe as a stream.",
"name": "__ini... | 2 | null | Implement the Python class `DBHandler` described below.
Class description:
This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name.
Method signatures and docstrings:
- def __init__(self, pipe, ev... | Implement the Python class `DBHandler` described below.
Class description:
This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name.
Method signatures and docstrings:
- def __init__(self, pipe, ev... | 730fe0e0dcbfba9bc818b665d86ebf1f0cc269fb | <|skeleton|>
class DBHandler:
"""This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name."""
def __init__(self, pipe, event, data):
"""Arguments: pipe: parent end of multiprocessin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBHandler:
"""This handler receives a "database command", in the form of a dictionary method name and its arguments, and the return value is sent to the session pipe with the same 'event' name."""
def __init__(self, pipe, event, data):
"""Arguments: pipe: parent end of multiprocessing.Pipe() even... | the_stack_v2_python_sparse | db.py | madberry/x84 | train | 0 |
14048504ec0bfa41af6dc6a8c20fcb6ac1f03952 | [
"self.state_manager = state_manager\nself.orchestrator = orchestrator\nself.extended = extended",
"health_check = HealthCheck()\ntry:\n now = self.state_manager.get_now()\n if now is None:\n raise Exception('None received from database for now()')\nexcept Exception:\n hcm = HealthCheckMessage(msg=... | <|body_start_0|>
self.state_manager = state_manager
self.orchestrator = orchestrator
self.extended = extended
<|end_body_0|>
<|body_start_1|>
health_check = HealthCheck()
try:
now = self.state_manager.get_now()
if now is None:
raise Except... | Returns Drydock health check status. | HealthCheckCombined | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HealthCheckCombined:
"""Returns Drydock health check status."""
def __init__(self, state_manager=None, orchestrator=None, extended=False):
"""Object initializer. :param orchestrator: instance of Drydock orchestrator"""
<|body_0|>
def get(self, req, resp):
"""Retu... | stack_v2_sparse_classes_36k_train_008917 | 4,455 | permissive | [
{
"docstring": "Object initializer. :param orchestrator: instance of Drydock orchestrator",
"name": "__init__",
"signature": "def __init__(self, state_manager=None, orchestrator=None, extended=False)"
},
{
"docstring": "Returns updated response with body if extended.",
"name": "get",
"si... | 2 | stack_v2_sparse_classes_30k_train_016910 | Implement the Python class `HealthCheckCombined` described below.
Class description:
Returns Drydock health check status.
Method signatures and docstrings:
- def __init__(self, state_manager=None, orchestrator=None, extended=False): Object initializer. :param orchestrator: instance of Drydock orchestrator
- def get(s... | Implement the Python class `HealthCheckCombined` described below.
Class description:
Returns Drydock health check status.
Method signatures and docstrings:
- def __init__(self, state_manager=None, orchestrator=None, extended=False): Object initializer. :param orchestrator: instance of Drydock orchestrator
- def get(s... | f99abfa4337f8cbb591513aac404b11208d4187c | <|skeleton|>
class HealthCheckCombined:
"""Returns Drydock health check status."""
def __init__(self, state_manager=None, orchestrator=None, extended=False):
"""Object initializer. :param orchestrator: instance of Drydock orchestrator"""
<|body_0|>
def get(self, req, resp):
"""Retu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HealthCheckCombined:
"""Returns Drydock health check status."""
def __init__(self, state_manager=None, orchestrator=None, extended=False):
"""Object initializer. :param orchestrator: instance of Drydock orchestrator"""
self.state_manager = state_manager
self.orchestrator = orchest... | the_stack_v2_python_sparse | python/drydock_provisioner/control/health.py | airshipit/drydock | train | 13 |
c015f7d1cb7f3ef62db3471c6959cb6cb2750a4b | [
"super(GateUnit, self).__init__()\nself.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)\nself.bn1 = nn.BatchNorm2d(in_feat)\nself.relu1 = nn.ReLU(inplace=True)\nself.conv2 = nn.Conv2d(in_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)\nself.bn2 = nn.BatchNorm2d(in... | <|body_start_0|>
super(GateUnit, self).__init__()
self.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm2d(in_feat)
self.relu1 = nn.ReLU(inplace=True)
self.conv2 = nn.Conv2d(in_feat, in_feat, kernel_size=3, padding=1, str... | GateUnit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
<|body_0|>
def forward(self, x1, x2):
"""x1 is smaller feature map"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(GateUnit, self)... | stack_v2_sparse_classes_36k_train_008918 | 29,670 | no_license | [
{
"docstring": "First is a smaller feature and second is a larger feature",
"name": "__init__",
"signature": "def __init__(self, in_feat, out_feat)"
},
{
"docstring": "x1 is smaller feature map",
"name": "forward",
"signature": "def forward(self, x1, x2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016161 | Implement the Python class `GateUnit` described below.
Class description:
Implement the GateUnit class.
Method signatures and docstrings:
- def __init__(self, in_feat, out_feat): First is a smaller feature and second is a larger feature
- def forward(self, x1, x2): x1 is smaller feature map | Implement the Python class `GateUnit` described below.
Class description:
Implement the GateUnit class.
Method signatures and docstrings:
- def __init__(self, in_feat, out_feat): First is a smaller feature and second is a larger feature
- def forward(self, x1, x2): x1 is smaller feature map
<|skeleton|>
class GateUn... | 23ab1cbe8a1e3f9d68ef774a51ce23eeff81aea9 | <|skeleton|>
class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
<|body_0|>
def forward(self, x1, x2):
"""x1 is smaller feature map"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
super(GateUnit, self).__init__()
self.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm2d(in_feat)
... | the_stack_v2_python_sparse | refinenet.py | JunhongXu/kaggle-carvana-car-masking | train | 1 | |
a1e487b2b9731d606624e3a2f3b6783e562ed98e | [
"self._io = IO_handler()\nself._phrase = self._io.hanle_in(phrase, encoding)\nself._word_count = None",
"if self._word_count is None:\n words = re.findall('\\\\w+', self._phrase.lower(), re.U)\n self._word_count = collections.Counter(self._io.handle_out(words))\nreturn self._word_count"
] | <|body_start_0|>
self._io = IO_handler()
self._phrase = self._io.hanle_in(phrase, encoding)
self._word_count = None
<|end_body_0|>
<|body_start_1|>
if self._word_count is None:
words = re.findall('\\w+', self._phrase.lower(), re.U)
self._word_count = collections.... | Phrase abstraction with word counter. | Phrase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Phrase:
"""Phrase abstraction with word counter."""
def __init__(self, phrase, encoding=None):
"""Please specify your encoding"""
<|body_0|>
def word_count(self):
"""Count the words"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self._io = IO_h... | stack_v2_sparse_classes_36k_train_008919 | 2,345 | no_license | [
{
"docstring": "Please specify your encoding",
"name": "__init__",
"signature": "def __init__(self, phrase, encoding=None)"
},
{
"docstring": "Count the words",
"name": "word_count",
"signature": "def word_count(self)"
}
] | 2 | null | Implement the Python class `Phrase` described below.
Class description:
Phrase abstraction with word counter.
Method signatures and docstrings:
- def __init__(self, phrase, encoding=None): Please specify your encoding
- def word_count(self): Count the words | Implement the Python class `Phrase` described below.
Class description:
Phrase abstraction with word counter.
Method signatures and docstrings:
- def __init__(self, phrase, encoding=None): Please specify your encoding
- def word_count(self): Count the words
<|skeleton|>
class Phrase:
"""Phrase abstraction with w... | be0e2f635a7558f56c61bc0b36c6146b01d1e6e6 | <|skeleton|>
class Phrase:
"""Phrase abstraction with word counter."""
def __init__(self, phrase, encoding=None):
"""Please specify your encoding"""
<|body_0|>
def word_count(self):
"""Count the words"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Phrase:
"""Phrase abstraction with word counter."""
def __init__(self, phrase, encoding=None):
"""Please specify your encoding"""
self._io = IO_handler()
self._phrase = self._io.hanle_in(phrase, encoding)
self._word_count = None
def word_count(self):
"""Count ... | the_stack_v2_python_sparse | all_data/exercism_data/python/word-count/b904bdcab75e49208be23279c28cd40b.py | itsolutionscorp/AutoStyle-Clustering | train | 4 |
8dcb13c4188770ec1f8a0cfb4ca8f75fba1a67cb | [
"next_index = next_object_key(self)\nnew_section = Section()\nnew_section.load_section_from_library(path, material_id)\nsetattr(self, str(next_index), new_section)\nreturn next_index",
"next_index = next_object_key(self)\nnew_section = Section()\nnew_section.load_custom_from_library(name, material_id)\nsetattr(se... | <|body_start_0|>
next_index = next_object_key(self)
new_section = Section()
new_section.load_section_from_library(path, material_id)
setattr(self, str(next_index), new_section)
return next_index
<|end_body_0|>
<|body_start_1|>
next_index = next_object_key(self)
n... | Creates an instance of the SkyCiv Sections class. | Sections | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path o... | stack_v2_sparse_classes_36k_train_008920 | 2,588 | permissive | [
{
"docstring": "Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path of the section in the section library, obtained by inspection from within SkyCiv Section Builder or by attaining the library tree via S3D.SB.getLibraryTree... | 3 | stack_v2_sparse_classes_30k_train_018825 | Implement the Python class `Sections` described below.
Class description:
Creates an instance of the SkyCiv Sections class.
Method signatures and docstrings:
- def add_library_section(self, path: list[str], material_id: int) -> int: Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an... | Implement the Python class `Sections` described below.
Class description:
Creates an instance of the SkyCiv Sections class.
Method signatures and docstrings:
- def add_library_section(self, path: list[str], material_id: int) -> int: Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an... | 1cf3dad7f8d451760df02886df41684add72a4eb | <|skeleton|>
class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sections:
"""Creates an instance of the SkyCiv Sections class."""
def add_library_section(self, path: list[str], material_id: int) -> int:
"""Add a section from the SkyCiv section library. Args: path (list[str]): Provided as an array of 4 strings (see example below). It is the path of the section... | the_stack_v2_python_sparse | src/skyciv/classes/model/components/sections/sections.py | osasanchezme/skyciv-pip | train | 0 |
636eb050a5e470e616a887bff836b44510132e1a | [
"self.authnzerver = authnzerver\nself.fernetkey = fernetkey\nself.ferneter = Fernet(fernetkey)\nself.executor = executor\nself.session_expiry = session_expiry\nself.httpclient = AsyncHTTPClient(force_instance=True)\nself.siteinfo = siteinfo\nself.ratelimit = ratelimit\nself.cachedir = cachedir\nself.basedir = based... | <|body_start_0|>
self.authnzerver = authnzerver
self.fernetkey = fernetkey
self.ferneter = Fernet(fernetkey)
self.executor = executor
self.session_expiry = session_expiry
self.httpclient = AsyncHTTPClient(force_instance=True)
self.siteinfo = siteinfo
self.... | This handles /admin. | AdminIndexHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminIndexHandler:
"""This handles /admin."""
def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir):
"""This just sets up some stuff."""
<|body_0|>
def get(self):
"""This shows the admin page."""
<|... | stack_v2_sparse_classes_36k_train_008921 | 27,340 | permissive | [
{
"docstring": "This just sets up some stuff.",
"name": "initialize",
"signature": "def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir)"
},
{
"docstring": "This shows the admin page.",
"name": "get",
"signature": "def get(self)"
... | 2 | stack_v2_sparse_classes_30k_train_000487 | Implement the Python class `AdminIndexHandler` described below.
Class description:
This handles /admin.
Method signatures and docstrings:
- def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir): This just sets up some stuff.
- def get(self): This shows the admi... | Implement the Python class `AdminIndexHandler` described below.
Class description:
This handles /admin.
Method signatures and docstrings:
- def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir): This just sets up some stuff.
- def get(self): This shows the admi... | b8256bf28aee42e628abe27f0203d6f5361fb84b | <|skeleton|>
class AdminIndexHandler:
"""This handles /admin."""
def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir):
"""This just sets up some stuff."""
<|body_0|>
def get(self):
"""This shows the admin page."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdminIndexHandler:
"""This handles /admin."""
def initialize(self, fernetkey, executor, authnzerver, basedir, session_expiry, siteinfo, ratelimit, cachedir):
"""This just sets up some stuff."""
self.authnzerver = authnzerver
self.fernetkey = fernetkey
self.ferneter = Ferne... | the_stack_v2_python_sparse | lccserver/frontend/admin_handlers.py | waqasbhatti/lcc-server | train | 4 |
219c7aa63c2a983a891214099e3cff69455bccc9 | [
"super().__init__(name)\nself.database = database\nself.searchTags = searchTags\nself.database.add_sensor_observer(self)",
"if isinstance(keys, (slice, float, int)):\n keys = (keys,)\nreturn [copy.deepcopy(entry.data) for entry in self.database.find_entries(tags=self.searchTags, keys=keys)]",
"sampleTags = [... | <|body_start_0|>
super().__init__(name)
self.database = database
self.searchTags = searchTags
self.database.add_sensor_observer(self)
<|end_body_0|>
<|body_start_1|>
if isinstance(keys, (slice, float, int)):
keys = (keys,)
return [copy.deepcopy(entry.data) fo... | DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observation is done on the database. TODO Consider changing database output interface. ... | DatabaseView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseView:
"""DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observation is done on the database. TODO Consi... | stack_v2_sparse_classes_36k_train_008922 | 2,048 | permissive | [
{
"docstring": "Parameters: database : NephelaeDataServer database to which subscribing and from which data will be fetched on a __getitem__. searchTags : list(str, ...) tags to search data in the database.",
"name": "__init__",
"signature": "def __init__(self, name, database, searchTags)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_020504 | Implement the Python class `DatabaseView` described below.
Class description:
DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observat... | Implement the Python class `DatabaseView` described below.
Class description:
DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observat... | d5f1abeae0b0473b895b4735f182ddae0516a1bd | <|skeleton|>
class DatabaseView:
"""DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observation is done on the database. TODO Consi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseView:
"""DatabaseView Dataview without parents made to access a NephelaeDataServer (The NephelaeDataServer play the role of a parent (but is not in the self.parent list). /!\\ This can only be used to manage SensorSample, only the add_sample observation is done on the database. TODO Consider changing ... | the_stack_v2_python_sparse | nephelae/dataviews/types/DatabaseView.py | pnarvor/nephelae_base | train | 0 |
1342dc471bb9ad0f89f4fba35056fa78a29404ec | [
"data_train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)\ntokenizer_pt, tokenizer_en = self.tokenize_dataset(data_train)\nself.tokenizer_pt = tokenizer_pt\nself.tokenizer_en = tokenizer_en\nself.data_train = data_train.map(self.tf_encode)\ndata_valid = tfds.load('ted_hrlr_translate/... | <|body_start_0|>
data_train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)
tokenizer_pt, tokenizer_en = self.tokenize_dataset(data_train)
self.tokenizer_pt = tokenizer_pt
self.tokenizer_en = tokenizer_en
self.data_train = data_train.map(self.tf_enco... | Dataset class | Dataset | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Dataset class"""
def __init__(self):
"""Constructor"""
<|body_0|>
def tokenize_dataset(self, data):
"""Method that creates sub-word tokenizers for our dataset"""
<|body_1|>
def encode(self, pt, en):
"""Method that encodes a transl... | stack_v2_sparse_classes_36k_train_008923 | 2,032 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method that creates sub-word tokenizers for our dataset",
"name": "tokenize_dataset",
"signature": "def tokenize_dataset(self, data)"
},
{
"docstring": "Method that encodes a tr... | 4 | stack_v2_sparse_classes_30k_train_009421 | Implement the Python class `Dataset` described below.
Class description:
Dataset class
Method signatures and docstrings:
- def __init__(self): Constructor
- def tokenize_dataset(self, data): Method that creates sub-word tokenizers for our dataset
- def encode(self, pt, en): Method that encodes a translation into toke... | Implement the Python class `Dataset` described below.
Class description:
Dataset class
Method signatures and docstrings:
- def __init__(self): Constructor
- def tokenize_dataset(self, data): Method that creates sub-word tokenizers for our dataset
- def encode(self, pt, en): Method that encodes a translation into toke... | 131be8fcf61aafb5a4ddc0b3853ba625560eb786 | <|skeleton|>
class Dataset:
"""Dataset class"""
def __init__(self):
"""Constructor"""
<|body_0|>
def tokenize_dataset(self, data):
"""Method that creates sub-word tokenizers for our dataset"""
<|body_1|>
def encode(self, pt, en):
"""Method that encodes a transl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""Dataset class"""
def __init__(self):
"""Constructor"""
data_train = tfds.load('ted_hrlr_translate/pt_to_en', split='train', as_supervised=True)
tokenizer_pt, tokenizer_en = self.tokenize_dataset(data_train)
self.tokenizer_pt = tokenizer_pt
self.tokenize... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/2-dataset.py | zahraaassaad/holbertonschool-machine_learning | train | 1 |
569b97e9b2cc854985c4a006086f81d13484c4fa | [
"if num < 0:\n return False\nelif num <= 1:\n return True\nleft = 1\nright = num - 1\nwhile left <= right:\n mid = (left + right) // 2\n mid_square = mid * mid\n if num == mid_square:\n return True\n elif num < mid_square:\n right = mid - 1\n else:\n left = mid + 1\nreturn ... | <|body_start_0|>
if num < 0:
return False
elif num <= 1:
return True
left = 1
right = num - 1
while left <= right:
mid = (left + right) // 2
mid_square = mid * mid
if num == mid_square:
return True
... | Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square. | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square."""
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
<|body_0|... | stack_v2_sparse_classes_36k_train_008924 | 1,905 | no_license | [
{
"docstring": ":type num: int :rtype: bool",
"name": "isPerfectSquare",
"signature": "def isPerfectSquare(self, num)"
},
{
"docstring": ":type num: int :rtype: bool",
"name": "isPerfectSquare",
"signature": "def isPerfectSquare(self, num)"
},
{
"docstring": ":type num: int :rtyp... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square.
Method signatures and docstrings:
- def isPerfectSquare(sel... | Implement the Python class `Solution` described below.
Class description:
Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square.
Method signatures and docstrings:
- def isPerfectSquare(sel... | 843db7190a95ebe310f5e867c02d28d43ca99248 | <|skeleton|>
class Solution:
"""Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square."""
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""Runtime: 20 ms, faster than 55.25% of Python online submissions for Valid Perfect Square. Memory Usage: 13.4 MB, less than 35.08% of Python online submissions for Valid Perfect Square."""
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
if num < 0:
... | the_stack_v2_python_sparse | search/binary_search/valid_perfect_square.py | YuanZheCSYZ/algorithm | train | 0 |
1b307bb242d4f2e0085c286024ddc959dab980c9 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.accessPackageAssignmentRequestWorkflowExten... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | CustomCalloutExtension | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomCalloutExtension:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomCalloutExtension:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_36k_train_008925 | 6,532 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: CustomCalloutExtension",
"name": "create_from_discriminator_value",
"signature": "def create_from_discrimina... | 3 | stack_v2_sparse_classes_30k_train_006923 | Implement the Python class `CustomCalloutExtension` described below.
Class description:
Implement the CustomCalloutExtension class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomCalloutExtension: Creates a new instance of the appropriate class b... | Implement the Python class `CustomCalloutExtension` described below.
Class description:
Implement the CustomCalloutExtension class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomCalloutExtension: Creates a new instance of the appropriate class b... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class CustomCalloutExtension:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomCalloutExtension:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomCalloutExtension:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> CustomCalloutExtension:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Ret... | the_stack_v2_python_sparse | msgraph/generated/models/custom_callout_extension.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
59747667445c5b05233e57943b460c731e42505d | [
"if hasattr(self, 'gate'):\n return isinstance(self.gate, DifferentiableUnitary)\nif hasattr(self, 'gates'):\n return all((isinstance(gate, DifferentiableUnitary) for gate in self.gates))\nraise AttributeError('Expected gate or gates field for composed gate %s.' % self.get_name())",
"if hasattr(self, 'gate'... | <|body_start_0|>
if hasattr(self, 'gate'):
return isinstance(self.gate, DifferentiableUnitary)
if hasattr(self, 'gates'):
return all((isinstance(gate, DifferentiableUnitary) for gate in self.gates))
raise AttributeError('Expected gate or gates field for composed gate %s.'... | The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its subgates (in either self.gate or self.gates) inherit from the base class. For m... | ComposedGate | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComposedGate:
"""The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its subgates (in either self.gate or self.g... | stack_v2_sparse_classes_36k_train_008926 | 1,859 | permissive | [
{
"docstring": "Check is all sub gates are differentiable.",
"name": "is_differentiable",
"signature": "def is_differentiable(self) -> bool"
},
{
"docstring": "Check is all sub gates are locally optimizable.",
"name": "is_locally_optimizable",
"signature": "def is_locally_optimizable(sel... | 2 | stack_v2_sparse_classes_30k_val_000692 | Implement the Python class `ComposedGate` described below.
Class description:
The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its ... | Implement the Python class `ComposedGate` described below.
Class description:
The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its ... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class ComposedGate:
"""The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its subgates (in either self.gate or self.g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComposedGate:
"""The ComposedGate class. A ComposedGate provides methods for determining if the gate is differentiable or locally optimizable. A ComposedGate is differentiable/locally optimizable if it inherits from the appropriate base class and all of its subgates (in either self.gate or self.gates) inherit... | the_stack_v2_python_sparse | bqskit/ir/gates/composedgate.py | mtreinish/bqskit | train | 0 |
22dba2c5cf6c001c17dbedd38e4cd64a2c9be617 | [
"self._export_dir = export_dir\nself._best = None\nif isinstance(cmp_fn, tuple):\n self.cmp_fn = cmp_fn[0]\n self.is_export = cmp_fn[1]\nelse:\n self.cmp_fn = cmp_fn\n self.is_export = False\nself._best_result = None\nself._epoch_count = 0",
"log.debug('New evaluate result: %s \\nold: %s' % (repr(eval... | <|body_start_0|>
self._export_dir = export_dir
self._best = None
if isinstance(cmp_fn, tuple):
self.cmp_fn = cmp_fn[0]
self.is_export = cmp_fn[1]
else:
self.cmp_fn = cmp_fn
self.is_export = False
self._best_result = None
sel... | export saved model accordingto `cmp_fn` | BestResultExporter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BestResultExporter:
"""export saved model accordingto `cmp_fn`"""
def __init__(self, export_dir, cmp_fn):
"""doc"""
<|body_0|>
def export(self, exe, program, eval_model_spec, eval_result, state):
"""doc"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008927 | 8,759 | permissive | [
{
"docstring": "doc",
"name": "__init__",
"signature": "def __init__(self, export_dir, cmp_fn)"
},
{
"docstring": "doc",
"name": "export",
"signature": "def export(self, exe, program, eval_model_spec, eval_result, state)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000961 | Implement the Python class `BestResultExporter` described below.
Class description:
export saved model accordingto `cmp_fn`
Method signatures and docstrings:
- def __init__(self, export_dir, cmp_fn): doc
- def export(self, exe, program, eval_model_spec, eval_result, state): doc | Implement the Python class `BestResultExporter` described below.
Class description:
export saved model accordingto `cmp_fn`
Method signatures and docstrings:
- def __init__(self, export_dir, cmp_fn): doc
- def export(self, exe, program, eval_model_spec, eval_result, state): doc
<|skeleton|>
class BestResultExporter:... | e6ab0261eb719c21806bbadfd94001ecfe27de45 | <|skeleton|>
class BestResultExporter:
"""export saved model accordingto `cmp_fn`"""
def __init__(self, export_dir, cmp_fn):
"""doc"""
<|body_0|>
def export(self, exe, program, eval_model_spec, eval_result, state):
"""doc"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BestResultExporter:
"""export saved model accordingto `cmp_fn`"""
def __init__(self, export_dir, cmp_fn):
"""doc"""
self._export_dir = export_dir
self._best = None
if isinstance(cmp_fn, tuple):
self.cmp_fn = cmp_fn[0]
self.is_export = cmp_fn[1]
... | the_stack_v2_python_sparse | competition/ogbg_molhiv/propeller/paddle/train/exporter.py | PaddlePaddle/PaddleHelix | train | 771 |
3966e7685870d24be8eb237e028ec65f319c4a25 | [
"self.memoryChartVirt = MemoryChart('virt')\nself.memoryChartVirt.signalNamespace(self, 'memoryChartVirt')\nself.registerMethodForRpc(self.uri + '/memoryChartVirt.data', self.memoryChartVirt, self.memoryChartVirt.data)\nself.memoryChartSwap = MemoryChart('swap')\nself.memoryChartSwap.signalNamespace(self, 'memoryCh... | <|body_start_0|>
self.memoryChartVirt = MemoryChart('virt')
self.memoryChartVirt.signalNamespace(self, 'memoryChartVirt')
self.registerMethodForRpc(self.uri + '/memoryChartVirt.data', self.memoryChartVirt, self.memoryChartVirt.data)
self.memoryChartSwap = MemoryChart('swap')
self... | This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection | MemoryMonitorServerProtocol | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MemoryMonitorServerProtocol:
"""This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection"""
def onSessionOpen(self):
"""When connection is established, we crea... | stack_v2_sparse_classes_36k_train_008928 | 3,362 | no_license | [
{
"docstring": "When connection is established, we create our model instances and register them for RPC. that's it.",
"name": "onSessionOpen",
"signature": "def onSessionOpen(self)"
},
{
"docstring": "When connection is gone (i.e. client close window, navigated away from the page), stop the mode... | 2 | stack_v2_sparse_classes_30k_train_017586 | Implement the Python class `MemoryMonitorServerProtocol` described below.
Class description:
This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection
Method signatures and docstrings:
- def onS... | Implement the Python class `MemoryMonitorServerProtocol` described below.
Class description:
This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection
Method signatures and docstrings:
- def onS... | 16d3284d83ad5f8bd5fb6aaa048d5b444892b31a | <|skeleton|>
class MemoryMonitorServerProtocol:
"""This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection"""
def onSessionOpen(self):
"""When connection is established, we crea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MemoryMonitorServerProtocol:
"""This is simple memory monitor server protocol. As with other server classes model is created, when new connection is established, and deleted when client closes websocket connection"""
def onSessionOpen(self):
"""When connection is established, we create our model ... | the_stack_v2_python_sparse | src/web/server_memory.py | vminakov/system-monitor | train | 0 |
a709e348d0ac489ee9f649b493f77a818055518b | [
"tester = app.test_client(self)\nresponse = tester.get('/', content_type='html/text')\nself.assertEqual(response.status_code, 200)",
"tester = app.test_client(self)\nresponse = tester.get('/', content_type='html/text')\nself.assertIn('<title>Flask Stock Visualizer</title>', response.data)"
] | <|body_start_0|>
tester = app.test_client(self)
response = tester.get('/', content_type='html/text')
self.assertEqual(response.status_code, 200)
<|end_body_0|>
<|body_start_1|>
tester = app.test_client(self)
response = tester.get('/', content_type='html/text')
self.asser... | BasicTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicTestCase:
def test_index(self):
"""Ensure flask was set up correctly."""
<|body_0|>
def test_index_slightly_better(self):
"""Ensure '/' contains expected HTML."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tester = app.test_client(self)
... | stack_v2_sparse_classes_36k_train_008929 | 629 | no_license | [
{
"docstring": "Ensure flask was set up correctly.",
"name": "test_index",
"signature": "def test_index(self)"
},
{
"docstring": "Ensure '/' contains expected HTML.",
"name": "test_index_slightly_better",
"signature": "def test_index_slightly_better(self)"
}
] | 2 | null | Implement the Python class `BasicTestCase` described below.
Class description:
Implement the BasicTestCase class.
Method signatures and docstrings:
- def test_index(self): Ensure flask was set up correctly.
- def test_index_slightly_better(self): Ensure '/' contains expected HTML. | Implement the Python class `BasicTestCase` described below.
Class description:
Implement the BasicTestCase class.
Method signatures and docstrings:
- def test_index(self): Ensure flask was set up correctly.
- def test_index_slightly_better(self): Ensure '/' contains expected HTML.
<|skeleton|>
class BasicTestCase:
... | 7993f94d4fb8007a7e366687af11dd8aeb7ca7ed | <|skeleton|>
class BasicTestCase:
def test_index(self):
"""Ensure flask was set up correctly."""
<|body_0|>
def test_index_slightly_better(self):
"""Ensure '/' contains expected HTML."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicTestCase:
def test_index(self):
"""Ensure flask was set up correctly."""
tester = app.test_client(self)
response = tester.get('/', content_type='html/text')
self.assertEqual(response.status_code, 200)
def test_index_slightly_better(self):
"""Ensure '/' contain... | the_stack_v2_python_sparse | Flask-Malaria Eradication/tests.py | sambapython/python | train | 8 | |
44cd910dda05b0f07c9339f3a0fc6d95e9977bb3 | [
"if '_xml_ns' in kwargs:\n self._xml_ns = kwargs['_xml_ns']\nif '_xml_ns_key' in kwargs:\n self._xml_ns_key = kwargs['_xml_ns_key']\nself.Azimuth = Azimuth\nself.Slope = Slope\nself.Squint = Squint\nself.Graze = Graze\nself.Tilt = Tilt\nself.DopplerConeAngle = DopplerConeAngle\nself.Extensions = Extensions\ns... | <|body_start_0|>
if '_xml_ns' in kwargs:
self._xml_ns = kwargs['_xml_ns']
if '_xml_ns_key' in kwargs:
self._xml_ns_key = kwargs['_xml_ns_key']
self.Azimuth = Azimuth
self.Slope = Slope
self.Squint = Squint
self.Graze = Graze
self.Tilt = Til... | Key geometry parameters independent of product processing. All values computed at the center time of the full collection. | ExploitationFeaturesCollectionGeometryType | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-public-domain"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExploitationFeaturesCollectionGeometryType:
"""Key geometry parameters independent of product processing. All values computed at the center time of the full collection."""
def __init__(self, Azimuth=None, Slope=None, Squint=None, Graze=None, Tilt=None, DopplerConeAngle=None, Extensions=None,... | stack_v2_sparse_classes_36k_train_008930 | 34,922 | permissive | [
{
"docstring": "Parameters ---------- Azimuth : None|float Slope : None|float Squint : None|float Graze : None|float Tilt : None|float DopplerConeAngle : None|float Extensions : None|ParametersCollection|dict kwargs",
"name": "__init__",
"signature": "def __init__(self, Azimuth=None, Slope=None, Squint=... | 2 | null | Implement the Python class `ExploitationFeaturesCollectionGeometryType` described below.
Class description:
Key geometry parameters independent of product processing. All values computed at the center time of the full collection.
Method signatures and docstrings:
- def __init__(self, Azimuth=None, Slope=None, Squint=... | Implement the Python class `ExploitationFeaturesCollectionGeometryType` described below.
Class description:
Key geometry parameters independent of product processing. All values computed at the center time of the full collection.
Method signatures and docstrings:
- def __init__(self, Azimuth=None, Slope=None, Squint=... | de1b1886f161a83b6c89aadc7a2c7cfc4892ef81 | <|skeleton|>
class ExploitationFeaturesCollectionGeometryType:
"""Key geometry parameters independent of product processing. All values computed at the center time of the full collection."""
def __init__(self, Azimuth=None, Slope=None, Squint=None, Graze=None, Tilt=None, DopplerConeAngle=None, Extensions=None,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExploitationFeaturesCollectionGeometryType:
"""Key geometry parameters independent of product processing. All values computed at the center time of the full collection."""
def __init__(self, Azimuth=None, Slope=None, Squint=None, Graze=None, Tilt=None, DopplerConeAngle=None, Extensions=None, **kwargs):
... | the_stack_v2_python_sparse | sarpy/io/product/sidd2_elements/ExploitationFeatures.py | ngageoint/sarpy | train | 192 |
9abbb516d5fa52ead1845cfc888b466131d9d205 | [
"super(Embedding_LS, self).__init__()\nself.num_classes = num_classes\nself.label_smoothing_prob = label_smoothing_prob\nself.embed = LinearND(num_classes, embedding_dim, bias=False, dropout=dropout)",
"y = _to_onehot(y, self.num_classes, self.label_smoothing_prob)\ny = self.embed(y)\nreturn y"
] | <|body_start_0|>
super(Embedding_LS, self).__init__()
self.num_classes = num_classes
self.label_smoothing_prob = label_smoothing_prob
self.embed = LinearND(num_classes, embedding_dim, bias=False, dropout=dropout)
<|end_body_0|>
<|body_start_1|>
y = _to_onehot(y, self.num_classes... | Embedding_LS | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Embedding_LS:
def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0):
"""Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embeddin... | stack_v2_sparse_classes_36k_train_008931 | 4,283 | no_license | [
{
"docstring": "Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target spaces dropout (float, optional): the probability to drop nodes of the embedding label_smoothing_p... | 2 | stack_v2_sparse_classes_30k_train_002261 | Implement the Python class `Embedding_LS` described below.
Class description:
Implement the Embedding_LS class.
Method signatures and docstrings:
- def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in... | Implement the Python class `Embedding_LS` described below.
Class description:
Implement the Embedding_LS class.
Method signatures and docstrings:
- def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0): Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in... | b6b60a338d65bb369d0034f423feb09db10db8b7 | <|skeleton|>
class Embedding_LS:
def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0):
"""Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embeddin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Embedding_LS:
def __init__(self, num_classes, embedding_dim, dropout=0, label_smoothing_prob=0.0):
"""Embedding layer with label smoothing. Args: num_classes (int): the number of nodes in softmax layer (including <SOS> and <EOS> classes) embedding_dim (int): the dimension of the embedding in target sp... | the_stack_v2_python_sparse | models/pytorch/linear.py | carolinebear/pytorch_end2end_speech_recognition | train | 0 | |
6d695534710d9c62902c0649bbedc02a386225d8 | [
"from __builtin__ import xrange\nresult = []\n\ndef dfs(previous_total, previous_value, pop, low_index, previous_str):\n \"\"\"\n :param int previous_total: previous total, shoud not be modified.\n :param int previous_value: previous single value.\n :param str pop: previous op.\n... | <|body_start_0|>
from __builtin__ import xrange
result = []
def dfs(previous_total, previous_value, pop, low_index, previous_str):
"""
:param int previous_total: previous total, shoud not be modified.
:param int previous_value: previous single... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addOperators(self, num, target):
""":type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of "001" convert to int is '1' '00' -> '0' '01' -> '1' moving index"""
<|body_0|>
def rewrite(self, num, targe... | stack_v2_sparse_classes_36k_train_008932 | 5,951 | no_license | [
{
"docstring": ":type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of \"001\" convert to int is '1' '00' -> '0' '01' -> '1' moving index",
"name": "addOperators",
"signature": "def addOperators(self, num, target)"
},
{
"docstring": ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addOperators(self, num, target): :type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of "001" convert to int is... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addOperators(self, num, target): :type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of "001" convert to int is... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def addOperators(self, num, target):
""":type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of "001" convert to int is '1' '00' -> '0' '01' -> '1' moving index"""
<|body_0|>
def rewrite(self, num, targe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def addOperators(self, num, target):
""":type num: str :type target: int :rtype: List[str] 1 23 12 3 123 -- 1 23 1 2 3 1 23 -- 12 3 12 3 -- 123 123 beware of "001" convert to int is '1' '00' -> '0' '01' -> '1' moving index"""
from __builtin__ import xrange
result = []
... | the_stack_v2_python_sparse | depth-first-search/282_Expression_Add_Operators_hard.py | vsdrun/lc_public | train | 6 | |
1cf6b4db235a6f269be8f1ee3c8410d0dae769cf | [
"super().__init__()\nself.file_paths = file_paths\nself.single_file = single_file\nself.start = start\nself.chunk_size = chunk_size\nif self.single_file and (not chunk_size):\n raise DDSException('Missing chunk_size argument...')",
"if self.single_file:\n with open(self.file_paths[0]) as file_paths_fd:\n ... | <|body_start_0|>
super().__init__()
self.file_paths = file_paths
self.single_file = single_file
self.start = start
self.chunk_size = chunk_size
if self.single_file and (not chunk_size):
raise DDSException('Missing chunk_size argument...')
<|end_body_0|>
<|bod... | Worker file loader. | WorkerFileLoader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkerFileLoader:
"""Worker file loader."""
def __init__(self, file_paths, single_file=False, start=0, chunk_size=None):
"""Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a single file? :param start: Start position. :param chunk_size... | stack_v2_sparse_classes_36k_train_008933 | 6,375 | permissive | [
{
"docstring": "Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a single file? :param start: Start position. :param chunk_size: Chunk size. :returns: None.",
"name": "__init__",
"signature": "def __init__(self, file_paths, single_file=False, start=0, chu... | 2 | null | Implement the Python class `WorkerFileLoader` described below.
Class description:
Worker file loader.
Method signatures and docstrings:
- def __init__(self, file_paths, single_file=False, start=0, chunk_size=None): Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a sin... | Implement the Python class `WorkerFileLoader` described below.
Class description:
Worker file loader.
Method signatures and docstrings:
- def __init__(self, file_paths, single_file=False, start=0, chunk_size=None): Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a sin... | 5f7a31436d0e6f5acbeb66fa36ab8aad18dc4092 | <|skeleton|>
class WorkerFileLoader:
"""Worker file loader."""
def __init__(self, file_paths, single_file=False, start=0, chunk_size=None):
"""Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a single file? :param start: Start position. :param chunk_size... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkerFileLoader:
"""Worker file loader."""
def __init__(self, file_paths, single_file=False, start=0, chunk_size=None):
"""Create new WorkerFileLoader object. :param file_paths: List of file paths. :param single_file: Is a single file? :param start: Start position. :param chunk_size: Chunk size.... | the_stack_v2_python_sparse | compss/programming_model/bindings/python/src/pycompss/dds/partition_generators.py | bsc-wdc/compss | train | 39 |
1a0d5ac5132ae7c124adbbf66cfc17bf497c73d8 | [
"cmd = 'fleetrun dist_fleet_tree_node.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\nout, err = pro.communicate()\npro.wait()\npro.returncode == 0",
"cmd = 'fleetrun dist_fleet_grahp_engine.py'\npro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=s... | <|body_start_0|>
cmd = 'fleetrun dist_fleet_tree_node.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = pro.communicate()
pro.wait()
pro.returncode == 0
<|end_body_0|>
<|body_start_1|>
cmd = 'fleetrun dist_fleet_grahp_... | test all comm api | TestTreeNodeAndGrahpEngineApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestTreeNodeAndGrahpEngineApi:
"""test all comm api"""
def test_tree_node(self):
"""test_tree_node"""
<|body_0|>
def test_graph_engine(self):
"""test_tree_node"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cmd = 'fleetrun dist_fleet_tree_node.... | stack_v2_sparse_classes_36k_train_008934 | 762 | no_license | [
{
"docstring": "test_tree_node",
"name": "test_tree_node",
"signature": "def test_tree_node(self)"
},
{
"docstring": "test_tree_node",
"name": "test_graph_engine",
"signature": "def test_graph_engine(self)"
}
] | 2 | null | Implement the Python class `TestTreeNodeAndGrahpEngineApi` described below.
Class description:
test all comm api
Method signatures and docstrings:
- def test_tree_node(self): test_tree_node
- def test_graph_engine(self): test_tree_node | Implement the Python class `TestTreeNodeAndGrahpEngineApi` described below.
Class description:
test all comm api
Method signatures and docstrings:
- def test_tree_node(self): test_tree_node
- def test_graph_engine(self): test_tree_node
<|skeleton|>
class TestTreeNodeAndGrahpEngineApi:
"""test all comm api"""
... | e3562ab40b574f06bba68df6895a055fa31a085d | <|skeleton|>
class TestTreeNodeAndGrahpEngineApi:
"""test all comm api"""
def test_tree_node(self):
"""test_tree_node"""
<|body_0|>
def test_graph_engine(self):
"""test_tree_node"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestTreeNodeAndGrahpEngineApi:
"""test all comm api"""
def test_tree_node(self):
"""test_tree_node"""
cmd = 'fleetrun dist_fleet_tree_node.py'
pro = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = pro.communicate()
pro.w... | the_stack_v2_python_sparse | dist_cts/dist_fleet_pipeline/test_dist_fleet_tree_node_and_graph_engine.py | gentelyang/scripts | train | 0 |
716598e54713fde901b3625461d59204dc4e9cb7 | [
"self.input_size = input_size\nself.output_size = output_size\nself.X = tf.placeholder(tf.float32, shape=[None, self.input_size])\nself.Y = tf.placeholder(tf.float32, shape=[None, self.output_size])\nself.weights = tf.Variable(tf.glorot_uniform_initializer()((self.input_size, self.output_size)))\nself.biases = tf.V... | <|body_start_0|>
self.input_size = input_size
self.output_size = output_size
self.X = tf.placeholder(tf.float32, shape=[None, self.input_size])
self.Y = tf.placeholder(tf.float32, shape=[None, self.output_size])
self.weights = tf.Variable(tf.glorot_uniform_initializer()((self.inp... | SoftmaxRegression | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
<|body_0|>
def Regression(self):
"""Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchN... | stack_v2_sparse_classes_36k_train_008935 | 19,475 | no_license | [
{
"docstring": "Function: Initialization of all variables",
"name": "__init__",
"signature": "def __init__(self, input_size, output_size, dropout=False, BN=False)"
},
{
"docstring": "Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchNormalization()",
... | 5 | stack_v2_sparse_classes_30k_train_005159 | Implement the Python class `SoftmaxRegression` described below.
Class description:
Implement the SoftmaxRegression class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, dropout=False, BN=False): Function: Initialization of all variables
- def Regression(self): Function: Define softmax... | Implement the Python class `SoftmaxRegression` described below.
Class description:
Implement the SoftmaxRegression class.
Method signatures and docstrings:
- def __init__(self, input_size, output_size, dropout=False, BN=False): Function: Initialization of all variables
- def Regression(self): Function: Define softmax... | 929e28c3ea5aec63bc655035c48d96d2d3cff5bc | <|skeleton|>
class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
<|body_0|>
def Regression(self):
"""Function: Define softmax function as y = sigmoid(A * x + b) Using tf function tf.layers.BatchN... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SoftmaxRegression:
def __init__(self, input_size, output_size, dropout=False, BN=False):
"""Function: Initialization of all variables"""
self.input_size = input_size
self.output_size = output_size
self.X = tf.placeholder(tf.float32, shape=[None, self.input_size])
self.Y... | the_stack_v2_python_sparse | Ao_Zhang/assignment2/assignment2_question3.py | ZhangAoCanada/CSI5138_Assignments | train | 1 | |
e3079993328eb502d206b4fe93ef708a18071277 | [
"if filters is None:\n filters = {}\norm_filters = super(EventResource, self).build_filters(filters)\nquery = filters.get('q')\ncategory_pk = filters.get('catpk')\nif query is not None:\n sqs = SearchQuerySet().models(Event).load_all().auto_query(query)\n orm_filters['pk__in'] = [i.pk for i in sqs]\nif cat... | <|body_start_0|>
if filters is None:
filters = {}
orm_filters = super(EventResource, self).build_filters(filters)
query = filters.get('q')
category_pk = filters.get('catpk')
if query is not None:
sqs = SearchQuerySet().models(Event).load_all().auto_query(q... | EventResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
<|body_0|>
def dehydrate_image(self, bundle):
"""Ensures data includes a url for an app-sized thumbnail"""
<|body_1|>
def dehydrate(self, bundle):... | stack_v2_sparse_classes_36k_train_008936 | 2,337 | no_license | [
{
"docstring": "Custom filters used for category and searching.",
"name": "build_filters",
"signature": "def build_filters(self, filters=None)"
},
{
"docstring": "Ensures data includes a url for an app-sized thumbnail",
"name": "dehydrate_image",
"signature": "def dehydrate_image(self, b... | 3 | stack_v2_sparse_classes_30k_train_021410 | Implement the Python class `EventResource` described below.
Class description:
Implement the EventResource class.
Method signatures and docstrings:
- def build_filters(self, filters=None): Custom filters used for category and searching.
- def dehydrate_image(self, bundle): Ensures data includes a url for an app-sized... | Implement the Python class `EventResource` described below.
Class description:
Implement the EventResource class.
Method signatures and docstrings:
- def build_filters(self, filters=None): Custom filters used for category and searching.
- def dehydrate_image(self, bundle): Ensures data includes a url for an app-sized... | 3ed85e856a026001a1d91d09d31d944c64704824 | <|skeleton|>
class EventResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
<|body_0|>
def dehydrate_image(self, bundle):
"""Ensures data includes a url for an app-sized thumbnail"""
<|body_1|>
def dehydrate(self, bundle):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventResource:
def build_filters(self, filters=None):
"""Custom filters used for category and searching."""
if filters is None:
filters = {}
orm_filters = super(EventResource, self).build_filters(filters)
query = filters.get('q')
category_pk = filters.get('c... | the_stack_v2_python_sparse | scenable/events/api.py | gregarious/betasite | train | 0 | |
e4791412da0cc3439476c78f0b8df7db19e05957 | [
"if data.get('action') is None:\n raise ValidationError({'action': 'This field is required.'})\nif data['action'] == FinancialAidStatus.APPROVED:\n if data.get('tier_program_id') is None:\n raise ValidationError({'tier_program_id': 'This field is required.'})\n if data.get('justification') is None:\... | <|body_start_0|>
if data.get('action') is None:
raise ValidationError({'action': 'This field is required.'})
if data['action'] == FinancialAidStatus.APPROVED:
if data.get('tier_program_id') is None:
raise ValidationError({'tier_program_id': 'This field is required... | Serializer for financial aid actions | FinancialAidActionSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FinancialAidActionSerializer:
"""Serializer for financial aid actions"""
def validate(self, data):
"""Validators for this serializer"""
<|body_0|>
def save(self):
"""Save method for this serializer"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008937 | 6,670 | no_license | [
{
"docstring": "Validators for this serializer",
"name": "validate",
"signature": "def validate(self, data)"
},
{
"docstring": "Save method for this serializer",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006550 | Implement the Python class `FinancialAidActionSerializer` described below.
Class description:
Serializer for financial aid actions
Method signatures and docstrings:
- def validate(self, data): Validators for this serializer
- def save(self): Save method for this serializer | Implement the Python class `FinancialAidActionSerializer` described below.
Class description:
Serializer for financial aid actions
Method signatures and docstrings:
- def validate(self, data): Validators for this serializer
- def save(self): Save method for this serializer
<|skeleton|>
class FinancialAidActionSerial... | 3c166bc52dfe8d7aa04f922134f4f6deeff49eb6 | <|skeleton|>
class FinancialAidActionSerializer:
"""Serializer for financial aid actions"""
def validate(self, data):
"""Validators for this serializer"""
<|body_0|>
def save(self):
"""Save method for this serializer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FinancialAidActionSerializer:
"""Serializer for financial aid actions"""
def validate(self, data):
"""Validators for this serializer"""
if data.get('action') is None:
raise ValidationError({'action': 'This field is required.'})
if data['action'] == FinancialAidStatus.A... | the_stack_v2_python_sparse | financialaid/serializers.py | avontd2868/micromasters | train | 0 |
516f3a4265f6a4df81c1182c586c251c759b02bc | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('cici_fyl', 'cici_fyl')\nurl = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/1d9509a8b2fd485d9ad471ba2fdb1f90_0.geojson'\nresponse = urllib.request.urlopen(url).read().decode('utf-8')\nr = js... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cici_fyl', 'cici_fyl')
url = 'http://bostonopendata-boston.opendata.arcgis.com/datasets/1d9509a8b2fd485d9ad471ba2fdb1f90_0.geojson'
response = url... | schoolrestaurant | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class schoolrestaurant:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_36k_train_008938 | 4,759 | permissive | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_012200 | Implement the Python class `schoolrestaurant` described below.
Class description:
Implement the schoolrestaurant class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | Implement the Python class `schoolrestaurant` described below.
Class description:
Implement the schoolrestaurant class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=N... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class schoolrestaurant:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class schoolrestaurant:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('cici_fyl', 'cici_fyl')
url... | the_stack_v2_python_sparse | cici_fyl/project/cici_fyl/schoolrestaurant.py | lingyigu/course-2017-spr-proj | train | 0 | |
d7df72c6a44d1cbeba1db77e46c9f2c90c04edb2 | [
"super(BinaryExpression, self).__init__()\nself.args = []\nself.operator = operator",
"if len(self.args) == 2:\n return '({0!s}) {1:s} {2!s}'.format(self.args[0], self.operator, self.args[1])\nreturn self.operator",
"if not isinstance(lhs, Expression):\n raise errors.ParseError('Left hand side is not an e... | <|body_start_0|>
super(BinaryExpression, self).__init__()
self.args = []
self.operator = operator
<|end_body_0|>
<|body_start_1|>
if len(self.args) == 2:
return '({0!s}) {1:s} {2!s}'.format(self.args[0], self.operator, self.args[1])
return self.operator
<|end_body_1|... | An event filter parser expression which takes two other expressions. | BinaryExpression | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryExpression:
"""An event filter parser expression which takes two other expressions."""
def __init__(self, operator=''):
"""Initializes an event filter parser binary expression. Args: operator (str): operator, such as "and" or "&&"."""
<|body_0|>
def __repr__(self):... | stack_v2_sparse_classes_36k_train_008939 | 7,105 | permissive | [
{
"docstring": "Initializes an event filter parser binary expression. Args: operator (str): operator, such as \"and\" or \"&&\".",
"name": "__init__",
"signature": "def __init__(self, operator='')"
},
{
"docstring": "Retrieves a string representation of the object for debugging.",
"name": "_... | 4 | null | Implement the Python class `BinaryExpression` described below.
Class description:
An event filter parser expression which takes two other expressions.
Method signatures and docstrings:
- def __init__(self, operator=''): Initializes an event filter parser binary expression. Args: operator (str): operator, such as "and... | Implement the Python class `BinaryExpression` described below.
Class description:
An event filter parser expression which takes two other expressions.
Method signatures and docstrings:
- def __init__(self, operator=''): Initializes an event filter parser binary expression. Args: operator (str): operator, such as "and... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class BinaryExpression:
"""An event filter parser expression which takes two other expressions."""
def __init__(self, operator=''):
"""Initializes an event filter parser binary expression. Args: operator (str): operator, such as "and" or "&&"."""
<|body_0|>
def __repr__(self):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryExpression:
"""An event filter parser expression which takes two other expressions."""
def __init__(self, operator=''):
"""Initializes an event filter parser binary expression. Args: operator (str): operator, such as "and" or "&&"."""
super(BinaryExpression, self).__init__()
... | the_stack_v2_python_sparse | plaso/filters/expressions.py | log2timeline/plaso | train | 1,506 |
8a04bc228de5da95600daa29ac3fdb5193da2324 | [
"uf = UnionFindMapWithDist2()\nfor (key1, key2), value in zip(equations, values):\n id1, id2 = (id(key1), id(key2))\n if not uf.isConnected(id1, id2):\n uf.union(id1, id2, value)\n else:\n dist = uf.dist(id1, id2)\n if abs(dist - value) > EPS:\n return True\nreturn False",
... | <|body_start_0|>
uf = UnionFindMapWithDist2()
for (key1, key2), value in zip(equations, values):
id1, id2 = (id(key1), id(key2))
if not uf.isConnected(id1, id2):
uf.union(id1, id2, value)
else:
dist = uf.dist(id1, id2)
i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool:
"""检查方程是否存在矛盾"""
<|body_0|>
def checkContradictions2(self, equations: List[List[str]], values: List[float]) -> bool:
"""dfs或bfs求出每个点到每个组的根的距离,再逐一检验"""
<|body_1|>... | stack_v2_sparse_classes_36k_train_008940 | 2,228 | no_license | [
{
"docstring": "检查方程是否存在矛盾",
"name": "checkContradictions",
"signature": "def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool"
},
{
"docstring": "dfs或bfs求出每个点到每个组的根的距离,再逐一检验",
"name": "checkContradictions2",
"signature": "def checkContradictions2(self, ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool: 检查方程是否存在矛盾
- def checkContradictions2(self, equations: List[List[str]], values: List[float... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool: 检查方程是否存在矛盾
- def checkContradictions2(self, equations: List[List[str]], values: List[float... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Solution:
def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool:
"""检查方程是否存在矛盾"""
<|body_0|>
def checkContradictions2(self, equations: List[List[str]], values: List[float]) -> bool:
"""dfs或bfs求出每个点到每个组的根的距离,再逐一检验"""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkContradictions(self, equations: List[List[str]], values: List[float]) -> bool:
"""检查方程是否存在矛盾"""
uf = UnionFindMapWithDist2()
for (key1, key2), value in zip(equations, values):
id1, id2 = (id(key1), id(key2))
if not uf.isConnected(id1, id2):
... | the_stack_v2_python_sparse | 14_并查集/经典题/维护到根节点距离/2307. 检查方程中的矛盾之处.py | 981377660LMT/algorithm-study | train | 225 | |
1a00e7f6dbc7c39d4e077799185542ebfcfa4dd0 | [
"if result_schema is None:\n return {}\nresult = result_schema.get_computed_entity_columns(entity, **options)\nif result is None:\n return {}\noptions.update(result_schema=result_schema)\nresult = serializer_services.serialize(result, **options)\nreturn result",
"if result_schema is None:\n return {}\nre... | <|body_start_0|>
if result_schema is None:
return {}
result = result_schema.get_computed_entity_columns(entity, **options)
if result is None:
return {}
options.update(result_schema=result_schema)
result = serializer_services.serialize(result, **options)
... | schema manager class. | SchemaManager | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchemaManager:
"""schema manager class."""
def get_computed_entity_columns(self, entity, result_schema=None, **options):
"""gets a dict containing all computed columns to be added to the result. if `result_schema` is not provided, it returns an empty dict. note that the result dict s... | stack_v2_sparse_classes_36k_train_008941 | 2,114 | permissive | [
{
"docstring": "gets a dict containing all computed columns to be added to the result. if `result_schema` is not provided, it returns an empty dict. note that the result dict should not contain any `BaseEntity` or `ROW_RESULT` values, otherwise a max recursion error may occur. :param BaseEntity entity: the actu... | 2 | null | Implement the Python class `SchemaManager` described below.
Class description:
schema manager class.
Method signatures and docstrings:
- def get_computed_entity_columns(self, entity, result_schema=None, **options): gets a dict containing all computed columns to be added to the result. if `result_schema` is not provid... | Implement the Python class `SchemaManager` described below.
Class description:
schema manager class.
Method signatures and docstrings:
- def get_computed_entity_columns(self, entity, result_schema=None, **options): gets a dict containing all computed columns to be added to the result. if `result_schema` is not provid... | 9d4776498225de4f3d16a4600b5b19212abe8562 | <|skeleton|>
class SchemaManager:
"""schema manager class."""
def get_computed_entity_columns(self, entity, result_schema=None, **options):
"""gets a dict containing all computed columns to be added to the result. if `result_schema` is not provided, it returns an empty dict. note that the result dict s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SchemaManager:
"""schema manager class."""
def get_computed_entity_columns(self, entity, result_schema=None, **options):
"""gets a dict containing all computed columns to be added to the result. if `result_schema` is not provided, it returns an empty dict. note that the result dict should not con... | the_stack_v2_python_sparse | src/pyrin/api/schema/manager.py | mononobi/pyrin | train | 20 |
d83bea28f33a0a43f6fdf8ad90714239e45e97f3 | [
"self.login_with_cookie()\nuser_page = dimissionPage.DimissionPage(self.dr)\nl = user_page.delete_dimission()\nself.assertEqual(l[0] - 1, l[1])",
"self.login_with_cookie()\nuser_page = dimissionPage.DimissionPage(self.dr)\nl = user_page.recover_dimission()\nself.assertEqual(l[0] - 1, l[1])"
] | <|body_start_0|>
self.login_with_cookie()
user_page = dimissionPage.DimissionPage(self.dr)
l = user_page.delete_dimission()
self.assertEqual(l[0] - 1, l[1])
<|end_body_0|>
<|body_start_1|>
self.login_with_cookie()
user_page = dimissionPage.DimissionPage(self.dr)
... | 离职库测试 | TestDimission | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDimission:
"""离职库测试"""
def test_del_dimission(self):
"""从离职库中删除用户"""
<|body_0|>
def test_revover_dimission(self):
"""从离职库中还原用户"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.login_with_cookie()
user_page = dimissionPage.Dimissi... | stack_v2_sparse_classes_36k_train_008942 | 799 | no_license | [
{
"docstring": "从离职库中删除用户",
"name": "test_del_dimission",
"signature": "def test_del_dimission(self)"
},
{
"docstring": "从离职库中还原用户",
"name": "test_revover_dimission",
"signature": "def test_revover_dimission(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004991 | Implement the Python class `TestDimission` described below.
Class description:
离职库测试
Method signatures and docstrings:
- def test_del_dimission(self): 从离职库中删除用户
- def test_revover_dimission(self): 从离职库中还原用户 | Implement the Python class `TestDimission` described below.
Class description:
离职库测试
Method signatures and docstrings:
- def test_del_dimission(self): 从离职库中删除用户
- def test_revover_dimission(self): 从离职库中还原用户
<|skeleton|>
class TestDimission:
"""离职库测试"""
def test_del_dimission(self):
"""从离职库中删除用户"""
... | 91de99c0cba6b339cb95ea2ee4ba7d5b937a4ab6 | <|skeleton|>
class TestDimission:
"""离职库测试"""
def test_del_dimission(self):
"""从离职库中删除用户"""
<|body_0|>
def test_revover_dimission(self):
"""从离职库中还原用户"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDimission:
"""离职库测试"""
def test_del_dimission(self):
"""从离职库中删除用户"""
self.login_with_cookie()
user_page = dimissionPage.DimissionPage(self.dr)
l = user_page.delete_dimission()
self.assertEqual(l[0] - 1, l[1])
def test_revover_dimission(self):
"""从离... | the_stack_v2_python_sparse | JustCC/testcase/test_23_organize_dimission.py | ganlp/JUST | train | 0 |
43c7c509ea963bed711e8465d285e21f411c719c | [
"super().__init__(**kwargs)\nif text is None:\n raise SelectError('Required text parameter is missing')\nself.text = text\nself.font_name = font_name\nself.font_size = font_size\nif self.height is None:\n self.height = 0.03\nif self.width is None:\n self.width = self.height * 0.5 * len(text)",
"text_pos ... | <|body_start_0|>
super().__init__(**kwargs)
if text is None:
raise SelectError('Required text parameter is missing')
self.text = text
self.font_name = font_name
self.font_size = font_size
if self.height is None:
self.height = 0.03
if self.w... | Place text at position | BlockText | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlockText:
"""Place text at position"""
def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs):
"""Setup object :text: text string to display :font_name: font name default: system font :font_size: font size default:12"""
<|body_0|>
def display(self):
... | stack_v2_sparse_classes_36k_train_008943 | 3,836 | no_license | [
{
"docstring": "Setup object :text: text string to display :font_name: font name default: system font :font_size: font size default:12",
"name": "__init__",
"signature": "def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs)"
},
{
"docstring": "Display text in canvas",
"n... | 2 | stack_v2_sparse_classes_30k_train_017282 | Implement the Python class `BlockText` described below.
Class description:
Place text at position
Method signatures and docstrings:
- def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs): Setup object :text: text string to display :font_name: font name default: system font :font_size: font size d... | Implement the Python class `BlockText` described below.
Class description:
Place text at position
Method signatures and docstrings:
- def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs): Setup object :text: text string to display :font_name: font name default: system font :font_size: font size d... | 407d542e1c8b09718c6e931f1991562805f04607 | <|skeleton|>
class BlockText:
"""Place text at position"""
def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs):
"""Setup object :text: text string to display :font_name: font name default: system font :font_size: font size default:12"""
<|body_0|>
def display(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlockText:
"""Place text at position"""
def __init__(self, text=None, font_name='Tahoma', font_size=12, **kwargs):
"""Setup object :text: text string to display :font_name: font name default: system font :font_size: font size default:12"""
super().__init__(**kwargs)
if text is Non... | the_stack_v2_python_sparse | src/src/block_text.py | raysmith619/race_track | train | 0 |
d59704128656e8a2f7539c3eabae5c763395e213 | [
"if model._meta.app_label == 'syncwerk_ccnet_models':\n return 'ccnet'\nreturn None",
"if model._meta.app_label == 'syncwerk_ccnet_models':\n return 'ccnet'\nreturn None",
"if obj1._meta.app_label == 'syncwerk_ccnet_models' or obj2._meta.app_label == 'syncwerk_ccnet_models':\n return True\nreturn None"... | <|body_start_0|>
if model._meta.app_label == 'syncwerk_ccnet_models':
return 'ccnet'
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label == 'syncwerk_ccnet_models':
return 'ccnet'
return None
<|end_body_1|>
<|body_start_2|>
if obj1._meta... | A router to control all database operations on models related to ccnet | SyncwerkCcnetModelsRouter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyncwerkCcnetModelsRouter:
"""A router to control all database operations on models related to ccnet"""
def db_for_read(self, model, **hints):
"""Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet'"""
<|body_0|>
def db_for_write(self, model... | stack_v2_sparse_classes_36k_train_008944 | 1,265 | permissive | [
{
"docstring": "Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet'",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Point all operations on syncwerk_ccnet_models models to 'ccnet'",
"name": "db_for_write",
"s... | 4 | stack_v2_sparse_classes_30k_train_006794 | Implement the Python class `SyncwerkCcnetModelsRouter` described below.
Class description:
A router to control all database operations on models related to ccnet
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet... | Implement the Python class `SyncwerkCcnetModelsRouter` described below.
Class description:
A router to control all database operations on models related to ccnet
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet... | 13b3ed26a04248211ef91ca70dccc617be27a3c3 | <|skeleton|>
class SyncwerkCcnetModelsRouter:
"""A router to control all database operations on models related to ccnet"""
def db_for_read(self, model, **hints):
"""Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet'"""
<|body_0|>
def db_for_write(self, model... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SyncwerkCcnetModelsRouter:
"""A router to control all database operations on models related to ccnet"""
def db_for_read(self, model, **hints):
"""Point all operations which has app_label='syncwerk_ccnet_models' models to 'ccnet'"""
if model._meta.app_label == 'syncwerk_ccnet_models':
... | the_stack_v2_python_sparse | fhs/usr/share/python/syncwerk/restapi/restapi/syncwerk_ccnet_models/routers.py | syncwerk/syncwerk-server-restapi | train | 0 |
04021339b4be3ae193900a1857477640ee228926 | [
"probabilities = []\nlist_theoretical_amplitude = []\nbest_algorithms = []\nconfigurations = []\nlist_number_calls_made = []\nfor eta_group in self._eta_groups:\n self._global_eta_group = eta_group\n result = self._compute_theoretical_best_configuration()\n best_algorithms.append(result['best_algorithm'])\... | <|body_start_0|>
probabilities = []
list_theoretical_amplitude = []
best_algorithms = []
configurations = []
list_number_calls_made = []
for eta_group in self._eta_groups:
self._global_eta_group = eta_group
result = self._compute_theoretical_best_c... | Representation of the theoretical One Shot Optimization | TheoreticalOneShotOptimization | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TheoreticalOneShotOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations:
"""Finds out the theoretical optimal configuration for each pair of attenuation levels"""
<|... | stack_v2_sparse_classes_36k_train_008945 | 3,017 | permissive | [
{
"docstring": "Finds out the theoretical optimal configuration for each pair of attenuation levels",
"name": "compute_theoretical_optimal_results",
"signature": "def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations"
},
{
"docstring": "Find out the theoretical... | 2 | stack_v2_sparse_classes_30k_train_017644 | Implement the Python class `TheoreticalOneShotOptimization` described below.
Class description:
Representation of the theoretical One Shot Optimization
Method signatures and docstrings:
- def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations: Finds out the theoretical optimal config... | Implement the Python class `TheoreticalOneShotOptimization` described below.
Class description:
Representation of the theoretical One Shot Optimization
Method signatures and docstrings:
- def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations: Finds out the theoretical optimal config... | ea37fca21fc4c8cf7ac6a39b3a6666e8a4fe5a19 | <|skeleton|>
class TheoreticalOneShotOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations:
"""Finds out the theoretical optimal configuration for each pair of attenuation levels"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TheoreticalOneShotOptimization:
"""Representation of the theoretical One Shot Optimization"""
def compute_theoretical_optimal_results(self) -> TheoreticalOneShotOptimalConfigurations:
"""Finds out the theoretical optimal configuration for each pair of attenuation levels"""
probabilities =... | the_stack_v2_python_sparse | qcd/optimizations/theoreticaloneshotoptimization.py | iamtxena/quantum-channel-discrimination | train | 0 |
e669bce7a6f60541978b3057826e3637ec22734b | [
"if message is not None:\n self.message = message\nif code is not None:\n self.code = code",
"if len(value) > 255:\n raise ValidationError(self.message, self.code)\nif value[-1] == '.':\n value = value[:-1]\nif not self.regex.match(value):\n raise ValidationError(self.message, self.code)"
] | <|body_start_0|>
if message is not None:
self.message = message
if code is not None:
self.code = code
<|end_body_0|>
<|body_start_1|>
if len(value) > 255:
raise ValidationError(self.message, self.code)
if value[-1] == '.':
value = value[:-... | Validator for fqdn. | HostnameValidator | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostnameValidator:
"""Validator for fqdn."""
def __init__(self, message=None, code=None):
"""Constructor."""
<|body_0|>
def __call__(self, value):
"""Check value."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if message is not None:
... | stack_v2_sparse_classes_36k_train_008946 | 1,896 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, message=None, code=None)"
},
{
"docstring": "Check value.",
"name": "__call__",
"signature": "def __call__(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007712 | Implement the Python class `HostnameValidator` described below.
Class description:
Validator for fqdn.
Method signatures and docstrings:
- def __init__(self, message=None, code=None): Constructor.
- def __call__(self, value): Check value. | Implement the Python class `HostnameValidator` described below.
Class description:
Validator for fqdn.
Method signatures and docstrings:
- def __init__(self, message=None, code=None): Constructor.
- def __call__(self, value): Check value.
<|skeleton|>
class HostnameValidator:
"""Validator for fqdn."""
def _... | df699aab0799ec1725b6b89be38e56285821c889 | <|skeleton|>
class HostnameValidator:
"""Validator for fqdn."""
def __init__(self, message=None, code=None):
"""Constructor."""
<|body_0|>
def __call__(self, value):
"""Check value."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HostnameValidator:
"""Validator for fqdn."""
def __init__(self, message=None, code=None):
"""Constructor."""
if message is not None:
self.message = message
if code is not None:
self.code = code
def __call__(self, value):
"""Check value."""
... | the_stack_v2_python_sparse | modoboa/lib/validators.py | modoboa/modoboa | train | 2,201 |
cd14bc5ce3550f3b2bdb47912c2ac6c9aeb5d2cb | [
"self.driver = driver\nself.value = value\nself.by = by\nself.locator = (self.by, self.value)\nself.webElement = None",
"element = WebDriverWait(self.driver, 10).until(EC.visibility_of_element_located(locator=self.locator))\nself.webElement = element\nreturn None",
"element = WebDriverWait(self.driver, 10).unti... | <|body_start_0|>
self.driver = driver
self.value = value
self.by = by
self.locator = (self.by, self.value)
self.webElement = None
<|end_body_0|>
<|body_start_1|>
element = WebDriverWait(self.driver, 10).until(EC.visibility_of_element_located(locator=self.locator))
... | BaseElement | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseElement:
def __init__(self, driver, by, value):
"""This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: arg3 and is element locator"""
<|body_0|>
def find(self):
"""This finds the eleme... | stack_v2_sparse_classes_36k_train_008947 | 1,218 | no_license | [
{
"docstring": "This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: arg3 and is element locator",
"name": "__init__",
"signature": "def __init__(self, driver, by, value)"
},
{
"docstring": "This finds the element on t... | 3 | null | Implement the Python class `BaseElement` described below.
Class description:
Implement the BaseElement class.
Method signatures and docstrings:
- def __init__(self, driver, by, value): This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: ar... | Implement the Python class `BaseElement` described below.
Class description:
Implement the BaseElement class.
Method signatures and docstrings:
- def __init__(self, driver, by, value): This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: ar... | 2b7edfafc4e448bd558c034044570496ca68bf2d | <|skeleton|>
class BaseElement:
def __init__(self, driver, by, value):
"""This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: arg3 and is element locator"""
<|body_0|>
def find(self):
"""This finds the eleme... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseElement:
def __init__(self, driver, by, value):
"""This initializes the values :param driver: arg1 and is driver which runs chrome :param value: arg2 and is element value :param by: arg3 and is element locator"""
self.driver = driver
self.value = value
self.by = by
... | the_stack_v2_python_sparse | Page_Object_Model2/base_element.py | gsudarshan1990/Training_Projects | train | 0 | |
bbf771a38895a27528da1f5fce3587b4fa42e030 | [
"self.post_parser = reqparse.RequestParser()\nself.post_parser.add_argument('Name', type=str, required=True, help='No rule object name provided', location='json')\nself.post_parser.add_argument('Method', type=str, required=True, help='No rule method provided', location='json')\nself.post_parser.add_argument('Role',... | <|body_start_0|>
self.post_parser = reqparse.RequestParser()
self.post_parser.add_argument('Name', type=str, required=True, help='No rule object name provided', location='json')
self.post_parser.add_argument('Method', type=str, required=True, help='No rule method provided', location='json')
... | DefaultRules | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultRules:
def __init__(self):
"""Constructeur: liste les champs attendus dans le corps HTML"""
<|body_0|>
def get(self):
"""affiche toutes les regles par defaut associees aux noms d'objets"""
<|body_1|>
def post(self):
"""ajoute une regle par... | stack_v2_sparse_classes_36k_train_008948 | 2,623 | no_license | [
{
"docstring": "Constructeur: liste les champs attendus dans le corps HTML",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "affiche toutes les regles par defaut associees aux noms d'objets",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_020199 | Implement the Python class `DefaultRules` described below.
Class description:
Implement the DefaultRules class.
Method signatures and docstrings:
- def __init__(self): Constructeur: liste les champs attendus dans le corps HTML
- def get(self): affiche toutes les regles par defaut associees aux noms d'objets
- def pos... | Implement the Python class `DefaultRules` described below.
Class description:
Implement the DefaultRules class.
Method signatures and docstrings:
- def __init__(self): Constructeur: liste les champs attendus dans le corps HTML
- def get(self): affiche toutes les regles par defaut associees aux noms d'objets
- def pos... | 8f107644a74fe46827ec5ed53d0457022bd1608b | <|skeleton|>
class DefaultRules:
def __init__(self):
"""Constructeur: liste les champs attendus dans le corps HTML"""
<|body_0|>
def get(self):
"""affiche toutes les regles par defaut associees aux noms d'objets"""
<|body_1|>
def post(self):
"""ajoute une regle par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DefaultRules:
def __init__(self):
"""Constructeur: liste les champs attendus dans le corps HTML"""
self.post_parser = reqparse.RequestParser()
self.post_parser.add_argument('Name', type=str, required=True, help='No rule object name provided', location='json')
self.post_parser.a... | the_stack_v2_python_sparse | authapp/view_def_rules.py | ldurandadomia/Flask-Restful | train | 0 | |
b503371719c19983f130de0cad10ad51b0deb2c8 | [
"rules = [['(?i)([aeiou])x$', '\\\\1x'], ['(?i)([])([ns])$', '|1\\\\2es'], ['(?i)(^[bcdfghjklmnpqrstvwxyz]*)an$', '\\\\1anes'], ['(?i)([])s$', '|1ses'], ['(?i)(^[bcdfghjklmnpqrstvwxyz]*)([aeiou])([ns])$', '\\\\1\\\\2\\\\3es'], ['(?i)([aeiou])$', '\\\\1s'], ['(?i)([aeiou])s$', '\\\\1s'], ['(?i)([])(s)$', '|1\\\\2es'... | <|body_start_0|>
rules = [['(?i)([aeiou])x$', '\\1x'], ['(?i)([])([ns])$', '|1\\2es'], ['(?i)(^[bcdfghjklmnpqrstvwxyz]*)an$', '\\1anes'], ['(?i)([])s$', '|1ses'], ['(?i)(^[bcdfghjklmnpqrstvwxyz]*)([aeiou])([ns])$', '\\1\\2\\3es'], ['(?i)([aeiou])$', '\\1s'], ['(?i)([aeiou])s$', '\\1s'], ['(?i)([])(s)$', '|1\\2e... | Inflector for pluralize and singularize Spanish nouns. | Spanish | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Spanish:
"""Inflector for pluralize and singularize Spanish nouns."""
def pluralize(self, word):
"""Pluralizes Spanish nouns."""
<|body_0|>
def singularize(self, word):
"""Singularizes Spanish nouns."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_008949 | 36,915 | no_license | [
{
"docstring": "Pluralizes Spanish nouns.",
"name": "pluralize",
"signature": "def pluralize(self, word)"
},
{
"docstring": "Singularizes Spanish nouns.",
"name": "singularize",
"signature": "def singularize(self, word)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000162 | Implement the Python class `Spanish` described below.
Class description:
Inflector for pluralize and singularize Spanish nouns.
Method signatures and docstrings:
- def pluralize(self, word): Pluralizes Spanish nouns.
- def singularize(self, word): Singularizes Spanish nouns. | Implement the Python class `Spanish` described below.
Class description:
Inflector for pluralize and singularize Spanish nouns.
Method signatures and docstrings:
- def pluralize(self, word): Pluralizes Spanish nouns.
- def singularize(self, word): Singularizes Spanish nouns.
<|skeleton|>
class Spanish:
"""Inflec... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class Spanish:
"""Inflector for pluralize and singularize Spanish nouns."""
def pluralize(self, word):
"""Pluralizes Spanish nouns."""
<|body_0|>
def singularize(self, word):
"""Singularizes Spanish nouns."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Spanish:
"""Inflector for pluralize and singularize Spanish nouns."""
def pluralize(self, word):
"""Pluralizes Spanish nouns."""
rules = [['(?i)([aeiou])x$', '\\1x'], ['(?i)([])([ns])$', '|1\\2es'], ['(?i)(^[bcdfghjklmnpqrstvwxyz]*)an$', '\\1anes'], ['(?i)([])s$', '|1ses'], ['(?i)(^[bcdfg... | the_stack_v2_python_sparse | repoData/noklesta-SublimeRailsNav/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
88c10e162d8c9e4f32954becb73f9742e39f2479 | [
"super(AdbShellSshConnectionBuilder, self).__init__(*args, **kwargs)\nself._serial_number = None\nreturn",
"if self._serial_number is None:\n if hasattr(self.parameters, 'serial_number'):\n self._serial_number = self.parameters.serial_number\nreturn self._serial_number",
"if self._connection is None:\... | <|body_start_0|>
super(AdbShellSshConnectionBuilder, self).__init__(*args, **kwargs)
self._serial_number = None
return
<|end_body_0|>
<|body_start_1|>
if self._serial_number is None:
if hasattr(self.parameters, 'serial_number'):
self._serial_number = self.par... | A class to build an adb-shell connection over ssh | AdbShellSshConnectionBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdbShellSshConnectionBuilder:
"""A class to build an adb-shell connection over ssh"""
def __init__(self, *args, **kwargs):
""":param: - `parameters`: An object with `hostname`, `username`, and `password` attributes"""
<|body_0|>
def serial_number(self):
"""A seri... | stack_v2_sparse_classes_36k_train_008950 | 10,538 | permissive | [
{
"docstring": ":param: - `parameters`: An object with `hostname`, `username`, and `password` attributes",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "A serial number for the USB connection",
"name": "serial_number",
"signature": "def serial_... | 3 | stack_v2_sparse_classes_30k_train_016716 | Implement the Python class `AdbShellSshConnectionBuilder` described below.
Class description:
A class to build an adb-shell connection over ssh
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): :param: - `parameters`: An object with `hostname`, `username`, and `password` attributes
- def serial... | Implement the Python class `AdbShellSshConnectionBuilder` described below.
Class description:
A class to build an adb-shell connection over ssh
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): :param: - `parameters`: An object with `hostname`, `username`, and `password` attributes
- def serial... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class AdbShellSshConnectionBuilder:
"""A class to build an adb-shell connection over ssh"""
def __init__(self, *args, **kwargs):
""":param: - `parameters`: An object with `hostname`, `username`, and `password` attributes"""
<|body_0|>
def serial_number(self):
"""A seri... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdbShellSshConnectionBuilder:
"""A class to build an adb-shell connection over ssh"""
def __init__(self, *args, **kwargs):
""":param: - `parameters`: An object with `hostname`, `username`, and `password` attributes"""
super(AdbShellSshConnectionBuilder, self).__init__(*args, **kwargs)
... | the_stack_v2_python_sparse | apetools/builders/subbuilders/connectionbuilder.py | russell-n/oldape | train | 0 |
a68ac4fff2c6dd140f5baecc0b0d38453e065515 | [
"datafile = open(trace_file, 'r')\ntrace_list = []\nwhile True:\n line = datafile.readline()\n if not line:\n break\n PC, TNT = line.split()\n PC = int(PC, 16)\n TNT = int(TNT)\n trace = Trace(PC, TNT)\n trace_list.append(trace)\nreturn trace_list",
"binary_address = bin(int(address))[... | <|body_start_0|>
datafile = open(trace_file, 'r')
trace_list = []
while True:
line = datafile.readline()
if not line:
break
PC, TNT = line.split()
PC = int(PC, 16)
TNT = int(TNT)
trace = Trace(PC, TNT)
... | TraceGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TraceGenerator:
def trace_list_generator(trace_file):
"""Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: trace.txt :return: a list of trace"""
<|body_0|>
def input_vector_generator(global_hr, local... | stack_v2_sparse_classes_36k_train_008951 | 1,596 | no_license | [
{
"docstring": "Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: trace.txt :return: a list of trace",
"name": "trace_list_generator",
"signature": "def trace_list_generator(trace_file)"
},
{
"docstring": ":param global_... | 2 | null | Implement the Python class `TraceGenerator` described below.
Class description:
Implement the TraceGenerator class.
Method signatures and docstrings:
- def trace_list_generator(trace_file): Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: tr... | Implement the Python class `TraceGenerator` described below.
Class description:
Implement the TraceGenerator class.
Method signatures and docstrings:
- def trace_list_generator(trace_file): Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: tr... | 2711bc08f15266bec4ca135e8e3e629df46713eb | <|skeleton|>
class TraceGenerator:
def trace_list_generator(trace_file):
"""Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: trace.txt :return: a list of trace"""
<|body_0|>
def input_vector_generator(global_hr, local... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TraceGenerator:
def trace_list_generator(trace_file):
"""Transfer trace.txt into a list of trace, where trace.PC is the decimal address, trace.TNT is branch result :param trace_file: trace.txt :return: a list of trace"""
datafile = open(trace_file, 'r')
trace_list = []
while Tr... | the_stack_v2_python_sparse | 6.基于机器学习的CPU分支预测/Trace_Initializer.py | unlimitediw/CheckCode | train | 0 | |
3244bf8ea0d56d10eea595fbe67aa8ccbe21fafd | [
"super(KeepLaneTest, self).__init__(name, actor, 0, None, optional)\nself.logger.debug('%s.__init__()' % self.__class__.__name__)\nworld = self.actor.get_world()\nblueprint = world.get_blueprint_library().find('sensor.other.lane_invasion')\nself._lane_sensor = world.spawn_actor(blueprint, carla.Transform(), attach_... | <|body_start_0|>
super(KeepLaneTest, self).__init__(name, actor, 0, None, optional)
self.logger.debug('%s.__init__()' % self.__class__.__name__)
world = self.actor.get_world()
blueprint = world.get_blueprint_library().find('sensor.other.lane_invasion')
self._lane_sensor = world.s... | This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result | KeepLaneTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KeepLaneTest:
"""This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result"""
def __init__(self, actor, optional=False, name='CheckKeepL... | stack_v2_sparse_classes_36k_train_008952 | 44,616 | permissive | [
{
"docstring": "Construction with sensor setup",
"name": "__init__",
"signature": "def __init__(self, actor, optional=False, name='CheckKeepLane')"
},
{
"docstring": "Check lane invasion count",
"name": "update",
"signature": "def update(self)"
},
{
"docstring": "Cleanup sensor",... | 4 | null | Implement the Python class `KeepLaneTest` described below.
Class description:
This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result
Method signatures and docs... | Implement the Python class `KeepLaneTest` described below.
Class description:
This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result
Method signatures and docs... | 8ab0894b92e1f994802a218002021ee075c405bf | <|skeleton|>
class KeepLaneTest:
"""This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result"""
def __init__(self, actor, optional=False, name='CheckKeepL... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KeepLaneTest:
"""This class contains an atomic test for keeping lane. Important parameters: - actor: CARLA actor to be used for this test - optional [optional]: If True, the result is not considered for an overall pass/fail result"""
def __init__(self, actor, optional=False, name='CheckKeepLane'):
... | the_stack_v2_python_sparse | carla_rllib/carla_rllib-prak_evaluator-carla_rllib-prak_evaluator/carla_rllib/prak_evaluator/srunner/scenarioconfigs/scenariomanager/scenarioatomics/atomic_criteria.py | TinaMenke/Deep-Reinforcement-Learning | train | 9 |
d1de51861655c5b6f23ac101ab5a67507e31988a | [
"self.shooters_total = difficulty\nself.asteroids_total = difficulty\nsuper().__init__(**kwargs)",
"player = GamePlayer.random()\nshooters = HunterGroup.random(n=self.shooters_total)\nshooters.spread(100)\nplayers = PlayerGroup(player, activate=True, shooting=True)\nspaceships = SuperSpaceShipGroup(players, shoot... | <|body_start_0|>
self.shooters_total = difficulty
self.asteroids_total = difficulty
super().__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
player = GamePlayer.random()
shooters = HunterGroup.random(n=self.shooters_total)
shooters.spread(100)
players = PlayerG... | Level in which the goal is to destroy all hunters. | DestroyHunters | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DestroyHunters:
"""Level in which the goal is to destroy all hunters."""
def __init__(self, difficulty, **kwargs):
"""Create the level by creating the groups."""
<|body_0|>
def start(self):
"""Start the game by creating the game group with hunters."""
<|b... | stack_v2_sparse_classes_36k_train_008953 | 10,293 | no_license | [
{
"docstring": "Create the level by creating the groups.",
"name": "__init__",
"signature": "def __init__(self, difficulty, **kwargs)"
},
{
"docstring": "Start the game by creating the game group with hunters.",
"name": "start",
"signature": "def start(self)"
},
{
"docstring": "S... | 3 | null | Implement the Python class `DestroyHunters` described below.
Class description:
Level in which the goal is to destroy all hunters.
Method signatures and docstrings:
- def __init__(self, difficulty, **kwargs): Create the level by creating the groups.
- def start(self): Start the game by creating the game group with hu... | Implement the Python class `DestroyHunters` described below.
Class description:
Level in which the goal is to destroy all hunters.
Method signatures and docstrings:
- def __init__(self, difficulty, **kwargs): Create the level by creating the groups.
- def start(self): Start the game by creating the game group with hu... | ebfcaaf4a028eddb36bbc99184eb3f7a86eb24ed | <|skeleton|>
class DestroyHunters:
"""Level in which the goal is to destroy all hunters."""
def __init__(self, difficulty, **kwargs):
"""Create the level by creating the groups."""
<|body_0|>
def start(self):
"""Start the game by creating the game group with hunters."""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DestroyHunters:
"""Level in which the goal is to destroy all hunters."""
def __init__(self, difficulty, **kwargs):
"""Create the level by creating the groups."""
self.shooters_total = difficulty
self.asteroids_total = difficulty
super().__init__(**kwargs)
def start(se... | the_stack_v2_python_sparse | Game Structure/geometry/version5/myasteroidgame.py | MarcPartensky/Python-Games | train | 2 |
aa511bcdceb466eae4e2a0f0e3d087b8dd1413b0 | [
"super(ChannelIncreaseBlock, self).__init__()\nself.layers = list()\nfor block_name in blocks:\n self.layers.append(NAME_BLOCKS[block_name](base_channel=base_channel))\nself.layers = Sequential(*self.layers)\nself.blocks = self.layers.children() if isinstance(self.layers.children(), list) else list(self.layers.c... | <|body_start_0|>
super(ChannelIncreaseBlock, self).__init__()
self.layers = list()
for block_name in blocks:
self.layers.append(NAME_BLOCKS[block_name](base_channel=base_channel))
self.layers = Sequential(*self.layers)
self.blocks = self.layers.children() if isinstanc... | Channel increase block, which passes several blocks, and concat the result on channel dim. | ChannelIncreaseBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChannelIncreaseBlock:
"""Channel increase block, which passes several blocks, and concat the result on channel dim."""
def __init__(self, blocks, base_channel):
"""Construct the class ChannelIncreaseBlock. :param blocks: list of string of the blocks :param base_channel: number of inp... | stack_v2_sparse_classes_36k_train_008954 | 5,337 | permissive | [
{
"docstring": "Construct the class ChannelIncreaseBlock. :param blocks: list of string of the blocks :param base_channel: number of input channels",
"name": "__init__",
"signature": "def __init__(self, blocks, base_channel)"
},
{
"docstring": "Calculate the output of the model. :param x: input ... | 2 | null | Implement the Python class `ChannelIncreaseBlock` described below.
Class description:
Channel increase block, which passes several blocks, and concat the result on channel dim.
Method signatures and docstrings:
- def __init__(self, blocks, base_channel): Construct the class ChannelIncreaseBlock. :param blocks: list o... | Implement the Python class `ChannelIncreaseBlock` described below.
Class description:
Channel increase block, which passes several blocks, and concat the result on channel dim.
Method signatures and docstrings:
- def __init__(self, blocks, base_channel): Construct the class ChannelIncreaseBlock. :param blocks: list o... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class ChannelIncreaseBlock:
"""Channel increase block, which passes several blocks, and concat the result on channel dim."""
def __init__(self, blocks, base_channel):
"""Construct the class ChannelIncreaseBlock. :param blocks: list of string of the blocks :param base_channel: number of inp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChannelIncreaseBlock:
"""Channel increase block, which passes several blocks, and concat the result on channel dim."""
def __init__(self, blocks, base_channel):
"""Construct the class ChannelIncreaseBlock. :param blocks: list of string of the blocks :param base_channel: number of input channels""... | the_stack_v2_python_sparse | zeus/networks/mtm_sr.py | huawei-noah/xingtian | train | 308 |
d9f8ac579e96ff4f0e71ccbd81d1691530d6cea7 | [
"values = super(website_sale, self).checkout_values(data)\nif data:\n values['checkout'].update({'accept_invoice': bool(data.get('accept_invoice', False))})\nreturn values",
"cr, uid, context, registry = (request.cr, request.uid, request.context, request.registry)\npartner_obj = registry.get('res.partner')\nsu... | <|body_start_0|>
values = super(website_sale, self).checkout_values(data)
if data:
values['checkout'].update({'accept_invoice': bool(data.get('accept_invoice', False))})
return values
<|end_body_0|>
<|body_start_1|>
cr, uid, context, registry = (request.cr, request.uid, requ... | website_sale | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class website_sale:
def checkout_values(self, data=None):
"""Overload to add invoice param"""
<|body_0|>
def checkout_form_save(self, checkout):
"""overload to store accept invoice checkbox"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
values = super(we... | stack_v2_sparse_classes_36k_train_008955 | 1,461 | no_license | [
{
"docstring": "Overload to add invoice param",
"name": "checkout_values",
"signature": "def checkout_values(self, data=None)"
},
{
"docstring": "overload to store accept invoice checkbox",
"name": "checkout_form_save",
"signature": "def checkout_form_save(self, checkout)"
}
] | 2 | null | Implement the Python class `website_sale` described below.
Class description:
Implement the website_sale class.
Method signatures and docstrings:
- def checkout_values(self, data=None): Overload to add invoice param
- def checkout_form_save(self, checkout): overload to store accept invoice checkbox | Implement the Python class `website_sale` described below.
Class description:
Implement the website_sale class.
Method signatures and docstrings:
- def checkout_values(self, data=None): Overload to add invoice param
- def checkout_form_save(self, checkout): overload to store accept invoice checkbox
<|skeleton|>
clas... | 3681cbad05d5748198318fc1774be77b5f6b420e | <|skeleton|>
class website_sale:
def checkout_values(self, data=None):
"""Overload to add invoice param"""
<|body_0|>
def checkout_form_save(self, checkout):
"""overload to store accept invoice checkbox"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class website_sale:
def checkout_values(self, data=None):
"""Overload to add invoice param"""
values = super(website_sale, self).checkout_values(data)
if data:
values['checkout'].update({'accept_invoice': bool(data.get('accept_invoice', False))})
return values
def ch... | the_stack_v2_python_sparse | website_sale_request_invoice/controllers/main.py | dbertha/odoo-addons | train | 1 | |
70c1a75cd41ccf9d1878125313543b58ef428e0a | [
"similarity_calc = region_similarity_calculator.IouSimilarity()\nmatcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=unmatched_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)\nbox_coder = faster_rcnn_box_coder.FasterRcnnBoxCoder()\nself._target_assigner = targe... | <|body_start_0|>
similarity_calc = region_similarity_calculator.IouSimilarity()
matcher = argmax_matcher.ArgMaxMatcher(match_threshold, unmatched_threshold=unmatched_threshold, negatives_lower_than_unmatched=True, force_match_for_each_row=True)
box_coder = faster_rcnn_box_coder.FasterRcnnBoxCode... | Labeler for multiscale anchor boxes. | AnchorLabeler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.7, unmatched_threshold=0.3, rpn_batch_size_per_im=256, rpn_fg_fraction=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of cl... | stack_v2_sparse_classes_36k_train_008956 | 23,318 | permissive | [
{
"docstring": "Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. num_classes: integer number representing number of classes in the dataset. match_threshold: a float number between 0 and 1 representing the lower-bound threshold to assign positive labels for anch... | 3 | stack_v2_sparse_classes_30k_train_007407 | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.7, unmatched_threshold=0.3, rpn_batch_size_per_im=256, rpn_fg_fraction=0.5): Constructs anchor labeler to a... | Implement the Python class `AnchorLabeler` described below.
Class description:
Labeler for multiscale anchor boxes.
Method signatures and docstrings:
- def __init__(self, anchors, num_classes, match_threshold=0.7, unmatched_threshold=0.3, rpn_batch_size_per_im=256, rpn_fg_fraction=0.5): Constructs anchor labeler to a... | 4b387b6ad1066f2ee67b112e152e15cf37038130 | <|skeleton|>
class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.7, unmatched_threshold=0.3, rpn_batch_size_per_im=256, rpn_fg_fraction=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of cl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnchorLabeler:
"""Labeler for multiscale anchor boxes."""
def __init__(self, anchors, num_classes, match_threshold=0.7, unmatched_threshold=0.3, rpn_batch_size_per_im=256, rpn_fg_fraction=0.5):
"""Constructs anchor labeler to assign labels to anchors. Args: anchors: an instance of class Anchors. ... | the_stack_v2_python_sparse | models/experimental/mask_rcnn/anchors.py | boristown/tpu | train | 5 |
70c31a39e9a68781adcf48ae144d5102247855eb | [
"self.__df = df\nself.__strategy = strategy\nself.__pos_func = pos_func\nself.__evaluate_func = evaluate_func\nself.__result_handler = result_handler\nself.__context = context",
"if self.__strategy.available_to_calculate(self.__df):\n signal_df = self.__strategy.calculate_signals(self.__df)\n pos_df = self.... | <|body_start_0|>
self.__df = df
self.__strategy = strategy
self.__pos_func = pos_func
self.__evaluate_func = evaluate_func
self.__result_handler = result_handler
self.__context = context
<|end_body_0|>
<|body_start_1|>
if self.__strategy.available_to_calculate(se... | 单次回测逻辑 | StrategyBacktest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StrategyBacktest:
"""单次回测逻辑"""
def __init__(self, df: pd.DataFrame, strategy: BaseExchangeStrategy, pos_func, evaluate_func, result_handler, context=None):
"""回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, open, high, low, close, volume] strategy : BaseExchangeSt... | stack_v2_sparse_classes_36k_train_008957 | 1,768 | permissive | [
{
"docstring": "回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, open, high, low, close, volume] strategy : BaseExchangeStrategy 策略 pos_func: (df) -> pos_df 仓位方法 evaluate_func : (pod_df) -> df_ev 评估方法 result_handler : (context, df_pos, df_ev, strategy, error_des) -> result_df 结果处理",
"name... | 2 | stack_v2_sparse_classes_30k_train_011247 | Implement the Python class `StrategyBacktest` described below.
Class description:
单次回测逻辑
Method signatures and docstrings:
- def __init__(self, df: pd.DataFrame, strategy: BaseExchangeStrategy, pos_func, evaluate_func, result_handler, context=None): 回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, ... | Implement the Python class `StrategyBacktest` described below.
Class description:
单次回测逻辑
Method signatures and docstrings:
- def __init__(self, df: pd.DataFrame, strategy: BaseExchangeStrategy, pos_func, evaluate_func, result_handler, context=None): 回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, ... | 9a9a67d5298fe4e32c9419273f06cfa28b71b53a | <|skeleton|>
class StrategyBacktest:
"""单次回测逻辑"""
def __init__(self, df: pd.DataFrame, strategy: BaseExchangeStrategy, pos_func, evaluate_func, result_handler, context=None):
"""回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, open, high, low, close, volume] strategy : BaseExchangeSt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StrategyBacktest:
"""单次回测逻辑"""
def __init__(self, df: pd.DataFrame, strategy: BaseExchangeStrategy, pos_func, evaluate_func, result_handler, context=None):
"""回测配置初始化 Parameters ---------- df : pd.DataFrame [candle_begin_time, open, high, low, close, volume] strategy : BaseExchangeStrategy 策略 pos... | the_stack_v2_python_sparse | cy_widgets/backtest/strategy.py | cragod/CYWidgets | train | 1 |
1f6f4b9fdbc4758ecf8b23b43f45dfea993ffcb1 | [
"from ..jobfolder.ordered_dict import OrderedDict\nsuper(RelaxExtract.IntermediateMassExtract, self).__init__(*args, **kwargs)\nself.dicttype = OrderedDict\n' Type of dictionary to use. \\n \\n Always ordered dictionary for intermediate mass extraction.\\n Makes it easier to explore ongoing c... | <|body_start_0|>
from ..jobfolder.ordered_dict import OrderedDict
super(RelaxExtract.IntermediateMassExtract, self).__init__(*args, **kwargs)
self.dicttype = OrderedDict
' Type of dictionary to use. \n \n Always ordered dictionary for intermediate mass extraction.\n ... | Focuses on intermediate steps. | IntermediateMassExtract | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntermediateMassExtract:
"""Focuses on intermediate steps."""
def __init__(self, *args, **kwargs):
"""Makes sure we are using ordered dict."""
<|body_0|>
def __getitem__(self, value):
"""Gets intermediate step. Adds ability to get runs as numbers: ``self.details[... | stack_v2_sparse_classes_36k_train_008958 | 6,637 | no_license | [
{
"docstring": "Makes sure we are using ordered dict.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Gets intermediate step. Adds ability to get runs as numbers: ``self.details[0]`` is equivalent to ``self.details['relax/0']``",
"name": "__getitem... | 4 | null | Implement the Python class `IntermediateMassExtract` described below.
Class description:
Focuses on intermediate steps.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Makes sure we are using ordered dict.
- def __getitem__(self, value): Gets intermediate step. Adds ability to get runs as num... | Implement the Python class `IntermediateMassExtract` described below.
Class description:
Focuses on intermediate steps.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Makes sure we are using ordered dict.
- def __getitem__(self, value): Gets intermediate step. Adds ability to get runs as num... | 9c0ab667f94dc4629404a8ec99cbeaa323f0c8b3 | <|skeleton|>
class IntermediateMassExtract:
"""Focuses on intermediate steps."""
def __init__(self, *args, **kwargs):
"""Makes sure we are using ordered dict."""
<|body_0|>
def __getitem__(self, value):
"""Gets intermediate step. Adds ability to get runs as numbers: ``self.details[... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IntermediateMassExtract:
"""Focuses on intermediate steps."""
def __init__(self, *args, **kwargs):
"""Makes sure we are using ordered dict."""
from ..jobfolder.ordered_dict import OrderedDict
super(RelaxExtract.IntermediateMassExtract, self).__init__(*args, **kwargs)
self.... | the_stack_v2_python_sparse | dftcrystal/relax.py | Shibu778/LaDa | train | 0 |
435b2f192cd22e0af748734c701b465bcc46ee9f | [
"agent = request.user.userinfo.agent\ndata = ModelMessage.get_smtp_info(agent_id=agent.id)\ndata['password'] = ''\ncontext = {'status': 200, 'msg': '获取数据成功', 'data': data}\nreturn Response(context)",
"agent = request.user.userinfo.agent\nemail = ModelMessage.objects.get_or_create(agent=agent, type=1)[0]\nemail_se... | <|body_start_0|>
agent = request.user.userinfo.agent
data = ModelMessage.get_smtp_info(agent_id=agent.id)
data['password'] = ''
context = {'status': 200, 'msg': '获取数据成功', 'data': data}
return Response(context)
<|end_body_0|>
<|body_start_1|>
agent = request.user.userinfo... | 邮件服务信息 | SMTPinfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMTPinfo:
"""邮件服务信息"""
def get(self, request):
"""获取邮件配置信息"""
<|body_0|>
def put(self, request):
"""修改邮件配置信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
agent = request.user.userinfo.agent
data = ModelMessage.get_smtp_info(agent_id=a... | stack_v2_sparse_classes_36k_train_008959 | 32,690 | no_license | [
{
"docstring": "获取邮件配置信息",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "修改邮件配置信息",
"name": "put",
"signature": "def put(self, request)"
}
] | 2 | null | Implement the Python class `SMTPinfo` described below.
Class description:
邮件服务信息
Method signatures and docstrings:
- def get(self, request): 获取邮件配置信息
- def put(self, request): 修改邮件配置信息 | Implement the Python class `SMTPinfo` described below.
Class description:
邮件服务信息
Method signatures and docstrings:
- def get(self, request): 获取邮件配置信息
- def put(self, request): 修改邮件配置信息
<|skeleton|>
class SMTPinfo:
"""邮件服务信息"""
def get(self, request):
"""获取邮件配置信息"""
<|body_0|>
def put(se... | d6e025d7e9d9e3aecfd399c77f376130edd8a2df | <|skeleton|>
class SMTPinfo:
"""邮件服务信息"""
def get(self, request):
"""获取邮件配置信息"""
<|body_0|>
def put(self, request):
"""修改邮件配置信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SMTPinfo:
"""邮件服务信息"""
def get(self, request):
"""获取邮件配置信息"""
agent = request.user.userinfo.agent
data = ModelMessage.get_smtp_info(agent_id=agent.id)
data['password'] = ''
context = {'status': 200, 'msg': '获取数据成功', 'data': data}
return Response(context)
... | the_stack_v2_python_sparse | soc_system/views/set_views.py | sundw2015/841 | train | 4 |
f5629e682fd4bc02a02a90ffed28960461a4f6c6 | [
"event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_REQUEST', client=self.client_id, description=self.args.reason)\nflow.Events.PublishEvent('Audit', event, token=self.token)\nreturn self.ApprovalUrnBuilder(self.client_id.Path(), self.token.username, self.args.reason)",
"client = aff4.F... | <|body_start_0|>
event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_REQUEST', client=self.client_id, description=self.args.reason)
flow.Events.PublishEvent('Audit', event, token=self.token)
return self.ApprovalUrnBuilder(self.client_id.Path(), self.token.username, self... | A flow to request approval to access a client. | RequestClientApprovalFlow | [
"Apache-2.0",
"DOC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestClientApprovalFlow:
"""A flow to request approval to access a client."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
<|body_0|>
def BuildSubjectTitle(self):
"""Returns the string with subject's title."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_008960 | 28,119 | permissive | [
{
"docstring": "Builds approval object urn.",
"name": "BuildApprovalUrn",
"signature": "def BuildApprovalUrn(self)"
},
{
"docstring": "Returns the string with subject's title.",
"name": "BuildSubjectTitle",
"signature": "def BuildSubjectTitle(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004607 | Implement the Python class `RequestClientApprovalFlow` described below.
Class description:
A flow to request approval to access a client.
Method signatures and docstrings:
- def BuildApprovalUrn(self): Builds approval object urn.
- def BuildSubjectTitle(self): Returns the string with subject's title. | Implement the Python class `RequestClientApprovalFlow` described below.
Class description:
A flow to request approval to access a client.
Method signatures and docstrings:
- def BuildApprovalUrn(self): Builds approval object urn.
- def BuildSubjectTitle(self): Returns the string with subject's title.
<|skeleton|>
cl... | ba1648b97a76f844ffb8e1891cc9e2680f9b1c6e | <|skeleton|>
class RequestClientApprovalFlow:
"""A flow to request approval to access a client."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
<|body_0|>
def BuildSubjectTitle(self):
"""Returns the string with subject's title."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestClientApprovalFlow:
"""A flow to request approval to access a client."""
def BuildApprovalUrn(self):
"""Builds approval object urn."""
event = rdfvalue.AuditEvent(user=self.token.username, action='CLIENT_APPROVAL_REQUEST', client=self.client_id, description=self.args.reason)
... | the_stack_v2_python_sparse | lib/aff4_objects/security.py | defaultnamehere/grr | train | 3 |
3fbecc85055c7686cc1c130e31580696b39a86dd | [
"email = self.request.get('email')\ndate = self.request.get('date')\nself.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)",
"email = self.request.get('email')\ndate = self.request.get('date')\nself.hello_request(api_url='timeline/admin/invalidate/{}/{}'.form... | <|body_start_0|>
email = self.request.get('email')
date = self.request.get('date')
self.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)
<|end_body_0|>
<|body_start_1|>
email = self.request.get('email')
date = self.request.g... | TimelineAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
<|body_0|>
def post(self):
"""Invalidate cache for user timeline"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
email = self.request.get('email')
date = self.request.get('date')
... | stack_v2_sparse_classes_36k_train_008961 | 2,336 | no_license | [
{
"docstring": "Retrieve user timeline",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Invalidate cache for user timeline",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `TimelineAPI` described below.
Class description:
Implement the TimelineAPI class.
Method signatures and docstrings:
- def get(self): Retrieve user timeline
- def post(self): Invalidate cache for user timeline | Implement the Python class `TimelineAPI` described below.
Class description:
Implement the TimelineAPI class.
Method signatures and docstrings:
- def get(self): Retrieve user timeline
- def post(self): Invalidate cache for user timeline
<|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user tim... | 44a274372d72416d7f7f95d76b6882ca3b4baff7 | <|skeleton|>
class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
<|body_0|>
def post(self):
"""Invalidate cache for user timeline"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimelineAPI:
def get(self):
"""Retrieve user timeline"""
email = self.request.get('email')
date = self.request.get('date')
self.hello_request(api_url='timeline/admin/{}/{}'.format(email, date), type='GET', api_info=self.suripu_app)
def post(self):
"""Invalidate cac... | the_stack_v2_python_sparse | api/timeline.py | hello/hello-admin | train | 2 | |
75a6d6c96d50acb40e177503a01403ea348a7e0e | [
"self.seed = 33\nreset(self.seed)\nself.testing = testing\nself.layer = layer\nself.case = case\nself.model_dtype = self.testing.get('model_dtype')\npaddle.set_default_dtype(self.model_dtype)\nself.layer_name = self.layer.get('Layer').get('layer_name')\nself.layer_param = self.layer.get('Layer').get('params')\nself... | <|body_start_0|>
self.seed = 33
reset(self.seed)
self.testing = testing
self.layer = layer
self.case = case
self.model_dtype = self.testing.get('model_dtype')
paddle.set_default_dtype(self.model_dtype)
self.layer_name = self.layer.get('Layer').get('layer_n... | 构建Layer导出的通用类 | LayerExport | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LayerExport:
"""构建Layer导出的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
<|body_0|>
def jit_save(self):
"""jit.save(layer)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.seed = 33
reset(self.seed)
self.testing =... | stack_v2_sparse_classes_36k_train_008962 | 1,579 | no_license | [
{
"docstring": "初始化",
"name": "__init__",
"signature": "def __init__(self, testing, case, layer)"
},
{
"docstring": "jit.save(layer)",
"name": "jit_save",
"signature": "def jit_save(self)"
}
] | 2 | null | Implement the Python class `LayerExport` described below.
Class description:
构建Layer导出的通用类
Method signatures and docstrings:
- def __init__(self, testing, case, layer): 初始化
- def jit_save(self): jit.save(layer) | Implement the Python class `LayerExport` described below.
Class description:
构建Layer导出的通用类
Method signatures and docstrings:
- def __init__(self, testing, case, layer): 初始化
- def jit_save(self): jit.save(layer)
<|skeleton|>
class LayerExport:
"""构建Layer导出的通用类"""
def __init__(self, testing, case, layer):
... | bd3790ce72a2a26611b5eda3901651b5a809348f | <|skeleton|>
class LayerExport:
"""构建Layer导出的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
<|body_0|>
def jit_save(self):
"""jit.save(layer)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LayerExport:
"""构建Layer导出的通用类"""
def __init__(self, testing, case, layer):
"""初始化"""
self.seed = 33
reset(self.seed)
self.testing = testing
self.layer = layer
self.case = case
self.model_dtype = self.testing.get('model_dtype')
paddle.set_def... | the_stack_v2_python_sparse | framework/e2e/paddleLT/engine/export.py | PaddlePaddle/PaddleTest | train | 42 |
c418ec166e1284e0d99225df099e1d7cc6ed9c54 | [
"prefix_function = [0] * len(pattern)\nborder = 0\nfor i in range(1, len(pattern)):\n while border > 0 and pattern[i] != pattern[border]:\n border = prefix_function[border - 1]\n if pattern[i] == pattern[border]:\n border += 1\n else:\n border = 0\n prefix_function[i] = border\nretu... | <|body_start_0|>
prefix_function = [0] * len(pattern)
border = 0
for i in range(1, len(pattern)):
while border > 0 and pattern[i] != pattern[border]:
border = prefix_function[border - 1]
if pattern[i] == pattern[border]:
border += 1
... | Util | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Util:
def _compute_prefix_function(pattern):
"""Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the whole S. Examples: 'a' is a border of 'arba' 'ab' is a border of 'abcdab' 'abab' is a border ... | stack_v2_sparse_classes_36k_train_008963 | 3,748 | no_license | [
{
"docstring": "Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the whole S. Examples: 'a' is a border of 'arba' 'ab' is a border of 'abcdab' 'abab' is a border of 'ababab' 'ab' is not a border of 'ab' Definition: The... | 3 | stack_v2_sparse_classes_30k_train_010282 | Implement the Python class `Util` described below.
Class description:
Implement the Util class.
Method signatures and docstrings:
- def _compute_prefix_function(pattern): Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the ... | Implement the Python class `Util` described below.
Class description:
Implement the Util class.
Method signatures and docstrings:
- def _compute_prefix_function(pattern): Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the ... | 01dd6f0dadf62a520bcafafddf7bf2b79e8e2603 | <|skeleton|>
class Util:
def _compute_prefix_function(pattern):
"""Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the whole S. Examples: 'a' is a border of 'arba' 'ab' is a border of 'abcdab' 'abab' is a border ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Util:
def _compute_prefix_function(pattern):
"""Computes the prefix function on the pattern. Definition: The border of string S is a prefix, which is equal to a suffix of S, but not equal to the whole S. Examples: 'a' is a border of 'arba' 'ab' is a border of 'abcdab' 'abab' is a border of 'ababab' 'a... | the_stack_v2_python_sparse | course4-strings/assignments/assignment_003_suffix_array_matching/suffix_array_matching_with_kmp.py | dmitri-mamrukov/coursera-data-structures-and-algorithms | train | 1 | |
4bd2466bd0b7dd2a9cda0f53e216372bf9503a0a | [
"user_id = token_auth.current_user()\nsearch_dto = TeamSearchDTO()\nsearch_dto.team_name = request.args.get('team_name', None)\nsearch_dto.member = request.args.get('member', None)\nsearch_dto.manager = request.args.get('manager', None)\nsearch_dto.member_request = request.args.get('member_request', None)\nsearch_d... | <|body_start_0|>
user_id = token_auth.current_user()
search_dto = TeamSearchDTO()
search_dto.team_name = request.args.get('team_name', None)
search_dto.member = request.args.get('member', None)
search_dto.manager = request.args.get('manager', None)
search_dto.member_reque... | TeamsAllAPI | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamsAllAPI:
def get(self):
"""Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: query name: team_name description: name ... | stack_v2_sparse_classes_36k_train_008964 | 12,780 | permissive | [
{
"docstring": "Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: query name: team_name description: name of the team to filter by type: str defa... | 2 | stack_v2_sparse_classes_30k_train_020128 | Implement the Python class `TeamsAllAPI` described below.
Class description:
Implement the TeamsAllAPI class.
Method signatures and docstrings:
- def get(self): Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required... | Implement the Python class `TeamsAllAPI` described below.
Class description:
Implement the TeamsAllAPI class.
Method signatures and docstrings:
- def get(self): Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required... | 45bf3937c74902226096aee5b49e7abea62df524 | <|skeleton|>
class TeamsAllAPI:
def get(self):
"""Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: query name: team_name description: name ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeamsAllAPI:
def get(self):
"""Gets all teams --- tags: - teams produces: - application/json parameters: - in: header name: Authorization description: Base64 encoded session token required: true type: string default: Token sessionTokenHere== - in: query name: team_name description: name of the team to... | the_stack_v2_python_sparse | backend/api/teams/resources.py | hotosm/tasking-manager | train | 526 | |
7309c1a5226dcdfd7341a0e2d2b6bc5161404fc0 | [
"enterprise_client = EnterpriseApiClient(auth_token)\nenterprise_data = enterprise_client.get_with_access_to(user, enterprise_id)\nif not enterprise_data:\n return None\nreturn enterprise_data",
"enterprise_in_url = request.parser_context.get('kwargs', {}).get('enterprise_id', '')\nif 'enterprises_with_access'... | <|body_start_0|>
enterprise_client = EnterpriseApiClient(auth_token)
enterprise_data = enterprise_client.get_with_access_to(user, enterprise_id)
if not enterprise_data:
return None
return enterprise_data
<|end_body_0|>
<|body_start_1|>
enterprise_in_url = request.par... | Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise. | HasDataAPIDjangoGroupAccess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HasDataAPIDjangoGroupAccess:
"""Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise."""
def get_enterprise_with_access_to(self, auth_token, user, enterprise_id):
"""Get... | stack_v2_sparse_classes_36k_train_008965 | 4,847 | no_license | [
{
"docstring": "Get the enterprise customer data that the user has enterprise_data_api access to. Returns: enterprise or None if unable to get or user is not associated with an enterprise",
"name": "get_enterprise_with_access_to",
"signature": "def get_enterprise_with_access_to(self, auth_token, user, e... | 2 | stack_v2_sparse_classes_30k_train_011901 | Implement the Python class `HasDataAPIDjangoGroupAccess` described below.
Class description:
Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise.
Method signatures and docstrings:
- def get_enterprise_w... | Implement the Python class `HasDataAPIDjangoGroupAccess` described below.
Class description:
Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise.
Method signatures and docstrings:
- def get_enterprise_w... | d16a25b035b2e810b8ab2b0a2ac032b216562e26 | <|skeleton|>
class HasDataAPIDjangoGroupAccess:
"""Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise."""
def get_enterprise_with_access_to(self, auth_token, user, enterprise_id):
"""Get... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HasDataAPIDjangoGroupAccess:
"""Permission that checks to see if the request user is part of the enterprise_data_api django group. Also checks that the user is authorized for the request's enterprise."""
def get_enterprise_with_access_to(self, auth_token, user, enterprise_id):
"""Get the enterpri... | the_stack_v2_python_sparse | edx/app/analytics_api/venvs/analytics_api/lib/python2.7/site-packages/enterprise_data/permissions.py | JosiahKennedy/openedx-branded | train | 0 |
43bc742e88650eb5c8cbe3c29336985cf2a8c8c7 | [
"super(KNNDist, self).__init__()\nself.k = k\nself.alpha = alpha",
"B, K = pc.shape[:2]\npc = pc.transpose(2, 1)\ninner = -2.0 * torch.matmul(pc.transpose(2, 1), pc)\nxx = torch.sum(pc ** 2, dim=1, keepdim=True)\ndist = xx + inner + xx.transpose(2, 1)\nassert dist.min().item() >= -1e-06\nneg_value, _ = (-dist).to... | <|body_start_0|>
super(KNNDist, self).__init__()
self.k = k
self.alpha = alpha
<|end_body_0|>
<|body_start_1|>
B, K = pc.shape[:2]
pc = pc.transpose(2, 1)
inner = -2.0 * torch.matmul(pc.transpose(2, 1), pc)
xx = torch.sum(pc ** 2, dim=1, keepdim=True)
dis... | KNNDist | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
<|body_0|>
def forward(self, pc, wei... | stack_v2_sparse_classes_36k_train_008966 | 11,583 | permissive | [
{
"docstring": "Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05.",
"name": "__init__",
"signature": "def __init__(self, k=5, alpha=1.05)"
},
{
"docstring": "K... | 2 | stack_v2_sparse_classes_30k_train_011021 | Implement the Python class `KNNDist` described below.
Class description:
Implement the KNNDist class.
Method signatures and docstrings:
- def __init__(self, k=5, alpha=1.05): Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): thresh... | Implement the Python class `KNNDist` described below.
Class description:
Implement the KNNDist class.
Method signatures and docstrings:
- def __init__(self, k=5, alpha=1.05): Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): thresh... | 4e2462b66fa1eac90cfbf61fa0dc635d223fdf2f | <|skeleton|>
class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
<|body_0|>
def forward(self, pc, wei... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KNNDist:
def __init__(self, k=5, alpha=1.05):
"""Compute kNN distance punishment within a point cloud. Args: k (int, optional): kNN neighbor num. Defaults to 5. alpha (float, optional): threshold = mean + alpha * std. Defaults to 1.05."""
super(KNNDist, self).__init__()
self.k = k
... | the_stack_v2_python_sparse | baselines/attack/util/dist_utils.py | code-roamer/IF-Defense | train | 0 | |
4c4cdde8d51657a733b6cadd0cbfae3f28cff9db | [
"path = os.path.join(settings.data_path, settings.DATA['file_name'])\ntest_data = read_test_data.ReadExcel().read_sheet(path, sheet)\nreturn test_data",
"log_path = os.path.join(settings.test_log_path, settings.LOG['log_file'])\nlogger = test_log.get_log(name=settings.LOG['name'], level=settings.LOG['level'], log... | <|body_start_0|>
path = os.path.join(settings.data_path, settings.DATA['file_name'])
test_data = read_test_data.ReadExcel().read_sheet(path, sheet)
return test_data
<|end_body_0|>
<|body_start_1|>
log_path = os.path.join(settings.test_log_path, settings.LOG['log_file'])
logger =... | MiddleHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MiddleHandler:
def get_test_data(self, sheet):
"""读取data.xlsx的结果"""
<|body_0|>
def log_init(self):
"""log初始化"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
path = os.path.join(settings.data_path, settings.DATA['file_name'])
test_data = read... | stack_v2_sparse_classes_36k_train_008967 | 875 | no_license | [
{
"docstring": "读取data.xlsx的结果",
"name": "get_test_data",
"signature": "def get_test_data(self, sheet)"
},
{
"docstring": "log初始化",
"name": "log_init",
"signature": "def log_init(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017100 | Implement the Python class `MiddleHandler` described below.
Class description:
Implement the MiddleHandler class.
Method signatures and docstrings:
- def get_test_data(self, sheet): 读取data.xlsx的结果
- def log_init(self): log初始化 | Implement the Python class `MiddleHandler` described below.
Class description:
Implement the MiddleHandler class.
Method signatures and docstrings:
- def get_test_data(self, sheet): 读取data.xlsx的结果
- def log_init(self): log初始化
<|skeleton|>
class MiddleHandler:
def get_test_data(self, sheet):
"""读取data.xl... | abd4671b88b650a3b21d63ea50ffd5f64578826f | <|skeleton|>
class MiddleHandler:
def get_test_data(self, sheet):
"""读取data.xlsx的结果"""
<|body_0|>
def log_init(self):
"""log初始化"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MiddleHandler:
def get_test_data(self, sheet):
"""读取data.xlsx的结果"""
path = os.path.join(settings.data_path, settings.DATA['file_name'])
test_data = read_test_data.ReadExcel().read_sheet(path, sheet)
return test_data
def log_init(self):
"""log初始化"""
log_path... | the_stack_v2_python_sparse | middle_handler/middlehandler.py | wyuuu1210/autotest | train | 0 | |
39b9ed870d57e9cdc81824e3afec72738b037014 | [
"super(MMFasterRCNN, self).__init__()\ncfg = ConfigManager(cfg)\nlogger.info('===== BUILDING MODEL ======')\nself.featurizer = Featurizer(cfg)\nlogger.info(f'Built backbone {cfg.BACKBONE}')\nlogger.info('Building downstream components via shape testing')\nN, D, H, W = get_shape_info(self.featurizer.backbone, (1, 3,... | <|body_start_0|>
super(MMFasterRCNN, self).__init__()
cfg = ConfigManager(cfg)
logger.info('===== BUILDING MODEL ======')
self.featurizer = Featurizer(cfg)
logger.info(f'Built backbone {cfg.BACKBONE}')
logger.info('Building downstream components via shape testing')
... | MMFasterRCNN | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MMFasterRCNN:
def __init__(self, cfg):
"""Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs"""
<|body_0|>
def forward(self, input_windows, neighbor_windows, radii, angles, colors, proposals, device):
"""Process a... | stack_v2_sparse_classes_36k_train_008968 | 3,533 | permissive | [
{
"docstring": "Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs",
"name": "__init__",
"signature": "def __init__(self, cfg)"
},
{
"docstring": "Process an Image through the network :param input_windows: Tensor representing target window pi... | 3 | null | Implement the Python class `MMFasterRCNN` described below.
Class description:
Implement the MMFasterRCNN class.
Method signatures and docstrings:
- def __init__(self, cfg): Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs
- def forward(self, input_windows, neigh... | Implement the Python class `MMFasterRCNN` described below.
Class description:
Implement the MMFasterRCNN class.
Method signatures and docstrings:
- def __init__(self, cfg): Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs
- def forward(self, input_windows, neigh... | 5ed4a4c149e03773690668437d2f93aa532453c6 | <|skeleton|>
class MMFasterRCNN:
def __init__(self, cfg):
"""Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs"""
<|body_0|>
def forward(self, input_windows, neighbor_windows, radii, angles, colors, proposals, device):
"""Process a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MMFasterRCNN:
def __init__(self, cfg):
"""Initialize a MMFasterRCNN network :param cfg: configuration file path for the network, see model configs"""
super(MMFasterRCNN, self).__init__()
cfg = ConfigManager(cfg)
logger.info('===== BUILDING MODEL ======')
self.featurizer... | the_stack_v2_python_sparse | cosmos/ingestion/ingest/process/detection/src/torch_model/model/model.py | UW-COSMOS/Cosmos | train | 39 | |
e21a20afbea56534d5163025dc7f9af39c5520cd | [
"super().__init__()\naction_latent_features = 128\nif action_converter.is_singular_discrete:\n self.action_encoder = nn.Embedding(action_converter.shape[0], action_latent_features)\nelse:\n self.action_encoder = nn.Linear(action_converter.shape[0], action_latent_features)\nself.hidden = nn.Sequential(nn.Linea... | <|body_start_0|>
super().__init__()
action_latent_features = 128
if action_converter.is_singular_discrete:
self.action_encoder = nn.Embedding(action_converter.shape[0], action_latent_features)
else:
self.action_encoder = nn.Linear(action_converter.shape[0], action... | ForwardModel | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForwardModel:
def __init__(self, action_converter: ActionSpace, state_latent_features: int):
""":param action_converter: :param state_latent_features:"""
<|body_0|>
def forward(self, state_latent: torch.Tensor, action: torch.Tensor) -> torch.Tensor:
""":param state_l... | stack_v2_sparse_classes_36k_train_008969 | 8,668 | permissive | [
{
"docstring": ":param action_converter: :param state_latent_features:",
"name": "__init__",
"signature": "def __init__(self, action_converter: ActionSpace, state_latent_features: int)"
},
{
"docstring": ":param state_latent: :param action: :return:",
"name": "forward",
"signature": "def... | 2 | stack_v2_sparse_classes_30k_train_016635 | Implement the Python class `ForwardModel` described below.
Class description:
Implement the ForwardModel class.
Method signatures and docstrings:
- def __init__(self, action_converter: ActionSpace, state_latent_features: int): :param action_converter: :param state_latent_features:
- def forward(self, state_latent: to... | Implement the Python class `ForwardModel` described below.
Class description:
Implement the ForwardModel class.
Method signatures and docstrings:
- def __init__(self, action_converter: ActionSpace, state_latent_features: int): :param action_converter: :param state_latent_features:
- def forward(self, state_latent: to... | 21e3564696062b67151b013fd5e47df46cf44aa5 | <|skeleton|>
class ForwardModel:
def __init__(self, action_converter: ActionSpace, state_latent_features: int):
""":param action_converter: :param state_latent_features:"""
<|body_0|>
def forward(self, state_latent: torch.Tensor, action: torch.Tensor) -> torch.Tensor:
""":param state_l... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ForwardModel:
def __init__(self, action_converter: ActionSpace, state_latent_features: int):
""":param action_converter: :param state_latent_features:"""
super().__init__()
action_latent_features = 128
if action_converter.is_singular_discrete:
self.action_encoder = ... | the_stack_v2_python_sparse | neodroidagent/utilities/exploration/intrinsic_signals/torch_isp/curiosity/icm.py | sintefneodroid/agent | train | 9 | |
1b3e7f27d35d4cd44bcb551bb2488bde2c8c119a | [
"super(UserSettings, self).AssertBasePermission(mr)\nif not mr.auth.user_id:\n raise permissions.PermissionException('Anonymous users are not allowed to edit user settings')",
"page_data = {'user_tab_mode': 'st3', 'logged_in_user_pb': template_helpers.PBProxy(mr.auth.user_pb), 'viewed_user': mr.auth.user_view,... | <|body_start_0|>
super(UserSettings, self).AssertBasePermission(mr)
if not mr.auth.user_id:
raise permissions.PermissionException('Anonymous users are not allowed to edit user settings')
<|end_body_0|>
<|body_start_1|>
page_data = {'user_tab_mode': 'st3', 'logged_in_user_pb': templa... | Shows a page with a simple form to edit user preferences. | UserSettings | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSettings:
"""Shows a page with a simple form to edit user preferences."""
def AssertBasePermission(self, mr):
"""Assert that the user has the permissions needed to view this page."""
<|body_0|>
def GatherPageData(self, mr):
"""Build up a dictionary of data va... | stack_v2_sparse_classes_36k_train_008970 | 2,299 | permissive | [
{
"docstring": "Assert that the user has the permissions needed to view this page.",
"name": "AssertBasePermission",
"signature": "def AssertBasePermission(self, mr)"
},
{
"docstring": "Build up a dictionary of data values to use when rendering the page.",
"name": "GatherPageData",
"sign... | 3 | null | Implement the Python class `UserSettings` described below.
Class description:
Shows a page with a simple form to edit user preferences.
Method signatures and docstrings:
- def AssertBasePermission(self, mr): Assert that the user has the permissions needed to view this page.
- def GatherPageData(self, mr): Build up a ... | Implement the Python class `UserSettings` described below.
Class description:
Shows a page with a simple form to edit user preferences.
Method signatures and docstrings:
- def AssertBasePermission(self, mr): Assert that the user has the permissions needed to view this page.
- def GatherPageData(self, mr): Build up a ... | b5d4783f99461438ca9e6a477535617fadab6ba3 | <|skeleton|>
class UserSettings:
"""Shows a page with a simple form to edit user preferences."""
def AssertBasePermission(self, mr):
"""Assert that the user has the permissions needed to view this page."""
<|body_0|>
def GatherPageData(self, mr):
"""Build up a dictionary of data va... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserSettings:
"""Shows a page with a simple form to edit user preferences."""
def AssertBasePermission(self, mr):
"""Assert that the user has the permissions needed to view this page."""
super(UserSettings, self).AssertBasePermission(mr)
if not mr.auth.user_id:
raise p... | the_stack_v2_python_sparse | appengine/monorail/sitewide/usersettings.py | xinghun61/infra | train | 2 |
c2bc0651b395535a5535f985ac288ef282f7f7e2 | [
"date_time = dfdatetime_time_elements.TimeElementsInMilliseconds()\ntry:\n date_time.CopyFromDateTimeString(date_time_string)\nexcept ValueError:\n raise errors.ParseError('Unsupported date and time string: {0!s}'.format(date_time_string))\nreturn date_time",
"if len(row) < self._MINIMUM_NUMBER_OF_COLUMNS:\... | <|body_start_0|>
date_time = dfdatetime_time_elements.TimeElementsInMilliseconds()
try:
date_time.CopyFromDateTimeString(date_time_string)
except ValueError:
raise errors.ParseError('Unsupported date and time string: {0!s}'.format(date_time_string))
return date_ti... | Shared code for parsing Program Compatibility Assistant (PCA) log files. | WindowsPCABaseParser | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WindowsPCABaseParser:
"""Shared code for parsing Program Compatibility Assistant (PCA) log files."""
def _ParseDateTime(self, date_time_string):
"""Parses date and time elements of a log line. Args: date_time_string (string): date and time string. Returns: dfdatetime.TimeElements: da... | stack_v2_sparse_classes_36k_train_008971 | 5,467 | permissive | [
{
"docstring": "Parses date and time elements of a log line. Args: date_time_string (string): date and time string. Returns: dfdatetime.TimeElements: date and time value. Raises: ParseError: if a valid date and time value cannot be derived from the time elements.",
"name": "_ParseDateTime",
"signature":... | 2 | null | Implement the Python class `WindowsPCABaseParser` described below.
Class description:
Shared code for parsing Program Compatibility Assistant (PCA) log files.
Method signatures and docstrings:
- def _ParseDateTime(self, date_time_string): Parses date and time elements of a log line. Args: date_time_string (string): d... | Implement the Python class `WindowsPCABaseParser` described below.
Class description:
Shared code for parsing Program Compatibility Assistant (PCA) log files.
Method signatures and docstrings:
- def _ParseDateTime(self, date_time_string): Parses date and time elements of a log line. Args: date_time_string (string): d... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class WindowsPCABaseParser:
"""Shared code for parsing Program Compatibility Assistant (PCA) log files."""
def _ParseDateTime(self, date_time_string):
"""Parses date and time elements of a log line. Args: date_time_string (string): date and time string. Returns: dfdatetime.TimeElements: da... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WindowsPCABaseParser:
"""Shared code for parsing Program Compatibility Assistant (PCA) log files."""
def _ParseDateTime(self, date_time_string):
"""Parses date and time elements of a log line. Args: date_time_string (string): date and time string. Returns: dfdatetime.TimeElements: date and time v... | the_stack_v2_python_sparse | plaso/parsers/winpca.py | log2timeline/plaso | train | 1,506 |
9fddf09f3eb4f7f344d45d8d5714b720e817d9cb | [
"self.master_unit = master_unit\nself.target_position = target_position\nself._identity = identity\nself._set_external_identity = set_external_identity\nself.set_identity(self._identity)",
"self._identity = identity\nif self._set_external_identity is not None:\n self._set_external_identity(self._identity)"
] | <|body_start_0|>
self.master_unit = master_unit
self.target_position = target_position
self._identity = identity
self._set_external_identity = set_external_identity
self.set_identity(self._identity)
<|end_body_0|>
<|body_start_1|>
self._identity = identity
if sel... | Container for data about robot's position in formation. | Configurator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Configurator:
"""Container for data about robot's position in formation."""
def __init__(self, master_unit, target_position, identity, set_external_identity=None):
"""Parameters ---------- master_unit : Any ID of master unit. It has to be compatible with locator. target_position : (d... | stack_v2_sparse_classes_36k_train_008972 | 1,612 | permissive | [
{
"docstring": "Parameters ---------- master_unit : Any ID of master unit. It has to be compatible with locator. target_position : (double, double) Target position relative to master unit. First field is distance, second is angle. identity : Any ID of robot. It has to be compatible with locator. set_external_id... | 2 | stack_v2_sparse_classes_30k_train_007209 | Implement the Python class `Configurator` described below.
Class description:
Container for data about robot's position in formation.
Method signatures and docstrings:
- def __init__(self, master_unit, target_position, identity, set_external_identity=None): Parameters ---------- master_unit : Any ID of master unit. I... | Implement the Python class `Configurator` described below.
Class description:
Container for data about robot's position in formation.
Method signatures and docstrings:
- def __init__(self, master_unit, target_position, identity, set_external_identity=None): Parameters ---------- master_unit : Any ID of master unit. I... | 81820b35dab10b14f58d66079b0a8f82ef819bee | <|skeleton|>
class Configurator:
"""Container for data about robot's position in formation."""
def __init__(self, master_unit, target_position, identity, set_external_identity=None):
"""Parameters ---------- master_unit : Any ID of master unit. It has to be compatible with locator. target_position : (d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Configurator:
"""Container for data about robot's position in formation."""
def __init__(self, master_unit, target_position, identity, set_external_identity=None):
"""Parameters ---------- master_unit : Any ID of master unit. It has to be compatible with locator. target_position : (double, double... | the_stack_v2_python_sparse | mrc/configuration/configurator.py | Lukasz1928/mobile-robots-control | train | 2 |
566425f72b89d3774592112a96d59f00997f63ba | [
"options = webdriver.ChromeOptions()\noptions.add_argument('headless')\noptions.add_argument('window-size=1920x1080')\noptions.add_argument('disable-gpu')\noptions.add_argument('user-agent=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Safari/537.36')\nop... | <|body_start_0|>
options = webdriver.ChromeOptions()
options.add_argument('headless')
options.add_argument('window-size=1920x1080')
options.add_argument('disable-gpu')
options.add_argument('user-agent=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like... | GetUsePoint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetUsePoint:
def get_selenium_driver(self):
"""Selenium Option을 설정하고 드라이버를 리턴"""
<|body_0|>
def make_dirs(self):
"""site-images 폴더가 없다면 생성"""
<|body_1|>
def download_images(self, img_url, img_path):
"""이미지를 다운받는 함수"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k_train_008973 | 1,410 | no_license | [
{
"docstring": "Selenium Option을 설정하고 드라이버를 리턴",
"name": "get_selenium_driver",
"signature": "def get_selenium_driver(self)"
},
{
"docstring": "site-images 폴더가 없다면 생성",
"name": "make_dirs",
"signature": "def make_dirs(self)"
},
{
"docstring": "이미지를 다운받는 함수",
"name": "download... | 3 | stack_v2_sparse_classes_30k_train_007914 | Implement the Python class `GetUsePoint` described below.
Class description:
Implement the GetUsePoint class.
Method signatures and docstrings:
- def get_selenium_driver(self): Selenium Option을 설정하고 드라이버를 리턴
- def make_dirs(self): site-images 폴더가 없다면 생성
- def download_images(self, img_url, img_path): 이미지를 다운받는 함수 | Implement the Python class `GetUsePoint` described below.
Class description:
Implement the GetUsePoint class.
Method signatures and docstrings:
- def get_selenium_driver(self): Selenium Option을 설정하고 드라이버를 리턴
- def make_dirs(self): site-images 폴더가 없다면 생성
- def download_images(self, img_url, img_path): 이미지를 다운받는 함수
<|... | 36b870d85ef43325713cac4fdebdcb476aac082c | <|skeleton|>
class GetUsePoint:
def get_selenium_driver(self):
"""Selenium Option을 설정하고 드라이버를 리턴"""
<|body_0|>
def make_dirs(self):
"""site-images 폴더가 없다면 생성"""
<|body_1|>
def download_images(self, img_url, img_path):
"""이미지를 다운받는 함수"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetUsePoint:
def get_selenium_driver(self):
"""Selenium Option을 설정하고 드라이버를 리턴"""
options = webdriver.ChromeOptions()
options.add_argument('headless')
options.add_argument('window-size=1920x1080')
options.add_argument('disable-gpu')
options.add_argument('user-age... | the_stack_v2_python_sparse | app/use_point/management/commands/_private.py | AsheKR/HappyMoney-backend | train | 0 | |
3e6f32a588102959ab0fe0f4a52a48c8a835e990 | [
"conn = serial_asyncio.open_serial_connection(**self.serial_settings)\nreader, _ = await conn\nwhile True:\n data = await reader.readline()\n self.telegram_buffer.append(data.decode('ascii'))\n for telegram in self.telegram_buffer.get_all():\n try:\n queue.put_nowait(self.telegram_parser.... | <|body_start_0|>
conn = serial_asyncio.open_serial_connection(**self.serial_settings)
reader, _ = await conn
while True:
data = await reader.readline()
self.telegram_buffer.append(data.decode('ascii'))
for telegram in self.telegram_buffer.get_all():
... | Serial reader using asyncio pyserial. | AsyncSerialReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsyncSerialReader:
"""Serial reader using asyncio pyserial."""
async def read(self, queue):
"""Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generator, values are pushed to provided queue for asynchronous ... | stack_v2_sparse_classes_36k_train_008974 | 4,520 | permissive | [
{
"docstring": "Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generator, values are pushed to provided queue for asynchronous processing. :rtype: None",
"name": "read",
"signature": "async def read(self, queue)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_011644 | Implement the Python class `AsyncSerialReader` described below.
Class description:
Serial reader using asyncio pyserial.
Method signatures and docstrings:
- async def read(self, queue): Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generat... | Implement the Python class `AsyncSerialReader` described below.
Class description:
Serial reader using asyncio pyserial.
Method signatures and docstrings:
- async def read(self, queue): Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generat... | 88923622a916877cf264de2b849bba0b94c3a347 | <|skeleton|>
class AsyncSerialReader:
"""Serial reader using asyncio pyserial."""
async def read(self, queue):
"""Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generator, values are pushed to provided queue for asynchronous ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsyncSerialReader:
"""Serial reader using asyncio pyserial."""
async def read(self, queue):
"""Read complete DSMR telegram's from the serial interface and parse it into CosemObject's and MbusObject's. Instead of being a generator, values are pushed to provided queue for asynchronous processing. :... | the_stack_v2_python_sparse | dsmr_parser/clients/serial_.py | ndokter/dsmr_parser | train | 105 |
a8904f2c319ee5ca143ec31fb7a53c891df28290 | [
"result = {'result': 'NG'}\nctrl_obj = CtrlGroup()\ncontent = ctrl_obj.get_groups(group_name)\nif content:\n result['result'] = 'OK'\n result['content'] = content\nreturn result",
"json_data = request.get_json(force=True)\nctrl_obj = CtrlGroup()\nresult = {'result': 'NG', 'error': ''}\ntry:\n ctrl_obj.ad... | <|body_start_0|>
result = {'result': 'NG'}
ctrl_obj = CtrlGroup()
content = ctrl_obj.get_groups(group_name)
if content:
result['result'] = 'OK'
result['content'] = content
return result
<|end_body_0|>
<|body_start_1|>
json_data = request.get_json(... | ApiGroup | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiGroup:
def get(self, group_name=None):
"""获取组的信息 :param group_name: :return:"""
<|body_0|>
def post(self):
"""新增组 :return:"""
<|body_1|>
def put(self):
"""修改组信息 :return:"""
<|body_2|>
def delete(self, group_id):
"""删除组 :pa... | stack_v2_sparse_classes_36k_train_008975 | 5,041 | no_license | [
{
"docstring": "获取组的信息 :param group_name: :return:",
"name": "get",
"signature": "def get(self, group_name=None)"
},
{
"docstring": "新增组 :return:",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "修改组信息 :return:",
"name": "put",
"signature": "def put(self)... | 4 | stack_v2_sparse_classes_30k_train_012000 | Implement the Python class `ApiGroup` described below.
Class description:
Implement the ApiGroup class.
Method signatures and docstrings:
- def get(self, group_name=None): 获取组的信息 :param group_name: :return:
- def post(self): 新增组 :return:
- def put(self): 修改组信息 :return:
- def delete(self, group_id): 删除组 :param group_i... | Implement the Python class `ApiGroup` described below.
Class description:
Implement the ApiGroup class.
Method signatures and docstrings:
- def get(self, group_name=None): 获取组的信息 :param group_name: :return:
- def post(self): 新增组 :return:
- def put(self): 修改组信息 :return:
- def delete(self, group_id): 删除组 :param group_i... | 64b31e7bdfcb8a4c95f0a8a607f0bcff576cec11 | <|skeleton|>
class ApiGroup:
def get(self, group_name=None):
"""获取组的信息 :param group_name: :return:"""
<|body_0|>
def post(self):
"""新增组 :return:"""
<|body_1|>
def put(self):
"""修改组信息 :return:"""
<|body_2|>
def delete(self, group_id):
"""删除组 :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApiGroup:
def get(self, group_name=None):
"""获取组的信息 :param group_name: :return:"""
result = {'result': 'NG'}
ctrl_obj = CtrlGroup()
content = ctrl_obj.get_groups(group_name)
if content:
result['result'] = 'OK'
result['content'] = content
... | the_stack_v2_python_sparse | Source/collaboration_2/app/api_1_0/api_group_members.py | lsn1183/web_project | train | 0 | |
b03ccf1b0e8d9d2df0b3bd90204089ab1d592506 | [
"super(Basic, self).__init__()\nself.cfg = cfg\nself.agent = agent\nself.policy_net = build_policy(cfg, self.agent)\nself.agent.unwrapped.policy_net = self.policy_net\nself.dynamics_block = mj_torch_block_factory(agent, 'dynamics').apply\nself.reward_block = mj_torch_block_factory(agent, 'reward').apply",
"action... | <|body_start_0|>
super(Basic, self).__init__()
self.cfg = cfg
self.agent = agent
self.policy_net = build_policy(cfg, self.agent)
self.agent.unwrapped.policy_net = self.policy_net
self.dynamics_block = mj_torch_block_factory(agent, 'dynamics').apply
self.reward_blo... | Basic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Basic:
def __init__(self, cfg, agent):
"""Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything."""
<|body_0|>
def forward(self, state):
"""Single pass. :param state: :return:"""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_36k_train_008976 | 1,643 | no_license | [
{
"docstring": "Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything.",
"name": "__init__",
"signature": "def __init__(self, cfg, agent)"
},
{
"docstring": "Single pass. :param state: :return:",
"name": "forward",
"signature": "def for... | 2 | stack_v2_sparse_classes_30k_val_000416 | Implement the Python class `Basic` described below.
Class description:
Implement the Basic class.
Method signatures and docstrings:
- def __init__(self, cfg, agent): Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything.
- def forward(self, state): Single pass. :par... | Implement the Python class `Basic` described below.
Class description:
Implement the Basic class.
Method signatures and docstrings:
- def __init__(self, cfg, agent): Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything.
- def forward(self, state): Single pass. :par... | b7d69c3bea44748411b259ddda1b7e9bb42985e0 | <|skeleton|>
class Basic:
def __init__(self, cfg, agent):
"""Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything."""
<|body_0|>
def forward(self, state):
"""Single pass. :param state: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Basic:
def __init__(self, cfg, agent):
"""Build the model from the fed config node. :param cfg: CfgNode containing the configurations of everything."""
super(Basic, self).__init__()
self.cfg = cfg
self.agent = agent
self.policy_net = build_policy(cfg, self.agent)
... | the_stack_v2_python_sparse | model/archs/basic.py | btilmon/Model-Based-RL | train | 0 | |
5dbcada26174abe15d3fab2e2fa678c1c8888d83 | [
"super().__init__(config or {}, *args, config_key=config_key, **kwargs)\nself.yes = yes\nself.no = no\nself.hide_value = hide_value",
"result = self.yes if str(value).lower() in self.yes_values else self.no\nif result == self.hide_value:\n return None\nreturn super().handle(result, context) if self.mapping els... | <|body_start_0|>
super().__init__(config or {}, *args, config_key=config_key, **kwargs)
self.yes = yes
self.no = no
self.hide_value = hide_value
<|end_body_0|>
<|body_start_1|>
result = self.yes if str(value).lower() in self.yes_values else self.no
if result == self.hide... | Yes or No handler. | YesNo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YesNo:
"""Yes or No handler."""
def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs):
"""Init method."""
<|body_0|>
def handle(self, value, ... | stack_v2_sparse_classes_36k_train_008977 | 4,580 | permissive | [
{
"docstring": "Init method.",
"name": "__init__",
"signature": "def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs)"
},
{
"docstring": "Handle boolean values.",
... | 2 | stack_v2_sparse_classes_30k_train_009209 | Implement the Python class `YesNo` described below.
Class description:
Yes or No handler.
Method signatures and docstrings:
- def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs): Init me... | Implement the Python class `YesNo` described below.
Class description:
Yes or No handler.
Method signatures and docstrings:
- def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs): Init me... | 00909d2c47d158bfeac300e1d7477c4f87c52096 | <|skeleton|>
class YesNo:
"""Yes or No handler."""
def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs):
"""Init method."""
<|body_0|>
def handle(self, value, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class YesNo:
"""Yes or No handler."""
def __init__(self, *args: str, yes=True, no=False, hide_value=None, config: typing.Optional[typing.Mapping[str, typing.Mapping]]=None, config_key: typing.Optional[str]=None, **kwargs):
"""Init method."""
super().__init__(config or {}, *args, config_key=conf... | the_stack_v2_python_sparse | knowit/properties/general.py | ratoaq2/knowit | train | 27 |
f75fcb224e5b2562f7f0a73d60a59430b7b0ef59 | [
"if not callable(self.val):\n raise TypeError('val must be callable')\nif not issubclass(ex, BaseException):\n raise TypeError('given arg must be exception')\nreturn self.builder(self.val, self.description, self.kind, ex)",
"if not self.expected:\n raise TypeError('expected exception not set, raises() mu... | <|body_start_0|>
if not callable(self.val):
raise TypeError('val must be callable')
if not issubclass(ex, BaseException):
raise TypeError('given arg must be exception')
return self.builder(self.val, self.description, self.kind, ex)
<|end_body_0|>
<|body_start_1|>
... | Expected exception mixin. | ExceptionMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExceptionMixin:
"""Expected exception mixin."""
def raises(self, ex):
"""Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must chain to :meth:`~when_called_with` to invoke ``val()``. Ar... | stack_v2_sparse_classes_36k_train_008978 | 4,692 | permissive | [
{
"docstring": "Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must chain to :meth:`~when_called_with` to invoke ``val()``. Args: ex: the expected exception Examples: Usage:: assert_that(some_func).raises(Runtim... | 2 | stack_v2_sparse_classes_30k_train_008342 | Implement the Python class `ExceptionMixin` described below.
Class description:
Expected exception mixin.
Method signatures and docstrings:
- def raises(self, ex): Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must c... | Implement the Python class `ExceptionMixin` described below.
Class description:
Expected exception mixin.
Method signatures and docstrings:
- def raises(self, ex): Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must c... | 4f830045d78004946db562536b0c875b1a2180c4 | <|skeleton|>
class ExceptionMixin:
"""Expected exception mixin."""
def raises(self, ex):
"""Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must chain to :meth:`~when_called_with` to invoke ``val()``. Ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExceptionMixin:
"""Expected exception mixin."""
def raises(self, ex):
"""Asserts that val is callable and set the expected exception. Just sets the expected exception, but never calls val, and therefore never failes. You must chain to :meth:`~when_called_with` to invoke ``val()``. Args: ex: the e... | the_stack_v2_python_sparse | assertpy/exception.py | assertpy/assertpy | train | 222 |
cbf9cb914cdf007e086f81c14499767dc7b0bfdb | [
"obj = convert_array(array).view(cls)\nobj.VTKObject = array\nobj.table = _vtk.vtkWeakReference()\nobj.table.Set(table)\nreturn obj",
"_vtk.VTKArray.__array_finalize__(self, obj)\nif np.shares_memory(self, obj):\n self.table = getattr(obj, 'table', None)\n self.VTKObject = getattr(obj, 'VTKObject', None)\ne... | <|body_start_0|>
obj = convert_array(array).view(cls)
obj.VTKObject = array
obj.table = _vtk.vtkWeakReference()
obj.table.Set(table)
return obj
<|end_body_0|>
<|body_start_1|>
_vtk.VTKArray.__array_finalize__(self, obj)
if np.shares_memory(self, obj):
... | An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated. | lookup_table_ndarray | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lookup_table_ndarray:
"""An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated."""
def __new__(cls, array, table=None):
"""Allocate the array."""
<|body_... | stack_v2_sparse_classes_36k_train_008979 | 34,948 | permissive | [
{
"docstring": "Allocate the array.",
"name": "__new__",
"signature": "def __new__(cls, array, table=None)"
},
{
"docstring": "Finalize array (associate with parent metadata).",
"name": "__array_finalize__",
"signature": "def __array_finalize__(self, obj)"
},
{
"docstring": "Impl... | 4 | null | Implement the Python class `lookup_table_ndarray` described below.
Class description:
An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated.
Method signatures and docstrings:
- def __new__(cls, a... | Implement the Python class `lookup_table_ndarray` described below.
Class description:
An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated.
Method signatures and docstrings:
- def __new__(cls, a... | 1b450b23340f367315fc914075d551e0a4df8cc3 | <|skeleton|>
class lookup_table_ndarray:
"""An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated."""
def __new__(cls, array, table=None):
"""Allocate the array."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class lookup_table_ndarray:
"""An ndarray which references the owning table and the underlying vtkArray. This class is used to ensure that the internal vtkLookupTable updates when the values array is updated."""
def __new__(cls, array, table=None):
"""Allocate the array."""
obj = convert_array(... | the_stack_v2_python_sparse | pyvista/plotting/lookup_table.py | pyvista/pyvista | train | 1,885 |
03d529ce12700fdafae2f792bb8b44968fe53cab | [
"embed_url = None\nyoutube_embed_url = 'https://www.youtube.com/embed/{}'\nvimeo_embed_url = 'https://player.vimeo.com/video/{}'\nif re.match(YOUTUBE_URL_RE, self.url):\n embed_url = youtube_embed_url.format(re.match(YOUTUBE_URL_RE, self.url).group(2))\nif re.match(VIMEO_URL_RE, self.url):\n embed_url = vimeo... | <|body_start_0|>
embed_url = None
youtube_embed_url = 'https://www.youtube.com/embed/{}'
vimeo_embed_url = 'https://player.vimeo.com/video/{}'
if re.match(YOUTUBE_URL_RE, self.url):
embed_url = youtube_embed_url.format(re.match(YOUTUBE_URL_RE, self.url).group(2))
if r... | Video | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Video:
def get_embed_url(self):
"""Get correct embed url for Youtube or Vimeo."""
<|body_0|>
def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
"""Set html field with correct iframe."""
<|body_1|>
<|end_skeleton|>
<|body... | stack_v2_sparse_classes_36k_train_008980 | 1,528 | permissive | [
{
"docstring": "Get correct embed url for Youtube or Vimeo.",
"name": "get_embed_url",
"signature": "def get_embed_url(self)"
},
{
"docstring": "Set html field with correct iframe.",
"name": "save",
"signature": "def save(self, force_insert=False, force_update=False, using=None, update_f... | 2 | stack_v2_sparse_classes_30k_train_018679 | Implement the Python class `Video` described below.
Class description:
Implement the Video class.
Method signatures and docstrings:
- def get_embed_url(self): Get correct embed url for Youtube or Vimeo.
- def save(self, force_insert=False, force_update=False, using=None, update_fields=None): Set html field with corre... | Implement the Python class `Video` described below.
Class description:
Implement the Video class.
Method signatures and docstrings:
- def get_embed_url(self): Get correct embed url for Youtube or Vimeo.
- def save(self, force_insert=False, force_update=False, using=None, update_fields=None): Set html field with corre... | b9b0a3d8b49d5d9b840656f84564ba0a6e016f98 | <|skeleton|>
class Video:
def get_embed_url(self):
"""Get correct embed url for Youtube or Vimeo."""
<|body_0|>
def save(self, force_insert=False, force_update=False, using=None, update_fields=None):
"""Set html field with correct iframe."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Video:
def get_embed_url(self):
"""Get correct embed url for Youtube or Vimeo."""
embed_url = None
youtube_embed_url = 'https://www.youtube.com/embed/{}'
vimeo_embed_url = 'https://player.vimeo.com/video/{}'
if re.match(YOUTUBE_URL_RE, self.url):
embed_url =... | the_stack_v2_python_sparse | glitter/blocks/video/models.py | developersociety/django-glitter | train | 3 | |
f5b603fbc7175286e8c21c1ad03fa3ed870cf7fc | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('gasparde_ljmcgann', 'gasparde_ljmcgann')\ncrimes = repo.gasparde_ljmcgann.crimes\nfor data in crimes.find():\n GeoLocation = Point(data['location'])\n neighBorhood = [neighborhood['Name'] for neigh... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('gasparde_ljmcgann', 'gasparde_ljmcgann')
crimes = repo.gasparde_ljmcgann.crimes
for data in crimes.find():
GeoLocation = Point(data['l... | crimeNeighborhood | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class crimeNeighborhood:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyt... | stack_v2_sparse_classes_36k_train_008981 | 4,427 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `crimeNeighborhood` described below.
Class description:
Implement the crimeNeighborhood class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime... | Implement the Python class `crimeNeighborhood` described below.
Class description:
Implement the crimeNeighborhood class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime... | 90284cf3debbac36eead07b8d2339cdd191b86cf | <|skeleton|>
class crimeNeighborhood:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everyt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class crimeNeighborhood:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('gasparde_ljmcgann', 'gasparde_ljm... | the_stack_v2_python_sparse | gasparde_ljmcgann/crimeNeighborhood.py | maximega/course-2019-spr-proj | train | 2 | |
8dfa800e5b3a51003d1289d75b35c24108b5c493 | [
"self.type = kwargs.pop('type', None)\nself.serializer = kwargs.pop('serializer', None)\nself._serializer = None\nif not isinstance(self.serializer, str):\n self._serializer = self.serializer\nassert self.type or self.serializer, 'JSONAPIRelationshipField must either specify a `type` or `serializer`.'\nsuper()._... | <|body_start_0|>
self.type = kwargs.pop('type', None)
self.serializer = kwargs.pop('serializer', None)
self._serializer = None
if not isinstance(self.serializer, str):
self._serializer = self.serializer
assert self.type or self.serializer, 'JSONAPIRelationshipField mu... | Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also accesses the related resource's schema to identify the JSON API type. | JSONAPIRelationshipField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONAPIRelationshipField:
"""Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also accesses the related resource's schema to id... | stack_v2_sparse_classes_36k_train_008982 | 4,253 | permissive | [
{
"docstring": "Create an object. kwargs must contain either a `type` or `serializer` parameter. :param kwargs: Relationship field parameters.",
"name": "__init__",
"signature": "def __init__(self, **kwargs: Any) -> None"
},
{
"docstring": "Decide whether to use pk only optimization.",
"name... | 5 | stack_v2_sparse_classes_30k_train_013497 | Implement the Python class `JSONAPIRelationshipField` described below.
Class description:
Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also acces... | Implement the Python class `JSONAPIRelationshipField` described below.
Class description:
Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also acces... | a7f4bddbaf55dbe68e9346005cf16442eb48024d | <|skeleton|>
class JSONAPIRelationshipField:
"""Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also accesses the related resource's schema to id... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONAPIRelationshipField:
"""Extends PrimaryKeyRelatedField to support various JSON API operations. This looks to see if the relationship will be included as a related resource, and returns a :ResourceIdField: along with the related serializer. It also accesses the related resource's schema to identify the JS... | the_stack_v2_python_sparse | rest_framework_json_schema/relations.py | paulcwatts/drf-json-schema | train | 15 |
c6eaf6a3db319e9e138d71a77d7bd5f67da7aeb0 | [
"self.session: Session = session\nself.event_types: Iterable[core_pb2.EventType] = event_types\nself.queue: Queue = Queue()\nself.add_handlers()",
"if core_pb2.EventType.NODE in self.event_types:\n self.session.node_handlers.append(self.queue.put)\nif core_pb2.EventType.LINK in self.event_types:\n self.sess... | <|body_start_0|>
self.session: Session = session
self.event_types: Iterable[core_pb2.EventType] = event_types
self.queue: Queue = Queue()
self.add_handlers()
<|end_body_0|>
<|body_start_1|>
if core_pb2.EventType.NODE in self.event_types:
self.session.node_handlers.ap... | Processes session events to generate grpc events. | EventStreamer | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventStreamer:
"""Processes session events to generate grpc events."""
def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None:
"""Create a EventStreamer instance. :param session: session to process events for :param event_types: types of events to pro... | stack_v2_sparse_classes_36k_train_008983 | 7,519 | permissive | [
{
"docstring": "Create a EventStreamer instance. :param session: session to process events for :param event_types: types of events to process",
"name": "__init__",
"signature": "def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None"
},
{
"docstring": "Add a sess... | 4 | null | Implement the Python class `EventStreamer` described below.
Class description:
Processes session events to generate grpc events.
Method signatures and docstrings:
- def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None: Create a EventStreamer instance. :param session: session to proc... | Implement the Python class `EventStreamer` described below.
Class description:
Processes session events to generate grpc events.
Method signatures and docstrings:
- def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None: Create a EventStreamer instance. :param session: session to proc... | 20071eed2e73a2287aa385698dd604f4933ae7ff | <|skeleton|>
class EventStreamer:
"""Processes session events to generate grpc events."""
def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None:
"""Create a EventStreamer instance. :param session: session to process events for :param event_types: types of events to pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventStreamer:
"""Processes session events to generate grpc events."""
def __init__(self, session: Session, event_types: Iterable[core_pb2.EventType]) -> None:
"""Create a EventStreamer instance. :param session: session to process events for :param event_types: types of events to process"""
... | the_stack_v2_python_sparse | daemon/core/api/grpc/events.py | coreemu/core | train | 606 |
43db75528a0ab1e0daf36efb161e70616ae17f6f | [
"if root is None:\n return []\ncolHash = {}\nself.bfsGetColumn(root, colHash)\nreturn [t[1] for t in sorted(colHash.iteritems())]",
"hashTable.setdefault(col, []).append(node.val)\nif node.left is not None:\n self.dfsGetColumn(node.left, col - 1, hashTable)\nif node.right is not None:\n self.dfsGetColumn... | <|body_start_0|>
if root is None:
return []
colHash = {}
self.bfsGetColumn(root, colHash)
return [t[1] for t in sorted(colHash.iteritems())]
<|end_body_0|>
<|body_start_1|>
hashTable.setdefault(col, []).append(node.val)
if node.left is not None:
s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def verticalOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def dfsGetColumn(self, node, col, hashTable):
""":type node: TreeNode :type col: int, the column number for node"""
<|body_1|>
def bfsGetColumn(self, r... | stack_v2_sparse_classes_36k_train_008984 | 4,136 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[List[int]]",
"name": "verticalOrder",
"signature": "def verticalOrder(self, root)"
},
{
"docstring": ":type node: TreeNode :type col: int, the column number for node",
"name": "dfsGetColumn",
"signature": "def dfsGetColumn(self, node, col... | 3 | stack_v2_sparse_classes_30k_train_010173 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def verticalOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def dfsGetColumn(self, node, col, hashTable): :type node: TreeNode :type col: int, the column number... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def verticalOrder(self, root): :type root: TreeNode :rtype: List[List[int]]
- def dfsGetColumn(self, node, col, hashTable): :type node: TreeNode :type col: int, the column number... | d2cbfb1022b1ee5bce8083c9940ba10320fc2d43 | <|skeleton|>
class Solution:
def verticalOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
<|body_0|>
def dfsGetColumn(self, node, col, hashTable):
""":type node: TreeNode :type col: int, the column number for node"""
<|body_1|>
def bfsGetColumn(self, r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def verticalOrder(self, root):
""":type root: TreeNode :rtype: List[List[int]]"""
if root is None:
return []
colHash = {}
self.bfsGetColumn(root, colHash)
return [t[1] for t in sorted(colHash.iteritems())]
def dfsGetColumn(self, node, col, has... | the_stack_v2_python_sparse | 314_Vertical_Traverse_BTree/vTraverseBTree.py | VividLiu/LeeCode_Practice | train | 1 | |
33a82a1eb768ebabecd91cdc41e51f48ab21c6cc | [
"au = 'aeiou'\nm = len(au)\nself.ans = 0\n\ndef helper(s, start):\n if len(s) == n:\n self.ans += 1\n return\n for i in range(start, m):\n helper(s + au[i], i)\nhelper('', 0)\nreturn self.ans",
"m = 5\nmemo = [[-1 for _ in range(n)] for _ in range(m)]\n\ndef helper(k, start):\n if k ... | <|body_start_0|>
au = 'aeiou'
m = len(au)
self.ans = 0
def helper(s, start):
if len(s) == n:
self.ans += 1
return
for i in range(start, m):
helper(s + au[i], i)
helper('', 0)
return self.ans
<|end_bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countVowelStrings(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countVowelStringsMemo(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
au = 'aeiou'
m = len(au)
self.ans = 0... | stack_v2_sparse_classes_36k_train_008985 | 2,040 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "countVowelStrings",
"signature": "def countVowelStrings(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "countVowelStringsMemo",
"signature": "def countVowelStringsMemo(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countVowelStrings(self, n): :type n: int :rtype: int
- def countVowelStringsMemo(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countVowelStrings(self, n): :type n: int :rtype: int
- def countVowelStringsMemo(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def countVowelStrings(s... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def countVowelStrings(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def countVowelStringsMemo(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countVowelStrings(self, n):
""":type n: int :rtype: int"""
au = 'aeiou'
m = len(au)
self.ans = 0
def helper(s, start):
if len(s) == n:
self.ans += 1
return
for i in range(start, m):
h... | the_stack_v2_python_sparse | C/CountSortedVowelStrings.py | bssrdf/pyleet | train | 2 | |
a41e69dbc219275f93c39902dba2361cafa1b604 | [
"self.username = username\nself.email = email\nself.password = bcrypt.generate_password_hash(password, current_app.config.get('BCRYPT_LOG_ROUNDS')).decode()\nself.created_at = created_at",
"try:\n days = current_app.config.get('TOKEN_EXPIRATION_DAYS')\n seconds = current_app.config.get('TOKEN_EXPIRATION_SEC... | <|body_start_0|>
self.username = username
self.email = email
self.password = bcrypt.generate_password_hash(password, current_app.config.get('BCRYPT_LOG_ROUNDS')).decode()
self.created_at = created_at
<|end_body_0|>
<|body_start_1|>
try:
days = current_app.config.get(... | MetaGenScope User model. | User | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
"""MetaGenScope User model."""
def __init__(self, username, email, password, created_at=datetime.datetime.utcnow()):
"""Initialize MetaGenScope User model."""
<|body_0|>
def encode_auth_token(cls, user_id):
"""Generate the auth token."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_008986 | 3,155 | permissive | [
{
"docstring": "Initialize MetaGenScope User model.",
"name": "__init__",
"signature": "def __init__(self, username, email, password, created_at=datetime.datetime.utcnow())"
},
{
"docstring": "Generate the auth token.",
"name": "encode_auth_token",
"signature": "def encode_auth_token(cls... | 3 | stack_v2_sparse_classes_30k_train_000545 | Implement the Python class `User` described below.
Class description:
MetaGenScope User model.
Method signatures and docstrings:
- def __init__(self, username, email, password, created_at=datetime.datetime.utcnow()): Initialize MetaGenScope User model.
- def encode_auth_token(cls, user_id): Generate the auth token.
-... | Implement the Python class `User` described below.
Class description:
MetaGenScope User model.
Method signatures and docstrings:
- def __init__(self, username, email, password, created_at=datetime.datetime.utcnow()): Initialize MetaGenScope User model.
- def encode_auth_token(cls, user_id): Generate the auth token.
-... | 609cd57c626c857c8efde8237a1f22f4d1e6065d | <|skeleton|>
class User:
"""MetaGenScope User model."""
def __init__(self, username, email, password, created_at=datetime.datetime.utcnow()):
"""Initialize MetaGenScope User model."""
<|body_0|>
def encode_auth_token(cls, user_id):
"""Generate the auth token."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class User:
"""MetaGenScope User model."""
def __init__(self, username, email, password, created_at=datetime.datetime.utcnow()):
"""Initialize MetaGenScope User model."""
self.username = username
self.email = email
self.password = bcrypt.generate_password_hash(password, current_... | the_stack_v2_python_sparse | app/users/user_models.py | MetaGenScope/metagenscope-server | train | 0 |
e751118729eed74d92ecbb67d8c0ce81e348b972 | [
"if graph.is_directed():\n raise ValueError('the graph is directed')\nself.graph = graph\nself.color = dict(((node, None) for node in self.graph.iternodes()))\nfor edge in self.graph.iteredges():\n if edge.source == edge.target:\n raise ValueError('a loop detected')\nself.saturation = dict(((node, set(... | <|body_start_0|>
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
self.color = dict(((node, None) for node in self.graph.iternodes()))
for edge in self.graph.iteredges():
if edge.source == edge.target:
raise Valu... | Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ... | SLFNodeColoring | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SLFNodeColoring:
"""Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ..."""
def __init__(self, graph):
... | stack_v2_sparse_classes_36k_train_008987 | 1,809 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self)"
},
{
"docstring": "Give node the smallest possible color.",
"name": "_greedy_co... | 3 | stack_v2_sparse_classes_30k_train_009091 | Implement the Python class `SLFNodeColoring` described below.
Class description:
Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ...
Me... | Implement the Python class `SLFNodeColoring` described below.
Class description:
Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ...
Me... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class SLFNodeColoring:
"""Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ..."""
def __init__(self, graph):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SLFNodeColoring:
"""Find a saturated largest first (SLF) node coloring. Computational complexity is O(V^2). Attributes ---------- graph : input undirected graph or multigraph color : dict with nodes (values are colors) Notes ----- Colors are 0, 1, 2, ..."""
def __init__(self, graph):
"""The algor... | the_stack_v2_python_sparse | graphtheory/coloring/nodecolorslf.py | kgashok/graphs-dict | train | 0 |
cb087d50974c918d07ba42b15f7f3f5e05f52eb5 | [
"k = CArray.zeros(shape=(x.shape[0], self._rv.shape[0]))\nx_nd, rv_nd = (x.tondarray(), self._rv.tondarray())\nif x.shape[0] <= self._rv.shape[0]:\n for i in range(k.shape[0]):\n k[i, :] = CArray(np.minimum(x_nd[i, :], rv_nd).sum(axis=1))\nelse:\n for j in range(k.shape[1]):\n k[:, j] = CArray(n... | <|body_start_0|>
k = CArray.zeros(shape=(x.shape[0], self._rv.shape[0]))
x_nd, rv_nd = (x.tondarray(), self._rv.tondarray())
if x.shape[0] <= self._rv.shape[0]:
for i in range(k.shape[0]):
k[i, :] = CArray(np.minimum(x_nd[i, :], rv_nd).sum(axis=1))
else:
... | Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from secml.array import CArray >>> from secml.ml.kernels.c_kernel_histintersect import CKern... | CKernelHistIntersect | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CKernelHistIntersect:
"""Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from secml.array import CArray >>> from secm... | stack_v2_sparse_classes_36k_train_008988 | 3,623 | permissive | [
{
"docstring": "Compute the histogram intersection kernel between x and cached rv. Parameters ---------- x : CArray or array_like Array of shape (n_x, n_features). Returns ------- kernel : CArray Kernel between x and cached rv. Array of shape (n_x, n_rv).",
"name": "_forward",
"signature": "def _forward... | 2 | stack_v2_sparse_classes_30k_train_006748 | Implement the Python class `CKernelHistIntersect` described below.
Class description:
Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from ... | Implement the Python class `CKernelHistIntersect` described below.
Class description:
Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from ... | 431373e65d8cfe2cb7cf042ce1a6c9519ea5a14a | <|skeleton|>
class CKernelHistIntersect:
"""Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from secml.array import CArray >>> from secm... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CKernelHistIntersect:
"""Histogram Intersection Kernel. Given matrices X and RV, this is computed by:: K(x, rv) = sum_i ( min(x[i], rv[i]) ) for each pair of rows in X and in RV. Attributes ---------- class_type : 'hist-intersect' Examples -------- >>> from secml.array import CArray >>> from secml.ml.kernels.... | the_stack_v2_python_sparse | src/secml/ml/kernels/c_kernel_histintersect.py | Cinofix/secml | train | 0 |
f94b8702b2bdd4ff7731f6cd356025dd1625696e | [
"self.trade_days = trade_days\nself.trade_strategy = trade_strategy\nself.profit_array = []",
"for ind, day in enumerate(self.trade_days):\n '\\n 以时间驱动，完成交易回测\\n '\n if hasattr(self.trade_strategy, 'buy_strategy'):\n self.trade_strategy.buy_strategy(ind, day, self.trade_days)\n ... | <|body_start_0|>
self.trade_days = trade_days
self.trade_strategy = trade_strategy
self.profit_array = []
<|end_body_0|>
<|body_start_1|>
for ind, day in enumerate(self.trade_days):
'\n 以时间驱动，完成交易回测\n '
if hasattr(self.trade_strategy, 'buy_s... | 交易回测系统 | TradeLoopBack | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TradeLoopBack:
"""交易回测系统"""
def __init__(self, trade_days, trade_strategy):
"""使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略"""
<|body_0|>
def execute_trade(self):
... | stack_v2_sparse_classes_36k_train_008989 | 1,479 | no_license | [
{
"docstring": "使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略",
"name": "__init__",
"signature": "def __init__(self, trade_days, trade_strategy)"
},
{
"docstring": "执行交易回测 :return:",
"name": "e... | 2 | stack_v2_sparse_classes_30k_train_016464 | Implement the Python class `TradeLoopBack` described below.
Class description:
交易回测系统
Method signatures and docstrings:
- def __init__(self, trade_days, trade_strategy): 使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略
- d... | Implement the Python class `TradeLoopBack` described below.
Class description:
交易回测系统
Method signatures and docstrings:
- def __init__(self, trade_days, trade_strategy): 使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略
- d... | 2294a4bbc38b3c5a0f978c4a6144d5aa4e5eefab | <|skeleton|>
class TradeLoopBack:
"""交易回测系统"""
def __init__(self, trade_days, trade_strategy):
"""使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略"""
<|body_0|>
def execute_trade(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TradeLoopBack:
"""交易回测系统"""
def __init__(self, trade_days, trade_strategy):
"""使用前面封装的StockTradeDays类和本节编写的交易策略类 TradeStrategyBase类初始化交易系统 :param trade_days: StockTradeDays交易数据序列 :param trade_strategy: TradeStrategyBase交易策略"""
self.trade_days = trade_days
self.trade_strategy = tra... | the_stack_v2_python_sparse | trade/stock/trade_loop_back.py | 13936292023/trade | train | 0 |
0b3068aec1ecc933b9a2f6b3b587809c033a5e3e | [
"if xsID in self:\n return dict.__getitem__(self, xsID)\nxsType = xsID[0]\nbuGroup = xsID[1]\nexistingXsOpts = [xsOpt for xsOpt in self.values() if xsOpt.xsType == xsType and xsOpt.buGroup < buGroup]\nif not any(existingXsOpts):\n return self._getDefault(xsID)\nelse:\n return sorted(existingXsOpts, key=lam... | <|body_start_0|>
if xsID in self:
return dict.__getitem__(self, xsID)
xsType = xsID[0]
buGroup = xsID[1]
existingXsOpts = [xsOpt for xsOpt in self.values() if xsOpt.xsType == xsType and xsOpt.buGroup < buGroup]
if not any(existingXsOpts):
return self._getD... | The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior. | XSSettings | [
"LicenseRef-scancode-free-unknown",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XSSettings:
"""The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior."""
def __getitem__(self, xsID):
"""Return the sto... | stack_v2_sparse_classes_36k_train_008990 | 11,956 | permissive | [
{
"docstring": "Return the stored settings of the same xs type and the lowest burnup group if they exist. Notes ----- 1. If `AA` and `AB` exist, but `AC` is created, then the intended behavior is that `AC` settings will be set to the settings in `AA`. 2. If only `YZ' exists and `YA` is created, then the intende... | 3 | stack_v2_sparse_classes_30k_train_003869 | Implement the Python class `XSSettings` described below.
Class description:
The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior.
Method signatures and ... | Implement the Python class `XSSettings` described below.
Class description:
The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior.
Method signatures and ... | 6c4fea1ca9d256a2599efd52af5e5ebe9860d192 | <|skeleton|>
class XSSettings:
"""The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior."""
def __getitem__(self, xsID):
"""Return the sto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XSSettings:
"""The container that holds the multiple individual XS settings for different ids. This is what the value of the cs setting is set to. It handles reading/writing the settings to file as well as some other special behavior."""
def __getitem__(self, xsID):
"""Return the stored settings ... | the_stack_v2_python_sparse | armi/physics/neutronics/crossSectionSettings.py | paulromano/armi | train | 1 |
a42149a31282b1ddb2a6c372ba43732e3eb90a0c | [
"self.sensor = sensor\nself.pump = pump\nself.decider = decider\nself.actions = {'PUMP_IN': pump.PUMP_IN, 'PUMP_OUT': pump.PUMP_OUT, 'PUMP_OFF': pump.PUMP_OFF}",
"cur_height = self.sensor.measure()\ncur_pump_status = self.pump.get_state()\nheight_status = self.decider.height_checker(cur_height)\nupdate = self.pum... | <|body_start_0|>
self.sensor = sensor
self.pump = pump
self.decider = decider
self.actions = {'PUMP_IN': pump.PUMP_IN, 'PUMP_OUT': pump.PUMP_OUT, 'PUMP_OFF': pump.PUMP_OFF}
<|end_body_0|>
<|body_start_1|>
cur_height = self.sensor.measure()
cur_pump_status = self.pump.get... | Encapsulates command and coordination for the water-regulation module | Controller | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typicall... | stack_v2_sparse_classes_36k_train_008991 | 1,896 | no_license | [
{
"docstring": "Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typically an instance of decider.Decider",
"name": "__init__",
"signature": "def __init__(self, sensor, pump, decider)"
},
{
"docstring": ... | 3 | null | Implement the Python class `Controller` described below.
Class description:
Encapsulates command and coordination for the water-regulation module
Method signatures and docstrings:
- def __init__(self, sensor, pump, decider): Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Ty... | Implement the Python class `Controller` described below.
Class description:
Encapsulates command and coordination for the water-regulation module
Method signatures and docstrings:
- def __init__(self, sensor, pump, decider): Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Ty... | b1fea0309b3495b3e1dc167d7029bc9e4b6f00f1 | <|skeleton|>
class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typicall... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""Encapsulates command and coordination for the water-regulation module"""
def __init__(self, sensor, pump, decider):
"""Create a new controller :param sensor: Typically an instance of sensor.Sensor :param pump: Typically an instance of pump.Pump :param decider: Typically an instance... | the_stack_v2_python_sparse | students/SeanTasaki/Lesson06/water-regulation/waterregulation/controller.py | UWPCE-PythonCert-ClassRepos/SP_Online_Course2_2018 | train | 4 |
7dce5cd12017c97b489d6ae4e4be97d8792fce07 | [
"self.restaurant = Restaurant.objects.create(name='RestA', address='123 Road', phone=None, email='RA@mail.com', city='Toronto', cuisine='Chinese', pricepoint='High', twitter='?', instagram='?', bio=None, GEO_location='?', external_delivery_link='?', cover_photo_url='picA', logo_url='urlA', rating='4.5')\nself.food ... | <|body_start_0|>
self.restaurant = Restaurant.objects.create(name='RestA', address='123 Road', phone=None, email='RA@mail.com', city='Toronto', cuisine='Chinese', pricepoint='High', twitter='?', instagram='?', bio=None, GEO_location='?', external_delivery_link='?', cover_photo_url='picA', logo_url='urlA', ratin... | TagClearCases | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagClearCases:
def setUp(self):
"""Create restaurant food, tag and food object for testing"""
<|body_0|>
def test_clear_tags(self):
"""Test if tag ids are cleared from food document"""
<|body_1|>
def test_clear_foods(self):
"""Test if food ids ar... | stack_v2_sparse_classes_36k_train_008992 | 24,925 | no_license | [
{
"docstring": "Create restaurant food, tag and food object for testing",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test if tag ids are cleared from food document",
"name": "test_clear_tags",
"signature": "def test_clear_tags(self)"
},
{
"docstring": "Tes... | 3 | stack_v2_sparse_classes_30k_train_000334 | Implement the Python class `TagClearCases` described below.
Class description:
Implement the TagClearCases class.
Method signatures and docstrings:
- def setUp(self): Create restaurant food, tag and food object for testing
- def test_clear_tags(self): Test if tag ids are cleared from food document
- def test_clear_fo... | Implement the Python class `TagClearCases` described below.
Class description:
Implement the TagClearCases class.
Method signatures and docstrings:
- def setUp(self): Create restaurant food, tag and food object for testing
- def test_clear_tags(self): Test if tag ids are cleared from food document
- def test_clear_fo... | 97242c072ab64704fd250a3ac2b62da05b0d3ca5 | <|skeleton|>
class TagClearCases:
def setUp(self):
"""Create restaurant food, tag and food object for testing"""
<|body_0|>
def test_clear_tags(self):
"""Test if tag ids are cleared from food document"""
<|body_1|>
def test_clear_foods(self):
"""Test if food ids ar... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagClearCases:
def setUp(self):
"""Create restaurant food, tag and food object for testing"""
self.restaurant = Restaurant.objects.create(name='RestA', address='123 Road', phone=None, email='RA@mail.com', city='Toronto', cuisine='Chinese', pricepoint='High', twitter='?', instagram='?', bio=Non... | the_stack_v2_python_sparse | server/restaurant/tests.py | CSCC01/team_08-project | train | 0 | |
6f9ff68b4f80ab7936346f58065c57756ea9ab4d | [
"self.fets_eval = FETS2D58H(mats_eval=self.mats_eval)\nsupport_slices = [[(0, slice(None), slice(None), 0, slice(None), slice(None))], [(slice(None), 0, slice(None), slice(None), 0, slice(None))]]\nsupport_dirs = [[0, 1, 2]]\nloading_slices = [(-1, slice(None), slice(None), -1, slice(None), slice(None)), (slice(Non... | <|body_start_0|>
self.fets_eval = FETS2D58H(mats_eval=self.mats_eval)
support_slices = [[(0, slice(None), slice(None), 0, slice(None), slice(None))], [(slice(None), 0, slice(None), slice(None), 0, slice(None))]]
support_dirs = [[0, 1, 2]]
loading_slices = [(-1, slice(None), slice(None), ... | TestMATS2D5 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMATS2D5:
def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001):
"""Assert that the symmetry is given for the applied loadings."""
<|body_0|>
def assert_stress_value(self, sig_expected, n_steps=3, load=0.0001):
"""Assert that the symmetry is given for t... | stack_v2_sparse_classes_36k_train_008993 | 4,336 | no_license | [
{
"docstring": "Assert that the symmetry is given for the applied loadings.",
"name": "assert_2D_symmetry_clamped_cube",
"signature": "def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001)"
},
{
"docstring": "Assert that the symmetry is given for the applied loadings.",
"name": "a... | 2 | null | Implement the Python class `TestMATS2D5` described below.
Class description:
Implement the TestMATS2D5 class.
Method signatures and docstrings:
- def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001): Assert that the symmetry is given for the applied loadings.
- def assert_stress_value(self, sig_expected, ... | Implement the Python class `TestMATS2D5` described below.
Class description:
Implement the TestMATS2D5 class.
Method signatures and docstrings:
- def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001): Assert that the symmetry is given for the applied loadings.
- def assert_stress_value(self, sig_expected, ... | 00de9f0eec52835d839a3c6c1407cac11a496339 | <|skeleton|>
class TestMATS2D5:
def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001):
"""Assert that the symmetry is given for the applied loadings."""
<|body_0|>
def assert_stress_value(self, sig_expected, n_steps=3, load=0.0001):
"""Assert that the symmetry is given for t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMATS2D5:
def assert_2D_symmetry_clamped_cube(self, load_dirs, load=0.001):
"""Assert that the symmetry is given for the applied loadings."""
self.fets_eval = FETS2D58H(mats_eval=self.mats_eval)
support_slices = [[(0, slice(None), slice(None), 0, slice(None), slice(None))], [(slice(... | the_stack_v2_python_sparse | ibvpy/mats/mats2D5/__test__.py | simvisage/bmcs | train | 1 | |
b8c7c97b09145b1b580d8f8a55d1d7a4bdc0d47e | [
"text = ''\nwith open(file_path, 'r') as file:\n for line in file.readlines():\n text += line\nreturn text",
"read = sys.stdin.readlines()\ntext = ''\nfor line in read:\n text += line\nreturn text"
] | <|body_start_0|>
text = ''
with open(file_path, 'r') as file:
for line in file.readlines():
text += line
return text
<|end_body_0|>
<|body_start_1|>
read = sys.stdin.readlines()
text = ''
for line in read:
text += line
retu... | Used in handling reading input. | Reader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reader:
"""Used in handling reading input."""
def read_file(file_path):
"""Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string"""
<|body_0|>
def read_input():
"""Reads a direct input. An input... | stack_v2_sparse_classes_36k_train_008994 | 855 | permissive | [
{
"docstring": "Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string",
"name": "read_file",
"signature": "def read_file(file_path)"
},
{
"docstring": "Reads a direct input. An input ends with CTRL+D. Enables inputting from a f... | 2 | stack_v2_sparse_classes_30k_train_012170 | Implement the Python class `Reader` described below.
Class description:
Used in handling reading input.
Method signatures and docstrings:
- def read_file(file_path): Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string
- def read_input(): Reads a d... | Implement the Python class `Reader` described below.
Class description:
Used in handling reading input.
Method signatures and docstrings:
- def read_file(file_path): Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string
- def read_input(): Reads a d... | 1f7bea099dac93696d5d2ebb8d76926efe5ceda4 | <|skeleton|>
class Reader:
"""Used in handling reading input."""
def read_file(file_path):
"""Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string"""
<|body_0|>
def read_input():
"""Reads a direct input. An input... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Reader:
"""Used in handling reading input."""
def read_file(file_path):
"""Reads a file and outputs it in a single string. :param str file_path: File pathname. :return str: File content in a string"""
text = ''
with open(file_path, 'r') as file:
for line in file.readli... | the_stack_v2_python_sparse | form/readers.py | ffhan/lingua | train | 0 |
4cd77b2e2bfd6f309db6ae8950497597b4a5f82b | [
"if num != 0 and num & num - 1 == 0 and (len(bin(num).split('1')[-1]) & 1 == 0):\n return True\nelse:\n return False",
"while num:\n num = num / 4.0\n if num == 4:\n return True\n elif num < 4:\n break\nreturn False"
] | <|body_start_0|>
if num != 0 and num & num - 1 == 0 and (len(bin(num).split('1')[-1]) & 1 == 0):
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
while num:
num = num / 4.0
if num == 4:
return True
elif nu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfFour(self, num):
""":type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数"""
<|body_0|>
def isPowerOfFour1(self, num):
""":type num: int :rtype: bool 循环"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if num != 0 and num & nu... | stack_v2_sparse_classes_36k_train_008995 | 949 | no_license | [
{
"docstring": ":type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数",
"name": "isPowerOfFour",
"signature": "def isPowerOfFour(self, num)"
},
{
"docstring": ":type num: int :rtype: bool 循环",
"name": "isPowerOfFour1",
"signature": "def isPowerOfFour1(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018573 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfFour(self, num): :type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数
- def isPowerOfFour1(self, num): :type num: int :rtype: bool 循环 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfFour(self, num): :type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数
- def isPowerOfFour1(self, num): :type num: int :rtype: bool 循环
<|skeleton|>
class Solution:... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def isPowerOfFour(self, num):
""":type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数"""
<|body_0|>
def isPowerOfFour1(self, num):
""":type num: int :rtype: bool 循环"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPowerOfFour(self, num):
""":type num: int :rtype: bool 位运算 特点除了只有一个1外 而且后面的0个数为偶数"""
if num != 0 and num & num - 1 == 0 and (len(bin(num).split('1')[-1]) & 1 == 0):
return True
else:
return False
def isPowerOfFour1(self, num):
""":ty... | the_stack_v2_python_sparse | 算法/位运算/4的幂.py | RichieSong/algorithm | train | 0 | |
d675ffb926b6f8f2fb131440c062b5fa10eee2f4 | [
"super().__init__()\nchannels = [input_channel] + channel_list\nmodules = list()\nfor i in range(1, len(channels)):\n modules.append(DownConvBlock(in_channels=channels[i - 1], out_channels=channels[i]))\nself.conv = nn.Sequential(*modules)\nfactor = 2 ** len(channel_list)\nself.fc_size = int(channel_list[-1] * H... | <|body_start_0|>
super().__init__()
channels = [input_channel] + channel_list
modules = list()
for i in range(1, len(channels)):
modules.append(DownConvBlock(in_channels=channels[i - 1], out_channels=channels[i]))
self.conv = nn.Sequential(*modules)
factor = 2... | Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network. | ConvEncoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvEncoder:
"""Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network."""
def __init__(self, H, W, input_channel, channel_list, hidden_dims, z_dim):
"""Init. Args: H(int): Height of the input data. W(int... | stack_v2_sparse_classes_36k_train_008996 | 10,936 | no_license | [
{
"docstring": "Init. Args: H(int): Height of the input data. W(int): Width of the input data input_channel(int): Number of channels in the input data. Typically 1 for grayscale and 3 for RGB. channel_list(List[int]): List of channels. Determines the number of convolutional layers and associated channels. ex: [... | 2 | stack_v2_sparse_classes_30k_train_013775 | Implement the Python class `ConvEncoder` described below.
Class description:
Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network.
Method signatures and docstrings:
- def __init__(self, H, W, input_channel, channel_list, hidden_dims, z_... | Implement the Python class `ConvEncoder` described below.
Class description:
Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network.
Method signatures and docstrings:
- def __init__(self, H, W, input_channel, channel_list, hidden_dims, z_... | 9027b529eaa4cf0a38f25512141810f92db99639 | <|skeleton|>
class ConvEncoder:
"""Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network."""
def __init__(self, H, W, input_channel, channel_list, hidden_dims, z_dim):
"""Init. Args: H(int): Height of the input data. W(int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvEncoder:
"""Convolutional encoder for images datasets. Convolutions (with 3x3 kernel size, see DownConvBlock for details) followed by a FC network."""
def __init__(self, H, W, input_channel, channel_list, hidden_dims, z_dim):
"""Init. Args: H(int): Height of the input data. W(int): Width of t... | the_stack_v2_python_sparse | grae/models/torch_modules.py | jakerhodes/GRAE | train | 0 |
2f63d7bbb540347bc8af6a2cb9cabf9c4c17954d | [
"profile = Shop_User(id=current_user.id).profile\nif profile:\n profile = marshal(profile, output_userProfile)\n return Response(data=profile)\nelse:\n return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无资料')",
"args = reqparse.RequestParser().add_argument('building', type=str, location='json',... | <|body_start_0|>
profile = Shop_User(id=current_user.id).profile
if profile:
profile = marshal(profile, output_userProfile)
return Response(data=profile)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOUND, message='无资料')
<|end_body_0|>
<|body_start_1|>
... | Profile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Profile:
def get(self):
"""获取个人资料 :return:"""
<|body_0|>
def put(self):
"""修改个人资料 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
profile = Shop_User(id=current_user.id).profile
if profile:
profile = marshal(profile, out... | stack_v2_sparse_classes_36k_train_008997 | 2,760 | no_license | [
{
"docstring": "获取个人资料 :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "修改个人资料 :return:",
"name": "put",
"signature": "def put(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014913 | Implement the Python class `Profile` described below.
Class description:
Implement the Profile class.
Method signatures and docstrings:
- def get(self): 获取个人资料 :return:
- def put(self): 修改个人资料 :return: | Implement the Python class `Profile` described below.
Class description:
Implement the Profile class.
Method signatures and docstrings:
- def get(self): 获取个人资料 :return:
- def put(self): 修改个人资料 :return:
<|skeleton|>
class Profile:
def get(self):
"""获取个人资料 :return:"""
<|body_0|>
def put(self)... | 34a2bf4a51cc40a22dd43cb5eb88af7c2f2c5120 | <|skeleton|>
class Profile:
def get(self):
"""获取个人资料 :return:"""
<|body_0|>
def put(self):
"""修改个人资料 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Profile:
def get(self):
"""获取个人资料 :return:"""
profile = Shop_User(id=current_user.id).profile
if profile:
profile = marshal(profile, output_userProfile)
return Response(data=profile)
else:
return Response(code=HttpStatus.HTTP_404_NOT_FOUND, m... | the_stack_v2_python_sparse | App/Shop/Controller/UserResource.py | Vulcanhy/api.grooo-master | train | 0 | |
31a0b3dc75b96d5dfd42e7cfccf7cc338e2a6a42 | [
"if dtype == np.int8 or dtype == np.int32:\n return DTYPE.INT\nelif dtype == np.uint or dtype == np.uint64:\n return DTYPE.ULONG\nelif dtype == np.int64:\n return DTYPE.LONG\nelif dtype == np.float32:\n return DTYPE.FLOAT\nelif dtype == np.float64:\n return DTYPE.DOUBLE\nelif dtype == np.bool:\n r... | <|body_start_0|>
if dtype == np.int8 or dtype == np.int32:
return DTYPE.INT
elif dtype == np.uint or dtype == np.uint64:
return DTYPE.ULONG
elif dtype == np.int64:
return DTYPE.LONG
elif dtype == np.float32:
return DTYPE.FLOAT
elif ... | TypeUtil | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TypeUtil:
def to_id_dtype(dtype):
"""to_numpy_dtype"""
<|body_0|>
def to_numpy_dtype(dtype):
"""to_numpy_dtype"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if dtype == np.int8 or dtype == np.int32:
return DTYPE.INT
elif dtype ... | stack_v2_sparse_classes_36k_train_008998 | 2,769 | permissive | [
{
"docstring": "to_numpy_dtype",
"name": "to_id_dtype",
"signature": "def to_id_dtype(dtype)"
},
{
"docstring": "to_numpy_dtype",
"name": "to_numpy_dtype",
"signature": "def to_numpy_dtype(dtype)"
}
] | 2 | null | Implement the Python class `TypeUtil` described below.
Class description:
Implement the TypeUtil class.
Method signatures and docstrings:
- def to_id_dtype(dtype): to_numpy_dtype
- def to_numpy_dtype(dtype): to_numpy_dtype | Implement the Python class `TypeUtil` described below.
Class description:
Implement the TypeUtil class.
Method signatures and docstrings:
- def to_id_dtype(dtype): to_numpy_dtype
- def to_numpy_dtype(dtype): to_numpy_dtype
<|skeleton|>
class TypeUtil:
def to_id_dtype(dtype):
"""to_numpy_dtype"""
... | 875ae298dfa84ee9815f53db5bf7a8b76a379a6f | <|skeleton|>
class TypeUtil:
def to_id_dtype(dtype):
"""to_numpy_dtype"""
<|body_0|>
def to_numpy_dtype(dtype):
"""to_numpy_dtype"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TypeUtil:
def to_id_dtype(dtype):
"""to_numpy_dtype"""
if dtype == np.int8 or dtype == np.int32:
return DTYPE.INT
elif dtype == np.uint or dtype == np.uint64:
return DTYPE.ULONG
elif dtype == np.int64:
return DTYPE.LONG
elif dtype == ... | the_stack_v2_python_sparse | src/foreign_if/python/main/python/frovedis/matrix/dtype.py | frovedis/frovedis | train | 68 | |
62b6b015d08e3d1fa302ec62d95e94250b82c7f5 | [
"if not root:\n return True\nreturn self.check(root) != -1",
"if not root:\n return 0\nelse:\n left = self.check(root.left)\n right = self.check(root.right)\n if left == -1 or right == -1 or abs(left - right) > 1:\n return -1\n else:\n return max(left, right) + 1"
] | <|body_start_0|>
if not root:
return True
return self.check(root) != -1
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
else:
left = self.check(root.left)
right = self.check(root.right)
if left == -1 or right == -1 or abs... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def check(self, root):
"""combine calculate depth of a tree (subtree) and examine whether subtrees are balanced together. If return -1 means current node is not balanced, else re... | stack_v2_sparse_classes_36k_train_008999 | 1,768 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isBalanced",
"signature": "def isBalanced(self, root)"
},
{
"docstring": "combine calculate depth of a tree (subtree) and examine whether subtrees are balanced together. If return -1 means current node is not balanced, else return actu... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def check(self, root): combine calculate depth of a tree (subtree) and examine whether subtrees are balanced toget... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isBalanced(self, root): :type root: TreeNode :rtype: bool
- def check(self, root): combine calculate depth of a tree (subtree) and examine whether subtrees are balanced toget... | 2bcd0f6a704346cdac4ecccd6c0baef579d38fac | <|skeleton|>
class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def check(self, root):
"""combine calculate depth of a tree (subtree) and examine whether subtrees are balanced together. If return -1 means current node is not balanced, else re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isBalanced(self, root):
""":type root: TreeNode :rtype: bool"""
if not root:
return True
return self.check(root) != -1
def check(self, root):
"""combine calculate depth of a tree (subtree) and examine whether subtrees are balanced together. If ret... | the_stack_v2_python_sparse | BalancedBinaryTree.py | marsunique/LeetCodeOJ | train | 1 |
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