blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
55985167491ac63bb4049ec33e7dbf677eb205fb | [
"if not isinstance(value, list):\n raise XRPLBinaryCodecException(f'Invalid type to construct a Path: expected list, received {value.__class__.__name__}.')\nbuffer: bytes = b''\nfor PathStep_dict in value:\n pathstep = PathStep.from_value(PathStep_dict)\n buffer += bytes(pathstep)\nreturn Path(buffer)",
... | <|body_start_0|>
if not isinstance(value, list):
raise XRPLBinaryCodecException(f'Invalid type to construct a Path: expected list, received {value.__class__.__name__}.')
buffer: bytes = b''
for PathStep_dict in value:
pathstep = PathStep.from_value(PathStep_dict)
... | Class for serializing/deserializing Paths. | Path | [
"ISC",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed f... | stack_v2_sparse_classes_36k_train_001500 | 9,067 | permissive | [
{
"docstring": "Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed from value. Raises: XRPLBinaryCodecException: If the supplied value is of the wrong type.",
"name": "from_value",
"signature": "def f... | 3 | null | Implement the Python class `Path` described below.
Class description:
Class for serializing/deserializing Paths.
Method signatures and docstrings:
- def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path: Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to cons... | Implement the Python class `Path` described below.
Class description:
Class for serializing/deserializing Paths.
Method signatures and docstrings:
- def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path: Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to cons... | e5bbdf458ad83e6670a4ebf3df63e17fed8b099f | <|skeleton|>
class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Path:
"""Class for serializing/deserializing Paths."""
def from_value(cls: Type[Path], value: List[Dict[str, str]]) -> Path:
"""Construct a Path from an array of dictionaries describing PathSteps. Args: value: The array to construct a Path object from. Returns: The Path constructed from value. Ra... | the_stack_v2_python_sparse | xrpl/core/binarycodec/types/path_set.py | yyolk/xrpl-py | train | 1 |
ae221d51657dab1f2855d85c500cece6263fcaa0 | [
"rv = []\nfor filename in os.listdir(self.cmd_dir):\n if filename.endswith('.py') and filename.startswith('cmd_'):\n rv.append(filename[4:-3])\nrv.sort()\nreturn rv",
"try:\n if sys.version_info[0] == 2:\n name = name.encode('ascii', 'replace')\n mod = __import__(self.cmd_namespace + name, ... | <|body_start_0|>
rv = []
for filename in os.listdir(self.cmd_dir):
if filename.endswith('.py') and filename.startswith('cmd_'):
rv.append(filename[4:-3])
rv.sort()
return rv
<|end_body_0|>
<|body_start_1|>
try:
if sys.version_info[0] == 2:... | DigitalOceanCLI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DigitalOceanCLI:
def list_commands(self, ctx):
"""list the commands found in the commands dir"""
<|body_0|>
def get_command(self, ctx, name):
"""import the requested command"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
rv = []
for filenam... | stack_v2_sparse_classes_36k_train_001501 | 2,455 | permissive | [
{
"docstring": "list the commands found in the commands dir",
"name": "list_commands",
"signature": "def list_commands(self, ctx)"
},
{
"docstring": "import the requested command",
"name": "get_command",
"signature": "def get_command(self, ctx, name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018224 | Implement the Python class `DigitalOceanCLI` described below.
Class description:
Implement the DigitalOceanCLI class.
Method signatures and docstrings:
- def list_commands(self, ctx): list the commands found in the commands dir
- def get_command(self, ctx, name): import the requested command | Implement the Python class `DigitalOceanCLI` described below.
Class description:
Implement the DigitalOceanCLI class.
Method signatures and docstrings:
- def list_commands(self, ctx): list the commands found in the commands dir
- def get_command(self, ctx, name): import the requested command
<|skeleton|>
class Digit... | cd78cb7effce3c56a10edafe41753a1751d1d7dc | <|skeleton|>
class DigitalOceanCLI:
def list_commands(self, ctx):
"""list the commands found in the commands dir"""
<|body_0|>
def get_command(self, ctx, name):
"""import the requested command"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DigitalOceanCLI:
def list_commands(self, ctx):
"""list the commands found in the commands dir"""
rv = []
for filename in os.listdir(self.cmd_dir):
if filename.endswith('.py') and filename.startswith('cmd_'):
rv.append(filename[4:-3])
rv.sort()
... | the_stack_v2_python_sparse | do_cli/contexts.py | meganlkm/do-cli | train | 0 | |
337eddbef26f1ccbfe0db7343b8bfe540a7d8811 | [
"c, h = carry\ninput_to_hidden = linear.Conv.partial(features=4 * features, kernel_size=kernel_size, strides=strides, padding=padding, bias=bias, dtype=dtype, name='ih')\nhidden_to_hidden = linear.Conv.partial(features=4 * features, kernel_size=kernel_size, strides=strides, padding=padding, bias=bias, dtype=dtype, ... | <|body_start_0|>
c, h = carry
input_to_hidden = linear.Conv.partial(features=4 * features, kernel_size=kernel_size, strides=strides, padding=padding, bias=bias, dtype=dtype, name='ih')
hidden_to_hidden = linear.Conv.partial(features=4 * features, kernel_size=kernel_size, strides=strides, padding... | DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on xingjian2015convolutional. Given x_t and the previous state (h_{t-1}, c_{t... | ConvLSTM | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvLSTM:
"""DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on xingjian2015convolutional. Given x_t a... | stack_v2_sparse_classes_36k_train_001502 | 16,408 | permissive | [
{
"docstring": "Constructs a convolutional LSTM. Args: carry: the hidden state of the Conv2DLSTM cell, initialized using `Conv2DLSTM.initialize_carry`. inputs: input data with dimensions (batch, spatial_dims..., features). features: number of convolution filters. kernel_size: shape of the convolutional kernel. ... | 2 | stack_v2_sparse_classes_30k_train_014693 | Implement the Python class `ConvLSTM` described below.
Class description:
DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on... | Implement the Python class `ConvLSTM` described below.
Class description:
DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on... | 87a483b2b93fa1dd7934da520348e6ce8d7851b4 | <|skeleton|>
class ConvLSTM:
"""DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on xingjian2015convolutional. Given x_t a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvLSTM:
"""DEPRECATION WARNING: The `flax.nn` module is Deprecated, use `flax.linen` instead. Learn more and find an upgrade guide at https://github.com/google/flax/blob/master/flax/linen/README.md" A convolutional LSTM cell. The implementation is based on xingjian2015convolutional. Given x_t and the previo... | the_stack_v2_python_sparse | flax/nn/recurrent.py | marcvanzee/flax | train | 3 |
bc4bd704e0e28659c92d5af3cf8dc43c1e6965be | [
"out_channels, in_channels, _, _ = weight.shape\nif ranks == 'evbmf':\n unfold_0 = tl.base.unfold(weight, 0)\n unfold_1 = tl.base.unfold(weight, 1)\n _, diag_0, _, _ = vbmf.EVBMF(unfold_0)\n _, diag_1, _, _ = vbmf.EVBMF(unfold_1)\n out_rank = diag_0.shape[0]\n in_rank = diag_1.shape[1]\nelif isins... | <|body_start_0|>
out_channels, in_channels, _, _ = weight.shape
if ranks == 'evbmf':
unfold_0 = tl.base.unfold(weight, 0)
unfold_1 = tl.base.unfold(weight, 1)
_, diag_0, _, _ = vbmf.EVBMF(unfold_0)
_, diag_1, _, _ = vbmf.EVBMF(unfold_1)
out_ran... | Decomposed (or compressed) convolutional layer. | DecomposedConv2d | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecomposedConv2d:
"""Decomposed (or compressed) convolutional layer."""
def choose_ranks(weight, ranks):
"""Choose the target ranks."""
<|body_0|>
def __init__(self, layer, ranks='evbmf', init=True):
"""Class initializer."""
<|body_1|>
def forward(se... | stack_v2_sparse_classes_36k_train_001503 | 5,386 | permissive | [
{
"docstring": "Choose the target ranks.",
"name": "choose_ranks",
"signature": "def choose_ranks(weight, ranks)"
},
{
"docstring": "Class initializer.",
"name": "__init__",
"signature": "def __init__(self, layer, ranks='evbmf', init=True)"
},
{
"docstring": "Forward propagation.... | 4 | stack_v2_sparse_classes_30k_test_000005 | Implement the Python class `DecomposedConv2d` described below.
Class description:
Decomposed (or compressed) convolutional layer.
Method signatures and docstrings:
- def choose_ranks(weight, ranks): Choose the target ranks.
- def __init__(self, layer, ranks='evbmf', init=True): Class initializer.
- def forward(self, ... | Implement the Python class `DecomposedConv2d` described below.
Class description:
Decomposed (or compressed) convolutional layer.
Method signatures and docstrings:
- def choose_ranks(weight, ranks): Choose the target ranks.
- def __init__(self, layer, ranks='evbmf', init=True): Class initializer.
- def forward(self, ... | fe5d1eb5ab5453be70c4be473fd3da71afe4b06c | <|skeleton|>
class DecomposedConv2d:
"""Decomposed (or compressed) convolutional layer."""
def choose_ranks(weight, ranks):
"""Choose the target ranks."""
<|body_0|>
def __init__(self, layer, ranks='evbmf', init=True):
"""Class initializer."""
<|body_1|>
def forward(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecomposedConv2d:
"""Decomposed (or compressed) convolutional layer."""
def choose_ranks(weight, ranks):
"""Choose the target ranks."""
out_channels, in_channels, _, _ = weight.shape
if ranks == 'evbmf':
unfold_0 = tl.base.unfold(weight, 0)
unfold_1 = tl.ba... | the_stack_v2_python_sparse | src/kegnet/utils/tucker.py | videoturingtest/KegNet | train | 0 |
7ee2c2015181d14ba2ca2558d54c194c6d80ea40 | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Request`` messages as boolean expressions over these facts: (1) ``HasRight(r)`` denoting whether the au... | PartyManagementServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PartyManagementServiceServicer:
"""This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Request`` messages as boolean expressions ove... | stack_v2_sparse_classes_36k_train_001504 | 16,483 | permissive | [
{
"docstring": "Return the identifier of the participant. All horizontally scaled replicas should return the same id. daml-on-kv-ledger: returns an identifier supplied on command line at launch time canton: returns globally unique identifier of the participant",
"name": "GetParticipantId",
"signature": ... | 5 | null | Implement the Python class `PartyManagementServiceServicer` described below.
Class description:
This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Reques... | Implement the Python class `PartyManagementServiceServicer` described below.
Class description:
This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Reques... | efdbb00e54614c0af650d7440faaffbde92ad1f4 | <|skeleton|>
class PartyManagementServiceServicer:
"""This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Request`` messages as boolean expressions ove... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PartyManagementServiceServicer:
"""This service allows inspecting the party management state of the ledger known to the participant and managing the participant-local party metadata. The authorization rules for its RPCs are specified on the ``<RpcName>Request`` messages as boolean expressions over these facts... | the_stack_v2_python_sparse | python/dazl/_gen/com/daml/ledger/api/v1/admin/party_management_service_pb2_grpc.py | digital-asset/dazl-client | train | 12 |
fbc71fc9cb47523ce6a7b1aed3f1c24b3723846b | [
"nums = [i ** 2 for i in range(1, n + 1) if i ** 2 <= n]\ndp = [10 ** 4] * (n + 1)\ndp[0] = 0\nfor j in range(1, n + 1):\n for num in nums:\n if j >= num:\n dp[j] = min(dp[j], dp[j - num] + 1)\nreturn dp[n]",
"nums = [i ** 2 for i in range(1, n + 1) if i ** 2 <= n]\ndp = [10 ** 4] * (n + 1)\n... | <|body_start_0|>
nums = [i ** 2 for i in range(1, n + 1) if i ** 2 <= n]
dp = [10 ** 4] * (n + 1)
dp[0] = 0
for j in range(1, n + 1):
for num in nums:
if j >= num:
dp[j] = min(dp[j], dp[j - num] + 1)
return dp[n]
<|end_body_0|>
<|b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numSquares(self, n: int) -> int:
"""版本一"""
<|body_0|>
def numSquares1(self, n: int) -> int:
"""版本二"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums = [i ** 2 for i in range(1, n + 1) if i ** 2 <= n]
dp = [10 ** 4] * (n + 1)... | stack_v2_sparse_classes_36k_train_001505 | 1,301 | no_license | [
{
"docstring": "版本一",
"name": "numSquares",
"signature": "def numSquares(self, n: int) -> int"
},
{
"docstring": "版本二",
"name": "numSquares1",
"signature": "def numSquares1(self, n: int) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_002904 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares(self, n: int) -> int: 版本一
- def numSquares1(self, n: int) -> int: 版本二 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numSquares(self, n: int) -> int: 版本一
- def numSquares1(self, n: int) -> int: 版本二
<|skeleton|>
class Solution:
def numSquares(self, n: int) -> int:
"""版本一"""
... | 9aee4fa0ea211d28ff1e5d9b70597421f9562959 | <|skeleton|>
class Solution:
def numSquares(self, n: int) -> int:
"""版本一"""
<|body_0|>
def numSquares1(self, n: int) -> int:
"""版本二"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numSquares(self, n: int) -> int:
"""版本一"""
nums = [i ** 2 for i in range(1, n + 1) if i ** 2 <= n]
dp = [10 ** 4] * (n + 1)
dp[0] = 0
for j in range(1, n + 1):
for num in nums:
if j >= num:
dp[j] = min(dp[j],... | the_stack_v2_python_sparse | Python/numSquares.py | Litao439420999/LeetCodeAlgorithm | train | 0 | |
be805a89a401f81a532397b06d6191d5ef02ce35 | [
"self.loaded = False\nself.instances = instances\nself.path = path",
"if not self.instances and (not self.loaded):\n self.loaded = True\n self.instances = {}\n for importer_wrapper in dynamic_directory_importer(path):\n if importer_wrapper.error:\n logger.error('Error Loading Plugin: {0... | <|body_start_0|>
self.loaded = False
self.instances = instances
self.path = path
<|end_body_0|>
<|body_start_1|>
if not self.instances and (not self.loaded):
self.loaded = True
self.instances = {}
for importer_wrapper in dynamic_directory_importer(pat... | PluginManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginManager:
def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY):
"""Used to initialize plugin"""
<|body_0|>
def _load(self, path=BASE_PLUGIN_DIRECTORY):
"""Lazy loading of plugins"""
<|body_1|>
def __getattr__(self, plugin_name, path=BASE_P... | stack_v2_sparse_classes_36k_train_001506 | 8,795 | permissive | [
{
"docstring": "Used to initialize plugin",
"name": "__init__",
"signature": "def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY)"
},
{
"docstring": "Lazy loading of plugins",
"name": "_load",
"signature": "def _load(self, path=BASE_PLUGIN_DIRECTORY)"
},
{
"docstring":... | 5 | stack_v2_sparse_classes_30k_train_017818 | Implement the Python class `PluginManager` described below.
Class description:
Implement the PluginManager class.
Method signatures and docstrings:
- def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY): Used to initialize plugin
- def _load(self, path=BASE_PLUGIN_DIRECTORY): Lazy loading of plugins
- def _... | Implement the Python class `PluginManager` described below.
Class description:
Implement the PluginManager class.
Method signatures and docstrings:
- def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY): Used to initialize plugin
- def _load(self, path=BASE_PLUGIN_DIRECTORY): Lazy loading of plugins
- def _... | d31d00bb8a28a8d0c999813f616b398f41516244 | <|skeleton|>
class PluginManager:
def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY):
"""Used to initialize plugin"""
<|body_0|>
def _load(self, path=BASE_PLUGIN_DIRECTORY):
"""Lazy loading of plugins"""
<|body_1|>
def __getattr__(self, plugin_name, path=BASE_P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PluginManager:
def __init__(self, instances=None, path=BASE_PLUGIN_DIRECTORY):
"""Used to initialize plugin"""
self.loaded = False
self.instances = instances
self.path = path
def _load(self, path=BASE_PLUGIN_DIRECTORY):
"""Lazy loading of plugins"""
if not ... | the_stack_v2_python_sparse | plugins/plugin_manager.py | ozoneplatform/ozp-backend | train | 1 | |
fac5d7f5c4698f79e94d9abaa3e5e6dfd71d5d0e | [
"self.name = name\nself.card_number = card_number\nself.apr_percent = apr_percent\nself.limit = limit\nself.balance = 0\nself.fees = 0",
"if purchase_price + self.balance + self.fees > self.limit:\n return False\nelse:\n self.balance += purchase_price\n return True",
"if payment_amount > 0 and payment_... | <|body_start_0|>
self.name = name
self.card_number = card_number
self.apr_percent = apr_percent
self.limit = limit
self.balance = 0
self.fees = 0
<|end_body_0|>
<|body_start_1|>
if purchase_price + self.balance + self.fees > self.limit:
return False
... | This class provides a template for a personal credit card. It has already been completely filled out for you. | CreditCard | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreditCard:
"""This class provides a template for a personal credit card. It has already been completely filled out for you."""
def __init__(self, name, card_number, apr_percent, limit):
"""Initialize an instance of the class. Arguments: name: The name of the account holder card_numb... | stack_v2_sparse_classes_36k_train_001507 | 6,139 | no_license | [
{
"docstring": "Initialize an instance of the class. Arguments: name: The name of the account holder card_number: The credit card number apr_percent: The APR, as a percentage (i.e. 20 instead of 0.2 for a 20 percent APR). limit: The limit on the card. Returns: None Sets the following class attributes: name = na... | 4 | null | Implement the Python class `CreditCard` described below.
Class description:
This class provides a template for a personal credit card. It has already been completely filled out for you.
Method signatures and docstrings:
- def __init__(self, name, card_number, apr_percent, limit): Initialize an instance of the class. ... | Implement the Python class `CreditCard` described below.
Class description:
This class provides a template for a personal credit card. It has already been completely filled out for you.
Method signatures and docstrings:
- def __init__(self, name, card_number, apr_percent, limit): Initialize an instance of the class. ... | 9f55c92f599166c9ccf9c8ed2c94e337a2423c60 | <|skeleton|>
class CreditCard:
"""This class provides a template for a personal credit card. It has already been completely filled out for you."""
def __init__(self, name, card_number, apr_percent, limit):
"""Initialize an instance of the class. Arguments: name: The name of the account holder card_numb... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreditCard:
"""This class provides a template for a personal credit card. It has already been completely filled out for you."""
def __init__(self, name, card_number, apr_percent, limit):
"""Initialize an instance of the class. Arguments: name: The name of the account holder card_number: The credi... | the_stack_v2_python_sparse | Copies/PythFound2/classes_2.py | MFahey0706/LocalMisc | train | 0 |
706ef83f8504f257c5a7d287bf342f597038bd88 | [
"declared = []\nfor obj in Rt.objective:\n var_list = splt('[+*/-]', obj)\n for v in var_list:\n if v not in declared:\n self.add_input(v)\n declared.append(v)\n self.add_output('Objective function ' + obj)",
"global counter\ncounter += 1\ncpacs_path = mif.get_tooloutput_file... | <|body_start_0|>
declared = []
for obj in Rt.objective:
var_list = splt('[+*/-]', obj)
for v in var_list:
if v not in declared:
self.add_input(v)
declared.append(v)
self.add_output('Objective function ' + obj)
<|... | Class to compute the objective function(s) | Objective | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Compute the objective expression"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
declar... | stack_v2_sparse_classes_36k_train_001508 | 21,151 | permissive | [
{
"docstring": "Setup inputs and outputs",
"name": "setup",
"signature": "def setup(self)"
},
{
"docstring": "Compute the objective expression",
"name": "compute",
"signature": "def compute(self, inputs, outputs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011601 | Implement the Python class `Objective` described below.
Class description:
Class to compute the objective function(s)
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Compute the objective expression | Implement the Python class `Objective` described below.
Class description:
Class to compute the objective function(s)
Method signatures and docstrings:
- def setup(self): Setup inputs and outputs
- def compute(self, inputs, outputs): Compute the objective expression
<|skeleton|>
class Objective:
"""Class to comp... | 3cc211507caab176a76213e442238abfa43afa42 | <|skeleton|>
class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
<|body_0|>
def compute(self, inputs, outputs):
"""Compute the objective expression"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Objective:
"""Class to compute the objective function(s)"""
def setup(self):
"""Setup inputs and outputs"""
declared = []
for obj in Rt.objective:
var_list = splt('[+*/-]', obj)
for v in var_list:
if v not in declared:
se... | the_stack_v2_python_sparse | ceasiompy/Optimisation/optimisation.py | schneo/CEASIOMpy | train | 0 |
5438d06bdd1830e1613cd34df1fb13235798e29b | [
"for i in range(len(s)):\n t = s[:i] + s[i + 1:]\n if t == t[::-1]:\n return True\nreturn s == s[::-1]",
"def is_pali_range(i, j):\n return all((s[k] == s[j - k + i] for k in range(i, j)))\nfor i in range(len(s) / 2):\n if s[i] != s[~i]:\n j = len(s) - 1 - i\n return is_pali_range... | <|body_start_0|>
for i in range(len(s)):
t = s[:i] + s[i + 1:]
if t == t[::-1]:
return True
return s == s[::-1]
<|end_body_0|>
<|body_start_1|>
def is_pali_range(i, j):
return all((s[k] == s[j - k + i] for k in range(i, j)))
for i in r... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validPalindrome(self, s: str) -> bool:
"""For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if the original string was a palindrome), then we'll return true"""
<|body_0|>
def val... | stack_v2_sparse_classes_36k_train_001509 | 1,977 | no_license | [
{
"docstring": "For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if the original string was a palindrome), then we'll return true",
"name": "validPalindrome",
"signature": "def validPalindrome(self, s: str) -> bool"
},... | 2 | stack_v2_sparse_classes_30k_train_007417 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validPalindrome(self, s: str) -> bool: For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validPalindrome(self, s: str) -> bool: For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if... | 727dec2e23e765925a5e7e003fc99aeaf25111e9 | <|skeleton|>
class Solution:
def validPalindrome(self, s: str) -> bool:
"""For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if the original string was a palindrome), then we'll return true"""
<|body_0|>
def val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def validPalindrome(self, s: str) -> bool:
"""For each index i in the given string, let's remove that character, then check if the resulting string is a palindrome. If it is, (or if the original string was a palindrome), then we'll return true"""
for i in range(len(s)):
t... | the_stack_v2_python_sparse | funNLearn/src/main/java/dsAlgo/leetcode/P6xx/P680_ValidPalindromeII.py | vishalpmittal/practice-fun | train | 0 | |
9c6684aa576dca6d54dd1489545aa23d4bb085fc | [
"tours = StatisticDAO.get_tours(start_date, end_date)\nlabels = [str(name) for name, count in tours]\ndata = [count for name, count in tours]\nreturn (labels, data)",
"tourguides = StatisticDAO.get_static_from_tour_guide(start_date, end_date)\nlabels = [str(name) for name, count in tourguides]\ndata = [count for ... | <|body_start_0|>
tours = StatisticDAO.get_tours(start_date, end_date)
labels = [str(name) for name, count in tours]
data = [count for name, count in tours]
return (labels, data)
<|end_body_0|>
<|body_start_1|>
tourguides = StatisticDAO.get_static_from_tour_guide(start_date, end_... | Statistics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Statistics:
def get_stat_by_registered_user(self, start_date, end_date):
"""Queries the tours from the database, then returns a tuple that contains labels and data, which are required to display the carts. :param start_date: the begin of the time interval :param end_date: the end of the ... | stack_v2_sparse_classes_36k_train_001510 | 2,012 | no_license | [
{
"docstring": "Queries the tours from the database, then returns a tuple that contains labels and data, which are required to display the carts. :param start_date: the begin of the time interval :param end_date: the end of the time interval :return: a tuple that contains: labels, data",
"name": "get_stat_b... | 3 | stack_v2_sparse_classes_30k_train_020337 | Implement the Python class `Statistics` described below.
Class description:
Implement the Statistics class.
Method signatures and docstrings:
- def get_stat_by_registered_user(self, start_date, end_date): Queries the tours from the database, then returns a tuple that contains labels and data, which are required to di... | Implement the Python class `Statistics` described below.
Class description:
Implement the Statistics class.
Method signatures and docstrings:
- def get_stat_by_registered_user(self, start_date, end_date): Queries the tours from the database, then returns a tuple that contains labels and data, which are required to di... | 84fcd3c95bd8792b1f1c9cfc5680b88282a0f922 | <|skeleton|>
class Statistics:
def get_stat_by_registered_user(self, start_date, end_date):
"""Queries the tours from the database, then returns a tuple that contains labels and data, which are required to display the carts. :param start_date: the begin of the time interval :param end_date: the end of the ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Statistics:
def get_stat_by_registered_user(self, start_date, end_date):
"""Queries the tours from the database, then returns a tuple that contains labels and data, which are required to display the carts. :param start_date: the begin of the time interval :param end_date: the end of the time interval ... | the_stack_v2_python_sparse | app/statistics/statistics.py | feco93/TouristGuide | train | 0 | |
2553acd15ed4409686ff5a07c3c71ec1af974796 | [
"Frame.__init__(self, master)\nself.pack()\nself.createWidgets()",
"top_frame = Frame(self)\nself.text_in = Entry(top_frame)\nself.label = Label(top_frame, text='Output label')\nself.text_in.pack()\nself.label.pack()\nself.r = IntVar()\nRadiobutton(top_frame, text='Upper case', variable=self.r, value=1).pack(side... | <|body_start_0|>
Frame.__init__(self, master)
self.pack()
self.createWidgets()
<|end_body_0|>
<|body_start_1|>
top_frame = Frame(self)
self.text_in = Entry(top_frame)
self.label = Label(top_frame, text='Output label')
self.text_in.pack()
self.label.pack()... | Application main window class. | Application | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_36k_train_001511 | 1,749 | permissive | [
{
"docstring": "Main frame initialization (mostly delegated)",
"name": "__init__",
"signature": "def __init__(self, master=None)"
},
{
"docstring": "Add all the widgets to the main frame.",
"name": "createWidgets",
"signature": "def createWidgets(self)"
},
{
"docstring": "Handle ... | 3 | stack_v2_sparse_classes_30k_train_003788 | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createWidgets(self): Add all the widgets to the main frame.
- def handle(self): Handle a c... | Implement the Python class `Application` described below.
Class description:
Application main window class.
Method signatures and docstrings:
- def __init__(self, master=None): Main frame initialization (mostly delegated)
- def createWidgets(self): Add all the widgets to the main frame.
- def handle(self): Handle a c... | 042e0ce964bc88b3f4132dcbd7e06c5f504eae34 | <|skeleton|>
class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
<|body_0|>
def createWidgets(self):
"""Add all the widgets to the main frame."""
<|body_1|>
def handle(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Application:
"""Application main window class."""
def __init__(self, master=None):
"""Main frame initialization (mostly delegated)"""
Frame.__init__(self, master)
self.pack()
self.createWidgets()
def createWidgets(self):
"""Add all the widgets to the main fram... | the_stack_v2_python_sparse | Python2/IntroGUI/src/texthandler.py | ceeblet/OST_PythonCertificationTrack | train | 0 |
1e41de733959a53c45a4cdd478d2252c255c743b | [
"for i in range(1, len(events)):\n assert events[i].obj == events[0].obj\nself.obj = events[0].obj\nself.events = events\nself.events.sort(key=lambda e: e.prob)\nprob = 0\nfor event in self.events:\n prob += event.prob\nassert util.approx(prob, 1.0)",
"f = random.random()\nevent = None\nfor i in range(len(s... | <|body_start_0|>
for i in range(1, len(events)):
assert events[i].obj == events[0].obj
self.obj = events[0].obj
self.events = events
self.events.sort(key=lambda e: e.prob)
prob = 0
for event in self.events:
prob += event.prob
assert util.ap... | A distribution as defined by the scavnger hunt problem. | Distribution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Distribution:
"""A distribution as defined by the scavnger hunt problem."""
def __init__(self, events):
"""The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describe the same object."""
<|body_0|>
def place(s... | stack_v2_sparse_classes_36k_train_001512 | 21,028 | no_license | [
{
"docstring": "The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describe the same object.",
"name": "__init__",
"signature": "def __init__(self, events)"
},
{
"docstring": "Generates a random location for the described object to ap... | 2 | stack_v2_sparse_classes_30k_train_021564 | Implement the Python class `Distribution` described below.
Class description:
A distribution as defined by the scavnger hunt problem.
Method signatures and docstrings:
- def __init__(self, events): The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describ... | Implement the Python class `Distribution` described below.
Class description:
A distribution as defined by the scavnger hunt problem.
Method signatures and docstrings:
- def __init__(self, events): The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describ... | bebffb2e886ba990f6b5fe6d51aa3ec4571c8d8c | <|skeleton|>
class Distribution:
"""A distribution as defined by the scavnger hunt problem."""
def __init__(self, events):
"""The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describe the same object."""
<|body_0|>
def place(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Distribution:
"""A distribution as defined by the scavnger hunt problem."""
def __init__(self, events):
"""The distribution is comprised of EVENTS. The events therein are collectively exhaustive, mutually exclusive, and describe the same object."""
for i in range(1, len(events)):
... | the_stack_v2_python_sparse | bwi_scavenger/scripts/absim/world.py | utexas-bwi/scavenger_hunt | train | 2 |
67e5670b3e365348f8797cfe2df8113397c3eee7 | [
"expected = '{SHA}X+lk6KR7JuJEH43YnmettCwICdU='\nresult = user.encodePassword('MoinMoin')\nself.assertEqual(result, expected, 'Expected \"%(expected)s\" but got \"%(result)s\"' % locals())\nresult = user.encodePassword(u'MoinMoin')\nself.assertEqual(result, expected, 'Expected \"%(expected)s\" but got \"%(result)s\... | <|body_start_0|>
expected = '{SHA}X+lk6KR7JuJEH43YnmettCwICdU='
result = user.encodePassword('MoinMoin')
self.assertEqual(result, expected, 'Expected "%(expected)s" but got "%(result)s"' % locals())
result = user.encodePassword(u'MoinMoin')
self.assertEqual(result, expected, 'Exp... | user: encode passwords tests | EncodePasswordTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodePasswordTestCase:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
<|body_0|>
def testUnicode(self):
"""user: encode unicode password"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
expected = '{SHA... | stack_v2_sparse_classes_36k_train_001513 | 8,790 | no_license | [
{
"docstring": "user: encode ascii password",
"name": "testAscii",
"signature": "def testAscii(self)"
},
{
"docstring": "user: encode unicode password",
"name": "testUnicode",
"signature": "def testUnicode(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002838 | Implement the Python class `EncodePasswordTestCase` described below.
Class description:
user: encode passwords tests
Method signatures and docstrings:
- def testAscii(self): user: encode ascii password
- def testUnicode(self): user: encode unicode password | Implement the Python class `EncodePasswordTestCase` described below.
Class description:
user: encode passwords tests
Method signatures and docstrings:
- def testAscii(self): user: encode ascii password
- def testUnicode(self): user: encode unicode password
<|skeleton|>
class EncodePasswordTestCase:
"""user: enco... | a2c30c3b742c65fb2c5bfbab1267d643823882a5 | <|skeleton|>
class EncodePasswordTestCase:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
<|body_0|>
def testUnicode(self):
"""user: encode unicode password"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncodePasswordTestCase:
"""user: encode passwords tests"""
def testAscii(self):
"""user: encode ascii password"""
expected = '{SHA}X+lk6KR7JuJEH43YnmettCwICdU='
result = user.encodePassword('MoinMoin')
self.assertEqual(result, expected, 'Expected "%(expected)s" but got "%(... | the_stack_v2_python_sparse | mysocietyorg/moin/lib/python2.4/site-packages/MoinMoin/_tests/test_user.py | MyfanwyNixon/orgsites | train | 0 |
681d0e58a9c8be76d6122471d48e45f2752e8512 | [
"self.__products = {}\nself.__item_code = ''\nself.__item_data = []\nself.__item_price = 0.0\nself.__item_name = ''",
"input_file = open('list_price.txt', 'r')\nfor line in input_file:\n line = line.split(',')\n self.__item_code = line[0]\n self.__item_price = float(line[1])\n self.__item_name = line[... | <|body_start_0|>
self.__products = {}
self.__item_code = ''
self.__item_data = []
self.__item_price = 0.0
self.__item_name = ''
<|end_body_0|>
<|body_start_1|>
input_file = open('list_price.txt', 'r')
for line in input_file:
line = line.split(',')
... | Class reads product list file, displays full list and specific item | ProductList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductList:
"""Class reads product list file, displays full list and specific item"""
def __init__(self):
"""Creates instance variables"""
<|body_0|>
def GenerateProductList(self):
"""Read data in for products and returns information as dictionary"""
<|b... | stack_v2_sparse_classes_36k_train_001514 | 2,595 | no_license | [
{
"docstring": "Creates instance variables",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Read data in for products and returns information as dictionary",
"name": "GenerateProductList",
"signature": "def GenerateProductList(self)"
},
{
"docstring": "D... | 4 | stack_v2_sparse_classes_30k_train_017122 | Implement the Python class `ProductList` described below.
Class description:
Class reads product list file, displays full list and specific item
Method signatures and docstrings:
- def __init__(self): Creates instance variables
- def GenerateProductList(self): Read data in for products and returns information as dict... | Implement the Python class `ProductList` described below.
Class description:
Class reads product list file, displays full list and specific item
Method signatures and docstrings:
- def __init__(self): Creates instance variables
- def GenerateProductList(self): Read data in for products and returns information as dict... | 37d8f5ef954bf8717a7eb7fd58bfa5607e339265 | <|skeleton|>
class ProductList:
"""Class reads product list file, displays full list and specific item"""
def __init__(self):
"""Creates instance variables"""
<|body_0|>
def GenerateProductList(self):
"""Read data in for products and returns information as dictionary"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductList:
"""Class reads product list file, displays full list and specific item"""
def __init__(self):
"""Creates instance variables"""
self.__products = {}
self.__item_code = ''
self.__item_data = []
self.__item_price = 0.0
self.__item_name = ''
d... | the_stack_v2_python_sparse | CSC121FinalProject_WakeMartUpgrade/show_list_prices.py | mischelay2001/WTCSC121 | train | 1 |
66524d582224d7d8747f38a06dee9f33b9ea2fdb | [
"self.name = None\nself.contents = []\nself.exclusions = ['*.pyc', '*.pyd', '*.pyo', '*.pyx', '*.pxi', '__pycache__', '*-info', 'EGG_INFO', '*.so']",
"parts = {}\nfor node in self.contents:\n self._add_part(node, os.path.basename(self.name), parts)\nreturn parts",
"if node.included:\n node_name = parent_n... | <|body_start_0|>
self.name = None
self.contents = []
self.exclusions = ['*.pyc', '*.pyd', '*.pyo', '*.pyx', '*.pxi', '__pycache__', '*-info', 'EGG_INFO', '*.so']
<|end_body_0|>
<|body_start_1|>
parts = {}
for node in self.contents:
self._add_part(node, os.path.basena... | The encapsulation of a memory-filesystem package. | QrcPackage | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QrcPackage:
"""The encapsulation of a memory-filesystem package."""
def __init__(self):
"""Initialise the package."""
<|body_0|>
def parts(self):
"""Return the package as a dict of parts."""
<|body_1|>
def _add_part(self, node, parent_name, parts):
... | stack_v2_sparse_classes_36k_train_001515 | 3,140 | permissive | [
{
"docstring": "Initialise the package.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Return the package as a dict of parts.",
"name": "parts",
"signature": "def parts(self)"
},
{
"docstring": "Add a single file or directory to the parts dict.",
"... | 3 | null | Implement the Python class `QrcPackage` described below.
Class description:
The encapsulation of a memory-filesystem package.
Method signatures and docstrings:
- def __init__(self): Initialise the package.
- def parts(self): Return the package as a dict of parts.
- def _add_part(self, node, parent_name, parts): Add a... | Implement the Python class `QrcPackage` described below.
Class description:
The encapsulation of a memory-filesystem package.
Method signatures and docstrings:
- def __init__(self): Initialise the package.
- def parts(self): Return the package as a dict of parts.
- def _add_part(self, node, parent_name, parts): Add a... | 4ed2b1b9a2407afcbffdf304020d42b81c4c8cdc | <|skeleton|>
class QrcPackage:
"""The encapsulation of a memory-filesystem package."""
def __init__(self):
"""Initialise the package."""
<|body_0|>
def parts(self):
"""Return the package as a dict of parts."""
<|body_1|>
def _add_part(self, node, parent_name, parts):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QrcPackage:
"""The encapsulation of a memory-filesystem package."""
def __init__(self):
"""Initialise the package."""
self.name = None
self.contents = []
self.exclusions = ['*.pyc', '*.pyd', '*.pyo', '*.pyx', '*.pxi', '__pycache__', '*-info', 'EGG_INFO', '*.so']
def p... | the_stack_v2_python_sparse | note/demo/pyqt_demo/pyqtdeploy-3.3.0/pyqtdeploy/project/project_parts.py | onsunsl/onsunsl.github.io | train | 1 |
20b84885e1395fc58b3a1bc7e5c96976f2fb02eb | [
"self.cam_files = cam_files\nself.log_files = log_files\nself.shrink_size = shrink_size / 2 if shrink_size else None\nself.resize_dims = resize_dims\nself.crop_size = crop_size\nself.str_angles = np.zeros(1)\nself.folder_name = folder_name\nself.batch_size = batch_size\nself.ds_min = ds_min\nself.ds_max = ds_max",
... | <|body_start_0|>
self.cam_files = cam_files
self.log_files = log_files
self.shrink_size = shrink_size / 2 if shrink_size else None
self.resize_dims = resize_dims
self.crop_size = crop_size
self.str_angles = np.zeros(1)
self.folder_name = folder_name
self.b... | Class for creating data preprocessor instances. | DataPreprocessor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataPreprocessor:
"""Class for creating data preprocessor instances."""
def __init__(self, cam_files, log_files, folder_name, batch_size=B_SIZE, ds_min=None, ds_max=None, shrink_size=None, resize_dims=RESIZE_DIMS, crop_size=CROP_SIZE):
"""Set the data preprocessor instance attributes... | stack_v2_sparse_classes_36k_train_001516 | 4,470 | permissive | [
{
"docstring": "Set the data preprocessor instance attributes. :param cam_files: input camera frame recordings :param log_files: measurement log files :param folder_name: name of the folder where the preprocessed data will be stored :param batch_size: preprocessing batch size (set to 64 by default) :param ds_mi... | 2 | stack_v2_sparse_classes_30k_train_016288 | Implement the Python class `DataPreprocessor` described below.
Class description:
Class for creating data preprocessor instances.
Method signatures and docstrings:
- def __init__(self, cam_files, log_files, folder_name, batch_size=B_SIZE, ds_min=None, ds_max=None, shrink_size=None, resize_dims=RESIZE_DIMS, crop_size=... | Implement the Python class `DataPreprocessor` described below.
Class description:
Class for creating data preprocessor instances.
Method signatures and docstrings:
- def __init__(self, cam_files, log_files, folder_name, batch_size=B_SIZE, ds_min=None, ds_max=None, shrink_size=None, resize_dims=RESIZE_DIMS, crop_size=... | 31d23471bccf2c5fe64d5c628a21150d65c2aeec | <|skeleton|>
class DataPreprocessor:
"""Class for creating data preprocessor instances."""
def __init__(self, cam_files, log_files, folder_name, batch_size=B_SIZE, ds_min=None, ds_max=None, shrink_size=None, resize_dims=RESIZE_DIMS, crop_size=CROP_SIZE):
"""Set the data preprocessor instance attributes... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataPreprocessor:
"""Class for creating data preprocessor instances."""
def __init__(self, cam_files, log_files, folder_name, batch_size=B_SIZE, ds_min=None, ds_max=None, shrink_size=None, resize_dims=RESIZE_DIMS, crop_size=CROP_SIZE):
"""Set the data preprocessor instance attributes. :param cam_... | the_stack_v2_python_sparse | comma.ai/data_preprocessor.py | SoftwareImpacts/SIMPAC-2021-129 | train | 0 |
12f84b3e187a5618b10053ae4d2fbcd9c99cd135 | [
"project = get_object_or_404(models.Project, slug=project_slug)\nif request.user.is_authenticated:\n rights = request.user.project_right(project)\nelse:\n rights = get_anonymous_rights(project)\ndata, labels = get_project_fields(project_slug)\nif data:\n if request.is_ajax():\n context = {'project':... | <|body_start_0|>
project = get_object_or_404(models.Project, slug=project_slug)
if request.user.is_authenticated:
rights = request.user.project_right(project)
else:
rights = get_anonymous_rights(project)
data, labels = get_project_fields(project_slug)
if d... | View to administrate a project | ProjectAdminView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectAdminView:
"""View to administrate a project"""
def get(self, request, project_slug):
"""Get the detail of project fields and edit it"""
<|body_0|>
def post(self, request, project_slug):
"""View to save modification done to a project"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_001517 | 24,105 | no_license | [
{
"docstring": "Get the detail of project fields and edit it",
"name": "get",
"signature": "def get(self, request, project_slug)"
},
{
"docstring": "View to save modification done to a project",
"name": "post",
"signature": "def post(self, request, project_slug)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001044 | Implement the Python class `ProjectAdminView` described below.
Class description:
View to administrate a project
Method signatures and docstrings:
- def get(self, request, project_slug): Get the detail of project fields and edit it
- def post(self, request, project_slug): View to save modification done to a project | Implement the Python class `ProjectAdminView` described below.
Class description:
View to administrate a project
Method signatures and docstrings:
- def get(self, request, project_slug): Get the detail of project fields and edit it
- def post(self, request, project_slug): View to save modification done to a project
... | 0ffdec153648561554cfe7664da4912feb2adc88 | <|skeleton|>
class ProjectAdminView:
"""View to administrate a project"""
def get(self, request, project_slug):
"""Get the detail of project fields and edit it"""
<|body_0|>
def post(self, request, project_slug):
"""View to save modification done to a project"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectAdminView:
"""View to administrate a project"""
def get(self, request, project_slug):
"""Get the detail of project fields and edit it"""
project = get_object_or_404(models.Project, slug=project_slug)
if request.user.is_authenticated:
rights = request.user.projec... | the_stack_v2_python_sparse | collab/views/views.py | maxreinhart/collab | train | 0 |
2bc64af81aca855540ffd89a0cbec8f5befad1db | [
"self.w, self.n = (w, len(w))\nfor i in range(1, self.n):\n self.w[i] += self.w[i - 1]",
"i, j, r = (0, self.n - 1, random.randint(1, self.w[-1]))\nwhile i <= j:\n m = (i + j) // 2\n if r == self.w[m]:\n return m\n elif r < self.w[m]:\n j = m - 1\n else:\n i = m + 1\nreturn i"
... | <|body_start_0|>
self.w, self.n = (w, len(w))
for i in range(1, self.n):
self.w[i] += self.w[i - 1]
<|end_body_0|>
<|body_start_1|>
i, j, r = (0, self.n - 1, random.randint(1, self.w[-1]))
while i <= j:
m = (i + j) // 2
if r == self.w[m]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.w, self.n = (w, len(w))
for i in range(1, self.n):
self.w[i] += self.w[... | stack_v2_sparse_classes_36k_train_001518 | 695 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010914 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | 12f62a218e827e6be2578b206dee9ce256da8d3d | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.w, self.n = (w, len(w))
for i in range(1, self.n):
self.w[i] += self.w[i - 1]
def pickIndex(self):
""":rtype: int"""
i, j, r = (0, self.n - 1, random.randint(1, self.w[-1]))
while i ... | the_stack_v2_python_sparse | Python3/0528_Random_Pick_With_Weight.py | kiranani/playground | train | 0 | |
178d7d8221ac670b1c450b8bde4f7a65b20a414d | [
"self.schemas = dict()\nfor url in schema_urls:\n name = url.split('/')[-1]\n self.schemas[name] = {'$ref': url, 'id': url}\nself.resolver = self.resolver_factory()\nself._json_gen = JsonGenerator(resolver=self.resolver)",
"if name is None:\n name = random.choice(list(self.schemas.keys()))\n schema = ... | <|body_start_0|>
self.schemas = dict()
for url in schema_urls:
name = url.split('/')[-1]
self.schemas[name] = {'$ref': url, 'id': url}
self.resolver = self.resolver_factory()
self._json_gen = JsonGenerator(resolver=self.resolver)
<|end_body_0|>
<|body_start_1|>
... | Used to generate random JSON from a from a list of URLs containing JSON schemas. | HCAJsonGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HCAJsonGenerator:
"""Used to generate random JSON from a from a list of URLs containing JSON schemas."""
def __init__(self, schema_urls):
""":param schema_urls: a list of JSON schema URLs."""
<|body_0|>
def generate(self, name: str=None) -> str:
"""Chooses a rand... | stack_v2_sparse_classes_36k_train_001519 | 2,792 | permissive | [
{
"docstring": ":param schema_urls: a list of JSON schema URLs.",
"name": "__init__",
"signature": "def __init__(self, schema_urls)"
},
{
"docstring": "Chooses a random JSON schema from self.schemas and generates JSON data. :param name: the name of a JSON schema to generate. If None, then a rand... | 4 | stack_v2_sparse_classes_30k_train_001046 | Implement the Python class `HCAJsonGenerator` described below.
Class description:
Used to generate random JSON from a from a list of URLs containing JSON schemas.
Method signatures and docstrings:
- def __init__(self, schema_urls): :param schema_urls: a list of JSON schema URLs.
- def generate(self, name: str=None) -... | Implement the Python class `HCAJsonGenerator` described below.
Class description:
Used to generate random JSON from a from a list of URLs containing JSON schemas.
Method signatures and docstrings:
- def __init__(self, schema_urls): :param schema_urls: a list of JSON schema URLs.
- def generate(self, name: str=None) -... | 3722323d4eed3089d25f6d6c9cbfb1672b7de939 | <|skeleton|>
class HCAJsonGenerator:
"""Used to generate random JSON from a from a list of URLs containing JSON schemas."""
def __init__(self, schema_urls):
""":param schema_urls: a list of JSON schema URLs."""
<|body_0|>
def generate(self, name: str=None) -> str:
"""Chooses a rand... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HCAJsonGenerator:
"""Used to generate random JSON from a from a list of URLs containing JSON schemas."""
def __init__(self, schema_urls):
""":param schema_urls: a list of JSON schema URLs."""
self.schemas = dict()
for url in schema_urls:
name = url.split('/')[-1]
... | the_stack_v2_python_sparse | attic/hca_generator.py | DataBiosphere/azul | train | 23 |
f2d8891caa9d8249ed8731d8babe9002366edba6 | [
"these_latitudes_deg, these_longitudes_deg = misc.create_latlng_grid(min_latitude_deg=MIN_GRID_LATITUDE_DEG, max_latitude_deg=MAX_GRID_LATITUDE_DEG, latitude_spacing_deg=LATITUDE_SPACING_DEG, min_longitude_deg=MIN_GRID_LONGITUDE_DEG, max_longitude_deg=MAX_GRID_LONGITUDE_DEG, longitude_spacing_deg=LONGITUDE_SPACING_... | <|body_start_0|>
these_latitudes_deg, these_longitudes_deg = misc.create_latlng_grid(min_latitude_deg=MIN_GRID_LATITUDE_DEG, max_latitude_deg=MAX_GRID_LATITUDE_DEG, latitude_spacing_deg=LATITUDE_SPACING_DEG, min_longitude_deg=MIN_GRID_LONGITUDE_DEG, max_longitude_deg=MAX_GRID_LONGITUDE_DEG, longitude_spacing_de... | Each method is a unit test for misc.py. | MiscTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MiscTests:
"""Each method is a unit test for misc.py."""
def test_create_latlng_grid(self):
"""Ensures correct output from create_latlng_grid."""
<|body_0|>
def test_find_best_and_worst_predictions(self):
"""Ensures correct output from find_best_and_worst_predict... | stack_v2_sparse_classes_36k_train_001520 | 2,969 | no_license | [
{
"docstring": "Ensures correct output from create_latlng_grid.",
"name": "test_create_latlng_grid",
"signature": "def test_create_latlng_grid(self)"
},
{
"docstring": "Ensures correct output from find_best_and_worst_predictions.",
"name": "test_find_best_and_worst_predictions",
"signatu... | 2 | stack_v2_sparse_classes_30k_train_017452 | Implement the Python class `MiscTests` described below.
Class description:
Each method is a unit test for misc.py.
Method signatures and docstrings:
- def test_create_latlng_grid(self): Ensures correct output from create_latlng_grid.
- def test_find_best_and_worst_predictions(self): Ensures correct output from find_b... | Implement the Python class `MiscTests` described below.
Class description:
Each method is a unit test for misc.py.
Method signatures and docstrings:
- def test_create_latlng_grid(self): Ensures correct output from create_latlng_grid.
- def test_find_best_and_worst_predictions(self): Ensures correct output from find_b... | 517d7cb2008a0ff06014c81e158c13bf8e17590a | <|skeleton|>
class MiscTests:
"""Each method is a unit test for misc.py."""
def test_create_latlng_grid(self):
"""Ensures correct output from create_latlng_grid."""
<|body_0|>
def test_find_best_and_worst_predictions(self):
"""Ensures correct output from find_best_and_worst_predict... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MiscTests:
"""Each method is a unit test for misc.py."""
def test_create_latlng_grid(self):
"""Ensures correct output from create_latlng_grid."""
these_latitudes_deg, these_longitudes_deg = misc.create_latlng_grid(min_latitude_deg=MIN_GRID_LATITUDE_DEG, max_latitude_deg=MAX_GRID_LATITUDE_... | the_stack_v2_python_sparse | ml4rt/utils/misc_test.py | thunderhoser/ml4rt | train | 4 |
30d2b0b1cf973edc2df016f7856a4ad03f37f3f4 | [
"parent = request.GET.get('parent', '')\nddlDmlType = request.GET.get('type', '')\nfilterInputValue = request.GET.get('filterInputValue', '')\nversion = request.GET.get('version', '')\ndic = {'parent': parent, 'ddlDmlType': ddlDmlType}\nobj = SqlCaseManage.objects.filter(**dic)\nif version:\n obj = obj.filter(ve... | <|body_start_0|>
parent = request.GET.get('parent', '')
ddlDmlType = request.GET.get('type', '')
filterInputValue = request.GET.get('filterInputValue', '')
version = request.GET.get('version', '')
dic = {'parent': parent, 'ddlDmlType': ddlDmlType}
obj = SqlCaseManage.obje... | SqlCaseManageList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑SQL测试用例"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建SQL测试用例 级联更新结构表ddl/dml的数量"""
<|body_... | stack_v2_sparse_classes_36k_train_001521 | 14,029 | no_license | [
{
"docstring": "SQL测试用例列表",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "编辑SQL测试用例",
"name": "put",
"signature": "def put(self, request, *args, **kwargs)"
},
{
"docstring": "创建SQL测试用例 级联更新结构表ddl/dml的数量",
"name": "post",
"signatu... | 4 | stack_v2_sparse_classes_30k_train_014142 | Implement the Python class `SqlCaseManageList` described below.
Class description:
Implement the SqlCaseManageList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): SQL测试用例列表
- def put(self, request, *args, **kwargs): 编辑SQL测试用例
- def post(self, request, *args, **kwargs): 创建SQL测试用例 级联... | Implement the Python class `SqlCaseManageList` described below.
Class description:
Implement the SqlCaseManageList class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): SQL测试用例列表
- def put(self, request, *args, **kwargs): 编辑SQL测试用例
- def post(self, request, *args, **kwargs): 创建SQL测试用例 级联... | f2523d6e51cde1b53ac6f453f8066b4b90c523b9 | <|skeleton|>
class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
<|body_0|>
def put(self, request, *args, **kwargs):
"""编辑SQL测试用例"""
<|body_1|>
def post(self, request, *args, **kwargs):
"""创建SQL测试用例 级联更新结构表ddl/dml的数量"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SqlCaseManageList:
def get(self, request, *args, **kwargs):
"""SQL测试用例列表"""
parent = request.GET.get('parent', '')
ddlDmlType = request.GET.get('type', '')
filterInputValue = request.GET.get('filterInputValue', '')
version = request.GET.get('version', '')
dic = ... | the_stack_v2_python_sparse | api/db/rest/sqlCaseManage.py | zhuzhanhao1/backend | train | 0 | |
7ada38ce3f9e547a2bbc91c707b9c16f68211b33 | [
"expectation = {'include': 'the good stuff'}\nresponse = Response(dummy_response())\ninstance = response[0]\nser = ReadOnlyElasticSerializer(instance)\nser.Meta.exclude = ['exclude']\nself.assertEqual(ser.data, expectation)",
"expectation = {'include': 'the good stuff', 'exclude': 'the bad stuff'}\nresponse = Res... | <|body_start_0|>
expectation = {'include': 'the good stuff'}
response = Response(dummy_response())
instance = response[0]
ser = ReadOnlyElasticSerializer(instance)
ser.Meta.exclude = ['exclude']
self.assertEqual(ser.data, expectation)
<|end_body_0|>
<|body_start_1|>
... | Serializer tests. | SerializerTests | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SerializerTests:
"""Serializer tests."""
def test_exclusion(self):
"""Test excluding key from serialized data"""
<|body_0|>
def test_nonexistent_exclusion(self):
"""Test proper handling of nonexistent key in exclusion list"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_36k_train_001522 | 12,045 | permissive | [
{
"docstring": "Test excluding key from serialized data",
"name": "test_exclusion",
"signature": "def test_exclusion(self)"
},
{
"docstring": "Test proper handling of nonexistent key in exclusion list",
"name": "test_nonexistent_exclusion",
"signature": "def test_nonexistent_exclusion(se... | 2 | stack_v2_sparse_classes_30k_train_021584 | Implement the Python class `SerializerTests` described below.
Class description:
Serializer tests.
Method signatures and docstrings:
- def test_exclusion(self): Test excluding key from serialized data
- def test_nonexistent_exclusion(self): Test proper handling of nonexistent key in exclusion list | Implement the Python class `SerializerTests` described below.
Class description:
Serializer tests.
Method signatures and docstrings:
- def test_exclusion(self): Test excluding key from serialized data
- def test_nonexistent_exclusion(self): Test proper handling of nonexistent key in exclusion list
<|skeleton|>
class... | 73d334a9f0df7c044c06989977a9a22dd2ff9b7a | <|skeleton|>
class SerializerTests:
"""Serializer tests."""
def test_exclusion(self):
"""Test excluding key from serialized data"""
<|body_0|>
def test_nonexistent_exclusion(self):
"""Test proper handling of nonexistent key in exclusion list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SerializerTests:
"""Serializer tests."""
def test_exclusion(self):
"""Test excluding key from serialized data"""
expectation = {'include': 'the good stuff'}
response = Response(dummy_response())
instance = response[0]
ser = ReadOnlyElasticSerializer(instance)
... | the_stack_v2_python_sparse | goldstone/drfes/tests.py | bhuvan-rk/goldstone-server | train | 0 |
5dcfad80b251d5db829b09203f88af2dd6a0f94a | [
"if not head or not head.next:\n return head\ncurr = head\nsize = 1\nwhile curr.next is not None:\n curr = curr.next\n size = size + 1\ncurr.next = head\nfor i in range(size - k % size):\n curr = curr.next\nnew_head = curr.next\ncurr.next = None\nreturn new_head",
"if head == None:\n return None\np... | <|body_start_0|>
if not head or not head.next:
return head
curr = head
size = 1
while curr.next is not None:
curr = curr.next
size = size + 1
curr.next = head
for i in range(size - k % size):
curr = curr.next
new_hea... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotateRight2(self, head, k):
""":type head: ListNode :type k: int :rtype: ListNode"""
<|body_0|>
def rotateRight(self, head, k):
""":type head: ListNode :type k: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n... | stack_v2_sparse_classes_36k_train_001523 | 1,635 | no_license | [
{
"docstring": ":type head: ListNode :type k: int :rtype: ListNode",
"name": "rotateRight2",
"signature": "def rotateRight2(self, head, k)"
},
{
"docstring": ":type head: ListNode :type k: int :rtype: ListNode",
"name": "rotateRight",
"signature": "def rotateRight(self, head, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotateRight2(self, head, k): :type head: ListNode :type k: int :rtype: ListNode
- def rotateRight(self, head, k): :type head: ListNode :type k: int :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotateRight2(self, head, k): :type head: ListNode :type k: int :rtype: ListNode
- def rotateRight(self, head, k): :type head: ListNode :type k: int :rtype: ListNode
<|skelet... | ab49373ff3fc306a03a90de02e1801b8cbe520d7 | <|skeleton|>
class Solution:
def rotateRight2(self, head, k):
""":type head: ListNode :type k: int :rtype: ListNode"""
<|body_0|>
def rotateRight(self, head, k):
""":type head: ListNode :type k: int :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotateRight2(self, head, k):
""":type head: ListNode :type k: int :rtype: ListNode"""
if not head or not head.next:
return head
curr = head
size = 1
while curr.next is not None:
curr = curr.next
size = size + 1
c... | the_stack_v2_python_sparse | finished/061.py | yiguid/LeetCodePractise | train | 0 | |
eac421170874c5e50e6aee8b4c18ff0a6cdda4c1 | [
"if not language in ACCEPTED_LANGUAGES:\n raise ValueError(f'Language {language} is not supported yet')\nself._language = language\nself._matcher = Matcher(nlp.vocab)\nif language == 'es':\n self._pattern = [{'POS': 'ADV', 'LOWER': {'IN': ['no', 'nunca', 'jamás', 'tampoco']}}]\nelse:\n pass\nself._matcher.... | <|body_start_0|>
if not language in ACCEPTED_LANGUAGES:
raise ValueError(f'Language {language} is not supported yet')
self._language = language
self._matcher = Matcher(nlp.vocab)
if language == 'es':
self._pattern = [{'POS': 'ADV', 'LOWER': {'IN': ['no', 'nunca', ... | This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component. | NegativeExpressionTagger | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NegativeExpressionTagger:
"""This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component."""
def __init__(self, nlp, language: str='es') -> None:
"""This constructor will initialize the object that tags verb phrases. Parameter... | stack_v2_sparse_classes_36k_train_001524 | 2,745 | no_license | [
{
"docstring": "This constructor will initialize the object that tags verb phrases. Parameters: nlp: The Spacy model to use this tagger with. language: The language that this pipeline will be used in. Returns: None.",
"name": "__init__",
"signature": "def __init__(self, nlp, language: str='es') -> None"... | 2 | stack_v2_sparse_classes_30k_train_017798 | Implement the Python class `NegativeExpressionTagger` described below.
Class description:
This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component.
Method signatures and docstrings:
- def __init__(self, nlp, language: str='es') -> None: This constructor wil... | Implement the Python class `NegativeExpressionTagger` described below.
Class description:
This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component.
Method signatures and docstrings:
- def __init__(self, nlp, language: str='es') -> None: This constructor wil... | f23342fbf2cb54a89cd381813ad9eee754b61094 | <|skeleton|>
class NegativeExpressionTagger:
"""This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component."""
def __init__(self, nlp, language: str='es') -> None:
"""This constructor will initialize the object that tags verb phrases. Parameter... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NegativeExpressionTagger:
"""This tagger has the task to find all verb phrases in a document. It needs to go after the 'Parser' pipeline component."""
def __init__(self, nlp, language: str='es') -> None:
"""This constructor will initialize the object that tags verb phrases. Parameters: nlp: The S... | the_stack_v2_python_sparse | src/processing/pipes/negative_expression_tagger.py | persuaide/Tesis_Chatbot | train | 0 |
3077088e5e3a6ce5ab65a0e1aaa97dc97975f27a | [
"super(TwoLayerNet, self).__init__()\nself.linear1 = torch.nn.Linear(D_in, H)\nself.linear2 = torch.nn.Linear(H, D_out)",
"h_relu = self.linear1(x).clamp(min=0)\ny_pred = self.linear2(h_relu)\nreturn y_pred"
] | <|body_start_0|>
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.linear1(x).clamp(min=0)
y_pred = self.linear2(h_relu)
return y_pred
<|end_body_1|>
| TwoLayerNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s... | stack_v2_sparse_classes_36k_train_001525 | 16,194 | no_license | [
{
"docstring": "在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008210 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。
- def forward(self, x): 在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。 | Implement the Python class `TwoLayerNet` described below.
Class description:
Implement the TwoLayerNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。
- def forward(self, x): 在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。
<|... | 272e0b674f2d8ebdca9eea0a35909d2c420212ae | <|skeleton|>
class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
<|body_0|>
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个输出张量。 我们可以使用构造函数中定义的模块以及张量上的任意的（可微分的）操作。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoLayerNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们实例化了两个nn.Linear模块，并将它们作为成员变量。"""
super(TwoLayerNet, self).__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.linear2 = torch.nn.Linear(H, D_out)
def forward(self, x):
"""在前向传播的函数中，我们接收一个输入的张量，也必须返回一个... | the_stack_v2_python_sparse | PyTorch/quick_start_2/function_try.py | StarkTan/Python | train | 0 | |
f592050eb75fa027c271798a4074784b43ea122c | [
"cluster = self.cluster\ncluster.populate([3]).start()\nnode = cluster.nodelist()[0]\nnode.drain(block_on_log=True)\ntry:\n node.decommission()\n self.assertFalse('Expected nodetool error')\nexcept ToolError as e:\n self.assertEqual('', e.stderr)\n self.assertTrue('Unsupported operation' in e.stdout)",
... | <|body_start_0|>
cluster = self.cluster
cluster.populate([3]).start()
node = cluster.nodelist()[0]
node.drain(block_on_log=True)
try:
node.decommission()
self.assertFalse('Expected nodetool error')
except ToolError as e:
self.assertEqua... | TestNodetool | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestNodetool:
def test_decommission_after_drain_is_invalid(self):
"""@jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and exit with an error code (which we receive as a ToolError exception)."""
<|body_0|>
def t... | stack_v2_sparse_classes_36k_train_001526 | 5,539 | permissive | [
{
"docstring": "@jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and exit with an error code (which we receive as a ToolError exception).",
"name": "test_decommission_after_drain_is_invalid",
"signature": "def test_decommission_after_drain... | 4 | stack_v2_sparse_classes_30k_train_018677 | Implement the Python class `TestNodetool` described below.
Class description:
Implement the TestNodetool class.
Method signatures and docstrings:
- def test_decommission_after_drain_is_invalid(self): @jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and ... | Implement the Python class `TestNodetool` described below.
Class description:
Implement the TestNodetool class.
Method signatures and docstrings:
- def test_decommission_after_drain_is_invalid(self): @jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and ... | 9ab09570b4750d9b801e2246d0fbd6016ee0a8ca | <|skeleton|>
class TestNodetool:
def test_decommission_after_drain_is_invalid(self):
"""@jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and exit with an error code (which we receive as a ToolError exception)."""
<|body_0|>
def t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestNodetool:
def test_decommission_after_drain_is_invalid(self):
"""@jira_ticket CASSANDRA-8741 Running a decommission after a drain should generate an unsupported operation message and exit with an error code (which we receive as a ToolError exception)."""
cluster = self.cluster
clus... | the_stack_v2_python_sparse | nodetool_test.py | DikangGu/cassandra-dtest | train | 1 | |
2361b9a96d30fbe16752a84561bf8799304d433a | [
"self.vocab, self.ids_to_tokens = load_vocab(vocab_file)\nnever_split = ('[UNK]', '[SEP]', '[PAD]', '[CLS]', '[MASK]')\nself.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case, never_split=never_split)\nself.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab)",
"split_tokens = []\nfor token in se... | <|body_start_0|>
self.vocab, self.ids_to_tokens = load_vocab(vocab_file)
never_split = ('[UNK]', '[SEP]', '[PAD]', '[CLS]', '[MASK]')
self.basic_tokenizer = BasicTokenizer(do_lower_case=do_lower_case, never_split=never_split)
self.wordpiece_tokenizer = WordpieceTokenizer(vocab=self.vocab... | BERT用の文章の単語分割クラスを実装 | BertTokenizer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BertTokenizer:
"""BERT用の文章の単語分割クラスを実装"""
def __init__(self, vocab_file, do_lower_case=True):
"""vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか"""
<|body_0|>
def tokenize(self, text):
"""文章を単語に分割する関数"""
<|body_1|>
def convert_tokens_to_ids(sel... | stack_v2_sparse_classes_36k_train_001527 | 30,882 | permissive | [
{
"docstring": "vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか",
"name": "__init__",
"signature": "def __init__(self, vocab_file, do_lower_case=True)"
},
{
"docstring": "文章を単語に分割する関数",
"name": "tokenize",
"signature": "def tokenize(self, text)"
},
{
"docstring": "分割された単語リ... | 4 | stack_v2_sparse_classes_30k_train_009553 | Implement the Python class `BertTokenizer` described below.
Class description:
BERT用の文章の単語分割クラスを実装
Method signatures and docstrings:
- def __init__(self, vocab_file, do_lower_case=True): vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか
- def tokenize(self, text): 文章を単語に分割する関数
- def convert_tokens_to_ids(self, t... | Implement the Python class `BertTokenizer` described below.
Class description:
BERT用の文章の単語分割クラスを実装
Method signatures and docstrings:
- def __init__(self, vocab_file, do_lower_case=True): vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか
- def tokenize(self, text): 文章を単語に分割する関数
- def convert_tokens_to_ids(self, t... | bada8e07bd7503ed6d7a371fafb7a29b52b06d62 | <|skeleton|>
class BertTokenizer:
"""BERT用の文章の単語分割クラスを実装"""
def __init__(self, vocab_file, do_lower_case=True):
"""vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか"""
<|body_0|>
def tokenize(self, text):
"""文章を単語に分割する関数"""
<|body_1|>
def convert_tokens_to_ids(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BertTokenizer:
"""BERT用の文章の単語分割クラスを実装"""
def __init__(self, vocab_file, do_lower_case=True):
"""vocab_file：ボキャブラリーへのパス do_lower_case：前処理で単語を小文字化するかどうか"""
self.vocab, self.ids_to_tokens = load_vocab(vocab_file)
never_split = ('[UNK]', '[SEP]', '[PAD]', '[CLS]', '[MASK]')
se... | the_stack_v2_python_sparse | 8_nlp_sentiment_bert/utils/bert.py | YutaroOgawa/pytorch_advanced | train | 811 |
8e5e4a8b188ac4a760496d3de2b2ad27a7251e13 | [
"qry = ServiceOperationQuery(self, 'approve', None, {'message': message})\nself.context.add_query(qry)\nreturn self",
"qry = ServiceOperationQuery(self, 'decline', None, {'message': message})\nself.context.add_query(qry)\nreturn self"
] | <|body_start_0|>
qry = ServiceOperationQuery(self, 'approve', None, {'message': message})
self.context.add_query(qry)
return self
<|end_body_0|>
<|body_start_1|>
qry = ServiceOperationQuery(self, 'decline', None, {'message': message})
self.context.add_query(qry)
return s... | ScheduleChangeRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduleChangeRequest:
def approve(self, message):
"""Approve an ScheduleChangeRequest object. :param str message: A custom approval message."""
<|body_0|>
def decline(self, message):
""":param str message: A custom approval message."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k_train_001528 | 757 | permissive | [
{
"docstring": "Approve an ScheduleChangeRequest object. :param str message: A custom approval message.",
"name": "approve",
"signature": "def approve(self, message)"
},
{
"docstring": ":param str message: A custom approval message.",
"name": "decline",
"signature": "def decline(self, me... | 2 | null | Implement the Python class `ScheduleChangeRequest` described below.
Class description:
Implement the ScheduleChangeRequest class.
Method signatures and docstrings:
- def approve(self, message): Approve an ScheduleChangeRequest object. :param str message: A custom approval message.
- def decline(self, message): :param... | Implement the Python class `ScheduleChangeRequest` described below.
Class description:
Implement the ScheduleChangeRequest class.
Method signatures and docstrings:
- def approve(self, message): Approve an ScheduleChangeRequest object. :param str message: A custom approval message.
- def decline(self, message): :param... | cbd245d1af8d69e013c469cfc2a9851f51c91417 | <|skeleton|>
class ScheduleChangeRequest:
def approve(self, message):
"""Approve an ScheduleChangeRequest object. :param str message: A custom approval message."""
<|body_0|>
def decline(self, message):
""":param str message: A custom approval message."""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScheduleChangeRequest:
def approve(self, message):
"""Approve an ScheduleChangeRequest object. :param str message: A custom approval message."""
qry = ServiceOperationQuery(self, 'approve', None, {'message': message})
self.context.add_query(qry)
return self
def decline(sel... | the_stack_v2_python_sparse | office365/teams/schedule/change_request.py | vgrem/Office365-REST-Python-Client | train | 1,006 | |
35b766ef72688aab34b36b1bf1154af470e9605c | [
"with dbconnections.pg_connection(must_commit, is_test) as cursor:\n if command_type == CMD_TYPE_TEXT and parameters is not None:\n cursor.execute(command, parameters)\n elif command_type == CMD_TYPE_TEXT and parameters is None:\n cursor.execute(command)\n elif command_type == CMD_TYPE_FUNCTI... | <|body_start_0|>
with dbconnections.pg_connection(must_commit, is_test) as cursor:
if command_type == CMD_TYPE_TEXT and parameters is not None:
cursor.execute(command, parameters)
elif command_type == CMD_TYPE_TEXT and parameters is None:
cursor.execute(co... | Data access layer class for postgresql data base | PgSqlDal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PgSqlDal:
"""Data access layer class for postgresql data base"""
def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False):
"""Execute queries without returns, command_type parameter must be a CMD_TYPE_FUNCTION or CMD_TYPE_TEXT constants"""
... | stack_v2_sparse_classes_36k_train_001529 | 2,014 | no_license | [
{
"docstring": "Execute queries without returns, command_type parameter must be a CMD_TYPE_FUNCTION or CMD_TYPE_TEXT constants",
"name": "execute_no_query",
"signature": "def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False)"
},
{
"docstring": "Execut... | 2 | stack_v2_sparse_classes_30k_train_012669 | Implement the Python class `PgSqlDal` described below.
Class description:
Data access layer class for postgresql data base
Method signatures and docstrings:
- def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False): Execute queries without returns, command_type parameter mus... | Implement the Python class `PgSqlDal` described below.
Class description:
Data access layer class for postgresql data base
Method signatures and docstrings:
- def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False): Execute queries without returns, command_type parameter mus... | 4b4125f762dea863f1df5fe0ef9bf2eddd7b3517 | <|skeleton|>
class PgSqlDal:
"""Data access layer class for postgresql data base"""
def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False):
"""Execute queries without returns, command_type parameter must be a CMD_TYPE_FUNCTION or CMD_TYPE_TEXT constants"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PgSqlDal:
"""Data access layer class for postgresql data base"""
def execute_no_query(cls, command, command_type, parameters=None, must_commit=True, is_test=False):
"""Execute queries without returns, command_type parameter must be a CMD_TYPE_FUNCTION or CMD_TYPE_TEXT constants"""
with db... | the_stack_v2_python_sparse | src/others/dals.py | matheusssilva/PyLoca | train | 0 |
b36fcfe7d6d5350afb995f1862d974729d01e333 | [
"parser.add_argument('appname', help='The sample app name, e.g. \"finance\".')\nparser.add_argument('--instance-id', required=True, type=str, help='The Cloud Spanner instance ID for the sample app.')\nparser.add_argument('--database-id', type=str, help='ID of the new Cloud Spanner database to create for the sample ... | <|body_start_0|>
parser.add_argument('appname', help='The sample app name, e.g. "finance".')
parser.add_argument('--instance-id', required=True, type=str, help='The Cloud Spanner instance ID for the sample app.')
parser.add_argument('--database-id', type=str, help='ID of the new Cloud Spanner da... | Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application. | Init | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args... | stack_v2_sparse_classes_36k_train_001530 | 9,146 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_011371 | Implement the Python class `Init` described below.
Class description:
Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application.
Method signatures and docstrings:
- def Args(parser): Args is call... | Implement the Python class `Init` described below.
Class description:
Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application.
Method signatures and docstrings:
- def Args(parser): Args is call... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Init:
"""Initialize a Cloud Spanner sample app. This command creates a Cloud Spanner database in the given instance for the sample app and loads any initial data required by the application."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An ... | the_stack_v2_python_sparse | lib/surface/spanner/samples/init.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
4e8f5f53432daf01602b07f8c2ee21fe281b051c | [
"for window in window_seq:\n x_window = self.split(window, depth=depth, **kwargs)\n for index, item in enumerate(x_window):\n yield item",
"indexed_window = list((self.Atom(index=index, value=value, state=0) for index, value in enumerate(sequence)))\nindexed_window = self.split_rec(indexed_window, **... | <|body_start_0|>
for window in window_seq:
x_window = self.split(window, depth=depth, **kwargs)
for index, item in enumerate(x_window):
yield item
<|end_body_0|>
<|body_start_1|>
indexed_window = list((self.Atom(index=index, value=value, state=0) for index, value... | Need to be calibrated | NikitinSWFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NikitinSWFilter:
"""Need to be calibrated"""
def aggregate_windows(self, window_seq, depth=0, **kwargs):
""":param window_seq: :param depth: :param kwargs: :return:"""
<|body_0|>
def split(self, sequence, use_first=True, **kwargs):
""":param sequence: :param use_... | stack_v2_sparse_classes_36k_train_001531 | 3,632 | permissive | [
{
"docstring": ":param window_seq: :param depth: :param kwargs: :return:",
"name": "aggregate_windows",
"signature": "def aggregate_windows(self, window_seq, depth=0, **kwargs)"
},
{
"docstring": ":param sequence: :param use_first: :param kwargs: :return:",
"name": "split",
"signature": ... | 3 | null | Implement the Python class `NikitinSWFilter` described below.
Class description:
Need to be calibrated
Method signatures and docstrings:
- def aggregate_windows(self, window_seq, depth=0, **kwargs): :param window_seq: :param depth: :param kwargs: :return:
- def split(self, sequence, use_first=True, **kwargs): :param ... | Implement the Python class `NikitinSWFilter` described below.
Class description:
Need to be calibrated
Method signatures and docstrings:
- def aggregate_windows(self, window_seq, depth=0, **kwargs): :param window_seq: :param depth: :param kwargs: :return:
- def split(self, sequence, use_first=True, **kwargs): :param ... | 617ff45c9c3c96bbd9a975aef15f1b2697282b9c | <|skeleton|>
class NikitinSWFilter:
"""Need to be calibrated"""
def aggregate_windows(self, window_seq, depth=0, **kwargs):
""":param window_seq: :param depth: :param kwargs: :return:"""
<|body_0|>
def split(self, sequence, use_first=True, **kwargs):
""":param sequence: :param use_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NikitinSWFilter:
"""Need to be calibrated"""
def aggregate_windows(self, window_seq, depth=0, **kwargs):
""":param window_seq: :param depth: :param kwargs: :return:"""
for window in window_seq:
x_window = self.split(window, depth=depth, **kwargs)
for index, item in... | the_stack_v2_python_sparse | shot_detector/filters/sliding_window/nikitin_swfilter.py | w495/python-video-shot-detector | train | 20 |
311a746fe3d5b3743c6fa746747ff0b0b40aa907 | [
"self.wifi_mac = wifi_mac\nself.id = id\nself.serial = serial\nself.device_fields = device_fields",
"if dictionary is None:\n return None\ndevice_fields = meraki_sdk.models.device_fields_model.DeviceFieldsModel.from_dictionary(dictionary.get('deviceFields')) if dictionary.get('deviceFields') else None\nwifi_ma... | <|body_start_0|>
self.wifi_mac = wifi_mac
self.id = id
self.serial = serial
self.device_fields = device_fields
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
device_fields = meraki_sdk.models.device_fields_model.DeviceFieldsModel.from_dict... | Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device to be modified. device_fields (DeviceFieldsModel): The new fi... | UpdateNetworkSmDeviceFieldsModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device t... | stack_v2_sparse_classes_36k_train_001532 | 2,396 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkSmDeviceFieldsModel class",
"name": "__init__",
"signature": "def __init__(self, device_fields=None, wifi_mac=None, id=None, serial=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dict... | 2 | stack_v2_sparse_classes_30k_train_006766 | Implement the Python class `UpdateNetworkSmDeviceFieldsModel` described below.
Class description:
Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. seri... | Implement the Python class `UpdateNetworkSmDeviceFieldsModel` described below.
Class description:
Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. seri... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNetworkSmDeviceFieldsModel:
"""Implementation of the 'updateNetworkSmDeviceFields' model. TODO: type model description here. Attributes: wifi_mac (string): The wifiMac of the device to be modified. id (string): The id of the device to be modified. serial (string): The serial of the device to be modified... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_sm_device_fields_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
feb5f0615cf0d98797ac27dff0810508a4297fd7 | [
"for attr in self.to_auto_overload[tensor_type]:\n if attr not in dir(PointerTensor) or attr in self.boolean_comparators:\n new_method = self._get_hooked_pointer_method(attr)\n setattr(PointerTensor, attr, new_method)",
"for attr in self.to_auto_overload[framework_cls]:\n new_method = self._ge... | <|body_start_0|>
for attr in self.to_auto_overload[tensor_type]:
if attr not in dir(PointerTensor) or attr in self.boolean_comparators:
new_method = self._get_hooked_pointer_method(attr)
setattr(PointerTensor, attr, new_method)
<|end_body_0|>
<|body_start_1|>
... | Hook for ALL THE POINTER THINGS that must be overloaded and/or modified | PointerHook | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointerHook:
"""Hook for ALL THE POINTER THINGS that must be overloaded and/or modified"""
def _hook_pointer_tensor_methods(self, tensor_type):
"""Add hooked version of all methods of the tensor_type to the Pointer tensor: instead of performing the native tensor method, it will be se... | stack_v2_sparse_classes_36k_train_001533 | 4,576 | permissive | [
{
"docstring": "Add hooked version of all methods of the tensor_type to the Pointer tensor: instead of performing the native tensor method, it will be sent remotely to the location the pointer is pointing at.",
"name": "_hook_pointer_tensor_methods",
"signature": "def _hook_pointer_tensor_methods(self, ... | 5 | null | Implement the Python class `PointerHook` described below.
Class description:
Hook for ALL THE POINTER THINGS that must be overloaded and/or modified
Method signatures and docstrings:
- def _hook_pointer_tensor_methods(self, tensor_type): Add hooked version of all methods of the tensor_type to the Pointer tensor: inst... | Implement the Python class `PointerHook` described below.
Class description:
Hook for ALL THE POINTER THINGS that must be overloaded and/or modified
Method signatures and docstrings:
- def _hook_pointer_tensor_methods(self, tensor_type): Add hooked version of all methods of the tensor_type to the Pointer tensor: inst... | cc4765bed880ad38a02505834f63df39e0815328 | <|skeleton|>
class PointerHook:
"""Hook for ALL THE POINTER THINGS that must be overloaded and/or modified"""
def _hook_pointer_tensor_methods(self, tensor_type):
"""Add hooked version of all methods of the tensor_type to the Pointer tensor: instead of performing the native tensor method, it will be se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PointerHook:
"""Hook for ALL THE POINTER THINGS that must be overloaded and/or modified"""
def _hook_pointer_tensor_methods(self, tensor_type):
"""Add hooked version of all methods of the tensor_type to the Pointer tensor: instead of performing the native tensor method, it will be sent remotely t... | the_stack_v2_python_sparse | syft/generic/frameworks/hook/pointers.py | tudorcebere/PySyft | train | 2 |
f7ceb9584c3f20fc0339fa3c5894df48f103387f | [
"apply_patch(self.request, save=False, src=self.request.validated['tender_src'])\nif all([i.auctionPeriod and i.auctionPeriod.endDate for i in self.request.validated['tender'].lots if i.status == 'active']):\n configurator = self.request.content_configurator\n add_next_awards(self.request, reverse=configurato... | <|body_start_0|>
apply_patch(self.request, save=False, src=self.request.validated['tender_src'])
if all([i.auctionPeriod and i.auctionPeriod.endDate for i in self.request.validated['tender'].lots if i.status == 'active']):
configurator = self.request.content_configurator
add_next... | Auctions resouce | TenderAuctionResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TenderAuctionResource:
"""Auctions resouce"""
def collection_post(self):
"""Report auction results. Report auction results ----------------------"""
<|body_0|>
def patch(self):
"""Set urls for access to auction for lot."""
<|body_1|>
def post(self):
... | stack_v2_sparse_classes_36k_train_001534 | 3,529 | permissive | [
{
"docstring": "Report auction results. Report auction results ----------------------",
"name": "collection_post",
"signature": "def collection_post(self)"
},
{
"docstring": "Set urls for access to auction for lot.",
"name": "patch",
"signature": "def patch(self)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_008227 | Implement the Python class `TenderAuctionResource` described below.
Class description:
Auctions resouce
Method signatures and docstrings:
- def collection_post(self): Report auction results. Report auction results ----------------------
- def patch(self): Set urls for access to auction for lot.
- def post(self): Repo... | Implement the Python class `TenderAuctionResource` described below.
Class description:
Auctions resouce
Method signatures and docstrings:
- def collection_post(self): Report auction results. Report auction results ----------------------
- def patch(self): Set urls for access to auction for lot.
- def post(self): Repo... | 5afdd3a62a8e562cf77e2d963d88f1a26613d16a | <|skeleton|>
class TenderAuctionResource:
"""Auctions resouce"""
def collection_post(self):
"""Report auction results. Report auction results ----------------------"""
<|body_0|>
def patch(self):
"""Set urls for access to auction for lot."""
<|body_1|>
def post(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TenderAuctionResource:
"""Auctions resouce"""
def collection_post(self):
"""Report auction results. Report auction results ----------------------"""
apply_patch(self.request, save=False, src=self.request.validated['tender_src'])
if all([i.auctionPeriod and i.auctionPeriod.endDate ... | the_stack_v2_python_sparse | src/openprocurement/tender/cfaua/views/auction.py | pontostroy/api | train | 0 |
44597edfb77c5122191b344429c6d006fa72212e | [
"super().__init__(name='CP2K_INPUT', subsections={})\nself.structure = structure\nself.charge = structure.charge\nself.potential_and_basis = potential_and_basis\nself.multiplicity = multiplicity\nself.override_default_params = override_default_params\nself.project_name = project_name\nself.kwargs = kwargs\nfor s in... | <|body_start_0|>
super().__init__(name='CP2K_INPUT', subsections={})
self.structure = structure
self.charge = structure.charge
self.potential_and_basis = potential_and_basis
self.multiplicity = multiplicity
self.override_default_params = override_default_params
se... | The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like "RUN_TYPE" or the overall verbosity. FORCE_EVAL is the largest section usually... | Cp2kInputSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cp2kInputSet:
"""The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like "RUN_TYPE" or the overall verbosity. F... | stack_v2_sparse_classes_36k_train_001535 | 48,942 | permissive | [
{
"docstring": "Args: structure: (Structure or Molecule) pymatgen structure or molecule object used to define the lattice, coordinates, and elements. This structure object cannot contain \"special\" species like the Dummy species, e.g. X, or fractional occupations, e.g. Fe0.2, etc. potential_and_basis: (dict) S... | 4 | stack_v2_sparse_classes_30k_train_004457 | Implement the Python class `Cp2kInputSet` described below.
Class description:
The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like... | Implement the Python class `Cp2kInputSet` described below.
Class description:
The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like... | 6dd3b42f569397fa1a86a16fcfaaa29534abb8ca | <|skeleton|>
class Cp2kInputSet:
"""The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like "RUN_TYPE" or the overall verbosity. F... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cp2kInputSet:
"""The basic representation of a CP2K input set as a collection of "sections" defining the simulation connected to a structure object. At the most basis level, CP2K requires a &GLOBAL section and &FORCE_EVAL section. Global sets parameters like "RUN_TYPE" or the overall verbosity. FORCE_EVAL is ... | the_stack_v2_python_sparse | pymatgen/io/cp2k/sets.py | Zhuoying/pymatgen | train | 2 |
d9807e1f9ca01f971e6ef85b3cffc89ccd0b6ce5 | [
"self.title = None\nself.title_font_size = 10\nself.plots = [PlotData(self)]\nself.columns = columns\nself.rows = rows",
"if self.title is not None:\n plt.title(self.title)\nfor index, cur_plot in enumerate(self.plots):\n plot = figure.add_subplot(self.rows, self.columns, index + 1)\n cur_plot.pyplot_vis... | <|body_start_0|>
self.title = None
self.title_font_size = 10
self.plots = [PlotData(self)]
self.columns = columns
self.rows = rows
<|end_body_0|>
<|body_start_1|>
if self.title is not None:
plt.title(self.title)
for index, cur_plot in enumerate(self.p... | Defines the complete data set of a figure consisting of one or more plots | FigureData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FigureData:
"""Defines the complete data set of a figure consisting of one or more plots"""
def __init__(self, columns=1, rows=1):
"""Initializer :param columns: The number of columns :param rows: The number of rows"""
<|body_0|>
def pyplot_visualize(self, figure):
... | stack_v2_sparse_classes_36k_train_001536 | 2,008 | permissive | [
{
"docstring": "Initializer :param columns: The number of columns :param rows: The number of rows",
"name": "__init__",
"signature": "def __init__(self, columns=1, rows=1)"
},
{
"docstring": "Visualizes the figure :param figure: The pyplot figure",
"name": "pyplot_visualize",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_006018 | Implement the Python class `FigureData` described below.
Class description:
Defines the complete data set of a figure consisting of one or more plots
Method signatures and docstrings:
- def __init__(self, columns=1, rows=1): Initializer :param columns: The number of columns :param rows: The number of rows
- def pyplo... | Implement the Python class `FigureData` described below.
Class description:
Defines the complete data set of a figure consisting of one or more plots
Method signatures and docstrings:
- def __init__(self, columns=1, rows=1): Initializer :param columns: The number of columns :param rows: The number of rows
- def pyplo... | e27b53e8e9eedc48abc99151f3adbb76f0a9b331 | <|skeleton|>
class FigureData:
"""Defines the complete data set of a figure consisting of one or more plots"""
def __init__(self, columns=1, rows=1):
"""Initializer :param columns: The number of columns :param rows: The number of rows"""
<|body_0|>
def pyplot_visualize(self, figure):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FigureData:
"""Defines the complete data set of a figure consisting of one or more plots"""
def __init__(self, columns=1, rows=1):
"""Initializer :param columns: The number of columns :param rows: The number of rows"""
self.title = None
self.title_font_size = 10
self.plots... | the_stack_v2_python_sparse | kaivy/plots/figure_data.py | team-kaivy/kaivy | train | 0 |
8fbe4b7520dbaf572c59d6f73b8f0a4537583b6f | [
"self.V = V\nself.num_param = num_param\nself.step = step\nif init_param.size == 0:\n self.init_param = np.zeros(num_param)\nelse:\n self.init_param = init_param\nself.max_iter = max_iter\nself.tol = tol\nself.report_data = []\nself.quad_conv = True\nself.grad = 0",
"b = FullMatrix(self.num_param, 1)\nif pa... | <|body_start_0|>
self.V = V
self.num_param = num_param
self.step = step
if init_param.size == 0:
self.init_param = np.zeros(num_param)
else:
self.init_param = init_param
self.max_iter = max_iter
self.tol = tol
self.report_data = []
... | An instance is a representation of the Quasi-Newton minimization problem. | QNM | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QNM:
"""An instance is a representation of the Quasi-Newton minimization problem."""
def __init__(self, V, num_param, init_param=np.empty(0), tol=10 ** (-7), step=np.float(10 ** (-7)), max_iter=10 ** 2):
"""V: Objective Function [python function which takes a np.ndarray as an input a... | stack_v2_sparse_classes_36k_train_001537 | 3,785 | no_license | [
{
"docstring": "V: Objective Function [python function which takes a np.ndarray as an input and returns a float] num_param: Number of paramters [int] init_param: Initial guess of parameters [np.ndarray] tol: Tolerance [float] step: Step size for calculating derivatives [np.float64] max_iter: Number of maximum i... | 6 | null | Implement the Python class `QNM` described below.
Class description:
An instance is a representation of the Quasi-Newton minimization problem.
Method signatures and docstrings:
- def __init__(self, V, num_param, init_param=np.empty(0), tol=10 ** (-7), step=np.float(10 ** (-7)), max_iter=10 ** 2): V: Objective Functio... | Implement the Python class `QNM` described below.
Class description:
An instance is a representation of the Quasi-Newton minimization problem.
Method signatures and docstrings:
- def __init__(self, V, num_param, init_param=np.empty(0), tol=10 ** (-7), step=np.float(10 ** (-7)), max_iter=10 ** 2): V: Objective Functio... | 7439f25c7809f4198e452f70ae4269447873f7db | <|skeleton|>
class QNM:
"""An instance is a representation of the Quasi-Newton minimization problem."""
def __init__(self, V, num_param, init_param=np.empty(0), tol=10 ** (-7), step=np.float(10 ** (-7)), max_iter=10 ** 2):
"""V: Objective Function [python function which takes a np.ndarray as an input a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QNM:
"""An instance is a representation of the Quasi-Newton minimization problem."""
def __init__(self, V, num_param, init_param=np.empty(0), tol=10 ** (-7), step=np.float(10 ** (-7)), max_iter=10 ** 2):
"""V: Objective Function [python function which takes a np.ndarray as an input and returns a ... | the_stack_v2_python_sparse | PA3/quasi_newton_min.py | ta275/Scientific-Computing-in-Python | train | 0 |
b751186e072b41eaa4a4d57ebaa6fe20be4b4161 | [
"url = reverse(self.list_url)\nresponse = self.client.get(url)\nself.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)\nself.assertNotIn('results', response.data)\nself.assertIn('detail', response.data)\nself.assertEqual(response.data['detail'], STR_401_MESSAGE)",
"user = self.template_users['staff_... | <|body_start_0|>
url = reverse(self.list_url)
response = self.client.get(url)
self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)
self.assertNotIn('results', response.data)
self.assertIn('detail', response.data)
self.assertEqual(response.data['detail'], S... | BasicReadApiTestCaseRunMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BasicReadApiTestCaseRunMixin:
def test_list_anonymous(self):
"""Anonymous user should NOT be able to list"""
<|body_0|>
def test_list_staff_user(self):
"""Staff user should be able to list EVERY object"""
<|body_1|>
def test_detail_anonymous(self):
... | stack_v2_sparse_classes_36k_train_001538 | 9,174 | permissive | [
{
"docstring": "Anonymous user should NOT be able to list",
"name": "test_list_anonymous",
"signature": "def test_list_anonymous(self)"
},
{
"docstring": "Staff user should be able to list EVERY object",
"name": "test_list_staff_user",
"signature": "def test_list_staff_user(self)"
},
... | 4 | null | Implement the Python class `BasicReadApiTestCaseRunMixin` described below.
Class description:
Implement the BasicReadApiTestCaseRunMixin class.
Method signatures and docstrings:
- def test_list_anonymous(self): Anonymous user should NOT be able to list
- def test_list_staff_user(self): Staff user should be able to li... | Implement the Python class `BasicReadApiTestCaseRunMixin` described below.
Class description:
Implement the BasicReadApiTestCaseRunMixin class.
Method signatures and docstrings:
- def test_list_anonymous(self): Anonymous user should NOT be able to list
- def test_list_staff_user(self): Staff user should be able to li... | 9baa530f2f3405322f74ccc145641148f253341b | <|skeleton|>
class BasicReadApiTestCaseRunMixin:
def test_list_anonymous(self):
"""Anonymous user should NOT be able to list"""
<|body_0|>
def test_list_staff_user(self):
"""Staff user should be able to list EVERY object"""
<|body_1|>
def test_detail_anonymous(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BasicReadApiTestCaseRunMixin:
def test_list_anonymous(self):
"""Anonymous user should NOT be able to list"""
url = reverse(self.list_url)
response = self.client.get(url)
self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED)
self.assertNotIn('results', res... | the_stack_v2_python_sparse | palvelutori/test_mixins.py | City-of-Turku/munpalvelut_backend | train | 0 | |
c2daa60062af0f947ca5adcfb6c793504d0d9f42 | [
"login_page.LoginPage(self.driver).login()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).close_weiChat()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).microshopmanager()\npo = landlord_microshopmanager_page.LandlordMicro... | <|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).microsh... | 房东微店 | TestMicroshopManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMicroshopManager:
"""房东微店"""
def test_edit_weidian(self):
"""编辑微店，更改微店名称和微店介绍"""
<|body_0|>
def test_view_again(self):
"""查看房东说明"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
... | stack_v2_sparse_classes_36k_train_001539 | 1,748 | permissive | [
{
"docstring": "编辑微店，更改微店名称和微店介绍",
"name": "test_edit_weidian",
"signature": "def test_edit_weidian(self)"
},
{
"docstring": "查看房东说明",
"name": "test_view_again",
"signature": "def test_view_again(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017658 | Implement the Python class `TestMicroshopManager` described below.
Class description:
房东微店
Method signatures and docstrings:
- def test_edit_weidian(self): 编辑微店，更改微店名称和微店介绍
- def test_view_again(self): 查看房东说明 | Implement the Python class `TestMicroshopManager` described below.
Class description:
房东微店
Method signatures and docstrings:
- def test_edit_weidian(self): 编辑微店，更改微店名称和微店介绍
- def test_view_again(self): 查看房东说明
<|skeleton|>
class TestMicroshopManager:
"""房东微店"""
def test_edit_weidian(self):
"""编辑微店，更改... | 192c70c49a8e9e072b9d0d0136f02c653c589410 | <|skeleton|>
class TestMicroshopManager:
"""房东微店"""
def test_edit_weidian(self):
"""编辑微店，更改微店名称和微店介绍"""
<|body_0|>
def test_view_again(self):
"""查看房东说明"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMicroshopManager:
"""房东微店"""
def test_edit_weidian(self):
"""编辑微店，更改微店名称和微店介绍"""
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).clos... | the_stack_v2_python_sparse | mayi/test_case/test_landlord_microshopmanager.py | 18701016443/mayi | train | 0 |
ae214b5ea2107f11399ec116af749a09cf22f958 | [
"searchtemplate = SearchTemplate.query.get(searchtemplate_id)\nif not searchtemplate:\n abort(HTTP_STATUS_CODE_NOT_FOUND, 'Search template was not found')\nreturn self.to_json(searchtemplate)",
"searchtemplate = SearchTemplate.query.get(searchtemplate_id)\nif not searchtemplate:\n abort(HTTP_STATUS_CODE_NOT... | <|body_start_0|>
searchtemplate = SearchTemplate.query.get(searchtemplate_id)
if not searchtemplate:
abort(HTTP_STATUS_CODE_NOT_FOUND, 'Search template was not found')
return self.to_json(searchtemplate)
<|end_body_0|>
<|body_start_1|>
searchtemplate = SearchTemplate.query.g... | Resource to get a search template. | SearchTemplateResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchTemplateResource:
"""Resource to get a search template."""
def get(self, searchtemplate_id):
"""Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Search template in JSON (instance of flask.wrappers.Response)"... | stack_v2_sparse_classes_36k_train_001540 | 7,889 | permissive | [
{
"docstring": "Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Search template in JSON (instance of flask.wrappers.Response)",
"name": "get",
"signature": "def get(self, searchtemplate_id)"
},
{
"docstring": "Handles DELETE... | 2 | stack_v2_sparse_classes_30k_train_001660 | Implement the Python class `SearchTemplateResource` described below.
Class description:
Resource to get a search template.
Method signatures and docstrings:
- def get(self, searchtemplate_id): Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Searc... | Implement the Python class `SearchTemplateResource` described below.
Class description:
Resource to get a search template.
Method signatures and docstrings:
- def get(self, searchtemplate_id): Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Searc... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SearchTemplateResource:
"""Resource to get a search template."""
def get(self, searchtemplate_id):
"""Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Search template in JSON (instance of flask.wrappers.Response)"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchTemplateResource:
"""Resource to get a search template."""
def get(self, searchtemplate_id):
"""Handles GET request to the resource. Args: searchtemplate_id: Primary key for a search template database model Returns: Search template in JSON (instance of flask.wrappers.Response)"""
se... | the_stack_v2_python_sparse | timesketch/api/v1/resources/searchtemplate.py | google/timesketch | train | 2,263 |
d3e05bf52fa25a894ec6c6e64cf351197e4d4898 | [
"nums = [str(i) for i in nums]\ncomp = lambda a, b: 1 if a + b > b + a else -1 if a + b < b + a else 0\nnums.sort(key=functools.cmp_to_key(comp), reverse=True)\nif nums and nums[0] == '0':\n return '0'\nreturn ''.join(nums)",
"nums = [str(x) for x in nums]\nlongest = max([len(x) for x in nums], default=0)\narr... | <|body_start_0|>
nums = [str(i) for i in nums]
comp = lambda a, b: 1 if a + b > b + a else -1 if a + b < b + a else 0
nums.sort(key=functools.cmp_to_key(comp), reverse=True)
if nums and nums[0] == '0':
return '0'
return ''.join(nums)
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_0|>
def largestNumber2(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nums = [str(i) for i in nums]
co... | stack_v2_sparse_classes_36k_train_001541 | 1,068 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: str",
"name": "largestNumber",
"signature": "def largestNumber(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: str",
"name": "largestNumber2",
"signature": "def largestNumber2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019073 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestNumber(self, nums): :type nums: List[int] :rtype: str
- def largestNumber2(self, nums): :type nums: List[int] :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestNumber(self, nums): :type nums: List[int] :rtype: str
- def largestNumber2(self, nums): :type nums: List[int] :rtype: str
<|skeleton|>
class Solution:
def larges... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_0|>
def largestNumber2(self, nums):
""":type nums: List[int] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestNumber(self, nums):
""":type nums: List[int] :rtype: str"""
nums = [str(i) for i in nums]
comp = lambda a, b: 1 if a + b > b + a else -1 if a + b < b + a else 0
nums.sort(key=functools.cmp_to_key(comp), reverse=True)
if nums and nums[0] == '0':
... | the_stack_v2_python_sparse | 179. Largest Number/largest.py | Macielyoung/LeetCode | train | 1 | |
206824568a0a155303ffc99e08954bbd0f041f68 | [
"y = np.array(y)\nif len(y.shape) == 2 and y.shape[1] > 1:\n self.classes_ = np.arange(y.shape[1])\nelif len(y.shape) == 2 and y.shape[1] == 1 or len(y.shape) == 1:\n self.classes_ = np.unique(y)\n y = np.searchsorted(self.classes_, y)\nelse:\n raise ValueError('Invalid shape for y: ' + str(y.shape))\ns... | <|body_start_0|>
y = np.array(y)
if len(y.shape) == 2 and y.shape[1] > 1:
self.classes_ = np.arange(y.shape[1])
elif len(y.shape) == 2 and y.shape[1] == 1 or len(y.shape) == 1:
self.classes_ = np.unique(y)
y = np.searchsorted(self.classes_, y)
else:
... | Implementation of the scikit-learn classifier API for Keras. | KerasClassifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KerasClassifier:
"""Implementation of the scikit-learn classifier API for Keras."""
def fit(self, x, y, **kwargs):
"""Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samples, n_features)` Training samples where n_samples in the... | stack_v2_sparse_classes_36k_train_001542 | 12,728 | permissive | [
{
"docstring": "Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samples, n_features)` Training samples where n_samples in the number of samples and n_features is the number of features. y : array-like, shape `(n_samples,)` or `(n_samples, n_outputs)` True... | 4 | stack_v2_sparse_classes_30k_train_002344 | Implement the Python class `KerasClassifier` described below.
Class description:
Implementation of the scikit-learn classifier API for Keras.
Method signatures and docstrings:
- def fit(self, x, y, **kwargs): Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samp... | Implement the Python class `KerasClassifier` described below.
Class description:
Implementation of the scikit-learn classifier API for Keras.
Method signatures and docstrings:
- def fit(self, x, y, **kwargs): Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samp... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class KerasClassifier:
"""Implementation of the scikit-learn classifier API for Keras."""
def fit(self, x, y, **kwargs):
"""Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samples, n_features)` Training samples where n_samples in the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KerasClassifier:
"""Implementation of the scikit-learn classifier API for Keras."""
def fit(self, x, y, **kwargs):
"""Constructs a new model with `build_fn` & fit the model to `(x, y)`. Arguments: x : array-like, shape `(n_samples, n_features)` Training samples where n_samples in the number of sa... | the_stack_v2_python_sparse | Tensorflow_Pandas_Numpy/source3.6/tensorflow/python/keras/_impl/keras/wrappers/scikit_learn.py | ryfeus/lambda-packs | train | 1,283 |
f014d651f639d342e5587e92b3d442a9e8f5047a | [
"response = super(EntryProtectionMixin, self).get(request, *args, **kwargs)\nif self.object.login_required and (not request.user.is_authenticated):\n return self.login()\nif self.object.password and self.object.password != self.request.session.get(self.session_key % self.object.pk):\n return self.password()\n... | <|body_start_0|>
response = super(EntryProtectionMixin, self).get(request, *args, **kwargs)
if self.object.login_required and (not request.user.is_authenticated):
return self.login()
if self.object.password and self.object.password != self.request.session.get(self.session_key % self.... | Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password. | EntryProtectionMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryProtectionMixin:
"""Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password."""
def get(self, request, *args, **kwargs):
"""Do the login and password protection."""
<|body_0|>
def post(self, req... | stack_v2_sparse_classes_36k_train_001543 | 2,280 | permissive | [
{
"docstring": "Do the login and password protection.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Do the login and password protection.",
"name": "post",
"signature": "def post(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017982 | Implement the Python class `EntryProtectionMixin` described below.
Class description:
Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Do the login and password ... | Implement the Python class `EntryProtectionMixin` described below.
Class description:
Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Do the login and password ... | 0f625237c6712156daa1f6d38055ea98b8bc7a1d | <|skeleton|>
class EntryProtectionMixin:
"""Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password."""
def get(self, request, *args, **kwargs):
"""Do the login and password protection."""
<|body_0|>
def post(self, req... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EntryProtectionMixin:
"""Mixin returning a login view if the current entry need authentication and password view if the entry is protected by a password."""
def get(self, request, *args, **kwargs):
"""Do the login and password protection."""
response = super(EntryProtectionMixin, self).ge... | the_stack_v2_python_sparse | zinnia/views/mixins/entry_protection.py | jplehmann/django-blog-zinnia | train | 1 |
6474087094ba9cce14ca77a0deae4e3c985ec8ba | [
"structure_klifs_ids = [structure_klifs_id]\nviewer = cls._from_structure_klifs_ids(structure_klifs_ids, klifs_session)\nreturn viewer",
"if feature_name in self._fingerprint.physicochemical:\n data = fingerprint.physicochemical[feature_name]\n data.index = fingerprint.residue_ids\n data.index = data.ind... | <|body_start_0|>
structure_klifs_ids = [structure_klifs_id]
viewer = cls._from_structure_klifs_ids(structure_klifs_ids, klifs_session)
return viewer
<|end_body_0|>
<|body_start_1|>
if feature_name in self._fingerprint.physicochemical:
data = fingerprint.physicochemical[featu... | View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer | StructureViewer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructureViewer:
"""View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer"""
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Initialize viewer from structure KLIFS ID: Generate fingerprint and fetch stru... | stack_v2_sparse_classes_36k_train_001544 | 2,492 | permissive | [
{
"docstring": "Initialize viewer from structure KLIFS ID: Generate fingerprint and fetch structure in PDB format.",
"name": "from_structure_klifs_id",
"signature": "def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None)"
},
{
"docstring": "Map feature values using color on res... | 2 | stack_v2_sparse_classes_30k_train_006271 | Implement the Python class `StructureViewer` described below.
Class description:
View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer
Method signatures and docstrings:
- def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None): Initialize viewer fro... | Implement the Python class `StructureViewer` described below.
Class description:
View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer
Method signatures and docstrings:
- def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None): Initialize viewer fro... | 8433bb64062ed785503b96b52f39bbdb02f66381 | <|skeleton|>
class StructureViewer:
"""View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer"""
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Initialize viewer from structure KLIFS ID: Generate fingerprint and fetch stru... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StructureViewer:
"""View a structure's fingerprint in 3D. Attributes ---------- Inherited from kissim.viewer.base._BaseViewer"""
def from_structure_klifs_id(cls, structure_klifs_id, klifs_session=None):
"""Initialize viewer from structure KLIFS ID: Generate fingerprint and fetch structure in PDB ... | the_stack_v2_python_sparse | kissim/viewer/structure.py | volkamerlab/kissim | train | 26 |
02e594295d5e51cbe86844b04df342034b05d7e1 | [
"Filter.__init__(self)\nap = KWArgsProcessor(self, kwargs)\nap.add('verbosity', default=0)\nap.add('evalfunc', default=lambda output, target: -Validator.MSE(output, target))\nap.add('wtRatio', default=array([1, 2], float))\nself.network = evolino_network\nself.dataset = dataset\nself.max_fitness = -Infinity",
"nu... | <|body_start_0|>
Filter.__init__(self)
ap = KWArgsProcessor(self, kwargs)
ap.add('verbosity', default=0)
ap.add('evalfunc', default=lambda output, target: -Validator.MSE(output, target))
ap.add('wtRatio', default=array([1, 2], float))
self.network = evolino_network
... | Evaluate all individuals of the Evolino population, and store their fitness value inside the population. | EvolinoEvaluation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvolinoEvaluation:
"""Evaluate all individuals of the Evolino population, and store their fitness value inside the population."""
def __init__(self, evolino_network, dataset, **kwargs):
""":key evolino_network: an instance of NetworkWrapper() :key dataset: The evaluation dataset :key... | stack_v2_sparse_classes_36k_train_001545 | 9,839 | permissive | [
{
"docstring": ":key evolino_network: an instance of NetworkWrapper() :key dataset: The evaluation dataset :key evalfunc: Compares output to target values and returns a scalar, denoting the fitness. Defaults to -mse(output, target). :key wtRatio: Float array of two values denoting the ratio between washout and ... | 3 | stack_v2_sparse_classes_30k_train_013092 | Implement the Python class `EvolinoEvaluation` described below.
Class description:
Evaluate all individuals of the Evolino population, and store their fitness value inside the population.
Method signatures and docstrings:
- def __init__(self, evolino_network, dataset, **kwargs): :key evolino_network: an instance of N... | Implement the Python class `EvolinoEvaluation` described below.
Class description:
Evaluate all individuals of the Evolino population, and store their fitness value inside the population.
Method signatures and docstrings:
- def __init__(self, evolino_network, dataset, **kwargs): :key evolino_network: an instance of N... | 33ead60704d126e58c10d458ddd1e5e5fd17b65d | <|skeleton|>
class EvolinoEvaluation:
"""Evaluate all individuals of the Evolino population, and store their fitness value inside the population."""
def __init__(self, evolino_network, dataset, **kwargs):
""":key evolino_network: an instance of NetworkWrapper() :key dataset: The evaluation dataset :key... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EvolinoEvaluation:
"""Evaluate all individuals of the Evolino population, and store their fitness value inside the population."""
def __init__(self, evolino_network, dataset, **kwargs):
""":key evolino_network: an instance of NetworkWrapper() :key dataset: The evaluation dataset :key evalfunc: Co... | the_stack_v2_python_sparse | pybrain/supervised/evolino/filter.py | pybrain2/pybrain2 | train | 14 |
b934c2c3ec76eb2917f0d7fdb706d993f6fc35c5 | [
"if self.cleaned_data['job2_product'] and self.cleaned_data['job2_qty'] is None:\n raise forms.ValidationError('Enter a quantity.')\nelse:\n return self.cleaned_data['job2_qty']",
"if self.cleaned_data['job3_product'] and self.cleaned_data['job3_qty'] is None:\n raise forms.ValidationError('Enter a quant... | <|body_start_0|>
if self.cleaned_data['job2_product'] and self.cleaned_data['job2_qty'] is None:
raise forms.ValidationError('Enter a quantity.')
else:
return self.cleaned_data['job2_qty']
<|end_body_0|>
<|body_start_1|>
if self.cleaned_data['job3_product'] and self.clea... | Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled in dynamically. | FastOrderForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FastOrderForm:
"""Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled in dynamically."""
def clean_job2_q... | stack_v2_sparse_classes_36k_train_001546 | 7,430 | no_license | [
{
"docstring": "If a product is selected for job 2, we also need a quantity.",
"name": "clean_job2_qty",
"signature": "def clean_job2_qty(self)"
},
{
"docstring": "If a product is selected for job 3, we also need a quantity.",
"name": "clean_job3_qty",
"signature": "def clean_job3_qty(se... | 4 | stack_v2_sparse_classes_30k_train_014438 | Implement the Python class `FastOrderForm` described below.
Class description:
Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled i... | Implement the Python class `FastOrderForm` described below.
Class description:
Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled i... | e0b127868d5d2a0b36adaf4e229771d8b7f9bab2 | <|skeleton|>
class FastOrderForm:
"""Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled in dynamically."""
def clean_job2_q... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FastOrderForm:
"""Form for adding a FastOrder. Data we need to get from user: due_date*, org*, ship_to*, po_number, additional_info,products + quantities (at least one required). All other fields of the Order model are either not relevant, or can by filled in dynamically."""
def clean_job2_qty(self):
... | the_stack_v2_python_sparse | orders/forms.py | MorrisonIO/mimic | train | 1 |
08aee8ec490b4e9910278eb8764bec683d1af6af | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | RoutingServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoutingServiceServicer:
"""Missing associated documentation comment in .proto file."""
def QueryOriginalStation(self, request, context):
"""查询起始工作站"""
<|body_0|>
def QueryNextStation(self, request, context):
"""查询下一个工作站"""
<|body_1|>
def QueryRouting... | stack_v2_sparse_classes_36k_train_001547 | 7,347 | no_license | [
{
"docstring": "查询起始工作站",
"name": "QueryOriginalStation",
"signature": "def QueryOriginalStation(self, request, context)"
},
{
"docstring": "查询下一个工作站",
"name": "QueryNextStation",
"signature": "def QueryNextStation(self, request, context)"
},
{
"docstring": "查询工艺路径",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_010896 | Implement the Python class `RoutingServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def QueryOriginalStation(self, request, context): 查询起始工作站
- def QueryNextStation(self, request, context): 查询下一个工作站
- def QueryRoutingChai... | Implement the Python class `RoutingServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def QueryOriginalStation(self, request, context): 查询起始工作站
- def QueryNextStation(self, request, context): 查询下一个工作站
- def QueryRoutingChai... | 0f6fe31a27de9bcf0697c28574b97555fe36d1e1 | <|skeleton|>
class RoutingServiceServicer:
"""Missing associated documentation comment in .proto file."""
def QueryOriginalStation(self, request, context):
"""查询起始工作站"""
<|body_0|>
def QueryNextStation(self, request, context):
"""查询下一个工作站"""
<|body_1|>
def QueryRouting... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoutingServiceServicer:
"""Missing associated documentation comment in .proto file."""
def QueryOriginalStation(self, request, context):
"""查询起始工作站"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('... | the_stack_v2_python_sparse | lib/grpc/wesrpc/warebasic/routing_pb2_grpc.py | cming091/autotest | train | 0 |
af88b08826fccb2da328d682b689f6f85bd54b71 | [
"self._fixtures_ep = data['_links']['fixtures']['href']\nself._players_ep = data['_links']['players']['href']\nself.id = int(data['_links']['self']['href'].split('/')[-1])\nself.name = data['name']\nself.code = data['code']\nself.short_name = data['shortName']\nself.market_value = data['squadMarketValue']\nself.cre... | <|body_start_0|>
self._fixtures_ep = data['_links']['fixtures']['href']
self._players_ep = data['_links']['players']['href']
self.id = int(data['_links']['self']['href'].split('/')[-1])
self.name = data['name']
self.code = data['code']
self.short_name = data['shortName']
... | Team | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Team:
def __init__(self, data):
"""Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type data: dict"""
<|body_0|>
def get_fixtures(self):
"""Return a list of Fixtur... | stack_v2_sparse_classes_36k_train_001548 | 1,940 | permissive | [
{
"docstring": "Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type data: dict",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Return a list of Fixture object... | 3 | stack_v2_sparse_classes_30k_train_014997 | Implement the Python class `Team` described below.
Class description:
Implement the Team class.
Method signatures and docstrings:
- def __init__(self, data): Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type dat... | Implement the Python class `Team` described below.
Class description:
Implement the Team class.
Method signatures and docstrings:
- def __init__(self, data): Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type dat... | 22ed081720c52ef58ec4d1b9ddeb0bf4542a03b4 | <|skeleton|>
class Team:
def __init__(self, data):
"""Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type data: dict"""
<|body_0|>
def get_fixtures(self):
"""Return a list of Fixtur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Team:
def __init__(self, data):
"""Takes a dict converted from the JSON response by the API and wraps the team data within an object. :param data: The team data from the API's response. :type data: dict"""
self._fixtures_ep = data['_links']['fixtures']['href']
self._players_ep = data['... | the_stack_v2_python_sparse | pyfootball/models/team.py | timorthi/pyfootball | train | 7 | |
c5990096f3b4ed3aabb1da476f06adc2f1488199 | [
"self._imalist = []\nilist = axe_asciidata.open(inlist)\nfor item in ilist[0]:\n if not os.path.isfile(getSIMDATA(item)):\n error_message = '\\nDid not find image: ' + str(getSIMDATA(item)) + ' !!'\n raise aXeSIMError(error_message)\n self._imalist.append(ArtImage(getSIMDATA(item.strip())))",
... | <|body_start_0|>
self._imalist = []
ilist = axe_asciidata.open(inlist)
for item in ilist[0]:
if not os.path.isfile(getSIMDATA(item)):
error_message = '\nDid not find image: ' + str(getSIMDATA(item)) + ' !!'
raise aXeSIMError(error_message)
... | Class for the image list | ArtImaList | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArtImaList:
"""Class for the image list"""
def __init__(self, inlist):
"""Initializer for the class @param inlist: name of list with the fits images @type inlist: string"""
<|body_0|>
def tofits(self, fitsname, indata_copy=0):
"""Converts and stores the spectra i... | stack_v2_sparse_classes_36k_train_001549 | 6,339 | permissive | [
{
"docstring": "Initializer for the class @param inlist: name of list with the fits images @type inlist: string",
"name": "__init__",
"signature": "def __init__(self, inlist)"
},
{
"docstring": "Converts and stores the spectra in a fits file Converts all images stored in the class instance to a ... | 2 | null | Implement the Python class `ArtImaList` described below.
Class description:
Class for the image list
Method signatures and docstrings:
- def __init__(self, inlist): Initializer for the class @param inlist: name of list with the fits images @type inlist: string
- def tofits(self, fitsname, indata_copy=0): Converts and... | Implement the Python class `ArtImaList` described below.
Class description:
Class for the image list
Method signatures and docstrings:
- def __init__(self, inlist): Initializer for the class @param inlist: name of list with the fits images @type inlist: string
- def tofits(self, fitsname, indata_copy=0): Converts and... | 043c173fd5497c18c2b1bfe8bcff65180bca3996 | <|skeleton|>
class ArtImaList:
"""Class for the image list"""
def __init__(self, inlist):
"""Initializer for the class @param inlist: name of list with the fits images @type inlist: string"""
<|body_0|>
def tofits(self, fitsname, indata_copy=0):
"""Converts and stores the spectra i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArtImaList:
"""Class for the image list"""
def __init__(self, inlist):
"""Initializer for the class @param inlist: name of list with the fits images @type inlist: string"""
self._imalist = []
ilist = axe_asciidata.open(inlist)
for item in ilist[0]:
if not os.pa... | the_stack_v2_python_sparse | stsdas/pkg/analysis/slitless/axe/axesrc/templateimages.py | spacetelescope/stsdas_stripped | train | 1 |
c6013f131a6b3e35cb594c75e7cd391dcc7d983f | [
"user = self.get_user(request, username)\ncards = Card.objects.filter(user=user).order_by('order')\nif user == request.user:\n form_action = reverse('flashcards')\nelse:\n form_action = reverse('user_flashcards', args=[user.username])\nform = CardForm()\nreturn render(request, 'flashcards.html', dict(cards=ca... | <|body_start_0|>
user = self.get_user(request, username)
cards = Card.objects.filter(user=user).order_by('order')
if user == request.user:
form_action = reverse('flashcards')
else:
form_action = reverse('user_flashcards', args=[user.username])
form = CardF... | FlashcardsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlashcardsView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def delete(self, request, pk, username=None):
"""Delete the flashcard."""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_001550 | 30,576 | permissive | [
{
"docstring": "Get form.",
"name": "get",
"signature": "def get(self, request, username=None)"
},
{
"docstring": "Form submit.",
"name": "post",
"signature": "def post(self, request, username=None)"
},
{
"docstring": "Delete the flashcard.",
"name": "delete",
"signature"... | 3 | stack_v2_sparse_classes_30k_train_012922 | Implement the Python class `FlashcardsView` described below.
Class description:
Implement the FlashcardsView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def delete(self, request, pk, username=None): Delete the fla... | Implement the Python class `FlashcardsView` described below.
Class description:
Implement the FlashcardsView class.
Method signatures and docstrings:
- def get(self, request, username=None): Get form.
- def post(self, request, username=None): Form submit.
- def delete(self, request, pk, username=None): Delete the fla... | 51a2ae2b29ae5c91a3cf7171f89edf225cc8a6f0 | <|skeleton|>
class FlashcardsView:
def get(self, request, username=None):
"""Get form."""
<|body_0|>
def post(self, request, username=None):
"""Form submit."""
<|body_1|>
def delete(self, request, pk, username=None):
"""Delete the flashcard."""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlashcardsView:
def get(self, request, username=None):
"""Get form."""
user = self.get_user(request, username)
cards = Card.objects.filter(user=user).order_by('order')
if user == request.user:
form_action = reverse('flashcards')
else:
form_action... | the_stack_v2_python_sparse | tool/views/views.py | mikekeda/tools | train | 0 | |
0129f130766d0561669caf1ee58401c880103583 | [
"fields = (Subject.name, Term.type, Term.id, Term.day, Term.time_from, Term.time_to, TermSignup.points, TermSignup.reason, TermSignup.reason_accepted, TermSignup.is_assigned)\nres = db.session.query(*fields).join(Term).join(TermGroup).outerjoin(TermSignup).filter(TermGroup.group_id.in_([i.id for i in g.user.groups]... | <|body_start_0|>
fields = (Subject.name, Term.type, Term.id, Term.day, Term.time_from, Term.time_to, TermSignup.points, TermSignup.reason, TermSignup.reason_accepted, TermSignup.is_assigned)
res = db.session.query(*fields).join(Term).join(TermGroup).outerjoin(TermSignup).filter(TermGroup.group_id.in_([i... | TermSignupAction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TermSignupAction:
def get(self):
"""Returns json in form: { 'subject_terms': [ { "subject_name": "math", "terms_aggregated": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ] }"""
<|body_0|>
def post(self):
"""Expects JSON of form: { 'terms_signup': [ { 'te... | stack_v2_sparse_classes_36k_train_001551 | 8,557 | no_license | [
{
"docstring": "Returns json in form: { 'subject_terms': [ { \"subject_name\": \"math\", \"terms_aggregated\": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ] }",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Expects JSON of form: { 'terms_signup': [ { 'term_id': 1, ... | 2 | stack_v2_sparse_classes_30k_train_008651 | Implement the Python class `TermSignupAction` described below.
Class description:
Implement the TermSignupAction class.
Method signatures and docstrings:
- def get(self): Returns json in form: { 'subject_terms': [ { "subject_name": "math", "terms_aggregated": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ... | Implement the Python class `TermSignupAction` described below.
Class description:
Implement the TermSignupAction class.
Method signatures and docstrings:
- def get(self): Returns json in form: { 'subject_terms': [ { "subject_name": "math", "terms_aggregated": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ... | 6495d082da54a135606cf8c8e25d2e6a9b789857 | <|skeleton|>
class TermSignupAction:
def get(self):
"""Returns json in form: { 'subject_terms': [ { "subject_name": "math", "terms_aggregated": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ] }"""
<|body_0|>
def post(self):
"""Expects JSON of form: { 'terms_signup': [ { 'te... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TermSignupAction:
def get(self):
"""Returns json in form: { 'subject_terms': [ { "subject_name": "math", "terms_aggregated": [ { 'term_type': 'Exercises', 'terms': [ ... ] } ] }, ... ] }"""
fields = (Subject.name, Term.type, Term.id, Term.day, Term.time_from, Term.time_to, TermSignup.points, T... | the_stack_v2_python_sparse | backend/src/application/views.py | disconnect3d/TermsScheduler | train | 1 | |
c1bce218f52678372c242fa2bdade9fdd4d33d68 | [
"n = len(s)\ndp = [[0] * n for _ in range(n)]\nans = ''\nfor i in range(n):\n for j in range(i, -1, -1):\n if s[i] == s[j] and (i - j <= 2 or dp[i - 1][j + 1] == 1):\n dp[i][j] = 1\n ans = max(ans, s[j:i + 1], key=len)\nreturn ans",
"n = len(s)\nres = ''\n\ndef _helper(s, l, r):\n ... | <|body_start_0|>
n = len(s)
dp = [[0] * n for _ in range(n)]
ans = ''
for i in range(n):
for j in range(i, -1, -1):
if s[i] == s[j] and (i - j <= 2 or dp[i - 1][j + 1] == 1):
dp[i][j] = 1
ans = max(ans, s[j:i + 1], key=l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome_1(self, s: str) -> str:
"""动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i] 为回文子串，即 dp[i-1][j+1]==1 时： dp[i][j]=1"""
<|body_0|>
def longestPalindrome(self, s:... | stack_v2_sparse_classes_36k_train_001552 | 2,295 | no_license | [
{
"docstring": "动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i] 为回文子串，即 dp[i-1][j+1]==1 时： dp[i][j]=1",
"name": "longestPalindrome_1",
"signature": "def longestPalindrome_1(self, s: str) -> str"
},
{
"docstring... | 2 | stack_v2_sparse_classes_30k_val_001023 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome_1(self, s: str) -> str: 动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome_1(self, s: str) -> str: 动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i... | 2b7f4a9fefbfd358f8ff31362d60e2007641ca29 | <|skeleton|>
class Solution:
def longestPalindrome_1(self, s: str) -> str:
"""动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i] 为回文子串，即 dp[i-1][j+1]==1 时： dp[i][j]=1"""
<|body_0|>
def longestPalindrome(self, s:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome_1(self, s: str) -> str:
"""动态规划： 1. dp[i][j] 表示 s[j:i+1] 是否为回文子串 2. 状态转移方程： - i==j: dp[i][j]=1 - i-j==1 且 s[i]==s[j]： dp[i][j]=1 - i-j>1 且 s[i]==s[j] 且 s[j+1:i] 为回文子串，即 dp[i-1][j+1]==1 时： dp[i][j]=1"""
n = len(s)
dp = [[0] * n for _ in range(n)]
... | the_stack_v2_python_sparse | Week_08/G20190343020242/LeetCode_5_0242.py | algorithm005-class01/algorithm005-class01 | train | 27 | |
591d658b9b382c729d725aae725eb8ec846731e2 | [
"super().__init__()\nself._hidden_dim = 20\nself.fc1 = nn.Linear(obs_dim, self._hidden_dim)\nself.fc2 = nn.Linear(self._hidden_dim, dim_latent)\nself.act = nn.ReLU(inplace=True)",
"x = self.act(self.fc1(x))\nx = self.act(self.fc2(x))\nreturn x"
] | <|body_start_0|>
super().__init__()
self._hidden_dim = 20
self.fc1 = nn.Linear(obs_dim, self._hidden_dim)
self.fc2 = nn.Linear(self._hidden_dim, dim_latent)
self.act = nn.ReLU(inplace=True)
<|end_body_0|>
<|body_start_1|>
x = self.act(self.fc1(x))
x = self.act(se... | Multi-Layer Perceptron network | MLP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MLP:
"""Multi-Layer Perceptron network"""
def __init__(self, obs_dim, dim_latent):
"""Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent"""
<|body_0|>
def forward(self, x):
"""forward method"""
<|body_1|... | stack_v2_sparse_classes_36k_train_001553 | 719 | permissive | [
{
"docstring": "Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent",
"name": "__init__",
"signature": "def __init__(self, obs_dim, dim_latent)"
},
{
"docstring": "forward method",
"name": "forward",
"signature": "def forward(self, x)"
... | 2 | stack_v2_sparse_classes_30k_train_009921 | Implement the Python class `MLP` described below.
Class description:
Multi-Layer Perceptron network
Method signatures and docstrings:
- def __init__(self, obs_dim, dim_latent): Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent
- def forward(self, x): forward method | Implement the Python class `MLP` described below.
Class description:
Multi-Layer Perceptron network
Method signatures and docstrings:
- def __init__(self, obs_dim, dim_latent): Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent
- def forward(self, x): forward method... | 3ad344901c3bb59e0bc16bb70202d2cfd538fd77 | <|skeleton|>
class MLP:
"""Multi-Layer Perceptron network"""
def __init__(self, obs_dim, dim_latent):
"""Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent"""
<|body_0|>
def forward(self, x):
"""forward method"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MLP:
"""Multi-Layer Perceptron network"""
def __init__(self, obs_dim, dim_latent):
"""Constructor Args: obs_dim: (int) dimension of observation latent_dim: (int) dimension of output latent"""
super().__init__()
self._hidden_dim = 20
self.fc1 = nn.Linear(obs_dim, self._hidd... | the_stack_v2_python_sparse | baselines/common/networks/mlp.py | baihuaxie/drl-lib | train | 0 |
b1b1bcbe87db7590dd2c458be6efb4c38a3a7667 | [
"super(INCEPTION_V3_FID, self).__init__()\nself.resize_input = resize_input\nself.output_blocks = sorted(output_blocks)\nself.last_needed_block = max(output_blocks)\nassert self.last_needed_block <= 3, 'Last possible output block index is 3'\nself.blocks = nn.ModuleList()\ninception = models.inception_v3()\nmodel_p... | <|body_start_0|>
super(INCEPTION_V3_FID, self).__init__()
self.resize_input = resize_input
self.output_blocks = sorted(output_blocks)
self.last_needed_block = max(output_blocks)
assert self.last_needed_block <= 3, 'Last possible output block index is 3'
self.blocks = nn.M... | Pretrained InceptionV3 network returning feature maps | INCEPTION_V3_FID | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class INCEPTION_V3_FID:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True):
"""Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return features of. Possibl... | stack_v2_sparse_classes_36k_train_001554 | 49,823 | no_license | [
{
"docstring": "Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return features of. Possible values are: - 0: corresponds to output of first max pooling - 1: corresponds to output of second max pooling - 2: corresponds to output which is fed to aux classifier ... | 2 | stack_v2_sparse_classes_30k_train_011141 | Implement the Python class `INCEPTION_V3_FID` described below.
Class description:
Pretrained InceptionV3 network returning feature maps
Method signatures and docstrings:
- def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True): Build pretrained InceptionV3 Parameters ---------- output_blocks : lis... | Implement the Python class `INCEPTION_V3_FID` described below.
Class description:
Pretrained InceptionV3 network returning feature maps
Method signatures and docstrings:
- def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True): Build pretrained InceptionV3 Parameters ---------- output_blocks : lis... | 2862124dca40daebb0aee79c5c36b17b3266a7f6 | <|skeleton|>
class INCEPTION_V3_FID:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True):
"""Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return features of. Possibl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class INCEPTION_V3_FID:
"""Pretrained InceptionV3 network returning feature maps"""
def __init__(self, output_blocks=[DEFAULT_BLOCK_INDEX], resize_input=True):
"""Build pretrained InceptionV3 Parameters ---------- output_blocks : list of int Indices of blocks to return features of. Possible values are:... | the_stack_v2_python_sparse | image_generation/model.py | azadis/Obj-GAN | train | 2 |
cef340a1f51bc3aac9ff6e53654353c6fdc989cc | [
"self._model_updater = ModelUpdater.get_instance()\nself._racer_profiles = racer_profiles\nself._num_of_agents = len(self._racer_profiles)\nself._race_data = race_data\nself._eval_metrics = eval_metrics\nself._run_phase_subject = run_phase_subject\nself._virtual_event_agent_camera_models = virtual_event_agent_camer... | <|body_start_0|>
self._model_updater = ModelUpdater.get_instance()
self._racer_profiles = racer_profiles
self._num_of_agents = len(self._racer_profiles)
self._race_data = race_data
self._eval_metrics = eval_metrics
self._run_phase_subject = run_phase_subject
self.... | VirtualEventGraphManager class | VirtualEventGraphManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VirtualEventGraphManager:
"""VirtualEventGraphManager class"""
def __init__(self, racer_profiles, race_data, eval_metrics, run_phase_subject, virtual_event_agent_camera_models):
"""VirtualEventGraphManager constructor Args: racer_profiles (list): list of racer profile object race_dat... | stack_v2_sparse_classes_36k_train_001555 | 9,816 | permissive | [
{
"docstring": "VirtualEventGraphManager constructor Args: racer_profiles (list): list of racer profile object race_data (VirtualEventRaceData): VirtualEventRaceData class instance eval_metrics (list): list of EvalMetrics class instance run_phase_subject (RunPhaseSubject): RunPhaseSubject class instance virtual... | 5 | null | Implement the Python class `VirtualEventGraphManager` described below.
Class description:
VirtualEventGraphManager class
Method signatures and docstrings:
- def __init__(self, racer_profiles, race_data, eval_metrics, run_phase_subject, virtual_event_agent_camera_models): VirtualEventGraphManager constructor Args: rac... | Implement the Python class `VirtualEventGraphManager` described below.
Class description:
VirtualEventGraphManager class
Method signatures and docstrings:
- def __init__(self, racer_profiles, race_data, eval_metrics, run_phase_subject, virtual_event_agent_camera_models): VirtualEventGraphManager constructor Args: rac... | 2ce50508dd4100eaef7f8729436549a801505705 | <|skeleton|>
class VirtualEventGraphManager:
"""VirtualEventGraphManager class"""
def __init__(self, racer_profiles, race_data, eval_metrics, run_phase_subject, virtual_event_agent_camera_models):
"""VirtualEventGraphManager constructor Args: racer_profiles (list): list of racer profile object race_dat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VirtualEventGraphManager:
"""VirtualEventGraphManager class"""
def __init__(self, racer_profiles, race_data, eval_metrics, run_phase_subject, virtual_event_agent_camera_models):
"""VirtualEventGraphManager constructor Args: racer_profiles (list): list of racer profile object race_data (VirtualEve... | the_stack_v2_python_sparse | bundle/markov/virtual_event/virtual_event_graph_manager.py | aws-deepracer-community/deepracer-simapp | train | 83 |
1f2ac86cd151c5dcf97453c05072a242af38e12b | [
"ticker = pero.LogTicker(base=2, major_count=7)\nticker(start=1.1, end=900.0)\nticks = ticker.major_ticks()\nself.assertEqual(ticks, (2, 4, 8, 16, 32, 64, 128, 256, 512))\nticker(start=1, end=900.0)\nticks = ticker.major_ticks()\nself.assertEqual(ticks, (1, 2, 4, 8, 16, 32, 64, 128, 256, 512))\nticker(start=0.1, en... | <|body_start_0|>
ticker = pero.LogTicker(base=2, major_count=7)
ticker(start=1.1, end=900.0)
ticks = ticker.major_ticks()
self.assertEqual(ticks, (2, 4, 8, 16, 32, 64, 128, 256, 512))
ticker(start=1, end=900.0)
ticks = ticker.major_ticks()
self.assertEqual(ticks, ... | Test case for logarithmic ticker with base 2. | TestCase | [
"LicenseRef-scancode-philippe-de-muyter",
"LicenseRef-scancode-commercial-license",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCase:
"""Test case for logarithmic ticker with base 2."""
def test_major_ticks(self):
"""Tests whether major ticks are generated works correctly."""
<|body_0|>
def test_minor_ticks(self):
"""Tests whether minor ticks are generated correctly."""
<|body... | stack_v2_sparse_classes_36k_train_001556 | 3,579 | permissive | [
{
"docstring": "Tests whether major ticks are generated works correctly.",
"name": "test_major_ticks",
"signature": "def test_major_ticks(self)"
},
{
"docstring": "Tests whether minor ticks are generated correctly.",
"name": "test_minor_ticks",
"signature": "def test_minor_ticks(self)"
... | 3 | null | Implement the Python class `TestCase` described below.
Class description:
Test case for logarithmic ticker with base 2.
Method signatures and docstrings:
- def test_major_ticks(self): Tests whether major ticks are generated works correctly.
- def test_minor_ticks(self): Tests whether minor ticks are generated correct... | Implement the Python class `TestCase` described below.
Class description:
Test case for logarithmic ticker with base 2.
Method signatures and docstrings:
- def test_major_ticks(self): Tests whether major ticks are generated works correctly.
- def test_minor_ticks(self): Tests whether minor ticks are generated correct... | d59b1bc056f3037b7b7ab635b6deb41120612965 | <|skeleton|>
class TestCase:
"""Test case for logarithmic ticker with base 2."""
def test_major_ticks(self):
"""Tests whether major ticks are generated works correctly."""
<|body_0|>
def test_minor_ticks(self):
"""Tests whether minor ticks are generated correctly."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCase:
"""Test case for logarithmic ticker with base 2."""
def test_major_ticks(self):
"""Tests whether major ticks are generated works correctly."""
ticker = pero.LogTicker(base=2, major_count=7)
ticker(start=1.1, end=900.0)
ticks = ticker.major_ticks()
self.as... | the_stack_v2_python_sparse | unittests/tickers/test_log2.py | xxao/pero | train | 31 |
e84bea0b08cf407b80e620c16efdebd4de6ac888 | [
"start = datetime.now()\ncount_users_in_db = User.objects.count()\ngenerator_users = GeneratorUsers(count_models_in_db=count_users_in_db)\ngenerated_users = generator_users.generate()\nUser.objects.bulk_create(generated_users)\nusers = User.objects.filter(employee=None).filter(is_superuser=False)\nGenerator.create_... | <|body_start_0|>
start = datetime.now()
count_users_in_db = User.objects.count()
generator_users = GeneratorUsers(count_models_in_db=count_users_in_db)
generated_users = generator_users.generate()
User.objects.bulk_create(generated_users)
users = User.objects.filter(emplo... | Generator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
def create_random_users():
"""Генерирует случайно сгенерированных пользователей в БД"""
<|body_0|>
def create_employee(users):
"""Создает случайного сотрудника по users в БД"""
<|body_1|>
def create_dependencies_employee():
"""Создает ... | stack_v2_sparse_classes_36k_train_001557 | 4,382 | no_license | [
{
"docstring": "Генерирует случайно сгенерированных пользователей в БД",
"name": "create_random_users",
"signature": "def create_random_users()"
},
{
"docstring": "Создает случайного сотрудника по users в БД",
"name": "create_employee",
"signature": "def create_employee(users)"
},
{
... | 6 | stack_v2_sparse_classes_30k_train_007982 | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def create_random_users(): Генерирует случайно сгенерированных пользователей в БД
- def create_employee(users): Создает случайного сотрудника по users в БД
- def create_depende... | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def create_random_users(): Генерирует случайно сгенерированных пользователей в БД
- def create_employee(users): Создает случайного сотрудника по users в БД
- def create_depende... | f4155105f22cfeec976cf2f18ad2a4df57bcb4a2 | <|skeleton|>
class Generator:
def create_random_users():
"""Генерирует случайно сгенерированных пользователей в БД"""
<|body_0|>
def create_employee(users):
"""Создает случайного сотрудника по users в БД"""
<|body_1|>
def create_dependencies_employee():
"""Создает ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
def create_random_users():
"""Генерирует случайно сгенерированных пользователей в БД"""
start = datetime.now()
count_users_in_db = User.objects.count()
generator_users = GeneratorUsers(count_models_in_db=count_users_in_db)
generated_users = generator_users.ge... | the_stack_v2_python_sparse | staff_tree/apps/staff/generator.py | RedPowDan/staff_tree | train | 0 | |
f2674c59d076454d41b1499abb16c0505beaa9c1 | [
"self.time = time\nself.name = name\nself._text = None\nself._position = None\nself._class_name = None",
"if self._text:\n return Tag(time=self.time, text=self._text, position=self._position, class_name=self._class_name)\nreturn None"
] | <|body_start_0|>
self.time = time
self.name = name
self._text = None
self._position = None
self._class_name = None
<|end_body_0|>
<|body_start_1|>
if self._text:
return Tag(time=self.time, text=self._text, position=self._position, class_name=self._class_name)... | The base class of an event. | EventData | [
"BSD-3-Clause",
"BSD-1-Clause",
"LicenseRef-scancode-bsd-x11",
"LicenseRef-scancode-other-permissive"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventData:
"""The base class of an event."""
def __init__(self, time, name):
"""Initializes an EventData. @param time: A string for event time. @param name: A string for event name."""
<|body_0|>
def GetTag(self):
"""Gets the tag for this event. @returns: A Tag o... | stack_v2_sparse_classes_36k_train_001558 | 17,308 | permissive | [
{
"docstring": "Initializes an EventData. @param time: A string for event time. @param name: A string for event name.",
"name": "__init__",
"signature": "def __init__(self, time, name)"
},
{
"docstring": "Gets the tag for this event. @returns: A Tag object. Returns None if no need to show tag.",... | 2 | stack_v2_sparse_classes_30k_train_017426 | Implement the Python class `EventData` described below.
Class description:
The base class of an event.
Method signatures and docstrings:
- def __init__(self, time, name): Initializes an EventData. @param time: A string for event time. @param name: A string for event name.
- def GetTag(self): Gets the tag for this eve... | Implement the Python class `EventData` described below.
Class description:
The base class of an event.
Method signatures and docstrings:
- def __init__(self, time, name): Initializes an EventData. @param time: A string for event time. @param name: A string for event name.
- def GetTag(self): Gets the tag for this eve... | 2ba7bcea4f9d9715cbb1c4e69271f7b185a0786e | <|skeleton|>
class EventData:
"""The base class of an event."""
def __init__(self, time, name):
"""Initializes an EventData. @param time: A string for event time. @param name: A string for event name."""
<|body_0|>
def GetTag(self):
"""Gets the tag for this event. @returns: A Tag o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventData:
"""The base class of an event."""
def __init__(self, time, name):
"""Initializes an EventData. @param time: A string for event time. @param name: A string for event name."""
self.time = time
self.name = name
self._text = None
self._position = None
... | the_stack_v2_python_sparse | external/adhd/scripts/audio_thread_log_viewer/viewer_c3.py | dongdong331/test | train | 2 |
e2500b794eb346bfb53f078459620f1812e6e165 | [
"last_occurrence = dict()\nfor index, char in enumerate(string):\n last_occurrence[char] = index\npartitions = []\nleft = right = 0\nfor index, char in enumerate(string):\n right = max(right, last_occurrence[char])\n if index == right:\n partitions.append(index - left + 1)\n left = index + 1\... | <|body_start_0|>
last_occurrence = dict()
for index, char in enumerate(string):
last_occurrence[char] = index
partitions = []
left = right = 0
for index, char in enumerate(string):
right = max(right, last_occurrence[char])
if index == right:
... | Labels | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Labels:
def all_partition_labels_(self, string: str) -> List[int]:
"""Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:"""
<|body_0|>
def all_partition_labels(self, string: str) -> List[int]:
"""Approach: Two Pointer... | stack_v2_sparse_classes_36k_train_001559 | 2,301 | no_license | [
{
"docstring": "Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:",
"name": "all_partition_labels_",
"signature": "def all_partition_labels_(self, string: str) -> List[int]"
},
{
"docstring": "Approach: Two Pointers / Greedy Time Complexity: O(N... | 2 | null | Implement the Python class `Labels` described below.
Class description:
Implement the Labels class.
Method signatures and docstrings:
- def all_partition_labels_(self, string: str) -> List[int]: Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:
- def all_partition_la... | Implement the Python class `Labels` described below.
Class description:
Implement the Labels class.
Method signatures and docstrings:
- def all_partition_labels_(self, string: str) -> List[int]: Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:
- def all_partition_la... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class Labels:
def all_partition_labels_(self, string: str) -> List[int]:
"""Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:"""
<|body_0|>
def all_partition_labels(self, string: str) -> List[int]:
"""Approach: Two Pointer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Labels:
def all_partition_labels_(self, string: str) -> List[int]:
"""Approach: Two Pointers / Greedy Time Complexity: O(N) Space Complexity: O(1) :param string: :return:"""
last_occurrence = dict()
for index, char in enumerate(string):
last_occurrence[char] = index
... | the_stack_v2_python_sparse | amazon/greedy_or_two_pointers/partition_labels.py | Shiv2157k/leet_code | train | 1 | |
acb34716021ba2a1b4d79985539ae1771e605516 | [
"super().__init__()\nself.s_dim = obs_dim\nself.a_dim = act_dim\nself._log_std_min = log_std_min\nself._log_std_max = log_std_max\nself.net = tf.keras.Sequential([tf.keras.layers.InputLayer(dtype=tf.float32, input_shape=self.s_dim, name='input')])\nfor i, hidden_size_i in enumerate(hidden_sizes):\n self.net.add(... | <|body_start_0|>
super().__init__()
self.s_dim = obs_dim
self.a_dim = act_dim
self._log_std_min = log_std_min
self._log_std_max = log_std_max
self.net = tf.keras.Sequential([tf.keras.layers.InputLayer(dtype=tf.float32, input_shape=self.s_dim, name='input')])
for i... | The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_sigma (torch.nn.modules.linear.Linear): The output layer which returns the log standard d... | SquashedGaussianActor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SquashedGaussianActor:
"""The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_sigma (torch.nn.modules.linear.Linear): ... | stack_v2_sparse_classes_36k_train_001560 | 4,775 | no_license | [
{
"docstring": "Constructs all the necessary attributes for the Squashed Gaussian Actor object. Args: obs_dim (int): The dimension of the observation space. act_dim (int): The dimension of the action space. hidden_sizes (list): Array containing the sizes of the hidden layers. log_std_min (int, optional): The mi... | 2 | stack_v2_sparse_classes_30k_train_008096 | Implement the Python class `SquashedGaussianActor` described below.
Class description:
The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_s... | Implement the Python class `SquashedGaussianActor` described below.
Class description:
The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_s... | 7828af7b44f54b0d9ed8a7bd11dd0dd4738a3d2e | <|skeleton|>
class SquashedGaussianActor:
"""The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_sigma (torch.nn.modules.linear.Linear): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SquashedGaussianActor:
"""The squashed gaussian actor network. Attributes: net (torch.nn.modules.container.Sequential): The input/hidden layers of the network. mu (torch.nn.modules.linear.Linear): The output layer which returns the mean of the actions. log_sigma (torch.nn.modules.linear.Linear): The output la... | the_stack_v2_python_sparse | sandbox/speed_comparison/timeit_comparison/gaussian_actor_tf2.py | rickstaa/LAC-TF2-TORCH-translation | train | 0 |
0bb3f99bd00d4dd913c9ad807c8ba7313258fcd2 | [
"if picking.state in ('cancel', 'done'):\n return True\nif picking.state in ('draft', 'confirmed', 'assigned'):\n self.validate_picking(cr, uid, [picking.id], context=context)\n return True\nreturn False",
"if picking.state == '2binvoiced':\n invoice_ids = self.action_invoice_create(cr, uid, [picking.... | <|body_start_0|>
if picking.state in ('cancel', 'done'):
return True
if picking.state in ('draft', 'confirmed', 'assigned'):
self.validate_picking(cr, uid, [picking.id], context=context)
return True
return False
<|end_body_0|>
<|body_start_1|>
if pick... | stock_picking | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_picking:
def auto_wkf_validate(self, cr, uid, picking, context=None):
"""Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :param browse_record picking: the picking to validate :return: True if the picking have been confirmed, Fal... | stack_v2_sparse_classes_36k_train_001561 | 15,477 | no_license | [
{
"docstring": "Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :param browse_record picking: the picking to validate :return: True if the picking have been confirmed, False if not",
"name": "auto_wkf_validate",
"signature": "def auto_wkf_validate(se... | 2 | null | Implement the Python class `stock_picking` described below.
Class description:
Implement the stock_picking class.
Method signatures and docstrings:
- def auto_wkf_validate(self, cr, uid, picking, context=None): Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :para... | Implement the Python class `stock_picking` described below.
Class description:
Implement the stock_picking class.
Method signatures and docstrings:
- def auto_wkf_validate(self, cr, uid, picking, context=None): Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :para... | 73c8a29a182460e6a8f7a97bbc15f1847dbdd63e | <|skeleton|>
class stock_picking:
def auto_wkf_validate(self, cr, uid, picking, context=None):
"""Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :param browse_record picking: the picking to validate :return: True if the picking have been confirmed, Fal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stock_picking:
def auto_wkf_validate(self, cr, uid, picking, context=None):
"""Interface method for the automatic worflow. Validate a picking in draft, confirmed or assigned state. :param browse_record picking: the picking to validate :return: True if the picking have been confirmed, False if not"""
... | the_stack_v2_python_sparse | base_sale_multichannels/workflow_job.py | GoContractPro/Odoo-GCP | train | 1 | |
8ea2ac8be3b1468ab9ca5fa52d6240db355dc9be | [
"self.x_angle = random.random() * math.pi\nself.y_angle = random.random() * math.pi\nself.z_angle = random.random() * math.pi\nself.name = f'[X = {self.x_angle}, Y = {self.y_angle}, Z = {self.z_angle}]'",
"Rx(self.x_angle) | qubit\nRy(self.y_angle) | qubit\nRz(self.z_angle) | qubit"
] | <|body_start_0|>
self.x_angle = random.random() * math.pi
self.y_angle = random.random() * math.pi
self.z_angle = random.random() * math.pi
self.name = f'[X = {self.x_angle}, Y = {self.y_angle}, Z = {self.z_angle}]'
<|end_body_0|>
<|body_start_1|>
Rx(self.x_angle) | qubit
... | This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi. | RandomRotationTestState | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomRotationTestState:
"""This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi."""
def __init__(self):
"""Creates a RandomRotationTestState instance."""
<|body_0|>
def prepare_state(self, q... | stack_v2_sparse_classes_36k_train_001562 | 6,176 | permissive | [
{
"docstring": "Creates a RandomRotationTestState instance.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Prepares a qubit in the test state. Parameters: qubit (Qureg): The qubit to prepare in the test state",
"name": "prepare_state",
"signature": "def prepar... | 2 | stack_v2_sparse_classes_30k_train_000773 | Implement the Python class `RandomRotationTestState` described below.
Class description:
This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi.
Method signatures and docstrings:
- def __init__(self): Creates a RandomRotationTestState insta... | Implement the Python class `RandomRotationTestState` described below.
Class description:
This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi.
Method signatures and docstrings:
- def __init__(self): Creates a RandomRotationTestState insta... | 941488f8f8a81a4b7d7fe28414ce14fa478a692a | <|skeleton|>
class RandomRotationTestState:
"""This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi."""
def __init__(self):
"""Creates a RandomRotationTestState instance."""
<|body_0|>
def prepare_state(self, q... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomRotationTestState:
"""This class represents a test case that rotates the qubit around all three axes of the Bloch sphere by random angles between 0 and pi."""
def __init__(self):
"""Creates a RandomRotationTestState instance."""
self.x_angle = random.random() * math.pi
self.... | the_stack_v2_python_sparse | ProjectQ/ProjectQErrorCorrection/ecc_test_implementation.py | taibah/qsfe | train | 0 |
a22529ec7eb4a121cb1ab05979cddee8ba06a557 | [
"super(AdamWeightDecayOptimizer, self).__init__(False, name)\nself.learning_rate = learning_rate\nself.weight_decay_rate = weight_decday_rate\nself.beta_1 = beta_1\nself.beta_2 = beta_2\nself.epsilon = epsilon\nself.exclude_from_weight_decay = exclude_from_weight_decay",
"assignments = []\nfor grad, param in grad... | <|body_start_0|>
super(AdamWeightDecayOptimizer, self).__init__(False, name)
self.learning_rate = learning_rate
self.weight_decay_rate = weight_decday_rate
self.beta_1 = beta_1
self.beta_2 = beta_2
self.epsilon = epsilon
self.exclude_from_weight_decay = exclude_fr... | A basic Adam optimizer that includes "correct" L2 weight decay. | AdamWeightDecayOptimizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWei... | stack_v2_sparse_classes_36k_train_001563 | 5,841 | no_license | [
{
"docstring": "Constructs a AdamWeightDecayOptimizer.",
"name": "__init__",
"signature": "def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer')"
},
{
"docstring": "See base class.",
... | 4 | null | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=Non... | Implement the Python class `AdamWeightDecayOptimizer` described below.
Class description:
A basic Adam optimizer that includes "correct" L2 weight decay.
Method signatures and docstrings:
- def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=Non... | e7997850ec74223b9cea036baf0cced43a4fa909 | <|skeleton|>
class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWei... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AdamWeightDecayOptimizer:
"""A basic Adam optimizer that includes "correct" L2 weight decay."""
def __init__(self, learning_rate, weight_decday_rate=0.0, beta_1=0.0, beta_2=0.999, epsilon=1e-06, exclude_from_weight_decay=None, name='AdamWeightDecayOptimizer'):
"""Constructs a AdamWeightDecayOptim... | the_stack_v2_python_sparse | LangueModel/BERT/optimization.py | colabnlp/nlp_research | train | 0 |
bc4b9f7f09e5b0a782c24562c25b716cd7a4ac4c | [
"ChapmanEnskogLennardJones.build_lennard_jones_parameters(cobj)\nif not hasattr(cobj, 'viscosity_collision_integral_callback'):\n cobj.viscosity_collision_integral_callback = collision_integral_neufeld_callback",
"units = b.params.get_metadata().derived_units\nT = pyunits.convert(T, to_units=pyunits.K)\nsigma ... | <|body_start_0|>
ChapmanEnskogLennardJones.build_lennard_jones_parameters(cobj)
if not hasattr(cobj, 'viscosity_collision_integral_callback'):
cobj.viscosity_collision_integral_callback = collision_integral_neufeld_callback
<|end_body_0|>
<|body_start_1|>
units = b.params.get_metada... | Implementation of pure component dynamic viscosity from Chapman Enskog Theory | visc_d_phase_comp | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class visc_d_phase_comp:
"""Implementation of pure component dynamic viscosity from Chapman Enskog Theory"""
def build_parameters(cobj, p):
"""Build Lennard Jones parameters and add callback for viscosity collision integral"""
<|body_0|>
def return_expression(b, cobj, p, T):
... | stack_v2_sparse_classes_36k_train_001564 | 4,502 | permissive | [
{
"docstring": "Build Lennard Jones parameters and add callback for viscosity collision integral",
"name": "build_parameters",
"signature": "def build_parameters(cobj, p)"
},
{
"docstring": "Return expression for visc_d_phase_comp",
"name": "return_expression",
"signature": "def return_e... | 2 | null | Implement the Python class `visc_d_phase_comp` described below.
Class description:
Implementation of pure component dynamic viscosity from Chapman Enskog Theory
Method signatures and docstrings:
- def build_parameters(cobj, p): Build Lennard Jones parameters and add callback for viscosity collision integral
- def ret... | Implement the Python class `visc_d_phase_comp` described below.
Class description:
Implementation of pure component dynamic viscosity from Chapman Enskog Theory
Method signatures and docstrings:
- def build_parameters(cobj, p): Build Lennard Jones parameters and add callback for viscosity collision integral
- def ret... | deacf4c422bc9e50cb347e11a8cbfa0195bd4274 | <|skeleton|>
class visc_d_phase_comp:
"""Implementation of pure component dynamic viscosity from Chapman Enskog Theory"""
def build_parameters(cobj, p):
"""Build Lennard Jones parameters and add callback for viscosity collision integral"""
<|body_0|>
def return_expression(b, cobj, p, T):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class visc_d_phase_comp:
"""Implementation of pure component dynamic viscosity from Chapman Enskog Theory"""
def build_parameters(cobj, p):
"""Build Lennard Jones parameters and add callback for viscosity collision integral"""
ChapmanEnskogLennardJones.build_lennard_jones_parameters(cobj)
... | the_stack_v2_python_sparse | idaes/models/properties/modular_properties/pure/ChapmanEnskog.py | IDAES/idaes-pse | train | 173 |
5f1f77d04e13021596fb23648679ce89135f94d4 | [
"self._row = row\nself._col = col\nself._graph = [[] for _ in range(row)]\nself._rowMatching = [-1] * row\nself._colMatching = [-1] * col\nself._matchingEdges: Optional[List[Tuple[int, int]]] = None",
"assert 0 <= u < self._row\nassert 0 <= v < self._col\nself._graph[u].append(v)",
"def dfs(cur: int) -> bool:\n... | <|body_start_0|>
self._row = row
self._col = col
self._graph = [[] for _ in range(row)]
self._rowMatching = [-1] * row
self._colMatching = [-1] * col
self._matchingEdges: Optional[List[Tuple[int, int]]] = None
<|end_body_0|>
<|body_start_1|>
assert 0 <= u < self.... | Hungarian | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Hungarian:
def __init__(self, row: int, col: int):
"""匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数"""
<|body_0|>
def addEdge(self, u: int, v: int) -> None:
"""男孩u和女孩v连边"""
<|body_1|>
def work(self) -> int:
"""返回最大匹配的个数"""... | stack_v2_sparse_classes_36k_train_001565 | 3,835 | no_license | [
{
"docstring": "匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数",
"name": "__init__",
"signature": "def __init__(self, row: int, col: int)"
},
{
"docstring": "男孩u和女孩v连边",
"name": "addEdge",
"signature": "def addEdge(self, u: int, v: int) -> None"
},
{
"docst... | 4 | null | Implement the Python class `Hungarian` described below.
Class description:
Implement the Hungarian class.
Method signatures and docstrings:
- def __init__(self, row: int, col: int): 匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数
- def addEdge(self, u: int, v: int) -> None: 男孩u和女孩v连边
- def work(... | Implement the Python class `Hungarian` described below.
Class description:
Implement the Hungarian class.
Method signatures and docstrings:
- def __init__(self, row: int, col: int): 匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数
- def addEdge(self, u: int, v: int) -> None: 男孩u和女孩v连边
- def work(... | 7e79e26bb8f641868561b186e34c1127ed63c9e0 | <|skeleton|>
class Hungarian:
def __init__(self, row: int, col: int):
"""匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数"""
<|body_0|>
def addEdge(self, u: int, v: int) -> None:
"""男孩u和女孩v连边"""
<|body_1|>
def work(self) -> int:
"""返回最大匹配的个数"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Hungarian:
def __init__(self, row: int, col: int):
"""匈牙利算法求无权二分图最大匹配 时间复杂度O(V * E) Args: row (int): 男孩的个数 col (int): 女孩的个数"""
self._row = row
self._col = col
self._graph = [[] for _ in range(row)]
self._rowMatching = [-1] * row
self._colMatching = [-1] * col
... | the_stack_v2_python_sparse | 7_graph/二分图/acwing习题/hungarian.py | 981377660LMT/algorithm-study | train | 225 | |
0f6f3f57c41d38cb9d7ccbe427991bb6b656616b | [
"super(MapBox, self).__init__(format_string=format_string, scheme=scheme, timeout=timeout, proxies=proxies, user_agent=user_agent, ssl_context=ssl_context)\nself.api_key = api_key\nself.domain = domain.strip('/')\nself.api = '%s://%s%s' % (self.scheme, self.domain, self.api_path)",
"features = json['features']\ni... | <|body_start_0|>
super(MapBox, self).__init__(format_string=format_string, scheme=scheme, timeout=timeout, proxies=proxies, user_agent=user_agent, ssl_context=ssl_context)
self.api_key = api_key
self.domain = domain.strip('/')
self.api = '%s://%s%s' % (self.scheme, self.domain, self.api_... | Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0 | MapBox | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapBox:
"""Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0"""
def __init__(self, api_key, format_string=None, scheme=None, timeout=DEFAULT_SENTINEL, proxies=DEFAULT_SENTINEL, user_agent=None, ssl_context=DEFAULT_SENTINEL, do... | stack_v2_sparse_classes_36k_train_001566 | 6,972 | permissive | [
{
"docstring": ":param str api_key: The API key required by Mapbox to perform geocoding requests. API keys are managed through Mapox's account page (https://www.mapbox.com/account/access-tokens). :param str format_string: See :attr:`geopy.geocoders.options.default_format_string`. :param str scheme: See :attr:`g... | 4 | stack_v2_sparse_classes_30k_train_002034 | Implement the Python class `MapBox` described below.
Class description:
Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0
Method signatures and docstrings:
- def __init__(self, api_key, format_string=None, scheme=None, timeout=DEFAULT_SENTINEL, proxies... | Implement the Python class `MapBox` described below.
Class description:
Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0
Method signatures and docstrings:
- def __init__(self, api_key, format_string=None, scheme=None, timeout=DEFAULT_SENTINEL, proxies... | 0c72430da633785fcb14e40d8b007c86081d515d | <|skeleton|>
class MapBox:
"""Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0"""
def __init__(self, api_key, format_string=None, scheme=None, timeout=DEFAULT_SENTINEL, proxies=DEFAULT_SENTINEL, user_agent=None, ssl_context=DEFAULT_SENTINEL, do... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MapBox:
"""Geocoder using the Mapbox API. Documentation at: https://www.mapbox.com/api-documentation/ .. versionadded:: 1.17.0"""
def __init__(self, api_key, format_string=None, scheme=None, timeout=DEFAULT_SENTINEL, proxies=DEFAULT_SENTINEL, user_agent=None, ssl_context=DEFAULT_SENTINEL, domain='api.map... | the_stack_v2_python_sparse | WatchDogs_Visualisation/mainVenv/lib/python3.7/site-packages/geopy/geocoders/mapbox.py | prashanth-thipparthi/WatchDogs_StockMarketAnalysis | train | 4 |
b7c45e3f066cbe69a04cf6d8f39d2f0333fa93c6 | [
"if not points:\n return 0\npoints.sort()\narrows = pop_ptr = overlap_ptr = 0\nwhile overlap_ptr < len(points):\n if points[overlap_ptr][0] > points[pop_ptr][-1]:\n pop_ptr = overlap_ptr\n arrows += 1\n points[pop_ptr][-1] = min(points[pop_ptr][-1], points[overlap_ptr][-1])\n overlap_ptr +... | <|body_start_0|>
if not points:
return 0
points.sort()
arrows = pop_ptr = overlap_ptr = 0
while overlap_ptr < len(points):
if points[overlap_ptr][0] > points[pop_ptr][-1]:
pop_ptr = overlap_ptr
arrows += 1
points[pop_ptr... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMinArrowShots(self, points: List[List[int]]) -> int:
"""------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------"""
<|body_0|>
def findMinArrowShots(self, points: List[List[int]]) -> int:
"""------ --- --------- ------ ---------... | stack_v2_sparse_classes_36k_train_001567 | 1,580 | no_license | [
{
"docstring": "------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------",
"name": "findMinArrowShots",
"signature": "def findMinArrowShots(self, points: List[List[int]]) -> int"
},
{
"docstring": "------ --- --------- ------ ----------- ---",
"name": "findMinArrowShots"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinArrowShots(self, points: List[List[int]]) -> int: ------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------
- def findMinArrowShots(self, points: L... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinArrowShots(self, points: List[List[int]]) -> int: ------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------
- def findMinArrowShots(self, points: L... | 218a8a97e3926788bb6320dda889bd379083570a | <|skeleton|>
class Solution:
def findMinArrowShots(self, points: List[List[int]]) -> int:
"""------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------"""
<|body_0|>
def findMinArrowShots(self, points: List[List[int]]) -> int:
"""------ --- --------- ------ ---------... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMinArrowShots(self, points: List[List[int]]) -> int:
"""------ --- <- make this the new end. ----- ^ | shoot ----- -------- ---------"""
if not points:
return 0
points.sort()
arrows = pop_ptr = overlap_ptr = 0
while overlap_ptr < len(points... | the_stack_v2_python_sparse | src/452.minimum-number-of-arrows-to-burst-balloons.py | tientheshy/leetcode-solutions | train | 0 | |
b5f32f84124af5ab1349b23a8d6ccc05ade5e833 | [
"super().__init__()\nself.out_dim = out_dim\nself.num_heads = num_heads\nself.d_k = out_dim // num_heads\nself.k_linear = k_linear\nself.q_linear = q_linear\nself.v_linear = v_linear\nself.w_att = w_att\nself.w_msg = w_msg\nself.mu = mu",
"with g.local_scope():\n feat_src, feat_dst = expand_as_pair(feat, g)\n ... | <|body_start_0|>
super().__init__()
self.out_dim = out_dim
self.num_heads = num_heads
self.d_k = out_dim // num_heads
self.k_linear = k_linear
self.q_linear = q_linear
self.v_linear = v_linear
self.w_att = w_att
self.w_msg = w_msg
self.mu =... | HGTAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HGTAttention:
def __init__(self, out_dim, num_heads, k_linear, q_linear, v_linear, w_att, w_msg, mu):
"""HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: nn.Linear(d_in, d_out) :param q_linear: nn.Linear(d_in, d_out) :param v_linear: nn.Linear(d_in, d_out... | stack_v2_sparse_classes_36k_train_001568 | 8,548 | no_license | [
{
"docstring": "HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: nn.Linear(d_in, d_out) :param q_linear: nn.Linear(d_in, d_out) :param v_linear: nn.Linear(d_in, d_out) :param w_att: tensor(K, d_out/K, d_out/K) :param w_msg: tensor(K, d_out/K, d_out/K) :param mu: tensor(1)",
... | 2 | stack_v2_sparse_classes_30k_train_009176 | Implement the Python class `HGTAttention` described below.
Class description:
Implement the HGTAttention class.
Method signatures and docstrings:
- def __init__(self, out_dim, num_heads, k_linear, q_linear, v_linear, w_att, w_msg, mu): HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: ... | Implement the Python class `HGTAttention` described below.
Class description:
Implement the HGTAttention class.
Method signatures and docstrings:
- def __init__(self, out_dim, num_heads, k_linear, q_linear, v_linear, w_att, w_msg, mu): HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: ... | b40071dc9f9fb20f081f4ed4944a7b65de919c18 | <|skeleton|>
class HGTAttention:
def __init__(self, out_dim, num_heads, k_linear, q_linear, v_linear, w_att, w_msg, mu):
"""HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: nn.Linear(d_in, d_out) :param q_linear: nn.Linear(d_in, d_out) :param v_linear: nn.Linear(d_in, d_out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HGTAttention:
def __init__(self, out_dim, num_heads, k_linear, q_linear, v_linear, w_att, w_msg, mu):
"""HGT注意力模块 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param k_linear: nn.Linear(d_in, d_out) :param q_linear: nn.Linear(d_in, d_out) :param v_linear: nn.Linear(d_in, d_out) :param w_att... | the_stack_v2_python_sparse | gnn/hgt/model.py | deepdumbo/pytorch-tutorial-1 | train | 0 | |
141859457fa78a8eaab25190c403812050348147 | [
"self._schema = customer_schema\nself.tracing_id = tracing_id\nwith ProviderDBAccessor(provider_uuid) as provider_accessor:\n self._provider = provider_accessor.get_provider()\ntry:\n self._updater = self._set_updater()\nexcept Exception as err:\n raise CostModelCostUpdaterError(err)",
"if self._provider... | <|body_start_0|>
self._schema = customer_schema
self.tracing_id = tracing_id
with ProviderDBAccessor(provider_uuid) as provider_accessor:
self._provider = provider_accessor.get_provider()
try:
self._updater = self._set_updater()
except Exception as err:
... | Update reporting summary tables. | CostModelCostUpdater | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CostModelCostUpdater:
"""Update reporting summary tables."""
def __init__(self, customer_schema, provider_uuid, tracing_id=None):
"""Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str): The provider uuid."""
<|body_0|>
def _set_u... | stack_v2_sparse_classes_36k_train_001569 | 3,840 | permissive | [
{
"docstring": "Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str): The provider uuid.",
"name": "__init__",
"signature": "def __init__(self, customer_schema, provider_uuid, tracing_id=None)"
},
{
"docstring": "Create the report charge updater object. O... | 4 | stack_v2_sparse_classes_30k_train_018196 | Implement the Python class `CostModelCostUpdater` described below.
Class description:
Update reporting summary tables.
Method signatures and docstrings:
- def __init__(self, customer_schema, provider_uuid, tracing_id=None): Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str):... | Implement the Python class `CostModelCostUpdater` described below.
Class description:
Update reporting summary tables.
Method signatures and docstrings:
- def __init__(self, customer_schema, provider_uuid, tracing_id=None): Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str):... | 0416e5216eb1ec4b41c8dd4999adde218b1ab2e1 | <|skeleton|>
class CostModelCostUpdater:
"""Update reporting summary tables."""
def __init__(self, customer_schema, provider_uuid, tracing_id=None):
"""Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str): The provider uuid."""
<|body_0|>
def _set_u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CostModelCostUpdater:
"""Update reporting summary tables."""
def __init__(self, customer_schema, provider_uuid, tracing_id=None):
"""Initializer. Args: customer_schema (str): Schema name for given customer. provider_uuid (str): The provider uuid."""
self._schema = customer_schema
... | the_stack_v2_python_sparse | koku/masu/processor/cost_model_cost_updater.py | project-koku/koku | train | 225 |
7a08fae5d220f1111339dcec9547605ed1f1adac | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn SynchronizationJob()",
"from .entity import Entity\nfrom .key_value_pair import KeyValuePair\nfrom .synchronization_schedule import SynchronizationSchedule\nfrom .synchronization_schema import SynchronizationSchema\nfrom .synchronizati... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return SynchronizationJob()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .key_value_pair import KeyValuePair
from .synchronization_schedule import SynchronizationSche... | SynchronizationJob | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SynchronizationJob:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationJob:
"""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 obje... | stack_v2_sparse_classes_36k_train_001570 | 4,015 | 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: SynchronizationJob",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_... | 3 | stack_v2_sparse_classes_30k_train_012099 | Implement the Python class `SynchronizationJob` described below.
Class description:
Implement the SynchronizationJob class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationJob: Creates a new instance of the appropriate class based on disc... | Implement the Python class `SynchronizationJob` described below.
Class description:
Implement the SynchronizationJob class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationJob: Creates a new instance of the appropriate class based on disc... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class SynchronizationJob:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationJob:
"""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 obje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SynchronizationJob:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> SynchronizationJob:
"""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: Sy... | the_stack_v2_python_sparse | msgraph/generated/models/synchronization_job.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
04334445b42d53e46e4fba9551cc43133686f543 | [
"self.total = sum(w)\nfor i in range(1, len(w)):\n w[i] += w[i - 1]\nself.w = w",
"ind = random.randint(0, self.total - 1)\nl, r = (0, len(self.w))\nwhile l + 1 < r:\n mid = (l + r) / 2\n if ind <= self.w[mid]:\n r = mid\n else:\n l = mid\nif ind <= self.w[l]:\n return l\nreturn r"
] | <|body_start_0|>
self.total = sum(w)
for i in range(1, len(w)):
w[i] += w[i - 1]
self.w = w
<|end_body_0|>
<|body_start_1|>
ind = random.randint(0, self.total - 1)
l, r = (0, len(self.w))
while l + 1 < r:
mid = (l + r) / 2
if ind <= se... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.total = sum(w)
for i in range(1, len(w)):
w[i] += w[i - 1]
self... | stack_v2_sparse_classes_36k_train_001571 | 824 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | bcb79f329bcb133e6421db8fc1f4780a4eedec39 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.total = sum(w)
for i in range(1, len(w)):
w[i] += w[i - 1]
self.w = w
def pickIndex(self):
""":rtype: int"""
ind = random.randint(0, self.total - 1)
l, r = (0, len(self.w))
... | the_stack_v2_python_sparse | 528. Random Pick with Weight.py | havenshi/leetcode | train | 1 | |
296f9e6210a14ad96edd1c6ccba151a89a822c2c | [
"self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)\nn = len(input_array)\nself.n = n\nfor i in range(n):\n self.tree[n + i] = input_array[i]\nfor i in range(n - 1, 0, -1):\n self.tree[i] = self.tree[i << 1] + self.tree[i << 1 | 1]",
"self.tree[index + self.n] = value\nindex = index + self.n\ni = index\nwhile i > ... | <|body_start_0|>
self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)
n = len(input_array)
self.n = n
for i in range(n):
self.tree[n + i] = input_array[i]
for i in range(n - 1, 0, -1):
self.tree[i] = self.tree[i << 1] + self.tree[i << 1 | 1]
<|end_body_0|>
<|body_... | An implementation of Segment Tree | SegmentTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
<|body_0|>
def update(self, index, value):
"""Update Args: index: to update value: new value Re... | stack_v2_sparse_classes_36k_train_001572 | 2,356 | no_license | [
{
"docstring": "init Segment Tree Args: input_array: Input array Returns: None Raises: None",
"name": "__init__",
"signature": "def __init__(self, input_array)"
},
{
"docstring": "Update Args: index: to update value: new value Returns: None Raises: None",
"name": "update",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_018039 | Implement the Python class `SegmentTree` described below.
Class description:
An implementation of Segment Tree
Method signatures and docstrings:
- def __init__(self, input_array): init Segment Tree Args: input_array: Input array Returns: None Raises: None
- def update(self, index, value): Update Args: index: to updat... | Implement the Python class `SegmentTree` described below.
Class description:
An implementation of Segment Tree
Method signatures and docstrings:
- def __init__(self, input_array): init Segment Tree Args: input_array: Input array Returns: None Raises: None
- def update(self, index, value): Update Args: index: to updat... | 11f4d25cb211740514c119a60962d075a0817abd | <|skeleton|>
class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
<|body_0|>
def update(self, index, value):
"""Update Args: index: to update value: new value Re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SegmentTree:
"""An implementation of Segment Tree"""
def __init__(self, input_array):
"""init Segment Tree Args: input_array: Input array Returns: None Raises: None"""
self.tree = [0] * (2 * self.MAX_ARRAY_SIZE)
n = len(input_array)
self.n = n
for i in range(n):
... | the_stack_v2_python_sparse | python/common/segment_tree.py | santhosh-kumar/AlgorithmsAndDataStructures | train | 2 |
258e556cb491348d7507a28684ae8a3eb27fe9bb | [
"identity = get_jwt_identity()\ncand_id = identity['id']\nsubcribe = get_subcribe(cand_id)\nif not subcribe:\n return response_object()\nelse:\n return response_object(200, 'Thành công.', data=subcribe.to_json())",
"identity = get_jwt_identity()\ncand_id = identity['id']\ntopic = request.json['topic']\nprov... | <|body_start_0|>
identity = get_jwt_identity()
cand_id = identity['id']
subcribe = get_subcribe(cand_id)
if not subcribe:
return response_object()
else:
return response_object(200, 'Thành công.', data=subcribe.to_json())
<|end_body_0|>
<|body_start_1|>
... | SubcribeEmail | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubcribeEmail:
def get(self):
"""get list subcribe email"""
<|body_0|>
def post(self):
"""subcribe email: (type= 0 daily, 1: week) (statis= 0: inactive, 1: active)"""
<|body_1|>
def delete(self):
"""Delete subcribe"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k_train_001573 | 3,272 | no_license | [
{
"docstring": "get list subcribe email",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "subcribe email: (type= 0 daily, 1: week) (statis= 0: inactive, 1: active)",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Delete subcribe",
"name": "del... | 3 | stack_v2_sparse_classes_30k_train_004856 | Implement the Python class `SubcribeEmail` described below.
Class description:
Implement the SubcribeEmail class.
Method signatures and docstrings:
- def get(self): get list subcribe email
- def post(self): subcribe email: (type= 0 daily, 1: week) (statis= 0: inactive, 1: active)
- def delete(self): Delete subcribe | Implement the Python class `SubcribeEmail` described below.
Class description:
Implement the SubcribeEmail class.
Method signatures and docstrings:
- def get(self): get list subcribe email
- def post(self): subcribe email: (type= 0 daily, 1: week) (statis= 0: inactive, 1: active)
- def delete(self): Delete subcribe
... | a23e4924b8c66940aa990ef9e19c360a34e5c44e | <|skeleton|>
class SubcribeEmail:
def get(self):
"""get list subcribe email"""
<|body_0|>
def post(self):
"""subcribe email: (type= 0 daily, 1: week) (statis= 0: inactive, 1: active)"""
<|body_1|>
def delete(self):
"""Delete subcribe"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubcribeEmail:
def get(self):
"""get list subcribe email"""
identity = get_jwt_identity()
cand_id = identity['id']
subcribe = get_subcribe(cand_id)
if not subcribe:
return response_object()
else:
return response_object(200, 'Thành công.',... | the_stack_v2_python_sparse | app/main/controller/subcribe_email_controller.py | loctran0169/automated-resume-screening-server | train | 0 | |
13c9f9a257c267056da237e11200e487b5e27a93 | [
"self.model = model\nself.n_epochs = params.n_epochs\nself.optimizer = optimizer\nself.criterion = criterion\nself.batch_size = params.batch_size\nself.device = device\nself.dataset = dataset\nself.val_split = params.val_split\nself._init_dataloaders()\nself.current_epoch = 0\nself.train_loss = []\nself.test_loss =... | <|body_start_0|>
self.model = model
self.n_epochs = params.n_epochs
self.optimizer = optimizer
self.criterion = criterion
self.batch_size = params.batch_size
self.device = device
self.dataset = dataset
self.val_split = params.val_split
self._init_d... | class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader instance): loader handling training data test_loader (DataLoader instance):... | Trainer | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
"""class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader instance): loader handling training data... | stack_v2_sparse_classes_36k_train_001574 | 4,916 | permissive | [
{
"docstring": "initializes training from a parameter class object Args: model (nn.Module subclass instance): model to be training dataset (DataSet subclass instance): providing data criterion (nn.Loss instance): loss function optimizer (nn.optim instance): optimizer for model parameters params (params class in... | 5 | stack_v2_sparse_classes_30k_train_013515 | Implement the Python class `Trainer` described below.
Class description:
class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader i... | Implement the Python class `Trainer` described below.
Class description:
class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader i... | 62921423b787ad8b81b8e60e8de42a3f6e113d88 | <|skeleton|>
class Trainer:
"""class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader instance): loader handling training data... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trainer:
"""class to provide framework for training a network. Attributes: TRAINING n_epochs (int): number of epochs of training model (nn.Module instance): model to be trained dataset (instance of DataSet subclass): to handle data train_loader (DataLoader instance): loader handling training data test_loader ... | the_stack_v2_python_sparse | utils/trainer.py | Bobby-Hua/birdsonearth | train | 0 |
d988bc7a57b4f9dcd271c1965bfc1978d414b4ce | [
"self.assertEquals(2, puzzle3.santa_alone_delivers('>'))\nself.assertEquals(4, puzzle3.santa_alone_delivers('^>v<'))\nself.assertEquals(2, puzzle3.santa_alone_delivers('^v^v^v^v^v'))",
"self.assertEquals(3, puzzle3.santa_with_robot_delivers('^v'))\nself.assertEquals(3, puzzle3.santa_with_robot_delivers('^>v<'))\n... | <|body_start_0|>
self.assertEquals(2, puzzle3.santa_alone_delivers('>'))
self.assertEquals(4, puzzle3.santa_alone_delivers('^>v<'))
self.assertEquals(2, puzzle3.santa_alone_delivers('^v^v^v^v^v'))
<|end_body_0|>
<|body_start_1|>
self.assertEquals(3, puzzle3.santa_with_robot_delivers('^v... | Tests for puzzle 3. | TestPuzzle3 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPuzzle3:
"""Tests for puzzle 3."""
def test_puzzle3a(self):
"""Tests for puzzle 3, part 1."""
<|body_0|>
def test_puzzle3b(self):
"""Tests for puzzle 3, part 1."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.assertEquals(2, puzzle3.san... | stack_v2_sparse_classes_36k_train_001575 | 744 | no_license | [
{
"docstring": "Tests for puzzle 3, part 1.",
"name": "test_puzzle3a",
"signature": "def test_puzzle3a(self)"
},
{
"docstring": "Tests for puzzle 3, part 1.",
"name": "test_puzzle3b",
"signature": "def test_puzzle3b(self)"
}
] | 2 | null | Implement the Python class `TestPuzzle3` described below.
Class description:
Tests for puzzle 3.
Method signatures and docstrings:
- def test_puzzle3a(self): Tests for puzzle 3, part 1.
- def test_puzzle3b(self): Tests for puzzle 3, part 1. | Implement the Python class `TestPuzzle3` described below.
Class description:
Tests for puzzle 3.
Method signatures and docstrings:
- def test_puzzle3a(self): Tests for puzzle 3, part 1.
- def test_puzzle3b(self): Tests for puzzle 3, part 1.
<|skeleton|>
class TestPuzzle3:
"""Tests for puzzle 3."""
def test_... | 99d1f68ddf92b989ff775c270d315eb8df4dbd55 | <|skeleton|>
class TestPuzzle3:
"""Tests for puzzle 3."""
def test_puzzle3a(self):
"""Tests for puzzle 3, part 1."""
<|body_0|>
def test_puzzle3b(self):
"""Tests for puzzle 3, part 1."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPuzzle3:
"""Tests for puzzle 3."""
def test_puzzle3a(self):
"""Tests for puzzle 3, part 1."""
self.assertEquals(2, puzzle3.santa_alone_delivers('>'))
self.assertEquals(4, puzzle3.santa_alone_delivers('^>v<'))
self.assertEquals(2, puzzle3.santa_alone_delivers('^v^v^v^v^... | the_stack_v2_python_sparse | puzzle3/python/test_puzzle3.py | jramaswami/Advent-Of-Code-2015 | train | 0 |
11955f5dff75c8df0908e72a0a0e978d8254355b | [
"coins.sort()\ndp = [1] + [0] * amount\nfor c in coins:\n for i in range(c, amount + 1):\n if dp[i - c]:\n dp[i] += dp[i - c]\nreturn dp[-1]",
"dp = [0] * (amount + 1)\ndp[0] = 1\nfor i in coins:\n for j in range(1, amount + 1):\n if j >= i:\n dp[j] += dp[j - i]\nreturn d... | <|body_start_0|>
coins.sort()
dp = [1] + [0] * amount
for c in coins:
for i in range(c, amount + 1):
if dp[i - c]:
dp[i] += dp[i - c]
return dp[-1]
<|end_body_0|>
<|body_start_1|>
dp = [0] * (amount + 1)
dp[0] = 1
f... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int beats 93.06%"""
<|body_0|>
def change0(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int https://leetcode.com/problems/coin-change-2/discuss... | stack_v2_sparse_classes_36k_train_001576 | 3,013 | no_license | [
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int beats 93.06%",
"name": "change",
"signature": "def change(self, amount, coins)"
},
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int https://leetcode.com/problems/coin-change-2/discuss/99210/python-O(n)-space... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int beats 93.06%
- def change0(self, amount, coins): :type amount: int :type coins: List[int] :r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int beats 93.06%
- def change0(self, amount, coins): :type amount: int :type coins: List[int] :r... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int beats 93.06%"""
<|body_0|>
def change0(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int https://leetcode.com/problems/coin-change-2/discuss... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int beats 93.06%"""
coins.sort()
dp = [1] + [0] * amount
for c in coins:
for i in range(c, amount + 1):
if dp[i - c]:
dp[i] += dp[i - c... | the_stack_v2_python_sparse | LeetCode/518_coin_change_2.py | yao23/Machine_Learning_Playground | train | 12 | |
9ab2f45a64c4a55bd88a8c0c07e101f1184bad59 | [
"tableaux = self._begin_tableaux(inference)\napplied_rules = {rule_name: [] for rule_name in tableaux_system.rules}\nfor node in LevelOrderIter(tableaux):\n for rule_name in tableaux_system.rules:\n result = tableaux_system.rule_is_applicable(node, rule_name, return_subst_dict=True)\n applicable = ... | <|body_start_0|>
tableaux = self._begin_tableaux(inference)
applied_rules = {rule_name: [] for rule_name in tableaux_system.rules}
for node in LevelOrderIter(tableaux):
for rule_name in tableaux_system.rules:
result = tableaux_system.rule_is_applicable(node, rule_name... | Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as parameter, and the tableaux solver will derive with the rules of the system you give... | TableauxSolver | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TableauxSolver:
"""Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as parameter, and the tableaux solver will de... | stack_v2_sparse_classes_36k_train_001577 | 9,699 | permissive | [
{
"docstring": "Builds a tableaux for an inference, given a tableaux system with which to operate. Parameters ---------- inference: logics.classes.propositional.Inference The Inference to build a tableaux for tableaux_system: logics.classes.propositional.proof_theories.TableauxSystem A TableauxSystem or any cla... | 2 | stack_v2_sparse_classes_30k_train_009773 | Implement the Python class `TableauxSolver` described below.
Class description:
Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as par... | Implement the Python class `TableauxSolver` described below.
Class description:
Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as par... | cc3e1665a4679616c282e8790cdac0a555191920 | <|skeleton|>
class TableauxSolver:
"""Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as parameter, and the tableaux solver will de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TableauxSolver:
"""Solver for tableaux systems Will build a tree for an (either valid or invalid) inference. When a branch is closed, does not continue adding nodes to it. Does not have the rules hardcoded. The ``solve`` method takes a tableaux system as parameter, and the tableaux solver will derive with the... | the_stack_v2_python_sparse | logics/utils/solvers/tableaux.py | ariroffe/logics | train | 15 |
2a7dea2803f4e5e02da421c0bb051aa76c514ddb | [
"self.__logger = logging.getLogger(__name__)\nself.verbose = verbose\nself.tmp_dir = tmp_dir\nself.algo_name = algo\nself.algo_base = AlgorithmBase(data=data, algo_name=self.algo_name, metric=target_metric, cv_n_jobs=CV_N_JOBS, hpo_algo=hpo_algo, verbose=verbose, random_state=random_state)",
"try:\n with Resul... | <|body_start_0|>
self.__logger = logging.getLogger(__name__)
self.verbose = verbose
self.tmp_dir = tmp_dir
self.algo_name = algo
self.algo_base = AlgorithmBase(data=data, algo_name=self.algo_name, metric=target_metric, cv_n_jobs=CV_N_JOBS, hpo_algo=hpo_algo, verbose=verbose, rand... | Trainer | [
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None):
"""Initialize new trainer"""
<|body_0|>
def start(self, max_evals):
"""Start with no limits"""
<|body... | stack_v2_sparse_classes_36k_train_001578 | 4,482 | permissive | [
{
"docstring": "Initialize new trainer",
"name": "__init__",
"signature": "def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None)"
},
{
"docstring": "Start with no limits",
"name": "start",
"sign... | 3 | null | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None): Initialize new trainer
- def st... | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None): Initialize new trainer
- def st... | 20d8df6172906337f81583dabb841d66b8f31857 | <|skeleton|>
class Trainer:
def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None):
"""Initialize new trainer"""
<|body_0|>
def start(self, max_evals):
"""Start with no limits"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trainer:
def __init__(self, tmp_dir, algo=None, data=None, target_metric=DEFAULT_TARGET_METRIC, hpo_algo=DEFAULT_HPO_ALGO, verbose=False, random_state=None):
"""Initialize new trainer"""
self.__logger = logging.getLogger(__name__)
self.verbose = verbose
self.tmp_dir = tmp_dir
... | the_stack_v2_python_sparse | new_algs/Sequence+algorithms/Selection+algorithm/trainer.py | coolsnake/JupyterNotebook | train | 0 | |
784ba2c982c389a3f7ca834225c5691aae21508b | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119. Th... | StorageRegistryServiceServicer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this d... | stack_v2_sparse_classes_36k_train_001579 | 5,403 | no_license | [
{
"docstring": "Returns the storage provider that is reponsible for the given resource reference. MUST return CODE_NOT_FOUND if the reference does not exist.",
"name": "GetStorageProvider",
"signature": "def GetStorageProvider(self, request, context)"
},
{
"docstring": "Returns a list of the ava... | 3 | stack_v2_sparse_classes_30k_train_019138 | Implement the Python class `StorageRegistryServiceServicer` described below.
Class description:
Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMM... | Implement the Python class `StorageRegistryServiceServicer` described below.
Class description:
Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMM... | dad1a042b38db5f8bedcac3b6af25066f4d6eef9 | <|skeleton|>
class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StorageRegistryServiceServicer:
"""Storage Registry API The Storage Registry API is meant to as registry to obtain information of available storage providers. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are t... | the_stack_v2_python_sparse | cs3/storageregistry/v0alpha/storageregistry_pb2_grpc.py | SamuAlfageme/python-cs3apis | train | 0 |
32c6919df8ea3cf051d571998588441650c45081 | [
"if not root:\n return ''\nqueue = []\nvalues = []\nqueue.append(root)\nwhile queue:\n top = queue.pop(0)\n if not top:\n values.append('n')\n continue\n values.append(str(top.val))\n queue.append(top.left)\n queue.append(top.right)\nreturn ','.join(values)",
"if not data:\n ret... | <|body_start_0|>
if not root:
return ''
queue = []
values = []
queue.append(root)
while queue:
top = queue.pop(0)
if not top:
values.append('n')
continue
values.append(str(top.val))
queue.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_001580 | 1,734 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_006148 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 46ab03e23d15ebd5434ef4dd5ae99130000b00a5 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
queue = []
values = []
queue.append(root)
while queue:
top = queue.pop(0)
if not top:
... | the_stack_v2_python_sparse | leetcode/297_二叉树的序列化与反序列化.py | zhulf0804/Coding.Python | train | 3 | |
f9992b4e5ef9e77c2596f230a432ccac79cf7f59 | [
"self.filter_quantities = (lambda name: True) if filter_quantities is None else filter_quantities\nself.filter_figures = (lambda name: True) if filter_figures is None else filter_figures\nself.n_histogram_bins = n_histogram_bins\nself.primary_metric = primary_metric",
"data = RegressionData(targets=ground_truth, ... | <|body_start_0|>
self.filter_quantities = (lambda name: True) if filter_quantities is None else filter_quantities
self.filter_figures = (lambda name: True) if filter_figures is None else filter_figures
self.n_histogram_bins = n_histogram_bins
self.primary_metric = primary_metric
<|end_bo... | Evaluator implementation for regression problems. | RegressionEvaluator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegressionEvaluator:
"""Evaluator implementation for regression problems."""
def __init__(self, filter_quantities: Optional[Callable[[str], bool]]=None, filter_figures: Optional[Callable[[str], bool]]=None, n_histogram_bins: int=DEFAULT_N_HISTOGRAM_BINS, primary_metric: Optional[str]=None):
... | stack_v2_sparse_classes_36k_train_001581 | 8,607 | permissive | [
{
"docstring": "Initializes the evaluator with the option to overwrite the default settings. Args: filter_quantities: Callable that receives a quantity name and returns `False` if the quantity should be excluded. Example: `filter_quantities=lambda name: \"vs Rest\" not in name` filter_figures: Callable that rec... | 2 | stack_v2_sparse_classes_30k_train_013433 | Implement the Python class `RegressionEvaluator` described below.
Class description:
Evaluator implementation for regression problems.
Method signatures and docstrings:
- def __init__(self, filter_quantities: Optional[Callable[[str], bool]]=None, filter_figures: Optional[Callable[[str], bool]]=None, n_histogram_bins:... | Implement the Python class `RegressionEvaluator` described below.
Class description:
Evaluator implementation for regression problems.
Method signatures and docstrings:
- def __init__(self, filter_quantities: Optional[Callable[[str], bool]]=None, filter_figures: Optional[Callable[[str], bool]]=None, n_histogram_bins:... | cc2ff22d25a8dd11da82c103e163e81865562ee9 | <|skeleton|>
class RegressionEvaluator:
"""Evaluator implementation for regression problems."""
def __init__(self, filter_quantities: Optional[Callable[[str], bool]]=None, filter_figures: Optional[Callable[[str], bool]]=None, n_histogram_bins: int=DEFAULT_N_HISTOGRAM_BINS, primary_metric: Optional[str]=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RegressionEvaluator:
"""Evaluator implementation for regression problems."""
def __init__(self, filter_quantities: Optional[Callable[[str], bool]]=None, filter_figures: Optional[Callable[[str], bool]]=None, n_histogram_bins: int=DEFAULT_N_HISTOGRAM_BINS, primary_metric: Optional[str]=None):
"""In... | the_stack_v2_python_sparse | src/metriculous/evaluators/_regression_evaluator.py | BikashShaw/metriculous | train | 0 |
a753668d4d1ff674ca97bbeb4c2d0bddc21d99e2 | [
"if string_param.startswith('$FILE'):\n path = re.findall('\\\\$FILE\\\\{\\\\\"(.*?)\\\\\"\\\\}', string_param)[0]\n base_folder = kwargs.get('base_folder', '.')\n path = ParseTool.get_possible_path(path, base_folder)\n with open(path, 'r') as read_file:\n string_param = ''.join(read_file)\nretur... | <|body_start_0|>
if string_param.startswith('$FILE'):
path = re.findall('\\$FILE\\{\\"(.*?)\\"\\}', string_param)[0]
base_folder = kwargs.get('base_folder', '.')
path = ParseTool.get_possible_path(path, base_folder)
with open(path, 'r') as read_file:
... | Enhanced parsing tools. | ParseTool | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParseTool:
"""Enhanced parsing tools."""
def parse_string_param_if_file(string_param: str, **kwargs):
"""Use $FILE{"data_path"} to load file from "data_path"."""
<|body_0|>
def parse_string_param_if_env(string_param: str, **kwargs):
"""Use $ENV{env_name} to load ... | stack_v2_sparse_classes_36k_train_001582 | 16,194 | permissive | [
{
"docstring": "Use $FILE{\"data_path\"} to load file from \"data_path\".",
"name": "parse_string_param_if_file",
"signature": "def parse_string_param_if_file(string_param: str, **kwargs)"
},
{
"docstring": "Use $ENV{env_name} to load environment variable \"env_name\".",
"name": "parse_strin... | 4 | null | Implement the Python class `ParseTool` described below.
Class description:
Enhanced parsing tools.
Method signatures and docstrings:
- def parse_string_param_if_file(string_param: str, **kwargs): Use $FILE{"data_path"} to load file from "data_path".
- def parse_string_param_if_env(string_param: str, **kwargs): Use $E... | Implement the Python class `ParseTool` described below.
Class description:
Enhanced parsing tools.
Method signatures and docstrings:
- def parse_string_param_if_file(string_param: str, **kwargs): Use $FILE{"data_path"} to load file from "data_path".
- def parse_string_param_if_env(string_param: str, **kwargs): Use $E... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class ParseTool:
"""Enhanced parsing tools."""
def parse_string_param_if_file(string_param: str, **kwargs):
"""Use $FILE{"data_path"} to load file from "data_path"."""
<|body_0|>
def parse_string_param_if_env(string_param: str, **kwargs):
"""Use $ENV{env_name} to load ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParseTool:
"""Enhanced parsing tools."""
def parse_string_param_if_file(string_param: str, **kwargs):
"""Use $FILE{"data_path"} to load file from "data_path"."""
if string_param.startswith('$FILE'):
path = re.findall('\\$FILE\\{\\"(.*?)\\"\\}', string_param)[0]
bas... | the_stack_v2_python_sparse | studio/micro-services/dolphinscheduler/dolphinscheduler-python/pydolphinscheduler/src/pydolphinscheduler/core/yaml_process_define.py | alldatacenter/alldata | train | 774 |
4733ce1f17759607c870d2a127c71c2ab2e8744c | [
"super(WrapEncoderLayer, self).__init__(name_cope)\nself._prepare_encoder_layer = PrepareEncoderDecoderLayer(self.full_name(), src_vocab_size, d_model, max_length, prepostprocess_dropout, word_emb_param_name=word_emb_param_names[0], pos_enc_param_name=pos_enc_param_names[0])\nself._encoder = EncoderLayer(self.full_... | <|body_start_0|>
super(WrapEncoderLayer, self).__init__(name_cope)
self._prepare_encoder_layer = PrepareEncoderDecoderLayer(self.full_name(), src_vocab_size, d_model, max_length, prepostprocess_dropout, word_emb_param_name=word_emb_param_names[0], pos_enc_param_name=pos_enc_param_names[0])
self.... | encoderlayer | WrapEncoderLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WrapEncoderLayer:
"""encoderlayer"""
def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, postprocess_cmd, weight_sharing):
"""The wrapper assembles to... | stack_v2_sparse_classes_36k_train_001583 | 40,228 | permissive | [
{
"docstring": "The wrapper assembles together all needed layers for the encoder.",
"name": "__init__",
"signature": "def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, ... | 2 | null | Implement the Python class `WrapEncoderLayer` described below.
Class description:
encoderlayer
Method signatures and docstrings:
- def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, p... | Implement the Python class `WrapEncoderLayer` described below.
Class description:
encoderlayer
Method signatures and docstrings:
- def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, p... | 420527996b6da60ca401717a734329f126ed0680 | <|skeleton|>
class WrapEncoderLayer:
"""encoderlayer"""
def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, postprocess_cmd, weight_sharing):
"""The wrapper assembles to... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WrapEncoderLayer:
"""encoderlayer"""
def __init__(self, name_cope, src_vocab_size, max_length, n_layer, n_head, d_key, d_value, d_model, d_inner_hid, prepostprocess_dropout, attention_dropout, relu_dropout, preprocess_cmd, postprocess_cmd, weight_sharing):
"""The wrapper assembles together all ne... | the_stack_v2_python_sparse | dygraph/transformer/model.py | chenbjin/models | train | 3 |
5f67b68dd51fe5b9c669862657c7b6a2dd754abe | [
"n, m = (len(text1), len(text2))\nif n * m == 0:\n return 0\ndp = [[0] * (m + 1) for _ in range(n + 1)]\nfor i in range(1, n + 1):\n for j in range(1, m + 1):\n if text1[i - 1] == text2[j - 1]:\n dp[i][j] = 1 + dp[i - 1][j - 1]\n else:\n dp[i][j] = max(dp[i - 1][j], dp[i][j... | <|body_start_0|>
n, m = (len(text1), len(text2))
if n * m == 0:
return 0
dp = [[0] * (m + 1) for _ in range(n + 1)]
for i in range(1, n + 1):
for j in range(1, m + 1):
if text1[i - 1] == text2[j - 1]:
dp[i][j] = 1 + dp[i - 1][j ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longest_common_subsequence(self, text1: str, text2: str) -> int:
"""动态规划。"""
<|body_0|>
def longest_common_subsequence_2(self, text1: str, text2: str) -> int:
"""动态规划。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n, m = (len(text1),... | stack_v2_sparse_classes_36k_train_001584 | 3,316 | no_license | [
{
"docstring": "动态规划。",
"name": "longest_common_subsequence",
"signature": "def longest_common_subsequence(self, text1: str, text2: str) -> int"
},
{
"docstring": "动态规划。",
"name": "longest_common_subsequence_2",
"signature": "def longest_common_subsequence_2(self, text1: str, text2: str)... | 2 | stack_v2_sparse_classes_30k_train_007487 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longest_common_subsequence(self, text1: str, text2: str) -> int: 动态规划。
- def longest_common_subsequence_2(self, text1: str, text2: str) -> int: 动态规划。 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longest_common_subsequence(self, text1: str, text2: str) -> int: 动态规划。
- def longest_common_subsequence_2(self, text1: str, text2: str) -> int: 动态规划。
<|skeleton|>
class Solu... | 6932d69353b94ec824dd0ddc86a92453f6673232 | <|skeleton|>
class Solution:
def longest_common_subsequence(self, text1: str, text2: str) -> int:
"""动态规划。"""
<|body_0|>
def longest_common_subsequence_2(self, text1: str, text2: str) -> int:
"""动态规划。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longest_common_subsequence(self, text1: str, text2: str) -> int:
"""动态规划。"""
n, m = (len(text1), len(text2))
if n * m == 0:
return 0
dp = [[0] * (m + 1) for _ in range(n + 1)]
for i in range(1, n + 1):
for j in range(1, m + 1):
... | the_stack_v2_python_sparse | 1143_longest-common-subsequence.py | Nigirimeshi/leetcode | train | 0 | |
c052853d0526608f97cfc4e2e0129cf21672b283 | [
"super(GeneralizedMLP, self).__init__(name=name)\nif layers is not None:\n self._layers = layers\nelse:\n self._layers = [64, 64, 1]\nif regularizer_weight:\n self._regularizers = {'w': tf.contrib.layers.l2_regularizer(scale=regularizer_weight)}\nelse:\n self._regularizers = None\nself._use_batchnorm = ... | <|body_start_0|>
super(GeneralizedMLP, self).__init__(name=name)
if layers is not None:
self._layers = layers
else:
self._layers = [64, 64, 1]
if regularizer_weight:
self._regularizers = {'w': tf.contrib.layers.l2_regularizer(scale=regularizer_weight)}... | A multilayer, fully-connected discriminator. | GeneralizedMLP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
<|body_0|>
def _build(self, input, is_train... | stack_v2_sparse_classes_36k_train_001585 | 2,866 | no_license | [
{
"docstring": "Constructs a GeneralizedMLP.",
"name": "__init__",
"signature": "def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None)"
},
{
"docstring": "Adds the network into the graph.",
"name": "_build",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_013416 | Implement the Python class `GeneralizedMLP` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None): Constructs a GeneralizedMLP.
- ... | Implement the Python class `GeneralizedMLP` described below.
Class description:
A multilayer, fully-connected discriminator.
Method signatures and docstrings:
- def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None): Constructs a GeneralizedMLP.
- ... | 358a09d491aab0794df9cc7f3f8064430a78fbc3 | <|skeleton|>
class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
<|body_0|>
def _build(self, input, is_train... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeneralizedMLP:
"""A multilayer, fully-connected discriminator."""
def __init__(self, name='fc_discriminator', regularizer_weight=0.0, use_batchnorm=False, layers=None, final_activation=None):
"""Constructs a GeneralizedMLP."""
super(GeneralizedMLP, self).__init__(name=name)
if la... | the_stack_v2_python_sparse | architectures/mlp_architectures.py | zwbgood6/temporal-hierarchy | train | 0 |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.weight, whisper_layer.self_attn.k_proj.weight, whisper_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.bias, torch.zeros_like(whisper_layer.self_attn.q... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.weight, whisper_layer.self_attn.k_proj.weight, whisper_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.bias, torch.ze... | WhisperEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieve... | stack_v2_sparse_classes_36k_train_001586 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, whisper_layer, config)"
... | 2 | stack_v2_sparse_classes_30k_train_006410 | Implement the Python class `WhisperEncoderLayerBetterTransformer` described below.
Class description:
Implement the WhisperEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, whisper_layer, config): A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` imple... | Implement the Python class `WhisperEncoderLayerBetterTransformer` described below.
Class description:
Implement the WhisperEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, whisper_layer, config): A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` imple... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieve... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieved."""
... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
36d3447e383906243ed73eb832b293d660c64551 | [
"self.x = x\nself.y = y\nself.speed = speed\nself.image = pygame.image.load('data/bullet.png').convert_alpha()",
"self.y -= self.speed\nif self.y < 0:\n return -1\nelse:\n return 1",
"x = self.x - self.image.get_width() / 2\ny = self.y - self.image.get_height() / 2\nscreen.blit(self.image, (x, y))"
] | <|body_start_0|>
self.x = x
self.y = y
self.speed = speed
self.image = pygame.image.load('data/bullet.png').convert_alpha()
<|end_body_0|>
<|body_start_1|>
self.y -= self.speed
if self.y < 0:
return -1
else:
return 1
<|end_body_1|>
<|body... | 子弹类 | Bullet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bullet:
"""子弹类"""
def __init__(self, x=0, y=-1, speed=1):
"""初始化成员变量"""
<|body_0|>
def move(self):
"""子弹运动 return -1：子弹摧毁，否则子弹存在"""
<|body_1|>
def show(self, screen):
"""子弹显示在屏幕上"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_001587 | 840 | no_license | [
{
"docstring": "初始化成员变量",
"name": "__init__",
"signature": "def __init__(self, x=0, y=-1, speed=1)"
},
{
"docstring": "子弹运动 return -1：子弹摧毁，否则子弹存在",
"name": "move",
"signature": "def move(self)"
},
{
"docstring": "子弹显示在屏幕上",
"name": "show",
"signature": "def show(self, scr... | 3 | stack_v2_sparse_classes_30k_train_003693 | Implement the Python class `Bullet` described below.
Class description:
子弹类
Method signatures and docstrings:
- def __init__(self, x=0, y=-1, speed=1): 初始化成员变量
- def move(self): 子弹运动 return -1：子弹摧毁，否则子弹存在
- def show(self, screen): 子弹显示在屏幕上 | Implement the Python class `Bullet` described below.
Class description:
子弹类
Method signatures and docstrings:
- def __init__(self, x=0, y=-1, speed=1): 初始化成员变量
- def move(self): 子弹运动 return -1：子弹摧毁，否则子弹存在
- def show(self, screen): 子弹显示在屏幕上
<|skeleton|>
class Bullet:
"""子弹类"""
def __init__(self, x=0, y=-1, s... | a1e624f0afc24ea5f159fa66fed178aa61bb0179 | <|skeleton|>
class Bullet:
"""子弹类"""
def __init__(self, x=0, y=-1, speed=1):
"""初始化成员变量"""
<|body_0|>
def move(self):
"""子弹运动 return -1：子弹摧毁，否则子弹存在"""
<|body_1|>
def show(self, screen):
"""子弹显示在屏幕上"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Bullet:
"""子弹类"""
def __init__(self, x=0, y=-1, speed=1):
"""初始化成员变量"""
self.x = x
self.y = y
self.speed = speed
self.image = pygame.image.load('data/bullet.png').convert_alpha()
def move(self):
"""子弹运动 return -1：子弹摧毁，否则子弹存在"""
self.y -= self.s... | the_stack_v2_python_sparse | pygame/aircraft/bullet.py | HappyRocky/pythonAI | train | 2 |
8369259d8eb29d70f1c7d450ac592fad6cc5dee6 | [
"self._compress = compress\nself._types = ['uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'float32', 'float64']\nself._color = color_lib.color(True)\nself._err = self._color.red('ERROR') + ': '\nif compressor == 'snappy':\n self._compressor = snappy.compress\n self._decompressor = s... | <|body_start_0|>
self._compress = compress
self._types = ['uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64', 'float32', 'float64']
self._color = color_lib.color(True)
self._err = self._color.red('ERROR') + ': '
if compressor == 'snappy':
self._c... | This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dims of the array, e.g. for rgb image, byte[1] = 3 byte[2:4]:int16 The first dim size... | serialize_numpy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class serialize_numpy:
"""This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dims of the array, e.g. for rgb image, byt... | stack_v2_sparse_classes_36k_train_001588 | 3,592 | no_license | [
{
"docstring": "The compressor can be snappy or zlib",
"name": "__init__",
"signature": "def __init__(self, compress=True, compressor='snappy')"
},
{
"docstring": "Parse the input string return dtype, shape, pure_data_str",
"name": "_parse_head",
"signature": "def _parse_head(self, raw_d... | 5 | stack_v2_sparse_classes_30k_test_000047 | Implement the Python class `serialize_numpy` described below.
Class description:
This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dim... | Implement the Python class `serialize_numpy` described below.
Class description:
This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dim... | 6ed13aa610a6f2e4e21a6c0349e0d10ebd3c3942 | <|skeleton|>
class serialize_numpy:
"""This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dims of the array, e.g. for rgb image, byt... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class serialize_numpy:
"""This class serialize and de-serialize the numpy array into string ----------------------------------------------------- The format of the serialized string byte[0]:int8 The dtype of the numpy data, see the self._types byte[1]:int8 The dims of the array, e.g. for rgb image, byte[1] = 3 byte... | the_stack_v2_python_sparse | serialize_lib.py | Akrit2013/pymodel | train | 1 |
5388c56d81e1f15971b74de5034f82622c34decc | [
"super().__init__(block_class)\nif not (isinstance(unfixed_dims, int) and unfixed_dims > 0 or unfixed_dims == 'any'):\n raise ValueError(f'{type(self).__name__} requires unfixed_dims to be \"any\" or an int > 0.')\nif not isinstance(fixed_dims, int) or not fixed_dims > 0:\n raise ValueError(f'{type(self).__na... | <|body_start_0|>
super().__init__(block_class)
if not (isinstance(unfixed_dims, int) and unfixed_dims > 0 or unfixed_dims == 'any'):
raise ValueError(f'{type(self).__name__} requires unfixed_dims to be "any" or an int > 0.')
if not isinstance(fixed_dims, int) or not fixed_dims > 0:
... | Propagator for fixed output size blocks. | FixedOutputPropagator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FixedOutputPropagator:
"""Propagator for fixed output size blocks."""
def __init__(self, block_class: str, unfixed_dims: Union[int, str]='any', fixed_dims: int=1):
"""Initializer for FixedOutputPropagator instance. Args: block_class: The name of the block class being propagated. unfi... | stack_v2_sparse_classes_36k_train_001589 | 4,438 | permissive | [
{
"docstring": "Initializer for FixedOutputPropagator instance. Args: block_class: The name of the block class being propagated. unfixed_dims: Number of unfixed dimensions. fixed_dims: Number of fixed dimensions. Raises: ValueError: If fixed_dims not int > 0. ValueError: If unfixed_dims not \"any\" or int > 0."... | 3 | stack_v2_sparse_classes_30k_train_002536 | Implement the Python class `FixedOutputPropagator` described below.
Class description:
Propagator for fixed output size blocks.
Method signatures and docstrings:
- def __init__(self, block_class: str, unfixed_dims: Union[int, str]='any', fixed_dims: int=1): Initializer for FixedOutputPropagator instance. Args: block_... | Implement the Python class `FixedOutputPropagator` described below.
Class description:
Propagator for fixed output size blocks.
Method signatures and docstrings:
- def __init__(self, block_class: str, unfixed_dims: Union[int, str]='any', fixed_dims: int=1): Initializer for FixedOutputPropagator instance. Args: block_... | 55eacc273e61ab0166b5692204a20ab756b92e4c | <|skeleton|>
class FixedOutputPropagator:
"""Propagator for fixed output size blocks."""
def __init__(self, block_class: str, unfixed_dims: Union[int, str]='any', fixed_dims: int=1):
"""Initializer for FixedOutputPropagator instance. Args: block_class: The name of the block class being propagated. unfi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FixedOutputPropagator:
"""Propagator for fixed output size blocks."""
def __init__(self, block_class: str, unfixed_dims: Union[int, str]='any', fixed_dims: int=1):
"""Initializer for FixedOutputPropagator instance. Args: block_class: The name of the block class being propagated. unfixed_dims: Num... | the_stack_v2_python_sparse | narchi/propagators/fixed.py | omni-us/narchi | train | 3 |
4a652fd91d5e1e53d085391e757b6c13917cbee8 | [
"self.idevice = idevice\nself.questionTextArea = TextAreaField(x_(u'Question:'), self.idevice.questionInstruc, question)\nself.questionTextArea.idevice = idevice\nself.isCorrect = isCorrect\nself.feedbackTextArea = TextAreaField(x_(u'Feedback'), self.idevice.feedbackInstruc, feedback)\nself.feedbackTextArea.idevice... | <|body_start_0|>
self.idevice = idevice
self.questionTextArea = TextAreaField(x_(u'Question:'), self.idevice.questionInstruc, question)
self.questionTextArea.idevice = idevice
self.isCorrect = isCorrect
self.feedbackTextArea = TextAreaField(x_(u'Feedback'), self.idevice.feedbackI... | A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element | TrueFalseQuestion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrueFalseQuestion:
"""A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element"""
def __init__(self, idevice, question='', isCorrect=False, feedback='', hint=''):
"""Initialize"""
<|body_0|>
def getResourcesField(self, this_resource... | stack_v2_sparse_classes_36k_train_001590 | 10,222 | no_license | [
{
"docstring": "Initialize",
"name": "__init__",
"signature": "def __init__(self, idevice, question='', isCorrect=False, feedback='', hint='')"
},
{
"docstring": "implement the specific resource finding mechanism for this iDevice:",
"name": "getResourcesField",
"signature": "def getResou... | 4 | stack_v2_sparse_classes_30k_train_009131 | Implement the Python class `TrueFalseQuestion` described below.
Class description:
A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element
Method signatures and docstrings:
- def __init__(self, idevice, question='', isCorrect=False, feedback='', hint=''): Initialize
- def getRe... | Implement the Python class `TrueFalseQuestion` described below.
Class description:
A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element
Method signatures and docstrings:
- def __init__(self, idevice, question='', isCorrect=False, feedback='', hint=''): Initialize
- def getRe... | 1a99c1788f0eb9f1e5d8c2ced3892d00cd9449ad | <|skeleton|>
class TrueFalseQuestion:
"""A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element"""
def __init__(self, idevice, question='', isCorrect=False, feedback='', hint=''):
"""Initialize"""
<|body_0|>
def getResourcesField(self, this_resource... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrueFalseQuestion:
"""A TrueFalse iDevice is built up of questions. Each question can be rendered as an XHTML element"""
def __init__(self, idevice, question='', isCorrect=False, feedback='', hint=''):
"""Initialize"""
self.idevice = idevice
self.questionTextArea = TextAreaField(x... | the_stack_v2_python_sparse | eXe/rev3426-3513/left-trunk-3513/exe/engine/truefalseidevice.py | joliebig/featurehouse_fstmerge_examples | train | 3 |
d84c86cf1518a530135e7afd7259def5828cd7f9 | [
"if root is None:\n return 'null'\nans = []\n\ndef dfs(root, ans):\n if root is not None:\n ans.append(root.val)\n dfs(root.left, ans)\n dfs(root.right, ans)\n else:\n ans.append('null')\ndfs(root, ans)\nreturn ','.join(list(map(str, ans)))",
"ans = data.split(',')\n\ndef tran... | <|body_start_0|>
if root is None:
return 'null'
ans = []
def dfs(root, ans):
if root is not None:
ans.append(root.val)
dfs(root.left, ans)
dfs(root.right, ans)
else:
ans.append('null')
df... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_001591 | 1,971 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_002742 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | c7becb56e207ee2de6dbf662c98db7eb5b9471ff | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return 'null'
ans = []
def dfs(root, ans):
if root is not None:
ans.append(root.val)
dfs(root.le... | the_stack_v2_python_sparse | books/《剑指offer》/剑指 Offer 37. 序列化二叉树.py | KevenGe/LeetCode-Solutions | train | 1 | |
6145b38b46939d669f7d673572337bb8cad2a191 | [
"question_wrapper = get_question_or_404(request.user, quiz_id, round_id, question_id)\ncontext = {'quiz_id': quiz_id, 'round_id': round_id, 'question_id': question_id, 'question': question_wrapper.host_info(), 'question_types': dict(QuestionType.choices), 'slide_types': dict(SlideType.choices), 'QuestionClass': Que... | <|body_start_0|>
question_wrapper = get_question_or_404(request.user, quiz_id, round_id, question_id)
context = {'quiz_id': quiz_id, 'round_id': round_id, 'question_id': question_id, 'question': question_wrapper.host_info(), 'question_types': dict(QuestionType.choices), 'slide_types': dict(SlideType.cho... | EditQuestionView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EditQuestionView:
def get(self, request, quiz_id, round_id, question_id):
"""Render the form to edit a question Attributes: None"""
<|body_0|>
def post(self, request, quiz_id, round_id, question_id):
"""Edit the attributes of the question model Attributes: PARAMS: - ... | stack_v2_sparse_classes_36k_train_001592 | 2,660 | no_license | [
{
"docstring": "Render the form to edit a question Attributes: None",
"name": "get",
"signature": "def get(self, request, quiz_id, round_id, question_id)"
},
{
"docstring": "Edit the attributes of the question model Attributes: PARAMS: - quiz_id, round_id, question_id POST: - question_info",
... | 2 | stack_v2_sparse_classes_30k_test_001157 | Implement the Python class `EditQuestionView` described below.
Class description:
Implement the EditQuestionView class.
Method signatures and docstrings:
- def get(self, request, quiz_id, round_id, question_id): Render the form to edit a question Attributes: None
- def post(self, request, quiz_id, round_id, question_... | Implement the Python class `EditQuestionView` described below.
Class description:
Implement the EditQuestionView class.
Method signatures and docstrings:
- def get(self, request, quiz_id, round_id, question_id): Render the form to edit a question Attributes: None
- def post(self, request, quiz_id, round_id, question_... | 923b8af85eda6136d4e815deb0f5c76ce22e2fc0 | <|skeleton|>
class EditQuestionView:
def get(self, request, quiz_id, round_id, question_id):
"""Render the form to edit a question Attributes: None"""
<|body_0|>
def post(self, request, quiz_id, round_id, question_id):
"""Edit the attributes of the question model Attributes: PARAMS: - ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EditQuestionView:
def get(self, request, quiz_id, round_id, question_id):
"""Render the form to edit a question Attributes: None"""
question_wrapper = get_question_or_404(request.user, quiz_id, round_id, question_id)
context = {'quiz_id': quiz_id, 'round_id': round_id, 'question_id': q... | the_stack_v2_python_sparse | quiz/views/question.py | AananthV/Quizwin | train | 0 | |
8c2363927715a59342ab27d3fd50eeccf8cfff05 | [
"super(KafkaHandler, self).__init__()\nself.connection_string = settings.get('hostname') + ':' + str(settings.get('port'))\nself.connection_timeout = settings.get('connection_timeout', 15)\nself.username = settings.get('username')\nself.password = settings.get('password')\nself.security_protocol = 'PLAINTEXT'\nself... | <|body_start_0|>
super(KafkaHandler, self).__init__()
self.connection_string = settings.get('hostname') + ':' + str(settings.get('port'))
self.connection_timeout = settings.get('connection_timeout', 15)
self.username = settings.get('username')
self.password = settings.get('passwo... | KafkaHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KafkaHandler:
def __init__(self, settings):
"""Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler type name."""
<|body_0|>
def send_message(self, queue_name, body):
"""Sends messag... | stack_v2_sparse_classes_36k_train_001593 | 3,302 | permissive | [
{
"docstring": "Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler type name.",
"name": "__init__",
"signature": "def __init__(self, settings)"
},
{
"docstring": "Sends message to the queue :param queue_name: ... | 3 | stack_v2_sparse_classes_30k_train_003653 | Implement the Python class `KafkaHandler` described below.
Class description:
Implement the KafkaHandler class.
Method signatures and docstrings:
- def __init__(self, settings): Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler ty... | Implement the Python class `KafkaHandler` described below.
Class description:
Implement the KafkaHandler class.
Method signatures and docstrings:
- def __init__(self, settings): Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler ty... | db34927e4c45df93438e2b7129f01388f1a34753 | <|skeleton|>
class KafkaHandler:
def __init__(self, settings):
"""Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler type name."""
<|body_0|>
def send_message(self, queue_name, body):
"""Sends messag... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KafkaHandler:
def __init__(self, settings):
"""Initializes the KafkaHandler with it's special connection string :param settings: settings from `mlapp > config.py` depending on handler type name."""
super(KafkaHandler, self).__init__()
self.connection_string = settings.get('hostname') ... | the_stack_v2_python_sparse | mlapp/handlers/message_queues/kafka_handler.py | ghas-results/mlapp | train | 0 | |
665a7577576b79da151d370760a12b2bea42c378 | [
"connect_mysql = ConnectMysql(host='202.104.102.166', user='rz_cm_master', password='TbLuENLK', port=3306, db='jydb')\nday = \"'2019-03-31'\"\nsql = 'SELECT m.roe,s.SecuCode FROM jydb.LC_MainIndexNew m INNER JOIN jydb.SecuMain s ON (m.CompanyCode = s.CompanyCode) INNER JOIN jydb.CT_SystemConst c ON (s.ListedState =... | <|body_start_0|>
connect_mysql = ConnectMysql(host='202.104.102.166', user='rz_cm_master', password='TbLuENLK', port=3306, db='jydb')
day = "'2019-03-31'"
sql = 'SELECT m.roe,s.SecuCode FROM jydb.LC_MainIndexNew m INNER JOIN jydb.SecuMain s ON (m.CompanyCode = s.CompanyCode) INNER JOIN jydb.CT_S... | TestAssetFinancialAnalysis | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAssetFinancialAnalysis:
def test_check_roe_threshold_greater_zero():
"""检查数据库绩优股(roe大于0)阈值数据准确性"""
<|body_0|>
def test_check_roe_threshold_less_zero():
"""检查数据库绩优股(roe小于0)阈值数据准确性"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
connect_mysql = Co... | stack_v2_sparse_classes_36k_train_001594 | 4,578 | no_license | [
{
"docstring": "检查数据库绩优股(roe大于0)阈值数据准确性",
"name": "test_check_roe_threshold_greater_zero",
"signature": "def test_check_roe_threshold_greater_zero()"
},
{
"docstring": "检查数据库绩优股(roe小于0)阈值数据准确性",
"name": "test_check_roe_threshold_less_zero",
"signature": "def test_check_roe_threshold_less... | 2 | null | Implement the Python class `TestAssetFinancialAnalysis` described below.
Class description:
Implement the TestAssetFinancialAnalysis class.
Method signatures and docstrings:
- def test_check_roe_threshold_greater_zero(): 检查数据库绩优股(roe大于0)阈值数据准确性
- def test_check_roe_threshold_less_zero(): 检查数据库绩优股(roe小于0)阈值数据准确性 | Implement the Python class `TestAssetFinancialAnalysis` described below.
Class description:
Implement the TestAssetFinancialAnalysis class.
Method signatures and docstrings:
- def test_check_roe_threshold_greater_zero(): 检查数据库绩优股(roe大于0)阈值数据准确性
- def test_check_roe_threshold_less_zero(): 检查数据库绩优股(roe小于0)阈值数据准确性
<|sk... | eae782a78ffde1276a0812a43d7deefb0bdedeb4 | <|skeleton|>
class TestAssetFinancialAnalysis:
def test_check_roe_threshold_greater_zero():
"""检查数据库绩优股(roe大于0)阈值数据准确性"""
<|body_0|>
def test_check_roe_threshold_less_zero():
"""检查数据库绩优股(roe小于0)阈值数据准确性"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAssetFinancialAnalysis:
def test_check_roe_threshold_greater_zero():
"""检查数据库绩优股(roe大于0)阈值数据准确性"""
connect_mysql = ConnectMysql(host='202.104.102.166', user='rz_cm_master', password='TbLuENLK', port=3306, db='jydb')
day = "'2019-03-31'"
sql = 'SELECT m.roe,s.SecuCode FROM j... | the_stack_v2_python_sparse | test_case/combination_master/fund_research/fund_page/position_analysis/test_asset_financial_analysis.py | liufubin-git/python | train | 0 | |
b03ee099689419212b91298a1cc3a692aa82e7e9 | [
"prices = [(s.count('0'), s.count('1')) for s in strs]\nprices = Counter(prices)\ndp = [[0] * (n + 1) for i in range(m + 1)]\n\ndef zeroOnePack2D(c0, c1, w=1):\n for i in range(m, c0 - 1, -1):\n for j in range(n, c1 - 1, -1):\n dp[i][j] = max(dp[i][j], dp[i - c0][j - c1] + w)\n\ndef completePac... | <|body_start_0|>
prices = [(s.count('0'), s.count('1')) for s in strs]
prices = Counter(prices)
dp = [[0] * (n + 1) for i in range(m + 1)]
def zeroOnePack2D(c0, c1, w=1):
for i in range(m, c0 - 1, -1):
for j in range(n, c1 - 1, -1):
dp[i][... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxForm(self, strs, m, n):
""":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int"""
<|body_0|>
def naiveFindMaxForm(self, strs, m, n):
""":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_001595 | 6,980 | no_license | [
{
"docstring": ":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int",
"name": "findMaxForm",
"signature": "def findMaxForm(self, strs, m, n)"
},
{
"docstring": ":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int",
"name": "naiveFindMaxForm",
"signatur... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs, m, n): :type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int
- def naiveFindMaxForm(self, strs, m, n): :type strs: List[str] :type m: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxForm(self, strs, m, n): :type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int
- def naiveFindMaxForm(self, strs, m, n): :type strs: List[str] :type m: ... | 97533d53c8892b6519e99f344489fa4fd4c9ab93 | <|skeleton|>
class Solution:
def findMaxForm(self, strs, m, n):
""":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int"""
<|body_0|>
def naiveFindMaxForm(self, strs, m, n):
""":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMaxForm(self, strs, m, n):
""":type strs: List[str] :type m: int of 0 :type n: int of 1 :rtype: int"""
prices = [(s.count('0'), s.count('1')) for s in strs]
prices = Counter(prices)
dp = [[0] * (n + 1) for i in range(m + 1)]
def zeroOnePack2D(c0, c1, ... | the_stack_v2_python_sparse | 4. DP/474.py | proTao/leetcode | train | 0 | |
c1ed945590b8e6007dc6137ecad43fdbab680693 | [
"super(EncodingDetectFilter, self).__init__(builder)\nself._normalize = self.builder.decoder.normalize\nself._meta = self._normalize('meta')",
"normalize = self._normalize\niname = normalize(name)\nif iname == self._meta:\n adict = dict([(normalize(key), val) for key, val in attr])\n value = str(adict.get(n... | <|body_start_0|>
super(EncodingDetectFilter, self).__init__(builder)
self._normalize = self.builder.decoder.normalize
self._meta = self._normalize('meta')
<|end_body_0|>
<|body_start_1|>
normalize = self._normalize
iname = normalize(name)
if iname == self._meta:
... | Extract template encoding and pass it properly to the builder | EncodingDetectFilter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncodingDetectFilter:
"""Extract template encoding and pass it properly to the builder"""
def __init__(self, builder):
"""Initialization"""
<|body_0|>
def handle_starttag(self, name, attr, closed, data):
"""Extract encoding from HTML meta element Here are samples... | stack_v2_sparse_classes_36k_train_001596 | 6,907 | permissive | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, builder)"
},
{
"docstring": "Extract encoding from HTML meta element Here are samples for the expected formats:: <meta charset=\"utf-8\"> <!-- HTML5 --> <meta http-equiv=\"Content-Type\" content=\"text/html; ch... | 3 | stack_v2_sparse_classes_30k_train_020970 | Implement the Python class `EncodingDetectFilter` described below.
Class description:
Extract template encoding and pass it properly to the builder
Method signatures and docstrings:
- def __init__(self, builder): Initialization
- def handle_starttag(self, name, attr, closed, data): Extract encoding from HTML meta ele... | Implement the Python class `EncodingDetectFilter` described below.
Class description:
Extract template encoding and pass it properly to the builder
Method signatures and docstrings:
- def __init__(self, builder): Initialization
- def handle_starttag(self, name, attr, closed, data): Extract encoding from HTML meta ele... | 65a93080281f9ce5c0379e9dbb111f14965a8613 | <|skeleton|>
class EncodingDetectFilter:
"""Extract template encoding and pass it properly to the builder"""
def __init__(self, builder):
"""Initialization"""
<|body_0|>
def handle_starttag(self, name, attr, closed, data):
"""Extract encoding from HTML meta element Here are samples... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncodingDetectFilter:
"""Extract template encoding and pass it properly to the builder"""
def __init__(self, builder):
"""Initialization"""
super(EncodingDetectFilter, self).__init__(builder)
self._normalize = self.builder.decoder.normalize
self._meta = self._normalize('me... | the_stack_v2_python_sparse | tdi/markup/soup/filters.py | ndparker/tdi | train | 4 |
062285f3854f1e3ad28a9a746c17eb49a2c678ad | [
"self.Tc = Tc\nself.Pc = Pc\nself.Vc = Vc\nself.Tb = Tb\nself.structureIndex = structureIndex",
"string = 'CriticalPointGroupContribution(Tc={0!r}, Pc={1!r}, Vc={2!r}, Tb={3!r}, structureIndex={4!r}'.format(self.Tc, self.Pc, self.Vc, self.Tb, self.structureIndex)\nstring += ')'\nreturn string"
] | <|body_start_0|>
self.Tc = Tc
self.Pc = Pc
self.Vc = Vc
self.Tb = Tb
self.structureIndex = structureIndex
<|end_body_0|>
<|body_start_1|>
string = 'CriticalPointGroupContribution(Tc={0!r}, Pc={1!r}, Vc={2!r}, Tb={3!r}, structureIndex={4!r}'.format(self.Tc, self.Pc, self.... | Joback group contribution to estimate critical properties | CriticalPointGroupContribution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CriticalPointGroupContribution:
"""Joback group contribution to estimate critical properties"""
def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None):
"""Note that argument names are retained for backward compatibility with loading database files."""
<|b... | stack_v2_sparse_classes_36k_train_001597 | 26,300 | permissive | [
{
"docstring": "Note that argument names are retained for backward compatibility with loading database files.",
"name": "__init__",
"signature": "def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None)"
},
{
"docstring": "Return a string representation that can be used to rec... | 2 | null | Implement the Python class `CriticalPointGroupContribution` described below.
Class description:
Joback group contribution to estimate critical properties
Method signatures and docstrings:
- def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None): Note that argument names are retained for backward ... | Implement the Python class `CriticalPointGroupContribution` described below.
Class description:
Joback group contribution to estimate critical properties
Method signatures and docstrings:
- def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None): Note that argument names are retained for backward ... | 349a4af759cf8877197772cd7eaca1e51d46eff5 | <|skeleton|>
class CriticalPointGroupContribution:
"""Joback group contribution to estimate critical properties"""
def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None):
"""Note that argument names are retained for backward compatibility with loading database files."""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CriticalPointGroupContribution:
"""Joback group contribution to estimate critical properties"""
def __init__(self, Tc=None, Pc=None, Vc=None, Tb=None, structureIndex=None):
"""Note that argument names are retained for backward compatibility with loading database files."""
self.Tc = Tc
... | the_stack_v2_python_sparse | rmgpy/data/transport.py | CanePan-cc/CanePanWorkshop | train | 2 |
b12f3ded460bd861d96e6c39c5e81eed204ef662 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn MacOSGeneralDeviceConfiguration()",
"from .app_list_item import AppListItem\nfrom .app_list_type import AppListType\nfrom .device_configuration import DeviceConfiguration\nfrom .required_password_type import RequiredPasswordType\nfrom ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return MacOSGeneralDeviceConfiguration()
<|end_body_0|>
<|body_start_1|>
from .app_list_item import AppListItem
from .app_list_type import AppListType
from .device_configuration import ... | This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource. | MacOSGeneralDeviceConfiguration | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:... | stack_v2_sparse_classes_36k_train_001598 | 6,806 | 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: MacOSGeneralDeviceConfiguration",
"name": "create_from_discriminator_value",
"signature": "def create_from_d... | 3 | stack_v2_sparse_classes_30k_train_000798 | Implement the Python class `MacOSGeneralDeviceConfiguration` described below.
Class description:
This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource.
Method signatures and docstrings:
- def create_from_discriminator_value(parse... | Implement the Python class `MacOSGeneralDeviceConfiguration` described below.
Class description:
This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource.
Method signatures and docstrings:
- def create_from_discriminator_value(parse... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MacOSGeneralDeviceConfiguration:
"""This topic provides descriptions of the declared methods, properties and relationships exposed by the macOSGeneralDeviceConfiguration resource."""
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> MacOSGeneralDeviceConfiguration:
"""C... | the_stack_v2_python_sparse | msgraph/generated/models/mac_o_s_general_device_configuration.py | microsoftgraph/msgraph-sdk-python | train | 135 |
3224c0598ce3b6cbd2dd18d804f8c3ec6cc792c4 | [
"super(SI_SNR, self).__init__()\nself.eps = eps\nself.pit = pit",
"B, C, S = Y.size()\nzero_mean_target = Y - torch.mean(Y, dim=-1, keepdim=True)\nzero_mean_estimate = Y_ - torch.mean(Y_, dim=-1, keepdim=True)\ns_target = torch.unsqueeze(zero_mean_target, dim=1)\ns_estimate = torch.unsqueeze(zero_mean_estimate, d... | <|body_start_0|>
super(SI_SNR, self).__init__()
self.eps = eps
self.pit = pit
<|end_body_0|>
<|body_start_1|>
B, C, S = Y.size()
zero_mean_target = Y - torch.mean(Y, dim=-1, keepdim=True)
zero_mean_estimate = Y_ - torch.mean(Y_, dim=-1, keepdim=True)
s_target = t... | Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325 | SI_SNR | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SI_SNR:
"""Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325"""
def __init__(self: 'SI_SNR', eps: f... | stack_v2_sparse_classes_36k_train_001599 | 3,577 | permissive | [
{
"docstring": "Initialization Keyword Arguments: eps {float} -- epsilon to avoid 0 division (default: {1e-8}) pit {bool} -- use pit training (default: {False})",
"name": "__init__",
"signature": "def __init__(self: 'SI_SNR', eps: float=1e-08, pit: bool=False) -> None"
},
{
"docstring": "Forward... | 2 | stack_v2_sparse_classes_30k_train_015713 | Implement the Python class `SI_SNR` described below.
Class description:
Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325
Met... | Implement the Python class `SI_SNR` described below.
Class description:
Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325
Met... | 2415502fa8a38d4624b1c71e926f1723bdc8535c | <|skeleton|>
class SI_SNR:
"""Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325"""
def __init__(self: 'SI_SNR', eps: f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SI_SNR:
"""Scale Invariant Signal to Noise Ratio with support for PIT Training Adapted from: - https://github.com/kaituoxu/Conv-TasNet Attributes: eps {float} -- epsilon to avoid 0 division pit {bool} -- use pit training https://arxiv.org/abs/1607.00325"""
def __init__(self: 'SI_SNR', eps: float=1e-08, p... | the_stack_v2_python_sparse | SPK_SP_Master/wass/convtasnet/loss.py | adamwhitakerwilson/speaker_separation | train | 0 |
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