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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
a86aaa32392ebd18a23c7cfbe689989e7dafcb08 | [
"behavior_id = uuid4()\nself.registered_behaviors.append((self.event.create_behavior(json_payload['name'], json_payload['parameters']), self.event.create_criteria(json_payload['criteria']), behavior_id))\nreturn behavior_id",
"for behavior, criteria, _ in self.registered_behaviors:\n if criteria.evaluate(attri... | <|body_start_0|>
behavior_id = uuid4()
self.registered_behaviors.append((self.event.create_behavior(json_payload['name'], json_payload['parameters']), self.event.create_criteria(json_payload['criteria']), behavior_id))
return behavior_id
<|end_body_0|>
<|body_start_1|>
for behavior, cri... | A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, criteria, and uuid). | BehaviorRegistry | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BehaviorRegistry:
"""A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, criteria, and uuid)."""
def register... | stack_v2_sparse_classes_36k_train_004800 | 13,532 | permissive | [
{
"docstring": "Register a behavior with the given JSON payload from a request.",
"name": "register_from_json",
"signature": "def register_from_json(self, json_payload)"
},
{
"docstring": "Retrive a previously-registered behavior given the set of attributes.",
"name": "behavior_for_attribute... | 3 | stack_v2_sparse_classes_30k_train_009871 | Implement the Python class `BehaviorRegistry` described below.
Class description:
A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, cr... | Implement the Python class `BehaviorRegistry` described below.
Class description:
A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, cr... | 8e7eeed84ec5ae97863f9330023298845623c639 | <|skeleton|>
class BehaviorRegistry:
"""A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, criteria, and uuid)."""
def register... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BehaviorRegistry:
"""A registry of behavior. :ivar EventDescription event: The event this registry is operating for. :ivar registered_behaviors: The set of criteria and behaviors to use for this event. Currently this is just a list of tuples of (behavior, criteria, and uuid)."""
def register_from_json(se... | the_stack_v2_python_sparse | mimic/model/behaviors.py | ranjithpeddi/mimic | train | 1 |
8da51f09e33e31f14ca61ee376e0577d436807c9 | [
"super().__init__()\nif p < 0 or p >= 1:\n raise ValueError('dropout probability has to be in [0, 1), but got {}'.format(p))\nself.p = p\nself.tie = tie\nself.transposed = transposed\nself.binomial = torch.distributions.binomial.Binomial(probs=1 - self.p)",
"if self.training:\n if not self.transposed:\n ... | <|body_start_0|>
super().__init__()
if p < 0 or p >= 1:
raise ValueError('dropout probability has to be in [0, 1), but got {}'.format(p))
self.p = p
self.tie = tie
self.transposed = transposed
self.binomial = torch.distributions.binomial.Binomial(probs=1 - sel... | DropoutNd | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DropoutNd:
def __init__(self, p: float=0.5, tie=True, transposed=True):
"""Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)"""
<|body_0|>
def forward(self, X):
"""Forward pass. X: (batch, dim, lengths...)"""
<|body_1|... | stack_v2_sparse_classes_36k_train_004801 | 13,449 | permissive | [
{
"docstring": "Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)",
"name": "__init__",
"signature": "def __init__(self, p: float=0.5, tie=True, transposed=True)"
},
{
"docstring": "Forward pass. X: (batch, dim, lengths...)",
"name": "forward",
"s... | 2 | null | Implement the Python class `DropoutNd` described below.
Class description:
Implement the DropoutNd class.
Method signatures and docstrings:
- def __init__(self, p: float=0.5, tie=True, transposed=True): Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)
- def forward(self, X): ... | Implement the Python class `DropoutNd` described below.
Class description:
Implement the DropoutNd class.
Method signatures and docstrings:
- def __init__(self, p: float=0.5, tie=True, transposed=True): Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)
- def forward(self, X): ... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class DropoutNd:
def __init__(self, p: float=0.5, tie=True, transposed=True):
"""Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)"""
<|body_0|>
def forward(self, X):
"""Forward pass. X: (batch, dim, lengths...)"""
<|body_1|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DropoutNd:
def __init__(self, p: float=0.5, tie=True, transposed=True):
"""Initialize dropout module. tie: tie dropout mask across sequence lengths (Dropout1d/2d/3d)"""
super().__init__()
if p < 0 or p >= 1:
raise ValueError('dropout probability has to be in [0, 1), but got... | the_stack_v2_python_sparse | espnet2/asr/state_spaces/components.py | espnet/espnet | train | 7,242 | |
e7f25cfe7b82e2dad2f5c71309aed325189091a8 | [
"kwargs['default'] = default\nkwargs['types'] = (Frame, tuple, list)\nsuper().__init__(**kwargs)",
"if isinstance(value, Frame):\n return value\nvalue = super().parse(value)\nif value is UNDEF or value is None:\n return value\nif callable(value):\n return value\nreturn Frame(*value)"
] | <|body_start_0|>
kwargs['default'] = default
kwargs['types'] = (Frame, tuple, list)
super().__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
if isinstance(value, Frame):
return value
value = super().parse(value)
if value is UNDEF or value is None:
... | Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height. | FrameProperty | [
"LicenseRef-scancode-philippe-de-muyter",
"LicenseRef-scancode-commercial-license",
"AGPL-3.0-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FrameProperty:
"""Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of MarkerProperty."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_004802 | 13,091 | permissive | [
{
"docstring": "Initializes a new instance of MarkerProperty.",
"name": "__init__",
"signature": "def __init__(self, default=UNDEF, **kwargs)"
},
{
"docstring": "Validates and converts given value.",
"name": "parse",
"signature": "def parse(self, value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010690 | Implement the Python class `FrameProperty` described below.
Class description:
Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height.
Method signatures and docstrings:
- def __init__(self, default=UNDEF, **kwargs): Initializes a n... | Implement the Python class `FrameProperty` described below.
Class description:
Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height.
Method signatures and docstrings:
- def __init__(self, default=UNDEF, **kwargs): Initializes a n... | d59b1bc056f3037b7b7ab635b6deb41120612965 | <|skeleton|>
class FrameProperty:
"""Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of MarkerProperty."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FrameProperty:
"""Defines a frame property. The value must be provided as a pero.Frame or as a tuple or list of four values for left x, top y, width and height."""
def __init__(self, default=UNDEF, **kwargs):
"""Initializes a new instance of MarkerProperty."""
kwargs['default'] = default
... | the_stack_v2_python_sparse | pero/drawing/frame.py | xxao/pero | train | 31 |
484d834f1066b5fbf67d373aa2266dc9afe32dcc | [
"self.name = name\nself.filepath = path\nself.numparam = numparam\nself.pre_exec_callback = pre_exec_callback\nself.post_exec_callback = post_exec_callback\nself.cwd = cwd\nif sys.version_info[0] == 2 and sys.platform == 'win32':\n self.filepath = self.filepath.encode(sys.getfilesystemencoding())",
"if len(arg... | <|body_start_0|>
self.name = name
self.filepath = path
self.numparam = numparam
self.pre_exec_callback = pre_exec_callback
self.post_exec_callback = post_exec_callback
self.cwd = cwd
if sys.version_info[0] == 2 and sys.platform == 'win32':
self.filepat... | Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html | ShellHook | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShellHook:
"""Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html"""
def __init__(self, name, path, numparam, pre_exec_callback=None, post_exec_callback=None, cwd=None):
"""Setup shell hook definition :param n... | stack_v2_sparse_classes_36k_train_004803 | 5,353 | permissive | [
{
"docstring": "Setup shell hook definition :param name: name of hook for error messages :param path: absolute path to executable file :param numparam: number of requirements parameters :param pre_exec_callback: closure for setup before execution Defaults to None. Takes in the variable argument list from the ex... | 2 | stack_v2_sparse_classes_30k_train_020941 | Implement the Python class `ShellHook` described below.
Class description:
Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html
Method signatures and docstrings:
- def __init__(self, name, path, numparam, pre_exec_callback=None, post_exec_callb... | Implement the Python class `ShellHook` described below.
Class description:
Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html
Method signatures and docstrings:
- def __init__(self, name, path, numparam, pre_exec_callback=None, post_exec_callb... | d59c99dcdcd280d7eec36a693dd80f8c8c831ea2 | <|skeleton|>
class ShellHook:
"""Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html"""
def __init__(self, name, path, numparam, pre_exec_callback=None, post_exec_callback=None, cwd=None):
"""Setup shell hook definition :param n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShellHook:
"""Hook by executable file Implements standard githooks(5) [0]: [0] http://www.kernel.org/pub/software/scm/git/docs/githooks.html"""
def __init__(self, name, path, numparam, pre_exec_callback=None, post_exec_callback=None, cwd=None):
"""Setup shell hook definition :param name: name of ... | the_stack_v2_python_sparse | modules/dbnd/src/dbnd/_vendor/dulwich/hooks.py | databand-ai/dbnd | train | 257 |
c603b1eb378134cb24286dac58e27273084a8ee2 | [
"if keys_to_features is None:\n keys_to_features = {names.TfRecordFields.image_encoded: tf.FixedLenFeature((), tf.string, default_value=''), names.TfRecordFields.object_bbox_ymin: tf.VarLenFeature(tf.float32), names.TfRecordFields.object_bbox_xmin: tf.VarLenFeature(tf.float32), names.TfRecordFields.object_bbox_y... | <|body_start_0|>
if keys_to_features is None:
keys_to_features = {names.TfRecordFields.image_encoded: tf.FixedLenFeature((), tf.string, default_value=''), names.TfRecordFields.object_bbox_ymin: tf.VarLenFeature(tf.float32), names.TfRecordFields.object_bbox_xmin: tf.VarLenFeature(tf.float32), names.T... | Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type. | DataDecoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataDecoder:
"""Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type."""
def __init__(self, keys_to_features=None, load_masks=False):
"""Constructor. Args: keys_to_features: dict or None, a dict mapping from tenso... | stack_v2_sparse_classes_36k_train_004804 | 4,706 | no_license | [
{
"docstring": "Constructor. Args: keys_to_features: dict or None, a dict mapping from tensor names to feature parsers. If None, a default mapping will be built. load_masks: bool scalar, whether to load instance masks.",
"name": "__init__",
"signature": "def __init__(self, keys_to_features=None, load_ma... | 2 | stack_v2_sparse_classes_30k_train_004106 | Implement the Python class `DataDecoder` described below.
Class description:
Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type.
Method signatures and docstrings:
- def __init__(self, keys_to_features=None, load_masks=False): Constructor. Args: ... | Implement the Python class `DataDecoder` described below.
Class description:
Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type.
Method signatures and docstrings:
- def __init__(self, keys_to_features=None, load_masks=False): Constructor. Args: ... | 5a53e02c690632bcf140d1b17327959609aab395 | <|skeleton|>
class DataDecoder:
"""Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type."""
def __init__(self, keys_to_features=None, load_masks=False):
"""Constructor. Args: keys_to_features: dict or None, a dict mapping from tenso... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataDecoder:
"""Data decoder implements a `decode` method that converts a serialized protobuf string into tensors of desired shape and type."""
def __init__(self, keys_to_features=None, load_masks=False):
"""Constructor. Args: keys_to_features: dict or None, a dict mapping from tensor names to fe... | the_stack_v2_python_sparse | data/data_decoder.py | chao-ji/tf-detection | train | 2 |
ba2b116d6e45cf8fd91004590a1d2c1f5a3dd4ce | [
"params = self.properties[self.TEMPLATE_PARAMS]\nparams[self.TEMPLATE_NAME] = self.physical_resource_name()\nparams['description'] = self.properties.get('description')\nLOG.debug('Vitrage params for template add: %s', params)\nadded_templates = self.client().template.add(template_str=self.properties[self.TEMPLATE_F... | <|body_start_0|>
params = self.properties[self.TEMPLATE_PARAMS]
params[self.TEMPLATE_NAME] = self.physical_resource_name()
params['description'] = self.properties.get('description')
LOG.debug('Vitrage params for template add: %s', params)
added_templates = self.client().template.... | A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. The VitrageTemplate resource generates and adds to Vitrage a template based on the... | VitrageTemplate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VitrageTemplate:
"""A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. The VitrageTemplate resource generates ... | stack_v2_sparse_classes_36k_train_004805 | 4,889 | permissive | [
{
"docstring": "Create a Vitrage template.",
"name": "handle_create",
"signature": "def handle_create(self)"
},
{
"docstring": "Delete the Vitrage template.",
"name": "handle_delete",
"signature": "def handle_delete(self)"
},
{
"docstring": "Validate a Vitrage template.",
"na... | 3 | stack_v2_sparse_classes_30k_train_013455 | Implement the Python class `VitrageTemplate` described below.
Class description:
A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. ... | Implement the Python class `VitrageTemplate` described below.
Class description:
A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. ... | a4ac653e35f16a5787bc5a2c934736656294b9b6 | <|skeleton|>
class VitrageTemplate:
"""A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. The VitrageTemplate resource generates ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VitrageTemplate:
"""A resource for managing Vitrage templates. A Vitrage template defines conditions and actions, based on the Vitrage topology graph. For example, if there is an "instance down" alarm on an instance, then execute a Mistral healing workflow. The VitrageTemplate resource generates and adds to V... | the_stack_v2_python_sparse | heat/engine/resources/openstack/vitrage/vitrage_template.py | stackriot/heat | train | 0 |
1c6315bf1ee497701ab03a0319aa9cf1024b13f0 | [
"url = '/booking/abort/'\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_code, 302)",
"url = '/booking/abort/'\nself.client.login(username=self.adminUN, password='pass')\nresponse = self.client.get(url, HTTP_HOST='website.domain')\nself.assertEqual(response.status_co... | <|body_start_0|>
url = '/booking/abort/'
response = self.client.get(url, HTTP_HOST='website.domain')
self.assertEqual(response.status_code, 302)
<|end_body_0|>
<|body_start_1|>
url = '/booking/abort/'
self.client.login(username=self.adminUN, password='pass')
response = s... | This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the current booking is cancelled. ============================== 29/10/2018 SE. | BookingAbortTestCase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BookingAbortTestCase:
"""This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the current booking is cancelled. ===========... | stack_v2_sparse_classes_36k_train_004806 | 26,818 | permissive | [
{
"docstring": "Test that the booking abort view will display an error whilst not logged in and no booking.",
"name": "test_not_logged_in_no_booking",
"signature": "def test_not_logged_in_no_booking(self)"
},
{
"docstring": "Test that the booking abort view will display an error whilst logged in... | 3 | null | Implement the Python class `BookingAbortTestCase` described below.
Class description:
This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the cu... | Implement the Python class `BookingAbortTestCase` described below.
Class description:
This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the cu... | 37d2942efcbdaad072f7a06ac876a40e0f69f702 | <|skeleton|>
class BookingAbortTestCase:
"""This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the current booking is cancelled. ===========... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BookingAbortTestCase:
"""This does not seem to be working currently. The "Cancel in progress booking" button takes user to an unrelated (broken) URL. The user then has to manually 'back' to get to the moorings website, and refresh in order to see that the current booking is cancelled. ========================... | the_stack_v2_python_sparse | mooring/test_views.py | dbca-wa/moorings | train | 0 |
7e211fd2c0414dcfea889002ba45d2d8c6c78b07 | [
"try:\n function = await self.application.objects.get(FunctionGenerator, id=int(function_id))\n await self.application.objects.delete(function)\n return self.json(JsonResponse(code=1, data={'functionId': function_id}))\nexcept FunctionGenerator.DoesNotExist:\n self.set_status(400)\n return self.json(... | <|body_start_0|>
try:
function = await self.application.objects.get(FunctionGenerator, id=int(function_id))
await self.application.objects.delete(function)
return self.json(JsonResponse(code=1, data={'functionId': function_id}))
except FunctionGenerator.DoesNotExist:
... | FunctionChangeHandler | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionChangeHandler:
async def delete(self, function_id, *args, **kwargs):
"""删除内置函数数据 :param function_id: 删除内置函数数据id"""
<|body_0|>
async def patch(self, function_id, *args, **kwargs):
"""更新内置函数数据 :param function_id: 更新内置函数数据的id"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_004807 | 17,374 | permissive | [
{
"docstring": "删除内置函数数据 :param function_id: 删除内置函数数据id",
"name": "delete",
"signature": "async def delete(self, function_id, *args, **kwargs)"
},
{
"docstring": "更新内置函数数据 :param function_id: 更新内置函数数据的id",
"name": "patch",
"signature": "async def patch(self, function_id, *args, **kwargs)... | 2 | stack_v2_sparse_classes_30k_train_016873 | Implement the Python class `FunctionChangeHandler` described below.
Class description:
Implement the FunctionChangeHandler class.
Method signatures and docstrings:
- async def delete(self, function_id, *args, **kwargs): 删除内置函数数据 :param function_id: 删除内置函数数据id
- async def patch(self, function_id, *args, **kwargs): 更新内... | Implement the Python class `FunctionChangeHandler` described below.
Class description:
Implement the FunctionChangeHandler class.
Method signatures and docstrings:
- async def delete(self, function_id, *args, **kwargs): 删除内置函数数据 :param function_id: 删除内置函数数据id
- async def patch(self, function_id, *args, **kwargs): 更新内... | dc9b4c55f0b3ace180c30b7f080eb5d88bb38fdb | <|skeleton|>
class FunctionChangeHandler:
async def delete(self, function_id, *args, **kwargs):
"""删除内置函数数据 :param function_id: 删除内置函数数据id"""
<|body_0|>
async def patch(self, function_id, *args, **kwargs):
"""更新内置函数数据 :param function_id: 更新内置函数数据的id"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FunctionChangeHandler:
async def delete(self, function_id, *args, **kwargs):
"""删除内置函数数据 :param function_id: 删除内置函数数据id"""
try:
function = await self.application.objects.get(FunctionGenerator, id=int(function_id))
await self.application.objects.delete(function)
... | the_stack_v2_python_sparse | apps/project/handlers.py | xiaoxiaolulu/MagicTestPlatform | train | 5 | |
27481856715f916d6c24c0199ed6a921390b783b | [
"stack = [0]\nresult = heights[0]\nheights = [0] + heights + [0]\nfor i in range(1, len(heights)):\n if heights[stack[-1]] < heights[i]:\n stack.append(i)\n elif heights[stack[-1]] == heights[i]:\n stack[-1] = i\n else:\n while stack and heights[stack[-1]] > heights[i]:\n mi... | <|body_start_0|>
stack = [0]
result = heights[0]
heights = [0] + heights + [0]
for i in range(1, len(heights)):
if heights[stack[-1]] < heights[i]:
stack.append(i)
elif heights[stack[-1]] == heights[i]:
stack[-1] = i
els... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
"""单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)"""
<|body_0|>
def dp(self, heights):
"""尝试使用动态规划"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
stack = [0]
result = heights[0]
heights = [0] + ... | stack_v2_sparse_classes_36k_train_004808 | 2,027 | no_license | [
{
"docstring": "单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)",
"name": "largestRectangleArea",
"signature": "def largestRectangleArea(self, heights)"
},
{
"docstring": "尝试使用动态规划",
"name": "dp",
"signature": "def dp(self, heights)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020560 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): 单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)
- def dp(self, heights): 尝试使用动态规划 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestRectangleArea(self, heights): 单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)
- def dp(self, heights): 尝试使用动态规划
<|skeleton|>
class Solution:
def largestRectangleArea(self, hei... | be46de7cdd29557c01d4b89f1c2f638e055b6d70 | <|skeleton|>
class Solution:
def largestRectangleArea(self, heights):
"""单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)"""
<|body_0|>
def dp(self, heights):
"""尝试使用动态规划"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def largestRectangleArea(self, heights):
"""单调栈 栈内元素对应的 heights 是从大到小(从栈顶到栈底)"""
stack = [0]
result = heights[0]
heights = [0] + heights + [0]
for i in range(1, len(heights)):
if heights[stack[-1]] < heights[i]:
stack.append(i)
... | the_stack_v2_python_sparse | python/No84.py | OhOHOh/LeetCodePractice | train | 0 | |
d2e06a0adebc7fe5a7f02aee935a55695c7562ff | [
"while i < j:\n if string[i] != string[j]:\n return False\n i += 1\n j -= 1\nreturn True",
"if start == len(string):\n result.append(curr_res[:])\n return\nfor i in range(start, len(string)):\n if self.is_palindrome(string, start, i):\n curr_res.append(string[start:i + 1])\n ... | <|body_start_0|>
while i < j:
if string[i] != string[j]:
return False
i += 1
j -= 1
return True
<|end_body_0|>
<|body_start_1|>
if start == len(string):
result.append(curr_res[:])
return
for i in range(start, le... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def is_palindrome(self, string, i, j):
"""Returns True if string from index i to j is a palindrome, False otherwise."""
<|body_0|>
def find_partition(self, string, start, curr_res, result):
"""Helper function for function partition."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_004809 | 1,712 | no_license | [
{
"docstring": "Returns True if string from index i to j is a palindrome, False otherwise.",
"name": "is_palindrome",
"signature": "def is_palindrome(self, string, i, j)"
},
{
"docstring": "Helper function for function partition.",
"name": "find_partition",
"signature": "def find_partiti... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_palindrome(self, string, i, j): Returns True if string from index i to j is a palindrome, False otherwise.
- def find_partition(self, string, start, curr_res, result): Hel... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_palindrome(self, string, i, j): Returns True if string from index i to j is a palindrome, False otherwise.
- def find_partition(self, string, start, curr_res, result): Hel... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def is_palindrome(self, string, i, j):
"""Returns True if string from index i to j is a palindrome, False otherwise."""
<|body_0|>
def find_partition(self, string, start, curr_res, result):
"""Helper function for function partition."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def is_palindrome(self, string, i, j):
"""Returns True if string from index i to j is a palindrome, False otherwise."""
while i < j:
if string[i] != string[j]:
return False
i += 1
j -= 1
return True
def find_partition(s... | the_stack_v2_python_sparse | Backtracking/palindrome_partitioning.py | vladn90/Algorithms | train | 0 | |
832266a9b594fad872c40bc323f2563ee6432334 | [
"stringX = format(x, 'b').zfill(32)\nstringY = format(y, 'b').zfill(32)\ndistance = 0\nfor i, chX in enumerate(stringX):\n chY = stringY[i]\n if chX != chY:\n distance += 1\nreturn distance",
"totalDistance = 0\nfor i in xrange(len(nums)):\n for j in xrange(i + 1, len(nums)):\n x = nums[i]\... | <|body_start_0|>
stringX = format(x, 'b').zfill(32)
stringY = format(y, 'b').zfill(32)
distance = 0
for i, chX in enumerate(stringX):
chY = stringY[i]
if chX != chY:
distance += 1
return distance
<|end_body_0|>
<|body_start_1|>
tot... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_0|>
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
stringX = format(x, 'b').zfi... | stack_v2_sparse_classes_36k_train_004810 | 1,447 | no_license | [
{
"docstring": ":type x: int :type y: int :rtype: int",
"name": "hammingDistance",
"signature": "def hammingDistance(self, x, y)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "totalHammingDistance",
"signature": "def totalHammingDistance(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hammingDistance(self, x, y): :type x: int :type y: int :rtype: int
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
... | 6fc170c04fadec6966fb7938a07474d4ee107b61 | <|skeleton|>
class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
<|body_0|>
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hammingDistance(self, x, y):
""":type x: int :type y: int :rtype: int"""
stringX = format(x, 'b').zfill(32)
stringY = format(y, 'b').zfill(32)
distance = 0
for i, chX in enumerate(stringX):
chY = stringY[i]
if chX != chY:
... | the_stack_v2_python_sparse | leetcode477.py | JoshuaW1990/leetcode-session1 | train | 0 | |
7ff20d2f3817695fbe07377b00deb27d0b3d0b72 | [
"super().__init__(serialName, debug)\nself.bytesStuffed = 0\nself.createCOM(serialName)\nself.run()",
"stop = False\nwhile not stop:\n print()\n self.getFile()\n self.checkBytes()\n self.buildHead()\n self.packet = self.head + self.fileBA + self.eop\n self.overhead = len(self.packet) / len(self.... | <|body_start_0|>
super().__init__(serialName, debug)
self.bytesStuffed = 0
self.createCOM(serialName)
self.run()
<|end_body_0|>
<|body_start_1|>
stop = False
while not stop:
print()
self.getFile()
self.checkBytes()
self.bui... | Client | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
<|body_0|>
def run(self):
"""Runs all the logic needed to send a file and receive a response."""
<|body_1|>
def checkBytes(sel... | stack_v2_sparse_classes_36k_train_004811 | 12,431 | no_license | [
{
"docstring": "Executed when the object is created. Used to create all needed attributes.",
"name": "__init__",
"signature": "def __init__(self, serialName, debug)"
},
{
"docstring": "Runs all the logic needed to send a file and receive a response.",
"name": "run",
"signature": "def run... | 5 | stack_v2_sparse_classes_30k_test_000229 | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, serialName, debug): Executed when the object is created. Used to create all needed attributes.
- def run(self): Runs all the logic needed to send a file and receiv... | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def __init__(self, serialName, debug): Executed when the object is created. Used to create all needed attributes.
- def run(self): Runs all the logic needed to send a file and receiv... | e8c6ee9672ad33c568d97ec07c3faa6dbf9359ac | <|skeleton|>
class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
<|body_0|>
def run(self):
"""Runs all the logic needed to send a file and receive a response."""
<|body_1|>
def checkBytes(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Client:
def __init__(self, serialName, debug):
"""Executed when the object is created. Used to create all needed attributes."""
super().__init__(serialName, debug)
self.bytesStuffed = 0
self.createCOM(serialName)
self.run()
def run(self):
"""Runs all the lo... | the_stack_v2_python_sparse | Projeto2/aplicacao.py | VFermat/CamadaFisica | train | 1 | |
e0d3fd0e0b7563cdde1016e0236299cb0d3b6369 | [
"self.screen = turtle.Screen()\nself.screen.bgcolor('lightgrey')\nself.turtle = turtle.Turtle(shape='turtle')\nself.turtle.pensize(3)",
"self.turtle.penup()\nself.turtle.setposition(x, y)\nself.turtle.pendown()\nself.turtle.color(color)\nself.turtle.pensize(10)\nself.turtle.circle(radius)",
"positions = [(0, 0,... | <|body_start_0|>
self.screen = turtle.Screen()
self.screen.bgcolor('lightgrey')
self.turtle = turtle.Turtle(shape='turtle')
self.turtle.pensize(3)
<|end_body_0|>
<|body_start_1|>
self.turtle.penup()
self.turtle.setposition(x, y)
self.turtle.pendown()
self... | MyTurtle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyTurtle:
def __init__(self):
"""Turtle Constructor"""
<|body_0|>
def draw_circle(self, x, y, color, radius=50):
"""Moves the turtle to the correct position and draws a circle"""
<|body_1|>
def draw_olympic_symbol(self):
"""Iterates over a set of... | stack_v2_sparse_classes_36k_train_004812 | 1,583 | permissive | [
{
"docstring": "Turtle Constructor",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Moves the turtle to the correct position and draws a circle",
"name": "draw_circle",
"signature": "def draw_circle(self, x, y, color, radius=50)"
},
{
"docstring": "Itera... | 4 | stack_v2_sparse_classes_30k_train_008130 | Implement the Python class `MyTurtle` described below.
Class description:
Implement the MyTurtle class.
Method signatures and docstrings:
- def __init__(self): Turtle Constructor
- def draw_circle(self, x, y, color, radius=50): Moves the turtle to the correct position and draws a circle
- def draw_olympic_symbol(self... | Implement the Python class `MyTurtle` described below.
Class description:
Implement the MyTurtle class.
Method signatures and docstrings:
- def __init__(self): Turtle Constructor
- def draw_circle(self, x, y, color, radius=50): Moves the turtle to the correct position and draws a circle
- def draw_olympic_symbol(self... | 63b448a35c5668790720d0fe414600510b9fe61a | <|skeleton|>
class MyTurtle:
def __init__(self):
"""Turtle Constructor"""
<|body_0|>
def draw_circle(self, x, y, color, radius=50):
"""Moves the turtle to the correct position and draws a circle"""
<|body_1|>
def draw_olympic_symbol(self):
"""Iterates over a set of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyTurtle:
def __init__(self):
"""Turtle Constructor"""
self.screen = turtle.Screen()
self.screen.bgcolor('lightgrey')
self.turtle = turtle.Turtle(shape='turtle')
self.turtle.pensize(3)
def draw_circle(self, x, y, color, radius=50):
"""Moves the turtle to th... | the_stack_v2_python_sparse | algorithm/python-algorithm/other-tools/turtle-graphics/drawOlypicSymbol.py | wangdingqiao/programmer-evolution-plan | train | 4 | |
50d44d0369da919acc494f6e9d7c2a2383474c61 | [
"contacts = self.load('contact_info', {})\ncontacts[message.sender.handle] = {'info': contact_info, 'name': message.sender.name}\nself.save('contact_info', contacts)\nself.say('Got it.', message=message)",
"contacts = self.load('contact_info', {})\ncontext = {'contacts': contacts}\ncontact_html = rendered_templat... | <|body_start_0|>
contacts = self.load('contact_info', {})
contacts[message.sender.handle] = {'info': contact_info, 'name': message.sender.name}
self.save('contact_info', contacts)
self.say('Got it.', message=message)
<|end_body_0|>
<|body_start_1|>
contacts = self.load('contact_... | EmergencyContactsPlugin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmergencyContactsPlugin:
def set_my_info(self, message, contact_info=''):
"""set my contact info to ____: Set your emergency contact info."""
<|body_0|>
def respond_to_contact_info(self, message):
"""contact info: Show everyone's emergency contact info."""
<|... | stack_v2_sparse_classes_36k_train_004813 | 1,049 | permissive | [
{
"docstring": "set my contact info to ____: Set your emergency contact info.",
"name": "set_my_info",
"signature": "def set_my_info(self, message, contact_info='')"
},
{
"docstring": "contact info: Show everyone's emergency contact info.",
"name": "respond_to_contact_info",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_018581 | Implement the Python class `EmergencyContactsPlugin` described below.
Class description:
Implement the EmergencyContactsPlugin class.
Method signatures and docstrings:
- def set_my_info(self, message, contact_info=''): set my contact info to ____: Set your emergency contact info.
- def respond_to_contact_info(self, m... | Implement the Python class `EmergencyContactsPlugin` described below.
Class description:
Implement the EmergencyContactsPlugin class.
Method signatures and docstrings:
- def set_my_info(self, message, contact_info=''): set my contact info to ____: Set your emergency contact info.
- def respond_to_contact_info(self, m... | 27a23ce47e3ec11b94f3355c2d2ee94c1958679c | <|skeleton|>
class EmergencyContactsPlugin:
def set_my_info(self, message, contact_info=''):
"""set my contact info to ____: Set your emergency contact info."""
<|body_0|>
def respond_to_contact_info(self, message):
"""contact info: Show everyone's emergency contact info."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EmergencyContactsPlugin:
def set_my_info(self, message, contact_info=''):
"""set my contact info to ____: Set your emergency contact info."""
contacts = self.load('contact_info', {})
contacts[message.sender.handle] = {'info': contact_info, 'name': message.sender.name}
self.save... | the_stack_v2_python_sparse | will/plugins/devops/emergency_contacts.py | skoczen/will | train | 359 | |
cc6a00b13cb5b167ea90298332034e3927bc856b | [
"l_icd = InternetConnectionData()\nl_xml = p_pyhouse_obj.Xml.XmlRoot\ntry:\n l_xml = l_xml.find('ComputerDivision')\n if l_xml == None:\n return l_icd\n l_internet_sect_xml = l_xml.find('InternetSection')\nexcept AttributeError as e_err:\n l_internet_sect_xml = None\n LOG.error('Internet secti... | <|body_start_0|>
l_icd = InternetConnectionData()
l_xml = p_pyhouse_obj.Xml.XmlRoot
try:
l_xml = l_xml.find('ComputerDivision')
if l_xml == None:
return l_icd
l_internet_sect_xml = l_xml.find('InternetSection')
except AttributeError as ... | API | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class API:
def read_internet_xml(self, p_pyhouse_obj):
"""Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element"""
<|body_0|>
def write_internet_xml(self, p_internet_obj):
"""Create a sub tree for... | stack_v2_sparse_classes_36k_train_004814 | 4,554 | permissive | [
{
"docstring": "Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element",
"name": "read_internet_xml",
"signature": "def read_internet_xml(self, p_pyhouse_obj)"
},
{
"docstring": "Create a sub tree for 'Internet' - the su... | 2 | stack_v2_sparse_classes_30k_train_012369 | Implement the Python class `API` described below.
Class description:
Implement the API class.
Method signatures and docstrings:
- def read_internet_xml(self, p_pyhouse_obj): Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element
- def write_i... | Implement the Python class `API` described below.
Class description:
Implement the API class.
Method signatures and docstrings:
- def read_internet_xml(self, p_pyhouse_obj): Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element
- def write_i... | 6444ed0b4c38ab59b9e419e4d54d65d598e6a54e | <|skeleton|>
class API:
def read_internet_xml(self, p_pyhouse_obj):
"""Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element"""
<|body_0|>
def write_internet_xml(self, p_internet_obj):
"""Create a sub tree for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class API:
def read_internet_xml(self, p_pyhouse_obj):
"""Reads zero or more <Internet> entries within the <InternetSection> @param p_internet_section_xml: is the <InternetSection> element"""
l_icd = InternetConnectionData()
l_xml = p_pyhouse_obj.Xml.XmlRoot
try:
l_xml = ... | the_stack_v2_python_sparse | src/Modules/Computer/Internet/internet_xml.py | bopopescu/PyHouse_1 | train | 0 | |
eeff7d8398e41d3b464f7fbe3240a59588c1cea5 | [
"length = len(nums)\noutput = [1] * length\nleft = 1\nright = 1\nfor i in range(0, length - 1):\n left = left * nums[i]\n output[i + 1] = output[i + 1] * left\nfor i in range(length - 1, 0, -1):\n right = right * nums[i]\n output[i - 1] = output[i - 1] * right\nreturn output",
"numForZero = 0\nproduct... | <|body_start_0|>
length = len(nums)
output = [1] * length
left = 1
right = 1
for i in range(0, length - 1):
left = left * nums[i]
output[i + 1] = output[i + 1] * left
for i in range(length - 1, 0, -1):
right = right * nums[i]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf_1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = len(nums)
... | stack_v2_sparse_classes_36k_train_004815 | 1,925 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf",
"signature": "def productExceptSelf(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "productExceptSelf_1",
"signature": "def productExceptSelf_1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017980 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf_1(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def productExceptSelf(self, nums): :type nums: List[int] :rtype: List[int]
- def productExceptSelf_1(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Solu... | ba58ac60b32e261e43482d7e71b32587700e3719 | <|skeleton|>
class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def productExceptSelf_1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def productExceptSelf(self, nums):
""":type nums: List[int] :rtype: List[int]"""
length = len(nums)
output = [1] * length
left = 1
right = 1
for i in range(0, length - 1):
left = left * nums[i]
output[i + 1] = output[i + 1] * le... | the_stack_v2_python_sparse | python/238_product_of_array_except_self.py | lingng/Leetcode | train | 0 | |
9377d4901bc563fee6c99a6caadccba0f29b8907 | [
"self.master = master\nmaster.grid_rowconfigure(0, weight=1)\nmaster.grid_columnconfigure(0, weight=1)\nself.main_frame = tkin.Frame(master, bg='#1e1e1e')\nself.main_frame.grid(row=0, column=0, sticky='nsew')\nself._invis_pic = tkin.PhotoImage(width=1, height=1)",
"self.master.bind('<Tab>', self.toggle_menu)\nsel... | <|body_start_0|>
self.master = master
master.grid_rowconfigure(0, weight=1)
master.grid_columnconfigure(0, weight=1)
self.main_frame = tkin.Frame(master, bg='#1e1e1e')
self.main_frame.grid(row=0, column=0, sticky='nsew')
self._invis_pic = tkin.PhotoImage(width=1, height=1... | Class for easily importing a menu system. | MainWindow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MainWindow:
"""Class for easily importing a menu system."""
def __init__(self, master):
"""Set default parameters on initialization."""
<|body_0|>
def initialize_menu(self, title=''):
"""Create menu system."""
<|body_1|>
def toggle_menu(self, event):... | stack_v2_sparse_classes_36k_train_004816 | 3,599 | no_license | [
{
"docstring": "Set default parameters on initialization.",
"name": "__init__",
"signature": "def __init__(self, master)"
},
{
"docstring": "Create menu system.",
"name": "initialize_menu",
"signature": "def initialize_menu(self, title='')"
},
{
"docstring": "Toggle menu displaye... | 3 | stack_v2_sparse_classes_30k_train_020698 | Implement the Python class `MainWindow` described below.
Class description:
Class for easily importing a menu system.
Method signatures and docstrings:
- def __init__(self, master): Set default parameters on initialization.
- def initialize_menu(self, title=''): Create menu system.
- def toggle_menu(self, event): Tog... | Implement the Python class `MainWindow` described below.
Class description:
Class for easily importing a menu system.
Method signatures and docstrings:
- def __init__(self, master): Set default parameters on initialization.
- def initialize_menu(self, title=''): Create menu system.
- def toggle_menu(self, event): Tog... | e452817429195593e9c7cd89fe052bd8ed89943a | <|skeleton|>
class MainWindow:
"""Class for easily importing a menu system."""
def __init__(self, master):
"""Set default parameters on initialization."""
<|body_0|>
def initialize_menu(self, title=''):
"""Create menu system."""
<|body_1|>
def toggle_menu(self, event):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MainWindow:
"""Class for easily importing a menu system."""
def __init__(self, master):
"""Set default parameters on initialization."""
self.master = master
master.grid_rowconfigure(0, weight=1)
master.grid_columnconfigure(0, weight=1)
self.main_frame = tkin.Frame(... | the_stack_v2_python_sparse | project_timeline/assets/menu.py | Keiyrti/python_projects | train | 0 |
2f7f96651680258aa1de5c4fc824f47e7c2f92cb | [
"Module.__init__(self)\nself.row = -1\nself.col = -1\nself.rowSpan = -1\nself.colSpan = -1\nself.sheetReference = None",
"def set_row_col(row, col):\n try:\n self.col = ord(col) - ord('A')\n self.row = int(row) - 1\n except:\n raise ModuleError(self, 'ColumnRowAddress format error')\nre... | <|body_start_0|>
Module.__init__(self)
self.row = -1
self.col = -1
self.rowSpan = -1
self.colSpan = -1
self.sheetReference = None
<|end_body_0|>
<|body_start_1|>
def set_row_col(row, col):
try:
self.col = ord(col) - ord('A')
... | CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location | CellLocation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CellLocation:
"""CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location"""
def __init__(self):
"""CellLocation() -> CellLocation Instantiate an empty cell location, i.e. any available cell"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_004817 | 10,309 | permissive | [
{
"docstring": "CellLocation() -> CellLocation Instantiate an empty cell location, i.e. any available cell",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "compute() -> None Translate input ports into (row, column) location",
"name": "compute",
"signature": "def... | 2 | null | Implement the Python class `CellLocation` described below.
Class description:
CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location
Method signatures and docstrings:
- def __init__(self): CellLocation() -> CellLocation Instantiate an empty cel... | Implement the Python class `CellLocation` described below.
Class description:
CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location
Method signatures and docstrings:
- def __init__(self): CellLocation() -> CellLocation Instantiate an empty cel... | 23ef56ec24b85c82416e1437a08381635328abe5 | <|skeleton|>
class CellLocation:
"""CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location"""
def __init__(self):
"""CellLocation() -> CellLocation Instantiate an empty cell location, i.e. any available cell"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CellLocation:
"""CellLocation is a Vistrail Module that allow users to specify where to put a visualization on a sheet, i.e. row, column location"""
def __init__(self):
"""CellLocation() -> CellLocation Instantiate an empty cell location, i.e. any available cell"""
Module.__init__(self)
... | the_stack_v2_python_sparse | vistrails_current/vistrails/packages/spreadsheet/basic_widgets.py | lumig242/VisTrailsRecommendation | train | 3 |
341d162608288e729940124af1ae357f3ccc90e4 | [
"page = request.args.get('page', 1, type=int)\nper_page = current_app.config['AWESOME_POST_PER_PAGE']\npagination = Post.query.with_parent(g.current_user).paginate(page, per_page)\nposts = pagination.items\ncurrent = url_for('.current_user_posts', page=page, _external=True)\nprev = None\nif pagination.has_prev:\n ... | <|body_start_0|>
page = request.args.get('page', 1, type=int)
per_page = current_app.config['AWESOME_POST_PER_PAGE']
pagination = Post.query.with_parent(g.current_user).paginate(page, per_page)
posts = pagination.items
current = url_for('.current_user_posts', page=page, _external... | CurrentUserPostsAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CurrentUserPostsAPI:
def get(self):
"""Get current user's all posts."""
<|body_0|>
def post(self):
"""Create new post."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
page = request.args.get('page', 1, type=int)
per_page = current_app.config... | stack_v2_sparse_classes_36k_train_004818 | 7,567 | permissive | [
{
"docstring": "Get current user's all posts.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Create new post.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008380 | Implement the Python class `CurrentUserPostsAPI` described below.
Class description:
Implement the CurrentUserPostsAPI class.
Method signatures and docstrings:
- def get(self): Get current user's all posts.
- def post(self): Create new post. | Implement the Python class `CurrentUserPostsAPI` described below.
Class description:
Implement the CurrentUserPostsAPI class.
Method signatures and docstrings:
- def get(self): Get current user's all posts.
- def post(self): Create new post.
<|skeleton|>
class CurrentUserPostsAPI:
def get(self):
"""Get ... | dd5cf5f1ae9df0d2d25e41c113df50b16a8465e7 | <|skeleton|>
class CurrentUserPostsAPI:
def get(self):
"""Get current user's all posts."""
<|body_0|>
def post(self):
"""Create new post."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CurrentUserPostsAPI:
def get(self):
"""Get current user's all posts."""
page = request.args.get('page', 1, type=int)
per_page = current_app.config['AWESOME_POST_PER_PAGE']
pagination = Post.query.with_parent(g.current_user).paginate(page, per_page)
posts = pagination.it... | the_stack_v2_python_sparse | awesome_flask_webapp/apis/v1/resources.py | yeh-George/awesome-flask-webapp | train | 0 | |
e7085d064b12f79c494c6e711c10d8c47f98ac1b | [
"self.widgetConfigs = ConvertConfigsToDictionary(widgetConfigs)\nself.modConfigs = ConvertConfigsToDictionary(modConfigs)\nself.positioningConfigs = ConvertConfigsToDictionary(positioningConfigs)\nself.sizingConfigs = ConvertConfigsToDictionary(sizingConfigs)\nself.serviceConfigs = ConvertConfigsToDictionary(servic... | <|body_start_0|>
self.widgetConfigs = ConvertConfigsToDictionary(widgetConfigs)
self.modConfigs = ConvertConfigsToDictionary(modConfigs)
self.positioningConfigs = ConvertConfigsToDictionary(positioningConfigs)
self.sizingConfigs = ConvertConfigsToDictionary(sizingConfigs)
self.se... | Represents the configuration for a knot package | PackageConfig | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PackageConfig:
"""Represents the configuration for a knot package"""
def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs):
"""Initialize the widget config with its widgets, positioning policies and sizing policies"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_004819 | 957 | no_license | [
{
"docstring": "Initialize the widget config with its widgets, positioning policies and sizing policies",
"name": "__init__",
"signature": "def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs)"
},
{
"docstring": "Set the package filename",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_004384 | Implement the Python class `PackageConfig` described below.
Class description:
Represents the configuration for a knot package
Method signatures and docstrings:
- def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs): Initialize the widget config with its widgets, positionin... | Implement the Python class `PackageConfig` described below.
Class description:
Represents the configuration for a knot package
Method signatures and docstrings:
- def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs): Initialize the widget config with its widgets, positionin... | 19b7bf08658ce329c7b076ce2014bae9f5f09268 | <|skeleton|>
class PackageConfig:
"""Represents the configuration for a knot package"""
def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs):
"""Initialize the widget config with its widgets, positioning policies and sizing policies"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PackageConfig:
"""Represents the configuration for a knot package"""
def __init__(self, widgetConfigs, modConfigs, positioningConfigs, sizingConfigs, serviceConfigs):
"""Initialize the widget config with its widgets, positioning policies and sizing policies"""
self.widgetConfigs = Convert... | the_stack_v2_python_sparse | src/knot/loader/config/package_config.py | cloew/Knot | train | 1 |
f0bdc18bbdc65c9e968d24215b8e50bef2352cc7 | [
"super(Conv1dSubsampling3, self).__init__()\nself.conv = torch.nn.Sequential(torch.nn.Conv1d(idim, odim, 3, 1), torch.nn.ReLU(), torch.nn.Conv1d(odim, odim, 5, 3), torch.nn.ReLU())\nself.out = torch.nn.Sequential(torch.nn.Linear(odim, odim), pos_enc if pos_enc is not None else PositionalEncoding(odim, dropout_rate)... | <|body_start_0|>
super(Conv1dSubsampling3, self).__init__()
self.conv = torch.nn.Sequential(torch.nn.Conv1d(idim, odim, 3, 1), torch.nn.ReLU(), torch.nn.Conv1d(odim, odim, 5, 3), torch.nn.ReLU())
self.out = torch.nn.Sequential(torch.nn.Linear(odim, odim), pos_enc if pos_enc is not None else Posi... | Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer. | Conv1dSubsampling3 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv1dSubsampling3:
"""Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k_train_004820 | 14,351 | permissive | [
{
"docstring": "Construct an Conv1dSubsampling3 object.",
"name": "__init__",
"signature": "def __init__(self, idim, odim, dropout_rate, pos_enc=None)"
},
{
"docstring": "Subsample x. Args: x (torch.Tensor): Input tensor (#batch, time, idim). x_mask (torch.Tensor): Input mask (#batch, 1, time). ... | 3 | null | Implement the Python class `Conv1dSubsampling3` described below.
Class description:
Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.
Method signatures and docstr... | Implement the Python class `Conv1dSubsampling3` described below.
Class description:
Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer.
Method signatures and docstr... | bcd20948db7846ee523443ef9fd78c7a1248c95e | <|skeleton|>
class Conv1dSubsampling3:
"""Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv1dSubsampling3:
"""Convolutional 1D subsampling (to 1/3 length). Args: idim (int): Input dimension. odim (int): Output dimension. dropout_rate (float): Dropout rate. pos_enc (torch.nn.Module): Custom position encoding layer."""
def __init__(self, idim, odim, dropout_rate, pos_enc=None):
"""Co... | the_stack_v2_python_sparse | espnet/nets/pytorch_backend/transformer/subsampling.py | espnet/espnet | train | 7,242 |
50ca28b928217194aab707c2587d4deefde3e3b2 | [
"v = 2.0\nr = utils.squared(v)\nself.assertTrue(r == 2.0 * 2.0)",
"v = 2.0\nr = utils.cubed(v)\nself.assertTrue(r == 2.0 * 2.0 * 2.0)"
] | <|body_start_0|>
v = 2.0
r = utils.squared(v)
self.assertTrue(r == 2.0 * 2.0)
<|end_body_0|>
<|body_start_1|>
v = 2.0
r = utils.cubed(v)
self.assertTrue(r == 2.0 * 2.0 * 2.0)
<|end_body_1|>
| Unit tests to check utils | TestUtils | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestUtils:
"""Unit tests to check utils"""
def test_squared(self):
"""test passable squaring"""
<|body_0|>
def test_cubed(self):
"""test passable cubing"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
v = 2.0
r = utils.squared(v)
... | stack_v2_sparse_classes_36k_train_004821 | 529 | permissive | [
{
"docstring": "test passable squaring",
"name": "test_squared",
"signature": "def test_squared(self)"
},
{
"docstring": "test passable cubing",
"name": "test_cubed",
"signature": "def test_cubed(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015709 | Implement the Python class `TestUtils` described below.
Class description:
Unit tests to check utils
Method signatures and docstrings:
- def test_squared(self): test passable squaring
- def test_cubed(self): test passable cubing | Implement the Python class `TestUtils` described below.
Class description:
Unit tests to check utils
Method signatures and docstrings:
- def test_squared(self): test passable squaring
- def test_cubed(self): test passable cubing
<|skeleton|>
class TestUtils:
"""Unit tests to check utils"""
def test_squared(... | d95952d48c01866ee44ff40814c49e0fbd2489ad | <|skeleton|>
class TestUtils:
"""Unit tests to check utils"""
def test_squared(self):
"""test passable squaring"""
<|body_0|>
def test_cubed(self):
"""test passable cubing"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestUtils:
"""Unit tests to check utils"""
def test_squared(self):
"""test passable squaring"""
v = 2.0
r = utils.squared(v)
self.assertTrue(r == 2.0 * 2.0)
def test_cubed(self):
"""test passable cubing"""
v = 2.0
r = utils.cubed(v)
sel... | the_stack_v2_python_sparse | XcMath_Tests/test_utils.py | Iwan-Zotow/runEGS | train | 2 |
739b536a345bfca29f875fc78d6b8a083759b866 | [
"self.procfile = procfile\nself.interval = interval\nself._server = server\nself.lastresult = None\nserver.post_event(yapc.priv_callback(self), 0)",
"if isinstance(event, yapc.priv_callback):\n output.vdbg(self.get_stat())\n self._server.post_event(yapc.priv_callback(self), self.interval)\nreturn True",
"... | <|body_start_0|>
self.procfile = procfile
self.interval = interval
self._server = server
self.lastresult = None
server.post_event(yapc.priv_callback(self), 0)
<|end_body_0|>
<|body_start_1|>
if isinstance(event, yapc.priv_callback):
output.vdbg(self.get_stat(... | Class to look at current statistics of interfaces @author ykk @date Auguest 2011 | interface_stat | [
"LicenseRef-scancode-x11-stanford"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class interface_stat:
"""Class to look at current statistics of interfaces @author ykk @date Auguest 2011"""
def __init__(self, server, interval=5, procfile='/proc/net/dev'):
"""Initialize @param server yapc core @param interval interval to look @param procfile file to look into"""
... | stack_v2_sparse_classes_36k_train_004822 | 8,177 | permissive | [
{
"docstring": "Initialize @param server yapc core @param interval interval to look @param procfile file to look into",
"name": "__init__",
"signature": "def __init__(self, server, interval=5, procfile='/proc/net/dev')"
},
{
"docstring": "Process event @param event event to process @return True"... | 4 | null | Implement the Python class `interface_stat` described below.
Class description:
Class to look at current statistics of interfaces @author ykk @date Auguest 2011
Method signatures and docstrings:
- def __init__(self, server, interval=5, procfile='/proc/net/dev'): Initialize @param server yapc core @param interval inte... | Implement the Python class `interface_stat` described below.
Class description:
Class to look at current statistics of interfaces @author ykk @date Auguest 2011
Method signatures and docstrings:
- def __init__(self, server, interval=5, procfile='/proc/net/dev'): Initialize @param server yapc core @param interval inte... | c3f5a31b74d5587671329eea9582ac8aed0c58a4 | <|skeleton|>
class interface_stat:
"""Class to look at current statistics of interfaces @author ykk @date Auguest 2011"""
def __init__(self, server, interval=5, procfile='/proc/net/dev'):
"""Initialize @param server yapc core @param interval interval to look @param procfile file to look into"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class interface_stat:
"""Class to look at current statistics of interfaces @author ykk @date Auguest 2011"""
def __init__(self, server, interval=5, procfile='/proc/net/dev'):
"""Initialize @param server yapc core @param interval interval to look @param procfile file to look into"""
self.procfil... | the_stack_v2_python_sparse | yapc/local/networkstate.py | yapkke/yapc | train | 1 |
30e3ca8b72cc31243d061348299db2db33ef26de | [
"self._quantile_value = quantile_value\nself._comparator_fn = comparator_fn\nself._error_loss_fn = functools.partial(loss_utils.pinball_loss, quantile=quantile)\nsuper(QuantileConstraint, self).__init__(time_step_spec, action_spec, constraint_network, error_loss_fn=self._error_loss_fn, name=name)",
"predicted_qua... | <|body_start_0|>
self._quantile_value = quantile_value
self._comparator_fn = comparator_fn
self._error_loss_fn = functools.partial(loss_utils.pinball_loss, quantile=quantile)
super(QuantileConstraint, self).__init__(time_step_spec, action_spec, constraint_network, error_loss_fn=self._err... | Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ``` | QuantileConstraint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuantileConstraint:
"""Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ```"""
def __init__(self, time_step_spec: types.TimeStep, action_spec: types.BoundedTensorSpec, constraint_... | stack_v2_sparse_classes_36k_train_004823 | 22,532 | permissive | [
{
"docstring": "Creates a trainable quantile constraint using a neural network. Args: time_step_spec: A `TimeStep` spec of the expected time_steps. action_spec: A nest of `BoundedTensorSpec` representing the actions. constraint_network: An instance of `tf_agents.network.Network` used to provide estimates of act... | 2 | null | Implement the Python class `QuantileConstraint` described below.
Class description:
Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ```
Method signatures and docstrings:
- def __init__(self, time_step_spe... | Implement the Python class `QuantileConstraint` described below.
Class description:
Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ```
Method signatures and docstrings:
- def __init__(self, time_step_spe... | eca1093d3a047e538f17f6ab92ab4d8144284f23 | <|skeleton|>
class QuantileConstraint:
"""Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ```"""
def __init__(self, time_step_spec: types.TimeStep, action_spec: types.BoundedTensorSpec, constraint_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuantileConstraint:
"""Class for representing a trainable quantile constraint. This constraint class implements a quantile constraint such as ``` Q_tau(x) >= v ``` or ``` Q_tau(x) <= v ```"""
def __init__(self, time_step_spec: types.TimeStep, action_spec: types.BoundedTensorSpec, constraint_network: type... | the_stack_v2_python_sparse | tf_agents/bandits/policies/constraints.py | tensorflow/agents | train | 2,755 |
82bb39dbb7391161dd61f37312a2e56b4923b0f9 | [
"email = self.request.get('email')\npassword = self.request.get('password')\nif self.dstore.is_user_cloud_admin():\n success, message = self.helper.change_password(cgi.escape(email), cgi.escape(password))\nelse:\n success = False\n message = 'Only the cloud administrator can change passwords.'\nflash_messa... | <|body_start_0|>
email = self.request.get('email')
password = self.request.get('password')
if self.dstore.is_user_cloud_admin():
success, message = self.helper.change_password(cgi.escape(email), cgi.escape(password))
else:
success = False
message = 'On... | Class to handle user password changes. | ChangePasswordPage | [
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChangePasswordPage:
"""Class to handle user password changes."""
def post(self):
"""Handler for POST requests."""
<|body_0|>
def get(self):
"""Handler for GET requests."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
email = self.request.get('em... | stack_v2_sparse_classes_36k_train_004824 | 37,207 | permissive | [
{
"docstring": "Handler for POST requests.",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "Handler for GET requests.",
"name": "get",
"signature": "def get(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000036 | Implement the Python class `ChangePasswordPage` described below.
Class description:
Class to handle user password changes.
Method signatures and docstrings:
- def post(self): Handler for POST requests.
- def get(self): Handler for GET requests. | Implement the Python class `ChangePasswordPage` described below.
Class description:
Class to handle user password changes.
Method signatures and docstrings:
- def post(self): Handler for POST requests.
- def get(self): Handler for GET requests.
<|skeleton|>
class ChangePasswordPage:
"""Class to handle user passw... | aa36e8dfaa295d53bec616ed07f91ec8c02fa4e1 | <|skeleton|>
class ChangePasswordPage:
"""Class to handle user password changes."""
def post(self):
"""Handler for POST requests."""
<|body_0|>
def get(self):
"""Handler for GET requests."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChangePasswordPage:
"""Class to handle user password changes."""
def post(self):
"""Handler for POST requests."""
email = self.request.get('email')
password = self.request.get('password')
if self.dstore.is_user_cloud_admin():
success, message = self.helper.chan... | the_stack_v2_python_sparse | AppDashboard/dashboard.py | shatterednirvana/appscale | train | 6 |
a81e15bfb0b8d4fe83832d10b6856ef22a314158 | [
"self.datastore_not_unmounted_reason = datastore_not_unmounted_reason\nself.datastore_unmounted = datastore_unmounted\nself.destroy_cloned_entity_info_vec = destroy_cloned_entity_info_vec\nself.mtype = mtype\nself.view_deleted = view_deleted",
"if dictionary is None:\n return None\ndatastore_not_unmounted_reas... | <|body_start_0|>
self.datastore_not_unmounted_reason = datastore_not_unmounted_reason
self.datastore_unmounted = datastore_unmounted
self.destroy_cloned_entity_info_vec = destroy_cloned_entity_info_vec
self.mtype = mtype
self.view_deleted = view_deleted
<|end_body_0|>
<|body_sta... | Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto extension Location Extension =================================================================... | DestroyClonedVMTaskInfoProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DestroyClonedVMTaskInfoProto:
"""Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto extension Location Extension =========... | stack_v2_sparse_classes_36k_train_004825 | 3,980 | permissive | [
{
"docstring": "Constructor for the DestroyClonedVMTaskInfoProto class",
"name": "__init__",
"signature": "def __init__(self, datastore_not_unmounted_reason=None, datastore_unmounted=None, destroy_cloned_entity_info_vec=None, mtype=None, view_deleted=None)"
},
{
"docstring": "Creates an instance... | 2 | stack_v2_sparse_classes_30k_train_019578 | Implement the Python class `DestroyClonedVMTaskInfoProto` described below.
Class description:
Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto... | Implement the Python class `DestroyClonedVMTaskInfoProto` described below.
Class description:
Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DestroyClonedVMTaskInfoProto:
"""Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto extension Location Extension =========... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DestroyClonedVMTaskInfoProto:
"""Implementation of the 'DestroyClonedVMTaskInfoProto' model. Each available extension is listed below along with the location of the proto file (relative to magneto/connectors) where it is defined. DestroyClonedVMTaskInfoProto extension Location Extension ======================... | the_stack_v2_python_sparse | cohesity_management_sdk/models/destroy_cloned_vm_task_info_proto.py | cohesity/management-sdk-python | train | 24 |
62dc8751e5bdeb435927fa839742fb29507d4590 | [
"self.row = 0\nself.col = 0\nself.vec2d = vec2d",
"self.hasNext()\nresult = self.vec2d[self.row][self.col]\nself.col += 1\nreturn result",
"while self.row < len(self.vec2d):\n if self.col < len(self.vec2d[self.row]):\n return True\n self.col = 0\n self.row += 1\nreturn False"
] | <|body_start_0|>
self.row = 0
self.col = 0
self.vec2d = vec2d
<|end_body_0|>
<|body_start_1|>
self.hasNext()
result = self.vec2d[self.row][self.col]
self.col += 1
return result
<|end_body_1|>
<|body_start_2|>
while self.row < len(self.vec2d):
... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_004826 | 1,783 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | null | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | d953abe2c9680f636563e76287d2f907e90ced63 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.row = 0
self.col = 0
self.vec2d = vec2d
def next(self):
""":rtype: int"""
self.hasNext()
result = self.vec2d[self.row][self.col]
... | the_stack_v2_python_sparse | Python_leetcode/251_flatten_2d_vector.py | xiangcao/Leetcode | train | 0 | |
da363f0d53d4c8a2cbcf70b3d3f4aaa6253fcce3 | [
"alarm = self.get_object()\ndate = alarm.alarm_time.strftime('%Y-%m-%d %H:%M:%S')\nreturn Response({'time': date})",
"queryset = Alarm.objects.all()\nquery_date = self.request.query_params.get('date', None)\nquery_user = self.request.query_params.get('username', None)\nif query_date is not None:\n date = datet... | <|body_start_0|>
alarm = self.get_object()
date = alarm.alarm_time.strftime('%Y-%m-%d %H:%M:%S')
return Response({'time': date})
<|end_body_0|>
<|body_start_1|>
queryset = Alarm.objects.all()
query_date = self.request.query_params.get('date', None)
query_user = self.requ... | AlarmViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlarmViewSet:
def js_time(self, request, pk=None):
"""Returns datetimefield as js accepted time"""
<|body_0|>
def get_queryset(self):
"""Allows queryset to be filtered by alarms for given date"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
alarm = ... | stack_v2_sparse_classes_36k_train_004827 | 14,885 | no_license | [
{
"docstring": "Returns datetimefield as js accepted time",
"name": "js_time",
"signature": "def js_time(self, request, pk=None)"
},
{
"docstring": "Allows queryset to be filtered by alarms for given date",
"name": "get_queryset",
"signature": "def get_queryset(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000408 | Implement the Python class `AlarmViewSet` described below.
Class description:
Implement the AlarmViewSet class.
Method signatures and docstrings:
- def js_time(self, request, pk=None): Returns datetimefield as js accepted time
- def get_queryset(self): Allows queryset to be filtered by alarms for given date | Implement the Python class `AlarmViewSet` described below.
Class description:
Implement the AlarmViewSet class.
Method signatures and docstrings:
- def js_time(self, request, pk=None): Returns datetimefield as js accepted time
- def get_queryset(self): Allows queryset to be filtered by alarms for given date
<|skelet... | bf0cffd77e0b745a625033134267b56e40595875 | <|skeleton|>
class AlarmViewSet:
def js_time(self, request, pk=None):
"""Returns datetimefield as js accepted time"""
<|body_0|>
def get_queryset(self):
"""Allows queryset to be filtered by alarms for given date"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlarmViewSet:
def js_time(self, request, pk=None):
"""Returns datetimefield as js accepted time"""
alarm = self.get_object()
date = alarm.alarm_time.strftime('%Y-%m-%d %H:%M:%S')
return Response({'time': date})
def get_queryset(self):
"""Allows queryset to be filte... | the_stack_v2_python_sparse | sleepsite/views.py | gracez72/sleepAppBackend | train | 0 | |
a67513f277511b882cb7d915c72ee52d4a728f86 | [
"self.img_width = img_width\nself.img_height = img_height\nself.flip_horiz = flip_horiz\nself.inter = inter",
"crops = []\nheight, width = image.shape[:2]\ncorners = [[0, 0, self.img_width, self.img_height], [width - self.img_width, 0, width, self.img_height], [width - self.img_width, height - self.img_height, wi... | <|body_start_0|>
self.img_width = img_width
self.img_height = img_height
self.flip_horiz = flip_horiz
self.inter = inter
<|end_body_0|>
<|body_start_1|>
crops = []
height, width = image.shape[:2]
corners = [[0, 0, self.img_width, self.img_height], [width - self.i... | CropPreprocessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CropPreprocessor:
def __init__(self, img_width, img_height, flip_horiz=True, inter=cv2.INTER_AREA):
"""Initialise the class :param img_width: desired image width :param img_height: desired image height :param flip_horiz: whether horizontal flips are also required :param inter: desired in... | stack_v2_sparse_classes_36k_train_004828 | 2,378 | no_license | [
{
"docstring": "Initialise the class :param img_width: desired image width :param img_height: desired image height :param flip_horiz: whether horizontal flips are also required :param inter: desired interpolation method",
"name": "__init__",
"signature": "def __init__(self, img_width, img_height, flip_h... | 2 | stack_v2_sparse_classes_30k_train_013294 | Implement the Python class `CropPreprocessor` described below.
Class description:
Implement the CropPreprocessor class.
Method signatures and docstrings:
- def __init__(self, img_width, img_height, flip_horiz=True, inter=cv2.INTER_AREA): Initialise the class :param img_width: desired image width :param img_height: de... | Implement the Python class `CropPreprocessor` described below.
Class description:
Implement the CropPreprocessor class.
Method signatures and docstrings:
- def __init__(self, img_width, img_height, flip_horiz=True, inter=cv2.INTER_AREA): Initialise the class :param img_width: desired image width :param img_height: de... | e9f2010715fa06f50095d05684617c86e18ca661 | <|skeleton|>
class CropPreprocessor:
def __init__(self, img_width, img_height, flip_horiz=True, inter=cv2.INTER_AREA):
"""Initialise the class :param img_width: desired image width :param img_height: desired image height :param flip_horiz: whether horizontal flips are also required :param inter: desired in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CropPreprocessor:
def __init__(self, img_width, img_height, flip_horiz=True, inter=cv2.INTER_AREA):
"""Initialise the class :param img_width: desired image width :param img_height: desired image height :param flip_horiz: whether horizontal flips are also required :param inter: desired interpolation me... | the_stack_v2_python_sparse | dltoolkit/preprocess/crop.py | GeoffBreemer/DLToolkit | train | 2 | |
ad817589c8a0344ed687beb385b63cad7b1757ab | [
"super().__init__()\nchannels, img_size, _ = img_shape\nmodel = [torch.nn.Conv2d(channels + c_dim, 64, 7, stride=1, padding=3, bias=False), torch.nn.InstanceNorm2d(64, affine=True, track_running_stats=True), torch.nn.ReLU(inplace=True)]\ncurr_dim = 64\nfor _ in range(2):\n model += [torch.nn.Conv2d(curr_dim, cur... | <|body_start_0|>
super().__init__()
channels, img_size, _ = img_shape
model = [torch.nn.Conv2d(channels + c_dim, 64, 7, stride=1, padding=3, bias=False), torch.nn.InstanceNorm2d(64, affine=True, track_running_stats=True), torch.nn.ReLU(inplace=True)]
curr_dim = 64
for _ in range(... | The Residual Generator | GeneratorResNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneratorResNet:
"""The Residual Generator"""
def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5):
"""Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimension, but not the batch dimension res_blocks : int number of... | stack_v2_sparse_classes_36k_train_004829 | 6,187 | permissive | [
{
"docstring": "Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimension, but not the batch dimension res_blocks : int number of residual blocks c_dim : int size of the code dimension",
"name": "__init__",
"signature": "def __init__(self, img_shape=... | 2 | stack_v2_sparse_classes_30k_train_003036 | Implement the Python class `GeneratorResNet` described below.
Class description:
The Residual Generator
Method signatures and docstrings:
- def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5): Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimensio... | Implement the Python class `GeneratorResNet` described below.
Class description:
The Residual Generator
Method signatures and docstrings:
- def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5): Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimensio... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class GeneratorResNet:
"""The Residual Generator"""
def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5):
"""Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimension, but not the batch dimension res_blocks : int number of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeneratorResNet:
"""The Residual Generator"""
def __init__(self, img_shape=(3, 128, 128), res_blocks=9, c_dim=5):
"""Parameters ---------- img_shape : tuple the shape of the generated images, should contain the channel dimension, but not the batch dimension res_blocks : int number of residual blo... | the_stack_v2_python_sparse | dlutils/models/gans/star/models.py | justusschock/dl-utils | train | 15 |
1c7cc4ed9032d5b9e3b050b369f0c068b0598dcb | [
"self.error = error\nself.source = source\nself.stats = stats\nself.status = status\nself.task_end_time_usecs = task_end_time_usecs\nself.task_start_time_usecs = task_start_time_usecs",
"if dictionary is None:\n return None\nerror = dictionary.get('error')\nsource = cohesity_management_sdk.models.protection_so... | <|body_start_0|>
self.error = error
self.source = source
self.stats = stats
self.status = status
self.task_end_time_usecs = task_end_time_usecs
self.task_start_time_usecs = task_start_time_usecs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
r... | Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is populated when the status is equal to 'kFailure'. sou... | CopySnapshotTaskStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is pop... | stack_v2_sparse_classes_36k_train_004830 | 4,290 | permissive | [
{
"docstring": "Constructor for the CopySnapshotTaskStatus class",
"name": "__init__",
"signature": "def __init__(self, error=None, source=None, stats=None, status=None, task_end_time_usecs=None, task_start_time_usecs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary ... | 2 | stack_v2_sparse_classes_30k_train_012259 | Implement the Python class `CopySnapshotTaskStatus` described below.
Class description:
Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) whi... | Implement the Python class `CopySnapshotTaskStatus` described below.
Class description:
Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) whi... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is pop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is populated when t... | the_stack_v2_python_sparse | cohesity_management_sdk/models/copy_snapshot_task_status.py | cohesity/management-sdk-python | train | 24 |
875c9f8bb3f7db8aa1850977fab4a54aba129495 | [
"if not root:\n return []\nres = []\n\ndef digui(root):\n if root:\n res.append(root.val)\n for i in root.children:\n digui(i)\ndigui(root)\nreturn res",
"if not root:\n return []\nres = []\nstack = [root]\nwhile stack:\n node = stack.pop()\n res.append(node.val)\n stack... | <|body_start_0|>
if not root:
return []
res = []
def digui(root):
if root:
res.append(root.val)
for i in root.children:
digui(i)
digui(root)
return res
<|end_body_0|>
<|body_start_1|>
if not roo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""递归"""
<|body_0|>
def preorder1(self, root: 'Node') -> List[int]:
"""迭代"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return []
res = []
def digui... | stack_v2_sparse_classes_36k_train_004831 | 1,083 | no_license | [
{
"docstring": "递归",
"name": "preorder",
"signature": "def preorder(self, root: 'Node') -> List[int]"
},
{
"docstring": "迭代",
"name": "preorder1",
"signature": "def preorder1(self, root: 'Node') -> List[int]"
}
] | 2 | stack_v2_sparse_classes_30k_train_019410 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorder(self, root: 'Node') -> List[int]: 递归
- def preorder1(self, root: 'Node') -> List[int]: 迭代 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorder(self, root: 'Node') -> List[int]: 递归
- def preorder1(self, root: 'Node') -> List[int]: 迭代
<|skeleton|>
class Solution:
def preorder(self, root: 'Node') -> List... | 069bb0b751ef7f469036b9897436eb5d138ffa24 | <|skeleton|>
class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""递归"""
<|body_0|>
def preorder1(self, root: 'Node') -> List[int]:
"""迭代"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorder(self, root: 'Node') -> List[int]:
"""递归"""
if not root:
return []
res = []
def digui(root):
if root:
res.append(root.val)
for i in root.children:
digui(i)
digui(root)
... | the_stack_v2_python_sparse | 算法/Week_02/589. N叉树的前序遍历.py | RichieSong/algorithm | train | 0 | |
e4486b57c2cf1394aa0d4a34b3d1f12b0f7b50b5 | [
"np.random.seed(rand_seed)\nself.w = {}\nself.b = {}\nself.z = {}\nself.a = {}\nself.dimensions = dimensions\nself.activation_funcs = activation_funcs\nself.loss_func = loss_func\nself.rand_seed = rand_seed\nself.num_layers = len(dimensions) - 1\nfor i in range(self.num_layers):\n self.w[i + 1] = np.random.randn... | <|body_start_0|>
np.random.seed(rand_seed)
self.w = {}
self.b = {}
self.z = {}
self.a = {}
self.dimensions = dimensions
self.activation_funcs = activation_funcs
self.loss_func = loss_func
self.rand_seed = rand_seed
self.num_layers = len(dim... | NN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NN:
def __init__(self, dimensions, activation_funcs, loss_func, rand_seed=None):
"""Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. dimensions: list of L+1 integers , with dimensions[i+1] and dimensions[i] being the number ... | stack_v2_sparse_classes_36k_train_004832 | 6,305 | no_license | [
{
"docstring": "Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. dimensions: list of L+1 integers , with dimensions[i+1] and dimensions[i] being the number of rows and columns for the W at layer i+1. dimensions[0] is the dimension of the data. dime... | 5 | stack_v2_sparse_classes_30k_train_008139 | Implement the Python class `NN` described below.
Class description:
Implement the NN class.
Method signatures and docstrings:
- def __init__(self, dimensions, activation_funcs, loss_func, rand_seed=None): Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. ... | Implement the Python class `NN` described below.
Class description:
Implement the NN class.
Method signatures and docstrings:
- def __init__(self, dimensions, activation_funcs, loss_func, rand_seed=None): Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. ... | ae4f9d5708fb5d732ec66b98ae600c20f32ccd04 | <|skeleton|>
class NN:
def __init__(self, dimensions, activation_funcs, loss_func, rand_seed=None):
"""Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. dimensions: list of L+1 integers , with dimensions[i+1] and dimensions[i] being the number ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NN:
def __init__(self, dimensions, activation_funcs, loss_func, rand_seed=None):
"""Specify a L layer feedforward network. Design consideration: we don't include data in this neural network class. dimensions: list of L+1 integers , with dimensions[i+1] and dimensions[i] being the number of rows and co... | the_stack_v2_python_sparse | project_3/nn_released/src/problem2.py | 7e11/CSE-326 | train | 1 | |
1df7cefeddf8ce40214ed4c927b97e1129815d33 | [
"self._host = host\nself._port = port\nself._login = login\nself._password = password\nself.data = None\nself.update()",
"try:\n self.data = hpilo.Ilo(hostname=self._host, login=self._login, password=self._password, port=self._port)\nexcept (hpilo.IloError, hpilo.IloCommunicationError, hpilo.IloLoginFailed) as... | <|body_start_0|>
self._host = host
self._port = port
self._login = login
self._password = password
self.data = None
self.update()
<|end_body_0|>
<|body_start_1|>
try:
self.data = hpilo.Ilo(hostname=self._host, login=self._login, password=self._passwor... | Gets the latest data from HP iLO. | HpIloData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HpIloData:
"""Gets the latest data from HP iLO."""
def __init__(self, host, port, login, password):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from HP iLO."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_004833 | 6,645 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, host, port, login, password)"
},
{
"docstring": "Get the latest data from HP iLO.",
"name": "update",
"signature": "def update(self)"
}
] | 2 | null | Implement the Python class `HpIloData` described below.
Class description:
Gets the latest data from HP iLO.
Method signatures and docstrings:
- def __init__(self, host, port, login, password): Initialize the data object.
- def update(self): Get the latest data from HP iLO. | Implement the Python class `HpIloData` described below.
Class description:
Gets the latest data from HP iLO.
Method signatures and docstrings:
- def __init__(self, host, port, login, password): Initialize the data object.
- def update(self): Get the latest data from HP iLO.
<|skeleton|>
class HpIloData:
"""Gets ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class HpIloData:
"""Gets the latest data from HP iLO."""
def __init__(self, host, port, login, password):
"""Initialize the data object."""
<|body_0|>
def update(self):
"""Get the latest data from HP iLO."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HpIloData:
"""Gets the latest data from HP iLO."""
def __init__(self, host, port, login, password):
"""Initialize the data object."""
self._host = host
self._port = port
self._login = login
self._password = password
self.data = None
self.update()
... | the_stack_v2_python_sparse | homeassistant/components/hp_ilo/sensor.py | home-assistant/core | train | 35,501 |
96c970e45e25902152dcf6a1e4eb27ce9b081897 | [
"N = len(nums) + 1\nfor i in range(0, len(nums)):\n if nums[i] < 0 or nums[i] >= N:\n nums[i] = 0\nnums.append(0)\nfor i in range(len(nums)):\n nums[nums[i] % N] += N\nfor i in range(1, len(nums)):\n if nums[i] < N:\n return i\nreturn N",
"N = len(nums)\nif N == 0:\n return 1\nfor s in r... | <|body_start_0|>
N = len(nums) + 1
for i in range(0, len(nums)):
if nums[i] < 0 or nums[i] >= N:
nums[i] = 0
nums.append(0)
for i in range(len(nums)):
nums[nums[i] % N] += N
for i in range(1, len(nums)):
if nums[i] < N:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
"""Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a new array that is used as a hash table The solution is the first element of such table that has not... | stack_v2_sparse_classes_36k_train_004834 | 2,584 | no_license | [
{
"docstring": "Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a new array that is used as a hash table The solution is the first element of such table that has not been filled",
"name": "firstMissingPositive",
"sig... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a ne... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a ne... | f4ac2609f8809ee543074a11dafc08726046f6a2 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
"""Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a new array that is used as a hash table The solution is the first element of such table that has not... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def firstMissingPositive(self, nums):
"""Storage is very limited so we do 3 tricks: - Remove elements that are <= 0 - Remove elements above N+1 - The remaining we re-arrange in a new array that is used as a hash table The solution is the first element of such table that has not been filled""... | the_stack_v2_python_sparse | LeetCode/41_first-missing-positive.py | curiousTauseef/Algorithms_and_solutions | train | 0 | |
8683db29734d51b02179b94a78a9ac8c63c70a58 | [
"log_file = os.path.join('logs', 'train-test.log')\nif os.path.exists(log_file):\n os.remove(log_file)\ncountry = 'brazil'\ndata_range = \"('2000-01-01', '2000-01-01')\"\neval_metric = {'rmse': 0.5}\nruntime = '00:00:01'\nmodel_version = 0.1\nmodel_version_note = 'test model'\nupdate_train_log(country, data_rang... | <|body_start_0|>
log_file = os.path.join('logs', 'train-test.log')
if os.path.exists(log_file):
os.remove(log_file)
country = 'brazil'
data_range = "('2000-01-01', '2000-01-01')"
eval_metric = {'rmse': 0.5}
runtime = '00:00:01'
model_version = 0.1
... | test the essential functionality | LoggerTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoggerTest:
"""test the essential functionality"""
def test_01_train(self):
"""ensure log file is created"""
<|body_0|>
def test_02_train(self):
"""ensure that content can be retrieved from log file"""
<|body_1|>
def test_03_predict(self):
""... | stack_v2_sparse_classes_36k_train_004835 | 3,141 | no_license | [
{
"docstring": "ensure log file is created",
"name": "test_01_train",
"signature": "def test_01_train(self)"
},
{
"docstring": "ensure that content can be retrieved from log file",
"name": "test_02_train",
"signature": "def test_02_train(self)"
},
{
"docstring": "ensure log file ... | 4 | stack_v2_sparse_classes_30k_train_010731 | Implement the Python class `LoggerTest` described below.
Class description:
test the essential functionality
Method signatures and docstrings:
- def test_01_train(self): ensure log file is created
- def test_02_train(self): ensure that content can be retrieved from log file
- def test_03_predict(self): ensure log fil... | Implement the Python class `LoggerTest` described below.
Class description:
test the essential functionality
Method signatures and docstrings:
- def test_01_train(self): ensure log file is created
- def test_02_train(self): ensure that content can be retrieved from log file
- def test_03_predict(self): ensure log fil... | 0b68917effa6128862d997c61dcae1d0df8ff109 | <|skeleton|>
class LoggerTest:
"""test the essential functionality"""
def test_01_train(self):
"""ensure log file is created"""
<|body_0|>
def test_02_train(self):
"""ensure that content can be retrieved from log file"""
<|body_1|>
def test_03_predict(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoggerTest:
"""test the essential functionality"""
def test_01_train(self):
"""ensure log file is created"""
log_file = os.path.join('logs', 'train-test.log')
if os.path.exists(log_file):
os.remove(log_file)
country = 'brazil'
data_range = "('2000-01-01... | the_stack_v2_python_sparse | unittests/logger_tests.py | ryusat/capstonepeerreveiw | train | 0 |
01a34991bbd044b99dcc65e1753a7bf438ebea07 | [
"visited = set()\nself.old_color = image[source_row][source_col]\nself.image = image\n\ndef fill(sr, sc):\n if str(sr) + str(sc) in visited:\n return\n visited.add(str(sr) + str(sc))\n length = len(self.image)\n height = len(self.image[0])\n if 0 <= sr < length and 0 <= sc < height:\n i... | <|body_start_0|>
visited = set()
self.old_color = image[source_row][source_col]
self.image = image
def fill(sr, sc):
if str(sr) + str(sc) in visited:
return
visited.add(str(sr) + str(sc))
length = len(self.image)
height = l... | First take (uses unecessary set) | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""First take (uses unecessary set)"""
def floodFill(self, image, source_row, source_col, new_color):
""":type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]"""
<|body_0|>
def floodFill(self, image, source_row, so... | stack_v2_sparse_classes_36k_train_004836 | 2,734 | no_license | [
{
"docstring": ":type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]",
"name": "floodFill",
"signature": "def floodFill(self, image, source_row, source_col, new_color)"
},
{
"docstring": ":type image: List[List[int]] :type sr: int :type sc: int :ty... | 2 | null | Implement the Python class `Solution` described below.
Class description:
First take (uses unecessary set)
Method signatures and docstrings:
- def floodFill(self, image, source_row, source_col, new_color): :type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]
- def flood... | Implement the Python class `Solution` described below.
Class description:
First take (uses unecessary set)
Method signatures and docstrings:
- def floodFill(self, image, source_row, source_col, new_color): :type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]
- def flood... | 844f502da4d6fb9cd69cf0a1ef71da3385a4d2b4 | <|skeleton|>
class Solution:
"""First take (uses unecessary set)"""
def floodFill(self, image, source_row, source_col, new_color):
""":type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]"""
<|body_0|>
def floodFill(self, image, source_row, so... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""First take (uses unecessary set)"""
def floodFill(self, image, source_row, source_col, new_color):
""":type image: List[List[int]] :type sr: int :type sc: int :type newColor: int :rtype: List[List[int]]"""
visited = set()
self.old_color = image[source_row][source_col]... | the_stack_v2_python_sparse | 733-flood_fill.py | stevestar888/leetcode-problems | train | 2 |
cb603965bb0b9eed8069c5f2c068d7d7053405ec | [
"dic_of_barcodes = {}\nif len(barcodes) < 3:\n return barcodes\nfor i in barcodes:\n if i not in dic_of_barcodes:\n dic_of_barcodes[i] = 1\n else:\n dic_of_barcodes[i] += 1\nkeys = list(dic_of_barcodes.keys())\nkeys = sorted(keys, key=lambda i: dic_of_barcodes[i], reverse=True)\nprint(keys)\n... | <|body_start_0|>
dic_of_barcodes = {}
if len(barcodes) < 3:
return barcodes
for i in barcodes:
if i not in dic_of_barcodes:
dic_of_barcodes[i] = 1
else:
dic_of_barcodes[i] += 1
keys = list(dic_of_barcodes.keys())
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rearrangeBarcodes(self, barcodes):
""":type barcodes: List[int] :rtype: List[int]"""
<|body_0|>
def rearrangeBarcodes2(self, barcodes):
""":type barcodes: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dic_... | stack_v2_sparse_classes_36k_train_004837 | 1,932 | no_license | [
{
"docstring": ":type barcodes: List[int] :rtype: List[int]",
"name": "rearrangeBarcodes",
"signature": "def rearrangeBarcodes(self, barcodes)"
},
{
"docstring": ":type barcodes: List[int] :rtype: List[int]",
"name": "rearrangeBarcodes2",
"signature": "def rearrangeBarcodes2(self, barcod... | 2 | stack_v2_sparse_classes_30k_train_005073 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rearrangeBarcodes(self, barcodes): :type barcodes: List[int] :rtype: List[int]
- def rearrangeBarcodes2(self, barcodes): :type barcodes: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rearrangeBarcodes(self, barcodes): :type barcodes: List[int] :rtype: List[int]
- def rearrangeBarcodes2(self, barcodes): :type barcodes: List[int] :rtype: List[int]
<|skelet... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def rearrangeBarcodes(self, barcodes):
""":type barcodes: List[int] :rtype: List[int]"""
<|body_0|>
def rearrangeBarcodes2(self, barcodes):
""":type barcodes: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rearrangeBarcodes(self, barcodes):
""":type barcodes: List[int] :rtype: List[int]"""
dic_of_barcodes = {}
if len(barcodes) < 3:
return barcodes
for i in barcodes:
if i not in dic_of_barcodes:
dic_of_barcodes[i] = 1
... | the_stack_v2_python_sparse | rearrangeBarcodes.py | NeilWangziyu/Leetcode_py | train | 2 | |
83e36b97895007fc65a9883476f8c6b25e9b9095 | [
"self.drive_vec = drive_vec\nself.object = object\nself.parent_site = parent_site",
"if dictionary is None:\n return None\ndrive_vec = None\nif dictionary.get('driveVec') != None:\n drive_vec = list()\n for structure in dictionary.get('driveVec'):\n drive_vec.append(cohesity_management_sdk.models.... | <|body_start_0|>
self.drive_vec = drive_vec
self.object = object
self.parent_site = parent_site
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
drive_vec = None
if dictionary.get('driveVec') != None:
drive_vec = list()
... | Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): This will store the details of the user whose drives is to be restored. parent_site (EntityProto)... | RestoreSiteParams_SiteOwner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RestoreSiteParams_SiteOwner:
"""Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): This will store the details of the user wh... | stack_v2_sparse_classes_36k_train_004838 | 2,656 | permissive | [
{
"docstring": "Constructor for the RestoreSiteParams_SiteOwner class",
"name": "__init__",
"signature": "def __init__(self, drive_vec=None, object=None, parent_site=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary represen... | 2 | stack_v2_sparse_classes_30k_train_020295 | Implement the Python class `RestoreSiteParams_SiteOwner` described below.
Class description:
Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): Thi... | Implement the Python class `RestoreSiteParams_SiteOwner` described below.
Class description:
Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): Thi... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class RestoreSiteParams_SiteOwner:
"""Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): This will store the details of the user wh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RestoreSiteParams_SiteOwner:
"""Implementation of the 'RestoreSiteParams_SiteOwner' model. TODO: type description here. Attributes: drive_vec (list of RestoreSiteParams_SiteOwner_Drive): The list of drives that are being restored. object (RestoreObject): This will store the details of the user whose drives is... | the_stack_v2_python_sparse | cohesity_management_sdk/models/restore_site_params_site_owner.py | cohesity/management-sdk-python | train | 24 |
1712bf86a0e4a5119437ec0f657f5918bc41905e | [
"if klass == sql.UpdateQuery:\n return super().chain(PostgresUpdateQuery)\nif klass == sql.InsertQuery:\n return super().chain(PostgresInsertQuery)\nreturn super().chain(klass)",
"for old_name, new_name in annotations.items():\n annotation = self.annotations.get(old_name)\n if not annotation:\n ... | <|body_start_0|>
if klass == sql.UpdateQuery:
return super().chain(PostgresUpdateQuery)
if klass == sql.InsertQuery:
return super().chain(PostgresInsertQuery)
return super().chain(klass)
<|end_body_0|>
<|body_start_1|>
for old_name, new_name in annotations.items(... | PostgresQuery | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PostgresQuery:
def chain(self, klass=None):
"""Chains this query to another. We override this so that we can make sure our subclassed query classes are used."""
<|body_0|>
def rename_annotations(self, annotations) -> None:
"""Renames the aliases for the specified ann... | stack_v2_sparse_classes_36k_train_004839 | 7,372 | permissive | [
{
"docstring": "Chains this query to another. We override this so that we can make sure our subclassed query classes are used.",
"name": "chain",
"signature": "def chain(self, klass=None)"
},
{
"docstring": "Renames the aliases for the specified annotations: .annotate(myfield=F('somestuf__myfiel... | 4 | null | Implement the Python class `PostgresQuery` described below.
Class description:
Implement the PostgresQuery class.
Method signatures and docstrings:
- def chain(self, klass=None): Chains this query to another. We override this so that we can make sure our subclassed query classes are used.
- def rename_annotations(sel... | Implement the Python class `PostgresQuery` described below.
Class description:
Implement the PostgresQuery class.
Method signatures and docstrings:
- def chain(self, klass=None): Chains this query to another. We override this so that we can make sure our subclassed query classes are used.
- def rename_annotations(sel... | e5503cb3f3c1b7959bd55253d3a79296f4c8f0ef | <|skeleton|>
class PostgresQuery:
def chain(self, klass=None):
"""Chains this query to another. We override this so that we can make sure our subclassed query classes are used."""
<|body_0|>
def rename_annotations(self, annotations) -> None:
"""Renames the aliases for the specified ann... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PostgresQuery:
def chain(self, klass=None):
"""Chains this query to another. We override this so that we can make sure our subclassed query classes are used."""
if klass == sql.UpdateQuery:
return super().chain(PostgresUpdateQuery)
if klass == sql.InsertQuery:
r... | the_stack_v2_python_sparse | psqlextra/sql.py | SectorLabs/django-postgres-extra | train | 645 | |
b20098cafc2fc4ec4161a010f5bf0d2188865d5e | [
"if left is None:\n left = 0\nif right is None:\n right = 3 * opt\nself.opt = opt\nself.left = left\nself.right = right\nself.weight = weight",
"opt = self.opt * density\nif value < opt:\n other = self.left * density\nelif value > opt:\n other = self.right * density\nelse:\n return 0\nfactor = (val... | <|body_start_0|>
if left is None:
left = 0
if right is None:
right = 3 * opt
self.opt = opt
self.left = left
self.right = right
self.weight = weight
<|end_body_0|>
<|body_start_1|>
opt = self.opt * density
if value < opt:
... | a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analytic form of the rating is cubic for both, the left and the right side of... | cube | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class cube:
"""a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analytic form of the rating is cubic for both... | stack_v2_sparse_classes_36k_train_004840 | 10,567 | permissive | [
{
"docstring": "initializes the rater - by default, left is set to zero, right is set to 3*opt - left should be smaller than opt, right should be bigger than opt - weight should be positive and is a factor multiplicated to the rates",
"name": "__init__",
"signature": "def __init__(self, opt, left=None, ... | 2 | stack_v2_sparse_classes_30k_train_008368 | Implement the Python class `cube` described below.
Class description:
a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analyt... | Implement the Python class `cube` described below.
Class description:
a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analyt... | 3a9693e37fd3afbd52001839966b0f2811fb4ccd | <|skeleton|>
class cube:
"""a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analytic form of the rating is cubic for both... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class cube:
"""a value rater - a cube rater has an optimal value, where the rate becomes zero - for a left (below the optimum) and a right value (above the optimum), the rating is value is set to 1 (modified by an overall weight factor for the rating) - the analytic form of the rating is cubic for both, the left an... | the_stack_v2_python_sparse | compiler/gdsMill/pyx/graph/axis/rater.py | kanokkorn/OpenRAM | train | 0 |
10425653e5a0284cff59494dc06448447e5210b7 | [
"lumMod = self._add_lumMod()\nlumMod.val = value\nreturn lumMod",
"lumOff = self._add_lumOff()\nlumOff.val = value\nreturn lumOff",
"self._remove_lumMod()\nself._remove_lumOff()\nreturn self"
] | <|body_start_0|>
lumMod = self._add_lumMod()
lumMod.val = value
return lumMod
<|end_body_0|>
<|body_start_1|>
lumOff = self._add_lumOff()
lumOff.val = value
return lumOff
<|end_body_1|>
<|body_start_2|>
self._remove_lumMod()
self._remove_lumOff()
... | Base class for <a:srgbClr> and <a:schemeClr> elements. | _BaseColorElement | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _BaseColorElement:
"""Base class for <a:srgbClr> and <a:schemeClr> elements."""
def add_lumMod(self, value):
"""Return a newly added <a:lumMod> child element."""
<|body_0|>
def add_lumOff(self, value):
"""Return a newly added <a:lumOff> child element."""
... | stack_v2_sparse_classes_36k_train_004841 | 2,024 | permissive | [
{
"docstring": "Return a newly added <a:lumMod> child element.",
"name": "add_lumMod",
"signature": "def add_lumMod(self, value)"
},
{
"docstring": "Return a newly added <a:lumOff> child element.",
"name": "add_lumOff",
"signature": "def add_lumOff(self, value)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_012284 | Implement the Python class `_BaseColorElement` described below.
Class description:
Base class for <a:srgbClr> and <a:schemeClr> elements.
Method signatures and docstrings:
- def add_lumMod(self, value): Return a newly added <a:lumMod> child element.
- def add_lumOff(self, value): Return a newly added <a:lumOff> child... | Implement the Python class `_BaseColorElement` described below.
Class description:
Base class for <a:srgbClr> and <a:schemeClr> elements.
Method signatures and docstrings:
- def add_lumMod(self, value): Return a newly added <a:lumMod> child element.
- def add_lumOff(self, value): Return a newly added <a:lumOff> child... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class _BaseColorElement:
"""Base class for <a:srgbClr> and <a:schemeClr> elements."""
def add_lumMod(self, value):
"""Return a newly added <a:lumMod> child element."""
<|body_0|>
def add_lumOff(self, value):
"""Return a newly added <a:lumOff> child element."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _BaseColorElement:
"""Base class for <a:srgbClr> and <a:schemeClr> elements."""
def add_lumMod(self, value):
"""Return a newly added <a:lumMod> child element."""
lumMod = self._add_lumMod()
lumMod.val = value
return lumMod
def add_lumOff(self, value):
"""Retur... | the_stack_v2_python_sparse | Pdf_docx_pptx_xlsx_epub_png/source/pptx/oxml/dml/color.py | ryfeus/lambda-packs | train | 1,283 |
1436eeb94d071103defcddc3abdb7610236b3b02 | [
"if obj.sender:\n serializer = UserSerializer(obj.sender, context=self.context, fields=['id', 'username', 'email', 'name', 'last_name', 'second_last_name', 'photo', 'thumbnail'])\n return serializer.data",
"if obj.target:\n serializer = NotificationTargetSerializer(obj, context=self.context)\n return ... | <|body_start_0|>
if obj.sender:
serializer = UserSerializer(obj.sender, context=self.context, fields=['id', 'username', 'email', 'name', 'last_name', 'second_last_name', 'photo', 'thumbnail'])
return serializer.data
<|end_body_0|>
<|body_start_1|>
if obj.target:
seri... | Serializer class for the ```tandlr.notifications.models.Notification``` model. | NotificationV2Serializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationV2Serializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
<|body_0|>
def get_target(self, obj):
""... | stack_v2_sparse_classes_36k_train_004842 | 3,769 | permissive | [
{
"docstring": "Returns the notification's sender serialized with the minimal required fields.",
"name": "get_sender",
"signature": "def get_sender(self, obj)"
},
{
"docstring": "Returns the notification's target serialized with the minimal required fields.",
"name": "get_target",
"signa... | 2 | null | Implement the Python class `NotificationV2Serializer` described below.
Class description:
Serializer class for the ```tandlr.notifications.models.Notification``` model.
Method signatures and docstrings:
- def get_sender(self, obj): Returns the notification's sender serialized with the minimal required fields.
- def g... | Implement the Python class `NotificationV2Serializer` described below.
Class description:
Serializer class for the ```tandlr.notifications.models.Notification``` model.
Method signatures and docstrings:
- def get_sender(self, obj): Returns the notification's sender serialized with the minimal required fields.
- def g... | 7349ce18f56658d67daedf5e1abb352b5c15a029 | <|skeleton|>
class NotificationV2Serializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
<|body_0|>
def get_target(self, obj):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationV2Serializer:
"""Serializer class for the ```tandlr.notifications.models.Notification``` model."""
def get_sender(self, obj):
"""Returns the notification's sender serialized with the minimal required fields."""
if obj.sender:
serializer = UserSerializer(obj.sender,... | the_stack_v2_python_sparse | src/tandlr/notifications/serializers.py | shrmoud/schoolapp | train | 0 |
6f04299c050564dc1dbac7eedee78161e389c0bb | [
"forest_predictions = self._base_estimator_predictions(X)\nif self._models_parameters.normalize_D:\n forest_predictions /= self._forest_norms\nreturn self._omp.predict(forest_predictions, forest_size)",
"forest_predictions = self._base_estimator_predictions(X)\nif forest_size is not None:\n weights = self._... | <|body_start_0|>
forest_predictions = self._base_estimator_predictions(X)
if self._models_parameters.normalize_D:
forest_predictions /= self._forest_norms
return self._omp.predict(forest_predictions, forest_size)
<|end_body_0|>
<|body_start_1|>
forest_predictions = self._bas... | NonNegativeOmpForestBinaryClassifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NonNegativeOmpForestBinaryClassifier:
def predict(self, X, forest_size=None):
"""Make prediction. If forest_size is None return the list of predictions of all intermediate solutions :param X: :return:"""
<|body_0|>
def predict_no_weights(self, X, forest_size=None):
"... | stack_v2_sparse_classes_36k_train_004843 | 5,444 | permissive | [
{
"docstring": "Make prediction. If forest_size is None return the list of predictions of all intermediate solutions :param X: :return:",
"name": "predict",
"signature": "def predict(self, X, forest_size=None)"
},
{
"docstring": "Make a prediction of the selected trees but without weight. If for... | 3 | stack_v2_sparse_classes_30k_test_000397 | Implement the Python class `NonNegativeOmpForestBinaryClassifier` described below.
Class description:
Implement the NonNegativeOmpForestBinaryClassifier class.
Method signatures and docstrings:
- def predict(self, X, forest_size=None): Make prediction. If forest_size is None return the list of predictions of all inte... | Implement the Python class `NonNegativeOmpForestBinaryClassifier` described below.
Class description:
Implement the NonNegativeOmpForestBinaryClassifier class.
Method signatures and docstrings:
- def predict(self, X, forest_size=None): Make prediction. If forest_size is None return the list of predictions of all inte... | 64ba63c01bd04f4f959d18aff27e245d8fff3403 | <|skeleton|>
class NonNegativeOmpForestBinaryClassifier:
def predict(self, X, forest_size=None):
"""Make prediction. If forest_size is None return the list of predictions of all intermediate solutions :param X: :return:"""
<|body_0|>
def predict_no_weights(self, X, forest_size=None):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NonNegativeOmpForestBinaryClassifier:
def predict(self, X, forest_size=None):
"""Make prediction. If forest_size is None return the list of predictions of all intermediate solutions :param X: :return:"""
forest_predictions = self._base_estimator_predictions(X)
if self._models_parameter... | the_stack_v2_python_sparse | code/bolsonaro/models/nn_omp_forest_classifier.py | swasun/RFOMT | train | 2 | |
29fc3d9269805e545c288fcc1c0e5e0d263c53db | [
"def remove(head):\n if not head:\n return (0, head)\n count, head.next = remove(head.next)\n return (count + 1, (head, head.next)[count + 1 == n])\nreturn remove(head)[1]",
"def index(node):\n if not node:\n return 0\n count = index(node.next)\n if count >= n:\n node.next.v... | <|body_start_0|>
def remove(head):
if not head:
return (0, head)
count, head.next = remove(head.next)
return (count + 1, (head, head.next)[count + 1 == n])
return remove(head)[1]
<|end_body_0|>
<|body_start_1|>
def index(node):
if ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd2(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
def removeNthFromEnd3(self, head... | stack_v2_sparse_classes_36k_train_004844 | 1,401 | no_license | [
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd1",
"signature": "def removeNthFromEnd1(self, head, n)"
},
{
"docstring": ":type head: ListNode :type n: int :rtype: ListNode",
"name": "removeNthFromEnd2",
"signature": "def removeNthFromEnd2(s... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd1(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd2(self, head, n): :type head: ListNode :type n: int :rtype: ListNod... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeNthFromEnd1(self, head, n): :type head: ListNode :type n: int :rtype: ListNode
- def removeNthFromEnd2(self, head, n): :type head: ListNode :type n: int :rtype: ListNod... | 8fb6c1d947046dabd58ff8482b2c0b41f39aa988 | <|skeleton|>
class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_0|>
def removeNthFromEnd2(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
<|body_1|>
def removeNthFromEnd3(self, head... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeNthFromEnd1(self, head, n):
""":type head: ListNode :type n: int :rtype: ListNode"""
def remove(head):
if not head:
return (0, head)
count, head.next = remove(head.next)
return (count + 1, (head, head.next)[count + 1 == n]... | the_stack_v2_python_sparse | Python/LeetCode/19.py | czx94/Algorithms-Collection | train | 2 | |
e9520b0229d51424a4fec399f32987722990a4f1 | [
"location_columns = ['precinct', 'LOCATION_ZIPCODE', 'Latitude', 'Longitude']\ndescriptor = ['TYPE', 'REASON']\ndate_cols = ['open_dt', 'target_dt', 'closed_dt']\npunctual = ['OnTime_Status', 'CASE_STATUS']\nidentif = ['CASE_ENQUIRY_ID']\ndf[date_cols] = df[date_cols].apply(pd.to_datetime, errors='coerce')\ncomplet... | <|body_start_0|>
location_columns = ['precinct', 'LOCATION_ZIPCODE', 'Latitude', 'Longitude']
descriptor = ['TYPE', 'REASON']
date_cols = ['open_dt', 'target_dt', 'closed_dt']
punctual = ['OnTime_Status', 'CASE_STATUS']
identif = ['CASE_ENQUIRY_ID']
df[date_cols] = df[dat... | three_one_one | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class three_one_one:
def clean_transform_data(df):
"""Project data, and clean empty values"""
<|body_0|>
def execute(trial=False, custom_url=None):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_1|>
def provenance(doc... | stack_v2_sparse_classes_36k_train_004845 | 5,946 | no_license | [
{
"docstring": "Project data, and clean empty values",
"name": "clean_transform_data",
"signature": "def clean_transform_data(df)"
},
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False, c... | 3 | stack_v2_sparse_classes_30k_train_003784 | Implement the Python class `three_one_one` described below.
Class description:
Implement the three_one_one class.
Method signatures and docstrings:
- def clean_transform_data(df): Project data, and clean empty values
- def execute(trial=False, custom_url=None): Retrieve some data sets (not using the API here for the ... | Implement the Python class `three_one_one` described below.
Class description:
Implement the three_one_one class.
Method signatures and docstrings:
- def clean_transform_data(df): Project data, and clean empty values
- def execute(trial=False, custom_url=None): Retrieve some data sets (not using the API here for the ... | b5ccaad97f6e35f9580e645ca764f36eb3406f43 | <|skeleton|>
class three_one_one:
def clean_transform_data(df):
"""Project data, and clean empty values"""
<|body_0|>
def execute(trial=False, custom_url=None):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_1|>
def provenance(doc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class three_one_one:
def clean_transform_data(df):
"""Project data, and clean empty values"""
location_columns = ['precinct', 'LOCATION_ZIPCODE', 'Latitude', 'Longitude']
descriptor = ['TYPE', 'REASON']
date_cols = ['open_dt', 'target_dt', 'closed_dt']
punctual = ['OnTime_Sta... | the_stack_v2_python_sparse | kaidb_vilin/three_one_one.py | dwang1995/course-2018-spr-proj | train | 1 | |
0b4b9113fbb7bbf5084c3eb5939941f21c061014 | [
"self.vocab_size = vocab_size\nself.vocab_name = 'vocab.%s' % self.vocab_size\nif not isinstance(training_dataset_filenames, list):\n training_dataset_filenames = [training_dataset_filenames]\nself.training_dataset_filenames = training_dataset_filenames",
"data_set = [['', self.training_dataset_filenames]]\nso... | <|body_start_0|>
self.vocab_size = vocab_size
self.vocab_name = 'vocab.%s' % self.vocab_size
if not isinstance(training_dataset_filenames, list):
training_dataset_filenames = [training_dataset_filenames]
self.training_dataset_filenames = training_dataset_filenames
<|end_body_... | gen subword | GenSubword | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenSubword:
"""gen subword"""
def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt'):
""":param vocab_size: :param vocab_name: :param training_dataset_filenames: list"""
<|body_0|>
def generate_data(self, data_dir, tmp_dir):
""":param data_di... | stack_v2_sparse_classes_36k_train_004846 | 12,969 | permissive | [
{
"docstring": ":param vocab_size: :param vocab_name: :param training_dataset_filenames: list",
"name": "__init__",
"signature": "def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt')"
},
{
"docstring": ":param data_dir: target dir(includes vocab file) :param tmp_dir: origi... | 2 | null | Implement the Python class `GenSubword` described below.
Class description:
gen subword
Method signatures and docstrings:
- def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt'): :param vocab_size: :param vocab_name: :param training_dataset_filenames: list
- def generate_data(self, data_dir, tmp... | Implement the Python class `GenSubword` described below.
Class description:
gen subword
Method signatures and docstrings:
- def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt'): :param vocab_size: :param vocab_name: :param training_dataset_filenames: list
- def generate_data(self, data_dir, tmp... | b8ec015fa9e16c0a879c619ee1f2aab8a393c7bd | <|skeleton|>
class GenSubword:
"""gen subword"""
def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt'):
""":param vocab_size: :param vocab_name: :param training_dataset_filenames: list"""
<|body_0|>
def generate_data(self, data_dir, tmp_dir):
""":param data_di... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenSubword:
"""gen subword"""
def __init__(self, vocab_size=8000, training_dataset_filenames='train.txt'):
""":param vocab_size: :param vocab_name: :param training_dataset_filenames: list"""
self.vocab_size = vocab_size
self.vocab_name = 'vocab.%s' % self.vocab_size
if not... | the_stack_v2_python_sparse | NLP/EMNLP2019-MAL/src/preprocess/problem.py | sserdoubleh/Research | train | 10 |
db1c03e8d30c27e0111a82600b69cf4dbf00ed48 | [
"super().__init__()\nif isinstance(output_size, int):\n output_size = (output_size, output_size)\nassert len(output_size) == 2\nassert isinstance(output_size[0], int) and isinstance(output_size[1], int)\nself.output_size = output_size\nif pooler_type == 'ROIAlign':\n self.level_poolers = [ROIAlign(output_size... | <|body_start_0|>
super().__init__()
if isinstance(output_size, int):
output_size = (output_size, output_size)
assert len(output_size) == 2
assert isinstance(output_size[0], int) and isinstance(output_size[1], int)
self.output_size = output_size
if pooler_type ... | Region of interest feature map pooler that supports pooling from one or more feature maps. | ROIPooler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ROIPooler:
"""Region of interest feature map pooler that supports pooling from one or more feature maps."""
def __init__(self, output_size, scales, sampling_ratio, pooler_type, canonical_box_size=224, canonical_level=4):
"""Args: output_size (int, tuple[int] or list[int]): output siz... | stack_v2_sparse_classes_36k_train_004847 | 7,279 | permissive | [
{
"docstring": "Args: output_size (int, tuple[int] or list[int]): output size of the pooled region, e.g., 14 x 14. If tuple or list is given, the length must be 2. scales (list[float]): The scale for each low-level pooling op relative to the input image. For a feature map with stride s relative to the input ima... | 2 | stack_v2_sparse_classes_30k_train_016944 | Implement the Python class `ROIPooler` described below.
Class description:
Region of interest feature map pooler that supports pooling from one or more feature maps.
Method signatures and docstrings:
- def __init__(self, output_size, scales, sampling_ratio, pooler_type, canonical_box_size=224, canonical_level=4): Arg... | Implement the Python class `ROIPooler` described below.
Class description:
Region of interest feature map pooler that supports pooling from one or more feature maps.
Method signatures and docstrings:
- def __init__(self, output_size, scales, sampling_ratio, pooler_type, canonical_box_size=224, canonical_level=4): Arg... | ca03f633111d540ea91b3de75dbfa1da813647be | <|skeleton|>
class ROIPooler:
"""Region of interest feature map pooler that supports pooling from one or more feature maps."""
def __init__(self, output_size, scales, sampling_ratio, pooler_type, canonical_box_size=224, canonical_level=4):
"""Args: output_size (int, tuple[int] or list[int]): output siz... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ROIPooler:
"""Region of interest feature map pooler that supports pooling from one or more feature maps."""
def __init__(self, output_size, scales, sampling_ratio, pooler_type, canonical_box_size=224, canonical_level=4):
"""Args: output_size (int, tuple[int] or list[int]): output size of the pool... | the_stack_v2_python_sparse | lib/modeling/poolers.py | SimeonZhang/detectron2_tensorflow | train | 13 |
74241f8345dc12760b5fd3c97df0447c895b2078 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn TeamsApp()",
"from .entity import Entity\nfrom .teams_app_definition import TeamsAppDefinition\nfrom .teams_app_distribution_method import TeamsAppDistributionMethod\nfrom .entity import Entity\nfrom .teams_app_definition import TeamsA... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return TeamsApp()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .teams_app_definition import TeamsAppDefinition
from .teams_app_distribution_method import TeamsAppDist... | TeamsApp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TeamsApp:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamsApp:
"""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: TeamsApp... | stack_v2_sparse_classes_36k_train_004848 | 3,371 | 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: TeamsApp",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_value(pars... | 3 | null | Implement the Python class `TeamsApp` described below.
Class description:
Implement the TeamsApp class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamsApp: Creates a new instance of the appropriate class based on discriminator value Args: parse_no... | Implement the Python class `TeamsApp` described below.
Class description:
Implement the TeamsApp class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamsApp: Creates a new instance of the appropriate class based on discriminator value Args: parse_no... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class TeamsApp:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamsApp:
"""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: TeamsApp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TeamsApp:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> TeamsApp:
"""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: TeamsApp"""
if... | the_stack_v2_python_sparse | msgraph/generated/models/teams_app.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
dc302e0aaac1a60300a15893b0fa0d373f2004ba | [
"self.host = host\nself.port = port\nself.info = info\nplatforms = []\nif any((asr.installed for asr in info.asr)):\n platforms.append(Platform.STT)\nif any((tts.installed for tts in info.tts)):\n platforms.append(Platform.TTS)\nif any((wake.installed for wake in info.wake)):\n platforms.append(Platform.WA... | <|body_start_0|>
self.host = host
self.port = port
self.info = info
platforms = []
if any((asr.installed for asr in info.asr)):
platforms.append(Platform.STT)
if any((tts.installed for tts in info.tts)):
platforms.append(Platform.TTS)
if an... | Hold info for Wyoming service. | WyomingService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WyomingService:
"""Hold info for Wyoming service."""
def __init__(self, host: str, port: int, info: Info) -> None:
"""Initialize Wyoming service."""
<|body_0|>
async def create(cls, host: str, port: int) -> WyomingService | None:
"""Create a Wyoming service."""
... | stack_v2_sparse_classes_36k_train_004849 | 2,321 | permissive | [
{
"docstring": "Initialize Wyoming service.",
"name": "__init__",
"signature": "def __init__(self, host: str, port: int, info: Info) -> None"
},
{
"docstring": "Create a Wyoming service.",
"name": "create",
"signature": "async def create(cls, host: str, port: int) -> WyomingService | Non... | 2 | null | Implement the Python class `WyomingService` described below.
Class description:
Hold info for Wyoming service.
Method signatures and docstrings:
- def __init__(self, host: str, port: int, info: Info) -> None: Initialize Wyoming service.
- async def create(cls, host: str, port: int) -> WyomingService | None: Create a ... | Implement the Python class `WyomingService` described below.
Class description:
Hold info for Wyoming service.
Method signatures and docstrings:
- def __init__(self, host: str, port: int, info: Info) -> None: Initialize Wyoming service.
- async def create(cls, host: str, port: int) -> WyomingService | None: Create a ... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class WyomingService:
"""Hold info for Wyoming service."""
def __init__(self, host: str, port: int, info: Info) -> None:
"""Initialize Wyoming service."""
<|body_0|>
async def create(cls, host: str, port: int) -> WyomingService | None:
"""Create a Wyoming service."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WyomingService:
"""Hold info for Wyoming service."""
def __init__(self, host: str, port: int, info: Info) -> None:
"""Initialize Wyoming service."""
self.host = host
self.port = port
self.info = info
platforms = []
if any((asr.installed for asr in info.asr)... | the_stack_v2_python_sparse | homeassistant/components/wyoming/data.py | home-assistant/core | train | 35,501 |
ce8cd1433ff91a6b83173b53dcdc62ddb8d66c01 | [
"super(VMRuntimeInstanceFactory, self).__init__(request_data, 8 if runtime_config_getter().threadsafe else 1, 10)\nself._runtime_config_getter = runtime_config_getter\nself._module_configuration = module_configuration\nself._docker_client = containers.NewDockerClient(version='1.9', timeout=self.DOCKER_D_REQUEST_TIM... | <|body_start_0|>
super(VMRuntimeInstanceFactory, self).__init__(request_data, 8 if runtime_config_getter().threadsafe else 1, 10)
self._runtime_config_getter = runtime_config_getter
self._module_configuration = module_configuration
self._docker_client = containers.NewDockerClient(version... | A factory that creates new VM runtime Instances. | VMRuntimeInstanceFactory | [
"Apache-2.0",
"LGPL-2.1-or-later",
"BSD-3-Clause",
"MIT",
"GPL-2.0-or-later",
"MPL-1.1",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VMRuntimeInstanceFactory:
"""A factory that creates new VM runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for VMRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided w... | stack_v2_sparse_classes_36k_train_004850 | 4,064 | permissive | [
{
"docstring": "Initializer for VMRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided with request information for use by API stubs. runtime_config_getter: A function that can be called without arguments and returns the runtime_config_pb2.Config containing the c... | 2 | null | Implement the Python class `VMRuntimeInstanceFactory` described below.
Class description:
A factory that creates new VM runtime Instances.
Method signatures and docstrings:
- def __init__(self, request_data, runtime_config_getter, module_configuration): Initializer for VMRuntimeInstanceFactory. Args: request_data: A ... | Implement the Python class `VMRuntimeInstanceFactory` described below.
Class description:
A factory that creates new VM runtime Instances.
Method signatures and docstrings:
- def __init__(self, request_data, runtime_config_getter, module_configuration): Initializer for VMRuntimeInstanceFactory. Args: request_data: A ... | d379afa2db3582d5c3be652165f0e9e2e0c154c6 | <|skeleton|>
class VMRuntimeInstanceFactory:
"""A factory that creates new VM runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for VMRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VMRuntimeInstanceFactory:
"""A factory that creates new VM runtime Instances."""
def __init__(self, request_data, runtime_config_getter, module_configuration):
"""Initializer for VMRuntimeInstanceFactory. Args: request_data: A wsgi_request_info.WSGIRequestInfo that will be provided with request i... | the_stack_v2_python_sparse | y/google-cloud-sdk/platform/google_appengine/google/appengine/tools/devappserver2/vm_runtime_factory.py | ychen820/microblog | train | 0 |
e0a88edc742408be66c534e5ac106a4d0e723017 | [
"if k <= 0:\n raise ValueError('k应该大于0.')\nnodeK = phead = head.next\ni = 1\nwhile nodeK and i < k:\n nodeK, i = (nodeK.next, i + 1)\nif i < k or not nodeK:\n raise ValueError('链表节点数小于k.')\nwhile nodeK.next:\n phead, nodeK = (phead.next, nodeK.next)\nreturn phead",
"odd = even = head\nwhile even:\n ... | <|body_start_0|>
if k <= 0:
raise ValueError('k应该大于0.')
nodeK = phead = head.next
i = 1
while nodeK and i < k:
nodeK, i = (nodeK.next, i + 1)
if i < k or not nodeK:
raise ValueError('链表节点数小于k.')
while nodeK.next:
phead, node... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def theLastKNode(self, head, k):
""":type head:ListNode :type k:int :rtype:ListNode"""
<|body_0|>
def theMiddleNode1(self, head):
""":type head:ListNode :rtype:ListNode"""
<|body_1|>
def theMiddleNode2(self, head):
""":type head:ListNod... | stack_v2_sparse_classes_36k_train_004851 | 1,407 | no_license | [
{
"docstring": ":type head:ListNode :type k:int :rtype:ListNode",
"name": "theLastKNode",
"signature": "def theLastKNode(self, head, k)"
},
{
"docstring": ":type head:ListNode :rtype:ListNode",
"name": "theMiddleNode1",
"signature": "def theMiddleNode1(self, head)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_011639 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def theLastKNode(self, head, k): :type head:ListNode :type k:int :rtype:ListNode
- def theMiddleNode1(self, head): :type head:ListNode :rtype:ListNode
- def theMiddleNode2(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def theLastKNode(self, head, k): :type head:ListNode :type k:int :rtype:ListNode
- def theMiddleNode1(self, head): :type head:ListNode :rtype:ListNode
- def theMiddleNode2(self, ... | 42a15943394ae533dcd0d5bbf52e4366ab0756ab | <|skeleton|>
class Solution:
def theLastKNode(self, head, k):
""":type head:ListNode :type k:int :rtype:ListNode"""
<|body_0|>
def theMiddleNode1(self, head):
""":type head:ListNode :rtype:ListNode"""
<|body_1|>
def theMiddleNode2(self, head):
""":type head:ListNod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def theLastKNode(self, head, k):
""":type head:ListNode :type k:int :rtype:ListNode"""
if k <= 0:
raise ValueError('k应该大于0.')
nodeK = phead = head.next
i = 1
while nodeK and i < k:
nodeK, i = (nodeK.next, i + 1)
if i < k or not ... | the_stack_v2_python_sparse | test22.py | nihao-hit/jianzhiOffer | train | 0 | |
3aafd25d5d4eb023f194ab6e87c861f0a9cf8591 | [
"self.description = description\nself.icap_uri = icap_uri\nself.tag = tag\nself.tag_id = tag_id",
"if dictionary is None:\n return None\ndescription = dictionary.get('description')\nicap_uri = dictionary.get('icapUri')\ntag = dictionary.get('tag')\ntag_id = dictionary.get('tagId')\nreturn cls(description, icap... | <|body_start_0|>
self.description = description
self.icap_uri = icap_uri
self.tag = tag
self.tag_id = tag_id
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
description = dictionary.get('description')
icap_uri = dictionary.get('icap... | Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any additional information admin might associate with the Antivirus service. icap_uri (string, requir... | AntivirusServiceConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AntivirusServiceConfig:
"""Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any additional information admin might associate wi... | stack_v2_sparse_classes_36k_train_004852 | 2,737 | permissive | [
{
"docstring": "Constructor for the AntivirusServiceConfig class",
"name": "__init__",
"signature": "def __init__(self, description=None, icap_uri=None, tag=None, tag_id=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary repr... | 2 | stack_v2_sparse_classes_30k_train_001658 | Implement the Python class `AntivirusServiceConfig` described below.
Class description:
Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any addition... | Implement the Python class `AntivirusServiceConfig` described below.
Class description:
Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any addition... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class AntivirusServiceConfig:
"""Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any additional information admin might associate wi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AntivirusServiceConfig:
"""Implementation of the 'AntivirusServiceConfig' model. Specifies configuration settings for antivirus service provider. Attributes: description (string): Specifies the description of the Antivirus service. This could be any additional information admin might associate with the Antivi... | the_stack_v2_python_sparse | cohesity_management_sdk/models/antivirus_service_config.py | cohesity/management-sdk-python | train | 24 |
dacff19333bff583f964a34b294d7e0f8a24ffbe | [
"errors = dict()\nrevisions = dict()\nfor line in trs_import.csv_lines():\n document_key = line['document_key']\n revision = int(line['revision'])\n if document_key not in revisions:\n revisions[document_key] = list()\n revisions[document_key].append(revision)\nlatest_revisions = Document.objects... | <|body_start_0|>
errors = dict()
revisions = dict()
for line in trs_import.csv_lines():
document_key = line['document_key']
revision = int(line['revision'])
if document_key not in revisions:
revisions[document_key] = list()
revision... | Global revision number validator. | RevisionsValidator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RevisionsValidator:
"""Global revision number validator."""
def validate(self, trs_import):
"""Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to check that all the revisions to create will have following... | stack_v2_sparse_classes_36k_train_004853 | 11,148 | permissive | [
{
"docstring": "Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to check that all the revisions to create will have following numbers.",
"name": "validate",
"signature": "def validate(self, trs_import)"
},
{
"docstri... | 2 | null | Implement the Python class `RevisionsValidator` described below.
Class description:
Global revision number validator.
Method signatures and docstrings:
- def validate(self, trs_import): Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to c... | Implement the Python class `RevisionsValidator` described below.
Class description:
Global revision number validator.
Method signatures and docstrings:
- def validate(self, trs_import): Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to c... | 60ff6f37778971ae356c5b2b20e0d174a8288bfe | <|skeleton|>
class RevisionsValidator:
"""Global revision number validator."""
def validate(self, trs_import):
"""Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to check that all the revisions to create will have following... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RevisionsValidator:
"""Global revision number validator."""
def validate(self, trs_import):
"""Validate the revision numbers. Multiple revisions of the same document can be created in a single csv. Because of that, we need to check that all the revisions to create will have following numbers."""
... | the_stack_v2_python_sparse | src/transmittals/validation.py | Talengi/phase | train | 8 |
2c7ab504802770985868fb45a4c59d1f2a8b6c40 | [
"qn = db.connection.ops.quote_name\nqs = _select_related_instances(Entry, 'section', [1], 'batch_select_entry', 'section_id')\ndb.reset_queries()\nlist(qs)\nsql = db.connection.queries[-1]['sql']\nself.failUnless(sql.startswith('SELECT (%s.%s) AS ' % (qn('batch_select_entry'), qn('section_id'))))",
"section = Sec... | <|body_start_0|>
qn = db.connection.ops.quote_name
qs = _select_related_instances(Entry, 'section', [1], 'batch_select_entry', 'section_id')
db.reset_queries()
list(qs)
sql = db.connection.queries[-1]['sql']
self.failUnless(sql.startswith('SELECT (%s.%s) AS ' % (qn('batch... | Ensure correct quoting of table and field names in queries | QuotingTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuotingTestCase:
"""Ensure correct quoting of table and field names in queries"""
def test_uses_backend_specific_quoting(self):
"""Backend-specific quotes should be used Table and field names should be quoted with the quote_name function provided by the database backend. The test her... | stack_v2_sparse_classes_36k_train_004854 | 39,573 | no_license | [
{
"docstring": "Backend-specific quotes should be used Table and field names should be quoted with the quote_name function provided by the database backend. The test here is a bit trivial since a real-life test case with PostgreSQL schema tricks or other table/field name munging would be difficult.",
"name"... | 2 | stack_v2_sparse_classes_30k_train_019716 | Implement the Python class `QuotingTestCase` described below.
Class description:
Ensure correct quoting of table and field names in queries
Method signatures and docstrings:
- def test_uses_backend_specific_quoting(self): Backend-specific quotes should be used Table and field names should be quoted with the quote_nam... | Implement the Python class `QuotingTestCase` described below.
Class description:
Ensure correct quoting of table and field names in queries
Method signatures and docstrings:
- def test_uses_backend_specific_quoting(self): Backend-specific quotes should be used Table and field names should be quoted with the quote_nam... | 0ac6653219c2701c13c508c5c4fc9bc3437eea06 | <|skeleton|>
class QuotingTestCase:
"""Ensure correct quoting of table and field names in queries"""
def test_uses_backend_specific_quoting(self):
"""Backend-specific quotes should be used Table and field names should be quoted with the quote_name function provided by the database backend. The test her... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuotingTestCase:
"""Ensure correct quoting of table and field names in queries"""
def test_uses_backend_specific_quoting(self):
"""Backend-specific quotes should be used Table and field names should be quoted with the quote_name function provided by the database backend. The test here is a bit tr... | the_stack_v2_python_sparse | repoData/lilspikey-django-batch-select/allPythonContent.py | aCoffeeYin/pyreco | train | 0 |
862c8250b34df1a532ee8a8bd5b21dfb8afda9e9 | [
"super().__init__()\nself.conv1 = SuperGATConv(in_dim, hidden_dim, num_heads, attn_type, neg_sample_ratio, feat_drop, attn_drop, negative_slope, F.elu)\nself.conv2 = SuperGATConv(num_heads * hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio, 0, attn_drop, negative_slope)",
"h = self.conv1(g, feat).flatt... | <|body_start_0|>
super().__init__()
self.conv1 = SuperGATConv(in_dim, hidden_dim, num_heads, attn_type, neg_sample_ratio, feat_drop, attn_drop, negative_slope, F.elu)
self.conv2 = SuperGATConv(num_heads * hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio, 0, attn_drop, negative_slope)
... | SuperGAT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperGAT:
def __init__(self, in_dim, hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio=0.5, feat_drop=0.0, attn_drop=0.0, negative_slope=0.2):
"""两层SuperGAT模型 :param in_dim: int 输入特征维数 :param hidden_dim: int 隐含特征维数 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param ... | stack_v2_sparse_classes_36k_train_004855 | 5,266 | no_license | [
{
"docstring": "两层SuperGAT模型 :param in_dim: int 输入特征维数 :param hidden_dim: int 隐含特征维数 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param attn_type: str 注意力类型，可选择GO, DP, SD和MX :param neg_sample_ratio: float, optional 负样本边数量占正样本边数量的比例，默认0.5 :param feat_drop: float, optional 输入特征Dropout概率，默认为0 :param at... | 2 | stack_v2_sparse_classes_30k_train_012577 | Implement the Python class `SuperGAT` described below.
Class description:
Implement the SuperGAT class.
Method signatures and docstrings:
- def __init__(self, in_dim, hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio=0.5, feat_drop=0.0, attn_drop=0.0, negative_slope=0.2): 两层SuperGAT模型 :param in_dim: int 输入特... | Implement the Python class `SuperGAT` described below.
Class description:
Implement the SuperGAT class.
Method signatures and docstrings:
- def __init__(self, in_dim, hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio=0.5, feat_drop=0.0, attn_drop=0.0, negative_slope=0.2): 两层SuperGAT模型 :param in_dim: int 输入特... | b40071dc9f9fb20f081f4ed4944a7b65de919c18 | <|skeleton|>
class SuperGAT:
def __init__(self, in_dim, hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio=0.5, feat_drop=0.0, attn_drop=0.0, negative_slope=0.2):
"""两层SuperGAT模型 :param in_dim: int 输入特征维数 :param hidden_dim: int 隐含特征维数 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperGAT:
def __init__(self, in_dim, hidden_dim, out_dim, num_heads, attn_type, neg_sample_ratio=0.5, feat_drop=0.0, attn_drop=0.0, negative_slope=0.2):
"""两层SuperGAT模型 :param in_dim: int 输入特征维数 :param hidden_dim: int 隐含特征维数 :param out_dim: int 输出特征维数 :param num_heads: int 注意力头数K :param attn_type: str... | the_stack_v2_python_sparse | gnn/supergat/model.py | deepdumbo/pytorch-tutorial-1 | train | 0 | |
99316f5465fb225bf04da7bfa63b27f5d4bace76 | [
"if heuristics not in [-1, 1, 2]:\n print('Invalid value for heuristics parameter.' + 'Check python3 robinmax.py --help.')\nepsilon = utils.epsilon(graph)\nself.graph = graph\nself.thresh_budget = thresh_budget\nself.max_thresh_dev = max_thresh_dev\nself.weight_budget = weight_budget\nself.max_weight_dev = max_w... | <|body_start_0|>
if heuristics not in [-1, 1, 2]:
print('Invalid value for heuristics parameter.' + 'Check python3 robinmax.py --help.')
epsilon = utils.epsilon(graph)
self.graph = graph
self.thresh_budget = thresh_budget
self.max_thresh_dev = max_thresh_dev
s... | The parameter class. Contains all the parameters necessary for the algorithm. | RobinmaxArgs | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RobinmaxArgs:
"""The parameter class. Contains all the parameters necessary for the algorithm."""
def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds, heuristics, disable_cuts, solve_as_lp, debug_level, out_f):
... | stack_v2_sparse_classes_36k_train_004856 | 3,360 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds, heuristics, disable_cuts, solve_as_lp, debug_level, out_f)"
},
{
"docstring": "Convert to string for pri... | 2 | stack_v2_sparse_classes_30k_train_007719 | Implement the Python class `RobinmaxArgs` described below.
Class description:
The parameter class. Contains all the parameters necessary for the algorithm.
Method signatures and docstrings:
- def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds,... | Implement the Python class `RobinmaxArgs` described below.
Class description:
The parameter class. Contains all the parameters necessary for the algorithm.
Method signatures and docstrings:
- def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds,... | 0745a09bcfa6f527817602433755afe6dea33f02 | <|skeleton|>
class RobinmaxArgs:
"""The parameter class. Contains all the parameters necessary for the algorithm."""
def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds, heuristics, disable_cuts, solve_as_lp, debug_level, out_f):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RobinmaxArgs:
"""The parameter class. Contains all the parameters necessary for the algorithm."""
def __init__(self, graph, thresh_budget, max_thresh_dev, weight_budget, max_weight_dev, max_cover_size, time_limit, num_seeds, heuristics, disable_cuts, solve_as_lp, debug_level, out_f):
"""Construct... | the_stack_v2_python_sparse | robinmax_args.py | sartorg/robinmax | train | 1 |
037c756c1c6721da6b1b95bcd77e54c144604b72 | [
"self.anchor = anchor\nself.sentence = sentence\nself.event_domain = event_domain\nself.event_type = event_type\nself.score = 0\nself._allocate_arrays(max_sentence_length, neighbor_distance)",
"int_type = 'int32'\nnum_labels = len(self.event_domain.event_types)\nself.label = np.zeros(num_labels, dtype=int_type)\n... | <|body_start_0|>
self.anchor = anchor
self.sentence = sentence
self.event_domain = event_domain
self.event_type = event_type
self.score = 0
self._allocate_arrays(max_sentence_length, neighbor_distance)
<|end_body_0|>
<|body_start_1|>
int_type = 'int32'
nu... | EventTriggerExample | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.t... | stack_v2_sparse_classes_36k_train_004857 | 36,438 | permissive | [
{
"docstring": "We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.text.text_span.Sentence :type event_domain: nlplingo.event.event_domain.EventDomain :type params: dict :type event_type: str",
"name": "__... | 2 | stack_v2_sparse_classes_30k_train_006452 | Implement the Python class `EventTriggerExample` described below.
Class description:
Implement the EventTriggerExample class.
Method signatures and docstrings:
- def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None): We are given a token, sentence as context, and ... | Implement the Python class `EventTriggerExample` described below.
Class description:
Implement the EventTriggerExample class.
Method signatures and docstrings:
- def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None): We are given a token, sentence as context, and ... | 32ff17b1320937faa3d3ebe727032f4b3e7a353d | <|skeleton|>
class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventTriggerExample:
def __init__(self, anchor, sentence, event_domain, max_sentence_length, neighbor_distance, event_type=None):
"""We are given a token, sentence as context, and event_type (present during training) :type anchor: nlplingo.text.text_span.Anchor :type sentence: nlplingo.text.text_span.... | the_stack_v2_python_sparse | nlplingo/sandbox/misc/event_trigger.py | BBN-E/nlplingo | train | 3 | |
f269327cb123dafd350fbf7b171333a5edd45f6d | [
"import collections\nimport itertools\nfrom __builtin__ import xrange\nf = collections.defaultdict(list)\nfor a, b, c in allowed:\n f[a + b].append(c)\nmemo = {}\n\ndef pyramid(bottom):\n if bottom not in memo:\n memo[bottom] = len(bottom) == 1 or any((pyramid(''.join(i)) for i in itertools.product(*(f... | <|body_start_0|>
import collections
import itertools
from __builtin__ import xrange
f = collections.defaultdict(list)
for a, b, c in allowed:
f[a + b].append(c)
memo = {}
def pyramid(bottom):
if bottom not in memo:
memo[bot... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def rewrite(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool DP, try them all!"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_004858 | 3,290 | no_license | [
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool",
"name": "pyramidTransition",
"signature": "def pyramidTransition(self, bottom, allowed)"
},
{
"docstring": ":type bottom: str :type allowed: List[str] :rtype: bool DP, try them all!",
"name": "rewrite",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_007313 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def rewrite(self, bottom, allowed): :type bottom: str :type allowed: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def pyramidTransition(self, bottom, allowed): :type bottom: str :type allowed: List[str] :rtype: bool
- def rewrite(self, bottom, allowed): :type bottom: str :type allowed: List[... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
<|body_0|>
def rewrite(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool DP, try them all!"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def pyramidTransition(self, bottom, allowed):
""":type bottom: str :type allowed: List[str] :rtype: bool"""
import collections
import itertools
from __builtin__ import xrange
f = collections.defaultdict(list)
for a, b, c in allowed:
f[a + b... | the_stack_v2_python_sparse | depth-first-search/756_Pyramid_Transition_Matrix.py | vsdrun/lc_public | train | 6 | |
3fb02a72c2fecc7279f623365e73158935fac589 | [
"self.ae = projetae.AutoEncodeur(2, 512, 128, 16, 0.01, 0.0012)\ninputdim = self.ae.input_dim\noutputdim = self.ae.decoder.output_dim\nself.assertEqual(inputdim, outputdim)",
"self.ae = projetae.AutoEncodeur(2, 512, 128, 16, 0.01, 0.0012)\npremiere_couche = self.ae.encoder.c1.units\nderniere_couche = self.ae.deco... | <|body_start_0|>
self.ae = projetae.AutoEncodeur(2, 512, 128, 16, 0.01, 0.0012)
inputdim = self.ae.input_dim
outputdim = self.ae.decoder.output_dim
self.assertEqual(inputdim, outputdim)
<|end_body_0|>
<|body_start_1|>
self.ae = projetae.AutoEncodeur(2, 512, 128, 16, 0.01, 0.0012... | Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension | TestSymmetrie | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSymmetrie:
"""Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension"""
def test_symmetrie(self):
"""Test de symmétrie: couche d'entrée et couche de sortie"""
<|body_0|>
def test_symmetrie_c1(self):
"""Test de symmétrie: prem... | stack_v2_sparse_classes_36k_train_004859 | 1,663 | no_license | [
{
"docstring": "Test de symmétrie: couche d'entrée et couche de sortie",
"name": "test_symmetrie",
"signature": "def test_symmetrie(self)"
},
{
"docstring": "Test de symmétrie: premiere couche apres entrée, derniere couche avant sortie",
"name": "test_symmetrie_c1",
"signature": "def tes... | 4 | stack_v2_sparse_classes_30k_train_006315 | Implement the Python class `TestSymmetrie` described below.
Class description:
Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension
Method signatures and docstrings:
- def test_symmetrie(self): Test de symmétrie: couche d'entrée et couche de sortie
- def test_symmetrie_c1(self): Te... | Implement the Python class `TestSymmetrie` described below.
Class description:
Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension
Method signatures and docstrings:
- def test_symmetrie(self): Test de symmétrie: couche d'entrée et couche de sortie
- def test_symmetrie_c1(self): Te... | bad9fe47ef72b66fad289985484de4d5c58c48eb | <|skeleton|>
class TestSymmetrie:
"""Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension"""
def test_symmetrie(self):
"""Test de symmétrie: couche d'entrée et couche de sortie"""
<|body_0|>
def test_symmetrie_c1(self):
"""Test de symmétrie: prem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSymmetrie:
"""Tests responsables de la confirmation que la k-eme et (n-k) couche ont la même dimension"""
def test_symmetrie(self):
"""Test de symmétrie: couche d'entrée et couche de sortie"""
self.ae = projetae.AutoEncodeur(2, 512, 128, 16, 0.01, 0.0012)
inputdim = self.ae.in... | the_stack_v2_python_sparse | AutoencodeurProbabiliste/sourceae/test_symmetrie.py | Anastasija-Kuramzina/ProjetAutoencodeur | train | 0 |
03c9bdc4e9a82386807ffa09b993f09e13e156b3 | [
"self.assertTrue(anagram('dormitory', 'dirtyroom'))\nself.assertTrue(anagram('iceman', 'cinema'))\nself.assertTrue(anagram('star', 'rats'))\nself.assertFalse(anagram('cat', 'dog'))",
"self.assertTrue(anagram_dd('dormitory', 'dirtyroom'))\nself.assertTrue(anagram_dd('iceman', 'cinema'))\nself.assertTrue(anagram_dd... | <|body_start_0|>
self.assertTrue(anagram('dormitory', 'dirtyroom'))
self.assertTrue(anagram('iceman', 'cinema'))
self.assertTrue(anagram('star', 'rats'))
self.assertFalse(anagram('cat', 'dog'))
<|end_body_0|>
<|body_start_1|>
self.assertTrue(anagram_dd('dormitory', 'dirtyroom'))... | AnagramTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnagramTest:
def test_anagram(self):
"""Testing the anagram function"""
<|body_0|>
def test_anagram_dd(self):
"""Testing the anagram default dict function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.assertTrue(anagram('dormitory', 'dirtyroo... | stack_v2_sparse_classes_36k_train_004860 | 4,060 | no_license | [
{
"docstring": "Testing the anagram function",
"name": "test_anagram",
"signature": "def test_anagram(self)"
},
{
"docstring": "Testing the anagram default dict function",
"name": "test_anagram_dd",
"signature": "def test_anagram_dd(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004418 | Implement the Python class `AnagramTest` described below.
Class description:
Implement the AnagramTest class.
Method signatures and docstrings:
- def test_anagram(self): Testing the anagram function
- def test_anagram_dd(self): Testing the anagram default dict function | Implement the Python class `AnagramTest` described below.
Class description:
Implement the AnagramTest class.
Method signatures and docstrings:
- def test_anagram(self): Testing the anagram function
- def test_anagram_dd(self): Testing the anagram default dict function
<|skeleton|>
class AnagramTest:
def test_a... | 79d3375b7b8db9236f51826623ffa1fd3966cce3 | <|skeleton|>
class AnagramTest:
def test_anagram(self):
"""Testing the anagram function"""
<|body_0|>
def test_anagram_dd(self):
"""Testing the anagram default dict function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnagramTest:
def test_anagram(self):
"""Testing the anagram function"""
self.assertTrue(anagram('dormitory', 'dirtyroom'))
self.assertTrue(anagram('iceman', 'cinema'))
self.assertTrue(anagram('star', 'rats'))
self.assertFalse(anagram('cat', 'dog'))
def test_anagram... | the_stack_v2_python_sparse | HW07-fransabetpour.py | fs412/codingsamples | train | 0 | |
b406ab7188b6d69dec0609e85796b95dd6982bf4 | [
"parser.add_argument('--group', help='Instance group name.', required=True)\nparser.add_argument('--action', help=\" Action to be performed on each instance. Currently only 'RECREATE' is\\n supported.\\n \", choices=['RECREATE'], default='RECREATE')\nparser.add_argument('--template', required=T... | <|body_start_0|>
parser.add_argument('--group', help='Instance group name.', required=True)
parser.add_argument('--action', help=" Action to be performed on each instance. Currently only 'RECREATE' is\n supported.\n ", choices=['RECREATE'], default='RECREATE')
parser.add_arg... | Starts a new rolling update. | Start | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Start:
"""Starts a new rolling update."""
def Args(parser):
"""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."""
... | stack_v2_sparse_classes_36k_train_004861 | 7,955 | 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"... | 3 | null | Implement the Python class `Start` described below.
Class description:
Starts a new rolling update.
Method signatures and docstrings:
- def Args(parser): 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 afte... | Implement the Python class `Start` described below.
Class description:
Starts a new rolling update.
Method signatures and docstrings:
- def Args(parser): 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 afte... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Start:
"""Starts a new rolling update."""
def Args(parser):
"""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."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Start:
"""Starts a new rolling update."""
def Args(parser):
"""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."""
parser.ad... | the_stack_v2_python_sparse | google-cloud-sdk/lib/surface/compute/rolling_updates/start.py | KaranToor/MA450 | train | 1 |
5926d20c572ca47764388d0aae517aa287246236 | [
"if not os.path.isdir(modules_path):\n logging.error('No such directory: ' + modules_path)\nif not os.path.isdir(tests_directory_path):\n logging.error('No such directory: ' + tests_directory_path)\nself.modules_path = modules_path\nself.tests_directory = tests_directory_path\nself.default_template = 'puppet_... | <|body_start_0|>
if not os.path.isdir(modules_path):
logging.error('No such directory: ' + modules_path)
if not os.path.isdir(tests_directory_path):
logging.error('No such directory: ' + tests_directory_path)
self.modules_path = modules_path
self.tests_directory =... | Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for test files - tests_directory_path* Output directory where files will be written - debu... | PuppetTestGenerator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PuppetTestGenerator:
"""Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for test files - tests_directory_path* Outp... | stack_v2_sparse_classes_36k_train_004862 | 5,110 | permissive | [
{
"docstring": "Constructor Constructor",
"name": "__init__",
"signature": "def __init__(self, tests_directory_path, modules_path)"
},
{
"docstring": "Find modules in library path Find all Puppet modules in module_library_path and create array of PuppetModule objects",
"name": "find_modules"... | 6 | stack_v2_sparse_classes_30k_train_009735 | Implement the Python class `PuppetTestGenerator` described below.
Class description:
Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for ... | Implement the Python class `PuppetTestGenerator` described below.
Class description:
Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for ... | 178812b1971a900c49a8afc1688afd7475a6ffbb | <|skeleton|>
class PuppetTestGenerator:
"""Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for test files - tests_directory_path* Outp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PuppetTestGenerator:
"""Puppet Test Generator This is main class. It finds all modules in the given directory and creates tests for them. You should give constructor following arguments: - local_modules_path* Path to puppet modules which will be scanned for test files - tests_directory_path* Output directory ... | the_stack_v2_python_sparse | fuelweb_test/puppet_tests/pp_testgenerator.py | mingj/fuel-main | train | 0 |
130b616169f7318b61f47f3d6d3b8bed9408bb03 | [
"self.TempSensor = TempSensorAdapterTask.TempSensorAdapterTask()\nself.looplimit = loop_param\nself.sleeptime = sleep_param",
"i = 0\nself.TempSensor.sensorDataManager.SEND_EMAIL_NOTIFICATION = self.sendEmail\nif self.enableAdapter == False:\n return False\nwhile i < self.looplimit or self.LOOP_FOREVER == True... | <|body_start_0|>
self.TempSensor = TempSensorAdapterTask.TempSensorAdapterTask()
self.looplimit = loop_param
self.sleeptime = sleep_param
<|end_body_0|>
<|body_start_1|>
i = 0
self.TempSensor.sensorDataManager.SEND_EMAIL_NOTIFICATION = self.sendEmail
if self.enableAdapte... | Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with | TempSensorAdapter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TempSensorAdapter:
"""Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with"""
def __init__(self, loop_param=1, sleep_param=3):
"""Constructor"""
<|body_0|>
def run_temp_adapter... | stack_v2_sparse_classes_36k_train_004863 | 2,478 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, loop_param=1, sleep_param=3)"
},
{
"docstring": "Run method to run TempSensorAdapterTask and read temperature from the senseHAT",
"name": "run_temp_adapter",
"signature": "def run_temp_adapter(self) -> boo... | 2 | null | Implement the Python class `TempSensorAdapter` described below.
Class description:
Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with
Method signatures and docstrings:
- def __init__(self, loop_param=1, sleep_param=3): Co... | Implement the Python class `TempSensorAdapter` described below.
Class description:
Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with
Method signatures and docstrings:
- def __init__(self, loop_param=1, sleep_param=3): Co... | dfd5fd8c757cae8b1306ae3e4eb2cfc9bf124fee | <|skeleton|>
class TempSensorAdapter:
"""Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with"""
def __init__(self, loop_param=1, sleep_param=3):
"""Constructor"""
<|body_0|>
def run_temp_adapter... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TempSensorAdapter:
"""Method to run TempSensorAdapterTask takes in sleeptime and looptime in the constructor has a bunch of settings to control the program behavior with"""
def __init__(self, loop_param=1, sleep_param=3):
"""Constructor"""
self.TempSensor = TempSensorAdapterTask.TempSenso... | the_stack_v2_python_sparse | apps/labs/module03/TempSensorAdapter.py | mnk400/iot-device | train | 0 |
fb3af232f47e3a0c26bfb739b84c004280112591 | [
"self.start = start\nself.home = home\nself.left_limit = left_limit\nself.right_limit = right_limit\nsuper().__init__(start, home)",
"self.position += random.choice((-1, 1))\nif self.position < self.left_limit:\n self.position += 1\nelif self.position > self.right_limit:\n self.position -= 1\nelse:\n sel... | <|body_start_0|>
self.start = start
self.home = home
self.left_limit = left_limit
self.right_limit = right_limit
super().__init__(start, home)
<|end_body_0|>
<|body_start_1|>
self.position += random.choice((-1, 1))
if self.position < self.left_limit:
... | BoundedWalker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BoundedWalker:
def __init__(self, start, home, left_limit, right_limit):
"""Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home left_limit : int The left boundary of walker movement right_limit : int Th... | stack_v2_sparse_classes_36k_train_004864 | 2,633 | no_license | [
{
"docstring": "Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home left_limit : int The left boundary of walker movement right_limit : int The right boundary of walker movement",
"name": "__init__",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_009700 | Implement the Python class `BoundedWalker` described below.
Class description:
Implement the BoundedWalker class.
Method signatures and docstrings:
- def __init__(self, start, home, left_limit, right_limit): Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends w... | Implement the Python class `BoundedWalker` described below.
Class description:
Implement the BoundedWalker class.
Method signatures and docstrings:
- def __init__(self, start, home, left_limit, right_limit): Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends w... | 527f908422b559e6afc1ec025c04336d7a13828d | <|skeleton|>
class BoundedWalker:
def __init__(self, start, home, left_limit, right_limit):
"""Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home left_limit : int The left boundary of walker movement right_limit : int Th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BoundedWalker:
def __init__(self, start, home, left_limit, right_limit):
"""Initialise the walker Arguments --------- start : int The walker's initial position home : int The walk ends when the walker reaches home left_limit : int The left boundary of walker movement right_limit : int The right bounda... | the_stack_v2_python_sparse | src/nicolai_munsterhjelm_ex/ex05/bounded_sim.py | Nicomunster/INF200-2019-Exercises | train | 0 | |
3019803152bc7807f566570960c2ce0e37966fce | [
"if sens_type not in self._sens_types:\n raise ValueError('illegal sensitivity type: \"{}\"'.format(sens_type))\nif isinstance(sig, HDLModulePort):\n sig = sig.signal\nelif sig is None and sens_type != 'any':\n raise ValueError('signal cannot be None')\nif not isinstance(sig, (HDLSignal, HDLSignalSlice, ty... | <|body_start_0|>
if sens_type not in self._sens_types:
raise ValueError('illegal sensitivity type: "{}"'.format(sens_type))
if isinstance(sig, HDLModulePort):
sig = sig.signal
elif sig is None and sens_type != 'any':
raise ValueError('signal cannot be None')
... | Signal sensitivity descriptor. | HDLSensitivityDescriptor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HDLSensitivityDescriptor:
"""Signal sensitivity descriptor."""
def __init__(self, sens_type, sig=None):
"""Initialize."""
<|body_0|>
def dumps(self):
"""Get representation."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if sens_type not in self... | stack_v2_sparse_classes_36k_train_004865 | 2,166 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, sens_type, sig=None)"
},
{
"docstring": "Get representation.",
"name": "dumps",
"signature": "def dumps(self)"
}
] | 2 | null | Implement the Python class `HDLSensitivityDescriptor` described below.
Class description:
Signal sensitivity descriptor.
Method signatures and docstrings:
- def __init__(self, sens_type, sig=None): Initialize.
- def dumps(self): Get representation. | Implement the Python class `HDLSensitivityDescriptor` described below.
Class description:
Signal sensitivity descriptor.
Method signatures and docstrings:
- def __init__(self, sens_type, sig=None): Initialize.
- def dumps(self): Get representation.
<|skeleton|>
class HDLSensitivityDescriptor:
"""Signal sensitivi... | 463412cf6a72456acc8cb99569e7dc9c9d472f6d | <|skeleton|>
class HDLSensitivityDescriptor:
"""Signal sensitivity descriptor."""
def __init__(self, sens_type, sig=None):
"""Initialize."""
<|body_0|>
def dumps(self):
"""Get representation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HDLSensitivityDescriptor:
"""Signal sensitivity descriptor."""
def __init__(self, sens_type, sig=None):
"""Initialize."""
if sens_type not in self._sens_types:
raise ValueError('illegal sensitivity type: "{}"'.format(sens_type))
if isinstance(sig, HDLModulePort):
... | the_stack_v2_python_sparse | hdltools/abshdl/sens.py | brunosmmm/hdltools | train | 2 |
9eb6c1dae0d3fa4a63d952654441af02a645f4aa | [
"self._d_model = d_model\nself._dropout_rate = dropout_rate\nself._norm_epsilon = norm_epsilon\nself._sep_conv11x1 = transformer_layers.SeparableConv1DLayer(min_relative_pos=-10, max_relative_pos=0, output_size=int(2 * d_model), depthwise_filter_initializer_scale=initializer_scale, pointwise_filter_initializer_scal... | <|body_start_0|>
self._d_model = d_model
self._dropout_rate = dropout_rate
self._norm_epsilon = norm_epsilon
self._sep_conv11x1 = transformer_layers.SeparableConv1DLayer(min_relative_pos=-10, max_relative_pos=0, output_size=int(2 * d_model), depthwise_filter_initializer_scale=initializer... | The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right branch. The outputs of the branches are summed and then passed through a layer norm. The outpu... | DecoderConvolutionalLayer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderConvolutionalLayer:
"""The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right branch. The outputs of the branches are s... | stack_v2_sparse_classes_36k_train_004866 | 8,851 | permissive | [
{
"docstring": "Create an DecoderConvolutionalLayer. Args: d_model: a positive integer, the dimension of the model dim. dropout_rate: a float between 0 and 1. initializer_scale: a positive float, the scale for the initializers of the separable convolutional filters. norm_epsilon: a small positive float, the eps... | 2 | stack_v2_sparse_classes_30k_test_000502 | Implement the Python class `DecoderConvolutionalLayer` described below.
Class description:
The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right br... | Implement the Python class `DecoderConvolutionalLayer` described below.
Class description:
The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right br... | fbf7b1e547e8b8cb134e81e1cd350c312c0b5a16 | <|skeleton|>
class DecoderConvolutionalLayer:
"""The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right branch. The outputs of the branches are s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderConvolutionalLayer:
"""The convolutional layers custom to the evolved transformer decoder. The input is passed through a 11x1 separable convolution followed by a ReLU on the left branch while it goes through a 7x1 separable convolution on the right branch. The outputs of the branches are summed and the... | the_stack_v2_python_sparse | mesh_tensorflow/transformer/evolved_transformer.py | tensorflow/mesh | train | 1,508 |
8a3e9d4242b3d6d14a099314dde1b9f17797ff14 | [
"group = self._client.create(name=name, domain=domain, description=description)\nif check:\n self.check_group_presence(group, must_present=True)\n assert_that(group.name, equal_to(name))\n if domain:\n assert_that(group.domain, equal_to(domain))\n if description:\n assert_that(group.descri... | <|body_start_0|>
group = self._client.create(name=name, domain=domain, description=description)
if check:
self.check_group_presence(group, must_present=True)
assert_that(group.name, equal_to(name))
if domain:
assert_that(group.domain, equal_to(domain))... | Group steps. | GroupSteps | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupSteps:
"""Group steps."""
def create_group(self, name, domain=None, description=None, check=True):
"""Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`): the domain of the group description (str): the descript... | stack_v2_sparse_classes_36k_train_004867 | 4,589 | no_license | [
{
"docstring": "Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`): the domain of the group description (str): the description of the group Returns: keystoneclient.v3.groups.Group: the created group returned from server Raises: TimeoutExpired... | 5 | null | Implement the Python class `GroupSteps` described below.
Class description:
Group steps.
Method signatures and docstrings:
- def create_group(self, name, domain=None, description=None, check=True): Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`)... | Implement the Python class `GroupSteps` described below.
Class description:
Group steps.
Method signatures and docstrings:
- def create_group(self, name, domain=None, description=None, check=True): Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`)... | e7583444cd24893ec6ae237b47db7c605b99b0c5 | <|skeleton|>
class GroupSteps:
"""Group steps."""
def create_group(self, name, domain=None, description=None, check=True):
"""Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`): the domain of the group description (str): the descript... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupSteps:
"""Group steps."""
def create_group(self, name, domain=None, description=None, check=True):
"""Step to create a group. Args: name (str): the name of the group domain (str or class `keystoneclient.v3.domains.Domain`): the domain of the group description (str): the description of the gr... | the_stack_v2_python_sparse | stepler/keystone/steps/groups.py | Mirantis/stepler | train | 16 |
ad7ab7242d76583f371031362955e4d18af5c04c | [
"plugins = plugins or []\nif not service_provider:\n return\nkeystone_idp_id = settings.KEYSTONE_PROVIDER_IDP_ID\nif service_provider == keystone_idp_id:\n return None\nfor plugin in plugins:\n unscoped_idp_auth = plugin.get_plugin(plugins=plugins, auth_url=auth_url, **kwargs)\n if unscoped_idp_auth:\n ... | <|body_start_0|>
plugins = plugins or []
if not service_provider:
return
keystone_idp_id = settings.KEYSTONE_PROVIDER_IDP_ID
if service_provider == keystone_idp_id:
return None
for plugin in plugins:
unscoped_idp_auth = plugin.get_plugin(plugin... | K2KAuthPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class K2KAuthPlugin:
def get_plugin(self, service_provider=None, auth_url=None, plugins=None, **kwargs):
"""Authenticate using keystone to keystone federation. This plugin uses other v3 plugins to authenticate a user to a identity provider in order to authenticate the user to a service provide... | stack_v2_sparse_classes_36k_train_004868 | 3,943 | permissive | [
{
"docstring": "Authenticate using keystone to keystone federation. This plugin uses other v3 plugins to authenticate a user to a identity provider in order to authenticate the user to a service provider :param service_provider: service provider ID :param auth_url: Keystone auth url :param plugins: list of open... | 2 | null | Implement the Python class `K2KAuthPlugin` described below.
Class description:
Implement the K2KAuthPlugin class.
Method signatures and docstrings:
- def get_plugin(self, service_provider=None, auth_url=None, plugins=None, **kwargs): Authenticate using keystone to keystone federation. This plugin uses other v3 plugin... | Implement the Python class `K2KAuthPlugin` described below.
Class description:
Implement the K2KAuthPlugin class.
Method signatures and docstrings:
- def get_plugin(self, service_provider=None, auth_url=None, plugins=None, **kwargs): Authenticate using keystone to keystone federation. This plugin uses other v3 plugin... | 7896fd8c77a6766a1156a520946efaf792b76ca5 | <|skeleton|>
class K2KAuthPlugin:
def get_plugin(self, service_provider=None, auth_url=None, plugins=None, **kwargs):
"""Authenticate using keystone to keystone federation. This plugin uses other v3 plugins to authenticate a user to a identity provider in order to authenticate the user to a service provide... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class K2KAuthPlugin:
def get_plugin(self, service_provider=None, auth_url=None, plugins=None, **kwargs):
"""Authenticate using keystone to keystone federation. This plugin uses other v3 plugins to authenticate a user to a identity provider in order to authenticate the user to a service provider :param servi... | the_stack_v2_python_sparse | openstack_auth/plugin/k2k.py | openstack/horizon | train | 1,060 | |
4e52d4f0aa4670eac13826cab934920be18a5148 | [
"super(DecoderRNN, self).__init__()\nself.embed = nn.Embedding(vocab_size, embed_size)\nself.lstm = nn.LSTM(embed_size, hidden_size, num_layers, batch_first=True)\nself.linear = nn.Linear(hidden_size, vocab_size)\nself.init_weights()",
"self.embed.weight.data.uniform_(-0.1, 0.1)\nself.linear.weight.data.uniform_(... | <|body_start_0|>
super(DecoderRNN, self).__init__()
self.embed = nn.Embedding(vocab_size, embed_size)
self.lstm = nn.LSTM(embed_size, hidden_size, num_layers, batch_first=True)
self.linear = nn.Linear(hidden_size, vocab_size)
self.init_weights()
<|end_body_0|>
<|body_start_1|>
... | DecoderRNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoderRNN:
def __init__(self, embed_size, hidden_size, vocab_size, num_layers):
"""Set the hyper-parameters and build the layers."""
<|body_0|>
def init_weights(self):
"""Initialize weights."""
<|body_1|>
def forward(self, features, captions, lengths):
... | stack_v2_sparse_classes_36k_train_004869 | 5,485 | no_license | [
{
"docstring": "Set the hyper-parameters and build the layers.",
"name": "__init__",
"signature": "def __init__(self, embed_size, hidden_size, vocab_size, num_layers)"
},
{
"docstring": "Initialize weights.",
"name": "init_weights",
"signature": "def init_weights(self)"
},
{
"doc... | 4 | stack_v2_sparse_classes_30k_train_014687 | Implement the Python class `DecoderRNN` described below.
Class description:
Implement the DecoderRNN class.
Method signatures and docstrings:
- def __init__(self, embed_size, hidden_size, vocab_size, num_layers): Set the hyper-parameters and build the layers.
- def init_weights(self): Initialize weights.
- def forwar... | Implement the Python class `DecoderRNN` described below.
Class description:
Implement the DecoderRNN class.
Method signatures and docstrings:
- def __init__(self, embed_size, hidden_size, vocab_size, num_layers): Set the hyper-parameters and build the layers.
- def init_weights(self): Initialize weights.
- def forwar... | 80150803ebe291db2b63db01115029b86f36a802 | <|skeleton|>
class DecoderRNN:
def __init__(self, embed_size, hidden_size, vocab_size, num_layers):
"""Set the hyper-parameters and build the layers."""
<|body_0|>
def init_weights(self):
"""Initialize weights."""
<|body_1|>
def forward(self, features, captions, lengths):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoderRNN:
def __init__(self, embed_size, hidden_size, vocab_size, num_layers):
"""Set the hyper-parameters and build the layers."""
super(DecoderRNN, self).__init__()
self.embed = nn.Embedding(vocab_size, embed_size)
self.lstm = nn.LSTM(embed_size, hidden_size, num_layers, ba... | the_stack_v2_python_sparse | tag_walk/fachung/models/tagwalk_cnn_rnn.py | Antobiotics/tagWalk | train | 2 | |
7b0cc1b07082df37919b963436d467c10074364a | [
"if num == 0:\n return 0\nreturn (num - 1) % 9 + 1",
"if num < 10:\n return num\nelse:\n res = 0\n for digit in str(num):\n res += int(digit)\n return self.addDigits(res)"
] | <|body_start_0|>
if num == 0:
return 0
return (num - 1) % 9 + 1
<|end_body_0|>
<|body_start_1|>
if num < 10:
return num
else:
res = 0
for digit in str(num):
res += int(digit)
return self.addDigits(res)
<|end_bod... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def addDigits(self, num):
""":type num: int :rtype: int"""
<|body_0|>
def addDigits_rec(self, num):
""":type num: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if num == 0:
return 0
return (num - 1) % ... | stack_v2_sparse_classes_36k_train_004870 | 735 | no_license | [
{
"docstring": ":type num: int :rtype: int",
"name": "addDigits",
"signature": "def addDigits(self, num)"
},
{
"docstring": ":type num: int :rtype: int",
"name": "addDigits_rec",
"signature": "def addDigits_rec(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addDigits(self, num): :type num: int :rtype: int
- def addDigits_rec(self, num): :type num: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def addDigits(self, num): :type num: int :rtype: int
- def addDigits_rec(self, num): :type num: int :rtype: int
<|skeleton|>
class Solution:
def addDigits(self, num):
... | 92b4b7c6b69d39bf79a9e20a9fc947304c2a1de5 | <|skeleton|>
class Solution:
def addDigits(self, num):
""":type num: int :rtype: int"""
<|body_0|>
def addDigits_rec(self, num):
""":type num: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def addDigits(self, num):
""":type num: int :rtype: int"""
if num == 0:
return 0
return (num - 1) % 9 + 1
def addDigits_rec(self, num):
""":type num: int :rtype: int"""
if num < 10:
return num
else:
res = 0
... | the_stack_v2_python_sparse | leet_0258_add_digits.py | kkaixiao/pythonalgo2 | train | 2 | |
f087aaa10b71c9afcc2f3bd32bc392eb8f59d516 | [
"cls._start_time = time.time()\nif not sys.stdout.isatty():\n return\nmax_length = cls.max_length - cls.indent - 3\nstring = string[:max_length]\nstring = ' ' * cls.indent + string + '...'\nsys.stdout.write(string)\nsys.stdout.flush()",
"if cls.print_time:\n time_string = f'{time.time() - cls._start_time:.2... | <|body_start_0|>
cls._start_time = time.time()
if not sys.stdout.isatty():
return
max_length = cls.max_length - cls.indent - 3
string = string[:max_length]
string = ' ' * cls.indent + string + '...'
sys.stdout.write(string)
sys.stdout.flush()
<|end_bod... | Class to nicely print out a command with timing info. | Command | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Class to nicely print out a command with timing info."""
def start(cls, string):
"""Print the 'start command' string."""
<|body_0|>
def end(cls, string):
"""Print the 'end of command' string."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_004871 | 7,457 | permissive | [
{
"docstring": "Print the 'start command' string.",
"name": "start",
"signature": "def start(cls, string)"
},
{
"docstring": "Print the 'end of command' string.",
"name": "end",
"signature": "def end(cls, string)"
}
] | 2 | null | Implement the Python class `Command` described below.
Class description:
Class to nicely print out a command with timing info.
Method signatures and docstrings:
- def start(cls, string): Print the 'start command' string.
- def end(cls, string): Print the 'end of command' string. | Implement the Python class `Command` described below.
Class description:
Class to nicely print out a command with timing info.
Method signatures and docstrings:
- def start(cls, string): Print the 'start command' string.
- def end(cls, string): Print the 'end of command' string.
<|skeleton|>
class Command:
"""Cl... | 88bf7f7c5ac44defc046ebf0719cde748092cfff | <|skeleton|>
class Command:
"""Class to nicely print out a command with timing info."""
def start(cls, string):
"""Print the 'start command' string."""
<|body_0|>
def end(cls, string):
"""Print the 'end of command' string."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""Class to nicely print out a command with timing info."""
def start(cls, string):
"""Print the 'start command' string."""
cls._start_time = time.time()
if not sys.stdout.isatty():
return
max_length = cls.max_length - cls.indent - 3
string = s... | the_stack_v2_python_sparse | src/dials/util/command_line.py | dials/dials | train | 71 |
b341a80d0b98d20bd612ab580d168513811c5f8f | [
"attr_d = source.AttrDict(zip('aeiou', range(1, 6)))\nattr_d.a = 0\nself.assertTrue('a' not in attr_d.__dict__, 'Wrong attribute assignment in AttrDict')\nself.assertEqual(attr_d['a'], 0, 'Wrong attribute assignment in AttrDict')\nself.assertEqual(attr_d.a, 0, 'Wrong attribute assignment in AttrDict')",
"attr_d =... | <|body_start_0|>
attr_d = source.AttrDict(zip('aeiou', range(1, 6)))
attr_d.a = 0
self.assertTrue('a' not in attr_d.__dict__, 'Wrong attribute assignment in AttrDict')
self.assertEqual(attr_d['a'], 0, 'Wrong attribute assignment in AttrDict')
self.assertEqual(attr_d.a, 0, 'Wrong ... | Test exercise mod 06 AttrDict | TestAttrDict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAttrDict:
"""Test exercise mod 06 AttrDict"""
def test_setattr_existent(self):
"""Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists"""
<|body_0|>
def test_setattr_new(self):
"""Check __setattr__ customization of At... | stack_v2_sparse_classes_36k_train_004872 | 8,327 | no_license | [
{
"docstring": "Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists",
"name": "test_setattr_existent",
"signature": "def test_setattr_existent(self)"
},
{
"docstring": "Check __setattr__ customization of AttrDict. It must update a dictionary key only if... | 4 | stack_v2_sparse_classes_30k_train_017780 | Implement the Python class `TestAttrDict` described below.
Class description:
Test exercise mod 06 AttrDict
Method signatures and docstrings:
- def test_setattr_existent(self): Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists
- def test_setattr_new(self): Check __setattr_... | Implement the Python class `TestAttrDict` described below.
Class description:
Test exercise mod 06 AttrDict
Method signatures and docstrings:
- def test_setattr_existent(self): Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists
- def test_setattr_new(self): Check __setattr_... | 8f082201e24f0f2b991d9388500fdbf95d6f073d | <|skeleton|>
class TestAttrDict:
"""Test exercise mod 06 AttrDict"""
def test_setattr_existent(self):
"""Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists"""
<|body_0|>
def test_setattr_new(self):
"""Check __setattr__ customization of At... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAttrDict:
"""Test exercise mod 06 AttrDict"""
def test_setattr_existent(self):
"""Check __setattr__ customization of AttrDict. It must update a dictionary key only if it exists"""
attr_d = source.AttrDict(zip('aeiou', range(1, 6)))
attr_d.a = 0
self.assertTrue('a' not ... | the_stack_v2_python_sparse | intermediate/exercises/mod_04_data_model/tests_mod_04.py | garciacastano09/pycourse | train | 0 |
7fa046e92ae745dab30e1f6d57a67417b35c612c | [
"state_id = self.request.get('sid')\nif not state_id:\n self.ReportError('Missing required parameters.', status=400)\n return\nstate = ndb.Key(page_state.PageState, state_id).get()\nif not state:\n self.ReportError('Invalid sid.', status=400)\n return\nself.response.out.write(state.value)",
"state = s... | <|body_start_0|>
state_id = self.request.get('sid')
if not state_id:
self.ReportError('Missing required parameters.', status=400)
return
state = ndb.Key(page_state.PageState, state_id).get()
if not state:
self.ReportError('Invalid sid.', status=400)
... | Handles short URI. | ShortUriHandler | [
"BSD-3-Clause",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShortUriHandler:
"""Handles short URI."""
def get(self):
"""Handles getting page states."""
<|body_0|>
def post(self):
"""Handles saving page states and getting state id."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
state_id = self.request.ge... | stack_v2_sparse_classes_36k_train_004873 | 1,456 | permissive | [
{
"docstring": "Handles getting page states.",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Handles saving page states and getting state id.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `ShortUriHandler` described below.
Class description:
Handles short URI.
Method signatures and docstrings:
- def get(self): Handles getting page states.
- def post(self): Handles saving page states and getting state id. | Implement the Python class `ShortUriHandler` described below.
Class description:
Handles short URI.
Method signatures and docstrings:
- def get(self): Handles getting page states.
- def post(self): Handles saving page states and getting state id.
<|skeleton|>
class ShortUriHandler:
"""Handles short URI."""
... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ShortUriHandler:
"""Handles short URI."""
def get(self):
"""Handles getting page states."""
<|body_0|>
def post(self):
"""Handles saving page states and getting state id."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShortUriHandler:
"""Handles short URI."""
def get(self):
"""Handles getting page states."""
state_id = self.request.get('sid')
if not state_id:
self.ReportError('Missing required parameters.', status=400)
return
state = ndb.Key(page_state.PageState,... | the_stack_v2_python_sparse | third_party/catapult/dashboard/dashboard/short_uri.py | metux/chromium-suckless | train | 5 |
e261913ca6a92f5484f083f1a655151de3e7f054 | [
"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!')"
] | <|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 management of links between Google Ads accounts and other accounts. | AccountLinkServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountLinkServiceServicer:
"""This service allows management of links between Google Ads accounts and other accounts."""
def GetAccountLink(self, request, context):
"""Returns the account link in full detail."""
<|body_0|>
def MutateAccountLink(self, request, context):
... | stack_v2_sparse_classes_36k_train_004874 | 3,318 | permissive | [
{
"docstring": "Returns the account link in full detail.",
"name": "GetAccountLink",
"signature": "def GetAccountLink(self, request, context)"
},
{
"docstring": "Creates or removes an account link.",
"name": "MutateAccountLink",
"signature": "def MutateAccountLink(self, request, context)... | 2 | stack_v2_sparse_classes_30k_train_013679 | Implement the Python class `AccountLinkServiceServicer` described below.
Class description:
This service allows management of links between Google Ads accounts and other accounts.
Method signatures and docstrings:
- def GetAccountLink(self, request, context): Returns the account link in full detail.
- def MutateAccou... | Implement the Python class `AccountLinkServiceServicer` described below.
Class description:
This service allows management of links between Google Ads accounts and other accounts.
Method signatures and docstrings:
- def GetAccountLink(self, request, context): Returns the account link in full detail.
- def MutateAccou... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class AccountLinkServiceServicer:
"""This service allows management of links between Google Ads accounts and other accounts."""
def GetAccountLink(self, request, context):
"""Returns the account link in full detail."""
<|body_0|>
def MutateAccountLink(self, request, context):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountLinkServiceServicer:
"""This service allows management of links between Google Ads accounts and other accounts."""
def GetAccountLink(self, request, context):
"""Returns the account link in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details(... | the_stack_v2_python_sparse | google/ads/google_ads/v4/proto/services/account_link_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
4674d8f45aa15b975aafc585bdbdc28224470ad6 | [
"if client is None:\n address = (self.host, self.port)\n self.socket = socket.socket()\n self.socket.connect(address)\nelse:\n self.socket = client\nreturn Connection.setup(self)",
"assert self.poll and self.socket\nstring = pickle.dumps(message)\nsize = len(string)\npacket = self.format % (size, self... | <|body_start_0|>
if client is None:
address = (self.host, self.port)
self.socket = socket.socket()
self.socket.connect(address)
else:
self.socket = client
return Connection.setup(self)
<|end_body_0|>
<|body_start_1|>
assert self.poll and s... | Client | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Client:
def setup(self, client=None):
"""Connect to the given address. If a host connection object is not already listening on this address, this will not work."""
<|body_0|>
def send(self, message):
"""Send a message across this connection. The message is converted ... | stack_v2_sparse_classes_36k_train_004875 | 5,772 | no_license | [
{
"docstring": "Connect to the given address. If a host connection object is not already listening on this address, this will not work.",
"name": "setup",
"signature": "def setup(self, client=None)"
},
{
"docstring": "Send a message across this connection. The message is converted to a string us... | 3 | stack_v2_sparse_classes_30k_train_005767 | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def setup(self, client=None): Connect to the given address. If a host connection object is not already listening on this address, this will not work.
- def send(self, message): Send ... | Implement the Python class `Client` described below.
Class description:
Implement the Client class.
Method signatures and docstrings:
- def setup(self, client=None): Connect to the given address. If a host connection object is not already listening on this address, this will not work.
- def send(self, message): Send ... | 4a7485044b35c73bb4ecd0c6499fe1060d338c54 | <|skeleton|>
class Client:
def setup(self, client=None):
"""Connect to the given address. If a host connection object is not already listening on this address, this will not work."""
<|body_0|>
def send(self, message):
"""Send a message across this connection. The message is converted ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Client:
def setup(self, client=None):
"""Connect to the given address. If a host connection object is not already listening on this address, this will not work."""
if client is None:
address = (self.host, self.port)
self.socket = socket.socket()
self.socket.... | the_stack_v2_python_sparse | network.py | kxgames/ClayPygeons | train | 0 | |
95108fbafc5973988bc322e247eddddd5d98999a | [
"transitions = model.transitions\nintent_logits, slots_logits = model.logits\ninput_intent_y, input_slots_y = model.input_y\nintent_score = tf.nn.softmax(intent_logits, name='intent_score')\nintent_preds = tf.argmax(intent_logits, axis=-1, name='intent_preds')\ny_intent_ground_truth = tf.argmax(input_intent_y, axis... | <|body_start_0|>
transitions = model.transitions
intent_logits, slots_logits = model.logits
input_intent_y, input_slots_y = model.input_y
intent_score = tf.nn.softmax(intent_logits, name='intent_score')
intent_preds = tf.argmax(intent_logits, axis=-1, name='intent_preds')
... | Solver for NLU joint model. | RawNLUJointSolver | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RawNLUJointSolver:
"""Solver for NLU joint model."""
def build_output(self, model):
"""Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation."""
<|body_0|>
def build_export_output(self, mode... | stack_v2_sparse_classes_36k_train_004876 | 3,365 | permissive | [
{
"docstring": "Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation.",
"name": "build_output",
"signature": "def build_output(self, model)"
},
{
"docstring": "Build the output of the model for export. `score` and ... | 2 | null | Implement the Python class `RawNLUJointSolver` described below.
Class description:
Solver for NLU joint model.
Method signatures and docstrings:
- def build_output(self, model): Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation.
- de... | Implement the Python class `RawNLUJointSolver` described below.
Class description:
Solver for NLU joint model.
Method signatures and docstrings:
- def build_output(self, model): Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation.
- de... | 7eb4e3be578a680737616efff6858d280595ff48 | <|skeleton|>
class RawNLUJointSolver:
"""Solver for NLU joint model."""
def build_output(self, model):
"""Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation."""
<|body_0|>
def build_export_output(self, mode... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RawNLUJointSolver:
"""Solver for NLU joint model."""
def build_output(self, model):
"""Build the output of the model. `score` and `input_y` are for loss calculation. `preds` and `y_ground_truth` are for metric calculation."""
transitions = model.transitions
intent_logits, slots_lo... | the_stack_v2_python_sparse | delta/utils/solver/raw_nlu_joint_solver.py | luffywalf/delta | train | 1 |
11af807d4c795e1dc52c10bc098ecc1c3c2b8c65 | [
"if delta_r is None:\n delta_r = 0\nif offset is None:\n offset = Point(0, 0, 0)\nif angle is None:\n angle = 0\nif weld_params is None:\n weld_params = WeldingState()\nself.offset = offset\nself.delta_r = delta_r\nself.angle = angle\nself.welding_parameters = weld_params",
"if not mod.offset.is_zero(... | <|body_start_0|>
if delta_r is None:
delta_r = 0
if offset is None:
offset = Point(0, 0, 0)
if angle is None:
angle = 0
if weld_params is None:
weld_params = WeldingState()
self.offset = offset
self.delta_r = delta_r
... | Modification | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Modification:
def __init__(self, offset=None, delta_r=None, angle=None, weld_params=None):
"""Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: offset {Point} -- offset (x,y,z) in meters (default: Point(0,0,0)) delta_r {float} -- delta r angle (d... | stack_v2_sparse_classes_36k_train_004877 | 2,560 | permissive | [
{
"docstring": "Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: offset {Point} -- offset (x,y,z) in meters (default: Point(0,0,0)) delta_r {float} -- delta r angle (default: 0) angle {float} -- torch angle (default: 0) weld_params {WeldingState} -- welding parameters ... | 2 | stack_v2_sparse_classes_30k_train_005147 | Implement the Python class `Modification` described below.
Class description:
Implement the Modification class.
Method signatures and docstrings:
- def __init__(self, offset=None, delta_r=None, angle=None, weld_params=None): Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: o... | Implement the Python class `Modification` described below.
Class description:
Implement the Modification class.
Method signatures and docstrings:
- def __init__(self, offset=None, delta_r=None, angle=None, weld_params=None): Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: o... | 7c39e1e5a6e98fc6c8dfcae6abf033f5d961b16c | <|skeleton|>
class Modification:
def __init__(self, offset=None, delta_r=None, angle=None, weld_params=None):
"""Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: offset {Point} -- offset (x,y,z) in meters (default: Point(0,0,0)) delta_r {float} -- delta r angle (d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Modification:
def __init__(self, offset=None, delta_r=None, angle=None, weld_params=None):
"""Initalize a Modification object Arguments: object {Modification} -- self Keyword Arguments: offset {Point} -- offset (x,y,z) in meters (default: Point(0,0,0)) delta_r {float} -- delta r angle (default: 0) ang... | the_stack_v2_python_sparse | src/rosweld/modification.py | HuaiLeiTang/rosweld_tools | train | 0 | |
4f3b0318c630b43da88388ca43e9262bd47dd651 | [
"pmf = thinkbayes.MakePoissonPmf(r, high, step=step)\nthinkbayes.Suite.__init__(self, pmf, name=r)\nself.r = r\nself.f = f",
"k = data\nn = hypo\np = self.f\nreturn thinkbayes.EvalBinomialPmf(k, n, p)",
"total = 0\nfor hypo, prob in self.Items():\n like = self.Likelihood(data, hypo)\n total += prob * like... | <|body_start_0|>
pmf = thinkbayes.MakePoissonPmf(r, high, step=step)
thinkbayes.Suite.__init__(self, pmf, name=r)
self.r = r
self.f = f
<|end_body_0|>
<|body_start_1|>
k = data
n = hypo
p = self.f
return thinkbayes.EvalBinomialPmf(k, n, p)
<|end_body_1|>
... | Represents hypotheses about n. | Detector | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
<|body_0... | stack_v2_sparse_classes_36k_train_004878 | 5,605 | permissive | [
{
"docstring": "Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n",
"name": "__init__",
"signature": "def __init__(self, r, f, high=500, step=5)"
},
{
"docstring": "Likelihood... | 3 | stack_v2_sparse_classes_30k_train_020649 | Implement the Python class `Detector` described below.
Class description:
Represents hypotheses about n.
Method signatures and docstrings:
- def __init__(self, r, f, high=500, step=5): Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step ... | Implement the Python class `Detector` described below.
Class description:
Represents hypotheses about n.
Method signatures and docstrings:
- def __init__(self, r, f, high=500, step=5): Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step ... | 53c7ce7ca7da62c9fbb3d991ae9e4e34d07ece5f | <|skeleton|>
class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
<|body_0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Detector:
"""Represents hypotheses about n."""
def __init__(self, r, f, high=500, step=5):
"""Initializes the suite. r: known emission rate, r f: fraction of particles registered high: maximum number of particles, n step: step size between hypothetical values of n"""
pmf = thinkbayes.Make... | the_stack_v2_python_sparse | python/learn/thinkbayes/jaynes.py | qrsforever/workspace | train | 2 |
a45bd42e3b29a6af758443782d1d7d411982823b | [
"super(Encoder, self).__init__()\nself.N = N\nself.dm = dm\nself.embedding = tf.keras.layers.Embedding(input_vocab, dm)\nself.positional_encoding = positional_encoding(max_seq_len, self.dm)\nself.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N)]\nself.dropout = tf.keras.layers.Dropout(drop_rate)",... | <|body_start_0|>
super(Encoder, self).__init__()
self.N = N
self.dm = dm
self.embedding = tf.keras.layers.Embedding(input_vocab, dm)
self.positional_encoding = positional_encoding(max_seq_len, self.dm)
self.blocks = [EncoderBlock(dm, h, hidden, drop_rate) for _ in range(N... | Encoder class for machine translation | Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] input_vocab ([type]): [... | stack_v2_sparse_classes_36k_train_004879 | 12,086 | no_license | [
{
"docstring": "[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] input_vocab ([type]): [description] max_seq_len ([type]): [description] drop_rate (float, optional): [description]. Defaults to 0.1.",
"name": "__init__",
"signat... | 2 | stack_v2_sparse_classes_30k_train_001961 | Implement the Python class `Encoder` described below.
Class description:
Encoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): [summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [descriptio... | Implement the Python class `Encoder` described below.
Class description:
Encoder class for machine translation
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1): [summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [descriptio... | 5f86dee95f4d1c32014d0d74a368f342ff3ce6f7 | <|skeleton|>
class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] input_vocab ([type]): [... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
"""Encoder class for machine translation"""
def __init__(self, N, dm, h, hidden, input_vocab, max_seq_len, drop_rate=0.1):
"""[summary] Args: N ([type]): [description] dm ([type]): [description] h ([type]): [description] hidden ([type]): [description] input_vocab ([type]): [description] ... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | d1sd41n/holbertonschool-machine_learning | train | 0 |
2d963f97e1d156da99ddb4473f36552dae6ae79b | [
"self.K = K\nif folder is not None:\n self.MoE_list = [None for k in range(K)]\n self.load(folder)\nelse:\n if type(N_exp_list) is int:\n N_exp_list = [N_exp_list for k in range(self.K)]\n if len(N_exp_list) != self.K:\n raise TypeError(\"Lenght of number of expters list doesn't match numb... | <|body_start_0|>
self.K = K
if folder is not None:
self.MoE_list = [None for k in range(K)]
self.load(folder)
else:
if type(N_exp_list) is int:
N_exp_list = [N_exp_list for k in range(self.K)]
if len(N_exp_list) != self.K:
... | This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they shall have same gating function model but might have different experts num... | MoE_list | [
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MoE_list:
"""This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they shall have same gating function model ... | stack_v2_sparse_classes_36k_train_004880 | 4,450 | permissive | [
{
"docstring": "Initialise class. If folder is given, model is loaded from folder. Otherwise a softmax gating function model is built with the required dimensionality and number of experts. Input: K number of MoE models in MoE_list folder folder at which the model should be loaded from. (If None, nothing is loa... | 6 | stack_v2_sparse_classes_30k_train_018646 | Implement the Python class `MoE_list` described below.
Class description:
This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they... | Implement the Python class `MoE_list` described below.
Class description:
This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they... | a786e9ce5845ba1f82980c5265307914c3c26e68 | <|skeleton|>
class MoE_list:
"""This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they shall have same gating function model ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MoE_list:
"""This class contains a list of MoE models and deals with them easily. This might be useful for multidimensional regression where each target dimension is fitted separately by a MoE model. All models must have same input space dimensionality; they shall have same gating function model but might hav... | the_stack_v2_python_sparse | dev/tries_checks/routines/MoE_list.py | stefanoschmidt1995/MLGW | train | 12 |
3d6095f593566bb252c83d23cc22d904bb93cbff | [
"rows = len(matrix)\ncols = len(matrix[0])\nresult = [[None] * rows for _ in range(cols)]\nfor i in range(rows):\n for j in range(cols):\n col = cols - i - 1\n result[j][col] = matrix[i][j]\nreturn result",
"size = len(matrix)\nfor row in range(size):\n for column in range(row, size):\n ... | <|body_start_0|>
rows = len(matrix)
cols = len(matrix[0])
result = [[None] * rows for _ in range(cols)]
for i in range(rows):
for j in range(cols):
col = cols - i - 1
result[j][col] = matrix[i][j]
return result
<|end_body_0|>
<|body_st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate_1(self, matrix):
""":type matrix: list of list of int :rtype: list of list of int"""
<|body_0|>
def rotate_2(self, matrix):
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
def rotate(self, matrix):
""... | stack_v2_sparse_classes_36k_train_004881 | 2,528 | no_license | [
{
"docstring": ":type matrix: list of list of int :rtype: list of list of int",
"name": "rotate_1",
"signature": "def rotate_1(self, matrix)"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"name": "rotate_2",
"signature": "def rotate_2(self, matrix)"
},
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_1(self, matrix): :type matrix: list of list of int :rtype: list of list of int
- def rotate_2(self, matrix): Do not return anything, modify matrix in-place instead.
- ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate_1(self, matrix): :type matrix: list of list of int :rtype: list of list of int
- def rotate_2(self, matrix): Do not return anything, modify matrix in-place instead.
- ... | ec48cbde4356208afac226d41752daffe674be2c | <|skeleton|>
class Solution:
def rotate_1(self, matrix):
""":type matrix: list of list of int :rtype: list of list of int"""
<|body_0|>
def rotate_2(self, matrix):
"""Do not return anything, modify matrix in-place instead."""
<|body_1|>
def rotate(self, matrix):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate_1(self, matrix):
""":type matrix: list of list of int :rtype: list of list of int"""
rows = len(matrix)
cols = len(matrix[0])
result = [[None] * rows for _ in range(cols)]
for i in range(rows):
for j in range(cols):
col =... | the_stack_v2_python_sparse | B2BSWE/Arrays/rotate_2d_array_90_degree_clockwise.py | librar127/PythonDS | train | 0 | |
0d9d0fcb29341f051b4b31640a98976da53f2422 | [
"for id, op in vars(cls).items():\n if isinstance(op, IOperation) and op.is_valid(operator, left, right):\n if isinstance(op, BinaryOperation):\n return op.build(left, right)\n else:\n from boa3.model.type.type import Type\n operand = right if left is Type.none else... | <|body_start_0|>
for id, op in vars(cls).items():
if isinstance(op, IOperation) and op.is_valid(operator, left, right):
if isinstance(op, BinaryOperation):
return op.build(left, right)
else:
from boa3.model.type.type import Type... | BinaryOp | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right opera... | stack_v2_sparse_classes_36k_train_004882 | 4,052 | permissive | [
{
"docstring": "Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right operand :return: The operation if exists. None otherwise; :rtype: BinaryOperation or None",
"name": "validate_type",
"... | 3 | stack_v2_sparse_classes_30k_train_011899 | Implement the Python class `BinaryOp` described below.
Class description:
Implement the BinaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]: Gets a binary operation given the operator and the operands types. :param oper... | Implement the Python class `BinaryOp` described below.
Class description:
Implement the BinaryOp class.
Method signatures and docstrings:
- def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]: Gets a binary operation given the operator and the operands types. :param oper... | e4ef340744b5bd25ade26f847eac50789b97f3e9 | <|skeleton|>
class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right opera... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryOp:
def validate_type(cls, operator: Operator, left: IType, right: IType) -> Optional[BinaryOperation]:
"""Gets a binary operation given the operator and the operands types. :param operator: binary operator :param left: type of the left operand :param right: type of the right operand :return: Th... | the_stack_v2_python_sparse | boa3/model/operation/binaryop.py | DanPopa46/neo3-boa | train | 0 | |
64dbd40925d5339305904116929bd29b19eab3e7 | [
"interpol = pero.PowInterpol(power=2)\nself.assertAlmostEqual(interpol.normalize(50, 0, 100), 0.25, 10)\nself.assertAlmostEqual(interpol.denormalize(0.25, 0, 100), 50, 10)\nself.assertAlmostEqual(interpol.normalize(0.01, 1, 100), -0.0001, 10)\nself.assertAlmostEqual(interpol.denormalize(-0.0001, 1, 100), 0.01, 10)\... | <|body_start_0|>
interpol = pero.PowInterpol(power=2)
self.assertAlmostEqual(interpol.normalize(50, 0, 100), 0.25, 10)
self.assertAlmostEqual(interpol.denormalize(0.25, 0, 100), 50, 10)
self.assertAlmostEqual(interpol.normalize(0.01, 1, 100), -0.0001, 10)
self.assertAlmostEqual(i... | Test case for power interpolator. | 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 power interpolator."""
def test_pow(self):
"""Tests whether interpolator works with 2 exponent."""
<|body_0|>
def test_sqrt(self):
"""Tests whether interpolator works with 1/2 exponent."""
<|body_1|>
def test_arrays(self):
... | stack_v2_sparse_classes_36k_train_004883 | 2,120 | permissive | [
{
"docstring": "Tests whether interpolator works with 2 exponent.",
"name": "test_pow",
"signature": "def test_pow(self)"
},
{
"docstring": "Tests whether interpolator works with 1/2 exponent.",
"name": "test_sqrt",
"signature": "def test_sqrt(self)"
},
{
"docstring": "Tests whet... | 3 | null | Implement the Python class `TestCase` described below.
Class description:
Test case for power interpolator.
Method signatures and docstrings:
- def test_pow(self): Tests whether interpolator works with 2 exponent.
- def test_sqrt(self): Tests whether interpolator works with 1/2 exponent.
- def test_arrays(self): Test... | Implement the Python class `TestCase` described below.
Class description:
Test case for power interpolator.
Method signatures and docstrings:
- def test_pow(self): Tests whether interpolator works with 2 exponent.
- def test_sqrt(self): Tests whether interpolator works with 1/2 exponent.
- def test_arrays(self): Test... | d59b1bc056f3037b7b7ab635b6deb41120612965 | <|skeleton|>
class TestCase:
"""Test case for power interpolator."""
def test_pow(self):
"""Tests whether interpolator works with 2 exponent."""
<|body_0|>
def test_sqrt(self):
"""Tests whether interpolator works with 1/2 exponent."""
<|body_1|>
def test_arrays(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCase:
"""Test case for power interpolator."""
def test_pow(self):
"""Tests whether interpolator works with 2 exponent."""
interpol = pero.PowInterpol(power=2)
self.assertAlmostEqual(interpol.normalize(50, 0, 100), 0.25, 10)
self.assertAlmostEqual(interpol.denormalize(0... | the_stack_v2_python_sparse | unittests/scales/test_pow.py | xxao/pero | train | 31 |
f589878f9056f5a44b4d6c0ac540962556174c79 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn AccessReviewHistoryScheduleSettings()",
"from .patterned_recurrence import PatternedRecurrence\nfrom .patterned_recurrence import PatternedRecurrence\nfields: Dict[str, Callable[[Any], None]] = {'@odata.type': lambda n: setattr(self, '... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return AccessReviewHistoryScheduleSettings()
<|end_body_0|>
<|body_start_1|>
from .patterned_recurrence import PatternedRecurrence
from .patterned_recurrence import PatternedRecurrence
... | AccessReviewHistoryScheduleSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccessReviewHistoryScheduleSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewHistoryScheduleSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discr... | stack_v2_sparse_classes_36k_train_004884 | 3,414 | 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: AccessReviewHistoryScheduleSettings",
"name": "create_from_discriminator_value",
"signature": "def create_fr... | 3 | null | Implement the Python class `AccessReviewHistoryScheduleSettings` described below.
Class description:
Implement the AccessReviewHistoryScheduleSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewHistoryScheduleSettings: Creates a ... | Implement the Python class `AccessReviewHistoryScheduleSettings` described below.
Class description:
Implement the AccessReviewHistoryScheduleSettings class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewHistoryScheduleSettings: Creates a ... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AccessReviewHistoryScheduleSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewHistoryScheduleSettings:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccessReviewHistoryScheduleSettings:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AccessReviewHistoryScheduleSettings:
"""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... | the_stack_v2_python_sparse | msgraph/generated/models/access_review_history_schedule_settings.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
b34232f3efbb7c2a39774ced02fb876516e47467 | [
"self.pv1_enabled = False\nself.pv2_enabled = False\nself.output1_enabled = False\nself.output2_enabled = False\nself.timestamp = None\nself.reading = []\nsuper().__init__()",
"try:\n self.timestamp = None\n self.reading = []\n ts = _time.time()\n if self.pv1_enabled:\n pv1 = _air_udc.read_pv1(... | <|body_start_0|>
self.pv1_enabled = False
self.pv2_enabled = False
self.output1_enabled = False
self.output2_enabled = False
self.timestamp = None
self.reading = []
super().__init__()
<|end_body_0|>
<|body_start_1|>
try:
self.timestamp = None
... | Read values worker. | ReadValueWorker | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self):
"""Initialize object."""
<|body_0|>
def run(self):
"""Read values from devices."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pv1_enabled = False
self.pv2_enabled = Fa... | stack_v2_sparse_classes_36k_train_004885 | 5,163 | no_license | [
{
"docstring": "Initialize object.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Read values from devices.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003602 | Implement the Python class `ReadValueWorker` described below.
Class description:
Read values worker.
Method signatures and docstrings:
- def __init__(self): Initialize object.
- def run(self): Read values from devices. | Implement the Python class `ReadValueWorker` described below.
Class description:
Read values worker.
Method signatures and docstrings:
- def __init__(self): Initialize object.
- def run(self): Read values from devices.
<|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self):
... | 25a9256522ea82e181639294e6d23ab2372a76b4 | <|skeleton|>
class ReadValueWorker:
"""Read values worker."""
def __init__(self):
"""Initialize object."""
<|body_0|>
def run(self):
"""Read values from devices."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReadValueWorker:
"""Read values worker."""
def __init__(self):
"""Initialize object."""
self.pv1_enabled = False
self.pv2_enabled = False
self.output1_enabled = False
self.output2_enabled = False
self.timestamp = None
self.reading = []
super... | the_stack_v2_python_sparse | hallbench/gui/airconditioningwidget.py | lnls-ima/hall-bench-control | train | 1 |
1478d9fafae4c2fe36b83996707609d776611c9d | [
"serialized = []\n\ndef recurse(root):\n if root:\n serialized.append(str(root.val))\n recurse(root.left)\n recurse(root.right)\n else:\n serialized.append('#')\nrecurse(root)\nreturn ' '.join(serialized)",
"def buildTree(vals):\n val = next(vals)\n if val == '#':\n ... | <|body_start_0|>
serialized = []
def recurse(root):
if root:
serialized.append(str(root.val))
recurse(root.left)
recurse(root.right)
else:
serialized.append('#')
recurse(root)
return ' '.join(seriali... | 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_004886 | 1,750 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 6de551327f96ec4d4b63d0045281b65bbb4f5d0f | <|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"""
serialized = []
def recurse(root):
if root:
serialized.append(str(root.val))
recurse(root.left)
recurse(root.right)
... | the_stack_v2_python_sparse | serialize.py | JingweiTu/leetcode | train | 0 | |
8f628d9883f132531e7589e207ab2ae7091bff3e | [
"print(\"'%s' is a scalar value of type '%s'.\" % (expr, value.type))\nprint('%s = %s' % (expr, str(value)))\nif is_child:\n Explorer.return_to_parent_value_prompt()\n Explorer.return_to_parent_value()\nreturn False",
"if datatype.code == gdb.TYPE_CODE_ENUM:\n if is_child:\n print(\"%s is of an en... | <|body_start_0|>
print("'%s' is a scalar value of type '%s'." % (expr, value.type))
print('%s = %s' % (expr, str(value)))
if is_child:
Explorer.return_to_parent_value_prompt()
Explorer.return_to_parent_value()
return False
<|end_body_0|>
<|body_start_1|>
... | Internal class used to explore scalar values. | ScalarExplorer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScalarExplorer:
"""Internal class used to explore scalar values."""
def explore_expr(expr, value, is_child):
"""Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information."""
<|body_0|>
def explore_type(name, datatype, i... | stack_v2_sparse_classes_36k_train_004887 | 26,692 | permissive | [
{
"docstring": "Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information.",
"name": "explore_expr",
"signature": "def explore_expr(expr, value, is_child)"
},
{
"docstring": "Function to explore scalar types. See Explorer.explore_type and Explo... | 2 | stack_v2_sparse_classes_30k_train_020372 | Implement the Python class `ScalarExplorer` described below.
Class description:
Internal class used to explore scalar values.
Method signatures and docstrings:
- def explore_expr(expr, value, is_child): Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information.
- de... | Implement the Python class `ScalarExplorer` described below.
Class description:
Internal class used to explore scalar values.
Method signatures and docstrings:
- def explore_expr(expr, value, is_child): Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information.
- de... | b90664de0bd4c1897a9f1f5d9e360a9631d38b34 | <|skeleton|>
class ScalarExplorer:
"""Internal class used to explore scalar values."""
def explore_expr(expr, value, is_child):
"""Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information."""
<|body_0|>
def explore_type(name, datatype, i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScalarExplorer:
"""Internal class used to explore scalar values."""
def explore_expr(expr, value, is_child):
"""Function to explore scalar values. See Explorer.explore_expr and Explorer.is_scalar_type for more information."""
print("'%s' is a scalar value of type '%s'." % (expr, value.typ... | the_stack_v2_python_sparse | toolchain/riscv/Linux/share/gdb/python/gdb/command/explore.py | bouffalolab/bl_iot_sdk | train | 244 |
e86d931933aee7d90c7745d2d0d90c8952bdb3d7 | [
"coords, instructs = parse(filename)\nmax_x = 0\nmax_y = 0\nfor x, y in coords:\n max_x = max(x, max_x)\n max_y = max(y, max_y)\nif max_x == 1305:\n max_x = 1310\nif max_y == 893:\n max_y = 894\ngrid = np.zeros((max_y + 1, max_x + 1), dtype=int)\nfor x, y in coords:\n grid[y][x] = 1\nfor var, amt in ... | <|body_start_0|>
coords, instructs = parse(filename)
max_x = 0
max_y = 0
for x, y in coords:
max_x = max(x, max_x)
max_y = max(y, max_y)
if max_x == 1305:
max_x = 1310
if max_y == 893:
max_y = 894
grid = np.zeros((ma... | AoC 2021 Day 13 | Day13 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Day13:
"""AoC 2021 Day 13"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 13 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2021 day 13 part 2"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_004888 | 2,946 | no_license | [
{
"docstring": "Given a filename, solve 2021 day 13 part 1",
"name": "part1",
"signature": "def part1(filename: str) -> int"
},
{
"docstring": "Given a filename, solve 2021 day 13 part 2",
"name": "part2",
"signature": "def part2(filename: str) -> int"
}
] | 2 | stack_v2_sparse_classes_30k_train_011947 | Implement the Python class `Day13` described below.
Class description:
AoC 2021 Day 13
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2021 day 13 part 1
- def part2(filename: str) -> int: Given a filename, solve 2021 day 13 part 2 | Implement the Python class `Day13` described below.
Class description:
AoC 2021 Day 13
Method signatures and docstrings:
- def part1(filename: str) -> int: Given a filename, solve 2021 day 13 part 1
- def part2(filename: str) -> int: Given a filename, solve 2021 day 13 part 2
<|skeleton|>
class Day13:
"""AoC 202... | e89db235837d2d05848210a18c9c2a4456085570 | <|skeleton|>
class Day13:
"""AoC 2021 Day 13"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 13 part 1"""
<|body_0|>
def part2(filename: str) -> int:
"""Given a filename, solve 2021 day 13 part 2"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Day13:
"""AoC 2021 Day 13"""
def part1(filename: str) -> int:
"""Given a filename, solve 2021 day 13 part 1"""
coords, instructs = parse(filename)
max_x = 0
max_y = 0
for x, y in coords:
max_x = max(x, max_x)
max_y = max(y, max_y)
if... | the_stack_v2_python_sparse | 2021/python2021/aoc/day13.py | mreishus/aoc | train | 16 |
57c4b6fb18cb2da88aadfed95fc5a616080a2b02 | [
"super().__init__(parent)\nself.setupUi(self)\nself.name = 'Data'\nself.config = DataConfig()\nself.pixelScaleLineEdit.setValidator(QDoubleValidator(0.0, LARGE_FLOAT_VALUE_FOR_VALIDATOR, 5))\nself.sigmaScaleLineEdit.setValidator(QDoubleValidator(-LARGE_FLOAT_VALUE_FOR_VALIDATOR, LARGE_FLOAT_VALUE_FOR_VALIDATOR, 5))... | <|body_start_0|>
super().__init__(parent)
self.setupUi(self)
self.name = 'Data'
self.config = DataConfig()
self.pixelScaleLineEdit.setValidator(QDoubleValidator(0.0, LARGE_FLOAT_VALUE_FOR_VALIDATOR, 5))
self.sigmaScaleLineEdit.setValidator(QDoubleValidator(-LARGE_FLOAT_VA... | Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget. | DataConfigTab | [
"Python-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataConfigTab:
"""Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget."""
def __init__(self, parent=None):
"""Initialize the class. Parameters ---------- parent : None, optional Top-level widget."""
<|body_0|>
def g... | stack_v2_sparse_classes_36k_train_004889 | 3,230 | permissive | [
{
"docstring": "Initialize the class. Parameters ---------- parent : None, optional Top-level widget.",
"name": "__init__",
"signature": "def __init__(self, parent=None)"
},
{
"docstring": "Get the configuration parameter's from the tab's widgets. Returns ------- `config.DataConfig` The current ... | 3 | null | Implement the Python class `DataConfigTab` described below.
Class description:
Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget.
Method signatures and docstrings:
- def __init__(self, parent=None): Initialize the class. Parameters ---------- parent : None, op... | Implement the Python class `DataConfigTab` described below.
Class description:
Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget.
Method signatures and docstrings:
- def __init__(self, parent=None): Initialize the class. Parameters ---------- parent : None, op... | 3d0242276198126240667ba13e95b7bdf901d053 | <|skeleton|>
class DataConfigTab:
"""Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget."""
def __init__(self, parent=None):
"""Initialize the class. Parameters ---------- parent : None, optional Top-level widget."""
<|body_0|>
def g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataConfigTab:
"""Class that handles the data configuration tab. Attributes ---------- name : str The name for the tab widget."""
def __init__(self, parent=None):
"""Initialize the class. Parameters ---------- parent : None, optional Top-level widget."""
super().__init__(parent)
s... | the_stack_v2_python_sparse | spot_motion_monitor/views/data_config_tab.py | lsst-sitcom/spot_motion_monitor | train | 0 |
01e83003debc5ad3df30a4bb95a10981412a4ddb | [
"from apysc.expression import expression_variables_util\nfrom apysc.expression.event_handler_scope import TemporaryNotHandlerScope\nwith TemporaryNotHandlerScope():\n result: CopyInterface = deepcopy(self)\n result.variable_name = expression_variables_util.get_next_variable_name(type_name=self.type_name)\n ... | <|body_start_0|>
from apysc.expression import expression_variables_util
from apysc.expression.event_handler_scope import TemporaryNotHandlerScope
with TemporaryNotHandlerScope():
result: CopyInterface = deepcopy(self)
result.variable_name = expression_variables_util.get_n... | CopyInterface | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopyInterface:
def _copy(self) -> Any:
"""Make a deep copy of this instance. Returns ------- result : * Copied instance."""
<|body_0|>
def _append_copy_expression(self, result_variable_name: str) -> None:
"""Append copy expression to file. Parameters ---------- resul... | stack_v2_sparse_classes_36k_train_004890 | 1,553 | permissive | [
{
"docstring": "Make a deep copy of this instance. Returns ------- result : * Copied instance.",
"name": "_copy",
"signature": "def _copy(self) -> Any"
},
{
"docstring": "Append copy expression to file. Parameters ---------- result_variable_name : str Copied value's variable name.",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_005305 | Implement the Python class `CopyInterface` described below.
Class description:
Implement the CopyInterface class.
Method signatures and docstrings:
- def _copy(self) -> Any: Make a deep copy of this instance. Returns ------- result : * Copied instance.
- def _append_copy_expression(self, result_variable_name: str) ->... | Implement the Python class `CopyInterface` described below.
Class description:
Implement the CopyInterface class.
Method signatures and docstrings:
- def _copy(self) -> Any: Make a deep copy of this instance. Returns ------- result : * Copied instance.
- def _append_copy_expression(self, result_variable_name: str) ->... | 5c6a4674e2e9684cb2cb1325dc9b070879d4d355 | <|skeleton|>
class CopyInterface:
def _copy(self) -> Any:
"""Make a deep copy of this instance. Returns ------- result : * Copied instance."""
<|body_0|>
def _append_copy_expression(self, result_variable_name: str) -> None:
"""Append copy expression to file. Parameters ---------- resul... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CopyInterface:
def _copy(self) -> Any:
"""Make a deep copy of this instance. Returns ------- result : * Copied instance."""
from apysc.expression import expression_variables_util
from apysc.expression.event_handler_scope import TemporaryNotHandlerScope
with TemporaryNotHandlerS... | the_stack_v2_python_sparse | apysc/type/copy_interface.py | TrendingTechnology/apysc | train | 0 | |
584268f75e9ca287fcc298e53a60aeddde4726ac | [
"m, n = (len(board), len(board[0]))\nfor i, j in product(range(m), range(n)):\n cnt = 0\n for di, dj in product(range(-1, 2), repeat=2):\n if di != 0 or dj != 0:\n ii, jj = (i + di, j + dj)\n if 0 <= ii < m and 0 <= jj < n:\n cnt += board[ii][jj] & 1\n if cnt == ... | <|body_start_0|>
m, n = (len(board), len(board[0]))
for i, j in product(range(m), range(n)):
cnt = 0
for di, dj in product(range(-1, 2), repeat=2):
if di != 0 or dj != 0:
ii, jj = (i + di, j + dj)
if 0 <= ii < m and 0 <= jj ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def gameOfLifeBit(self, board):
""":type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead."""
<|body_0|>
def gameOfLife(self, board):
""":type board: List[List[int]] :rtype: None Do not return anything, modify board ... | stack_v2_sparse_classes_36k_train_004891 | 4,934 | no_license | [
{
"docstring": ":type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead.",
"name": "gameOfLifeBit",
"signature": "def gameOfLifeBit(self, board)"
},
{
"docstring": ":type board: List[List[int]] :rtype: None Do not return anything, modify board in-place ins... | 2 | stack_v2_sparse_classes_30k_train_016730 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gameOfLifeBit(self, board): :type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead.
- def gameOfLife(self, board): :type board: List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def gameOfLifeBit(self, board): :type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead.
- def gameOfLife(self, board): :type board: List[... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def gameOfLifeBit(self, board):
""":type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead."""
<|body_0|>
def gameOfLife(self, board):
""":type board: List[List[int]] :rtype: None Do not return anything, modify board ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def gameOfLifeBit(self, board):
""":type board: List[List[int]] :rtype: None Do not return anything, modify board in-place instead."""
m, n = (len(board), len(board[0]))
for i, j in product(range(m), range(n)):
cnt = 0
for di, dj in product(range(-1, 2... | the_stack_v2_python_sparse | G/GameOfLife.py | bssrdf/pyleet | train | 2 | |
89ef6e14d4646b1732802e0548ae21f484fe1055 | [
"if not isinstance(K, Sequence) or len(K) != 3 or (not all((isinstance(x, Real) for x in K))):\n self.throw(ValueError, 'K must be a list or tuple of 3 real numbers, P, I, and D')\nself.K_P, self.K_I, self.K_D = K or DEFAULT_K\nself.P, self.I, self.D = (0.0, 0.0, 0.0)\nself.RC = RC\nself.dt = dt",
"decay = sel... | <|body_start_0|>
if not isinstance(K, Sequence) or len(K) != 3 or (not all((isinstance(x, Real) for x in K))):
self.throw(ValueError, 'K must be a list or tuple of 3 real numbers, P, I, and D')
self.K_P, self.K_I, self.K_D = K or DEFAULT_K
self.P, self.I, self.D = (0.0, 0.0, 0.0)
... | PID: agent that plays a PID policy Todo: - Allow for variable time deltas | PID | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PID:
"""PID: agent that plays a PID policy Todo: - Allow for variable time deltas"""
def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None:
"""Description: initializes the PID agent Args: K (Sequence[int]): sequence of PID parameters RC (Real): deca... | stack_v2_sparse_classes_36k_train_004892 | 2,144 | permissive | [
{
"docstring": "Description: initializes the PID agent Args: K (Sequence[int]): sequence of PID parameters RC (Real): decay parameter dt (Real): time increment Returns: None",
"name": "__init__",
"signature": "def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None"
},... | 2 | stack_v2_sparse_classes_30k_train_016595 | Implement the Python class `PID` described below.
Class description:
PID: agent that plays a PID policy Todo: - Allow for variable time deltas
Method signatures and docstrings:
- def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None: Description: initializes the PID agent Args: K (S... | Implement the Python class `PID` described below.
Class description:
PID: agent that plays a PID policy Todo: - Allow for variable time deltas
Method signatures and docstrings:
- def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None: Description: initializes the PID agent Args: K (S... | 74ba003fb24cae78f86016f6e1de3aeeff25d89d | <|skeleton|>
class PID:
"""PID: agent that plays a PID policy Todo: - Allow for variable time deltas"""
def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None:
"""Description: initializes the PID agent Args: K (Sequence[int]): sequence of PID parameters RC (Real): deca... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PID:
"""PID: agent that plays a PID policy Todo: - Allow for variable time deltas"""
def __init__(self, K: Sequence[int]=None, RC: Real=0.5, dt: Real=0.03, **kwargs) -> None:
"""Description: initializes the PID agent Args: K (Sequence[int]): sequence of PID parameters RC (Real): decay parameter d... | the_stack_v2_python_sparse | deluca/agents/_pid.py | MinRegret/deluca | train | 27 |
7122c079cdfa9351606d8b53e4dcdd84f4978827 | [
"power = 0\nfor dy in range(y, y + size - 1):\n power += self.cells[x + size - 1, dy]\nfor dx in range(x, x + size):\n power += self.cells[dx, y + size - 1]\nreturn power",
"if size == 1:\n return self.cells[x, y]\nelse:\n border = self.get_border_power(x, y, size)\n return self.get_square_power(x,... | <|body_start_0|>
power = 0
for dy in range(y, y + size - 1):
power += self.cells[x + size - 1, dy]
for dx in range(x, x + size):
power += self.cells[dx, y + size - 1]
return power
<|end_body_0|>
<|body_start_1|>
if size == 1:
return self.cells... | Grid with a cached square power calculation. | CachedGrid | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CachedGrid:
"""Grid with a cached square power calculation."""
def get_border_power(self, x: int, y: int, size: int) -> Power:
"""Calculate left and bottom area brims power."""
<|body_0|>
def get_square_power(self, x: int, y: int, size: int) -> Power:
"""Calculat... | stack_v2_sparse_classes_36k_train_004893 | 1,549 | permissive | [
{
"docstring": "Calculate left and bottom area brims power.",
"name": "get_border_power",
"signature": "def get_border_power(self, x: int, y: int, size: int) -> Power"
},
{
"docstring": "Calculate a cell square sum power by caching previous calls.",
"name": "get_square_power",
"signature... | 2 | null | Implement the Python class `CachedGrid` described below.
Class description:
Grid with a cached square power calculation.
Method signatures and docstrings:
- def get_border_power(self, x: int, y: int, size: int) -> Power: Calculate left and bottom area brims power.
- def get_square_power(self, x: int, y: int, size: in... | Implement the Python class `CachedGrid` described below.
Class description:
Grid with a cached square power calculation.
Method signatures and docstrings:
- def get_border_power(self, x: int, y: int, size: int) -> Power: Calculate left and bottom area brims power.
- def get_square_power(self, x: int, y: int, size: in... | 4b8ac6a97859b1320f77ba0ee91168b58db28cdb | <|skeleton|>
class CachedGrid:
"""Grid with a cached square power calculation."""
def get_border_power(self, x: int, y: int, size: int) -> Power:
"""Calculate left and bottom area brims power."""
<|body_0|>
def get_square_power(self, x: int, y: int, size: int) -> Power:
"""Calculat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CachedGrid:
"""Grid with a cached square power calculation."""
def get_border_power(self, x: int, y: int, size: int) -> Power:
"""Calculate left and bottom area brims power."""
power = 0
for dy in range(y, y + size - 1):
power += self.cells[x + size - 1, dy]
fo... | the_stack_v2_python_sparse | src/year2018/day11b.py | lancelote/advent_of_code | train | 11 |
b4977bf7b14d7cb44640fd1652348c04a546afb7 | [
"project, network, phases = cls._parse_args(network=network, phases=phases)\ndf = Pandas.export_data(network=network, phases=phases, join=True, delim=delim)\nif filename == '':\n filename = project.name\nfname = cls._parse_filename(filename=filename, ext='csv')\ndf.to_csv(fname, index=False)",
"from pandas imp... | <|body_start_0|>
project, network, phases = cls._parse_args(network=network, phases=phases)
df = Pandas.export_data(network=network, phases=phases, join=True, delim=delim)
if filename == '':
filename = project.name
fname = cls._parse_filename(filename=filename, ext='csv')
... | Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent rows contain the data. 2. The property names should be in the usual Open... | CSV | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSV:
"""Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent rows contain the data. 2. The property na... | stack_v2_sparse_classes_36k_train_004894 | 4,965 | permissive | [
{
"docstring": "Save all the pore and throat property data on the Network (and optionally on any Phases objects) to CSV files. Parameters ---------- network : OpenPNM Network The Network containing the data to be stored phases : list of OpenPNM Phases (optional) The Phases whose data should be stored. filename ... | 2 | stack_v2_sparse_classes_30k_train_020818 | Implement the Python class `CSV` described below.
Class description:
Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent ro... | Implement the Python class `CSV` described below.
Class description:
Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent ro... | 5ddd7f7317dd9c6d82e6db5256ec1800dd6eef5d | <|skeleton|>
class CSV:
"""Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent rows contain the data. 2. The property na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSV:
"""Reads and writes CSV (comma-separated-value files) containing pore and throat data Notes ----- There are a few rules governing how the data is be stored: 1. The first row of the file (column headers) must contain the property names. The subsequent rows contain the data. 2. The property names should be... | the_stack_v2_python_sparse | openpnm/io/_csv.py | ma-sadeghi/OpenPNM | train | 1 |
8b8f99308c08719fcdf6b9b418dac5dca68f25e9 | [
"text = Formatter.format_block(self, block)\ntext = self.indent(text, 2)\ntext = '::\\n\\n' + text\nreturn text",
"caption = elem.text\nif caption and caption.strip():\n caption = self.indent(textwrap.wrap(caption), 2)\n return '.. figure:: %s\\n\\n%s\\n' % (elem.get('filename'), caption)\nelse:\n return... | <|body_start_0|>
text = Formatter.format_block(self, block)
text = self.indent(text, 2)
text = '::\n\n' + text
return text
<|end_body_0|>
<|body_start_1|>
caption = elem.text
if caption and caption.strip():
caption = self.indent(textwrap.wrap(caption), 2)
... | Formatter for reST output. | ReSTFormatter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReSTFormatter:
"""Formatter for reST output."""
def format_block(self, block):
"""Format an <ipython-block> element."""
<|body_0|>
def format_figure(self, elem):
"""Format a <figure> element."""
<|body_1|>
def format_sheet(self, sheet):
"""Fo... | stack_v2_sparse_classes_36k_train_004895 | 2,064 | no_license | [
{
"docstring": "Format an <ipython-block> element.",
"name": "format_block",
"signature": "def format_block(self, block)"
},
{
"docstring": "Format a <figure> element.",
"name": "format_figure",
"signature": "def format_figure(self, elem)"
},
{
"docstring": "Format a reST sheet. ... | 3 | stack_v2_sparse_classes_30k_train_015467 | Implement the Python class `ReSTFormatter` described below.
Class description:
Formatter for reST output.
Method signatures and docstrings:
- def format_block(self, block): Format an <ipython-block> element.
- def format_figure(self, elem): Format a <figure> element.
- def format_sheet(self, sheet): Format a reST she... | Implement the Python class `ReSTFormatter` described below.
Class description:
Formatter for reST output.
Method signatures and docstrings:
- def format_block(self, block): Format an <ipython-block> element.
- def format_figure(self, elem): Format a <figure> element.
- def format_sheet(self, sheet): Format a reST she... | 9b32089282c94c706d819333a3a2388179e99e86 | <|skeleton|>
class ReSTFormatter:
"""Formatter for reST output."""
def format_block(self, block):
"""Format an <ipython-block> element."""
<|body_0|>
def format_figure(self, elem):
"""Format a <figure> element."""
<|body_1|>
def format_sheet(self, sheet):
"""Fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReSTFormatter:
"""Formatter for reST output."""
def format_block(self, block):
"""Format an <ipython-block> element."""
text = Formatter.format_block(self, block)
text = self.indent(text, 2)
text = '::\n\n' + text
return text
def format_figure(self, elem):
... | the_stack_v2_python_sparse | google-rkern/trunk/notabene/rest.py | minrk/ipython-svn-archive | train | 0 |
a2a7e7af2e545214939ee908cc17f519ba7f50de | [
"model = CGCNN(in_node_dim, hidden_node_dim, in_edge_dim, num_conv, predictor_hidden_feats, n_tasks, mode, n_classes)\nif mode == 'regression':\n loss: Loss = L2Loss()\n output_types = ['prediction']\nelse:\n loss = SparseSoftmaxCrossEntropy()\n output_types = ['prediction', 'loss']\nsuper(CGCNNModel, s... | <|body_start_0|>
model = CGCNN(in_node_dim, hidden_node_dim, in_edge_dim, num_conv, predictor_hidden_feats, n_tasks, mode, n_classes)
if mode == 'regression':
loss: Loss = L2Loss()
output_types = ['prediction']
else:
loss = SparseSoftmaxCrossEntropy()
... | Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCNNFeaturizer(), "transformers": []} >>> tasks, datasets, transformers = dc.mol... | CGCNNModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CGCNNModel:
"""Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCNNFeaturizer(), "transformers": []} >>> ... | stack_v2_sparse_classes_36k_train_004896 | 14,455 | permissive | [
{
"docstring": "This class accepts all the keyword arguments from TorchModel. Parameters ---------- in_node_dim: int, default 92 The length of the initial node feature vectors. The 92 is based on length of vectors in the atom_init.json. hidden_node_dim: int, default 64 The length of the hidden node feature vect... | 2 | null | Implement the Python class `CGCNNModel` described below.
Class description:
Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCN... | Implement the Python class `CGCNNModel` described below.
Class description:
Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCN... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class CGCNNModel:
"""Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCNNFeaturizer(), "transformers": []} >>> ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CGCNNModel:
"""Crystal Graph Convolutional Neural Network (CGCNN). Here is a simple example of code that uses the CGCNNModel with materials dataset. Examples -------- >>> import deepchem as dc >>> dataset_config = {"reload": False, "featurizer": dc.feat.CGCNNFeaturizer(), "transformers": []} >>> tasks, datase... | the_stack_v2_python_sparse | deepchem/models/torch_models/cgcnn.py | deepchem/deepchem | train | 4,876 |
7007de2fcf60e7f6c4ce3ba3aa18aa104a4dd5ed | [
"from numpy import array, dot, arccos, pi\nx = self.positionRelativeToSample(element)\nx = array(x)\nfrom . import units\nm = units.length.meter\ntry:\n x + m\n x /= m\nexcept:\n pass\nlx = vlen(x)\nbeam = self.request_coordinate_system().neutronBeamDirection\nlbeam = vlen(array(beam))\ncost = dot(x, beam)... | <|body_start_0|>
from numpy import array, dot, arccos, pi
x = self.positionRelativeToSample(element)
x = array(x)
from . import units
m = units.length.meter
try:
x + m
x /= m
except:
pass
lx = vlen(x)
beam = self... | A geometer that is most useful for inelastic direct-geometry chopper spectrometer. | ARCSGeometer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: Th... | stack_v2_sparse_classes_36k_train_004897 | 4,790 | no_license | [
{
"docstring": "scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: The element or the element signature Output: scattering angle, in radian Exceptions: KeyError Notes: scattering angle means angle from moderator to sample t... | 2 | stack_v2_sparse_classes_30k_train_018389 | Implement the Python class `ARCSGeometer` described below.
Class description:
A geometer that is most useful for inelastic direct-geometry chopper spectrometer.
Method signatures and docstrings:
- def scatteringAngle(self, element): scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle... | Implement the Python class `ARCSGeometer` described below.
Class description:
A geometer that is most useful for inelastic direct-geometry chopper spectrometer.
Method signatures and docstrings:
- def scatteringAngle(self, element): scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle... | 7d6fb88e7ec8245c488ab7988a8518de57dd73df | <|skeleton|>
class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: Th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ARCSGeometer:
"""A geometer that is most useful for inelastic direct-geometry chopper spectrometer."""
def scatteringAngle(self, element):
"""scatteringAngle( element) -> scattering angle in degrees Compute the scattering angle of the specified element in degrees. Inputs: element: The element or ... | the_stack_v2_python_sparse | instrument/geometers/ARCSGeometer.py | danse-inelastic/instrument | train | 0 |
a6c281e8f305aa16daccbae177e1962225fcf450 | [
"if not nums:\n return True\nsum_all = sum(nums)\nif sum_all & 1 == 1:\n return False\nsum_half = sum_all / 2\ndp = [[False for j in range(sum_half + 1)] for i in range(len(nums))]\nfor i in range(len(nums)):\n dp[i][0] = True\nfor i in range(1, len(nums)):\n for j in range(1, sum_half + 1):\n dp... | <|body_start_0|>
if not nums:
return True
sum_all = sum(nums)
if sum_all & 1 == 1:
return False
sum_half = sum_all / 2
dp = [[False for j in range(sum_half + 1)] for i in range(len(nums))]
for i in range(len(nums)):
dp[i][0] = True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return True
... | stack_v2_sparse_classes_36k_train_004898 | 1,997 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007454 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canPart... | 8853f85214ac88db024d26e228f1848dd5acd933 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
if not nums:
return True
sum_all = sum(nums)
if sum_all & 1 == 1:
return False
sum_half = sum_all / 2
dp = [[False for j in range(sum_half + 1)] for i in ran... | the_stack_v2_python_sparse | 416-PartitionEqualSubsetSum/PartitionEqualSubsetSum.py | cqxmzhc/my_leetcode_solutions | train | 2 | |
5fa9ac74608547f6c0963b65e1831279d1e3dee6 | [
"super(Decoder, self).__init__()\nself.example_size = example_size\nself.num_outputs = example_size[1] * example_size[0] * example_size[2]\nself.cuda_enabled = cuda_enabled\nfc1_output_size = 512\nfc2_output_size = 1024\nfc3_output_size = 4096\nfc4_output_size = 4096 * 3\nself.fc1 = nn.Linear(num_classes * output_u... | <|body_start_0|>
super(Decoder, self).__init__()
self.example_size = example_size
self.num_outputs = example_size[1] * example_size[0] * example_size[2]
self.cuda_enabled = cuda_enabled
fc1_output_size = 512
fc2_output_size = 1024
fc3_output_size = 4096
fc... | Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and send the [16,] vector to the decoder network to reconstruct a [784,] size ... | Decoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and send the [16,] vector to the decoder ne... | stack_v2_sparse_classes_36k_train_004899 | 3,631 | permissive | [
{
"docstring": "The decoder network consists of 3 fully connected layers, with 512, 1024, 784 neurons each.",
"name": "__init__",
"signature": "def __init__(self, num_classes, output_unit_size, cuda_enabled, example_size=(1, 28, 28))"
},
{
"docstring": "We send the outputs of the `DigitCaps` lay... | 2 | stack_v2_sparse_classes_30k_train_000230 | Implement the Python class `Decoder` described below.
Class description:
Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and ... | Implement the Python class `Decoder` described below.
Class description:
Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and ... | 0c6e7a6cccd7630751c8065befba14a0dbaeadd4 | <|skeleton|>
class Decoder:
"""Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and send the [16,] vector to the decoder ne... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Implement Decoder structure in section 4.1, Figure 2 to reconstruct a digit from the `DigitCaps` layer representation. The decoder network consists of 3 fully connected layers. For each [10, 16] output, we mask out the incorrect predictions, and send the [16,] vector to the decoder network to reco... | the_stack_v2_python_sparse | src/org/campagnelab/dl/pytorch/images/models/capsules/decoder.py | fac2003/ureg | train | 0 |
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