blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d1cf2693d6534155191cf92b85d6544d2c307cd2 | [
"data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])\nself.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea', realizations=np.array([1, 2]))\nself.plugin = DifferenceBetweenAdjacentGridSquares()",
"expected_x = np.array([[1, 1], [2, 2], [5, 5]])\nexpected_y = np.array([[1, 2, 3], [3, 6, 9]])\n... | <|body_start_0|>
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea', realizations=np.array([1, 2]))
self.plugin = DifferenceBetweenAdjacentGridSquares()
<|end_body_0|>
<|body_start_1|>
expected_x = np.array([[1,... | Test the process method. | Test_process | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_process:
"""Test the process method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_basic(self):
"""Test that differences are calculated along both the x and y dimensions and returned as separate cubes."""
<|body_1|>
def test_metadat... | stack_v2_sparse_classes_36k_train_016700 | 8,701 | permissive | [
{
"docstring": "Set up cube.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test that differences are calculated along both the x and y dimensions and returned as separate cubes.",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "... | 4 | null | Implement the Python class `Test_process` described below.
Class description:
Test the process method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_basic(self): Test that differences are calculated along both the x and y dimensions and returned as separate cubes.
- def test_metadata(se... | Implement the Python class `Test_process` described below.
Class description:
Test the process method.
Method signatures and docstrings:
- def setUp(self): Set up cube.
- def test_basic(self): Test that differences are calculated along both the x and y dimensions and returned as separate cubes.
- def test_metadata(se... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_process:
"""Test the process method."""
def setUp(self):
"""Set up cube."""
<|body_0|>
def test_basic(self):
"""Test that differences are calculated along both the x and y dimensions and returned as separate cubes."""
<|body_1|>
def test_metadat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_process:
"""Test the process method."""
def setUp(self):
"""Set up cube."""
data = np.array([[1, 2, 3], [2, 4, 6], [5, 10, 15]])
self.cube = set_up_variable_cube(data, 'wind_speed', 'm s-1', 'equalarea', realizations=np.array([1, 2]))
self.plugin = DifferenceBetweenAd... | the_stack_v2_python_sparse | improver_tests/utilities/test_DifferenceBetweenAdjacentGridSquares.py | metoppv/improver | train | 101 |
c99bf13de4fbee66cb3a560cb3943d311b88bb78 | [
"if k < 0:\n return 0\ndset = set()\ncnt = set()\nfor i in range(len(nums)):\n pexpect = nums[i] + k\n mexpect = nums[i] - k\n if pexpect in dset:\n cnt.add(tuple(sorted([nums[i]] + [pexpect])))\n if mexpect in dset:\n cnt.add(tuple(sorted([nums[i]] + [mexpect])))\n dset.add(nums[i])... | <|body_start_0|>
if k < 0:
return 0
dset = set()
cnt = set()
for i in range(len(nums)):
pexpect = nums[i] + k
mexpect = nums[i] - k
if pexpect in dset:
cnt.add(tuple(sorted([nums[i]] + [pexpect])))
if mexpect in ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findPairs(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def rewrite(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if k < 0:
... | stack_v2_sparse_classes_36k_train_016701 | 2,455 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "findPairs",
"signature": "def findPairs(self, nums, k)"
},
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "rewrite",
"signature": "def rewrite(self, nums, k)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006375 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def rewrite(self, nums, k): :type nums: List[int] :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findPairs(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def rewrite(self, nums, k): :type nums: List[int] :type k: int :rtype: int
<|skeleton|>
class Solu... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def findPairs(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def rewrite(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findPairs(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
if k < 0:
return 0
dset = set()
cnt = set()
for i in range(len(nums)):
pexpect = nums[i] + k
mexpect = nums[i] - k
if pexpect in ... | the_stack_v2_python_sparse | array/532_K-diff_Pairs_in_an_Array.py | vsdrun/lc_public | train | 6 | |
c8aacb0c4b8a4c310aaa6fcda5da9e7decf478db | [
"cg = ['0.5', '0.4', '0.3', '0.2']\nn = ['0', '0.1', '0', '0']\nself.assertEqual(sqlref.cg_n_cont('cg_test.tab'), (cg, n))",
"cg = ['0.5', '0.4', '0.3', '0.2']\nn = ['0', '0.1', '0', '0']\ntot = [('A', '0', 'ATGAATTGCCTGATAAAAAGGATTACCTTGATAGGGTAAATCATGCAGTT', '0.5', '0'), ('A', '1', 'TTCTGCATTCATTGACTGATTTATATAT... | <|body_start_0|>
cg = ['0.5', '0.4', '0.3', '0.2']
n = ['0', '0.1', '0', '0']
self.assertEqual(sqlref.cg_n_cont('cg_test.tab'), (cg, n))
<|end_body_0|>
<|body_start_1|>
cg = ['0.5', '0.4', '0.3', '0.2']
n = ['0', '0.1', '0', '0']
tot = [('A', '0', 'ATGAATTGCCTGATAAAAAGGA... | Tests for sqlref.py | SqlRefTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SqlRefTestCase:
"""Tests for sqlref.py"""
def test_cg_n_cont(self):
"""Does the list of cg and n percentages match up?"""
<|body_0|>
def test_mk_data(self):
"""Is the list of tuples correct?"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cg = [... | stack_v2_sparse_classes_36k_train_016702 | 1,720 | no_license | [
{
"docstring": "Does the list of cg and n percentages match up?",
"name": "test_cg_n_cont",
"signature": "def test_cg_n_cont(self)"
},
{
"docstring": "Is the list of tuples correct?",
"name": "test_mk_data",
"signature": "def test_mk_data(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007280 | Implement the Python class `SqlRefTestCase` described below.
Class description:
Tests for sqlref.py
Method signatures and docstrings:
- def test_cg_n_cont(self): Does the list of cg and n percentages match up?
- def test_mk_data(self): Is the list of tuples correct? | Implement the Python class `SqlRefTestCase` described below.
Class description:
Tests for sqlref.py
Method signatures and docstrings:
- def test_cg_n_cont(self): Does the list of cg and n percentages match up?
- def test_mk_data(self): Is the list of tuples correct?
<|skeleton|>
class SqlRefTestCase:
"""Tests fo... | dd1bebde30364fb46761631d63245f74edfb479a | <|skeleton|>
class SqlRefTestCase:
"""Tests for sqlref.py"""
def test_cg_n_cont(self):
"""Does the list of cg and n percentages match up?"""
<|body_0|>
def test_mk_data(self):
"""Is the list of tuples correct?"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SqlRefTestCase:
"""Tests for sqlref.py"""
def test_cg_n_cont(self):
"""Does the list of cg and n percentages match up?"""
cg = ['0.5', '0.4', '0.3', '0.2']
n = ['0', '0.1', '0', '0']
self.assertEqual(sqlref.cg_n_cont('cg_test.tab'), (cg, n))
def test_mk_data(self):
... | the_stack_v2_python_sparse | Python/DrosDel/test_sqlref.py | jess28/Old_project_code | train | 0 |
a57637e13030d2d006ca9a225a2765a675b9785e | [
"super().__init__()\nembed_dim = state_dim\ninputs = tf.keras.Input(shape=[None, state_dim])\noutputs = tf.keras.layers.LSTM(embed_dim)(inputs)\nif action_dim is None:\n inputs = tf.keras.Input(shape=(embed_dim,))\nelse:\n inputs = tf.keras.Input(shape=(embed_dim + action_dim,))\nif cross_norm:\n layers = ... | <|body_start_0|>
super().__init__()
embed_dim = state_dim
inputs = tf.keras.Input(shape=[None, state_dim])
outputs = tf.keras.layers.LSTM(embed_dim)(inputs)
if action_dim is None:
inputs = tf.keras.Input(shape=(embed_dim,))
else:
inputs = tf.keras.... | A critic network. | CriticNet | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CriticNet:
"""A critic network."""
def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False):
"""Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hidden dimensions. cross_norm: Whether to use cross norm.""... | stack_v2_sparse_classes_36k_train_016703 | 10,984 | permissive | [
{
"docstring": "Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hidden dimensions. cross_norm: Whether to use cross norm.",
"name": "__init__",
"signature": "def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False)"
},
... | 2 | null | Implement the Python class `CriticNet` described below.
Class description:
A critic network.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False): Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hi... | Implement the Python class `CriticNet` described below.
Class description:
A critic network.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False): Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hi... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class CriticNet:
"""A critic network."""
def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False):
"""Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hidden dimensions. cross_norm: Whether to use cross norm.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CriticNet:
"""A critic network."""
def __init__(self, state_dim, action_dim=None, hidden_dims=(256, 256), cross_norm=False):
"""Creates a neural net. Args: state_dim: State size. action_dim: Action size. hidden_dims: List of hidden dimensions. cross_norm: Whether to use cross norm."""
sup... | the_stack_v2_python_sparse | rl_repr/batch_rl/critic.py | Jimmy-INL/google-research | train | 1 |
4921ae59e580edd7b5c2c208725a2c0e3f924110 | [
"log.info('Getting list of simulations.')\ntry:\n self.sim_list = get_simulations(uut)\n log.info('Successfully got the list of simulations: {}'.format(self.sim_list))\nexcept Exception as e:\n raise Exception('Unable to get list of simulations.')",
"log.info('stopping simulation {}'.format(simulation_na... | <|body_start_0|>
log.info('Getting list of simulations.')
try:
self.sim_list = get_simulations(uut)
log.info('Successfully got the list of simulations: {}'.format(self.sim_list))
except Exception as e:
raise Exception('Unable to get list of simulations.')
<|en... | Trigger class to start/stop simulation | TriggerStopStartSimulation | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TriggerStopStartSimulation:
"""Trigger class to start/stop simulation"""
def get_simulations(self, uut):
"""Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results"""
<|body_0|>
def stop_simulation(self, uut, simulation_name):
"""Stop... | stack_v2_sparse_classes_36k_train_016704 | 4,753 | permissive | [
{
"docstring": "Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results",
"name": "get_simulations",
"signature": "def get_simulations(self, uut)"
},
{
"docstring": "Stop simulations Args: uut (`obj`): Device object simulation_name (`str`): simulation name Returns: N... | 3 | null | Implement the Python class `TriggerStopStartSimulation` described below.
Class description:
Trigger class to start/stop simulation
Method signatures and docstrings:
- def get_simulations(self, uut): Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results
- def stop_simulation(self, uut, s... | Implement the Python class `TriggerStopStartSimulation` described below.
Class description:
Trigger class to start/stop simulation
Method signatures and docstrings:
- def get_simulations(self, uut): Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results
- def stop_simulation(self, uut, s... | e42e51475cddcb10f5c7814d0fe892ac865742ba | <|skeleton|>
class TriggerStopStartSimulation:
"""Trigger class to start/stop simulation"""
def get_simulations(self, uut):
"""Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results"""
<|body_0|>
def stop_simulation(self, uut, simulation_name):
"""Stop... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TriggerStopStartSimulation:
"""Trigger class to start/stop simulation"""
def get_simulations(self, uut):
"""Get simulations Args: uut (`obj`): Device object Returns: None Raises: pyATS Results"""
log.info('Getting list of simulations.')
try:
self.sim_list = get_simulat... | the_stack_v2_python_sparse | pkgs/sdk-pkg/src/genie/libs/sdk/triggers/virl/virl.py | CiscoTestAutomation/genielibs | train | 109 |
6dc1a76ce56c9ad9ea66f81adb73aae50fab70c5 | [
"activation = Sigmoid()\noutput = Softmax()\nself.mulu = np.matmul(x, u)\nself.mulw = np.matmul(prev_s, w)\nself.sin = np.add(self.mulu, self.mulw)\nself.sout = activation.forward(self.sin)\nself.oin = np.matmul(self.sout, v)\nself.oout = output.forward(self.oin)",
"activation = Sigmoid()\noutput = Softmax()\nsel... | <|body_start_0|>
activation = Sigmoid()
output = Softmax()
self.mulu = np.matmul(x, u)
self.mulw = np.matmul(prev_s, w)
self.sin = np.add(self.mulu, self.mulw)
self.sout = activation.forward(self.sin)
self.oin = np.matmul(self.sout, v)
self.oout = output.f... | Layer | [
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Layer:
def forward(self, x, prev_s, u, w, v):
"""x : input array prev_s : array u,v,w : weight matrices"""
<|body_0|>
def backward(self, x, prev_s, y, u, w, v):
"""y : integer"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
activation = Sigmoid()
... | stack_v2_sparse_classes_36k_train_016705 | 7,270 | permissive | [
{
"docstring": "x : input array prev_s : array u,v,w : weight matrices",
"name": "forward",
"signature": "def forward(self, x, prev_s, u, w, v)"
},
{
"docstring": "y : integer",
"name": "backward",
"signature": "def backward(self, x, prev_s, y, u, w, v)"
}
] | 2 | null | Implement the Python class `Layer` described below.
Class description:
Implement the Layer class.
Method signatures and docstrings:
- def forward(self, x, prev_s, u, w, v): x : input array prev_s : array u,v,w : weight matrices
- def backward(self, x, prev_s, y, u, w, v): y : integer | Implement the Python class `Layer` described below.
Class description:
Implement the Layer class.
Method signatures and docstrings:
- def forward(self, x, prev_s, u, w, v): x : input array prev_s : array u,v,w : weight matrices
- def backward(self, x, prev_s, y, u, w, v): y : integer
<|skeleton|>
class Layer:
d... | 4ae6ba54e90af14af236e03e435eb0402dcac787 | <|skeleton|>
class Layer:
def forward(self, x, prev_s, u, w, v):
"""x : input array prev_s : array u,v,w : weight matrices"""
<|body_0|>
def backward(self, x, prev_s, y, u, w, v):
"""y : integer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Layer:
def forward(self, x, prev_s, u, w, v):
"""x : input array prev_s : array u,v,w : weight matrices"""
activation = Sigmoid()
output = Softmax()
self.mulu = np.matmul(x, u)
self.mulw = np.matmul(prev_s, w)
self.sin = np.add(self.mulu, self.mulw)
self... | the_stack_v2_python_sparse | machine_learning/deep_learning/python/rnn/rnn.py | ZoranPandovski/al-go-rithms | train | 1,421 | |
3340de3a43a0b13b8ca226a8fd36c15f4855701f | [
"self.surface = surface\nself.affine = affine\nself.has_hit = has_hit\nself.vertex_hit = vertex_hit\nself.surf_vox = self.surface.apply_affine(self.affine)",
"res = np.zeros(self.has_hit.shape, dtype='i4')\nuse = self.has_hit != -1\nres[use] = np.sum(self.vertex_hit[self.has_hit[use], :] != -1, -1)\nreturn res",
... | <|body_start_0|>
self.surface = surface
self.affine = affine
self.has_hit = has_hit
self.vertex_hit = vertex_hit
self.surf_vox = self.surface.apply_affine(self.affine)
<|end_body_0|>
<|body_start_1|>
res = np.zeros(self.has_hit.shape, dtype='i4')
use = self.has_h... | Represents the intersections between a surface and a grid. | GridSurfaceIntersection | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GridSurfaceIntersection:
"""Represents the intersections between a surface and a grid."""
def __init__(self, surface, affine, has_hit, vertex_hit):
"""Computes the intersection of the surface with the grid defined by `shape` and `affine`. This object will usually be created through g... | stack_v2_sparse_classes_36k_train_016706 | 24,374 | permissive | [
{
"docstring": "Computes the intersection of the surface with the grid defined by `shape` and `affine`. This object will usually be created through grid.intersect or grid.intersect_resolution Arguments: :param surface: 2D surface in a 3D space that intersects with the grid. :type surface: Mesh2D :param affine: ... | 4 | stack_v2_sparse_classes_30k_train_008081 | Implement the Python class `GridSurfaceIntersection` described below.
Class description:
Represents the intersections between a surface and a grid.
Method signatures and docstrings:
- def __init__(self, surface, affine, has_hit, vertex_hit): Computes the intersection of the surface with the grid defined by `shape` an... | Implement the Python class `GridSurfaceIntersection` described below.
Class description:
Represents the intersections between a surface and a grid.
Method signatures and docstrings:
- def __init__(self, surface, affine, has_hit, vertex_hit): Computes the intersection of the surface with the grid defined by `shape` an... | de00c15b946a99a048694f3d8b6ad822a835b299 | <|skeleton|>
class GridSurfaceIntersection:
"""Represents the intersections between a surface and a grid."""
def __init__(self, surface, affine, has_hit, vertex_hit):
"""Computes the intersection of the surface with the grid defined by `shape` and `affine`. This object will usually be created through g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GridSurfaceIntersection:
"""Represents the intersections between a surface and a grid."""
def __init__(self, surface, affine, has_hit, vertex_hit):
"""Computes the intersection of the surface with the grid defined by `shape` and `affine`. This object will usually be created through grid.intersect... | the_stack_v2_python_sparse | mcot/core/surface/grid.py | MichielCottaar/mcot.core | train | 1 |
f1b240251721a2af5c350b82e2f8c6b25198787b | [
"try:\n result = single_run(nnid, ver, node)\n return Response(json.dumps(result))\nexcept Exception as e:\n traceback.print_exc()\n return_data = {'status': '404', 'result': str(e)}\n return Response(json.dumps(return_data))",
"try:\n return_data = ''\n return Response(json.dumps(return_data... | <|body_start_0|>
try:
result = single_run(nnid, ver, node)
return Response(json.dumps(result))
except Exception as e:
traceback.print_exc()
return_data = {'status': '404', 'result': str(e)}
return Response(json.dumps(return_data))
<|end_body_0|... | RunManagerSingleRequest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_016707 | 2,307 | permissive | [
{
"docstring": "We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed",
"name": "post",
"signature": "def post(self, request, nnid, ver, node)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_006084 | Implement the Python class `RunManagerSingleRequest` described below.
Class description:
Implement the RunManagerSingleRequest class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # C... | Implement the Python class `RunManagerSingleRequest` described below.
Class description:
Implement the RunManagerSingleRequest class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # C... | 6ad2fbc7384e4dbe7e3e63bdb44c8ce0387f4b7f | <|skeleton|>
class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunManagerSingleRequest:
def post(self, request, nnid, ver, node):
"""We can execute single node with this api you must specify nnid, ver and node name for that purpose --- # Class Name : RunManagerSingleRequest # Description: request single node to be executed"""
try:
result = sin... | the_stack_v2_python_sparse | api/views/runmanager_single_request.py | yurimkoo/tensormsa | train | 1 | |
14ecdcd7412edf4c0c1cb50fbf59d2a48c8fb987 | [
"cnts = collections.Counter(s)\nres = l = r = 0\ninvalid = [key for key, value in cnts.items() if value < k]\nwindow = collections.defaultdict(int)\nfor r in range(1, len(s) + 1):\n window[s[r - 1]] += 1\n if s[r - 1] in invalid:\n while l < r:\n check = [key for key, value in window.items()... | <|body_start_0|>
cnts = collections.Counter(s)
res = l = r = 0
invalid = [key for key, value in cnts.items() if value < k]
window = collections.defaultdict(int)
for r in range(1, len(s) + 1):
window[s[r - 1]] += 1
if s[r - 1] in invalid:
wh... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring_refer(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cnts = collections.Co... | stack_v2_sparse_classes_36k_train_016708 | 2,486 | no_license | [
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s, k)"
},
{
"docstring": ":type s: str :type k: int :rtype: int",
"name": "longestSubstring_refer",
"signature": "def longestSubstring_refer(self, s, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring_refer(self, s, k): :type s: str :type k: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): :type s: str :type k: int :rtype: int
- def longestSubstring_refer(self, s, k): :type s: str :type k: int :rtype: int
<|skeleton|>
class Soluti... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_0|>
def longestSubstring_refer(self, s, k):
""":type s: str :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestSubstring(self, s, k):
""":type s: str :type k: int :rtype: int"""
cnts = collections.Counter(s)
res = l = r = 0
invalid = [key for key, value in cnts.items() if value < k]
window = collections.defaultdict(int)
for r in range(1, len(s) + 1):... | the_stack_v2_python_sparse | 395_longestSubstring.py | jennyChing/leetCode | train | 2 | |
90acc4c6f64af9f0513417fca149d619450bc5c7 | [
"self.name = name\nself.pos = []\nself.Pn = []\nself.flux = []\nself.pointCloud = []\nself.readpil3d()",
"res = np.loadtxt(self.name, delimiter=' ')\nself.pos = res[:, 0:3]\nself.Pn = res[:, 3:4]\nself.flux = res[:, -1]",
"self.pointCloud = VtkPointCloud()\nfor k in range(np.size(self.pos, 0)):\n self.pointC... | <|body_start_0|>
self.name = name
self.pos = []
self.Pn = []
self.flux = []
self.pointCloud = []
self.readpil3d()
<|end_body_0|>
<|body_start_1|>
res = np.loadtxt(self.name, delimiter=' ')
self.pos = res[:, 0:3]
self.Pn = res[:, 3:4]
self.... | Class representing a PILAGER3D output file. | PIL3D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PIL3D:
"""Class representing a PILAGER3D output file."""
def __init__(self, name):
"""Method to initialize class."""
<|body_0|>
def readpil3d(self):
"""Method to read in the pil3d txt file."""
<|body_1|>
def make_point_cloud(self):
"""Method ... | stack_v2_sparse_classes_36k_train_016709 | 3,136 | no_license | [
{
"docstring": "Method to initialize class.",
"name": "__init__",
"signature": "def __init__(self, name)"
},
{
"docstring": "Method to read in the pil3d txt file.",
"name": "readpil3d",
"signature": "def readpil3d(self)"
},
{
"docstring": "Method to plot the point cloud.",
"n... | 3 | stack_v2_sparse_classes_30k_test_000963 | Implement the Python class `PIL3D` described below.
Class description:
Class representing a PILAGER3D output file.
Method signatures and docstrings:
- def __init__(self, name): Method to initialize class.
- def readpil3d(self): Method to read in the pil3d txt file.
- def make_point_cloud(self): Method to plot the poi... | Implement the Python class `PIL3D` described below.
Class description:
Class representing a PILAGER3D output file.
Method signatures and docstrings:
- def __init__(self, name): Method to initialize class.
- def readpil3d(self): Method to read in the pil3d txt file.
- def make_point_cloud(self): Method to plot the poi... | 6b37842203ff4318a48dbf0258cbe2b253436e7d | <|skeleton|>
class PIL3D:
"""Class representing a PILAGER3D output file."""
def __init__(self, name):
"""Method to initialize class."""
<|body_0|>
def readpil3d(self):
"""Method to read in the pil3d txt file."""
<|body_1|>
def make_point_cloud(self):
"""Method ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PIL3D:
"""Class representing a PILAGER3D output file."""
def __init__(self, name):
"""Method to initialize class."""
self.name = name
self.pos = []
self.Pn = []
self.flux = []
self.pointCloud = []
self.readpil3d()
def readpil3d(self):
"... | the_stack_v2_python_sparse | plume/pil3d.py | tslowery78/PyLnD | train | 0 |
f0c4abdc1bb9a5fa59ff91b6504063065537b0e6 | [
"result = []\nif len(matrix) <= 0:\n return result\nself.foo(matrix, result, 0, 0)\nreturn result",
"n = len(matrix)\nm = len(matrix[0])\nif i >= n or j >= m or matrix[i][j] == '#':\n return\nfor col in range(j, m - j):\n if matrix[i][col] != '#':\n result.append(matrix[i][col])\n matrix[i]... | <|body_start_0|>
result = []
if len(matrix) <= 0:
return result
self.foo(matrix, result, 0, 0)
return result
<|end_body_0|>
<|body_start_1|>
n = len(matrix)
m = len(matrix[0])
if i >= n or j >= m or matrix[i][j] == '#':
return
for ... | Solution1 | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution1:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def foo(self, matrix, result, i, j):
"""every time only add most outer rows and cols into result i,j is the start point, we add elemtents clockwise then i+1,j+1... | stack_v2_sparse_classes_36k_train_016710 | 1,872 | permissive | [
{
"docstring": ":type matrix: List[List[int]] :rtype: List[int]",
"name": "spiralOrder",
"signature": "def spiralOrder(self, matrix)"
},
{
"docstring": "every time only add most outer rows and cols into result i,j is the start point, we add elemtents clockwise then i+1,j+1 => go to inner matrix ... | 2 | stack_v2_sparse_classes_30k_train_004599 | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def foo(self, matrix, result, i, j): every time only add most outer rows and cols into result i... | Implement the Python class `Solution1` described below.
Class description:
Implement the Solution1 class.
Method signatures and docstrings:
- def spiralOrder(self, matrix): :type matrix: List[List[int]] :rtype: List[int]
- def foo(self, matrix, result, i, j): every time only add most outer rows and cols into result i... | 2677b6d26bedb9bc6c6137a2392d0afaceb91ec2 | <|skeleton|>
class Solution1:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
<|body_0|>
def foo(self, matrix, result, i, j):
"""every time only add most outer rows and cols into result i,j is the start point, we add elemtents clockwise then i+1,j+1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution1:
def spiralOrder(self, matrix):
""":type matrix: List[List[int]] :rtype: List[int]"""
result = []
if len(matrix) <= 0:
return result
self.foo(matrix, result, 0, 0)
return result
def foo(self, matrix, result, i, j):
"""every time only a... | the_stack_v2_python_sparse | spiral_matrix/solution.py | haotianzhu/Questions_Solutions | train | 0 | |
d3dcd82fe22869609945cb73474af1c159388268 | [
"for pol in self.auth:\n if pol.actor == uid:\n return pol\nreturn None",
"pol = self.get_policy(uid)\nif pol is not None:\n session.delete(pol)",
"del session\npol = self.get_policy(uid)\npol.role = new_role"
] | <|body_start_0|>
for pol in self.auth:
if pol.actor == uid:
return pol
return None
<|end_body_0|>
<|body_start_1|>
pol = self.get_policy(uid)
if pol is not None:
session.delete(pol)
<|end_body_1|>
<|body_start_2|>
del session
pol ... | Base class for models with a list of authorization policies | Authorized | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Authorized:
"""Base class for models with a list of authorization policies"""
def get_policy(self, uid):
"""Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in auth list"""
<|body_0|>
def remove_policy(self... | stack_v2_sparse_classes_36k_train_016711 | 3,240 | no_license | [
{
"docstring": "Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in auth list",
"name": "get_policy",
"signature": "def get_policy(self, uid)"
},
{
"docstring": "Remove access granted to actor Args: session: (DBSession) uid: (str) ... | 3 | stack_v2_sparse_classes_30k_train_006426 | Implement the Python class `Authorized` described below.
Class description:
Base class for models with a list of authorization policies
Method signatures and docstrings:
- def get_policy(self, uid): Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in au... | Implement the Python class `Authorized` described below.
Class description:
Base class for models with a list of authorization policies
Method signatures and docstrings:
- def get_policy(self, uid): Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in au... | ff1feea27efa6544c0e443b953951bb50cbdd9bb | <|skeleton|>
class Authorized:
"""Base class for models with a list of authorization policies"""
def get_policy(self, uid):
"""Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in auth list"""
<|body_0|>
def remove_policy(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Authorized:
"""Base class for models with a list of authorization policies"""
def get_policy(self, uid):
"""Retrieve policy associated with a given actor. Args: uid: (str) id of actor Returns: (Policy) or None if no actor in auth list"""
for pol in self.auth:
if pol.actor == u... | the_stack_v2_python_sparse | seeweb/models/auth.py | pradal/seeweb | train | 0 |
b73d7e5faafb0c90fd244e8862bb4af25afdfc21 | [
"try:\n instance_message = await get_data_from_req(self.request).messages.get()\nexcept (ResourceNotFoundError, ResourceConflictError):\n return json_response(None)\nreturn json_response(instance_message)",
"user_id = self.request['client'].user_id\ninstance_message = await get_data_from_req(self.request).m... | <|body_start_0|>
try:
instance_message = await get_data_from_req(self.request).messages.get()
except (ResourceNotFoundError, ResourceConflictError):
return json_response(None)
return json_response(instance_message)
<|end_body_0|>
<|body_start_1|>
user_id = self.r... | MessagesView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessagesView:
async def get(self) -> r200[Optional[MessageResponse]]:
"""Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Successful operation"""
<|body_0|>
async def put(self, data: CreateMessageRequest) -> r200... | stack_v2_sparse_classes_36k_train_016712 | 2,470 | permissive | [
{
"docstring": "Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Successful operation",
"name": "get",
"signature": "async def get(self) -> r200[Optional[MessageResponse]]"
},
{
"docstring": "Create an administrative instance message... | 3 | stack_v2_sparse_classes_30k_val_000105 | Implement the Python class `MessagesView` described below.
Class description:
Implement the MessagesView class.
Method signatures and docstrings:
- async def get(self) -> r200[Optional[MessageResponse]]: Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Su... | Implement the Python class `MessagesView` described below.
Class description:
Implement the MessagesView class.
Method signatures and docstrings:
- async def get(self) -> r200[Optional[MessageResponse]]: Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Su... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class MessagesView:
async def get(self) -> r200[Optional[MessageResponse]]:
"""Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Successful operation"""
<|body_0|>
async def put(self, data: CreateMessageRequest) -> r200... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MessagesView:
async def get(self) -> r200[Optional[MessageResponse]]:
"""Get the administrative instance message. Fetches the active administrative instance message. Status Codes: 200: Successful operation"""
try:
instance_message = await get_data_from_req(self.request).messages.ge... | the_stack_v2_python_sparse | virtool/messages/api.py | virtool/virtool | train | 45 | |
f166dde05c4a9e67334a5886995788809efade81 | [
"user = self.get_current_user()\nif user:\n feature_ids = notifier.FeatureStar.get_user_stars(user.email())\nelse:\n feature_ids = []\ndata = {'featureIds': feature_ids}\nreturn data",
"feature = self.get_specified_feature()\nstarred = self.get_bool_param('starred', default=True)\nuser = self.get_current_us... | <|body_start_0|>
user = self.get_current_user()
if user:
feature_ids = notifier.FeatureStar.get_user_stars(user.email())
else:
feature_ids = []
data = {'featureIds': feature_ids}
return data
<|end_body_0|>
<|body_start_1|>
feature = self.get_speci... | Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature. | StarsAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StarsAPI:
"""Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature."""
def do_get(self, **kwargs):
"""Return a list of all starred fea... | stack_v2_sparse_classes_36k_train_016713 | 1,719 | permissive | [
{
"docstring": "Return a list of all starred feature IDs for the signed-in user.",
"name": "do_get",
"signature": "def do_get(self, **kwargs)"
},
{
"docstring": "Set or clear a star on the specified feature.",
"name": "do_post",
"signature": "def do_post(self, **kwargs)"
}
] | 2 | null | Implement the Python class `StarsAPI` described below.
Class description:
Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature.
Method signatures and docstrings:
- def... | Implement the Python class `StarsAPI` described below.
Class description:
Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature.
Method signatures and docstrings:
- def... | 17f9886d064da5bda84006d5866077727646fff2 | <|skeleton|>
class StarsAPI:
"""Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature."""
def do_get(self, **kwargs):
"""Return a list of all starred fea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StarsAPI:
"""Users can star a feature by clicking a star icon. The client-side has logic to toggle the star icon. When a user has starred a feature, they will be sent notification emails about changes to that feature."""
def do_get(self, **kwargs):
"""Return a list of all starred feature IDs for ... | the_stack_v2_python_sparse | api/stars_api.py | GoogleChrome/chromium-dashboard | train | 574 |
189aee25ee4d4969761b4e74750b80f6f3901232 | [
"def visit(s1, s2):\n n = len(s1)\n m = len(s2)\n if n != m:\n return False\n if s1 == s2:\n return True\n if sorted(s1) != sorted(s2):\n return False\n if n < 4:\n return True\n for i in range(1, n):\n if visit(s1[:i], s2[:i]) and visit(s1[i:], s2[i:]) or (vi... | <|body_start_0|>
def visit(s1, s2):
n = len(s1)
m = len(s2)
if n != m:
return False
if s1 == s2:
return True
if sorted(s1) != sorted(s2):
return False
if n < 4:
return True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isScramble(self, s1: str, s2: str) -> bool:
"""Simply testing that both strings contain the same strings does not work: Counter example: "abcde" and "caebd". "ab" is in the inverted order "ba" but separated by "e" which is before "d" => There are two crossed inversions and ... | stack_v2_sparse_classes_36k_train_016714 | 2,808 | no_license | [
{
"docstring": "Simply testing that both strings contain the same strings does not work: Counter example: \"abcde\" and \"caebd\". \"ab\" is in the inverted order \"ba\" but separated by \"e\" which is before \"d\" => There are two crossed inversions and this is not valid (inversions cut the space) Algorithm 1 ... | 2 | stack_v2_sparse_classes_30k_train_012883 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isScramble(self, s1: str, s2: str) -> bool: Simply testing that both strings contain the same strings does not work: Counter example: "abcde" and "caebd". "ab" is in the inve... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isScramble(self, s1: str, s2: str) -> bool: Simply testing that both strings contain the same strings does not work: Counter example: "abcde" and "caebd". "ab" is in the inve... | 3ffcfee5cedf421d5de6d0dec4ba53b0eecbbff8 | <|skeleton|>
class Solution:
def isScramble(self, s1: str, s2: str) -> bool:
"""Simply testing that both strings contain the same strings does not work: Counter example: "abcde" and "caebd". "ab" is in the inverted order "ba" but separated by "e" which is before "d" => There are two crossed inversions and ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isScramble(self, s1: str, s2: str) -> bool:
"""Simply testing that both strings contain the same strings does not work: Counter example: "abcde" and "caebd". "ab" is in the inverted order "ba" but separated by "e" which is before "d" => There are two crossed inversions and this is not va... | the_stack_v2_python_sparse | backtrack/ScrambleStrings.py | QuentinDuval/PythonExperiments | train | 3 | |
2944d7b9804845f3cdc732a8449737134101d294 | [
"self.designate = designate\nself.parameter = parameter\nself.answers = [Path(answer) for answer in answers]\nself.default = Path(default)\nself.question = question\nself.logical_unit = next(self._logic_unit)\nself.value = self.default",
"question = tag.find('question').text\ndefault = tag.find('answer').text\nan... | <|body_start_0|>
self.designate = designate
self.parameter = parameter
self.answers = [Path(answer) for answer in answers]
self.default = Path(default)
self.question = question
self.logical_unit = next(self._logic_unit)
self.value = self.default
<|end_body_0|>
<|... | ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows the author to describe a question that will be asked in the assembly window. If ... | ExternalFile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalFile:
"""ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows the author to describe a question that w... | stack_v2_sparse_classes_36k_train_016715 | 2,637 | permissive | [
{
"docstring": "Initialize object from arguments. Args: question (str): Question to ask. default (str): Default answer. answers (list of str): List of possible answers. parameter (str): The parameter associated with the external file. designate (bool): If True, the external files are assigned to logical unit nu... | 2 | stack_v2_sparse_classes_30k_train_005981 | Implement the Python class `ExternalFile` described below.
Class description:
ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows t... | Implement the Python class `ExternalFile` described below.
Class description:
ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows t... | f2deb5eb340a2814722eead5f8b6278a945c730d | <|skeleton|>
class ExternalFile:
"""ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows the author to describe a question that w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalFile:
"""ExternalFile class. The External File Specification allows the user to associate a TRNSYS parameter ( typically a logical unit) with an external file through the use of the TRNSYS ASSIGN, FILES, or DESIGNATE statements. This feature allows the author to describe a question that will be asked ... | the_stack_v2_python_sparse | trnsystor/externalfile.py | sturmianseq/trnsystor | train | 0 |
3e601976403ceac10bef638c213c0148ab34bc1c | [
"super().__init__(input_shape, filters, kernel_size, stride, dilation, groups, bias)\nif isinstance(padding, (*INT_TYPES, *FLOAT_TYPES)):\n self.padding_mode = 'constant'\n self._padding_value = padding\nelse:\n self.padding_mode = padding\n self._padding_value = 0.0\nif self.padding_mode == 'valid' or ... | <|body_start_0|>
super().__init__(input_shape, filters, kernel_size, stride, dilation, groups, bias)
if isinstance(padding, (*INT_TYPES, *FLOAT_TYPES)):
self.padding_mode = 'constant'
self._padding_value = padding
else:
self.padding_mode = padding
... | Conv | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Conv:
def __init__(self, input_shape, filters, kernel_size=3, stride=1, dilation=1, groups=1, padding='constant', bias=False):
"""Direct convolution layer generalized for different dims. This layer slightly extends functionality of original torch.nn.Conv* modules in four main aspects: 1)... | stack_v2_sparse_classes_36k_train_016716 | 13,566 | no_license | [
{
"docstring": "Direct convolution layer generalized for different dims. This layer slightly extends functionality of original torch.nn.Conv* modules in four main aspects: 1) Shape of the input tensor is passed as argument of constructor. 2) Shape of the output tensor can be accessed by 'output_shape' property ... | 3 | stack_v2_sparse_classes_30k_train_008231 | Implement the Python class `Conv` described below.
Class description:
Implement the Conv class.
Method signatures and docstrings:
- def __init__(self, input_shape, filters, kernel_size=3, stride=1, dilation=1, groups=1, padding='constant', bias=False): Direct convolution layer generalized for different dims. This lay... | Implement the Python class `Conv` described below.
Class description:
Implement the Conv class.
Method signatures and docstrings:
- def __init__(self, input_shape, filters, kernel_size=3, stride=1, dilation=1, groups=1, padding='constant', bias=False): Direct convolution layer generalized for different dims. This lay... | 9554e0f96703a37a9a41fc70dc8e70e45c6181a2 | <|skeleton|>
class Conv:
def __init__(self, input_shape, filters, kernel_size=3, stride=1, dilation=1, groups=1, padding='constant', bias=False):
"""Direct convolution layer generalized for different dims. This layer slightly extends functionality of original torch.nn.Conv* modules in four main aspects: 1)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Conv:
def __init__(self, input_shape, filters, kernel_size=3, stride=1, dilation=1, groups=1, padding='constant', bias=False):
"""Direct convolution layer generalized for different dims. This layer slightly extends functionality of original torch.nn.Conv* modules in four main aspects: 1) Shape of the ... | the_stack_v2_python_sparse | dnn_backend/radio_dep/models/models/pytorch/layers/conv.py | theVmagnificient/radiology_web | train | 0 | |
1c502a7a980e08d8ceb7b3a23fef094e82f18e77 | [
"with open(path) as f:\n data = f.read()\nif not preamble in data:\n if data.startswith('#!'):\n lines = data.splitlines(keepends=True)\n text = f\"{lines[0]}{preamble}{''.join(lines[1:])}\"\n else:\n text = f'{preamble}{data}'\n with open(path, 'wt') as f:\n f.write(text)",
... | <|body_start_0|>
with open(path) as f:
data = f.read()
if not preamble in data:
if data.startswith('#!'):
lines = data.splitlines(keepends=True)
text = f"{lines[0]}{preamble}{''.join(lines[1:])}"
else:
text = f'{preamble... | ApplyCopyrightCommand | [
"MIT",
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApplyCopyrightCommand:
def _check_add_copyright(self, path, preamble):
"""Check that the given file has the provided copyright and add it in case it is not present."""
<|body_0|>
def run(self):
"""Execution of the command action."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k_train_016717 | 14,165 | permissive | [
{
"docstring": "Check that the given file has the provided copyright and add it in case it is not present.",
"name": "_check_add_copyright",
"signature": "def _check_add_copyright(self, path, preamble)"
},
{
"docstring": "Execution of the command action.",
"name": "run",
"signature": "de... | 2 | stack_v2_sparse_classes_30k_val_000763 | Implement the Python class `ApplyCopyrightCommand` described below.
Class description:
Implement the ApplyCopyrightCommand class.
Method signatures and docstrings:
- def _check_add_copyright(self, path, preamble): Check that the given file has the provided copyright and add it in case it is not present.
- def run(sel... | Implement the Python class `ApplyCopyrightCommand` described below.
Class description:
Implement the ApplyCopyrightCommand class.
Method signatures and docstrings:
- def _check_add_copyright(self, path, preamble): Check that the given file has the provided copyright and add it in case it is not present.
- def run(sel... | fa6808a6ca8063751da92f683f2b810a0690a462 | <|skeleton|>
class ApplyCopyrightCommand:
def _check_add_copyright(self, path, preamble):
"""Check that the given file has the provided copyright and add it in case it is not present."""
<|body_0|>
def run(self):
"""Execution of the command action."""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApplyCopyrightCommand:
def _check_add_copyright(self, path, preamble):
"""Check that the given file has the provided copyright and add it in case it is not present."""
with open(path) as f:
data = f.read()
if not preamble in data:
if data.startswith('#!'):
... | the_stack_v2_python_sparse | setup.py | mramospe/minkit | train | 0 | |
f116f971af060012a99300b9af7568fb2a74b3f6 | [
"def process():\n for n, values in enumerate(data):\n funct7, in0, in1, expected = values if len(values) == 4 else (0,) + values\n yield self.dut.funct7.eq(funct7)\n yield self.dut.in0.eq(in0)\n yield self.dut.in1.eq(in1)\n yield self.dut.start.eq(1)\n yield\n yie... | <|body_start_0|>
def process():
for n, values in enumerate(data):
funct7, in0, in1, expected = values if len(values) == 4 else (0,) + values
yield self.dut.funct7.eq(funct7)
yield self.dut.in0.eq(in0)
yield self.dut.in1.eq(in1)
... | Base test class, suitable for testing simple instructions. | InstructionTestBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstructionTestBase:
"""Base test class, suitable for testing simple instructions."""
def verify(self, data, trace=False):
"""Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3-tuples (in0, in1, out) or 4-tuples (funct7, in0, in1, ou... | stack_v2_sparse_classes_36k_train_016718 | 13,874 | permissive | [
{
"docstring": "Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3-tuples (in0, in1, out) or 4-tuples (funct7, in0, in1, out)",
"name": "verify",
"signature": "def verify(self, data, trace=False)"
},
{
"docstring": "Verifies that our instruction... | 2 | stack_v2_sparse_classes_30k_train_017567 | Implement the Python class `InstructionTestBase` described below.
Class description:
Base test class, suitable for testing simple instructions.
Method signatures and docstrings:
- def verify(self, data, trace=False): Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3... | Implement the Python class `InstructionTestBase` described below.
Class description:
Base test class, suitable for testing simple instructions.
Method signatures and docstrings:
- def verify(self, data, trace=False): Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3... | d4f660ad81f8807558120bbd311371eff1a0ce3b | <|skeleton|>
class InstructionTestBase:
"""Base test class, suitable for testing simple instructions."""
def verify(self, data, trace=False):
"""Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3-tuples (in0, in1, out) or 4-tuples (funct7, in0, in1, ou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InstructionTestBase:
"""Base test class, suitable for testing simple instructions."""
def verify(self, data, trace=False):
"""Verifies instruction given explicit lists of inputs and outputs Parameters ---------- data: list of 3-tuples (in0, in1, out) or 4-tuples (funct7, in0, in1, out)"""
... | the_stack_v2_python_sparse | python/nmigen_cfu/cfu.py | JosephBushagour/CFU-Playground | train | 1 |
f26fb5fd9e1dfb042c6507e76c23a6d50398b547 | [
"if not node:\n return\nif node.val == V:\n if is_left_path:\n self.t2 = node\n else:\n self.t2 = node.right\nif is_left_path and node.val < V:\n self.t2 = node\nif not is_left_path and node.val > V:\n self.t2 = node\nif V < node.val:\n self.t1 = node\n self.find_split_point(node.... | <|body_start_0|>
if not node:
return
if node.val == V:
if is_left_path:
self.t2 = node
else:
self.t2 = node.right
if is_left_path and node.val < V:
self.t2 = node
if not is_left_path and node.val > V:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def find_split_point(self, node, is_left_path, V):
"""find the split point where both trees will be separated"""
<|body_0|>
def splitBST(self, root, V):
""":type root: TreeNode :type V: int :rtype: List[TreeNode]"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_016719 | 3,186 | no_license | [
{
"docstring": "find the split point where both trees will be separated",
"name": "find_split_point",
"signature": "def find_split_point(self, node, is_left_path, V)"
},
{
"docstring": ":type root: TreeNode :type V: int :rtype: List[TreeNode]",
"name": "splitBST",
"signature": "def split... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_split_point(self, node, is_left_path, V): find the split point where both trees will be separated
- def splitBST(self, root, V): :type root: TreeNode :type V: int :rtype... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def find_split_point(self, node, is_left_path, V): find the split point where both trees will be separated
- def splitBST(self, root, V): :type root: TreeNode :type V: int :rtype... | 877933424e6d2c590d6ac53db18bee951a3d9de4 | <|skeleton|>
class Solution:
def find_split_point(self, node, is_left_path, V):
"""find the split point where both trees will be separated"""
<|body_0|>
def splitBST(self, root, V):
""":type root: TreeNode :type V: int :rtype: List[TreeNode]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def find_split_point(self, node, is_left_path, V):
"""find the split point where both trees will be separated"""
if not node:
return
if node.val == V:
if is_left_path:
self.t2 = node
else:
self.t2 = node.righ... | the_stack_v2_python_sparse | leetcode/776.split-bst-messsss.py | siddhism/leetcode | train | 0 | |
29d15c4c250ca4850556ce4ef32048387d4e4249 | [
"e = data_types.WebTestExpectation('test*', ['tag1'], 'Failure')\nself.assertTrue(e._CompareWildcard('testing123'))\nself.assertTrue(e._CompareWildcard('virtual/some-identifier/testing123'))\nself.assertTrue(e._CompareWildcard('test'))\nself.assertTrue(e._CompareWildcard('virtual/some-identifier/test'))\nself.asser... | <|body_start_0|>
e = data_types.WebTestExpectation('test*', ['tag1'], 'Failure')
self.assertTrue(e._CompareWildcard('testing123'))
self.assertTrue(e._CompareWildcard('virtual/some-identifier/testing123'))
self.assertTrue(e._CompareWildcard('test'))
self.assertTrue(e._CompareWildc... | WebTestExpectationUnittest | [
"LGPL-2.0-or-later",
"LicenseRef-scancode-warranty-disclaimer",
"LGPL-2.1-only",
"GPL-1.0-or-later",
"GPL-2.0-only",
"LGPL-2.0-only",
"BSD-2-Clause",
"LicenseRef-scancode-other-copyleft",
"BSD-3-Clause",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebTestExpectationUnittest:
def testCompareWildcard(self):
"""Tests that wildcard comparisons work as expected."""
<|body_0|>
def testCompareNonWildcard(self):
"""Tests that non-wildcard comparisons work as expected."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_016720 | 10,707 | permissive | [
{
"docstring": "Tests that wildcard comparisons work as expected.",
"name": "testCompareWildcard",
"signature": "def testCompareWildcard(self)"
},
{
"docstring": "Tests that non-wildcard comparisons work as expected.",
"name": "testCompareNonWildcard",
"signature": "def testCompareNonWil... | 2 | stack_v2_sparse_classes_30k_train_005764 | Implement the Python class `WebTestExpectationUnittest` described below.
Class description:
Implement the WebTestExpectationUnittest class.
Method signatures and docstrings:
- def testCompareWildcard(self): Tests that wildcard comparisons work as expected.
- def testCompareNonWildcard(self): Tests that non-wildcard c... | Implement the Python class `WebTestExpectationUnittest` described below.
Class description:
Implement the WebTestExpectationUnittest class.
Method signatures and docstrings:
- def testCompareWildcard(self): Tests that wildcard comparisons work as expected.
- def testCompareNonWildcard(self): Tests that non-wildcard c... | fd8a8914ca0183f0add65ae55f04e287543c7d4a | <|skeleton|>
class WebTestExpectationUnittest:
def testCompareWildcard(self):
"""Tests that wildcard comparisons work as expected."""
<|body_0|>
def testCompareNonWildcard(self):
"""Tests that non-wildcard comparisons work as expected."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WebTestExpectationUnittest:
def testCompareWildcard(self):
"""Tests that wildcard comparisons work as expected."""
e = data_types.WebTestExpectation('test*', ['tag1'], 'Failure')
self.assertTrue(e._CompareWildcard('testing123'))
self.assertTrue(e._CompareWildcard('virtual/some-... | the_stack_v2_python_sparse | third_party/blink/tools/blinkpy/web_tests/stale_expectation_removal/data_types_unittest.py | SREERAGI18/chromium | train | 1 | |
d8399a088f67a1c4e3a9ba57bbb791d7c5c8b632 | [
"j = len(num2) - 1\na2 = 0\nb2 = 0\nwhile 0 != j:\n a2 = num2[j]\n for k in range(0, j):\n b2 = num2[k]\n if a2 + b2 + re1 + re2 == target:\n C.add((re1, re2, b2, a2))\n j = j - 1\nreturn C",
"i = 0\ntmp3 = len(num3) - 2\nwhile i < tmp3:\n i = i + 1\n lennum = tmp3 - i + 1\... | <|body_start_0|>
j = len(num2) - 1
a2 = 0
b2 = 0
while 0 != j:
a2 = num2[j]
for k in range(0, j):
b2 = num2[k]
if a2 + b2 + re1 + re2 == target:
C.add((re1, re2, b2, a2))
j = j - 1
return C
<|... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, num2, re1, re2, C, target):
""":type nums： List[int] :rtype: set()"""
<|body_0|>
def threeSum(self, num3, re1, C, target):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
def fourSum(self, nums, target):
... | stack_v2_sparse_classes_36k_train_016721 | 1,209 | no_license | [
{
"docstring": ":type nums： List[int] :rtype: set()",
"name": "twoSum",
"signature": "def twoSum(self, num2, re1, re2, C, target)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, num3, re1, C, target)"
},
{
"... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, num2, re1, re2, C, target): :type nums： List[int] :rtype: set()
- def threeSum(self, num3, re1, C, target): :type nums: List[int] :rtype: List[List[int]]
- def f... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, num2, re1, re2, C, target): :type nums： List[int] :rtype: set()
- def threeSum(self, num3, re1, C, target): :type nums: List[int] :rtype: List[List[int]]
- def f... | 9752533bc76ce5ecb881f61e33a3bc4b20dcf666 | <|skeleton|>
class Solution:
def twoSum(self, num2, re1, re2, C, target):
""":type nums： List[int] :rtype: set()"""
<|body_0|>
def threeSum(self, num3, re1, C, target):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
def fourSum(self, nums, target):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def twoSum(self, num2, re1, re2, C, target):
""":type nums： List[int] :rtype: set()"""
j = len(num2) - 1
a2 = 0
b2 = 0
while 0 != j:
a2 = num2[j]
for k in range(0, j):
b2 = num2[k]
if a2 + b2 + re1 + re2 ... | the_stack_v2_python_sparse | 018. 4Sum/18. 4Sum.py | 603lzy/LeetCode | train | 3 | |
09ff974d03ba24a1dcb439dca17d475edb2ab07b | [
"entity_normalizer_kwargs = _resolve_kwargs(kwargs=entity_normalizer_kwargs, default_kwargs=self.default_entity_normalizer_kwargs)\nentity_initializer_kwargs = self._update_embedding_init_with_default(entity_initializer_kwargs, embedding_dim=embedding_dim)\nrelation_initializer_kwargs = self._update_embedding_init_... | <|body_start_0|>
entity_normalizer_kwargs = _resolve_kwargs(kwargs=entity_normalizer_kwargs, default_kwargs=self.default_entity_normalizer_kwargs)
entity_initializer_kwargs = self._update_embedding_init_with_default(entity_initializer_kwargs, embedding_dim=embedding_dim)
relation_initializer_kwa... | An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE | PairRE | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PairRE:
"""An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE"""
def __init__(self, embedding_dim: int=200, p: int=1, power_norm: bool=False, entity_i... | stack_v2_sparse_classes_36k_train_016722 | 6,053 | permissive | [
{
"docstring": "Initialize PairRE via the :class:`pykeen.nn.modules.PairREInteraction` interaction. :param embedding_dim: The entity embedding dimension $d$. :param p: The $l_p$ norm. :param power_norm: Should the power norm be used? :param entity_initializer: Entity initializer function. Defaults to :func:`tor... | 2 | null | Implement the Python class `PairRE` described below.
Class description:
An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
Method signatures and docstrings:
- def __init__(self... | Implement the Python class `PairRE` described below.
Class description:
An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE
Method signatures and docstrings:
- def __init__(self... | 5ff3597b18ab9a220e34361d3c3f262060811df1 | <|skeleton|>
class PairRE:
"""An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE"""
def __init__(self, embedding_dim: int=200, p: int=1, power_norm: bool=False, entity_i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PairRE:
"""An implementation of PairRE from [chao2020]_. --- citation: author: Chao year: 2020 link: http://arxiv.org/abs/2011.03798 github: alipay/KnowledgeGraphEmbeddingsViaPairedRelationVectors_PairRE"""
def __init__(self, embedding_dim: int=200, p: int=1, power_norm: bool=False, entity_initializer: H... | the_stack_v2_python_sparse | src/pykeen/models/unimodal/pair_re.py | pykeen/pykeen | train | 1,308 |
7b8abec9f678cb3e13ef70ff6673518bd730bc38 | [
"res = []\nl = len(s)\nfor i in range(1, l):\n if s[i] == s[i - 1] == '+':\n res.append(s[:i - 1] + '--' + s[i + 1:])\nreturn res",
"firstmove = self.generatePossibleNextMoves(s)\nif len(firstmove) == 0:\n return False\nfor move in firstmove:\n if not self.canWin(move):\n return True\nretur... | <|body_start_0|>
res = []
l = len(s)
for i in range(1, l):
if s[i] == s[i - 1] == '+':
res.append(s[:i - 1] + '--' + s[i + 1:])
return res
<|end_body_0|>
<|body_start_1|>
firstmove = self.generatePossibleNextMoves(s)
if len(firstmove) == 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generatePossibleNextMoves(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def canWin(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
l = len(s)
for i in range(1,... | stack_v2_sparse_classes_36k_train_016723 | 650 | no_license | [
{
"docstring": ":type s: str :rtype: List[str]",
"name": "generatePossibleNextMoves",
"signature": "def generatePossibleNextMoves(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "canWin",
"signature": "def canWin(self, s)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generatePossibleNextMoves(self, s): :type s: str :rtype: List[str]
- def canWin(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generatePossibleNextMoves(self, s): :type s: str :rtype: List[str]
- def canWin(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def generatePossibleNex... | ef8c9422c481aa3c482933318c785ad28dd7703e | <|skeleton|>
class Solution:
def generatePossibleNextMoves(self, s):
""":type s: str :rtype: List[str]"""
<|body_0|>
def canWin(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def generatePossibleNextMoves(self, s):
""":type s: str :rtype: List[str]"""
res = []
l = len(s)
for i in range(1, l):
if s[i] == s[i - 1] == '+':
res.append(s[:i - 1] + '--' + s[i + 1:])
return res
def canWin(self, s):
... | the_stack_v2_python_sparse | python/filp_game_II.py | pzmrzy/LeetCode | train | 2 | |
0f8d2ecef4f95c75a59ceaa6267a8841fd9c93e8 | [
"p_list = list(p)\nif isinstance(p[1], dict):\n p[0] = p[1]\n if 'NO' in p_list:\n p[0]['encrypt']['salt'] = False\n elif 'USING' in p_list:\n p[0]['encrypt']['encryption_algorithm'] = p_list[-1]\n elif 'SALT' not in p_list:\n p[0]['encrypt']['integrity_algorithm'] = p_list[-1]\nels... | <|body_start_0|>
p_list = list(p)
if isinstance(p[1], dict):
p[0] = p[1]
if 'NO' in p_list:
p[0]['encrypt']['salt'] = False
elif 'USING' in p_list:
p[0]['encrypt']['encryption_algorithm'] = p_list[-1]
elif 'SALT' not in p_li... | Oracle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Oracle:
def p_encrypt(self, p):
"""encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING"""
<|body_0|>
def p_storage(self, p):
"""storage : STORAGE LP | storage id id | storage id id RP"""
<|body_1|>
def p_expr_storag... | stack_v2_sparse_classes_36k_train_016724 | 1,438 | permissive | [
{
"docstring": "encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING",
"name": "p_encrypt",
"signature": "def p_encrypt(self, p)"
},
{
"docstring": "storage : STORAGE LP | storage id id | storage id id RP",
"name": "p_storage",
"signature": "def p_st... | 3 | stack_v2_sparse_classes_30k_train_001003 | Implement the Python class `Oracle` described below.
Class description:
Implement the Oracle class.
Method signatures and docstrings:
- def p_encrypt(self, p): encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING
- def p_storage(self, p): storage : STORAGE LP | storage id id | st... | Implement the Python class `Oracle` described below.
Class description:
Implement the Oracle class.
Method signatures and docstrings:
- def p_encrypt(self, p): encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING
- def p_storage(self, p): storage : STORAGE LP | storage id id | st... | 8f69c9c3b58990f0d47dbe868fe4a572d51e2de7 | <|skeleton|>
class Oracle:
def p_encrypt(self, p):
"""encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING"""
<|body_0|>
def p_storage(self, p):
"""storage : STORAGE LP | storage id id | storage id id RP"""
<|body_1|>
def p_expr_storag... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Oracle:
def p_encrypt(self, p):
"""encrypt : ENCRYPT | encrypt NO SALT | encrypt SALT | encrypt USING STRING | encrypt STRING"""
p_list = list(p)
if isinstance(p[1], dict):
p[0] = p[1]
if 'NO' in p_list:
p[0]['encrypt']['salt'] = False
... | the_stack_v2_python_sparse | simple_ddl_parser/dialects/oracle.py | bjmc/simple-ddl-parser | train | 0 | |
6c1ccf4bbf6f4e3e80c43ccc498b8f96a2d13788 | [
"super().__init__()\nself.flatten = nn.Flatten()\nself.out_channels = style_channels\nself.downsample = None\nif in_channels != style_channels:\n self.downsample = ChannelPool(in_channels=in_channels, out_channels=style_channels, convolution=convolution, normalization=normalization)",
"if self.downsample is no... | <|body_start_0|>
super().__init__()
self.flatten = nn.Flatten()
self.out_channels = style_channels
self.downsample = None
if in_channels != style_channels:
self.downsample = ChannelPool(in_channels=in_channels, out_channels=style_channels, convolution=convolution, nor... | StyleReshape | [
"MIT",
"Apache-2.0",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StyleReshape:
def __init__(self, in_channels: int, style_channels: int, normalization: str='bn', convolution: str='conv', **kwargs) -> None:
"""Reshape feature-map into a style-vector. See Cellpose. Cellpose: - https://www.nature.com/articles/s41592-020-01018-x Takes in a feature map (B,... | stack_v2_sparse_classes_36k_train_016725 | 5,285 | permissive | [
{
"docstring": "Reshape feature-map into a style-vector. See Cellpose. Cellpose: - https://www.nature.com/articles/s41592-020-01018-x Takes in a feature map (B, C, H, W). Then averages, and normalizes it into to a style feature vector. Parameters ---------- in_channels : int Number of input channels. style_chan... | 2 | stack_v2_sparse_classes_30k_train_001255 | Implement the Python class `StyleReshape` described below.
Class description:
Implement the StyleReshape class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, style_channels: int, normalization: str='bn', convolution: str='conv', **kwargs) -> None: Reshape feature-map into a style-vector. Se... | Implement the Python class `StyleReshape` described below.
Class description:
Implement the StyleReshape class.
Method signatures and docstrings:
- def __init__(self, in_channels: int, style_channels: int, normalization: str='bn', convolution: str='conv', **kwargs) -> None: Reshape feature-map into a style-vector. Se... | 7f79405012eb934b419bbdba8de23f35e840ca85 | <|skeleton|>
class StyleReshape:
def __init__(self, in_channels: int, style_channels: int, normalization: str='bn', convolution: str='conv', **kwargs) -> None:
"""Reshape feature-map into a style-vector. See Cellpose. Cellpose: - https://www.nature.com/articles/s41592-020-01018-x Takes in a feature map (B,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StyleReshape:
def __init__(self, in_channels: int, style_channels: int, normalization: str='bn', convolution: str='conv', **kwargs) -> None:
"""Reshape feature-map into a style-vector. See Cellpose. Cellpose: - https://www.nature.com/articles/s41592-020-01018-x Takes in a feature map (B, C, H, W). The... | the_stack_v2_python_sparse | cellseg_models_pytorch/modules/misc_modules.py | okunator/cellseg_models.pytorch | train | 43 | |
b5f32f84124af5ab1349b23a8d6ccc05ade5e833 | [
"super().__init__()\nself.predict_ntype = predict_ntype\nself.adapt_fcs = nn.ModuleDict({ntype: nn.Linear(in_dim, hidden_dim) for ntype, in_dim in in_dims.items()})\nself.layers = nn.ModuleList([HGTLayer(hidden_dim, hidden_dim, num_heads, ntypes, etypes, dropout, use_norm) for _ in range(num_layers)])\nself.predict... | <|body_start_0|>
super().__init__()
self.predict_ntype = predict_ntype
self.adapt_fcs = nn.ModuleDict({ntype: nn.Linear(in_dim, hidden_dim) for ntype, in_dim in in_dims.items()})
self.layers = nn.ModuleList([HGTLayer(hidden_dim, hidden_dim, num_heads, ntypes, etypes, dropout, use_norm) f... | HGT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HGT:
def __init__(self, in_dims, hidden_dim, out_dim, num_heads, ntypes, etypes, predict_ntype, num_layers, dropout=0.2, use_norm=True):
"""HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :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 nty... | stack_v2_sparse_classes_36k_train_016726 | 8,548 | no_license | [
{
"docstring": "HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :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 ntypes: List[str] 顶点类型列表 :param etypes: List[(str, str, str)] 规范边类型列表 :param predict_ntype: str 待预测顶点类型 :param num_layers: int 层数 :param dropout: dropo... | 2 | stack_v2_sparse_classes_30k_train_014963 | Implement the Python class `HGT` described below.
Class description:
Implement the HGT class.
Method signatures and docstrings:
- def __init__(self, in_dims, hidden_dim, out_dim, num_heads, ntypes, etypes, predict_ntype, num_layers, dropout=0.2, use_norm=True): HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :par... | Implement the Python class `HGT` described below.
Class description:
Implement the HGT class.
Method signatures and docstrings:
- def __init__(self, in_dims, hidden_dim, out_dim, num_heads, ntypes, etypes, predict_ntype, num_layers, dropout=0.2, use_norm=True): HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :par... | b40071dc9f9fb20f081f4ed4944a7b65de919c18 | <|skeleton|>
class HGT:
def __init__(self, in_dims, hidden_dim, out_dim, num_heads, ntypes, etypes, predict_ntype, num_layers, dropout=0.2, use_norm=True):
"""HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :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 nty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HGT:
def __init__(self, in_dims, hidden_dim, out_dim, num_heads, ntypes, etypes, predict_ntype, num_layers, dropout=0.2, use_norm=True):
"""HGT模型 :param in_dims: Dict[str, int] 顶点类型到输入特征维数的映射 :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 ntypes: List[str]... | the_stack_v2_python_sparse | gnn/hgt/model.py | deepdumbo/pytorch-tutorial-1 | train | 0 | |
65faf6d1b9d2b7c2c348ad115c20fc840e0dcd4c | [
"if isinstance(key, int):\n return ESPTransformSuite(key)\nif key not in ESPTransformSuite._member_map_:\n return extend_enum(ESPTransformSuite, key, default)\nreturn ESPTransformSuite[key]",
"if not (isinstance(value, int) and 0 <= value <= 65535):\n raise ValueError('%r is not a valid %s' % (value, cls... | <|body_start_0|>
if isinstance(key, int):
return ESPTransformSuite(key)
if key not in ESPTransformSuite._member_map_:
return extend_enum(ESPTransformSuite, key, default)
return ESPTransformSuite[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) ... | [ESPTransformSuite] ESP Transform Suite IDs | ESPTransformSuite | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_016727 | 2,727 | permissive | [
{
"docstring": "Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:",
"name": "get",
"signature": "def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite'"
},
{
"docstring": "Lookup function used when value is not ... | 2 | null | Implement the Python class `ESPTransformSuite` described below.
Class description:
[ESPTransformSuite] ESP Transform Suite IDs
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite': Backport support for original codes. Args: key: Key to get enum item. default: Default... | Implement the Python class `ESPTransformSuite` described below.
Class description:
[ESPTransformSuite] ESP Transform Suite IDs
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite': Backport support for original codes. Args: key: Key to get enum item. default: Default... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ESPTransformSuite:
"""[ESPTransformSuite] ESP Transform Suite IDs"""
def get(key: 'int | str', default: 'int'=-1) -> 'ESPTransformSuite':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance(key, int)... | the_stack_v2_python_sparse | pcapkit/const/hip/esp_transform_suite.py | JarryShaw/PyPCAPKit | train | 204 |
a6a99ba75e9744fd4886bb06b052b77bea153e13 | [
"res = self.sumNumbers_(root)\nres = [int(i) for i in res]\nreturn sum(res)",
"if root is None:\n return []\nif root.left is None and root.right is None:\n return [str(root.val)]\nleft_sum: List[str] = self.sumNumbers_(root.left)\nres = []\nfor i in left_sum:\n res.append(str(root.val) + str(i))\nprint(r... | <|body_start_0|>
res = self.sumNumbers_(root)
res = [int(i) for i in res]
return sum(res)
<|end_body_0|>
<|body_start_1|>
if root is None:
return []
if root.left is None and root.right is None:
return [str(root.val)]
left_sum: List[str] = self.sum... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
<|body_0|>
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype... | stack_v2_sparse_classes_36k_train_016728 | 2,100 | no_license | [
{
"docstring": "从根节点到叶子节点的数字之和",
"name": "sumNumbers",
"signature": "def sumNumbers(self, root: TreeNode) -> int"
},
{
"docstring": "创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype: object",
"name": "sumNumbers_",
... | 2 | stack_v2_sparse_classes_30k_train_019763 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root: TreeNode) -> int: 从根节点到叶子节点的数字之和
- def sumNumbers_(self, root: TreeNode) -> List[str]: 创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个Lis... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sumNumbers(self, root: TreeNode) -> int: 从根节点到叶子节点的数字之和
- def sumNumbers_(self, root: TreeNode) -> List[str]: 创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个Lis... | cd46cf08a580c418cc40a68bf9b32371fc69a803 | <|skeleton|>
class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
<|body_0|>
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个List [95,91], 然后再去加上根节点， 用List[str]的原因是中间有00的情况，转化为int会丢掉 :rtype... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sumNumbers(self, root: TreeNode) -> int:
"""从根节点到叶子节点的数字之和"""
res = self.sumNumbers_(root)
res = [int(i) for i in res]
return sum(res)
def sumNumbers_(self, root: TreeNode) -> List[str]:
"""创建这个函数的原因是 # 输入：root = [4,9,0,5,1] 左边有两个路径495,491 那么左边应该返回是一个... | the_stack_v2_python_sparse | tree/129 sumNumbers.py | pangyouzhen/data-structure | train | 0 | |
697296e524064e82a251c7e26e7ad5629104e8b0 | [
"question = 'What language did you first learn to speak?'\nmy_survey = AnonymousSurvey(question)\nmy_survey.store_response('English')\nself.assertIn('English', my_survey.responses)",
"question = 'What language did you first learn to speak?'\nmy_survey = AnonymousSurvey(question)\nresponses = ['english', 'spanish'... | <|body_start_0|>
question = 'What language did you first learn to speak?'
my_survey = AnonymousSurvey(question)
my_survey.store_response('English')
self.assertIn('English', my_survey.responses)
<|end_body_0|>
<|body_start_1|>
question = 'What language did you first learn to spea... | Tests for the class AnonymousSurvey | TestAnonymousSurvey | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestAnonymousSurvey:
"""Tests for the class AnonymousSurvey"""
def test_store_single_response(self):
"""Test that a single response is stored properly"""
<|body_0|>
def test_store_three_responses(self):
"""Test that a single response is stored properly"""
... | stack_v2_sparse_classes_36k_train_016729 | 980 | no_license | [
{
"docstring": "Test that a single response is stored properly",
"name": "test_store_single_response",
"signature": "def test_store_single_response(self)"
},
{
"docstring": "Test that a single response is stored properly",
"name": "test_store_three_responses",
"signature": "def test_stor... | 2 | stack_v2_sparse_classes_30k_train_012784 | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Tests for the class AnonymousSurvey
Method signatures and docstrings:
- def test_store_single_response(self): Test that a single response is stored properly
- def test_store_three_responses(self): Test that a single response is store... | Implement the Python class `TestAnonymousSurvey` described below.
Class description:
Tests for the class AnonymousSurvey
Method signatures and docstrings:
- def test_store_single_response(self): Test that a single response is stored properly
- def test_store_three_responses(self): Test that a single response is store... | 81160304d8ef66ecde1bfd194261a5164cc934dd | <|skeleton|>
class TestAnonymousSurvey:
"""Tests for the class AnonymousSurvey"""
def test_store_single_response(self):
"""Test that a single response is stored properly"""
<|body_0|>
def test_store_three_responses(self):
"""Test that a single response is stored properly"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestAnonymousSurvey:
"""Tests for the class AnonymousSurvey"""
def test_store_single_response(self):
"""Test that a single response is stored properly"""
question = 'What language did you first learn to speak?'
my_survey = AnonymousSurvey(question)
my_survey.store_response... | the_stack_v2_python_sparse | chapter_11/test_survey.py | Raihan9797/Python-Crash-Course | train | 0 |
2125b2483ac6a846fa5c12e4ed03d12e74be0b07 | [
"r, phi = param_util.cart2polar(x, y, center_x=center_x, center_y=center_y)\nf_ = r * a_m / (1 - m ** 2) * np.cos(m * (phi - phi_m))\nreturn f_",
"r, phi = param_util.cart2polar(x, y, center_x=center_x, center_y=center_y)\nf_x = np.cos(phi) * a_m / (1 - m ** 2) * np.cos(m * (phi - phi_m)) + np.sin(phi) * m * a_m ... | <|body_start_0|>
r, phi = param_util.cart2polar(x, y, center_x=center_x, center_y=center_y)
f_ = r * a_m / (1 - m ** 2) * np.cos(m * (phi - phi_m))
return f_
<|end_body_0|>
<|body_start_1|>
r, phi = param_util.cart2polar(x, y, center_x=center_x, center_y=center_y)
f_x = np.cos(p... | This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole strength phi_m : float, multipole orientation in radian | Multipole | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Multipole:
"""This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole strength phi_m : float, multipole orientat... | stack_v2_sparse_classes_36k_train_016730 | 3,657 | permissive | [
{
"docstring": "Lensing potential of multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf :param x: x-coordinate to evaluate function :param y: y-coordinate to evaluate function :param m: int, multipole order, m>=... | 3 | stack_v2_sparse_classes_30k_train_011808 | Implement the Python class `Multipole` described below.
Class description:
This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole str... | Implement the Python class `Multipole` described below.
Class description:
This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole str... | 902a0f318da46bd444d408853f40f744603e2f35 | <|skeleton|>
class Multipole:
"""This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole strength phi_m : float, multipole orientat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Multipole:
"""This class contains a multipole contribution (for 1 component with m>=2) This uses the same definitions as Xu et al.(2013) in Appendix B3 https://arxiv.org/pdf/1307.4220.pdf Equation B12 m : int, multipole order, m>=2 a_m : float, multipole strength phi_m : float, multipole orientation in radian... | the_stack_v2_python_sparse | lenstronomy/LensModel/Profiles/multipole.py | sibirrer/lenstronomy | train | 115 |
76dbc748f8e3aeace1c514cb0b485559fe636073 | [
"self._logger = logging.getLogger(__name__)\n'Logger: The logger for this class.'\nself._job_store = job_store\n'The JobStore to obtain jobs from.'\nself._username = None\n'The remote user to connect as.'\nself._remote_cwlrunner = remote_cwlrunner\n'str: The remote path to the cwl runner executable.'\nself._sched =... | <|body_start_0|>
self._logger = logging.getLogger(__name__)
'Logger: The logger for this class.'
self._job_store = job_store
'The JobStore to obtain jobs from.'
self._username = None
'The remote user to connect as.'
self._remote_cwlrunner = remote_cwlrunner
... | JobRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobRunner:
def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None:
"""Create a JobRunner object. Args: job_store: The job store to get jobs from. config: The configuration. remote_cwlrunner: The location of the CWL runner to use."""
<|body_0|... | stack_v2_sparse_classes_36k_train_016731 | 5,414 | permissive | [
{
"docstring": "Create a JobRunner object. Args: job_store: The job store to get jobs from. config: The configuration. remote_cwlrunner: The location of the CWL runner to use.",
"name": "__init__",
"signature": "def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None... | 4 | stack_v2_sparse_classes_30k_train_019154 | Implement the Python class `JobRunner` described below.
Class description:
Implement the JobRunner class.
Method signatures and docstrings:
- def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None: Create a JobRunner object. Args: job_store: The job store to get jobs from. config... | Implement the Python class `JobRunner` described below.
Class description:
Implement the JobRunner class.
Method signatures and docstrings:
- def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None: Create a JobRunner object. Args: job_store: The job store to get jobs from. config... | f8ff51629d1198200bd84d59e78ca456321af940 | <|skeleton|>
class JobRunner:
def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None:
"""Create a JobRunner object. Args: job_store: The job store to get jobs from. config: The configuration. remote_cwlrunner: The location of the CWL runner to use."""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobRunner:
def __init__(self, job_store: SQLiteJobStore, config: Config, remote_cwlrunner: str) -> None:
"""Create a JobRunner object. Args: job_store: The job store to get jobs from. config: The configuration. remote_cwlrunner: The location of the CWL runner to use."""
self._logger = logging.... | the_stack_v2_python_sparse | cerise/back_end/job_runner.py | MD-Studio/cerise | train | 10 | |
1be1735112a3fcd166c986e007ac6ba66be0ffe3 | [
"title = 'Commission'\ndate_str = ''\nyear_str = ''\nfor item in response.css('.ms-rtestate-field > *'):\n if item.root.tag == 'h2':\n title = item.xpath('./text()').extract_first()\n continue\n if item.root.tag == 'h3':\n year_str = item.xpath('./text()').extract_first()\n continu... | <|body_start_0|>
title = 'Commission'
date_str = ''
year_str = ''
for item in response.css('.ms-rtestate-field > *'):
if item.root.tag == 'h2':
title = item.xpath('./text()').extract_first()
continue
if item.root.tag == 'h3':
... | IlEnvironmentalJusticeSpider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IlEnvironmentalJusticeSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_classification(self, title):
"""Parse or generate clas... | stack_v2_sparse_classes_36k_train_016732 | 4,301 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse or generate classification from allowed options.",
"name": "_pa... | 4 | null | Implement the Python class `IlEnvironmentalJusticeSpider` described below.
Class description:
Implement the IlEnvironmentalJusticeSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your... | Implement the Python class `IlEnvironmentalJusticeSpider` described below.
Class description:
Implement the IlEnvironmentalJusticeSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your... | 611fce6a2705446e25a2fc33e32090a571eb35d1 | <|skeleton|>
class IlEnvironmentalJusticeSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_classification(self, title):
"""Parse or generate clas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IlEnvironmentalJusticeSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
title = 'Commission'
date_str = ''
year_str = ''
for item in response.css('.ms-... | the_stack_v2_python_sparse | city_scrapers/spiders/il_environmental_justice.py | City-Bureau/city-scrapers | train | 308 | |
4cec7813fa60b0c381cb6fe43b878b12905d9fc3 | [
"results = []\nallInts = Int + Uint\nfor function in contract.functions_declared:\n f_results = set()\n for node in function.nodes:\n for ir in node.irs:\n if isinstance(ir, Binary) and ir.type in self.flip_table:\n if isinstance(ir.variable_left, Constant):\n ... | <|body_start_0|>
results = []
allInts = Int + Uint
for function in contract.functions_declared:
f_results = set()
for node in function.nodes:
for ir in node.irs:
if isinstance(ir, Binary) and ir.type in self.flip_table:
... | Type-based tautology or contradiction | TypeBasedTautology | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TypeBasedTautology:
"""Type-based tautology or contradiction"""
def detect_type_based_tautologies(self, contract):
"""Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract: Contract to detect assignment within. :return: A list o... | stack_v2_sparse_classes_36k_train_016733 | 5,484 | no_license | [
{
"docstring": "Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract: Contract to detect assignment within. :return: A list of nodes with tautolgies/contradictions.",
"name": "detect_type_based_tautologies",
"signature": "def detect_type_based_tau... | 2 | null | Implement the Python class `TypeBasedTautology` described below.
Class description:
Type-based tautology or contradiction
Method signatures and docstrings:
- def detect_type_based_tautologies(self, contract): Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract... | Implement the Python class `TypeBasedTautology` described below.
Class description:
Type-based tautology or contradiction
Method signatures and docstrings:
- def detect_type_based_tautologies(self, contract): Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract... | 7a55877bdde0d6adabe3ce9c4f92e8ba20b4b3cc | <|skeleton|>
class TypeBasedTautology:
"""Type-based tautology or contradiction"""
def detect_type_based_tautologies(self, contract):
"""Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract: Contract to detect assignment within. :return: A list o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TypeBasedTautology:
"""Type-based tautology or contradiction"""
def detect_type_based_tautologies(self, contract):
"""Detects and returns all nodes with tautology/contradiction comparisons (based on type alone). :param contract: Contract to detect assignment within. :return: A list of nodes with ... | the_stack_v2_python_sparse | fortress/detectors/statements/type_based_tautology.py | bydolson/fortress-security-audit-engine | train | 0 |
33aeb53524132e3e81b43fd854f442af1cf8ce2b | [
"super().__init__(*args, **kwargs)\nself._callback_fn = callback_fn\nself._current_task_info = None",
"task_name = task['name']\nif task_name == 'resource':\n return self._callback_fn['deal_with_resource']()\nelif task_name == 'collector_start_task':\n self._current_task_info = task['task_info']\n self._... | <|body_start_0|>
super().__init__(*args, **kwargs)
self._callback_fn = callback_fn
self._current_task_info = None
<|end_body_0|>
<|body_start_1|>
task_name = task['name']
if task_name == 'resource':
return self._callback_fn['deal_with_resource']()
elif task_n... | Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task | CollectorSlave | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions a... | stack_v2_sparse_classes_36k_train_016734 | 8,845 | permissive | [
{
"docstring": "Overview: Init callback functions additionally. Callback functions are methods in comm collector.",
"name": "__init__",
"signature": "def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None"
},
{
"docstring": "Overview: Process a task according to input task... | 2 | stack_v2_sparse_classes_30k_train_012080 | Implement the Python class `CollectorSlave` described below.
Class description:
Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task
Method signatures and docstrings:
- def __init__(self, *args, callback_fn: Dict[str, Callable... | Implement the Python class `CollectorSlave` described below.
Class description:
Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task
Method signatures and docstrings:
- def __init__(self, *args, callback_fn: Dict[str, Callable... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollectorSlave:
"""Overview: A slave, whose master is coordinator. Used to pass message between comm collector and coordinator. Interfaces: __init__, _process_task"""
def __init__(self, *args, callback_fn: Dict[str, Callable], **kwargs) -> None:
"""Overview: Init callback functions additionally. ... | the_stack_v2_python_sparse | ding/worker/collector/comm/flask_fs_collector.py | shengxuesun/DI-engine | train | 1 |
ce20f94ac8a6b5ea5cebc5a581fe60168cbd28a3 | [
"unconfirmed_orders = self.filtered(lambda so: so.state not in ['sale', 'done'])\nunconfirmed_orders.invoice_status = 'no'\nconfirmed_orders = self - unconfirmed_orders\nif not confirmed_orders:\n return\nline_invoice_status_all = [(d['order_id'][0], d['invoice_status']) for d in self.env['sale.order.line'].read... | <|body_start_0|>
unconfirmed_orders = self.filtered(lambda so: so.state not in ['sale', 'done'])
unconfirmed_orders.invoice_status = 'no'
confirmed_orders = self - unconfirmed_orders
if not confirmed_orders:
return
line_invoice_status_all = [(d['order_id'][0], d['invo... | SaleOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SaleOrder:
def _get_invoice_status(self):
"""Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to invoice. This is also the default value if the conditions of no other status is met. - to invoice: i... | stack_v2_sparse_classes_36k_train_016735 | 4,886 | no_license | [
{
"docstring": "Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to invoice. This is also the default value if the conditions of no other status is met. - to invoice: if any SO line is 'to invoice', the whole SO is 'to in... | 2 | stack_v2_sparse_classes_30k_train_007781 | Implement the Python class `SaleOrder` described below.
Class description:
Implement the SaleOrder class.
Method signatures and docstrings:
- def _get_invoice_status(self): Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to in... | Implement the Python class `SaleOrder` described below.
Class description:
Implement the SaleOrder class.
Method signatures and docstrings:
- def _get_invoice_status(self): Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to in... | 527ca57ace3d10f4f76ef0fd8a46f9f4a0581cc9 | <|skeleton|>
class SaleOrder:
def _get_invoice_status(self):
"""Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to invoice. This is also the default value if the conditions of no other status is met. - to invoice: i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SaleOrder:
def _get_invoice_status(self):
"""Compute the invoice status of a SO. Possible statuses: - no: if the SO is not in status 'sale' or 'done', we consider that there is nothing to invoice. This is also the default value if the conditions of no other status is met. - to invoice: if any SO line ... | the_stack_v2_python_sparse | custom_modules/sale_report_custom/models/sale_invoice_status_custom.py | westlyou/foodsfortomorrow | train | 0 | |
63dd27f99a9810668af35ffa0b8ba9f3d173fb94 | [
"self.root = Node()\nfor word in data:\n self.add(word)",
"node = self.root\nfor c in word:\n if c not in node.children:\n node.children[c] = Node()\n node = node.children[c]\nnode.is_word = True",
"node = self.root\nfor c in prefix:\n if c not in node.children:\n return False\n nod... | <|body_start_0|>
self.root = Node()
for word in data:
self.add(word)
<|end_body_0|>
<|body_start_1|>
node = self.root
for c in word:
if c not in node.children:
node.children[c] = Node()
node = node.children[c]
node.is_word = Tr... | Dictionary class that looks like a trie | Dictionary | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dictionary:
"""Dictionary class that looks like a trie"""
def __init__(self, data: List[str]):
""":param data: list of words :type data: List[str]"""
<|body_0|>
def add(self, word):
"""Add the word into the dictionary"""
<|body_1|>
def is_prefix(self... | stack_v2_sparse_classes_36k_train_016736 | 1,379 | no_license | [
{
"docstring": ":param data: list of words :type data: List[str]",
"name": "__init__",
"signature": "def __init__(self, data: List[str])"
},
{
"docstring": "Add the word into the dictionary",
"name": "add",
"signature": "def add(self, word)"
},
{
"docstring": ":return: True if th... | 4 | stack_v2_sparse_classes_30k_train_006102 | Implement the Python class `Dictionary` described below.
Class description:
Dictionary class that looks like a trie
Method signatures and docstrings:
- def __init__(self, data: List[str]): :param data: list of words :type data: List[str]
- def add(self, word): Add the word into the dictionary
- def is_prefix(self, pr... | Implement the Python class `Dictionary` described below.
Class description:
Dictionary class that looks like a trie
Method signatures and docstrings:
- def __init__(self, data: List[str]): :param data: list of words :type data: List[str]
- def add(self, word): Add the word into the dictionary
- def is_prefix(self, pr... | 597964f0dbe07f335d8cd5a8a0f8439039940ea8 | <|skeleton|>
class Dictionary:
"""Dictionary class that looks like a trie"""
def __init__(self, data: List[str]):
""":param data: list of words :type data: List[str]"""
<|body_0|>
def add(self, word):
"""Add the word into the dictionary"""
<|body_1|>
def is_prefix(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dictionary:
"""Dictionary class that looks like a trie"""
def __init__(self, data: List[str]):
""":param data: list of words :type data: List[str]"""
self.root = Node()
for word in data:
self.add(word)
def add(self, word):
"""Add the word into the dictiona... | the_stack_v2_python_sparse | nfadeeva/assignment3/dictionary.py | flerdacodeu/CodeU-2018-Group7 | train | 0 |
6f9caafc549beea5b3756706faed5ee5ee719966 | [
"self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)\nself._serial_port = serial_port\nself._attr_name = name\nself._attributes = {LAMP_HOURS: STATE_UNKNOWN, INPUT_SOURCE: STATE_UNKNOWN, ECO_MODE: STATE_UNKNOWN}",
"ret = ''\ntry:\n if not self.ser.is_open:\n self.ser... | <|body_start_0|>
self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)
self._serial_port = serial_port
self._attr_name = name
self._attributes = {LAMP_HOURS: STATE_UNKNOWN, INPUT_SOURCE: STATE_UNKNOWN, ECO_MODE: STATE_UNKNOWN}
<|end_body_0|>
<|body_sta... | Represents an Acer Projector as a switch. | AcerSwitch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
<|body_0|>
def _write_read(self, msg: str) -> str:
"""Write to the projector a... | stack_v2_sparse_classes_36k_train_016737 | 4,527 | permissive | [
{
"docstring": "Init of the Acer projector.",
"name": "__init__",
"signature": "def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None"
},
{
"docstring": "Write to the projector and read the return.",
"name": "_write_read",
"signature": "def _write_read... | 6 | stack_v2_sparse_classes_30k_train_013061 | Implement the Python class `AcerSwitch` described below.
Class description:
Represents an Acer Projector as a switch.
Method signatures and docstrings:
- def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None: Init of the Acer projector.
- def _write_read(self, msg: str) -> str: Wri... | Implement the Python class `AcerSwitch` described below.
Class description:
Represents an Acer Projector as a switch.
Method signatures and docstrings:
- def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None: Init of the Acer projector.
- def _write_read(self, msg: str) -> str: Wri... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
<|body_0|>
def _write_read(self, msg: str) -> str:
"""Write to the projector a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AcerSwitch:
"""Represents an Acer Projector as a switch."""
def __init__(self, serial_port: str, name: str, timeout: int, write_timeout: int) -> None:
"""Init of the Acer projector."""
self.ser = serial.Serial(port=serial_port, timeout=timeout, write_timeout=write_timeout)
self._s... | the_stack_v2_python_sparse | homeassistant/components/acer_projector/switch.py | home-assistant/core | train | 35,501 |
e7c93a36e6cc5fbe90c6faaa7f64a7a79d8469cc | [
"self.protocol = self.dstype[datasourcetype]\nself.kwargs = kwargs\nmodule_ = importlib.import_module('contextmonkey.tracelayer.handlers.%s.%sRequestHandlerFactory' % (self.protocol.lower(), self.protocol))\nclass_ = getattr(module_, '%sRequestHandlerFactory' % self.protocol)\nself.datasourcehandlerconnection = cla... | <|body_start_0|>
self.protocol = self.dstype[datasourcetype]
self.kwargs = kwargs
module_ = importlib.import_module('contextmonkey.tracelayer.handlers.%s.%sRequestHandlerFactory' % (self.protocol.lower(), self.protocol))
class_ = getattr(module_, '%sRequestHandlerFactory' % self.protocol... | Provide methods to fetch traces from file, model, and database. | DataSourceHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataSourceHandler:
"""Provide methods to fetch traces from file, model, and database."""
def __init__(self, datasourcetype, **kwargs):
"""Initialize appropriate source handler factory."""
<|body_0|>
def executeFetch(self, uuid, modality):
"""Forward trace fetch r... | stack_v2_sparse_classes_36k_train_016738 | 4,232 | no_license | [
{
"docstring": "Initialize appropriate source handler factory.",
"name": "__init__",
"signature": "def __init__(self, datasourcetype, **kwargs)"
},
{
"docstring": "Forward trace fetch request to appropriate source handler factory.",
"name": "executeFetch",
"signature": "def executeFetch(... | 2 | stack_v2_sparse_classes_30k_test_000664 | Implement the Python class `DataSourceHandler` described below.
Class description:
Provide methods to fetch traces from file, model, and database.
Method signatures and docstrings:
- def __init__(self, datasourcetype, **kwargs): Initialize appropriate source handler factory.
- def executeFetch(self, uuid, modality): ... | Implement the Python class `DataSourceHandler` described below.
Class description:
Provide methods to fetch traces from file, model, and database.
Method signatures and docstrings:
- def __init__(self, datasourcetype, **kwargs): Initialize appropriate source handler factory.
- def executeFetch(self, uuid, modality): ... | 9974889a726d7f60c6da0d6ccab97113ce635a14 | <|skeleton|>
class DataSourceHandler:
"""Provide methods to fetch traces from file, model, and database."""
def __init__(self, datasourcetype, **kwargs):
"""Initialize appropriate source handler factory."""
<|body_0|>
def executeFetch(self, uuid, modality):
"""Forward trace fetch r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataSourceHandler:
"""Provide methods to fetch traces from file, model, and database."""
def __init__(self, datasourcetype, **kwargs):
"""Initialize appropriate source handler factory."""
self.protocol = self.dstype[datasourcetype]
self.kwargs = kwargs
module_ = importlib.... | the_stack_v2_python_sparse | contextmonkey/tracelayer/handlers/DataSourceHandler.py | manojrege/contextmonkey | train | 6 |
a7bd2a80bcf6a27c11ef916604536f12ff6d21f2 | [
"content = parent._content\nif content is not None:\n content = build_graves_on_subsection(content, path)\n if content is None:\n DocWarning(path, 'Listing element with empty content.')\nhead = parent._head\nif head is None:\n DocWarning(path, 'Listing element without empty head.')\nelse:\n head,... | <|body_start_0|>
content = parent._content
if content is not None:
content = build_graves_on_subsection(content, path)
if content is None:
DocWarning(path, 'Listing element with empty content.')
head = parent._head
if head is None:
DocW... | Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element. | GravedListingElement | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GravedListingElement:
"""Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element."""
def __new__(cls, parent, path):
... | stack_v2_sparse_classes_36k_train_016739 | 25,556 | permissive | [
{
"docstring": "Creates a new graved listing element. Parameters ---------- parent : ``TextListingElement`` The source listing element. path : ``QualPath`` The path of the respective docstring. Returns ------- self : `None`, ``GravedListingElement`` Returns `None`, if would have been creating an empty listing e... | 2 | stack_v2_sparse_classes_30k_train_010428 | Implement the Python class `GravedListingElement` described below.
Class description:
Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element.
Method ... | Implement the Python class `GravedListingElement` described below.
Class description:
Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element.
Method ... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class GravedListingElement:
"""Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element."""
def __new__(cls, parent, path):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GravedListingElement:
"""Represents a graved listing element. Attributes ---------- content : `None`, `list` of (`str`, ``Grave``) The graved content of the listing element. head : `None`, `list` of (`str`, ``Grave``) The graved head of the element."""
def __new__(cls, parent, path):
"""Creates a... | the_stack_v2_python_sparse | hata/ext/patchouli/graver.py | HuyaneMatsu/hata | train | 3 |
c08a846ebee5b57f0c4724033fc390764c341b61 | [
"super().__init__(enclosure)\nself.redfish['ChassisType'] = 'Enclosure'\nself.redfish['Model'] = enclosure['enclosureModel']\nself.redfish['IndicatorLED'] = self._map_indicator_led(enclosure['uidState'])\nself.redfish['Links']['Contains'] = list()\nself._set_links_to_computer_system(enclosure['deviceBays'])\nself.r... | <|body_start_0|>
super().__init__(enclosure)
self.redfish['ChassisType'] = 'Enclosure'
self.redfish['Model'] = enclosure['enclosureModel']
self.redfish['IndicatorLED'] = self._map_indicator_led(enclosure['uidState'])
self.redfish['Links']['Contains'] = list()
self._set_li... | Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources. | EnclosureChassis | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnclosureChassis:
"""Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources."""
def __init__(self, enclosure, environmental_configuration, manager_uuid):
"""Enclosure Chassis c... | stack_v2_sparse_classes_36k_train_016740 | 4,192 | permissive | [
{
"docstring": "Enclosure Chassis constructor Populates self.redfish with hardcoded Enclosure Chassis values and with the response of OneView enclosure. Args: enclosure: An object containing the Oneview enclosure to create the Redfish JSON. environmental_configuration: An object having information about the rac... | 3 | stack_v2_sparse_classes_30k_val_000352 | Implement the Python class `EnclosureChassis` described below.
Class description:
Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources.
Method signatures and docstrings:
- def __init__(self, enclosure, enviro... | Implement the Python class `EnclosureChassis` described below.
Class description:
Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources.
Method signatures and docstrings:
- def __init__(self, enclosure, enviro... | ffc86ea0a9e5d192ab6a2fe21c1717957b55d1da | <|skeleton|>
class EnclosureChassis:
"""Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources."""
def __init__(self, enclosure, environmental_configuration, manager_uuid):
"""Enclosure Chassis c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnclosureChassis:
"""Creates an Enclosure Chassis Redfish dict Populates self.redfish with some hardcoded Enclosure Chassis values and with the response of OneView enclosure resources."""
def __init__(self, enclosure, environmental_configuration, manager_uuid):
"""Enclosure Chassis constructor Po... | the_stack_v2_python_sparse | oneview_redfish_toolkit/api/enclosure_chassis.py | shobhit-sinha/oneview-redfish-toolkit | train | 2 |
c17a8bce2977f8585dcf4b55dbd0d230813bf14b | [
"self.audit_log_dest = audit_log_dest\nself.bct_file_path = bct_file_path\nself.control_file_path_vec = control_file_path_vec\nself.db_config_file_path = db_config_file_path\nself.diag_dest = diag_dest\nself.enable_archive_log_mode = enable_archive_log_mode\nself.fra_dest = fra_dest\nself.fra_size_mb = fra_size_mb\... | <|body_start_0|>
self.audit_log_dest = audit_log_dest
self.bct_file_path = bct_file_path
self.control_file_path_vec = control_file_path_vec
self.db_config_file_path = db_config_file_path
self.diag_dest = diag_dest
self.enable_archive_log_mode = enable_archive_log_mode
... | Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_path_vec (list of string): List of paths where the control file needs to be multip... | OracleDBConfig | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OracleDBConfig:
"""Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_path_vec (list of string): List of paths... | stack_v2_sparse_classes_36k_train_016741 | 5,676 | permissive | [
{
"docstring": "Constructor for the OracleDBConfig class",
"name": "__init__",
"signature": "def __init__(self, audit_log_dest=None, bct_file_path=None, control_file_path_vec=None, db_config_file_path=None, diag_dest=None, enable_archive_log_mode=None, fra_dest=None, fra_size_mb=None, num_tempfiles=None... | 2 | null | Implement the Python class `OracleDBConfig` described below.
Class description:
Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_p... | Implement the Python class `OracleDBConfig` described below.
Class description:
Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_p... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class OracleDBConfig:
"""Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_path_vec (list of string): List of paths... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OracleDBConfig:
"""Implementation of the 'OracleDBConfig' model. This proto captures the oracle database configuration for alternate DB restore. Attributes: audit_log_dest (string): Audit log destination. bct_file_path (string): BCT file path. control_file_path_vec (list of string): List of paths where the co... | the_stack_v2_python_sparse | cohesity_management_sdk/models/oracle_db_config.py | cohesity/management-sdk-python | train | 24 |
d8efa965b2c94d7618bd9fafe511a61f0614a385 | [
"if not filepath:\n raise Exception('ERROR: Invalid dataset path.')\nself.type = type\nself.filepath = filepath\nself.up_sites = up_sites\nself.down_sites = down_sites\nself.donor_site = []\nself.acceptor_site = []\nself.neg_donor_site = []\nself.neg_acceptor_site = []\nif self.type not in {'train', 'test'}:\n ... | <|body_start_0|>
if not filepath:
raise Exception('ERROR: Invalid dataset path.')
self.type = type
self.filepath = filepath
self.up_sites = up_sites
self.down_sites = down_sites
self.donor_site = []
self.acceptor_site = []
self.neg_donor_site =... | Sequence | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one seque... | stack_v2_sparse_classes_36k_train_016742 | 5,098 | no_license | [
{
"docstring": "All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one sequence each. type: str (one of \"train\", \"test\") Set the data type. Way of reading would be different. up_sites: int, d... | 4 | stack_v2_sparse_classes_30k_train_006427 | Implement the Python class `Sequence` described below.
Class description:
Implement the Sequence class.
Method signatures and docstrings:
- def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None: All kinds of splice site sequences for training. Parameters ---------- filepath:... | Implement the Python class `Sequence` described below.
Class description:
Implement the Sequence class.
Method signatures and docstrings:
- def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None: All kinds of splice site sequences for training. Parameters ---------- filepath:... | 3302ff7222d191f632695f0b9465ec2555f1b0af | <|skeleton|>
class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one seque... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sequence:
def __init__(self, filepath: str, type: str='train', up_sites: int=5, down_sites: int=5) -> None:
"""All kinds of splice site sequences for training. Parameters ---------- filepath: str or path-like The directory path of the dataset. Files in which are txts containing one sequence each. type... | the_stack_v2_python_sparse | Utils/extract.py | Newiz430/SplicePredictor | train | 1 | |
27030efc0c77340363f09947933f782e14d55a15 | [
"if not any((key.startswith('cat_') for key in kwargs.keys())):\n kwargs['cat_pattern'] = CAT_PATTERN\nCategorizedCorpusReader.__init__(self, kwargs)\nCorpusReader.__init__(self, root, fileids, encoding)\nself.tags = tags",
"if fileids is not None and categories is not None:\n raise ValueError('Specify file... | <|body_start_0|>
if not any((key.startswith('cat_') for key in kwargs.keys())):
kwargs['cat_pattern'] = CAT_PATTERN
CategorizedCorpusReader.__init__(self, kwargs)
CorpusReader.__init__(self, root, fileids, encoding)
self.tags = tags
<|end_body_0|>
<|body_start_1|>
if... | A corpus reader for raw HTML documents to enable preprocessing. | HTMLCorpusReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTMLCorpusReader:
"""A corpus reader for raw HTML documents to enable preprocessing."""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Initialize the corpus reader. Categorization arguments (``cat_pattern``, ``cat_map``, and ``cat_file``) are ... | stack_v2_sparse_classes_36k_train_016743 | 3,637 | permissive | [
{
"docstring": "Initialize the corpus reader. Categorization arguments (``cat_pattern``, ``cat_map``, and ``cat_file``) are passed to the ``CategorizedCorpusReader`` constructor. The remaining arguments are passed to the ``CorpusReader`` constructor.",
"name": "__init__",
"signature": "def __init__(self... | 4 | null | Implement the Python class `HTMLCorpusReader` described below.
Class description:
A corpus reader for raw HTML documents to enable preprocessing.
Method signatures and docstrings:
- def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs): Initialize the corpus reader. Categorization argume... | Implement the Python class `HTMLCorpusReader` described below.
Class description:
A corpus reader for raw HTML documents to enable preprocessing.
Method signatures and docstrings:
- def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs): Initialize the corpus reader. Categorization argume... | 43fd3317b641e0830905a734226afad3a0ea19f6 | <|skeleton|>
class HTMLCorpusReader:
"""A corpus reader for raw HTML documents to enable preprocessing."""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Initialize the corpus reader. Categorization arguments (``cat_pattern``, ``cat_map``, and ``cat_file``) are ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTMLCorpusReader:
"""A corpus reader for raw HTML documents to enable preprocessing."""
def __init__(self, root, fileids=DOC_PATTERN, encoding='utf8', tags=TAGS, **kwargs):
"""Initialize the corpus reader. Categorization arguments (``cat_pattern``, ``cat_map``, and ``cat_file``) are passed to the... | the_stack_v2_python_sparse | snippets/ch02/reader.py | foxbook/atap | train | 401 |
ca813c490d8b9b04f642140945bdb8fe6c8f1aeb | [
"content_type = ContentType.objects.get_for_model(instance.__class__)\nqueryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)\nreturn queryset",
"try:\n my_avg = self.filter_by_model(instance).aggregate(Avg('rating'))\nexcept ZeroDivisionError:\n logging.error(error_han... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(instance.__class__)
queryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)
return queryset
<|end_body_0|>
<|body_start_1|>
try:
my_avg = self.filter_by_model(instance).agg... | RateManager | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
<|body_0|>
def avg_rate(self, instance, avg=0):
"""emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dada... | stack_v2_sparse_classes_36k_train_016744 | 2,877 | permissive | [
{
"docstring": "filter kardane content bar assasse model",
"name": "filter_by_model",
"signature": "def filter_by_model(self, instance)"
},
{
"docstring": "emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dadan",
"name": "avg_... | 2 | stack_v2_sparse_classes_30k_train_004243 | Implement the Python class `RateManager` described below.
Class description:
Implement the RateManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): filter kardane content bar assasse model
- def avg_rate(self, instance, avg=0): emtiaz dehi be post bar assasse rate entekhab shude (az... | Implement the Python class `RateManager` described below.
Class description:
Implement the RateManager class.
Method signatures and docstrings:
- def filter_by_model(self, instance): filter kardane content bar assasse model
- def avg_rate(self, instance, avg=0): emtiaz dehi be post bar assasse rate entekhab shude (az... | aef47922fdd6488550881ed9d42bf30a0d33a32a | <|skeleton|>
class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
<|body_0|>
def avg_rate(self, instance, avg=0):
"""emtiaz dehi be post bar assasse rate entekhab shude (az 1 ta 5) taghsim bar tedad e user haey ke be in post emtiaz dada... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RateManager:
def filter_by_model(self, instance):
"""filter kardane content bar assasse model"""
content_type = ContentType.objects.get_for_model(instance.__class__)
queryset = super(RateManager, self).filter(content_type=content_type, object_id=instance.id)
return queryset
... | the_stack_v2_python_sparse | src/rates/models.py | m3h-D/Myinfoblog | train | 0 | |
93fd4d52773593a9dd25aa68a4c3e2c36261f1f6 | [
"self.source = None\nself.data = None\nself.size = size\nself.choice_source = []\nself.weight = np.array([])",
"self.source = data\nself.data = data\nself._handle_data_source()",
"if isinstance(self.source, list):\n self.data = self.source\n self.weight = np.array([])\nelif isinstance(self.source, dict):\... | <|body_start_0|>
self.source = None
self.data = None
self.size = size
self.choice_source = []
self.weight = np.array([])
<|end_body_0|>
<|body_start_1|>
self.source = data
self.data = data
self._handle_data_source()
<|end_body_1|>
<|body_start_2|>
... | randomChoice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class randomChoice:
def __init__(self, size: int=5):
"""随机选择类 外部参数: :param size:生成的数据量总数"""
<|body_0|>
def add(self, data: [List[Any], Dict]):
"""添加数据集 :param data: 数据集 :return:"""
<|body_1|>
def _handle_data_source(self):
"""处理数据源"""
<|body_2|... | stack_v2_sparse_classes_36k_train_016745 | 2,458 | no_license | [
{
"docstring": "随机选择类 外部参数: :param size:生成的数据量总数",
"name": "__init__",
"signature": "def __init__(self, size: int=5)"
},
{
"docstring": "添加数据集 :param data: 数据集 :return:",
"name": "add",
"signature": "def add(self, data: [List[Any], Dict])"
},
{
"docstring": "处理数据源",
"name": "... | 5 | stack_v2_sparse_classes_30k_train_017574 | Implement the Python class `randomChoice` described below.
Class description:
Implement the randomChoice class.
Method signatures and docstrings:
- def __init__(self, size: int=5): 随机选择类 外部参数: :param size:生成的数据量总数
- def add(self, data: [List[Any], Dict]): 添加数据集 :param data: 数据集 :return:
- def _handle_data_source(self... | Implement the Python class `randomChoice` described below.
Class description:
Implement the randomChoice class.
Method signatures and docstrings:
- def __init__(self, size: int=5): 随机选择类 外部参数: :param size:生成的数据量总数
- def add(self, data: [List[Any], Dict]): 添加数据集 :param data: 数据集 :return:
- def _handle_data_source(self... | a81c897e4481926daaafdbaf89d7087b793cd462 | <|skeleton|>
class randomChoice:
def __init__(self, size: int=5):
"""随机选择类 外部参数: :param size:生成的数据量总数"""
<|body_0|>
def add(self, data: [List[Any], Dict]):
"""添加数据集 :param data: 数据集 :return:"""
<|body_1|>
def _handle_data_source(self):
"""处理数据源"""
<|body_2|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class randomChoice:
def __init__(self, size: int=5):
"""随机选择类 外部参数: :param size:生成的数据量总数"""
self.source = None
self.data = None
self.size = size
self.choice_source = []
self.weight = np.array([])
def add(self, data: [List[Any], Dict]):
"""添加数据集 :param dat... | the_stack_v2_python_sparse | backend/maybe/patterns/random_choice.py | HalfLeaf/Maybe | train | 1 | |
1b0f74feca4f6fe4f71e4405f11880a178f4e31c | [
"self.check_authenticator_managed_groups()\ngroup = self.find_group(group_name)\ndata = self.get_json_body()\nself._check_group_model(data)\nif 'users' not in data:\n raise web.HTTPError(400, 'Must specify users to add')\nself.log.info('Adding %i users to group %s', len(data['users']), group_name)\nself.log.debu... | <|body_start_0|>
self.check_authenticator_managed_groups()
group = self.find_group(group_name)
data = self.get_json_body()
self._check_group_model(data)
if 'users' not in data:
raise web.HTTPError(400, 'Must specify users to add')
self.log.info('Adding %i user... | Modify a group's user list | GroupUsersAPIHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupUsersAPIHandler:
"""Modify a group's user list"""
def post(self, group_name):
"""POST adds users to a group"""
<|body_0|>
async def delete(self, group_name):
"""DELETE removes users from a group"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_016746 | 8,154 | permissive | [
{
"docstring": "POST adds users to a group",
"name": "post",
"signature": "def post(self, group_name)"
},
{
"docstring": "DELETE removes users from a group",
"name": "delete",
"signature": "async def delete(self, group_name)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016293 | Implement the Python class `GroupUsersAPIHandler` described below.
Class description:
Modify a group's user list
Method signatures and docstrings:
- def post(self, group_name): POST adds users to a group
- async def delete(self, group_name): DELETE removes users from a group | Implement the Python class `GroupUsersAPIHandler` described below.
Class description:
Modify a group's user list
Method signatures and docstrings:
- def post(self, group_name): POST adds users to a group
- async def delete(self, group_name): DELETE removes users from a group
<|skeleton|>
class GroupUsersAPIHandler:
... | 7757dea8a463e75d8a540e85deee45c1635dd273 | <|skeleton|>
class GroupUsersAPIHandler:
"""Modify a group's user list"""
def post(self, group_name):
"""POST adds users to a group"""
<|body_0|>
async def delete(self, group_name):
"""DELETE removes users from a group"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupUsersAPIHandler:
"""Modify a group's user list"""
def post(self, group_name):
"""POST adds users to a group"""
self.check_authenticator_managed_groups()
group = self.find_group(group_name)
data = self.get_json_body()
self._check_group_model(data)
if 'u... | the_stack_v2_python_sparse | jupyterhub/apihandlers/groups.py | jupyterhub/jupyterhub | train | 6,751 |
1aa9346fa138c7829dddd1202f8af83899087106 | [
"try:\n return_data = ''\n return Response(json.dumps(return_data))\nexcept Exception as e:\n return_data = {'status': '404', 'result': str(e)}\n return Response(json.dumps(return_data))",
"try:\n return_data = ''\n if type == 'log':\n return_data = RunManagerMoniter().get_view_obj_log(id... | <|body_start_0|>
try:
return_data = ''
return Response(json.dumps(return_data))
except Exception as e:
return_data = {'status': '404', 'result': str(e)}
return Response(json.dumps(return_data))
<|end_body_0|>
<|body_start_1|>
try:
retu... | RunManagerCelery | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunManagerCelery:
def post(self, request, nnid):
"""CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet)"""
<|body_0|>
def get(self, request, type, id, line):
"""CRUD of workflow informat... | stack_v2_sparse_classes_36k_train_016747 | 2,345 | permissive | [
{
"docstring": "CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet)",
"name": "post",
"signature": "def post(self, request, nnid)"
},
{
"docstring": "CRUD of workflow information --- # Class Name : RunManagerWorkFlo... | 4 | stack_v2_sparse_classes_30k_test_000510 | Implement the Python class `RunManagerCelery` described below.
Class description:
Implement the RunManagerCelery class.
Method signatures and docstrings:
- def post(self, request, nnid): CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet... | Implement the Python class `RunManagerCelery` described below.
Class description:
Implement the RunManagerCelery class.
Method signatures and docstrings:
- def post(self, request, nnid): CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet... | 6ad2fbc7384e4dbe7e3e63bdb44c8ce0387f4b7f | <|skeleton|>
class RunManagerCelery:
def post(self, request, nnid):
"""CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet)"""
<|body_0|>
def get(self, request, type, id, line):
"""CRUD of workflow informat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RunManagerCelery:
def post(self, request, nnid):
"""CRUD of workflow information --- # Class Name : RunManagerWorkFlow # Description: CRUD of workflow information (not implemented yet)"""
try:
return_data = ''
return Response(json.dumps(return_data))
except Exce... | the_stack_v2_python_sparse | api/views/runmanager_celery.py | yurimkoo/tensormsa | train | 1 | |
1a75e952d9d3e270051b2c7f7aae701f30d74a93 | [
"self.base_filters = filters or []\nself.polling_interval = polling_interval\nself.continue_interval = continue_interval or polling_interval\nself.should_continue = continue_func\nstart_timestamp = _GetTailStartingTimestamp(filters, num_prev_entries)\nlog.debug('start timestamp: {}'.format(start_timestamp))\nself.l... | <|body_start_0|>
self.base_filters = filters or []
self.polling_interval = polling_interval
self.continue_interval = continue_interval or polling_interval
self.should_continue = continue_func
start_timestamp = _GetTailStartingTimestamp(filters, num_prev_entries)
log.debug... | A class which fetches job logs. | LogFetcher | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogFetcher:
"""A class which fetches job logs."""
def __init__(self, filters=None, polling_interval=10, continue_func=lambda x: True, continue_interval=None, num_prev_entries=None):
"""Initializes the LogFetcher. Args: filters: list of string filters used in the API call. polling_int... | stack_v2_sparse_classes_36k_train_016748 | 9,319 | permissive | [
{
"docstring": "Initializes the LogFetcher. Args: filters: list of string filters used in the API call. polling_interval: amount of time to sleep between each poll. continue_func: One-arg function that takes in the number of empty polls and outputs a boolean to decide if we should keep polling or not. If not gi... | 3 | stack_v2_sparse_classes_30k_train_014302 | Implement the Python class `LogFetcher` described below.
Class description:
A class which fetches job logs.
Method signatures and docstrings:
- def __init__(self, filters=None, polling_interval=10, continue_func=lambda x: True, continue_interval=None, num_prev_entries=None): Initializes the LogFetcher. Args: filters:... | Implement the Python class `LogFetcher` described below.
Class description:
A class which fetches job logs.
Method signatures and docstrings:
- def __init__(self, filters=None, polling_interval=10, continue_func=lambda x: True, continue_interval=None, num_prev_entries=None): Initializes the LogFetcher. Args: filters:... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class LogFetcher:
"""A class which fetches job logs."""
def __init__(self, filters=None, polling_interval=10, continue_func=lambda x: True, continue_interval=None, num_prev_entries=None):
"""Initializes the LogFetcher. Args: filters: list of string filters used in the API call. polling_int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogFetcher:
"""A class which fetches job logs."""
def __init__(self, filters=None, polling_interval=10, continue_func=lambda x: True, continue_interval=None, num_prev_entries=None):
"""Initializes the LogFetcher. Args: filters: list of string filters used in the API call. polling_interval: amount... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/command_lib/logs/stream.py | bopopescu/socialliteapp | train | 0 |
2db7ed8951cad880e828dbb04b7ad6d53582d307 | [
"super(DQNBase, self).__init__()\nencoder_kwargs, lstm_kwargs, head_kwargs = get_kwargs(kwargs)\nself._encoder = Encoder(obs_dim, embedding_dim, **encoder_kwargs)\nif lstm_kwargs['lstm_type'] != 'none':\n lstm_kwargs['input_size'] = embedding_dim\n lstm_kwargs['hidden_size'] = embedding_dim\n self._lstm = ... | <|body_start_0|>
super(DQNBase, self).__init__()
encoder_kwargs, lstm_kwargs, head_kwargs = get_kwargs(kwargs)
self._encoder = Encoder(obs_dim, embedding_dim, **encoder_kwargs)
if lstm_kwargs['lstm_type'] != 'none':
lstm_kwargs['input_size'] = embedding_dim
lstm_k... | Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward | DQNBase | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DQNBase:
"""Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward"""
def __init__(self, obs_dim: Union[int, tuple], action_dim: tuple, embedding_dim: int=64, **kwargs) -> None:
"""Overview: Init the DQNBase according to arguments, including en... | stack_v2_sparse_classes_36k_train_016749 | 9,851 | permissive | [
{
"docstring": "Overview: Init the DQNBase according to arguments, including encoder, lstm(if needed) and head. Arguments: - obs_dim (:obj:`Union[int, tuple]`): a tuple of observation dim - action_dim (:obj:`int`): the num of action dim, \\\\ note that it can be a tuple containing more than one element - embedd... | 3 | stack_v2_sparse_classes_30k_train_004912 | Implement the Python class `DQNBase` described below.
Class description:
Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward
Method signatures and docstrings:
- def __init__(self, obs_dim: Union[int, tuple], action_dim: tuple, embedding_dim: int=64, **kwargs) -> None: Overvi... | Implement the Python class `DQNBase` described below.
Class description:
Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward
Method signatures and docstrings:
- def __init__(self, obs_dim: Union[int, tuple], action_dim: tuple, embedding_dim: int=64, **kwargs) -> None: Overvi... | 09d507c412235a2f0cf9c0b3485ec9ed15fb6421 | <|skeleton|>
class DQNBase:
"""Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward"""
def __init__(self, obs_dim: Union[int, tuple], action_dim: tuple, embedding_dim: int=64, **kwargs) -> None:
"""Overview: Init the DQNBase according to arguments, including en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DQNBase:
"""Overview: Base class for DQN based models. Interface: __init__, forward, fast_timestep_forward"""
def __init__(self, obs_dim: Union[int, tuple], action_dim: tuple, embedding_dim: int=64, **kwargs) -> None:
"""Overview: Init the DQNBase according to arguments, including encoder, lstm(i... | the_stack_v2_python_sparse | ctools/model/dqn/dqn_network.py | LFhase/DI-star | train | 1 |
15e4ab9e27e989001f959e55b15fea2a585346ff | [
"numsLen = len(nums)\nfor i in range(numsLen):\n while nums[i] < i + 1 and nums[i] > 0 and (nums[i] != nums[nums[i] - 1]):\n temp = nums[nums[i] - 1]\n nums[nums[i] - 1] = nums[i]\n nums[i] = temp\nfor i in range(numsLen):\n if nums[i] != i + 1:\n return i + 1\nreturn numsLen + 1",... | <|body_start_0|>
numsLen = len(nums)
for i in range(numsLen):
while nums[i] < i + 1 and nums[i] > 0 and (nums[i] != nums[nums[i] - 1]):
temp = nums[nums[i] - 1]
nums[nums[i] - 1] = nums[i]
nums[i] = temp
for i in range(numsLen):
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)"""
<|body_0|>
def firstMissingPositiveFast(self, nums):
""":type nums: List[int] :rtype: int 简单易懂且高效 O(n)"""
<|body_1... | stack_v2_sparse_classes_36k_train_016750 | 1,822 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)",
"name": "firstMissingPositive",
"signature": "def firstMissingPositive(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int 简单易懂且高效 O(n)",
"name": "firstMissingPositiveFa... | 2 | stack_v2_sparse_classes_30k_train_018556 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)
- def firstMissingPositiveFast(self, nums): :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def firstMissingPositive(self, nums): :type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)
- def firstMissingPositiveFast(self, nums): :type... | 9f49766a2b375a6c65f7bfa96df513875ddd772d | <|skeleton|>
class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)"""
<|body_0|>
def firstMissingPositiveFast(self, nums):
""":type nums: List[int] :rtype: int 简单易懂且高效 O(n)"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def firstMissingPositive(self, nums):
""":type nums: List[int] :rtype: int 根据正整数数组的特性, 在原数组的空间上做一次排序, 然后根据索引和值之间的关系得到结果 O(n) & O(k)"""
numsLen = len(nums)
for i in range(numsLen):
while nums[i] < i + 1 and nums[i] > 0 and (nums[i] != nums[nums[i] - 1]):
... | the_stack_v2_python_sparse | Leetcode/41.firstMissingPositive.py | Song2017/Leetcode_python | train | 1 | |
92f9e438254e9ca051e276306f955c51c96eeae1 | [
"A = expand(root)\nA.append(val)\nreturn self.constructMaximumBinaryTree(A)",
"if len(nums) == 0:\n return None\nif len(nums) == 1:\n return TreeNode(nums[0])\nmaxn = 0\nmaxi = -1\nfor i in range(len(nums)):\n if nums[i] > maxn:\n maxi = i\n maxn = nums[i]\nroot = TreeNode(maxn)\nroot.left ... | <|body_start_0|>
A = expand(root)
A.append(val)
return self.constructMaximumBinaryTree(A)
<|end_body_0|>
<|body_start_1|>
if len(nums) == 0:
return None
if len(nums) == 1:
return TreeNode(nums[0])
maxn = 0
maxi = -1
for i in range(... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def insertIntoMaxTree(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
<|body_0|>
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_016751 | 1,283 | no_license | [
{
"docstring": ":type root: TreeNode :type val: int :rtype: TreeNode",
"name": "insertIntoMaxTree",
"signature": "def insertIntoMaxTree(self, root, val)"
},
{
"docstring": ":type nums: List[int] :rtype: TreeNode",
"name": "constructMaximumBinaryTree",
"signature": "def constructMaximumBi... | 2 | stack_v2_sparse_classes_30k_train_016137 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insertIntoMaxTree(self, root, val): :type root: TreeNode :type val: int :rtype: TreeNode
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insertIntoMaxTree(self, root, val): :type root: TreeNode :type val: int :rtype: TreeNode
- def constructMaximumBinaryTree(self, nums): :type nums: List[int] :rtype: TreeNode
... | 70f16a872cb203f77eeddb812e734ad1d46df79d | <|skeleton|>
class Solution:
def insertIntoMaxTree(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
<|body_0|>
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def insertIntoMaxTree(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
A = expand(root)
A.append(val)
return self.constructMaximumBinaryTree(A)
def constructMaximumBinaryTree(self, nums):
""":type nums: List[int] :rtype: TreeNo... | the_stack_v2_python_sparse | maximum-binary-tree-2.py | cannium/leetcode | train | 0 | |
0eb3fcd0d702d496a3a4fae9768d297b8e4949ee | [
"self.ev = ev\nself.weight = weight.weight()\nself.output = output\nself.selection = None\nself.addRow('entry', ak.ones_like(self.weight) == 1)",
"if self.selection is None and selection is not None:\n self.selection = selection\nelif selection is not None and cumulative == False:\n selection = self.selecti... | <|body_start_0|>
self.ev = ev
self.weight = weight.weight()
self.output = output
self.selection = None
self.addRow('entry', ak.ones_like(self.weight) == 1)
<|end_body_0|>
<|body_start_1|>
if self.selection is None and selection is not None:
self.selection = s... | Cutflow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cutflow:
def __init__(self, output, ev, weight, selection=None):
"""output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object"""
<|body_0|>
def addRow(self, name, selection, cumulative=True):
"""If cumulative is set to False, the cut w... | stack_v2_sparse_classes_36k_train_016752 | 1,472 | no_license | [
{
"docstring": "output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object",
"name": "__init__",
"signature": "def __init__(self, output, ev, weight, selection=None)"
},
{
"docstring": "If cumulative is set to False, the cut will not be added to self.selection",
... | 2 | stack_v2_sparse_classes_30k_train_016216 | Implement the Python class `Cutflow` described below.
Class description:
Implement the Cutflow class.
Method signatures and docstrings:
- def __init__(self, output, ev, weight, selection=None): output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object
- def addRow(self, name, selection... | Implement the Python class `Cutflow` described below.
Class description:
Implement the Cutflow class.
Method signatures and docstrings:
- def __init__(self, output, ev, weight, selection=None): output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object
- def addRow(self, name, selection... | e3b335c2e9a0dcb9e08ef56a2546dd7f40d276ba | <|skeleton|>
class Cutflow:
def __init__(self, output, ev, weight, selection=None):
"""output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object"""
<|body_0|>
def addRow(self, name, selection, cumulative=True):
"""If cumulative is set to False, the cut w... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cutflow:
def __init__(self, output, ev, weight, selection=None):
"""output: the accumulator object ev: NanoEvent weight: coffea analysis_tools Weights object"""
self.ev = ev
self.weight = weight.weight()
self.output = output
self.selection = None
self.addRow('en... | the_stack_v2_python_sparse | analysis/Tools/cutflow.py | danbarto/tW_scattering | train | 0 | |
b81b6ef019de45edc91a029c6ff65c4e0be8ac5c | [
"if len(result.affected_code) == 0:\n return 'The result is not associated with any source code.'\nfilenames = set((src.renamed_file(file_diff_dict) for src in result.affected_code))\nif any((exists(filename) for filename in filenames)):\n return True\nreturn \"The result is associated with source code that d... | <|body_start_0|>
if len(result.affected_code) == 0:
return 'The result is not associated with any source code.'
filenames = set((src.renamed_file(file_diff_dict) for src in result.affected_code))
if any((exists(filename) for filename in filenames)):
return True
re... | IgnoreResultAction | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IgnoreResultAction:
def is_applicable(result: Result, original_file_dict, file_diff_dict):
"""For being applicable, the result has to point to a number of files that have to exist i.e. have not been previously deleted."""
<|body_0|>
def apply(self, result, original_file_dict... | stack_v2_sparse_classes_36k_train_016753 | 4,109 | no_license | [
{
"docstring": "For being applicable, the result has to point to a number of files that have to exist i.e. have not been previously deleted.",
"name": "is_applicable",
"signature": "def is_applicable(result: Result, original_file_dict, file_diff_dict)"
},
{
"docstring": "Add ignore comment",
... | 3 | stack_v2_sparse_classes_30k_train_021396 | Implement the Python class `IgnoreResultAction` described below.
Class description:
Implement the IgnoreResultAction class.
Method signatures and docstrings:
- def is_applicable(result: Result, original_file_dict, file_diff_dict): For being applicable, the result has to point to a number of files that have to exist i... | Implement the Python class `IgnoreResultAction` described below.
Class description:
Implement the IgnoreResultAction class.
Method signatures and docstrings:
- def is_applicable(result: Result, original_file_dict, file_diff_dict): For being applicable, the result has to point to a number of files that have to exist i... | d494b3041069d377d6a7a9c296a14334f2fa5acc | <|skeleton|>
class IgnoreResultAction:
def is_applicable(result: Result, original_file_dict, file_diff_dict):
"""For being applicable, the result has to point to a number of files that have to exist i.e. have not been previously deleted."""
<|body_0|>
def apply(self, result, original_file_dict... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IgnoreResultAction:
def is_applicable(result: Result, original_file_dict, file_diff_dict):
"""For being applicable, the result has to point to a number of files that have to exist i.e. have not been previously deleted."""
if len(result.affected_code) == 0:
return 'The result is not... | the_stack_v2_python_sparse | python/coala_coala/coala-master/coalib/results/result_actions/IgnoreResultAction.py | LiuFang816/SALSTM_py_data | train | 10 | |
152021b92f91f4c156ede394ffa98af52bf571a5 | [
"lmodel = LangModel(logfile='lmwrap.log')\nnbest = 1.6\nwith self.assertRaises(NBestError) as er:\n lmodel.init(nbest=nbest)",
"lmodel = LangModel(logfile='lmwrap.log')\nnbest = 2\nlmodel.init(nbest=nbest)\nevidence = ['t']\nreturn_mode = 'letter'\nwith self.assertRaises(EvidenceDataStructError) as er:\n lm... | <|body_start_0|>
lmodel = LangModel(logfile='lmwrap.log')
nbest = 1.6
with self.assertRaises(NBestError) as er:
lmodel.init(nbest=nbest)
<|end_body_0|>
<|body_start_1|>
lmodel = LangModel(logfile='lmwrap.log')
nbest = 2
lmodel.init(nbest=nbest)
eviden... | TestOCLM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestOCLM:
def test_incorrect_nbest(self):
"""confirm an assertion error as the provided nbest arg is invalid"""
<|body_0|>
def test_incorrect_evidence(self):
"""confirm the process provides an error given an incorrect input"""
<|body_1|>
def test_valid_o... | stack_v2_sparse_classes_36k_train_016754 | 1,832 | permissive | [
{
"docstring": "confirm an assertion error as the provided nbest arg is invalid",
"name": "test_incorrect_nbest",
"signature": "def test_incorrect_nbest(self)"
},
{
"docstring": "confirm the process provides an error given an incorrect input",
"name": "test_incorrect_evidence",
"signatur... | 3 | null | Implement the Python class `TestOCLM` described below.
Class description:
Implement the TestOCLM class.
Method signatures and docstrings:
- def test_incorrect_nbest(self): confirm an assertion error as the provided nbest arg is invalid
- def test_incorrect_evidence(self): confirm the process provides an error given a... | Implement the Python class `TestOCLM` described below.
Class description:
Implement the TestOCLM class.
Method signatures and docstrings:
- def test_incorrect_nbest(self): confirm an assertion error as the provided nbest arg is invalid
- def test_incorrect_evidence(self): confirm the process provides an error given a... | 397ce67c15a9e84d8a6c13f621fad3cf6b62df2e | <|skeleton|>
class TestOCLM:
def test_incorrect_nbest(self):
"""confirm an assertion error as the provided nbest arg is invalid"""
<|body_0|>
def test_incorrect_evidence(self):
"""confirm the process provides an error given an incorrect input"""
<|body_1|>
def test_valid_o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestOCLM:
def test_incorrect_nbest(self):
"""confirm an assertion error as the provided nbest arg is invalid"""
lmodel = LangModel(logfile='lmwrap.log')
nbest = 1.6
with self.assertRaises(NBestError) as er:
lmodel.init(nbest=nbest)
def test_incorrect_evidence(s... | the_stack_v2_python_sparse | bcipy/language_model/integration/oclm_itest.py | nik-sm/BciPy | train | 0 | |
227b67acc3af1459d1f52eb6dea52e39782e2e39 | [
"if not root:\n return None\nif key > root.val:\n root.right = self.deleteNode(root.right, key)\nelif key < root.val:\n root.left = self.deleteNode(root.left, key)\nelif not root.left and (not root.right):\n root = None\nelif root.right:\n root.val = self.successor(root)\n root.right = self.delete... | <|body_start_0|>
if not root:
return None
if key > root.val:
root.right = self.deleteNode(root.right, key)
elif key < root.val:
root.left = self.deleteNode(root.left, key)
elif not root.left and (not root.right):
root = None
elif ro... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""One step right and then always left"""
<|body_1|>
def predecessor(self, root):
"""One step left and the... | stack_v2_sparse_classes_36k_train_016755 | 2,749 | no_license | [
{
"docstring": ":type root: TreeNode :type key: int :rtype: TreeNode",
"name": "deleteNode",
"signature": "def deleteNode(self, root, key)"
},
{
"docstring": "One step right and then always left",
"name": "successor",
"signature": "def successor(self, root)"
},
{
"docstring": "On... | 3 | stack_v2_sparse_classes_30k_train_002555 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): One step right and then always left
- def predecessor(self, roo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): One step right and then always left
- def predecessor(self, roo... | 90c000c3be70727cde4f7494fbbb1c425bfd3da4 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""One step right and then always left"""
<|body_1|>
def predecessor(self, root):
"""One step left and the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
if not root:
return None
if key > root.val:
root.right = self.deleteNode(root.right, key)
elif key < root.val:
root.left = self.deleteNode(r... | the_stack_v2_python_sparse | 450.delete-node-in-a-bst.py | chenjienan/python-leetcode | train | 16 | |
f6e5903a736af89c2246a2e369ceba279cdd0b0b | [
"x, y = (point[0], point[1])\nif neb_num == 8:\n return [(x - 1, y - 1), (x, y - 1), (x - 1, y), (x + 1, y), (x, y + 1), (x + 1, y + 1), (x + 1, y - 1), (x - 1, y + 1)]\nelif neb_num == 4:\n return [(x, y - 1), (x - 1, y), (x + 1, y), (x, y + 1)]\nelse:\n raise ValueError('neb_num can only be int 4 or 8')"... | <|body_start_0|>
x, y = (point[0], point[1])
if neb_num == 8:
return [(x - 1, y - 1), (x, y - 1), (x - 1, y), (x + 1, y), (x, y + 1), (x + 1, y + 1), (x + 1, y - 1), (x - 1, y + 1)]
elif neb_num == 4:
return [(x, y - 1), (x - 1, y), (x + 1, y), (x, y + 1)]
else:
... | 广度遍历得到斑块 | GetPlaque | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetPlaque:
"""广度遍历得到斑块"""
def __get_neb(point, neb_num=8):
"""4 邻接"""
<|body_0|>
def get_plaque_index_data(point_mat, ban_all):
"""获取斑块的 index 矩阵，每一个斑块获取一个唯一的 index"""
<|body_1|>
def get_plaque(point_mat, neb_num=8):
"""获取斑块"""
<|body... | stack_v2_sparse_classes_36k_train_016756 | 2,943 | no_license | [
{
"docstring": "4 邻接",
"name": "__get_neb",
"signature": "def __get_neb(point, neb_num=8)"
},
{
"docstring": "获取斑块的 index 矩阵，每一个斑块获取一个唯一的 index",
"name": "get_plaque_index_data",
"signature": "def get_plaque_index_data(point_mat, ban_all)"
},
{
"docstring": "获取斑块",
"name": "g... | 3 | null | Implement the Python class `GetPlaque` described below.
Class description:
广度遍历得到斑块
Method signatures and docstrings:
- def __get_neb(point, neb_num=8): 4 邻接
- def get_plaque_index_data(point_mat, ban_all): 获取斑块的 index 矩阵，每一个斑块获取一个唯一的 index
- def get_plaque(point_mat, neb_num=8): 获取斑块 | Implement the Python class `GetPlaque` described below.
Class description:
广度遍历得到斑块
Method signatures and docstrings:
- def __get_neb(point, neb_num=8): 4 邻接
- def get_plaque_index_data(point_mat, ban_all): 获取斑块的 index 矩阵，每一个斑块获取一个唯一的 index
- def get_plaque(point_mat, neb_num=8): 获取斑块
<|skeleton|>
class GetPlaque:
... | 32e64be10a6cd2856850f6720d70b4c6e7033f4e | <|skeleton|>
class GetPlaque:
"""广度遍历得到斑块"""
def __get_neb(point, neb_num=8):
"""4 邻接"""
<|body_0|>
def get_plaque_index_data(point_mat, ban_all):
"""获取斑块的 index 矩阵，每一个斑块获取一个唯一的 index"""
<|body_1|>
def get_plaque(point_mat, neb_num=8):
"""获取斑块"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetPlaque:
"""广度遍历得到斑块"""
def __get_neb(point, neb_num=8):
"""4 邻接"""
x, y = (point[0], point[1])
if neb_num == 8:
return [(x - 1, y - 1), (x, y - 1), (x - 1, y), (x + 1, y), (x, y + 1), (x + 1, y + 1), (x + 1, y - 1), (x - 1, y + 1)]
elif neb_num == 4:
... | the_stack_v2_python_sparse | Algo/BFS/GetPlaque.py | newjokker/PyUtil | train | 0 |
ebe141539dd6d2314dc63c5d9450aed1333338c3 | [
"parser = super(GenericRequest, self).get_parser(prog_name)\nparser.add_argument('-m', '--method', choices=self.app.workspace.config.ALL_METHODS, help='override query method')\nparser.add_argument('-k', '--kwargs', type=lambda x: dict(yaml.safe_load(x)), help='payload/params to send. format is yaml')\nparser.add_ar... | <|body_start_0|>
parser = super(GenericRequest, self).get_parser(prog_name)
parser.add_argument('-m', '--method', choices=self.app.workspace.config.ALL_METHODS, help='override query method')
parser.add_argument('-k', '--kwargs', type=lambda x: dict(yaml.safe_load(x)), help='payload/params to sen... | The generic request class for all requests | GenericRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericRequest:
"""The generic request class for all requests"""
def get_parser(self, prog_name):
"""Overriding parent method"""
<|body_0|>
def get_request(self, method, site_id, endpoint_id, args):
"""Get the request object"""
<|body_1|>
def update_... | stack_v2_sparse_classes_36k_train_016757 | 3,998 | permissive | [
{
"docstring": "Overriding parent method",
"name": "get_parser",
"signature": "def get_parser(self, prog_name)"
},
{
"docstring": "Get the request object",
"name": "get_request",
"signature": "def get_request(self, method, site_id, endpoint_id, args)"
},
{
"docstring": "Update th... | 4 | stack_v2_sparse_classes_30k_train_009007 | Implement the Python class `GenericRequest` described below.
Class description:
The generic request class for all requests
Method signatures and docstrings:
- def get_parser(self, prog_name): Overriding parent method
- def get_request(self, method, site_id, endpoint_id, args): Get the request object
- def update_requ... | Implement the Python class `GenericRequest` described below.
Class description:
The generic request class for all requests
Method signatures and docstrings:
- def get_parser(self, prog_name): Overriding parent method
- def get_request(self, method, site_id, endpoint_id, args): Get the request object
- def update_requ... | f65fc86163c25f843a94341f09b20db28c1511d7 | <|skeleton|>
class GenericRequest:
"""The generic request class for all requests"""
def get_parser(self, prog_name):
"""Overriding parent method"""
<|body_0|>
def get_request(self, method, site_id, endpoint_id, args):
"""Get the request object"""
<|body_1|>
def update_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenericRequest:
"""The generic request class for all requests"""
def get_parser(self, prog_name):
"""Overriding parent method"""
parser = super(GenericRequest, self).get_parser(prog_name)
parser.add_argument('-m', '--method', choices=self.app.workspace.config.ALL_METHODS, help='ov... | the_stack_v2_python_sparse | resteasycli/cmd/generic_request.py | sayanarijit/RESTEasyCLI | train | 1 |
4543fe908c8f40c729c61d69fbff56f825d7bfc6 | [
"host = get_live_server_host()\nport = get_live_server_port()\nasync with websockets.serve(self.handler, host, port):\n await self.bus.run()",
"channel_id = path.split('/')[-2]\nchannel_name = make_channel_group_name(channel_id)\nawait self.bus.subscribe(channel_name, websocket)\ntry:\n await websocket.wait... | <|body_start_0|>
host = get_live_server_host()
port = get_live_server_port()
async with websockets.serve(self.handler, host, port):
await self.bus.run()
<|end_body_0|>
<|body_start_1|>
channel_id = path.split('/')[-2]
channel_name = make_channel_group_name(channel_id... | WebsocketsPublisherApp | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
<|body_0|>
async def handler(self, websocket, path):
"""Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id fo... | stack_v2_sparse_classes_36k_train_016758 | 1,271 | permissive | [
{
"docstring": "Called once per session.",
"name": "__call__",
"signature": "async def __call__(self)"
},
{
"docstring": "Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id found in the request's path.",
"name": "ha... | 2 | stack_v2_sparse_classes_30k_train_014811 | Implement the Python class `WebsocketsPublisherApp` described below.
Class description:
Implement the WebsocketsPublisherApp class.
Method signatures and docstrings:
- async def __call__(self): Called once per session.
- async def handler(self, websocket, path): Called once per new connection. Adds/removes the websoc... | Implement the Python class `WebsocketsPublisherApp` described below.
Class description:
Implement the WebsocketsPublisherApp class.
Method signatures and docstrings:
- async def __call__(self): Called once per session.
- async def handler(self, websocket, path): Called once per new connection. Adds/removes the websoc... | dd769be089d457cf36db2506520028bc5f506ac3 | <|skeleton|>
class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
<|body_0|>
async def handler(self, websocket, path):
"""Called once per new connection. Adds/removes the websocket connection to/from the channel group corresponding to the channel id fo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WebsocketsPublisherApp:
async def __call__(self):
"""Called once per session."""
host = get_live_server_host()
port = get_live_server_port()
async with websockets.serve(self.handler, host, port):
await self.bus.run()
async def handler(self, websocket, path):
... | the_stack_v2_python_sparse | src/wagtail_live/publishers/websockets/app.py | 7saikat7/wagtail-live | train | 0 | |
81d5db8a0a780bde548e2ffd96bb277224830dea | [
"x = 2\nit = power_of(x)\nfor index in xrange(101):\n self.assertEqual(it.next(), pow(x, index))",
"x = 3\nit = power_of(x)\nfor index in xrange(1001):\n self.assertEqual(it.next(), pow(x, index))",
"x = 7\nit = power_of(x)\nfor index in xrange(10001):\n self.assertEqual(it.next(), pow(x, index))"
] | <|body_start_0|>
x = 2
it = power_of(x)
for index in xrange(101):
self.assertEqual(it.next(), pow(x, index))
<|end_body_0|>
<|body_start_1|>
x = 3
it = power_of(x)
for index in xrange(1001):
self.assertEqual(it.next(), pow(x, index))
<|end_body_1|... | TestPowerOf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestPowerOf:
def test_power_of_2(self):
"""Test power_of(2) until 100"""
<|body_0|>
def test_power_of_3(self):
"""Test power_of(3) until 1000"""
<|body_1|>
def test_power_of_7(self):
"""Test power_of(7) until 10000"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k_train_016759 | 1,221 | no_license | [
{
"docstring": "Test power_of(2) until 100",
"name": "test_power_of_2",
"signature": "def test_power_of_2(self)"
},
{
"docstring": "Test power_of(3) until 1000",
"name": "test_power_of_3",
"signature": "def test_power_of_3(self)"
},
{
"docstring": "Test power_of(7) until 10000",
... | 3 | null | Implement the Python class `TestPowerOf` described below.
Class description:
Implement the TestPowerOf class.
Method signatures and docstrings:
- def test_power_of_2(self): Test power_of(2) until 100
- def test_power_of_3(self): Test power_of(3) until 1000
- def test_power_of_7(self): Test power_of(7) until 10000 | Implement the Python class `TestPowerOf` described below.
Class description:
Implement the TestPowerOf class.
Method signatures and docstrings:
- def test_power_of_2(self): Test power_of(2) until 100
- def test_power_of_3(self): Test power_of(3) until 1000
- def test_power_of_7(self): Test power_of(7) until 10000
<|... | 8f082201e24f0f2b991d9388500fdbf95d6f073d | <|skeleton|>
class TestPowerOf:
def test_power_of_2(self):
"""Test power_of(2) until 100"""
<|body_0|>
def test_power_of_3(self):
"""Test power_of(3) until 1000"""
<|body_1|>
def test_power_of_7(self):
"""Test power_of(7) until 10000"""
<|body_2|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestPowerOf:
def test_power_of_2(self):
"""Test power_of(2) until 100"""
x = 2
it = power_of(x)
for index in xrange(101):
self.assertEqual(it.next(), pow(x, index))
def test_power_of_3(self):
"""Test power_of(3) until 1000"""
x = 3
it = ... | the_stack_v2_python_sparse | advanced/exercises/mod_05_functools/tests_mod_05.py | garciacastano09/pycourse | train | 0 | |
2c0df9f03df95ff3c29592068e1eeef99b056058 | [
"self.config_instance = config_instance\nself.exp_time = self.config_instance.config_file['credentials']['exp_time']\nif unit_test:\n sys.path.append('./')\nself.authentication_method = self.config_instance.config_file['credentials']['authentication_method']\nself.inf_renew_time = inf_renew_time\nself.unit_test ... | <|body_start_0|>
self.config_instance = config_instance
self.exp_time = self.config_instance.config_file['credentials']['exp_time']
if unit_test:
sys.path.append('./')
self.authentication_method = self.config_instance.config_file['credentials']['authentication_method']
... | Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API calls as those credentials. | CredCache | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CredCache:
"""Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API calls as those credentials."""
def... | stack_v2_sparse_classes_36k_train_016760 | 7,720 | permissive | [
{
"docstring": "Constructs a new credential cache. Inputs: config_instance: instance of Config inf_renew_time: the that each credential is renewed (seconds) unit_test: boolean indicating a unit-test is being run.",
"name": "__init__",
"signature": "def __init__(self, config_instance, inf_renew_time, uni... | 4 | stack_v2_sparse_classes_30k_train_006119 | Implement the Python class `CredCache` described below.
Class description:
Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API ... | Implement the Python class `CredCache` described below.
Class description:
Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API ... | 794b24a84cdc71067f709fcd48b9312c5847af31 | <|skeleton|>
class CredCache:
"""Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API calls as those credentials."""
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CredCache:
"""Credentials cache for XMLRPC services. Authenticated users are given a time-limited credential. Credentials map to Core instances, and can be used for repeated calls from a client. CredCaches also handle verifying credentials, and invoking API calls as those credentials."""
def __init__(sel... | the_stack_v2_python_sparse | roster-server/roster_server/credentials.py | BackupGGCode/roster-dns-management | train | 0 |
dc6b309a620b69181fb8544edb56021db5bbebf7 | [
"self.hash_map = collections.defaultdict(list)\nfor i in range(len(nums)):\n self.hash_map[nums[i]].append(i)",
"if target in self.hash_map:\n len_list = len(self.hash_map[target])\n r = random.randrange(len_list)\n return self.hash_map[target][r]\nreturn -1"
] | <|body_start_0|>
self.hash_map = collections.defaultdict(list)
for i in range(len(nums)):
self.hash_map[nums[i]].append(i)
<|end_body_0|>
<|body_start_1|>
if target in self.hash_map:
len_list = len(self.hash_map[target])
r = random.randrange(len_list)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.hash_map = collections.defaultdict(list)
for i in range(... | stack_v2_sparse_classes_36k_train_016761 | 735 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": ":type target: int :rtype: int",
"name": "pick",
"signature": "def pick(self, target)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def pick(self, target): :type target: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def pick(self, target): :type target: int :rtype: int
<|skeleton|>
class Solution:
def __init__(self, nums):
""":t... | f05aac9aeadec1febe4c8323849c0a9f07a1fd1c | <|skeleton|>
class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def pick(self, target):
""":type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, nums):
""":type nums: List[int]"""
self.hash_map = collections.defaultdict(list)
for i in range(len(nums)):
self.hash_map[nums[i]].append(i)
def pick(self, target):
""":type target: int :rtype: int"""
if target in self.hash_... | the_stack_v2_python_sparse | Mocks/Facebook/Medium/398.Random_Pick_index.py | ramakanthd92/LeetCode | train | 2 | |
aafacde07c280415d633cd7cea20a6198261e9f3 | [
"driver = init_driver('https://www.olx.ua/uk/nedvizhimost/kvartiry-komnaty/arenda-kvartir-komnat/')\ndriver.execute_script('arguments[0].click();', driver.find_element_by_id('cityField'))\nsoup = BeautifulSoup(driver.page_source, 'html.parser')\nitems = soup.find_all('a', class_='link gray')\nurls = {}\nwith sessio... | <|body_start_0|>
driver = init_driver('https://www.olx.ua/uk/nedvizhimost/kvartiry-komnaty/arenda-kvartir-komnat/')
driver.execute_script('arguments[0].click();', driver.find_element_by_id('cityField'))
soup = BeautifulSoup(driver.page_source, 'html.parser')
items = soup.find_all('a', cl... | Class for filling db with state xref reference from olx | OlxStateXRefServicesLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OlxStateXRefServicesLoader:
"""Class for filling db with state xref reference from olx"""
def get_states() -> dict:
"""Navigating through site olx.com and getting states :return: dict"""
<|body_0|>
def load(self, *args, **kwargs) -> int:
"""Load states from OLX R... | stack_v2_sparse_classes_36k_train_016762 | 7,788 | no_license | [
{
"docstring": "Navigating through site olx.com and getting states :return: dict",
"name": "get_states",
"signature": "def get_states() -> dict"
},
{
"docstring": "Load states from OLX Returns amount of fetched states :return: int",
"name": "load",
"signature": "def load(self, *args, **k... | 2 | null | Implement the Python class `OlxStateXRefServicesLoader` described below.
Class description:
Class for filling db with state xref reference from olx
Method signatures and docstrings:
- def get_states() -> dict: Navigating through site olx.com and getting states :return: dict
- def load(self, *args, **kwargs) -> int: L... | Implement the Python class `OlxStateXRefServicesLoader` described below.
Class description:
Class for filling db with state xref reference from olx
Method signatures and docstrings:
- def get_states() -> dict: Navigating through site olx.com and getting states :return: dict
- def load(self, *args, **kwargs) -> int: L... | 80cd627f47e0499ddcb2c3313dbd67f1a90145c9 | <|skeleton|>
class OlxStateXRefServicesLoader:
"""Class for filling db with state xref reference from olx"""
def get_states() -> dict:
"""Navigating through site olx.com and getting states :return: dict"""
<|body_0|>
def load(self, *args, **kwargs) -> int:
"""Load states from OLX R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OlxStateXRefServicesLoader:
"""Class for filling db with state xref reference from olx"""
def get_states() -> dict:
"""Navigating through site olx.com and getting states :return: dict"""
driver = init_driver('https://www.olx.ua/uk/nedvizhimost/kvartiry-komnaty/arenda-kvartir-komnat/')
... | the_stack_v2_python_sparse | service_api/services/olx/loaders.py | Project-Franchise/client-service | train | 1 |
d3a43d6e492a02b34495ac2b3c7d7b20565b763e | [
"if K == 0:\n return 5\n\ndef trailingZeroes(n):\n if n == 0:\n return 0\n import math\n k = int(math.log(n, 5))\n ans = 0\n for i in range(1, k + 1):\n ans += n // 5 ** i\n return ans\nhight, low = (K * 5, 5)\nwhile low <= hight:\n mid = (low + hight) // 2\n a = trailingZer... | <|body_start_0|>
if K == 0:
return 5
def trailingZeroes(n):
if n == 0:
return 0
import math
k = int(math.log(n, 5))
ans = 0
for i in range(1, k + 1):
ans += n // 5 ** i
return ans
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preimageSizeFZF(self, K):
""":type K: int :rtype: int 35MS"""
<|body_0|>
def preimageSizeFZF_1(self, K):
""":type K: int :rtype: int 33ms"""
<|body_1|>
def preimageSizeFZF_2(self, K):
""":type K: int :rtype: int 31ms"""
<|bo... | stack_v2_sparse_classes_36k_train_016763 | 3,083 | no_license | [
{
"docstring": ":type K: int :rtype: int 35MS",
"name": "preimageSizeFZF",
"signature": "def preimageSizeFZF(self, K)"
},
{
"docstring": ":type K: int :rtype: int 33ms",
"name": "preimageSizeFZF_1",
"signature": "def preimageSizeFZF_1(self, K)"
},
{
"docstring": ":type K: int :rt... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preimageSizeFZF(self, K): :type K: int :rtype: int 35MS
- def preimageSizeFZF_1(self, K): :type K: int :rtype: int 33ms
- def preimageSizeFZF_2(self, K): :type K: int :rtype:... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preimageSizeFZF(self, K): :type K: int :rtype: int 35MS
- def preimageSizeFZF_1(self, K): :type K: int :rtype: int 33ms
- def preimageSizeFZF_2(self, K): :type K: int :rtype:... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def preimageSizeFZF(self, K):
""":type K: int :rtype: int 35MS"""
<|body_0|>
def preimageSizeFZF_1(self, K):
""":type K: int :rtype: int 33ms"""
<|body_1|>
def preimageSizeFZF_2(self, K):
""":type K: int :rtype: int 31ms"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preimageSizeFZF(self, K):
""":type K: int :rtype: int 35MS"""
if K == 0:
return 5
def trailingZeroes(n):
if n == 0:
return 0
import math
k = int(math.log(n, 5))
ans = 0
for i in range... | the_stack_v2_python_sparse | PreimageSizeOfFactorialZeroesFunction_HARD_793.py | 953250587/leetcode-python | train | 2 | |
e2063b4154f217d2ff5041f56af8865f22ccaa65 | [
"challenges: List[Dict[str, Any]] = []\nchallenges = WeeklyChallengesMP.Table(self, challenges)\nUtility.WriteFile(self, f'{self.eXAssets}/weeklyChallengesMP.json', challenges)\nlog.info(f'Compiled {len(challenges):,} Weekly Multiplayer Challenges')",
"table: List[Dict[str, Any]] = Utility.ReadCSV(self, f'{self.i... | <|body_start_0|>
challenges: List[Dict[str, Any]] = []
challenges = WeeklyChallengesMP.Table(self, challenges)
Utility.WriteFile(self, f'{self.eXAssets}/weeklyChallengesMP.json', challenges)
log.info(f'Compiled {len(challenges):,} Weekly Multiplayer Challenges')
<|end_body_0|>
<|body_st... | Weekly Multiplayer Challenges XAssets. | WeeklyChallengesMP | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WeeklyChallengesMP:
"""Weekly Multiplayer Challenges XAssets."""
def Compile(self: Any) -> None:
"""Compile the Weekly Multiplayer Challenges XAssets."""
<|body_0|>
def Table(self: Any, challenges: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Compile the wee... | stack_v2_sparse_classes_36k_train_016764 | 13,794 | permissive | [
{
"docstring": "Compile the Weekly Multiplayer Challenges XAssets.",
"name": "Compile",
"signature": "def Compile(self: Any) -> None"
},
{
"docstring": "Compile the weekly_challenges.csv XAsset.",
"name": "Table",
"signature": "def Table(self: Any, challenges: List[Dict[str, Any]]) -> Li... | 2 | stack_v2_sparse_classes_30k_train_014666 | Implement the Python class `WeeklyChallengesMP` described below.
Class description:
Weekly Multiplayer Challenges XAssets.
Method signatures and docstrings:
- def Compile(self: Any) -> None: Compile the Weekly Multiplayer Challenges XAssets.
- def Table(self: Any, challenges: List[Dict[str, Any]]) -> List[Dict[str, A... | Implement the Python class `WeeklyChallengesMP` described below.
Class description:
Weekly Multiplayer Challenges XAssets.
Method signatures and docstrings:
- def Compile(self: Any) -> None: Compile the Weekly Multiplayer Challenges XAssets.
- def Table(self: Any, challenges: List[Dict[str, Any]]) -> List[Dict[str, A... | 82d3198a64eb2905e96dd536ce2f0acb52f9ce77 | <|skeleton|>
class WeeklyChallengesMP:
"""Weekly Multiplayer Challenges XAssets."""
def Compile(self: Any) -> None:
"""Compile the Weekly Multiplayer Challenges XAssets."""
<|body_0|>
def Table(self: Any, challenges: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Compile the wee... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WeeklyChallengesMP:
"""Weekly Multiplayer Challenges XAssets."""
def Compile(self: Any) -> None:
"""Compile the Weekly Multiplayer Challenges XAssets."""
challenges: List[Dict[str, Any]] = []
challenges = WeeklyChallengesMP.Table(self, challenges)
Utility.WriteFile(self, f... | the_stack_v2_python_sparse | ModernWarfare/XAssets/challenges.py | dbuentello/Hyde | train | 0 |
d214c48e10421e0d5014368ad970f76ec577805f | [
"super().__init__(**kwargs)\nself.density: float = kwargs.get('density', 1)\nself.specific_heat: float = kwargs.get('specific_heat', 4.184)\nself.min_flow_rate: float = kwargs.get('min_flow_rate', 0)\nself.power: Callable[[float], float] = kwargs.get('power', lambda x: 0)",
"flow_rate = self.min_flow_rate\nif sel... | <|body_start_0|>
super().__init__(**kwargs)
self.density: float = kwargs.get('density', 1)
self.specific_heat: float = kwargs.get('specific_heat', 4.184)
self.min_flow_rate: float = kwargs.get('min_flow_rate', 0)
self.power: Callable[[float], float] = kwargs.get('power', lambda x... | TwoPhaseImmersionCoolerPowerModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TwoPhaseImmersionCoolerPowerModel:
def __init__(self, **kwargs):
"""Two-Phase Immersion cooling system power consumption model. :param float density: Density of the fluid (in g/cm^3). By default, it is set to 1 (i.e., water). :param float specific_heat: Specific heat of the fluid (in J/g... | stack_v2_sparse_classes_36k_train_016765 | 3,314 | permissive | [
{
"docstring": "Two-Phase Immersion cooling system power consumption model. :param float density: Density of the fluid (in g/cm^3). By default, it is set to 1 (i.e., water). :param float specific_heat: Specific heat of the fluid (in J/gK). By default, it is set to 4.184 (i.e., water). :param float t_difference:... | 2 | null | Implement the Python class `TwoPhaseImmersionCoolerPowerModel` described below.
Class description:
Implement the TwoPhaseImmersionCoolerPowerModel class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Two-Phase Immersion cooling system power consumption model. :param float density: Density of the f... | Implement the Python class `TwoPhaseImmersionCoolerPowerModel` described below.
Class description:
Implement the TwoPhaseImmersionCoolerPowerModel class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Two-Phase Immersion cooling system power consumption model. :param float density: Density of the f... | cb425605de3341d27ce43fb326b300cb8ac781f6 | <|skeleton|>
class TwoPhaseImmersionCoolerPowerModel:
def __init__(self, **kwargs):
"""Two-Phase Immersion cooling system power consumption model. :param float density: Density of the fluid (in g/cm^3). By default, it is set to 1 (i.e., water). :param float specific_heat: Specific heat of the fluid (in J/g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TwoPhaseImmersionCoolerPowerModel:
def __init__(self, **kwargs):
"""Two-Phase Immersion cooling system power consumption model. :param float density: Density of the fluid (in g/cm^3). By default, it is set to 1 (i.e., water). :param float specific_heat: Specific heat of the fluid (in J/gK). By default... | the_stack_v2_python_sparse | mercury/plugin/edc/cooler_power.py | greenlsi/mercury_mso_framework | train | 2 | |
e60bdf2928f121a623e928237f8ce8e684856c0d | [
"for x in range(30):\n for y in range(30):\n self.play_agent(x, y)\nfor x in range(30):\n for y in range(30):\n agent = self.board.at(x, y)\n agent.last_against = agent.curr_against\n agent.curr_against = {}\nfor x in range(30):\n for y in range(30):\n self.find_best_neig... | <|body_start_0|>
for x in range(30):
for y in range(30):
self.play_agent(x, y)
for x in range(30):
for y in range(30):
agent = self.board.at(x, y)
agent.last_against = agent.curr_against
agent.curr_against = {}
... | Runs a game using the imitation dynamics | ImitationGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImitationGame:
"""Runs a game using the imitation dynamics"""
def update(self):
"""Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are calculated as the average of payoffs against all neighbor... | stack_v2_sparse_classes_36k_train_016766 | 3,767 | no_license | [
{
"docstring": "Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are calculated as the average of payoffs against all neighbors played (thus border agents are roughly equal to inner agents). 2. Update agent states. 3. Eac... | 4 | stack_v2_sparse_classes_30k_train_007709 | Implement the Python class `ImitationGame` described below.
Class description:
Runs a game using the imitation dynamics
Method signatures and docstrings:
- def update(self): Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are ... | Implement the Python class `ImitationGame` described below.
Class description:
Runs a game using the imitation dynamics
Method signatures and docstrings:
- def update(self): Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are ... | 52b27e36474afef3d8d24a7c39d0cbb879e0184d | <|skeleton|>
class ImitationGame:
"""Runs a game using the imitation dynamics"""
def update(self):
"""Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are calculated as the average of payoffs against all neighbor... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImitationGame:
"""Runs a game using the imitation dynamics"""
def update(self):
"""Updates a single round of the game. The phases of the round are as follows: 1. Each agent first plays against all of its neighbors. Payoffs are calculated as the average of payoffs against all neighbors played (thu... | the_stack_v2_python_sparse | pyevo/imitation_game.py | nwoodbury/pyevo | train | 0 |
1a1b4036aa581d87abc3673229fef35287eeef37 | [
"tfrecord_cache_files = dataset_util.get_cache_files_coco(data_dir, cache_dir)\nif not tfrecord_cache_files.is_cached():\n label_map = dataset_util.get_label_map_coco(data_dir)\n cache_writer = dataset_util.COCOCacheFilesWriter(label_map=label_map, max_num_images=max_num_images)\n cache_writer.write_files(... | <|body_start_0|>
tfrecord_cache_files = dataset_util.get_cache_files_coco(data_dir, cache_dir)
if not tfrecord_cache_files.is_cached():
label_map = dataset_util.get_label_map_coco(data_dir)
cache_writer = dataset_util.COCOCacheFilesWriter(label_map=label_map, max_num_images=max_n... | Dataset library for object detector. | Dataset | [
"Apache-2.0",
"dtoa"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dataset:
"""Dataset library for object detector."""
def from_coco_folder(cls, data_dir: str, max_num_images: Optional[int]=None, cache_dir: Optional[str]=None) -> 'Dataset':
"""Loads images and labels from the given directory in COCO format. - https://cocodataset.org/#home Folder str... | stack_v2_sparse_classes_36k_train_016767 | 6,432 | permissive | [
{
"docstring": "Loads images and labels from the given directory in COCO format. - https://cocodataset.org/#home Folder structure should be: <data_dir>/ images/ <file0>.jpg ... labels.json The `labels.json` annotations file should should have the following format: { \"categories\": [{\"id\": 0, \"name\": \"back... | 3 | null | Implement the Python class `Dataset` described below.
Class description:
Dataset library for object detector.
Method signatures and docstrings:
- def from_coco_folder(cls, data_dir: str, max_num_images: Optional[int]=None, cache_dir: Optional[str]=None) -> 'Dataset': Loads images and labels from the given directory i... | Implement the Python class `Dataset` described below.
Class description:
Dataset library for object detector.
Method signatures and docstrings:
- def from_coco_folder(cls, data_dir: str, max_num_images: Optional[int]=None, cache_dir: Optional[str]=None) -> 'Dataset': Loads images and labels from the given directory i... | 007824594bf1d07c7c1467df03a43886f8a4b3ad | <|skeleton|>
class Dataset:
"""Dataset library for object detector."""
def from_coco_folder(cls, data_dir: str, max_num_images: Optional[int]=None, cache_dir: Optional[str]=None) -> 'Dataset':
"""Loads images and labels from the given directory in COCO format. - https://cocodataset.org/#home Folder str... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dataset:
"""Dataset library for object detector."""
def from_coco_folder(cls, data_dir: str, max_num_images: Optional[int]=None, cache_dir: Optional[str]=None) -> 'Dataset':
"""Loads images and labels from the given directory in COCO format. - https://cocodataset.org/#home Folder structure should... | the_stack_v2_python_sparse | mediapipe/model_maker/python/vision/object_detector/dataset.py | google/mediapipe | train | 23,940 |
07a1f87e7d6dd8af96372a79410b3f881c54ff0e | [
"MOD = int(1000000000.0 + 7)\ns = 0\nret = (0, 0)\n\ndef sum_tree(node):\n if not node:\n return 0\n cur = node.val + sum_tree(node.left) + sum_tree(node.right)\n nonlocal ret, s\n ret = max(ret, divmod(cur * (s - cur), MOD))\n return cur\ns = sum_tree(root)\nret = (0, 0)\nsum_tree(root)\nretu... | <|body_start_0|>
MOD = int(1000000000.0 + 7)
s = 0
ret = (0, 0)
def sum_tree(node):
if not node:
return 0
cur = node.val + sum_tree(node.left) + sum_tree(node.right)
nonlocal ret, s
ret = max(ret, divmod(cur * (s - cur), MO... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProduct(self, root: Optional[TreeNode]) -> int:
"""Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def maxProduct(self, root: Optional[TreeNode]) -> int:
"""Dec 11, 2022 16:48"""
<|body_1|>
def maxProduct(se... | stack_v2_sparse_classes_36k_train_016768 | 13,179 | no_license | [
{
"docstring": "Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)",
"name": "maxProduct",
"signature": "def maxProduct(self, root: Optional[TreeNode]) -> int"
},
{
"docstring": "Dec 11, 2022 16:48",
"name": "maxProduct",
"signature": "def maxProduct(self, root: Optional[Tre... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, root: Optional[TreeNode]) -> int: Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)
- def maxProduct(self, root: Optional[TreeNode]) -> int: De... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProduct(self, root: Optional[TreeNode]) -> int: Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)
- def maxProduct(self, root: Optional[TreeNode]) -> int: De... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def maxProduct(self, root: Optional[TreeNode]) -> int:
"""Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def maxProduct(self, root: Optional[TreeNode]) -> int:
"""Dec 11, 2022 16:48"""
<|body_1|>
def maxProduct(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProduct(self, root: Optional[TreeNode]) -> int:
"""Aug 26, 2021 01:12 Time complexity: O(n) Space complexity: O(1)"""
MOD = int(1000000000.0 + 7)
s = 0
ret = (0, 0)
def sum_tree(node):
if not node:
return 0
cur =... | the_stack_v2_python_sparse | leetcode/solved/1465_Maximum_Product_of_Splitted_Binary_Tree/solution.py | sungminoh/algorithms | train | 0 | |
e529a1fa3a382a175b227720b7096e6a023731ed | [
"if type(x) == list:\n self.x = np.array(x)\nelse:\n self.x = x\nself.E = E\nself.alpha = alpha\nself.R = R\nself.Rsig = Rsig\nself.dist = dist\nself.qc = qc\nself.qpar = qpar\nself.qparsig = qparsig\nself.norm = norm\nself.qoff = qoff\nself.bkg = bkg\nself.sig = sig\nself.N = N\nself.__mpar__ = mpar\nself.ch... | <|body_start_0|>
if type(x) == list:
self.x = np.array(x)
else:
self.x = x
self.E = E
self.alpha = alpha
self.R = R
self.Rsig = Rsig
self.dist = dist
self.qc = qc
self.qpar = qpar
self.qparsig = qparsig
self.... | Rod_Sphere | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rod_Sphere:
def __init__(self, x=0, E=10.0, alpha=0.1, R=10.0, Rsig=1.0, dist='Gaussian', qc=0.0217, qpar=0.1, qparsig=0.0, N=50, sig=0.0, norm=1.0, qoff=0.0, bkg=0.0, mpar={}):
"""Provides rod scan from spherical objects dispersed on a substrate x : Array of Qz values of rod scan E : En... | stack_v2_sparse_classes_36k_train_016769 | 4,207 | permissive | [
{
"docstring": "Provides rod scan from spherical objects dispersed on a substrate x : Array of Qz values of rod scan E : Energy of X-ray in unit of keV alpha : incident angle in unit of degree R : Mean radius of spheres in inverse units of Qz Rsig : Width of distribution of spheres in inverse units of Qz dist :... | 4 | null | Implement the Python class `Rod_Sphere` described below.
Class description:
Implement the Rod_Sphere class.
Method signatures and docstrings:
- def __init__(self, x=0, E=10.0, alpha=0.1, R=10.0, Rsig=1.0, dist='Gaussian', qc=0.0217, qpar=0.1, qparsig=0.0, N=50, sig=0.0, norm=1.0, qoff=0.0, bkg=0.0, mpar={}): Provides... | Implement the Python class `Rod_Sphere` described below.
Class description:
Implement the Rod_Sphere class.
Method signatures and docstrings:
- def __init__(self, x=0, E=10.0, alpha=0.1, R=10.0, Rsig=1.0, dist='Gaussian', qc=0.0217, qpar=0.1, qparsig=0.0, N=50, sig=0.0, norm=1.0, qoff=0.0, bkg=0.0, mpar={}): Provides... | abbb091e703cfc3580a39b68070f5b60d3abb86b | <|skeleton|>
class Rod_Sphere:
def __init__(self, x=0, E=10.0, alpha=0.1, R=10.0, Rsig=1.0, dist='Gaussian', qc=0.0217, qpar=0.1, qparsig=0.0, N=50, sig=0.0, norm=1.0, qoff=0.0, bkg=0.0, mpar={}):
"""Provides rod scan from spherical objects dispersed on a substrate x : Array of Qz values of rod scan E : En... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Rod_Sphere:
def __init__(self, x=0, E=10.0, alpha=0.1, R=10.0, Rsig=1.0, dist='Gaussian', qc=0.0217, qpar=0.1, qparsig=0.0, N=50, sig=0.0, norm=1.0, qoff=0.0, bkg=0.0, mpar={}):
"""Provides rod scan from spherical objects dispersed on a substrate x : Array of Qz values of rod scan E : Energy of X-ray ... | the_stack_v2_python_sparse | Functions/GISAXS/Rod_Sphere.py | chemmatcars/XModFit | train | 0 | |
316f88510958c5181c8659b386d2c9a2ec5e1cd3 | [
"max_position = 0\nfor i, n in enumerate(nums[:-1]):\n if max_position < i:\n break\n max_position = max(max_position, i + n)\nreturn max_position >= len(nums) - 1",
"max_position = len(nums) - 1\nfor i in range(len(nums) - 2, -1, -1):\n if i + nums[i] >= max_position:\n max_position = i\nr... | <|body_start_0|>
max_position = 0
for i, n in enumerate(nums[:-1]):
if max_position < i:
break
max_position = max(max_position, i + n)
return max_position >= len(nums) - 1
<|end_body_0|>
<|body_start_1|>
max_position = len(nums) - 1
for i ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canJump(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canJump_reverse(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
max_position = 0
for i, n in enumer... | stack_v2_sparse_classes_36k_train_016770 | 1,393 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canJump",
"signature": "def canJump(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canJump_reverse",
"signature": "def canJump_reverse(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canJump(self, nums): :type nums: List[int] :rtype: bool
- def canJump_reverse(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 canJump(self, nums): :type nums: List[int] :rtype: bool
- def canJump_reverse(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canJump(s... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def canJump(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def canJump_reverse(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 canJump(self, nums):
""":type nums: List[int] :rtype: bool"""
max_position = 0
for i, n in enumerate(nums[:-1]):
if max_position < i:
break
max_position = max(max_position, i + n)
return max_position >= len(nums) - 1
de... | the_stack_v2_python_sparse | src/lt_55.py | oxhead/CodingYourWay | train | 0 | |
f7896acfd5ecdec01a4d3bce506150d34f945dd3 | [
"level = []\n\ndef dfs(node, c):\n if c >= len(level):\n level.append([])\n if node is None:\n level[c].append('null')\n return\n level[c].append(node.val)\n dfs(node.left, c + 1)\n dfs(node.right, c + 1)\ndfs(root, 0)\ns = ''\nfor i in range(len(level)):\n for j in range(len(... | <|body_start_0|>
level = []
def dfs(node, c):
if c >= len(level):
level.append([])
if node is None:
level[c].append('null')
return
level[c].append(node.val)
dfs(node.left, c + 1)
dfs(node.right, ... | 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_016771 | 1,832 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_001173 | 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:... | d376ca3a76254076f2b226f169b8296bdf44ad08 | <|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"""
level = []
def dfs(node, c):
if c >= len(level):
level.append([])
if node is None:
level[c].append('null')
... | the_stack_v2_python_sparse | 297. Serialize and Deserialize Binary Tree.py | nvnnv/Leetcode | train | 0 | |
bc81200a2e2b2f7dba09d85ff95f67f5d367c4ec | [
"self.driver.get(url)\nself.driver.max_window()\nself.driver.find_element(locator.HeaderLocator.about_button).click()\nself.driver.pause(3)\nself.driver.switch_to_window()\nabout_is_dispayed = self.driver.is_display(locator.HeaderLocator.about_title)\nself.driver.pause(3)\ntt_check.assertTrue(about_is_dispayed, '关于... | <|body_start_0|>
self.driver.get(url)
self.driver.max_window()
self.driver.find_element(locator.HeaderLocator.about_button).click()
self.driver.pause(3)
self.driver.switch_to_window()
about_is_dispayed = self.driver.is_display(locator.HeaderLocator.about_title)
se... | about | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class about:
def test_about(self):
"""测试首页底部关于淘车-跳转,@author:xulanzhong"""
<|body_0|>
def test_contact(self):
"""测试首页底部联系我们-跳转,@author:xulanzhong"""
<|body_1|>
def test_B_lisence(self):
"""测试首页底部营业执照-跳转,@author:xulanzhong"""
<|body_2|>
def ... | stack_v2_sparse_classes_36k_train_016772 | 2,780 | no_license | [
{
"docstring": "测试首页底部关于淘车-跳转,@author:xulanzhong",
"name": "test_about",
"signature": "def test_about(self)"
},
{
"docstring": "测试首页底部联系我们-跳转,@author:xulanzhong",
"name": "test_contact",
"signature": "def test_contact(self)"
},
{
"docstring": "测试首页底部营业执照-跳转,@author:xulanzhong",
... | 5 | stack_v2_sparse_classes_30k_val_000084 | Implement the Python class `about` described below.
Class description:
Implement the about class.
Method signatures and docstrings:
- def test_about(self): 测试首页底部关于淘车-跳转,@author:xulanzhong
- def test_contact(self): 测试首页底部联系我们-跳转,@author:xulanzhong
- def test_B_lisence(self): 测试首页底部营业执照-跳转,@author:xulanzhong
- def tes... | Implement the Python class `about` described below.
Class description:
Implement the about class.
Method signatures and docstrings:
- def test_about(self): 测试首页底部关于淘车-跳转,@author:xulanzhong
- def test_contact(self): 测试首页底部联系我们-跳转,@author:xulanzhong
- def test_B_lisence(self): 测试首页底部营业执照-跳转,@author:xulanzhong
- def tes... | 204856bd33c06d25f2970eba13799db75d4fd4fe | <|skeleton|>
class about:
def test_about(self):
"""测试首页底部关于淘车-跳转,@author:xulanzhong"""
<|body_0|>
def test_contact(self):
"""测试首页底部联系我们-跳转,@author:xulanzhong"""
<|body_1|>
def test_B_lisence(self):
"""测试首页底部营业执照-跳转,@author:xulanzhong"""
<|body_2|>
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class about:
def test_about(self):
"""测试首页底部关于淘车-跳转,@author:xulanzhong"""
self.driver.get(url)
self.driver.max_window()
self.driver.find_element(locator.HeaderLocator.about_button).click()
self.driver.pause(3)
self.driver.switch_to_window()
about_is_dispayed =... | the_stack_v2_python_sparse | mc/taochePC/test_crawler/test_homepage/test_about.py | boeai/mc | train | 0 | |
7870403d3f627a83170025084286e50f8a78e77b | [
"uf = UF(len(edges))\nres = None\nfor e in edges:\n n1, n2 = (e[0], e[1])\n if uf.connected(n1, n2):\n res = e[:]\n else:\n uf.union(n1, n2)\nreturn res",
"n = len(edges)\nroots = [i for i in range(n + 1)]\n\ndef find(i):\n while roots[i] != i:\n roots[i] = roots[roots[i]]\n ... | <|body_start_0|>
uf = UF(len(edges))
res = None
for e in edges:
n1, n2 = (e[0], e[1])
if uf.connected(n1, n2):
res = e[:]
else:
uf.union(n1, n2)
return res
<|end_body_0|>
<|body_start_1|>
n = len(edges)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findRedundantConnection(self, edges):
""":type edges: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findRedundantConnectionUF(self, edges):
""":type edges: List[List[int]] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_016773 | 2,038 | no_license | [
{
"docstring": ":type edges: List[List[int]] :rtype: List[int]",
"name": "findRedundantConnection",
"signature": "def findRedundantConnection(self, edges)"
},
{
"docstring": ":type edges: List[List[int]] :rtype: List[int]",
"name": "findRedundantConnectionUF",
"signature": "def findRedun... | 2 | stack_v2_sparse_classes_30k_train_016630 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRedundantConnection(self, edges): :type edges: List[List[int]] :rtype: List[int]
- def findRedundantConnectionUF(self, edges): :type edges: List[List[int]] :rtype: List[i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findRedundantConnection(self, edges): :type edges: List[List[int]] :rtype: List[int]
- def findRedundantConnectionUF(self, edges): :type edges: List[List[int]] :rtype: List[i... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def findRedundantConnection(self, edges):
""":type edges: List[List[int]] :rtype: List[int]"""
<|body_0|>
def findRedundantConnectionUF(self, edges):
""":type edges: List[List[int]] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findRedundantConnection(self, edges):
""":type edges: List[List[int]] :rtype: List[int]"""
uf = UF(len(edges))
res = None
for e in edges:
n1, n2 = (e[0], e[1])
if uf.connected(n1, n2):
res = e[:]
else:
... | the_stack_v2_python_sparse | R/RedundantConnection.py | bssrdf/pyleet | train | 2 | |
56eac98739988e25be08b22d52d2514cbda78dff | [
"super(GANLoss, self).__init__()\nself.register_buffer('real_label', torch.tensor(real_label))\nself.register_buffer('fake_label', torch.tensor(fake_label))\nself.gan_mode = gan_mode\nif gan_mode == 'vanilla':\n self.loss = nn.BCEWithLogitsLoss()\nelif gan_mode == 'lsgan':\n self.loss = nn.MSELoss()\nelif gan... | <|body_start_0|>
super(GANLoss, self).__init__()
self.register_buffer('real_label', torch.tensor(real_label))
self.register_buffer('fake_label', torch.tensor(fake_label))
self.gan_mode = gan_mode
if gan_mode == 'vanilla':
self.loss = nn.BCEWithLogitsLoss()
eli... | GANLoss | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GANLoss:
def __init__(self, gan_mode, real_label=1.0, fake_label=0.0):
"""Initialize the GANLoss class gan_mode: type of gan loss"""
<|body_0|>
def getLabelTensor(self, pred, targ_is_real):
"""Return the real label or fake label as a tensor with the same dimension as... | stack_v2_sparse_classes_36k_train_016774 | 3,750 | no_license | [
{
"docstring": "Initialize the GANLoss class gan_mode: type of gan loss",
"name": "__init__",
"signature": "def __init__(self, gan_mode, real_label=1.0, fake_label=0.0)"
},
{
"docstring": "Return the real label or fake label as a tensor with the same dimension as the prediction (from the discrim... | 3 | stack_v2_sparse_classes_30k_train_014806 | Implement the Python class `GANLoss` described below.
Class description:
Implement the GANLoss class.
Method signatures and docstrings:
- def __init__(self, gan_mode, real_label=1.0, fake_label=0.0): Initialize the GANLoss class gan_mode: type of gan loss
- def getLabelTensor(self, pred, targ_is_real): Return the rea... | Implement the Python class `GANLoss` described below.
Class description:
Implement the GANLoss class.
Method signatures and docstrings:
- def __init__(self, gan_mode, real_label=1.0, fake_label=0.0): Initialize the GANLoss class gan_mode: type of gan loss
- def getLabelTensor(self, pred, targ_is_real): Return the rea... | 14fdb90f84cc33ea1f59bc8e94cbf2214b9334d8 | <|skeleton|>
class GANLoss:
def __init__(self, gan_mode, real_label=1.0, fake_label=0.0):
"""Initialize the GANLoss class gan_mode: type of gan loss"""
<|body_0|>
def getLabelTensor(self, pred, targ_is_real):
"""Return the real label or fake label as a tensor with the same dimension as... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GANLoss:
def __init__(self, gan_mode, real_label=1.0, fake_label=0.0):
"""Initialize the GANLoss class gan_mode: type of gan loss"""
super(GANLoss, self).__init__()
self.register_buffer('real_label', torch.tensor(real_label))
self.register_buffer('fake_label', torch.tensor(fake... | the_stack_v2_python_sparse | models/losses.py | athena913/pix2pix | train | 0 | |
645036034bd3756d5f769ac8924989d2528edec3 | [
"self.lat = lat\nself.lon = lon\nself.age = age\nself.beach_time = beach_time\nself.pt = Point(self.lon, self.lat)\nself.intervalo = None\nself.id_intervalo = None",
"data = self.beach_time\ndif = data - data_inicio\ndelta = dif / datetime.timedelta(hours=dt)\nint_delta = int(delta)\nresult = data_inicio + dateti... | <|body_start_0|>
self.lat = lat
self.lon = lon
self.age = age
self.beach_time = beach_time
self.pt = Point(self.lon, self.lat)
self.intervalo = None
self.id_intervalo = None
<|end_body_0|>
<|body_start_1|>
data = self.beach_time
dif = data - data_... | Class Lagrangian Partic | Partic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Partic:
"""Class Lagrangian Partic"""
def __init__(self, lat, lon, age, beach_time):
"""inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha particula no ficheiro de saída lagranxiana :param age: idade en... | stack_v2_sparse_classes_36k_train_016775 | 1,159 | no_license | [
{
"docstring": "inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha particula no ficheiro de saída lagranxiana :param age: idade en segundos dunha particula no ficheiro de saída lagranxiana",
"name": "__init__",
"signature"... | 2 | stack_v2_sparse_classes_30k_test_000109 | Implement the Python class `Partic` described below.
Class description:
Class Lagrangian Partic
Method signatures and docstrings:
- def __init__(self, lat, lon, age, beach_time): inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha partic... | Implement the Python class `Partic` described below.
Class description:
Class Lagrangian Partic
Method signatures and docstrings:
- def __init__(self, lat, lon, age, beach_time): inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha partic... | e3c577e6048d546706df0c6191a0d0d10a58d3d8 | <|skeleton|>
class Partic:
"""Class Lagrangian Partic"""
def __init__(self, lat, lon, age, beach_time):
"""inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha particula no ficheiro de saída lagranxiana :param age: idade en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Partic:
"""Class Lagrangian Partic"""
def __init__(self, lat, lon, age, beach_time):
"""inicia a clase Partic da partícula :param lat: latitude dunha particula no ficheiro de saída lagranxiana :param lon: lonxitude dunha particula no ficheiro de saída lagranxiana :param age: idade en segundos dun... | the_stack_v2_python_sparse | cleanatlantic/partic.py | pedromontero/CLEANATLANTIC | train | 1 |
1f07a9714ea50c7b34cb01050863600b811acce4 | [
"super(Generator, self).__init__()\nself.rnn = nn.LSTM(input_size=vid_feat_size, hidden_size=hidden_size, bidirectional=True, num_layers=1)\nself.drop = nn.Dropout(p=dropout_p)\nself.linear = nn.Linear(hidden_size * 2, 2)\nself.tau = tau",
"batch_size = vid_feats.shape[0]\nnum_frames = vid_feats.shape[1]\nout, _ ... | <|body_start_0|>
super(Generator, self).__init__()
self.rnn = nn.LSTM(input_size=vid_feat_size, hidden_size=hidden_size, bidirectional=True, num_layers=1)
self.drop = nn.Dropout(p=dropout_p)
self.linear = nn.Linear(hidden_size * 2, 2)
self.tau = tau
<|end_body_0|>
<|body_start_1... | Generator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Generator:
def __init__(self, dropout_p, hidden_size, vid_feat_size, tau):
"""Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_size: Size of the video features tau: non-negative scalar temperature"""
... | stack_v2_sparse_classes_36k_train_016776 | 3,887 | no_license | [
{
"docstring": "Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_size: Size of the video features tau: non-negative scalar temperature",
"name": "__init__",
"signature": "def __init__(self, dropout_p, hidden_size, vid_feat_... | 2 | stack_v2_sparse_classes_30k_train_009291 | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, dropout_p, hidden_size, vid_feat_size, tau): Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linea... | Implement the Python class `Generator` described below.
Class description:
Implement the Generator class.
Method signatures and docstrings:
- def __init__(self, dropout_p, hidden_size, vid_feat_size, tau): Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linea... | 5f347de39f5583cd043c6f572178da08f7c0de94 | <|skeleton|>
class Generator:
def __init__(self, dropout_p, hidden_size, vid_feat_size, tau):
"""Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_size: Size of the video features tau: non-negative scalar temperature"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Generator:
def __init__(self, dropout_p, hidden_size, vid_feat_size, tau):
"""Args: dropout_p: Dropout probability for intermediate dropout layers hidden_size: Size of the intermediate linear layers vid_feat_size: Size of the video features tau: non-negative scalar temperature"""
super(Generat... | the_stack_v2_python_sparse | model/RationaleNet.py | AmmieQi/pytorch-video-caption-rationale | train | 0 | |
1464e1d9a6998cf4778e568d0df48bdbe1670d3a | [
"super(GeM, self).__init__()\nself.power = power\nself.eps = 1e-06",
"if axis is None:\n axis = [1, 2]\nreturn gem(x, power=self.power, eps=self.eps, axis=axis)"
] | <|body_start_0|>
super(GeM, self).__init__()
self.power = power
self.eps = 1e-06
<|end_body_0|>
<|body_start_1|>
if axis is None:
axis = [1, 2]
return gem(x, power=self.power, eps=self.eps, axis=axis)
<|end_body_1|>
| Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference. | GeM | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeM:
"""Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference."""
def __init__(self, power=3.0):
"""Initialization of the generalized mean pooling (GeM) laye... | stack_v2_sparse_classes_36k_train_016777 | 6,125 | permissive | [
{
"docstring": "Initialization of the generalized mean pooling (GeM) layer. Args: power: Float power > 0 is an inverse exponent parameter, used during the generalized mean pooling computation. Setting this exponent as power > 1 increases the contrast of the pooled feature map and focuses on the salient features... | 2 | stack_v2_sparse_classes_30k_train_002752 | Implement the Python class `GeM` described below.
Class description:
Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference.
Method signatures and docstrings:
- def __init__(self, power=3.0): ... | Implement the Python class `GeM` described below.
Class description:
Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference.
Method signatures and docstrings:
- def __init__(self, power=3.0): ... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class GeM:
"""Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference."""
def __init__(self, power=3.0):
"""Initialization of the generalized mean pooling (GeM) laye... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeM:
"""Generalized mean pooling (GeM) layer. Generalized Mean Pooling (GeM) computes the generalized mean of each channel in a tensor. See https://arxiv.org/abs/1711.02512 for a reference."""
def __init__(self, power=3.0):
"""Initialization of the generalized mean pooling (GeM) layer. Args: powe... | the_stack_v2_python_sparse | research/delf/delf/python/pooling_layers/pooling.py | jianzhnie/models | train | 2 |
520fe00cc716b0d14c311139d797c94855f8d2f4 | [
"config_info = common_utils.load_config_json(workspacer.CONFIG_FILE)\nself.assertEqual(len(config_info), 10)\nself.assertGreaterEqual(len(config_info['secret_info']), 3)",
"test_bundles = {'image_win10_power_20210801_test': {'BundleId': 'abc-123123123'}, 'image_win10_power_20210803_test': {'BundleId': 'abc-123123... | <|body_start_0|>
config_info = common_utils.load_config_json(workspacer.CONFIG_FILE)
self.assertEqual(len(config_info), 10)
self.assertGreaterEqual(len(config_info['secret_info']), 3)
<|end_body_0|>
<|body_start_1|>
test_bundles = {'image_win10_power_20210801_test': {'BundleId': 'abc-12... | Standard test class, for all common_utils functions | TestCommonUtils | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCommonUtils:
"""Standard test class, for all common_utils functions"""
def test_load_config_json(self):
"""Test the method used for loading the config json Note if any config files diverge, a separate test should be added"""
<|body_0|>
def test_determine_team_bundle_... | stack_v2_sparse_classes_36k_train_016778 | 1,945 | permissive | [
{
"docstring": "Test the method used for loading the config json Note if any config files diverge, a separate test should be added",
"name": "test_load_config_json",
"signature": "def test_load_config_json(self)"
},
{
"docstring": "Test the method that returns the correct bundle_id",
"name":... | 2 | stack_v2_sparse_classes_30k_train_020320 | Implement the Python class `TestCommonUtils` described below.
Class description:
Standard test class, for all common_utils functions
Method signatures and docstrings:
- def test_load_config_json(self): Test the method used for loading the config json Note if any config files diverge, a separate test should be added
-... | Implement the Python class `TestCommonUtils` described below.
Class description:
Standard test class, for all common_utils functions
Method signatures and docstrings:
- def test_load_config_json(self): Test the method used for loading the config json Note if any config files diverge, a separate test should be added
-... | bcdd157023ee6e28016d10158f82fb02beea76b9 | <|skeleton|>
class TestCommonUtils:
"""Standard test class, for all common_utils functions"""
def test_load_config_json(self):
"""Test the method used for loading the config json Note if any config files diverge, a separate test should be added"""
<|body_0|>
def test_determine_team_bundle_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCommonUtils:
"""Standard test class, for all common_utils functions"""
def test_load_config_json(self):
"""Test the method used for loading the config json Note if any config files diverge, a separate test should be added"""
config_info = common_utils.load_config_json(workspacer.CONFI... | the_stack_v2_python_sparse | test_common_utils.py | BrionStone/aws_workspace_maker | train | 0 |
96d8f0f1a34ee424dcf4ad70ead68b4a5097cf88 | [
"with self.make_session() as session:\n profile = (yield as_future(session.query(Profile).filter(Profile.username == username).first))\n if profile:\n tasks = [task.to_dict() for task in profile.tasks]\n self.send_response({'username': profile.username, 'tasks': tasks})",
"with self.make_sessi... | <|body_start_0|>
with self.make_session() as session:
profile = (yield as_future(session.query(Profile).filter(Profile.username == username).first))
if profile:
tasks = [task.to_dict() for task in profile.tasks]
self.send_response({'username': profile.user... | View for reading and adding new tasks. | TaskListView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskListView:
"""View for reading and adding new tasks."""
def get(self, username):
"""Get all tasks for an existing user."""
<|body_0|>
def post(self, username):
"""Create a new task."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
with self.ma... | stack_v2_sparse_classes_36k_train_016779 | 1,647 | no_license | [
{
"docstring": "Get all tasks for an existing user.",
"name": "get",
"signature": "def get(self, username)"
},
{
"docstring": "Create a new task.",
"name": "post",
"signature": "def post(self, username)"
}
] | 2 | null | Implement the Python class `TaskListView` described below.
Class description:
View for reading and adding new tasks.
Method signatures and docstrings:
- def get(self, username): Get all tasks for an existing user.
- def post(self, username): Create a new task. | Implement the Python class `TaskListView` described below.
Class description:
View for reading and adding new tasks.
Method signatures and docstrings:
- def get(self, username): Get all tasks for an existing user.
- def post(self, username): Create a new task.
<|skeleton|>
class TaskListView:
"""View for reading... | 0f1badabba07fbe7f5f792b7e543c0748eecd6c7 | <|skeleton|>
class TaskListView:
"""View for reading and adding new tasks."""
def get(self, username):
"""Get all tasks for an existing user."""
<|body_0|>
def post(self, username):
"""Create a new task."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskListView:
"""View for reading and adding new tasks."""
def get(self, username):
"""Get all tasks for an existing user."""
with self.make_session() as session:
profile = (yield as_future(session.query(Profile).filter(Profile.username == username).first))
if prof... | the_stack_v2_python_sparse | tornadoPractice/archive/TaskListView.py | devendraprasad1984/python | train | 0 |
58442ec5a3579557a6370bcd1c3cb39fc6271bfd | [
"super(EncoderDecoder, self).__init__()\nself.embed_size = 300\nself.hidden_size = 600\n'\\n Converting words to vectors\\n '\nself.embedding = nn.Embedding(len(vocabulary), self.embed_size)\ninitrange = 0.1\nself.embedding.weight.data.uniform_(-initrange, initrange)\n'\\n An RNN (LSTM) with dr... | <|body_start_0|>
super(EncoderDecoder, self).__init__()
self.embed_size = 300
self.hidden_size = 600
'\n Converting words to vectors\n '
self.embedding = nn.Embedding(len(vocabulary), self.embed_size)
initrange = 0.1
self.embedding.weight.data.unifor... | EncoderDecoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderDecoder:
def __init__(self):
"""Define all the parameters of the model"""
<|body_0|>
def forward(self, input, hidden=None):
"""Running the model :param input: :param hidden: :return hidden, decoded:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_016780 | 12,072 | permissive | [
{
"docstring": "Define all the parameters of the model",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Running the model :param input: :param hidden: :return hidden, decoded:",
"name": "forward",
"signature": "def forward(self, input, hidden=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009769 | Implement the Python class `EncoderDecoder` described below.
Class description:
Implement the EncoderDecoder class.
Method signatures and docstrings:
- def __init__(self): Define all the parameters of the model
- def forward(self, input, hidden=None): Running the model :param input: :param hidden: :return hidden, dec... | Implement the Python class `EncoderDecoder` described below.
Class description:
Implement the EncoderDecoder class.
Method signatures and docstrings:
- def __init__(self): Define all the parameters of the model
- def forward(self, input, hidden=None): Running the model :param input: :param hidden: :return hidden, dec... | 5f380a16be38217e87259f0d93da93c10c37b6a2 | <|skeleton|>
class EncoderDecoder:
def __init__(self):
"""Define all the parameters of the model"""
<|body_0|>
def forward(self, input, hidden=None):
"""Running the model :param input: :param hidden: :return hidden, decoded:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderDecoder:
def __init__(self):
"""Define all the parameters of the model"""
super(EncoderDecoder, self).__init__()
self.embed_size = 300
self.hidden_size = 600
'\n Converting words to vectors\n '
self.embedding = nn.Embedding(len(vocabulary), ... | the_stack_v2_python_sparse | Natural Language Processing/nlp.py | SpencerOfwiti/machine-learning-algorithms | train | 2 | |
ff1f6c94bb7828a74956ee36ac566edcd140bc73 | [
"query = request.GET.get('query')\nqueryset = Release.objects.filter(projects=project, organization_id=project.organization_id).select_related('owner')\nif query:\n queryset = queryset.filter(version__istartswith=query)\nqueryset = queryset.extra(select={'sort': 'COALESCE(date_released, date_added)'})\nreturn se... | <|body_start_0|>
query = request.GET.get('query')
queryset = Release.objects.filter(projects=project, organization_id=project.organization_id).select_related('owner')
if query:
queryset = queryset.filter(version__istartswith=query)
queryset = queryset.extra(select={'sort': 'C... | ProjectReleasesEndpoint | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectReleasesEndpoint:
def get(self, request, project):
"""List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug o... | stack_v2_sparse_classes_36k_train_016781 | 6,430 | permissive | [
{
"docstring": "List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of the project to list the releases of. :qparam string query: this par... | 2 | stack_v2_sparse_classes_30k_train_004259 | Implement the Python class `ProjectReleasesEndpoint` described below.
Class description:
Implement the ProjectReleasesEndpoint class.
Method signatures and docstrings:
- def get(self, request, project): List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string... | Implement the Python class `ProjectReleasesEndpoint` described below.
Class description:
Implement the ProjectReleasesEndpoint class.
Method signatures and docstrings:
- def get(self, request, project): List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string... | b937615079d7b24dc225a83b99b1b65da932fc66 | <|skeleton|>
class ProjectReleasesEndpoint:
def get(self, request, project):
"""List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectReleasesEndpoint:
def get(self, request, project):
"""List a Project's Releases ````````````````````````` Retrieve a list of releases for a given project. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of the project ... | the_stack_v2_python_sparse | src/sentry/api/endpoints/project_releases.py | atlassian/sentry | train | 1 | |
931c1ee02f9e339be91ec69cf54c9c4005651d63 | [
"select_interro_options = [{'id': 'select_interro_test_empty', 'label': '-- Please choose --', 'value': '-'}] + [{'id': 'select_interro_{}'.format(interro.pk), 'label': interro.modele.description, 'value': interro.pk} for interro in Interrogation.objects.filter(user=request.user)]\ndata_step = data.get(wz_user_step... | <|body_start_0|>
select_interro_options = [{'id': 'select_interro_test_empty', 'label': '-- Please choose --', 'value': '-'}] + [{'id': 'select_interro_{}'.format(interro.pk), 'label': interro.modele.description, 'value': interro.pk} for interro in Interrogation.objects.filter(user=request.user)]
data_s... | WizardStepNewExamStep2 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WizardStepNewExamStep2:
def get_content(self, request, wz_user_step, data, **kwargs):
"""Args: request: the current request wz_user_step: current wz_user_step model data: all data gathered step after step **kwargs: other arguments (company and uuid amongst others) Returns: Object that sh... | stack_v2_sparse_classes_36k_train_016782 | 6,848 | permissive | [
{
"docstring": "Args: request: the current request wz_user_step: current wz_user_step model data: all data gathered step after step **kwargs: other arguments (company and uuid amongst others) Returns: Object that should be returned as JSON",
"name": "get_content",
"signature": "def get_content(self, req... | 3 | null | Implement the Python class `WizardStepNewExamStep2` described below.
Class description:
Implement the WizardStepNewExamStep2 class.
Method signatures and docstrings:
- def get_content(self, request, wz_user_step, data, **kwargs): Args: request: the current request wz_user_step: current wz_user_step model data: all da... | Implement the Python class `WizardStepNewExamStep2` described below.
Class description:
Implement the WizardStepNewExamStep2 class.
Method signatures and docstrings:
- def get_content(self, request, wz_user_step, data, **kwargs): Args: request: the current request wz_user_step: current wz_user_step model data: all da... | 7c76474ad41769804965a11550501321d7b1889b | <|skeleton|>
class WizardStepNewExamStep2:
def get_content(self, request, wz_user_step, data, **kwargs):
"""Args: request: the current request wz_user_step: current wz_user_step model data: all data gathered step after step **kwargs: other arguments (company and uuid amongst others) Returns: Object that sh... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WizardStepNewExamStep2:
def get_content(self, request, wz_user_step, data, **kwargs):
"""Args: request: the current request wz_user_step: current wz_user_step model data: all data gathered step after step **kwargs: other arguments (company and uuid amongst others) Returns: Object that should be return... | the_stack_v2_python_sparse | wizard/views/json/step/new_exam/step_2.py | olivierpons/evalr | train | 0 | |
c147a2b746def4c944fee5dd763cdf7043d1dddb | [
"session = Session()\ntry:\n query = session.query(Organization).order_by(Organization.legal_name, Organization.created_on)\n data, paging = get_collection_page(req, query)\n resp.media = {'data': data, 'paging': paging}\nfinally:\n session.close()",
"session = Session()\ntry:\n errors = validate_p... | <|body_start_0|>
session = Session()
try:
query = session.query(Organization).order_by(Organization.legal_name, Organization.created_on)
data, paging = get_collection_page(req, query)
resp.media = {'data': data, 'paging': paging}
finally:
session.c... | GET and POST organizations. | Collection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Collection:
"""GET and POST organizations."""
def on_get(self, req, resp):
"""GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation."""
<|body_0|>
def on_post(self, req, resp):
"""Cr... | stack_v2_sparse_classes_36k_train_016783 | 7,046 | no_license | [
{
"docstring": "GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation.",
"name": "on_get",
"signature": "def on_get(self, req, resp)"
},
{
"docstring": "Creates a new organization. :param req: See Falcon Request doc... | 2 | stack_v2_sparse_classes_30k_train_016625 | Implement the Python class `Collection` described below.
Class description:
GET and POST organizations.
Method signatures and docstrings:
- def on_get(self, req, resp): GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation.
- def on_post... | Implement the Python class `Collection` described below.
Class description:
GET and POST organizations.
Method signatures and docstrings:
- def on_get(self, req, resp): GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation.
- def on_post... | 62723133595829230e5b589431a32cda3b092460 | <|skeleton|>
class Collection:
"""GET and POST organizations."""
def on_get(self, req, resp):
"""GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation."""
<|body_0|>
def on_post(self, req, resp):
"""Cr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Collection:
"""GET and POST organizations."""
def on_get(self, req, resp):
"""GETs a paged collection of organizations. :param req: See Falcon Request documentation. :param resp: See Falcon Response documentation."""
session = Session()
try:
query = session.query(Organ... | the_stack_v2_python_sparse | knoweak/api/resources/organization.py | psvaiter/knoweak-api | train | 0 |
d18644e26c23e697de22a4815419a5e4dae53723 | [
"_LOG.info('Create the DB schema for: %s', engine)\nself._engine = engine\nself._meta = MetaData()\nself.experiment = Table('experiment', self._meta, Column('exp_id', String(255), nullable=False), Column('description', String(1024)), Column('root_env_config', String(1024), nullable=False), Column('git_repo', String... | <|body_start_0|>
_LOG.info('Create the DB schema for: %s', engine)
self._engine = engine
self._meta = MetaData()
self.experiment = Table('experiment', self._meta, Column('exp_id', String(255), nullable=False), Column('description', String(1024)), Column('root_env_config', String(1024), n... | A class to define and create the DB schema. | DbSchema | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DbSchema:
"""A class to define and create the DB schema."""
def __init__(self, engine: Engine):
"""Declare the SQLAlchemy schema for the database."""
<|body_0|>
def create(self) -> 'DbSchema':
"""Create the DB schema."""
<|body_1|>
def __repr__(self)... | stack_v2_sparse_classes_36k_train_016784 | 6,611 | permissive | [
{
"docstring": "Declare the SQLAlchemy schema for the database.",
"name": "__init__",
"signature": "def __init__(self, engine: Engine)"
},
{
"docstring": "Create the DB schema.",
"name": "create",
"signature": "def create(self) -> 'DbSchema'"
},
{
"docstring": "Produce a string w... | 3 | stack_v2_sparse_classes_30k_train_008217 | Implement the Python class `DbSchema` described below.
Class description:
A class to define and create the DB schema.
Method signatures and docstrings:
- def __init__(self, engine: Engine): Declare the SQLAlchemy schema for the database.
- def create(self) -> 'DbSchema': Create the DB schema.
- def __repr__(self) -> ... | Implement the Python class `DbSchema` described below.
Class description:
A class to define and create the DB schema.
Method signatures and docstrings:
- def __init__(self, engine: Engine): Declare the SQLAlchemy schema for the database.
- def create(self) -> 'DbSchema': Create the DB schema.
- def __repr__(self) -> ... | 0db80043dad256d77dc4c2b4fc54aa0b0aa2597f | <|skeleton|>
class DbSchema:
"""A class to define and create the DB schema."""
def __init__(self, engine: Engine):
"""Declare the SQLAlchemy schema for the database."""
<|body_0|>
def create(self) -> 'DbSchema':
"""Create the DB schema."""
<|body_1|>
def __repr__(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DbSchema:
"""A class to define and create the DB schema."""
def __init__(self, engine: Engine):
"""Declare the SQLAlchemy schema for the database."""
_LOG.info('Create the DB schema for: %s', engine)
self._engine = engine
self._meta = MetaData()
self.experiment = T... | the_stack_v2_python_sparse | mlos_bench/mlos_bench/storage/sql/schema.py | microsoft/MLOS | train | 109 |
138338e54292d88b340bd40a27dcc7fe96038bf9 | [
"settings.addListsToRepository('skeinforge_tools.craft_plugins.home.html', '', self)\nself.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Home', self, '')\nself.openWikiManualHelpPage = settings.HelpPage().getOpenFromAbsolute('http://www.bits... | <|body_start_0|>
settings.addListsToRepository('skeinforge_tools.craft_plugins.home.html', '', self)
self.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Home', self, '')
self.openWikiManualHelpPage = settings.HelpPage().ge... | A class to handle the home settings. | HomeRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HomeRepository:
"""A class to handle the home settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Home button has been clicked."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_016785 | 8,710 | no_license | [
{
"docstring": "Set the default settings, execute title & settings fileName.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Home button has been clicked.",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014193 | Implement the Python class `HomeRepository` described below.
Class description:
A class to handle the home settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Home button has been clicked. | Implement the Python class `HomeRepository` described below.
Class description:
A class to handle the home settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Home button has been clicked.
<|skeleton|>
class HomeRepositor... | fd69d8e856780c826386dc973ceabcc03623f3e8 | <|skeleton|>
class HomeRepository:
"""A class to handle the home settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Home button has been clicked."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HomeRepository:
"""A class to handle the home settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
settings.addListsToRepository('skeinforge_tools.craft_plugins.home.html', '', self)
self.fileNameInput = settings.FileNameInput().getFr... | the_stack_v2_python_sparse | skeinforge_tools/craft_plugins/home.py | bmander/skeinforge | train | 34 |
19bdb62449eb1c3a44ee0e075d6c331c3a4d6ce8 | [
"self.snmp_object = snmp_object\ntest_oid = '.1.3.6.1.2.1.1.1.0'\nsuper().__init__(snmp_object, test_oid, tags=['system'])",
"data_dict = defaultdict(lambda: defaultdict(dict))\nfinal = {}\ngetvalues = [0]\nkey = 0\noidroot = '.1.3.6.1.2.1.1'\nfor node in range(1, 7):\n oid = '{}.{}.0'.format(oidroot, node)\n ... | <|body_start_0|>
self.snmp_object = snmp_object
test_oid = '.1.3.6.1.2.1.1.1.0'
super().__init__(snmp_object, test_oid, tags=['system'])
<|end_body_0|>
<|body_start_1|>
data_dict = defaultdict(lambda: defaultdict(dict))
final = {}
getvalues = [0]
key = 0
... | Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a response to the OID, False if not. system: Returns all relevant system information ... | Snmpv2Query | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Snmpv2Query:
"""Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a response to the OID, False if not. system: R... | stack_v2_sparse_classes_36k_train_016786 | 2,947 | permissive | [
{
"docstring": "Function for intializing the class. Args: snmp_object: SNMP Interact class object from snmp_manager.py Returns: None",
"name": "__init__",
"signature": "def __init__(self, snmp_object)"
},
{
"docstring": "Get system data from device. Args: None Returns: final: Final results",
... | 2 | null | Implement the Python class `Snmpv2Query` described below.
Class description:
Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a respo... | Implement the Python class `Snmpv2Query` described below.
Class description:
Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a respo... | ae82589fbbab77fef6d6be09c1fcca5846f595a8 | <|skeleton|>
class Snmpv2Query:
"""Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a response to the OID, False if not. system: R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Snmpv2Query:
"""Class interacts with devices supporting SNMPv2-MIB. Args: None Returns: None Key Methods: supported: Queries the device to determine whether the MIB is supported using a known OID defined in the MIB. Returns True if the device returns a response to the OID, False if not. system: Returns all re... | the_stack_v2_python_sparse | switchmap/snmp/mib_snmpv2.py | PalisadoesFoundation/switchmap-ng | train | 8 |
ed4eb0bcfc0bae64639a6bec0c52ce12cadc8aa9 | [
"self.kids = dict()\nself.val = None\nself.isWord = False",
"current_node = self\nfor idx, letter in enumerate(word):\n if letter not in current_node.kids:\n current_node.kids[letter] = WordDictionary()\n current_node.kids[letter].val = letter\n current_node = current_node.kids[letter]\n if... | <|body_start_0|>
self.kids = dict()
self.val = None
self.isWord = False
<|end_body_0|>
<|body_start_1|>
current_node = self
for idx, letter in enumerate(word):
if letter not in current_node.kids:
current_node.kids[letter] = WordDictionary()
... | WordDictionary | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDictionary:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def addWord(self, word):
"""Adds a word into the data structure. :type word: str :rtype: void"""
<|body_1|>
def search(self, word):
"""Returns if the word i... | stack_v2_sparse_classes_36k_train_016787 | 2,131 | permissive | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Adds a word into the data structure. :type word: str :rtype: void",
"name": "addWord",
"signature": "def addWord(self, word)"
},
{
"docstring": "Returns... | 3 | stack_v2_sparse_classes_30k_train_001111 | Implement the Python class `WordDictionary` described below.
Class description:
Implement the WordDictionary class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def addWord(self, word): Adds a word into the data structure. :type word: str :rtype: void
- def search(sel... | Implement the Python class `WordDictionary` described below.
Class description:
Implement the WordDictionary class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def addWord(self, word): Adds a word into the data structure. :type word: str :rtype: void
- def search(sel... | f462b66ae849f4332a4b150f206dd49c7519e83b | <|skeleton|>
class WordDictionary:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def addWord(self, word):
"""Adds a word into the data structure. :type word: str :rtype: void"""
<|body_1|>
def search(self, word):
"""Returns if the word i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDictionary:
def __init__(self):
"""Initialize your data structure here."""
self.kids = dict()
self.val = None
self.isWord = False
def addWord(self, word):
"""Adds a word into the data structure. :type word: str :rtype: void"""
current_node = self
... | the_stack_v2_python_sparse | LeetCode/DataStructure/trie/word_dictionary.py | hooyao/Coding-Py3 | train | 0 | |
b2f0faf6733885316a14c0f06744044a03c59255 | [
"task_id = request.GET.get('task_id', '')\nif not task_id:\n error_msg = 'task_id invalid.'\n return api_error(status.HTTP_400_BAD_REQUEST, error_msg)\nresp = query_dtable_io_status(task_id)\nif resp.status_code == 400:\n error_msg = 'task_id invalid.'\n return api_error(status.HTTP_400_BAD_REQUEST, err... | <|body_start_0|>
task_id = request.GET.get('task_id', '')
if not task_id:
error_msg = 'task_id invalid.'
return api_error(status.HTTP_400_BAD_REQUEST, error_msg)
resp = query_dtable_io_status(task_id)
if resp.status_code == 400:
error_msg = 'task_id in... | DTableIOStatus | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DTableIOStatus:
def get(self, request):
"""Get task status by task id :param request: :return:"""
<|body_0|>
def delete(self, request):
"""Delete task by task_id :param request: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
task_id = requ... | stack_v2_sparse_classes_36k_train_016788 | 12,942 | no_license | [
{
"docstring": "Get task status by task id :param request: :return:",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Delete task by task_id :param request: :return:",
"name": "delete",
"signature": "def delete(self, request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019649 | Implement the Python class `DTableIOStatus` described below.
Class description:
Implement the DTableIOStatus class.
Method signatures and docstrings:
- def get(self, request): Get task status by task id :param request: :return:
- def delete(self, request): Delete task by task_id :param request: :return: | Implement the Python class `DTableIOStatus` described below.
Class description:
Implement the DTableIOStatus class.
Method signatures and docstrings:
- def get(self, request): Get task status by task id :param request: :return:
- def delete(self, request): Delete task by task_id :param request: :return:
<|skeleton|>... | 3d08b64bf2a3724326eab9dfa771863bc6743bc2 | <|skeleton|>
class DTableIOStatus:
def get(self, request):
"""Get task status by task id :param request: :return:"""
<|body_0|>
def delete(self, request):
"""Delete task by task_id :param request: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DTableIOStatus:
def get(self, request):
"""Get task status by task id :param request: :return:"""
task_id = request.GET.get('task_id', '')
if not task_id:
error_msg = 'task_id invalid.'
return api_error(status.HTTP_400_BAD_REQUEST, error_msg)
resp = quer... | the_stack_v2_python_sparse | seahub/api2/endpoints/dtable_io.py | flazx/dtable-web | train | 0 | |
9aaaac180142af446bacd842649be82a7963827e | [
"if vals.get('tax_ids'):\n if len(vals.get('tax_ids')[0][2]) > 1:\n raise UserError('A product can only have one tax')\nreturn super(InheritAccountInvoiceLine, self).create(vals)",
"if vals.get('tax_ids'):\n if len(vals.get('tax_ids')[0][2]) > 1:\n raise UserError('A product can only have one ... | <|body_start_0|>
if vals.get('tax_ids'):
if len(vals.get('tax_ids')[0][2]) > 1:
raise UserError('A product can only have one tax')
return super(InheritAccountInvoiceLine, self).create(vals)
<|end_body_0|>
<|body_start_1|>
if vals.get('tax_ids'):
if len(va... | InheritAccountInvoiceLine | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InheritAccountInvoiceLine:
def create(self, vals):
"""Inheriting the core function, create to validate to stop adding two or more taxes to the product"""
<|body_0|>
def write(self, vals):
"""Inheriting the core function, write to validate to stop adding two or more t... | stack_v2_sparse_classes_36k_train_016789 | 1,589 | no_license | [
{
"docstring": "Inheriting the core function, create to validate to stop adding two or more taxes to the product",
"name": "create",
"signature": "def create(self, vals)"
},
{
"docstring": "Inheriting the core function, write to validate to stop adding two or more taxes to the product",
"nam... | 2 | stack_v2_sparse_classes_30k_train_001238 | Implement the Python class `InheritAccountInvoiceLine` described below.
Class description:
Implement the InheritAccountInvoiceLine class.
Method signatures and docstrings:
- def create(self, vals): Inheriting the core function, create to validate to stop adding two or more taxes to the product
- def write(self, vals)... | Implement the Python class `InheritAccountInvoiceLine` described below.
Class description:
Implement the InheritAccountInvoiceLine class.
Method signatures and docstrings:
- def create(self, vals): Inheriting the core function, create to validate to stop adding two or more taxes to the product
- def write(self, vals)... | 9de7a2ce6a17d43107ee08085c9f83a525382798 | <|skeleton|>
class InheritAccountInvoiceLine:
def create(self, vals):
"""Inheriting the core function, create to validate to stop adding two or more taxes to the product"""
<|body_0|>
def write(self, vals):
"""Inheriting the core function, write to validate to stop adding two or more t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InheritAccountInvoiceLine:
def create(self, vals):
"""Inheriting the core function, create to validate to stop adding two or more taxes to the product"""
if vals.get('tax_ids'):
if len(vals.get('tax_ids')[0][2]) > 1:
raise UserError('A product can only have one tax'... | the_stack_v2_python_sparse | custom_taxes/models/custom_invoice.py | EshangAllion/cenmetrix_v12 | train | 0 | |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([bart_layer.self_attn.q_proj.weight, bart_layer.self_attn.k_proj.weight, bart_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([bart_layer.self_attn.q_proj.bias, bart_layer.self_attn.k_proj.bias, bart_layer.self_attn... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([bart_layer.self_attn.q_proj.weight, bart_layer.self_attn.k_proj.weight, bart_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([bart_layer.self_attn.q_proj.bias, bart_layer.self_attn... | BartEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BartEncoderLayerBetterTransformer:
def __init__(self, bart_layer, config):
"""A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation. Args: bart_layer (`torch.nn.Module`): The original `BartEncoderLayer` where the weights needs to be retrieved."""
... | stack_v2_sparse_classes_36k_train_016790 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation. Args: bart_layer (`torch.nn.Module`): The original `BartEncoderLayer` where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, bart_layer, config)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_004157 | Implement the Python class `BartEncoderLayerBetterTransformer` described below.
Class description:
Implement the BartEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, bart_layer, config): A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation.... | Implement the Python class `BartEncoderLayerBetterTransformer` described below.
Class description:
Implement the BartEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, bart_layer, config): A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation.... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class BartEncoderLayerBetterTransformer:
def __init__(self, bart_layer, config):
"""A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation. Args: bart_layer (`torch.nn.Module`): The original `BartEncoderLayer` where the weights needs to be retrieved."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BartEncoderLayerBetterTransformer:
def __init__(self, bart_layer, config):
"""A simple conversion of the `BartEncoderLayer` to its `BetterTransformer` implementation. Args: bart_layer (`torch.nn.Module`): The original `BartEncoderLayer` where the weights needs to be retrieved."""
super().__ini... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
07f361369e2d9dd9a11ce9a1eda5577e116772e9 | [
"if not self._run_id:\n if self.config.pipelineRunId:\n self._run_id = str(self.config.pipelineRunId.__root__)\n else:\n self._run_id = str(uuid.uuid4())\nreturn self._run_id",
"if self.config.ingestionPipelineFQN:\n if state in (PipelineState.queued, PipelineState.running):\n pipeli... | <|body_start_0|>
if not self._run_id:
if self.config.pipelineRunId:
self._run_id = str(self.config.pipelineRunId.__root__)
else:
self._run_id = str(uuid.uuid4())
return self._run_id
<|end_body_0|>
<|body_start_1|>
if self.config.ingestionP... | Helper methods to manage IngestionPipeline status and workflow run ID | WorkflowStatusMixin | [
"Apache-2.0",
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkflowStatusMixin:
"""Helper methods to manage IngestionPipeline status and workflow run ID"""
def run_id(self) -> str:
"""If the config does not have an informed run id, we'll generate and assign one here."""
<|body_0|>
def set_ingestion_pipeline_status(self, state: P... | stack_v2_sparse_classes_36k_train_016791 | 3,278 | permissive | [
{
"docstring": "If the config does not have an informed run id, we'll generate and assign one here.",
"name": "run_id",
"signature": "def run_id(self) -> str"
},
{
"docstring": "Method to set the pipeline status of current ingestion pipeline",
"name": "set_ingestion_pipeline_status",
"si... | 3 | stack_v2_sparse_classes_30k_train_005188 | Implement the Python class `WorkflowStatusMixin` described below.
Class description:
Helper methods to manage IngestionPipeline status and workflow run ID
Method signatures and docstrings:
- def run_id(self) -> str: If the config does not have an informed run id, we'll generate and assign one here.
- def set_ingestio... | Implement the Python class `WorkflowStatusMixin` described below.
Class description:
Helper methods to manage IngestionPipeline status and workflow run ID
Method signatures and docstrings:
- def run_id(self) -> str: If the config does not have an informed run id, we'll generate and assign one here.
- def set_ingestio... | 8d5f9a2d49ab8f9e85ccf058cb02c2fda287afc6 | <|skeleton|>
class WorkflowStatusMixin:
"""Helper methods to manage IngestionPipeline status and workflow run ID"""
def run_id(self) -> str:
"""If the config does not have an informed run id, we'll generate and assign one here."""
<|body_0|>
def set_ingestion_pipeline_status(self, state: P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkflowStatusMixin:
"""Helper methods to manage IngestionPipeline status and workflow run ID"""
def run_id(self) -> str:
"""If the config does not have an informed run id, we'll generate and assign one here."""
if not self._run_id:
if self.config.pipelineRunId:
... | the_stack_v2_python_sparse | govern/data-meta/OpenMetadata/ingestion/src/metadata/workflow/workflow_status_mixin.py | alldatacenter/alldata | train | 774 |
773cca7cfe72067d2b3179a17cf1aaf969be0f9a | [
"self.num_rnn_layers = hyper_parameters['model'].get('num_rnn_layers', 1)\nself.rnn_type = hyper_parameters['model'].get('rnn_type', 'LSTM')\nself.rnn_units = hyper_parameters['model'].get('rnn_units', 512)\nself.crf_mode = hyper_parameters['model'].get('crf_mode', 'reg')\nself.supports_masking = hyper_parameters['... | <|body_start_0|>
self.num_rnn_layers = hyper_parameters['model'].get('num_rnn_layers', 1)
self.rnn_type = hyper_parameters['model'].get('rnn_type', 'LSTM')
self.rnn_units = hyper_parameters['model'].get('rnn_units', 512)
self.crf_mode = hyper_parameters['model'].get('crf_mode', 'reg')
... | BilstmCRFGraph | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BilstmCRFGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_016792 | 3,345 | permissive | [
{
"docstring": "初始化 :param hyper_parameters: json，超参",
"name": "__init__",
"signature": "def __init__(self, hyper_parameters)"
},
{
"docstring": "构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl",
"name": "create_model",
"signature": "def create_mod... | 3 | stack_v2_sparse_classes_30k_train_020841 | Implement the Python class `BilstmCRFGraph` described below.
Class description:
Implement the BilstmCRFGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper para... | Implement the Python class `BilstmCRFGraph` described below.
Class description:
Implement the BilstmCRFGraph class.
Method signatures and docstrings:
- def __init__(self, hyper_parameters): 初始化 :param hyper_parameters: json，超参
- def create_model(self, hyper_parameters): 构建神经网络 :param hyper_parameters:json, hyper para... | 1d7b8f9938cb8b6d7744e9caabc3eb41c8891283 | <|skeleton|>
class BilstmCRFGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
<|body_0|>
def create_model(self, hyper_parameters):
"""构建神经网络 :param hyper_parameters:json, hyper parameters of network :return: tensor, moedl"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BilstmCRFGraph:
def __init__(self, hyper_parameters):
"""初始化 :param hyper_parameters: json，超参"""
self.num_rnn_layers = hyper_parameters['model'].get('num_rnn_layers', 1)
self.rnn_type = hyper_parameters['model'].get('rnn_type', 'LSTM')
self.rnn_units = hyper_parameters['model']... | the_stack_v2_python_sparse | macropodus/network/graph/bilstm_crf.py | a627414850/Macropodus | train | 0 | |
6f64efdb14998a2bfd728bdcdedcea2ef27de6f6 | [
"return_type = self.second\nwhile isinstance(return_type, ComplexType):\n return_type = return_type.second\nreturn return_type",
"arguments = [self.first]\nremaining_type = self.second\nwhile isinstance(remaining_type, ComplexType):\n arguments.append(remaining_type.first)\n remaining_type = remaining_ty... | <|body_start_0|>
return_type = self.second
while isinstance(return_type, ComplexType):
return_type = return_type.second
return return_type
<|end_body_0|>
<|body_start_1|>
arguments = [self.first]
remaining_type = self.second
while isinstance(remaining_type, C... | In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return_type`` and ``argument_type`` functions to ``ComplexType``. | ComplexType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComplexType:
"""In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return_type`` and ``argument_type`` functions... | stack_v2_sparse_classes_36k_train_016793 | 36,351 | permissive | [
{
"docstring": "Gives the final return type for this function. If the function takes a single argument, this is just ``self.second``. If the function takes multiple arguments and returns a basic type, this should be the final ``.second`` after following all complex types. That is the implementation here in the ... | 3 | null | Implement the Python class `ComplexType` described below.
Class description:
In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return... | Implement the Python class `ComplexType` described below.
Class description:
In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return... | ccf60824b28f0ce8ceda44a7ce52a0d117669115 | <|skeleton|>
class ComplexType:
"""In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return_type`` and ``argument_type`` functions... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComplexType:
"""In NLTK, a ``ComplexType`` is a function. These functions are curried, so if you need multiple arguments for your function you nest ``ComplexTypes``. That currying makes things difficult for us, and we mitigate the problems by adding ``return_type`` and ``argument_type`` functions to ``Complex... | the_stack_v2_python_sparse | allennlp/allennlp/semparse/type_declarations/type_declaration.py | ethanjperez/convince | train | 27 |
bc7b2384045e28fe1f1254b8c95c8a36dcc45273 | [
"self.name = name\nself.required = name in all_args\nself.validators = []\nif not isinstance(types, tuple):\n types = (types,)\nfor type_ in types:\n self.validators.append(type_() if type(type_) is type else type_)",
"processed_value = value\nfor type_validator in self.validators:\n try:\n proces... | <|body_start_0|>
self.name = name
self.required = name in all_args
self.validators = []
if not isinstance(types, tuple):
types = (types,)
for type_ in types:
self.validators.append(type_() if type(type_) is type else type_)
<|end_body_0|>
<|body_start_1|>... | This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument. | ParameterType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterType:
"""This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument."""
def __init__(self, name, types, all_args):
"""Constructor. :param str name: The name of the argument :param list types: The... | stack_v2_sparse_classes_36k_train_016794 | 8,864 | permissive | [
{
"docstring": "Constructor. :param str name: The name of the argument :param list types: The list of types (validators) which have to be applied to incoming parameter :param set all_args: The list of all arguments. This is required to check if parameter is mandatory or not.",
"name": "__init__",
"signa... | 2 | stack_v2_sparse_classes_30k_train_014088 | Implement the Python class `ParameterType` described below.
Class description:
This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument.
Method signatures and docstrings:
- def __init__(self, name, types, all_args): Constructor. :param ... | Implement the Python class `ParameterType` described below.
Class description:
This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument.
Method signatures and docstrings:
- def __init__(self, name, types, all_args): Constructor. :param ... | bc0cfe3067bf1cbf26789f7443a36e7cdd2ac869 | <|skeleton|>
class ParameterType:
"""This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument."""
def __init__(self, name, types, all_args):
"""Constructor. :param str name: The name of the argument :param list types: The... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterType:
"""This class incapsulates metadata about parameter. It stores if parameter is mandatory and a list of validator and the name of the argument."""
def __init__(self, name, types, all_args):
"""Constructor. :param str name: The name of the argument :param list types: The list of type... | the_stack_v2_python_sparse | backend/api/check_params.py | omarabdalhamid/boss | train | 0 |
e5b98006f2d47e4b0183060427ccf1be69609c21 | [
"self.error = ftol\nself.iterationMax = iterations_max\nself.correct_factor = correct_factor",
"iteration = state['iteration']\nold_value = state['old_value']\nnew_value = state['new_value']\nold_parameters = state['old_parameters']\nnew_parameters = state['new_parameters']\nreturn iteration > self.iterationMax o... | <|body_start_0|>
self.error = ftol
self.iterationMax = iterations_max
self.correct_factor = correct_factor
<|end_body_0|>
<|body_start_1|>
iteration = state['iteration']
old_value = state['old_value']
new_value = state['new_value']
old_parameters = state['old_par... | The Akaike information criterion | AICCriterion | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AICCriterion:
"""The Akaike information criterion"""
def __init__(self, ftol, iterations_max, correct_factor=1.0):
"""Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol is the relative tolerance of the AIC criterion - correct_... | stack_v2_sparse_classes_36k_train_016795 | 2,400 | permissive | [
{
"docstring": "Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol is the relative tolerance of the AIC criterion - correct_factor is the modifiying factor for the weight of the parameters size",
"name": "__init__",
"signature": "def __init__(sel... | 2 | stack_v2_sparse_classes_30k_train_007707 | Implement the Python class `AICCriterion` described below.
Class description:
The Akaike information criterion
Method signatures and docstrings:
- def __init__(self, ftol, iterations_max, correct_factor=1.0): Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol ... | Implement the Python class `AICCriterion` described below.
Class description:
The Akaike information criterion
Method signatures and docstrings:
- def __init__(self, ftol, iterations_max, correct_factor=1.0): Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol ... | 3d298e908ff55340cd3612078508be0c791f63a8 | <|skeleton|>
class AICCriterion:
"""The Akaike information criterion"""
def __init__(self, ftol, iterations_max, correct_factor=1.0):
"""Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol is the relative tolerance of the AIC criterion - correct_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AICCriterion:
"""The Akaike information criterion"""
def __init__(self, ftol, iterations_max, correct_factor=1.0):
"""Initializes the criterion with a max number of iterations and an error fraction for the monotony test - ftol is the relative tolerance of the AIC criterion - correct_factor is the... | the_stack_v2_python_sparse | PyDSTool/Toolbox/optimizers/criterion/information_criteria.py | mdlama/pydstool | train | 2 |
b854e668d4929b5e271e62838ee82a045c7da417 | [
"def _byte_size(i):\n for j in range(8):\n if 1 & data[i] >> 7 - j != 1:\n return j\n return 8\n\ndef _rec(i):\n if i == len(data):\n return True\n byte_size = _byte_size(i)\n if byte_size == 0:\n return _rec(i + 1)\n if byte_size == 1 or byte_size > 4 or i + byte_s... | <|body_start_0|>
def _byte_size(i):
for j in range(8):
if 1 & data[i] >> 7 - j != 1:
return j
return 8
def _rec(i):
if i == len(data):
return True
byte_size = _byte_size(i)
if byte_size == 0:... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def validUtf8(self, data: List[int]) -> bool:
"""04/20/2020 06:37"""
<|body_0|>
def validUtf8(self, data: List[int]) -> bool:
"""10/03/2022 21:32"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def _byte_size(i):
for j in range... | stack_v2_sparse_classes_36k_train_016796 | 3,814 | no_license | [
{
"docstring": "04/20/2020 06:37",
"name": "validUtf8",
"signature": "def validUtf8(self, data: List[int]) -> bool"
},
{
"docstring": "10/03/2022 21:32",
"name": "validUtf8",
"signature": "def validUtf8(self, data: List[int]) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validUtf8(self, data: List[int]) -> bool: 04/20/2020 06:37
- def validUtf8(self, data: List[int]) -> bool: 10/03/2022 21:32 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def validUtf8(self, data: List[int]) -> bool: 04/20/2020 06:37
- def validUtf8(self, data: List[int]) -> bool: 10/03/2022 21:32
<|skeleton|>
class Solution:
def validUtf8(s... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def validUtf8(self, data: List[int]) -> bool:
"""04/20/2020 06:37"""
<|body_0|>
def validUtf8(self, data: List[int]) -> bool:
"""10/03/2022 21:32"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def validUtf8(self, data: List[int]) -> bool:
"""04/20/2020 06:37"""
def _byte_size(i):
for j in range(8):
if 1 & data[i] >> 7 - j != 1:
return j
return 8
def _rec(i):
if i == len(data):
... | the_stack_v2_python_sparse | leetcode/solved/393_UTF-8_Validation/solution.py | sungminoh/algorithms | train | 0 | |
74bc6036a6b7e0ec5031a7d1023a1b570f6948ab | [
"super().__init__()\nself.level1 = CBR(3, 16, 3, 2)\nself.sample1 = InputProjectionA(1)\nself.sample2 = InputProjectionA(2)\nself.b1 = BR(16 + 3)\nself.level2_0 = DownSamplerB(16 + 3, 64)\nself.level2 = nn.ModuleList()\nfor i in range(0, p):\n self.level2.append(DilatedParllelResidualBlockB(64, 64))\nself.b2 = B... | <|body_start_0|>
super().__init__()
self.level1 = CBR(3, 16, 3, 2)
self.sample1 = InputProjectionA(1)
self.sample2 = InputProjectionA(2)
self.b1 = BR(16 + 3)
self.level2_0 = DownSamplerB(16 + 3, 64)
self.level2 = nn.ModuleList()
for i in range(0, p):
... | This class defines the ESPNetX4-C network in the paper | ESPNetX4_Encoder | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ESPNetX4_Encoder:
"""This class defines the ESPNetX4-C network in the paper"""
def __init__(self, classes=19, p=5, q=3):
""":param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth multiplier :param q: depth multiplier"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_016797 | 44,685 | permissive | [
{
"docstring": ":param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth multiplier :param q: depth multiplier",
"name": "__init__",
"signature": "def __init__(self, classes=19, p=5, q=3)"
},
{
"docstring": ":param input: Receives the input RGB image :re... | 2 | null | Implement the Python class `ESPNetX4_Encoder` described below.
Class description:
This class defines the ESPNetX4-C network in the paper
Method signatures and docstrings:
- def __init__(self, classes=19, p=5, q=3): :param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth mult... | Implement the Python class `ESPNetX4_Encoder` described below.
Class description:
This class defines the ESPNetX4-C network in the paper
Method signatures and docstrings:
- def __init__(self, classes=19, p=5, q=3): :param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth mult... | 27272e43126a507a6d93b21cd2372f5432f61237 | <|skeleton|>
class ESPNetX4_Encoder:
"""This class defines the ESPNetX4-C network in the paper"""
def __init__(self, classes=19, p=5, q=3):
""":param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth multiplier :param q: depth multiplier"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ESPNetX4_Encoder:
"""This class defines the ESPNetX4-C network in the paper"""
def __init__(self, classes=19, p=5, q=3):
""":param classes: number of classes in the dataset. Default is 20 for the cityscapes :param p: depth multiplier :param q: depth multiplier"""
super().__init__()
... | the_stack_v2_python_sparse | model/ESPNetX4.py | Ethan-ye/Efficient-Segmentation-Networks | train | 0 |
6fa0e727342da59ddf1910e47a2e3312a0cfb782 | [
"self.config_entry = config_entry\nself.data = dict(self.config_entry.data)\nself._all_region_codes_sorted: dict[str, str] = {}\nself.regions: dict[str, dict[str, Any]] = {}\nfor name in CONST_REGIONS:\n self.regions[name] = {}\n if name not in self.data:\n self.data[name] = []",
"errors: dict[str, A... | <|body_start_0|>
self.config_entry = config_entry
self.data = dict(self.config_entry.data)
self._all_region_codes_sorted: dict[str, str] = {}
self.regions: dict[str, dict[str, Any]] = {}
for name in CONST_REGIONS:
self.regions[name] = {}
if name not in sel... | Handle a option flow for nut. | OptionsFlowHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptionsFlowHandler:
"""Handle a option flow for nut."""
def __init__(self, config_entry: config_entries.ConfigEntry) -> None:
"""Initialize options flow."""
<|body_0|>
async def async_step_init(self, user_input=None):
"""Handle options flow."""
<|body_1|>... | stack_v2_sparse_classes_36k_train_016798 | 9,354 | permissive | [
{
"docstring": "Initialize options flow.",
"name": "__init__",
"signature": "def __init__(self, config_entry: config_entries.ConfigEntry) -> None"
},
{
"docstring": "Handle options flow.",
"name": "async_step_init",
"signature": "async def async_step_init(self, user_input=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014965 | Implement the Python class `OptionsFlowHandler` described below.
Class description:
Handle a option flow for nut.
Method signatures and docstrings:
- def __init__(self, config_entry: config_entries.ConfigEntry) -> None: Initialize options flow.
- async def async_step_init(self, user_input=None): Handle options flow. | Implement the Python class `OptionsFlowHandler` described below.
Class description:
Handle a option flow for nut.
Method signatures and docstrings:
- def __init__(self, config_entry: config_entries.ConfigEntry) -> None: Initialize options flow.
- async def async_step_init(self, user_input=None): Handle options flow.
... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class OptionsFlowHandler:
"""Handle a option flow for nut."""
def __init__(self, config_entry: config_entries.ConfigEntry) -> None:
"""Initialize options flow."""
<|body_0|>
async def async_step_init(self, user_input=None):
"""Handle options flow."""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OptionsFlowHandler:
"""Handle a option flow for nut."""
def __init__(self, config_entry: config_entries.ConfigEntry) -> None:
"""Initialize options flow."""
self.config_entry = config_entry
self.data = dict(self.config_entry.data)
self._all_region_codes_sorted: dict[str, s... | the_stack_v2_python_sparse | homeassistant/components/nina/config_flow.py | home-assistant/core | train | 35,501 |
0199f93f852d0f1dad8dce51c4bd2c2f64898011 | [
"timestamp_string = plist_key.get(plist_value_name, None)\nif not timestamp_string:\n return None\ntry:\n timestamp = float(timestamp_string)\nexcept (TypeError, ValueError):\n parser_mediator.ProduceExtractionWarning('unable to convert Cocoa timestamp: {0:s} to a floating-point value'.format(timestamp_str... | <|body_start_0|>
timestamp_string = plist_key.get(plist_value_name, None)
if not timestamp_string:
return None
try:
timestamp = float(timestamp_string)
except (TypeError, ValueError):
parser_mediator.ProduceExtractionWarning('unable to convert Cocoa ti... | Plist parser plugin for Safari history plist files. | SafariHistoryPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SafariHistoryPlugin:
"""Plist parser plugin for Safari history plist files."""
def _GetDateTimeValueFromTimestamp(self, parser_mediator, plist_key, plist_value_name):
"""Retrieves a date and time value from a Cocoa timestamp. Args: parser_mediator (ParserMediator): mediates interacti... | stack_v2_sparse_classes_36k_train_016799 | 3,790 | permissive | [
{
"docstring": "Retrieves a date and time value from a Cocoa timestamp. Args: parser_mediator (ParserMediator): mediates interactions between parsers and other components, such as storage and dfVFS. plist_key (object): plist key. plist_value_name (str): name of the value in the plist key. Returns: dfdatetime.Ti... | 2 | null | Implement the Python class `SafariHistoryPlugin` described below.
Class description:
Plist parser plugin for Safari history plist files.
Method signatures and docstrings:
- def _GetDateTimeValueFromTimestamp(self, parser_mediator, plist_key, plist_value_name): Retrieves a date and time value from a Cocoa timestamp. A... | Implement the Python class `SafariHistoryPlugin` described below.
Class description:
Plist parser plugin for Safari history plist files.
Method signatures and docstrings:
- def _GetDateTimeValueFromTimestamp(self, parser_mediator, plist_key, plist_value_name): Retrieves a date and time value from a Cocoa timestamp. A... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class SafariHistoryPlugin:
"""Plist parser plugin for Safari history plist files."""
def _GetDateTimeValueFromTimestamp(self, parser_mediator, plist_key, plist_value_name):
"""Retrieves a date and time value from a Cocoa timestamp. Args: parser_mediator (ParserMediator): mediates interacti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SafariHistoryPlugin:
"""Plist parser plugin for Safari history plist files."""
def _GetDateTimeValueFromTimestamp(self, parser_mediator, plist_key, plist_value_name):
"""Retrieves a date and time value from a Cocoa timestamp. Args: parser_mediator (ParserMediator): mediates interactions between p... | the_stack_v2_python_sparse | plaso/parsers/plist_plugins/safari_history.py | log2timeline/plaso | train | 1,506 |
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