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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8fc37e7d94ee6be04d8679cf32a5c470c31fe52e | [
"self.steps = int(math.log10(n) / math.log10(2))\nA = {i: x for i, x in enumerate(parent)}\nself.jump = [A]\nfor _ in xrange(self.steps):\n B = {}\n for i in A:\n if A[i] in A:\n B[i] = A[A[i]]\n self.jump += (B,)\n A = B",
"steps = self.steps\nwhile k and node != -1:\n if k >= 1 ... | <|body_start_0|>
self.steps = int(math.log10(n) / math.log10(2))
A = {i: x for i, x in enumerate(parent)}
self.jump = [A]
for _ in xrange(self.steps):
B = {}
for i in A:
if A[i] in A:
B[i] = A[A[i]]
self.jump += (B,)... | TreeAncestor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreeAncestor:
def __init__(self, n, parent):
""":type n: int :type parent: List[int]"""
<|body_0|>
def getKthAncestor(self, node, k):
""":type node: int :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.steps = int(math.l... | stack_v2_sparse_classes_36k_train_004300 | 1,889 | no_license | [
{
"docstring": ":type n: int :type parent: List[int]",
"name": "__init__",
"signature": "def __init__(self, n, parent)"
},
{
"docstring": ":type node: int :type k: int :rtype: int",
"name": "getKthAncestor",
"signature": "def getKthAncestor(self, node, k)"
}
] | 2 | null | Implement the Python class `TreeAncestor` described below.
Class description:
Implement the TreeAncestor class.
Method signatures and docstrings:
- def __init__(self, n, parent): :type n: int :type parent: List[int]
- def getKthAncestor(self, node, k): :type node: int :type k: int :rtype: int | Implement the Python class `TreeAncestor` described below.
Class description:
Implement the TreeAncestor class.
Method signatures and docstrings:
- def __init__(self, n, parent): :type n: int :type parent: List[int]
- def getKthAncestor(self, node, k): :type node: int :type k: int :rtype: int
<|skeleton|>
class Tree... | edff905f63ab95cdd40447b27a9c449c9cefec37 | <|skeleton|>
class TreeAncestor:
def __init__(self, n, parent):
""":type n: int :type parent: List[int]"""
<|body_0|>
def getKthAncestor(self, node, k):
""":type node: int :type k: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreeAncestor:
def __init__(self, n, parent):
""":type n: int :type parent: List[int]"""
self.steps = int(math.log10(n) / math.log10(2))
A = {i: x for i, x in enumerate(parent)}
self.jump = [A]
for _ in xrange(self.steps):
B = {}
for i in A:
... | the_stack_v2_python_sparse | _1483_Kth_Ancestor_of_a_Tree_Node.py | mingweihe/leetcode | train | 3 | |
701af51cbd6221f3aaf62a315e4e3b4b57fa6ccc | [
"logits = tf.constant([[0.1, 0.2, 0.7], [0.5, 0.2, 0.3], [0.2, 0.2, 0.6]])\nlabels = tf.constant([2, 0, 1])\noutput = tf_metrics.accuracy(logits, labels)\nself.assertAllClose(output, 0.6666667)",
"logits = tf.constant([[0.1, 0.2, 0.7], [0.5, 0.2, 0.3], [0.6, 0.1, 0.3], [0.2, 0.3, 0.5], [0.2, 0.5, 0.3], [0.2, 0.2,... | <|body_start_0|>
logits = tf.constant([[0.1, 0.2, 0.7], [0.5, 0.2, 0.3], [0.2, 0.2, 0.6]])
labels = tf.constant([2, 0, 1])
output = tf_metrics.accuracy(logits, labels)
self.assertAllClose(output, 0.6666667)
<|end_body_0|>
<|body_start_1|>
logits = tf.constant([[0.1, 0.2, 0.7], [... | tf metrics utils unittest | TFMetricUtilsTest | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFMetricUtilsTest:
"""tf metrics utils unittest"""
def test_accuracy(self):
"""test accuracy"""
<|body_0|>
def test_confusion_matrix(self):
"""test confusion matrix"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
logits = tf.constant([[0.1, 0.2,... | stack_v2_sparse_classes_36k_train_004301 | 1,680 | permissive | [
{
"docstring": "test accuracy",
"name": "test_accuracy",
"signature": "def test_accuracy(self)"
},
{
"docstring": "test confusion matrix",
"name": "test_confusion_matrix",
"signature": "def test_confusion_matrix(self)"
}
] | 2 | null | Implement the Python class `TFMetricUtilsTest` described below.
Class description:
tf metrics utils unittest
Method signatures and docstrings:
- def test_accuracy(self): test accuracy
- def test_confusion_matrix(self): test confusion matrix | Implement the Python class `TFMetricUtilsTest` described below.
Class description:
tf metrics utils unittest
Method signatures and docstrings:
- def test_accuracy(self): test accuracy
- def test_confusion_matrix(self): test confusion matrix
<|skeleton|>
class TFMetricUtilsTest:
"""tf metrics utils unittest"""
... | 7eb4e3be578a680737616efff6858d280595ff48 | <|skeleton|>
class TFMetricUtilsTest:
"""tf metrics utils unittest"""
def test_accuracy(self):
"""test accuracy"""
<|body_0|>
def test_confusion_matrix(self):
"""test confusion matrix"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFMetricUtilsTest:
"""tf metrics utils unittest"""
def test_accuracy(self):
"""test accuracy"""
logits = tf.constant([[0.1, 0.2, 0.7], [0.5, 0.2, 0.3], [0.2, 0.2, 0.6]])
labels = tf.constant([2, 0, 1])
output = tf_metrics.accuracy(logits, labels)
self.assertAllClos... | the_stack_v2_python_sparse | delta/utils/metrics/tf_metrics_test.py | luffywalf/delta | train | 1 |
52de90c9239df0a5c356aa3a10c15529dbf13a8f | [
"self.address = address\nself.is_alert_auditing_enabled = is_alert_auditing_enabled\nself.is_cluster_auditing_enabled = is_cluster_auditing_enabled\nself.is_data_protection_enabled = is_data_protection_enabled\nself.is_filer_auditing_enabled = is_filer_auditing_enabled\nself.is_ssh_log_enabled = is_ssh_log_enabled\... | <|body_start_0|>
self.address = address
self.is_alert_auditing_enabled = is_alert_auditing_enabled
self.is_cluster_auditing_enabled = is_cluster_auditing_enabled
self.is_data_protection_enabled = is_data_protection_enabled
self.is_filer_auditing_enabled = is_filer_auditing_enable... | Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server. is_alert_auditing_enabled (bool): Specifies if cohesity alert should be sent to ... | OldSyslogServer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OldSyslogServer:
"""Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server. is_alert_auditing_enabled (bool): Spe... | stack_v2_sparse_classes_36k_train_004302 | 5,035 | permissive | [
{
"docstring": "Constructor for the OldSyslogServer class",
"name": "__init__",
"signature": "def __init__(self, address=None, is_alert_auditing_enabled=None, is_cluster_auditing_enabled=None, is_data_protection_enabled=None, is_filer_auditing_enabled=None, is_ssh_log_enabled=None, name=None, port=None,... | 2 | stack_v2_sparse_classes_30k_train_001353 | Implement the Python class `OldSyslogServer` described below.
Class description:
Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server... | Implement the Python class `OldSyslogServer` described below.
Class description:
Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class OldSyslogServer:
"""Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server. is_alert_auditing_enabled (bool): Spe... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OldSyslogServer:
"""Implementation of the 'OldSyslogServer' model. Specifies the syslog servers configuration to upload Cluster audit logs and filer audit logs. Attributes: address (string, required): Specifies the IP address or hostname of the syslog server. is_alert_auditing_enabled (bool): Specifies if coh... | the_stack_v2_python_sparse | cohesity_management_sdk/models/old_syslog_server.py | cohesity/management-sdk-python | train | 24 |
f00defa699fd87c608a01f9856165bda5e4a0fc3 | [
"TrainerMixin.__init__(self)\nself.estimator = estimator\nself.file_path = file_path\nself.k = k",
"mask_kgb = y != -1\nX_kgb, y_kgb = (X[mask_kgb], y[mask_kgb])\nself.estimator.fit(X_kgb, y_kgb)\npred_cut = pd.qcut(self.estimator.predict_proba(X)[:, 1], self.k, labels=False)\nfor i in range(self.k):\n mask = ... | <|body_start_0|>
TrainerMixin.__init__(self)
self.estimator = estimator
self.file_path = file_path
self.k = k
<|end_body_0|>
<|body_start_1|>
mask_kgb = y != -1
X_kgb, y_kgb = (X[mask_kgb], y[mask_kgb])
self.estimator.fit(X_kgb, y_kgb)
pred_cut = pd.qcut(... | 重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。 | ReWeighting | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReWeighting:
"""重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。"""
def __init__(self, estimator, file_path: str=None, k: int=10):
"""初始化函数 :param estimato... | stack_v2_sparse_classes_36k_train_004303 | 17,175 | no_license | [
{
"docstring": "初始化函数 :param estimator: 学习器 :param file_path: 最终建模使用样本输出路径 :param k: 分箱数量",
"name": "__init__",
"signature": "def __init__(self, estimator, file_path: str=None, k: int=10)"
},
{
"docstring": "拟合学习器 :param X: 包括通过样本和拒绝样本 :param y: -1代表拒绝样本，0,1代表通过样本 :return:",
"name": "fit",
... | 2 | stack_v2_sparse_classes_30k_train_018035 | Implement the Python class `ReWeighting` described below.
Class description:
重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。
Method signatures and docstrings:
- def __init__(self, estimato... | Implement the Python class `ReWeighting` described below.
Class description:
重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。
Method signatures and docstrings:
- def __init__(self, estimato... | 1634ac69e8616f85c4233039e2d40246149a1617 | <|skeleton|>
class ReWeighting:
"""重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。"""
def __init__(self, estimator, file_path: str=None, k: int=10):
"""初始化函数 :param estimato... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReWeighting:
"""重新加权法 step 1. 构建KGB模型，并对全量样本打分，得到P(bad)。 step 2. 将全量样本按P(bad)升序排列，分箱统计每箱中的放贷和拒绝样本数。 step 3. 计算每个分箱中放贷好坏样本的权重，weight = (reject + accept) / accept。 step 4. 引入样本权重，利用放贷好坏样本构建KGB模型。"""
def __init__(self, estimator, file_path: str=None, k: int=10):
"""初始化函数 :param estimator: 学习器 :param... | the_stack_v2_python_sparse | model_training/RITrainer.py | pengliang1226/model_procedure | train | 0 |
338efbda77c256534607e00a3fd209eef6d62c93 | [
"kwargs = self.filter_sk_params(Model.predict, kwargs)\nprobas = self.model.predict(x, **kwargs)\nreturn probas",
"kwargs = self.filter_sk_params(Model.predict, kwargs)\nprobas = self.model.predict(x, **kwargs)\nreturn np.argmax(probas, axis=1)"
] | <|body_start_0|>
kwargs = self.filter_sk_params(Model.predict, kwargs)
probas = self.model.predict(x, **kwargs)
return probas
<|end_body_0|>
<|body_start_1|>
kwargs = self.filter_sk_params(Model.predict, kwargs)
probas = self.model.predict(x, **kwargs)
return np.argmax(p... | Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search methods). | FunctionalKerasClassifier | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search metho... | stack_v2_sparse_classes_36k_train_004304 | 7,877 | permissive | [
{
"docstring": "Predict classes from features. Args: x: np.array or scipy.sparse.*matrix array of features **kwargs: additional keyword arguments Returns: y_pred: np.array 2-D array of class predicted probabilities",
"name": "predict_proba",
"signature": "def predict_proba(self, x, **kwargs)"
},
{
... | 2 | null | Implement the Python class `FunctionalKerasClassifier` described below.
Class description:
Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the sci... | Implement the Python class `FunctionalKerasClassifier` described below.
Class description:
Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the sci... | dea327aa9e7ef7f7bca5a6c225dbdca1077a06e9 | <|skeleton|>
class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search metho... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FunctionalKerasClassifier:
"""Helper scikit-learn wrapper for a Keras model. The default KerasClassifier's predict() method does not work for functional Keras models (https://github.com/fchollet/keras/issues/2524); this breaks using this wrapper with the scikit-learn framework (e.g., search methods)."""
... | the_stack_v2_python_sparse | sparse_data/exp_framework/dnn.py | Tarkiyah/googleResearch | train | 11 |
620e6244d1969215d76512ea24d19e9492a8e3c3 | [
"\"\"\"\n case 1: Only two points influence each other\n\n (0,1)*\n (0,0)* * (10,0)\n\n \"\"\"\nvertices1 = np.array([[0, 1], [10, 0], [0, 0]])\nd1 = 10\ngradients1 = np.array([[0, 18], [0, 0], [0, -18]])\nenergy1 = 81\n'\\n case 2: Triangle with 45 a deg. angle... | <|body_start_0|>
"""
case 1: Only two points influence each other
(0,1)*
(0,0)* * (10,0)
"""
vertices1 = np.array([[0, 1], [10, 0], [0, 0]])
d1 = 10
gradients1 = np.array([[0, 18], [0, 0], [0, -18]])
... | TestVertexConstraint | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestVertexConstraint:
def setUp(self):
""":return:"""
<|body_0|>
def test_vertex_constraint_grad(self):
"""Tests whether the vertex_constraint_grad function works."""
<|body_1|>
def test_vertex_constraint(self):
"""Tests whether the vertex_constr... | stack_v2_sparse_classes_36k_train_004305 | 19,054 | no_license | [
{
"docstring": ":return:",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests whether the vertex_constraint_grad function works.",
"name": "test_vertex_constraint_grad",
"signature": "def test_vertex_constraint_grad(self)"
},
{
"docstring": "Tests whether th... | 3 | stack_v2_sparse_classes_30k_train_007438 | Implement the Python class `TestVertexConstraint` described below.
Class description:
Implement the TestVertexConstraint class.
Method signatures and docstrings:
- def setUp(self): :return:
- def test_vertex_constraint_grad(self): Tests whether the vertex_constraint_grad function works.
- def test_vertex_constraint(s... | Implement the Python class `TestVertexConstraint` described below.
Class description:
Implement the TestVertexConstraint class.
Method signatures and docstrings:
- def setUp(self): :return:
- def test_vertex_constraint_grad(self): Tests whether the vertex_constraint_grad function works.
- def test_vertex_constraint(s... | 63cbf87823d772c9db18d285f7ff211d18551472 | <|skeleton|>
class TestVertexConstraint:
def setUp(self):
""":return:"""
<|body_0|>
def test_vertex_constraint_grad(self):
"""Tests whether the vertex_constraint_grad function works."""
<|body_1|>
def test_vertex_constraint(self):
"""Tests whether the vertex_constr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestVertexConstraint:
def setUp(self):
""":return:"""
"""
case 1: Only two points influence each other
(0,1)*
(0,0)* * (10,0)
"""
vertices1 = np.array([[0, 1], [10, 0], [0, 0]])
d1 = 10
... | the_stack_v2_python_sparse | main_directory/test_energies.py | Jeronics/cac-segmenter | train | 3 | |
7a390cd85462a5e04ac2661a37eb5505404792fa | [
"order = []\nvowels = ['a', 'e', 'i', 'o', 'u', 'A', 'E', 'I', 'O', 'U']\nans = list(s)\nleft, right = (0, len(ans) - 1)\nwhile left <= right:\n if ans[left] in vowels and ans[right] in vowels:\n ans[left], ans[right] = (ans[right], ans[left])\n left += 1\n right -= 1\n continue\n ... | <|body_start_0|>
order = []
vowels = ['a', 'e', 'i', 'o', 'u', 'A', 'E', 'I', 'O', 'U']
ans = list(s)
left, right = (0, len(ans) - 1)
while left <= right:
if ans[left] in vowels and ans[right] in vowels:
ans[left], ans[right] = (ans[right], ans[left])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
order = []
vowels = ['a', 'e', 'i', 'o', 'u', 'A', 'E', '... | stack_v2_sparse_classes_36k_train_004306 | 1,572 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowels",
"signature": "def reverseVowels(self, s)"
},
{
"docstring": ":type s: str :rtype: str",
"name": "reverseVowels",
"signature": "def reverseVowels(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000166 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseVowels(self, s): :type s: str :rtype: str
- def reverseVowels(self, s): :type s: str :rtype: str | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseVowels(self, s): :type s: str :rtype: str
- def reverseVowels(self, s): :type s: str :rtype: str
<|skeleton|>
class Solution:
def reverseVowels(self, s):
... | dda63f5b196bfcdc4062bdad8d47076f36a9d89a | <|skeleton|>
class Solution:
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def reverseVowels(self, s):
""":type s: str :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseVowels(self, s):
""":type s: str :rtype: str"""
order = []
vowels = ['a', 'e', 'i', 'o', 'u', 'A', 'E', 'I', 'O', 'U']
ans = list(s)
left, right = (0, len(ans) - 1)
while left <= right:
if ans[left] in vowels and ans[right] in vo... | the_stack_v2_python_sparse | Google/345_Reverse_Vowels_of_a_String.py | bwang8482/LeetCode | train | 1 | |
c60b5913ef4ddf2664966045fbe0baed96323909 | [
"result = ''\ntext = wikiText\nwhile True:\n startIdx = text.find('{{')\n if startIdx >= 0:\n result += text[:startIdx]\n endIdx = text.find('}}', startIdx)\n if endIdx >= 0:\n handled = False\n templateText = text[startIdx + 2:endIdx]\n if handler is not ... | <|body_start_0|>
result = ''
text = wikiText
while True:
startIdx = text.find('{{')
if startIdx >= 0:
result += text[:startIdx]
endIdx = text.find('}}', startIdx)
if endIdx >= 0:
handled = False
... | Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler. | TemplateParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text... | stack_v2_sparse_classes_36k_train_004307 | 6,755 | no_license | [
{
"docstring": "Parse the given wiki text and substitute each template in the text using the specified template handler.",
"name": "parse",
"signature": "def parse(cls, wikiText, handler)"
},
{
"docstring": "Creates a :@link Template from the given text. That is, the template's name and paramete... | 2 | stack_v2_sparse_classes_30k_train_005505 | Implement the Python class `TemplateParser` described below.
Class description:
Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler.
Method signatures and docstrings:
- def... | Implement the Python class `TemplateParser` described below.
Class description:
Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler.
Method signatures and docstrings:
- def... | 58e12957dee8b4b18127df9daeb8825d8ada7923 | <|skeleton|>
class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TemplateParser:
"""Static helper class for parsing wiki markup text that contains templates. The template parser identifies templates in the given wiki text and replaces them as specified by a :@link ITemplateHandler."""
def parse(cls, wikiText, handler):
"""Parse the given wiki text and substitu... | the_stack_v2_python_sparse | api/util/TemplateParser.py | oldeucryptoboi/wiktionary-parser | train | 0 |
6a3d2f51687307b98ce071de0da9a4952066a91b | [
"result = []\nif not root:\n return result\nqueue = collections.deque()\nqueue.append(root)\nwhile queue:\n node = queue.popleft()\n if node:\n result.append(node.val)\n else:\n result.append('null')\n if node:\n queue.append(node.left)\n queue.append(node.right)\nreturn r... | <|body_start_0|>
result = []
if not root:
return result
queue = collections.deque()
queue.append(root)
while queue:
node = queue.popleft()
if node:
result.append(node.val)
else:
result.append('null')
... | 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_004308 | 1,470 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | d8f96b0ec1a85abeef1ce8c0cc409ed501ce088b | <|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"""
result = []
if not root:
return result
queue = collections.deque()
queue.append(root)
while queue:
node = queue.popleft()
... | the_stack_v2_python_sparse | Python/SerializeDeserializeBT.py | miaojiang1987/LeetCode | train | 1 | |
c373807f10c6a72c295cb702e3a50002a71bb8fc | [
"if self is EdgeApproach.GRAD_CHOICE or self is EdgeApproach.MULTI_GRAD_CHOICE:\n return True\nreturn False",
"if self is EdgeApproach.MULTI or self is EdgeApproach.MULTI_GRAD_CHOICE:\n return True\nreturn False",
"if self is EdgeApproach.RANDOM:\n return 'random'\nelif self is EdgeApproach.SINGLE:\n ... | <|body_start_0|>
if self is EdgeApproach.GRAD_CHOICE or self is EdgeApproach.MULTI_GRAD_CHOICE:
return True
return False
<|end_body_0|>
<|body_start_1|>
if self is EdgeApproach.MULTI or self is EdgeApproach.MULTI_GRAD_CHOICE:
return True
return False
<|end_body_1... | an object for the different edge-based-attack approaches | EdgeApproach | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdgeApproach:
"""an object for the different edge-based-attack approaches"""
def isGlobal(self) -> bool:
"""whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool"""
<|body_0|>
def isMulti(self) -> bool:
"""whether or not the se... | stack_v2_sparse_classes_36k_train_004309 | 6,766 | no_license | [
{
"docstring": "whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool",
"name": "isGlobal",
"signature": "def isGlobal(self) -> bool"
},
{
"docstring": "whether or not the selected approach is a MUTLI approach Returns ------- is_multi: bool",
"name": "isMu... | 3 | stack_v2_sparse_classes_30k_train_014648 | Implement the Python class `EdgeApproach` described below.
Class description:
an object for the different edge-based-attack approaches
Method signatures and docstrings:
- def isGlobal(self) -> bool: whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool
- def isMulti(self) -> bool: ... | Implement the Python class `EdgeApproach` described below.
Class description:
an object for the different edge-based-attack approaches
Method signatures and docstrings:
- def isGlobal(self) -> bool: whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool
- def isMulti(self) -> bool: ... | 96ef03959e188c8f12bd47cd190034602fc93b38 | <|skeleton|>
class EdgeApproach:
"""an object for the different edge-based-attack approaches"""
def isGlobal(self) -> bool:
"""whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool"""
<|body_0|>
def isMulti(self) -> bool:
"""whether or not the se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EdgeApproach:
"""an object for the different edge-based-attack approaches"""
def isGlobal(self) -> bool:
"""whether or not the selected approach is a GLOBAL approach Returns ------- is_global: bool"""
if self is EdgeApproach.GRAD_CHOICE or self is EdgeApproach.MULTI_GRAD_CHOICE:
... | the_stack_v2_python_sparse | implementation/classes/approach_classes.py | benfinkelshtein/SINGLE | train | 8 |
bbaa932d3795fc8ea56d31e4152e4357673646c8 | [
"m = len(findNums)\nn = len(nums)\nif not nums:\n return []\nres = [-1] * m\nloc = {}\nj = 0\nloc[nums[0]] = 0\nfor i in range(m):\n a = findNums[i]\n if a not in loc:\n while nums[j] != a:\n j += 1\n loc[nums[j]] = j\n for k in range(loc[a] + 1, n):\n if nums[k] > a:... | <|body_start_0|>
m = len(findNums)
n = len(nums)
if not nums:
return []
res = [-1] * m
loc = {}
j = 0
loc[nums[0]] = 0
for i in range(m):
a = findNums[i]
if a not in loc:
while nums[j] != a:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def nextGreaterElement(self, findNums, nums):
""":type findNums: List[int] :type nums: List[int] :rtype: List[int]"""
<|body_0|>
def nextGreaterElementsII(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def findRelativeRan... | stack_v2_sparse_classes_36k_train_004310 | 2,863 | no_license | [
{
"docstring": ":type findNums: List[int] :type nums: List[int] :rtype: List[int]",
"name": "nextGreaterElement",
"signature": "def nextGreaterElement(self, findNums, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "nextGreaterElementsII",
"signature": "def ne... | 4 | stack_v2_sparse_classes_30k_train_018463 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElement(self, findNums, nums): :type findNums: List[int] :type nums: List[int] :rtype: List[int]
- def nextGreaterElementsII(self, nums): :type nums: List[int] :rt... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def nextGreaterElement(self, findNums, nums): :type findNums: List[int] :type nums: List[int] :rtype: List[int]
- def nextGreaterElementsII(self, nums): :type nums: List[int] :rt... | a2841fdb624548fdc6ef430e23ca46f3300e0558 | <|skeleton|>
class Solution:
def nextGreaterElement(self, findNums, nums):
""":type findNums: List[int] :type nums: List[int] :rtype: List[int]"""
<|body_0|>
def nextGreaterElementsII(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
def findRelativeRan... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def nextGreaterElement(self, findNums, nums):
""":type findNums: List[int] :type nums: List[int] :rtype: List[int]"""
m = len(findNums)
n = len(nums)
if not nums:
return []
res = [-1] * m
loc = {}
j = 0
loc[nums[0]] = 0
... | the_stack_v2_python_sparse | weeklyContest18B.py | sfeng77/myleetcode | train | 1 | |
b27962bce96f542c1bf887f25951b3caced3a98d | [
"self.api_version = api_version\nself.kind = kind\nself.metadata = metadata\nself.spec = spec",
"if dictionary is None:\n return None\napi_version = dictionary.get('apiVersion')\nkind = dictionary.get('kind')\nmetadata = cohesity_management_sdk.models.object_meta.ObjectMeta.from_dictionary(dictionary.get('meta... | <|body_start_0|>
self.api_version = api_version
self.kind = kind
self.metadata = metadata
self.spec = spec
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
api_version = dictionary.get('apiVersion')
kind = dictionary.get('kind')
... | Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schem... | PVCInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PVCInfo:
"""Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of this representation of an object. Serv... | stack_v2_sparse_classes_36k_train_004311 | 2,667 | permissive | [
{
"docstring": "Constructor for the PVCInfo class",
"name": "__init__",
"signature": "def __init__(self, api_version=None, kind=None, metadata=None, spec=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of th... | 2 | null | Implement the Python class `PVCInfo` described below.
Class description:
Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of... | Implement the Python class `PVCInfo` described below.
Class description:
Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PVCInfo:
"""Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of this representation of an object. Serv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PVCInfo:
"""Implementation of the 'PVCInfo' model. Message that encapsulates information about a PVC. We only extract relevant information from a larger response sent by Kubernetes. Attributes: api_version (string): APIVersion defines the versioned schema of this representation of an object. Servers should co... | the_stack_v2_python_sparse | cohesity_management_sdk/models/pvc_info.py | cohesity/management-sdk-python | train | 24 |
939c8f3e13c277b866ccc25d6381950b72c5b446 | [
"if not height:\n return 0\nres = 0\nprev, local_sum = (0, 0)\nindex = height.index(max(height))\nfor h in height[0:index + 1]:\n if h < prev:\n local_sum += prev - h\n else:\n res += local_sum\n local_sum, prev = (0, h)\nprev, local_sum = (0, 0)\nfor i in range(len(height) - 1, index ... | <|body_start_0|>
if not height:
return 0
res = 0
prev, local_sum = (0, 0)
index = height.index(max(height))
for h in height[0:index + 1]:
if h < prev:
local_sum += prev - h
else:
res += local_sum
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def trap2(self, A):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not height:
return 0
res = 0
... | stack_v2_sparse_classes_36k_train_004312 | 1,274 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int",
"name": "trap2",
"signature": "def trap2(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int
- def trap2(self, A): :type height: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def trap(self, height): :type height: List[int] :rtype: int
- def trap2(self, A): :type height: List[int] :rtype: int
<|skeleton|>
class Solution:
def trap(self, height):
... | 4aa3a3a0da8b911e140446352debb9b567b6d78b | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int"""
<|body_0|>
def trap2(self, A):
""":type height: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int"""
if not height:
return 0
res = 0
prev, local_sum = (0, 0)
index = height.index(max(height))
for h in height[0:index + 1]:
if h < prev:
local_sum +=... | the_stack_v2_python_sparse | trapping_rain_water_42.py | adiggo/leetcode_py | train | 0 | |
672cdab38bcbc5817b8d16904c9db78e1612bb42 | [
"diagonal = {}\nfor i, lst in enumerate(nums):\n for j, num in enumerate(lst):\n if i + j not in diagonal:\n diagonal[i + j] = []\n diagonal[i + j].append(num)\nrst = []\nfor i in range(len(diagonal)):\n rst.extend(list(reversed(diagonal[i])))\nreturn rst",
"rst = []\nfor i, lst in ... | <|body_start_0|>
diagonal = {}
for i, lst in enumerate(nums):
for j, num in enumerate(lst):
if i + j not in diagonal:
diagonal[i + j] = []
diagonal[i + j].append(num)
rst = []
for i in range(len(diagonal)):
rst.e... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
<|body_0|>
def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]:
"""使用list存储"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
diagonal = {}
... | stack_v2_sparse_classes_36k_train_004313 | 1,309 | no_license | [
{
"docstring": "使用dict存储",
"name": "findDiagonalOrder",
"signature": "def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]"
},
{
"docstring": "使用list存储",
"name": "findDiagonalOrder_2",
"signature": "def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]: 使用dict存储
- def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]: 使用list存储 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]: 使用dict存储
- def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]: 使用list存储
<|skeleton|>
class Soluti... | e420eb456086db32d1d6b9576c8dcd73e041cbef | <|skeleton|>
class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
<|body_0|>
def findDiagonalOrder_2(self, nums: List[List[int]]) -> List[int]:
"""使用list存储"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDiagonalOrder(self, nums: List[List[int]]) -> List[int]:
"""使用dict存储"""
diagonal = {}
for i, lst in enumerate(nums):
for j, num in enumerate(lst):
if i + j not in diagonal:
diagonal[i + j] = []
diagonal[i... | the_stack_v2_python_sparse | TrainFor1024/others/1424.py | yangwei-nlp/LeetCode-Python | train | 0 | |
d3780d70e5a147f2bb59781c3b19ccfac1c3c115 | [
"self.base_name = name\nself.cmd = cmd\nself.params = list(param_generator)\nself.env_vars = env_vars",
"num_experiments = 1 if len(self.params) == 0 else len(self.params)\nfor experiment_idx in range(num_experiments):\n cmd_tokens = [self.cmd]\n experiment_name_tokens = [self.base_name]\n param_shorthan... | <|body_start_0|>
self.base_name = name
self.cmd = cmd
self.params = list(param_generator)
self.env_vars = env_vars
<|end_body_0|>
<|body_start_1|>
num_experiments = 1 if len(self.params) == 0 else len(self.params)
for experiment_idx in range(num_experiments):
... | Experiment | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Experiment:
def __init__(self, name, cmd, param_generator=(), env_vars=None):
""":param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts"""
<|body_0|>
def generate_experiments(self, experiment_arg_name, customize_experiment_na... | stack_v2_sparse_classes_36k_train_004314 | 7,490 | permissive | [
{
"docstring": ":param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts",
"name": "__init__",
"signature": "def __init__(self, name, cmd, param_generator=(), env_vars=None)"
},
{
"docstring": "Yields tuples of (cmd, experiment_name)",
"name": ... | 2 | stack_v2_sparse_classes_30k_train_000259 | Implement the Python class `Experiment` described below.
Class description:
Implement the Experiment class.
Method signatures and docstrings:
- def __init__(self, name, cmd, param_generator=(), env_vars=None): :param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts
- d... | Implement the Python class `Experiment` described below.
Class description:
Implement the Experiment class.
Method signatures and docstrings:
- def __init__(self, name, cmd, param_generator=(), env_vars=None): :param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts
- d... | 7e1e69550f4de4cdc003d8db5bb39e186803aee9 | <|skeleton|>
class Experiment:
def __init__(self, name, cmd, param_generator=(), env_vars=None):
""":param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts"""
<|body_0|>
def generate_experiments(self, experiment_arg_name, customize_experiment_na... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Experiment:
def __init__(self, name, cmd, param_generator=(), env_vars=None):
""":param cmd: base command to append the parameters to :param param_generator: iterable of parameter dicts"""
self.base_name = name
self.cmd = cmd
self.params = list(param_generator)
self.env... | the_stack_v2_python_sparse | sample_factory/launcher/run_description.py | alex-petrenko/sample-factory | train | 644 | |
7b68256b40c277ef2e6d3eb26675c4a8d7bf005d | [
"super(SelfAttention, self).__init__()\nset_seed()\nself._hidden_size = kwargs.get('hidden_size', 128)\nself._expansion_size = kwargs.get('expansion_size', 1024)\nself._attention_layers = kwargs.get('attention_layers', 512)\nself._activation_fn = kwargs.get('activation_fn', 'leaky ReLU')\nself._seqlen = kwargs.get(... | <|body_start_0|>
super(SelfAttention, self).__init__()
set_seed()
self._hidden_size = kwargs.get('hidden_size', 128)
self._expansion_size = kwargs.get('expansion_size', 1024)
self._attention_layers = kwargs.get('attention_layers', 512)
self._activation_fn = kwargs.get('ac... | SelfAttention | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
def __init__(self, **kwargs):
"""Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hidden units after concatenating the hidden units for both directions : attention_layers (int): : seqlen ... | stack_v2_sparse_classes_36k_train_004315 | 28,550 | permissive | [
{
"docstring": "Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hidden units after concatenating the hidden units for both directions : attention_layers (int): : seqlen (int): length of the padded SMILES string",
"name": ... | 4 | stack_v2_sparse_classes_30k_train_002762 | Implement the Python class `SelfAttention` described below.
Class description:
Implement the SelfAttention class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hid... | Implement the Python class `SelfAttention` described below.
Class description:
Implement the SelfAttention class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hid... | a730e02153709b9c0e7f83deb0042ae9f9c1ce15 | <|skeleton|>
class SelfAttention:
def __init__(self, **kwargs):
"""Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hidden units after concatenating the hidden units for both directions : attention_layers (int): : seqlen ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
def __init__(self, **kwargs):
"""Initialiser. : expansion_size (int): adjustable hyperparameter. Intermediate dimension to yield attention weights : hidden_size (int): hidden units after concatenating the hidden units for both directions : attention_layers (int): : seqlen (int): length ... | the_stack_v2_python_sparse | model/snn.py | licj1/Siamese-RNN-Self-Attention | train | 0 | |
536fce87c6c80651254a716fdf6c5268173018ab | [
"driver = self.driver\nexpanded = test.element_exists(driver, self.MENU_CONTAINER_LOCATOR) and self.find_element(self.MENU_CONTAINER_LOCATOR).is_displayed()\nreturn expanded",
"button = self.find_element(self.EXPAND_BUTTON_LOCATOR)\nif not self.fixed:\n actions.scroll.into_view(self.driver, button)\nbutton.cli... | <|body_start_0|>
driver = self.driver
expanded = test.element_exists(driver, self.MENU_CONTAINER_LOCATOR) and self.find_element(self.MENU_CONTAINER_LOCATOR).is_displayed()
return expanded
<|end_body_0|>
<|body_start_1|>
button = self.find_element(self.EXPAND_BUTTON_LOCATOR)
if n... | Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator for the button that expands the nav menu :var COLLAPSE_BUTTON_LOCATOR: Locator for the... | CollapsibleNavObject | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CollapsibleNavObject:
"""Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator for the button that expands the nav me... | stack_v2_sparse_classes_36k_train_004316 | 4,428 | permissive | [
{
"docstring": "Check if the nav menu is expanded This method checks if the element located by :attr:`MENU_CONTAINER_LOCATOR` exists and is visible. This should be sufficient for many common implementations of collapsible navs, but can be overridden if this isn't a reliable detection method for an implementatio... | 3 | null | Implement the Python class `CollapsibleNavObject` described below.
Class description:
Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator... | Implement the Python class `CollapsibleNavObject` described below.
Class description:
Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator... | 31c91905611dee9cc13dbf37e7c0cfbf9ca0173f | <|skeleton|>
class CollapsibleNavObject:
"""Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator for the button that expands the nav me... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CollapsibleNavObject:
"""Subclass of :class:`NavObject` with additional methods for collapsible nav menus In addition to the variables for :class:`NavObject`, the following variables need to be defined for collapsible navs :var EXPAND_BUTTON_LOCATOR: Locator for the button that expands the nav menu :var COLLA... | the_stack_v2_python_sparse | venv/lib/python3.5/site-packages/webdriver_test_tools/pageobject/nav.py | alexmudra/python_experiments | train | 0 |
63713407184a93986c403a48e68e687c41b2b73f | [
"def count(inv_idx, m, left, right):\n return bisect.bisect_right(inv_idx[m], right) - bisect.bisect_left(inv_idx[m], left)\nself.__arr = arr\nself.__inv_idx = collections.defaultdict(list)\nfor i, x in enumerate(self.__arr):\n self.__inv_idx[x].append(i)\nself.__segment_tree = SegmentTreeRecu(arr, functools.... | <|body_start_0|>
def count(inv_idx, m, left, right):
return bisect.bisect_right(inv_idx[m], right) - bisect.bisect_left(inv_idx[m], left)
self.__arr = arr
self.__inv_idx = collections.defaultdict(list)
for i, x in enumerate(self.__arr):
self.__inv_idx[x].append(i)... | MajorityChecker1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MajorityChecker1:
def __init__(self, arr):
""":type arr: List[int]"""
<|body_0|>
def query(self, left, right, threshold):
""":type left: int :type right: int :type threshold: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def count(... | stack_v2_sparse_classes_36k_train_004317 | 6,042 | no_license | [
{
"docstring": ":type arr: List[int]",
"name": "__init__",
"signature": "def __init__(self, arr)"
},
{
"docstring": ":type left: int :type right: int :type threshold: int :rtype: int",
"name": "query",
"signature": "def query(self, left, right, threshold)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018599 | Implement the Python class `MajorityChecker1` described below.
Class description:
Implement the MajorityChecker1 class.
Method signatures and docstrings:
- def __init__(self, arr): :type arr: List[int]
- def query(self, left, right, threshold): :type left: int :type right: int :type threshold: int :rtype: int | Implement the Python class `MajorityChecker1` described below.
Class description:
Implement the MajorityChecker1 class.
Method signatures and docstrings:
- def __init__(self, arr): :type arr: List[int]
- def query(self, left, right, threshold): :type left: int :type right: int :type threshold: int :rtype: int
<|skel... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class MajorityChecker1:
def __init__(self, arr):
""":type arr: List[int]"""
<|body_0|>
def query(self, left, right, threshold):
""":type left: int :type right: int :type threshold: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MajorityChecker1:
def __init__(self, arr):
""":type arr: List[int]"""
def count(inv_idx, m, left, right):
return bisect.bisect_right(inv_idx[m], right) - bisect.bisect_left(inv_idx[m], left)
self.__arr = arr
self.__inv_idx = collections.defaultdict(list)
for... | the_stack_v2_python_sparse | python/_1001_1500/1157_online-majority-element-in-subarray.py | Wang-Yann/LeetCodeMe | train | 0 | |
7d9960d2ae1e01f4f501629c5177b1dc6692b1ca | [
"if subarray_beam_ids is None:\n subarray_beam_ids = []\nif station_ids is None:\n station_ids = []\nif channel_blocks is None:\n channel_blocks = []\nself.interface = interface\nself.subarray_beam_ids = list(subarray_beam_ids)\nself.station_ids = list(station_ids)\nself.channel_blocks = list(channel_block... | <|body_start_0|>
if subarray_beam_ids is None:
subarray_beam_ids = []
if station_ids is None:
station_ids = []
if channel_blocks is None:
channel_blocks = []
self.interface = interface
self.subarray_beam_ids = list(subarray_beam_ids)
se... | AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute. | AssignedResources | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssignedResources:
"""AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute."""
def __init__(self, *, interface: Optional[str]=SCHEMA, subarray_beam_ids: List[int]=None, station_ids: List[List[int]]=None, channel_blocks: List[int... | stack_v2_sparse_classes_36k_train_004318 | 2,045 | permissive | [
{
"docstring": "Create a new object for an MCCSSubarray.assigned_resources response. :param subarray_beam_ids: subarray beam IDs to allocate to the subarray :param station_ids: IDs of stations to allocate :param channel_blocks: channels to allocate :param interface: the JSON schema this object claims to be comp... | 2 | stack_v2_sparse_classes_30k_train_018029 | Implement the Python class `AssignedResources` described below.
Class description:
AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute.
Method signatures and docstrings:
- def __init__(self, *, interface: Optional[str]=SCHEMA, subarray_beam_ids: List[in... | Implement the Python class `AssignedResources` described below.
Class description:
AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute.
Method signatures and docstrings:
- def __init__(self, *, interface: Optional[str]=SCHEMA, subarray_beam_ids: List[in... | 87083655aca8f8f53a26dba253a0189d8519714b | <|skeleton|>
class AssignedResources:
"""AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute."""
def __init__(self, *, interface: Optional[str]=SCHEMA, subarray_beam_ids: List[int]=None, station_ids: List[List[int]]=None, channel_blocks: List[int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AssignedResources:
"""AssignedResources is the object representation of the JSON returned by the MCCSSubarray.assigned_resources attribute."""
def __init__(self, *, interface: Optional[str]=SCHEMA, subarray_beam_ids: List[int]=None, station_ids: List[List[int]]=None, channel_blocks: List[int]=None):
... | the_stack_v2_python_sparse | src/ska_tmc_cdm/messages/mccssubarray/assigned_resources.py | ska-telescope/cdm-shared-library | train | 0 |
8e5d0a34919d67fa0b258a7135ff62540a52a347 | [
"pos = 0\nfound = False\nwhile pos < len(alist) and (not found):\n if alist[pos] == item:\n found = True\n else:\n pos = pos + 1\nreturn found",
"pos = 0\nfound = False\nstop = False\nwhile pos < len(alist) and (not found) and (not stop):\n if alist[pos] == item:\n found = True\n ... | <|body_start_0|>
pos = 0
found = False
while pos < len(alist) and (not found):
if alist[pos] == item:
found = True
else:
pos = pos + 1
return found
<|end_body_0|>
<|body_start_1|>
pos = 0
found = False
stop ... | Class that performs searching techniques on given data. | SearchingAlgs | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchingAlgs:
"""Class that performs searching techniques on given data."""
def unorderedSequentialSearch(self, alist, item):
"""Search an item using sequential/linear search technique ."""
<|body_0|>
def orderedSequentialSearch(self, alist, item):
"""Search an ... | stack_v2_sparse_classes_36k_train_004319 | 1,545 | no_license | [
{
"docstring": "Search an item using sequential/linear search technique .",
"name": "unorderedSequentialSearch",
"signature": "def unorderedSequentialSearch(self, alist, item)"
},
{
"docstring": "Search an item in an ordered list using sequential search technique.",
"name": "orderedSequentia... | 2 | null | Implement the Python class `SearchingAlgs` described below.
Class description:
Class that performs searching techniques on given data.
Method signatures and docstrings:
- def unorderedSequentialSearch(self, alist, item): Search an item using sequential/linear search technique .
- def orderedSequentialSearch(self, ali... | Implement the Python class `SearchingAlgs` described below.
Class description:
Class that performs searching techniques on given data.
Method signatures and docstrings:
- def unorderedSequentialSearch(self, alist, item): Search an item using sequential/linear search technique .
- def orderedSequentialSearch(self, ali... | 7235f5d37d76d696037a1ad66885a76742ff3b18 | <|skeleton|>
class SearchingAlgs:
"""Class that performs searching techniques on given data."""
def unorderedSequentialSearch(self, alist, item):
"""Search an item using sequential/linear search technique ."""
<|body_0|>
def orderedSequentialSearch(self, alist, item):
"""Search an ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SearchingAlgs:
"""Class that performs searching techniques on given data."""
def unorderedSequentialSearch(self, alist, item):
"""Search an item using sequential/linear search technique ."""
pos = 0
found = False
while pos < len(alist) and (not found):
if alist... | the_stack_v2_python_sparse | algorithms/searching/searching_algs.py | dhanraju/python | train | 0 |
77a3b5ae2e761b991f9a0655ec958169e3368494 | [
"sample_params = self.param_kwargs.copy()\nfor param_name in self.EXTRA_PARAMS:\n del sample_params[param_name]\nreturn sample_params",
"cohort_params = self.sample_params()\ndel cohort_params['sample']\nreturn cohort_params"
] | <|body_start_0|>
sample_params = self.param_kwargs.copy()
for param_name in self.EXTRA_PARAMS:
del sample_params[param_name]
return sample_params
<|end_body_0|>
<|body_start_1|>
cohort_params = self.sample_params()
del cohort_params['sample']
return cohort_pa... | Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter. | ReportsTask | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReportsTask:
"""Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter."""
def sample_params(self):
"""Remove the extra parameters that the report generation needs, but that are not neede... | stack_v2_sparse_classes_36k_train_004320 | 1,387 | no_license | [
{
"docstring": "Remove the extra parameters that the report generation needs, but that are not needed or expected by the tasks upstream:",
"name": "sample_params",
"signature": "def sample_params(self)"
},
{
"docstring": "Remove all the extra parameters of the report generation and also remove t... | 2 | stack_v2_sparse_classes_30k_train_006393 | Implement the Python class `ReportsTask` described below.
Class description:
Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter.
Method signatures and docstrings:
- def sample_params(self): Remove the extra parameters... | Implement the Python class `ReportsTask` described below.
Class description:
Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter.
Method signatures and docstrings:
- def sample_params(self): Remove the extra parameters... | 040a62c11e5bae306e2de4cc3e0a78772ee580b3 | <|skeleton|>
class ReportsTask:
"""Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter."""
def sample_params(self):
"""Remove the extra parameters that the report generation needs, but that are not neede... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReportsTask:
"""Abstract class to provide common parameters to GenerateReports and GenerateReportsCohort. See the former class for a full explanation of each parameter."""
def sample_params(self):
"""Remove the extra parameters that the report generation needs, but that are not needed or expected... | the_stack_v2_python_sparse | paip/task_types/reports_task.py | biocodices/paip | train | 1 |
981207fc1e8b1b076d16b04652d745c16a15ffba | [
"try:\n challenge = doc.attrib['challenge']\nexcept KeyError:\n challenge = None\npairiter = doc.iter('pair')\nreturn [RTEPair(pair, challenge=challenge) for pair in pairiter]",
"if isinstance(fileids, str):\n fileids = [fileids]\nreturn concat([self._read_etree(self.xml(fileid)) for fileid in fileids])"... | <|body_start_0|>
try:
challenge = doc.attrib['challenge']
except KeyError:
challenge = None
pairiter = doc.iter('pair')
return [RTEPair(pair, challenge=challenge) for pair in pairiter]
<|end_body_0|>
<|body_start_1|>
if isinstance(fileids, str):
... | Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents. | RTECorpusReader | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"CC-BY-NC-ND-3.0",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RTECorpusReader:
"""Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents."""
def _read_etree(self, doc):
"""Map the XML input into an RTEPair. This uses the ``getiterat... | stack_v2_sparse_classes_36k_train_004321 | 4,639 | permissive | [
{
"docstring": "Map the XML input into an RTEPair. This uses the ``getiterator()`` method from the ElementTree package to find all the ``<pair>`` elements. :param doc: a parsed XML document :rtype: list(RTEPair)",
"name": "_read_etree",
"signature": "def _read_etree(self, doc)"
},
{
"docstring":... | 2 | stack_v2_sparse_classes_30k_train_003346 | Implement the Python class `RTECorpusReader` described below.
Class description:
Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents.
Method signatures and docstrings:
- def _read_etree(self, doc): Map... | Implement the Python class `RTECorpusReader` described below.
Class description:
Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents.
Method signatures and docstrings:
- def _read_etree(self, doc): Map... | 582e6e35f0e6c984b44ec49dcb8846d9c011d0a8 | <|skeleton|>
class RTECorpusReader:
"""Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents."""
def _read_etree(self, doc):
"""Map the XML input into an RTEPair. This uses the ``getiterat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RTECorpusReader:
"""Corpus reader for corpora in RTE challenges. This is just a wrapper around the XMLCorpusReader. See module docstring above for the expected structure of input documents."""
def _read_etree(self, doc):
"""Map the XML input into an RTEPair. This uses the ``getiterator()`` method... | the_stack_v2_python_sparse | nltk/corpus/reader/rte.py | nltk/nltk | train | 11,860 |
181461c35702ffb5572d06c50837d6edc3d9982a | [
"rows = len(grid)\nif rows == 0:\n return 0\ncols = len(grid[0])\ndirs = [(-1, 0), (1, 0), (0, -1), (0, 1)]\nself.marks = [[False] * cols for _ in range(rows)]\nans = 0\n\ndef dfs(i, j):\n self.marks[i][j] = True\n for d in dirs:\n x, y = (d[0] + i, d[1] + j)\n if 0 <= x < rows and 0 <= y < c... | <|body_start_0|>
rows = len(grid)
if rows == 0:
return 0
cols = len(grid[0])
dirs = [(-1, 0), (1, 0), (0, -1), (0, 1)]
self.marks = [[False] * cols for _ in range(rows)]
ans = 0
def dfs(i, j):
self.marks[i][j] = True
for d in d... | 给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。 | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。"""
def numIslands_dfs(self, grid) -> int:
"""遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法"""
<|body_0|>
def numIslands_bfs(self, grid) -> int:
"""广度优先, 数组存储单个岛屿... | stack_v2_sparse_classes_36k_train_004322 | 3,903 | permissive | [
{
"docstring": "遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法",
"name": "numIslands_dfs",
"signature": "def numIslands_dfs(self, grid) -> int"
},
{
"docstring": "广度优先, 数组存储单个岛屿所有的网格",
"name": "numIslands_bfs",
"signature": "def numIslands_bfs(self, grid) -> int"
},
{
"docstring": "并... | 3 | stack_v2_sparse_classes_30k_train_011721 | Implement the Python class `Solution` described below.
Class description:
给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。
Method signatures and docstrings:
- def numIslands_dfs(self, grid) -> int: 遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法
- def numIslands_bfs(self, grid) -... | Implement the Python class `Solution` described below.
Class description:
给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。
Method signatures and docstrings:
- def numIslands_dfs(self, grid) -> int: 遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法
- def numIslands_bfs(self, grid) -... | 9f49766a2b375a6c65f7bfa96df513875ddd772d | <|skeleton|>
class Solution:
"""给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。"""
def numIslands_dfs(self, grid) -> int:
"""遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法"""
<|body_0|>
def numIslands_bfs(self, grid) -> int:
"""广度优先, 数组存储单个岛屿... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
"""给定一个由 '1'（陆地）和 '0'（水）组成的的二维网格，计算岛屿的数量。一个岛被水包围， 并且它是通过水平方向或垂直方向上相邻的陆地连接而成的。你可以假设网格的四个边均被水包围。"""
def numIslands_dfs(self, grid) -> int:
"""遍历岛屿, self.marks[i][j]标记已经查找过的网格 深度优先, 回溯法"""
rows = len(grid)
if rows == 0:
return 0
cols = len(grid[0])
... | the_stack_v2_python_sparse | Leetcode/200.numIslands.py | Song2017/Leetcode_python | train | 1 |
8db25d8068975d54c140c65ee9a58d80caac5a8b | [
"if isinstance(key, int):\n return HomeAddressReply(key)\nif key not in HomeAddressReply._member_map_:\n return extend_enum(HomeAddressReply, key, default)\nreturn HomeAddressReply[key]",
"if not (isinstance(value, int) and 0 <= value <= 255):\n raise ValueError('%r is not a valid %s' % (value, cls.__nam... | <|body_start_0|>
if isinstance(key, int):
return HomeAddressReply(key)
if key not in HomeAddressReply._member_map_:
return extend_enum(HomeAddressReply, key, default)
return HomeAddressReply[key]
<|end_body_0|>
<|body_start_1|>
if not (isinstance(value, int) and ... | [HomeAddressReply] IPv4 Home Address Reply Status Codes | HomeAddressReply | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HomeAddressReply:
"""[HomeAddressReply] IPv4 Home Address Reply Status Codes"""
def get(key: 'int | str', default: 'int'=-1) -> 'HomeAddressReply':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
... | stack_v2_sparse_classes_36k_train_004323 | 2,296 | 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) -> 'HomeAddressReply'"
},
{
"docstring": "Lookup function used when value is not f... | 2 | null | Implement the Python class `HomeAddressReply` described below.
Class description:
[HomeAddressReply] IPv4 Home Address Reply Status Codes
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'HomeAddressReply': Backport support for original codes. Args: key: Key to get enum item. defaul... | Implement the Python class `HomeAddressReply` described below.
Class description:
[HomeAddressReply] IPv4 Home Address Reply Status Codes
Method signatures and docstrings:
- def get(key: 'int | str', default: 'int'=-1) -> 'HomeAddressReply': Backport support for original codes. Args: key: Key to get enum item. defaul... | a6fe49ec58f09e105bec5a00fb66d9b3f22730d9 | <|skeleton|>
class HomeAddressReply:
"""[HomeAddressReply] IPv4 Home Address Reply Status Codes"""
def get(key: 'int | str', default: 'int'=-1) -> 'HomeAddressReply':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HomeAddressReply:
"""[HomeAddressReply] IPv4 Home Address Reply Status Codes"""
def get(key: 'int | str', default: 'int'=-1) -> 'HomeAddressReply':
"""Backport support for original codes. Args: key: Key to get enum item. default: Default value if not found. :meta private:"""
if isinstance... | the_stack_v2_python_sparse | pcapkit/const/mh/home_address_reply.py | JarryShaw/PyPCAPKit | train | 204 |
545fed3f1a27a00c8da8f7b56d5a0ab5ff200dce | [
"self.headers = headers or {}\nself.cookies = cookies or {}\nif request:\n token = request.QUERY.get(settings.SESSION_COOKIE_NAME) or request.META.get('HTTP_TBKT_TOKEN') or request.COOKIES.get('tbkt_token')\n self.cookies['tbkt_token'] = token",
"assert alias in settings.API_URLROOT, alias\nurlroot = settin... | <|body_start_0|>
self.headers = headers or {}
self.cookies = cookies or {}
if request:
token = request.QUERY.get(settings.SESSION_COOKIE_NAME) or request.META.get('HTTP_TBKT_TOKEN') or request.COOKIES.get('tbkt_token')
self.cookies['tbkt_token'] = token
<|end_body_0|>
<|... | Hub | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Hub:
def __init__(self, request=None, headers=None, cookies=None):
""":param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典"""
<|body_0|>
def __getattr__(self, alias):
""":param alias: 接口服务器别名 公... | stack_v2_sparse_classes_36k_train_004324 | 4,472 | no_license | [
{
"docstring": ":param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典",
"name": "__init__",
"signature": "def __init__(self, request=None, headers=None, cookies=None)"
},
{
"docstring": ":param alias: 接口服务器别名 公共接口: com 银行接口... | 2 | stack_v2_sparse_classes_30k_train_017156 | Implement the Python class `Hub` described below.
Class description:
Implement the Hub class.
Method signatures and docstrings:
- def __init__(self, request=None, headers=None, cookies=None): :param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典... | Implement the Python class `Hub` described below.
Class description:
Implement the Hub class.
Method signatures and docstrings:
- def __init__(self, request=None, headers=None, cookies=None): :param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典... | 1f08cbfccc1ae2123d92670c0afed9b59ae645b8 | <|skeleton|>
class Hub:
def __init__(self, request=None, headers=None, cookies=None):
""":param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典"""
<|body_0|>
def __getattr__(self, alias):
""":param alias: 接口服务器别名 公... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Hub:
def __init__(self, request=None, headers=None, cookies=None):
""":param request: django.http.HttpRequest对象 如果request不为空, 意味着每次调用都携带登录状态 :param headers: 自定义公共头部字典 :param cookies: 自定义公共cookie字典"""
self.headers = headers or {}
self.cookies = cookies or {}
if request:
... | the_stack_v2_python_sparse | tbkt/libs/utils/tbktapi.py | GUAN-YE/hd_api_djs | train | 1 | |
4aab9a9cbcee3e6c40fff168ed9e4b53f3bb4e9e | [
"if not matrix:\n return\nm, n = (len(matrix), len(matrix[0]))\ndp = [[matrix[0][0] for j in range(n)] for i in range(m)]\nfor i in range(1, m):\n dp[i][0] = matrix[i][0] + dp[i - 1][0]\nfor j in range(1, n):\n dp[0][j] = matrix[0][j] + dp[0][j - 1]\nfor i in range(1, m):\n for j in range(1, n):\n ... | <|body_start_0|>
if not matrix:
return
m, n = (len(matrix), len(matrix[0]))
dp = [[matrix[0][0] for j in range(n)] for i in range(m)]
for i in range(1, m):
dp[i][0] = matrix[i][0] + dp[i - 1][0]
for j in range(1, n):
dp[0][j] = matrix[0][j] + d... | NumMatrix | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_004325 | 1,337 | no_license | [
{
"docstring": ":type matrix: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, matrix)"
},
{
"docstring": ":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int",
"name": "sumRegion",
"signature": "def sumRegion(self, row1, col1, row2, col2)"
... | 2 | stack_v2_sparse_classes_30k_test_000747 | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | Implement the Python class `NumMatrix` described below.
Class description:
Implement the NumMatrix class.
Method signatures and docstrings:
- def __init__(self, matrix): :type matrix: List[List[int]]
- def sumRegion(self, row1, col1, row2, col2): :type row1: int :type col1: int :type row2: int :type col2: int :rtype:... | 7ff4d8ed1b8897385da046ba7f4afc0796d6ddc1 | <|skeleton|>
class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
<|body_0|>
def sumRegion(self, row1, col1, row2, col2):
""":type row1: int :type col1: int :type row2: int :type col2: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if not matrix:
return
m, n = (len(matrix), len(matrix[0]))
dp = [[matrix[0][0] for j in range(n)] for i in range(m)]
for i in range(1, m):
dp[i][0] = matrix[i][0] + dp[i -... | the_stack_v2_python_sparse | 304_Range_Sum_Query_2D_Immutable.py | gzk2018/leetcode | train | 0 | |
2c3a09aba7e43d32e82027bb4b3530cbc5b65d88 | [
"h = [(row[0], row, 1) for row in matrix]\nprint(h)\nfor _ in range(k - 1):\n v, r, i = h[0]\n if i < len(r):\n heapreplace(h, (r[i], r, i + 1))\n else:\n heappop(h)\n print(h)\nreturn h[0][0]",
"min_heap = [(matrix[0][0], 0, 0)]\nwhile min_heap and k:\n k -= 1\n res, i, j = he... | <|body_start_0|>
h = [(row[0], row, 1) for row in matrix]
print(h)
for _ in range(k - 1):
v, r, i = h[0]
if i < len(r):
heapreplace(h, (r[i], r, i + 1))
else:
heappop(h)
print(h)
return h[0][0]
<|end_body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def kthSmallest(self, matrix, k):
""":type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify function"""
<|body_0|>
def kthSmallest(self, matrix, k):
""":type matrix: List[List... | stack_v2_sparse_classes_36k_train_004326 | 2,203 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify function",
"name": "kthSmallest",
"signature": "def kthSmallest(self, matrix, k)"
},
{
"docstring": ":type matrix: List[List[int]] :rtype: int ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, matrix, k): :type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify functio... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def kthSmallest(self, matrix, k): :type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify functio... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def kthSmallest(self, matrix, k):
""":type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify function"""
<|body_0|>
def kthSmallest(self, matrix, k):
""":type matrix: List[List... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def kthSmallest(self, matrix, k):
""":type matrix: List[List[int]] :rtype: int binary search first locate row then column use heap to store sorted elements till kth, heapify function"""
h = [(row[0], row, 1) for row in matrix]
print(h)
for _ in range(k - 1):
... | the_stack_v2_python_sparse | 378_kthSmallestInSortedMatrix.py | jennyChing/leetCode | train | 2 | |
60f460d3550fe6c7fb2b6ede0d4ada8e8bb210db | [
"IO_files = {}\nfile_names = set()\nfor fl in in_dir.files:\n if self.name not in fl.users:\n if utils.splitext(fl.name)[-1] in self.input_types:\n IO_files['-!i'] = os.path.join(in_dir.path, fl.name)\n command_ids = [utils.infer_path_id(IO_files['-!i'])]\n in_dir.use_file... | <|body_start_0|>
IO_files = {}
file_names = set()
for fl in in_dir.files:
if self.name not in fl.users:
if utils.splitext(fl.name)[-1] in self.input_types:
IO_files['-!i'] = os.path.join(in_dir.path, fl.name)
command_ids = [util... | Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the function. input_type: Inp... | tabix | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tabix:
"""Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name... | stack_v2_sparse_classes_36k_train_004327 | 10,695 | permissive | [
{
"docstring": "Infers the input and output file paths. This method must keep the directory objects up to date of the file edits! Parameters: in_cmd: A dict containing the command line. in_dir: Input directory (instance of filetypes.Directory). out_dir: Output directory (instance of filetypes.Directory). Return... | 2 | stack_v2_sparse_classes_30k_train_005718 | Implement the Python class `tabix` described below.
Class description:
Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date a... | Implement the Python class `tabix` described below.
Class description:
Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date a... | fd83eee4be0bb78c67a111fd1c1c1dff4c16aefe | <|skeleton|>
class tabix:
"""Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tabix:
"""Class for indexing .vcf files with bgzip & tabix. Parameters: in_cmd: String containing a command line in_dir: Directory object containing input files out_dir: Directory object containing output files NOTICE! Keep the directory objects up to date about file edits! Attributes: name: Name of the funct... | the_stack_v2_python_sparse | modules/tabix.py | tyrmi/STAPLER | train | 4 |
eeffcc318b757bd95445d3f5a767835f6efe4f2a | [
"super(MovingAverage, self).__init__()\nself.window_size = window_size\nself.dimension = dimension",
"ret = torch.cumsum(input_tensor, dim=self.dimension)\nret[:, self.window_size:] = ret[:, self.window_size:] - ret[:, :-self.window_size]\nreturn ret[:, self.window_size - 1:] / self.window_size"
] | <|body_start_0|>
super(MovingAverage, self).__init__()
self.window_size = window_size
self.dimension = dimension
<|end_body_0|>
<|body_start_1|>
ret = torch.cumsum(input_tensor, dim=self.dimension)
ret[:, self.window_size:] = ret[:, self.window_size:] - ret[:, :-self.window_size... | MovingAverage | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovingAverage:
def __init__(self, window_size: int, dimension: int):
"""Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window"""
<|body_0|>
def forward(self, input_tensor: torch.Tensor):
"""Parameters ---------- ... | stack_v2_sparse_classes_36k_train_004328 | 1,792 | permissive | [
{
"docstring": "Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window",
"name": "__init__",
"signature": "def __init__(self, window_size: int, dimension: int)"
},
{
"docstring": "Parameters ---------- input_tensor: torch.Tensor of shape (B, ... | 2 | stack_v2_sparse_classes_30k_test_000382 | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, window_size: int, dimension: int): Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window
- def... | Implement the Python class `MovingAverage` described below.
Class description:
Implement the MovingAverage class.
Method signatures and docstrings:
- def __init__(self, window_size: int, dimension: int): Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window
- def... | 8ac7ccb17de4aaeb40325deda952652b0fc107ef | <|skeleton|>
class MovingAverage:
def __init__(self, window_size: int, dimension: int):
"""Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window"""
<|body_0|>
def forward(self, input_tensor: torch.Tensor):
"""Parameters ---------- ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovingAverage:
def __init__(self, window_size: int, dimension: int):
"""Parameters ---------- window_size: sliding windows size dimension: dimension we want to apply sliding window"""
super(MovingAverage, self).__init__()
self.window_size = window_size
self.dimension = dimensio... | the_stack_v2_python_sparse | layers.py | Stress-Puppy/EMNLP2020 | train | 0 | |
bbe542760a5fab2b6860dfa2cfd2b2daf83330ba | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\ntry:\n mapping_value = parse_node.get_child_node('@odata.type').get_str_value()\nexcept AttributeError:\n mapping_value = None\nif mapping_value and mapping_value.casefold() == '#microsoft.graph.taskFileAttachment'.casefold():\n from .... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
try:
mapping_value = parse_node.get_child_node('@odata.type').get_str_value()
except AttributeError:
mapping_value = None
if mapping_value and mapping_value.casefold() ==... | AttachmentBase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttachmentBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttachmentBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_36k_train_004329 | 3,410 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: AttachmentBase",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator_valu... | 3 | stack_v2_sparse_classes_30k_train_002989 | Implement the Python class `AttachmentBase` described below.
Class description:
Implement the AttachmentBase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttachmentBase: Creates a new instance of the appropriate class based on discriminator va... | Implement the Python class `AttachmentBase` described below.
Class description:
Implement the AttachmentBase class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttachmentBase: Creates a new instance of the appropriate class based on discriminator va... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class AttachmentBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttachmentBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttachmentBase:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> AttachmentBase:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: Attachment... | the_stack_v2_python_sparse | msgraph/generated/models/attachment_base.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
8924fed3b9ab9869866483c7ef4c2e83991a016b | [
"lines = open_model(file_path)\nparser = self.instantiate(lines)\nbuilt = parser.build(lines)\nreturn built",
"subtrees = [list(g) for k, g in groupby(lines, key=lambda x: x != '') if k]\njoint = self.build_mpt_from_subtrees(subtrees)\nreturn joint",
"mpts = []\nleaf_step = 0\nfor subtree in subtrees:\n bmpt... | <|body_start_0|>
lines = open_model(file_path)
parser = self.instantiate(lines)
built = parser.build(lines)
return built
<|end_body_0|>
<|body_start_1|>
subtrees = [list(g) for k, g in groupby(lines, key=lambda x: x != '') if k]
joint = self.build_mpt_from_subtrees(subtr... | Parsing for easy format | Parser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Parser:
"""Parsing for easy format"""
def parse(self, file_path):
"""Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------"""
<|body_0|>
def build(self, lines):
"""Build MPT from lines. Can have multiple subtrees... | stack_v2_sparse_classes_36k_train_004330 | 5,711 | permissive | [
{
"docstring": "Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------",
"name": "parse",
"signature": "def parse(self, file_path)"
},
{
"docstring": "Build MPT from lines. Can have multiple subtrees.",
"name": "build",
"signature": "def ... | 4 | stack_v2_sparse_classes_30k_train_008409 | Implement the Python class `Parser` described below.
Class description:
Parsing for easy format
Method signatures and docstrings:
- def parse(self, file_path): Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------
- def build(self, lines): Build MPT from lines. Can h... | Implement the Python class `Parser` described below.
Class description:
Parsing for easy format
Method signatures and docstrings:
- def parse(self, file_path): Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------
- def build(self, lines): Build MPT from lines. Can h... | 820fb6c9019623bc98f14c894ced9ed5d70eb96b | <|skeleton|>
class Parser:
"""Parsing for easy format"""
def parse(self, file_path):
"""Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------"""
<|body_0|>
def build(self, lines):
"""Build MPT from lines. Can have multiple subtrees... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Parser:
"""Parsing for easy format"""
def parse(self, file_path):
"""Parse the mpt from the file Parameters ---------- file_path : str path to the model file Returns -------"""
lines = open_model(file_path)
parser = self.instantiate(lines)
built = parser.build(lines)
... | the_stack_v2_python_sparse | mptpy/tools/parsing.py | saurabhr/mptpy | train | 0 |
3f57a3105668df5a1e4d8dc2a23ba80f3223ebb7 | [
"self.size = size\nself.que_list = [None] * self.size\nself.count = 0",
"i = self.count\nself.que_list[i] = enqueue_data\nself.count += 1",
"dequeued_value = self.que_list[0]\nfor i in range(0, len(self.que_list) - 1):\n self.que_list[i] = self.que_list[i + 1]\nself.que_list[len(self.que_list) - 1] = None\ns... | <|body_start_0|>
self.size = size
self.que_list = [None] * self.size
self.count = 0
<|end_body_0|>
<|body_start_1|>
i = self.count
self.que_list[i] = enqueue_data
self.count += 1
<|end_body_1|>
<|body_start_2|>
dequeued_value = self.que_list[0]
for i in ... | queクラス 引数：リストのサイズ | que | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
<|body_0|>
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
<|body_1|>
def dequeue(self):
"""デキューした値を返す"""
<|body_2|>
def is_empty(self):
"""空ならT... | stack_v2_sparse_classes_36k_train_004331 | 2,175 | no_license | [
{
"docstring": "引数：リストのサイズ",
"name": "__init__",
"signature": "def __init__(self, size)"
},
{
"docstring": "引数：エンキューしたい数値",
"name": "enqueue",
"signature": "def enqueue(self, enqueue_data)"
},
{
"docstring": "デキューした値を返す",
"name": "dequeue",
"signature": "def dequeue(self)... | 4 | stack_v2_sparse_classes_30k_test_000855 | Implement the Python class `que` described below.
Class description:
queクラス 引数：リストのサイズ
Method signatures and docstrings:
- def __init__(self, size): 引数：リストのサイズ
- def enqueue(self, enqueue_data): 引数：エンキューしたい数値
- def dequeue(self): デキューした値を返す
- def is_empty(self): 空ならTrue, 空でないならFalseを返す | Implement the Python class `que` described below.
Class description:
queクラス 引数：リストのサイズ
Method signatures and docstrings:
- def __init__(self, size): 引数：リストのサイズ
- def enqueue(self, enqueue_data): 引数：エンキューしたい数値
- def dequeue(self): デキューした値を返す
- def is_empty(self): 空ならTrue, 空でないならFalseを返す
<|skeleton|>
class que:
""... | c594461944316b6655ddaf7e877dd6b293649f53 | <|skeleton|>
class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
<|body_0|>
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
<|body_1|>
def dequeue(self):
"""デキューした値を返す"""
<|body_2|>
def is_empty(self):
"""空ならT... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class que:
"""queクラス 引数：リストのサイズ"""
def __init__(self, size):
"""引数：リストのサイズ"""
self.size = size
self.que_list = [None] * self.size
self.count = 0
def enqueue(self, enqueue_data):
"""引数：エンキューしたい数値"""
i = self.count
self.que_list[i] = enqueue_data
... | the_stack_v2_python_sparse | a0303_stack_que.py | j-d-0630/python | train | 0 |
fec16c9a90fdd5bdfa66b122f2004dbbaeeccb07 | [
"while True:\n r = rand7()\n c = rand7()\n n = c + (r - 1) * 7\n if n <= 40:\n break\nreturn 1 + (n - 1) % 10",
"while True:\n r = rand7()\n c = rand7()\n n = c + (r - 1) * 7\n if n <= 40:\n return 1 + (n - 1) % 10\n r = n - 40\n c = rand7()\n n = c + (r - 1) * 7\n ... | <|body_start_0|>
while True:
r = rand7()
c = rand7()
n = c + (r - 1) * 7
if n <= 40:
break
return 1 + (n - 1) % 10
<|end_body_0|>
<|body_start_1|>
while True:
r = rand7()
c = rand7()
n = c + (r -... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rand10(self):
""":rtype: int"""
<|body_0|>
def rand10_1(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
while True:
r = rand7()
c = rand7()
n = c + (r - 1) * 7
if n ... | stack_v2_sparse_classes_36k_train_004332 | 996 | no_license | [
{
"docstring": ":rtype: int",
"name": "rand10",
"signature": "def rand10(self)"
},
{
"docstring": ":rtype: int",
"name": "rand10_1",
"signature": "def rand10_1(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004467 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rand10(self): :rtype: int
- def rand10_1(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rand10(self): :rtype: int
- def rand10_1(self): :rtype: int
<|skeleton|>
class Solution:
def rand10(self):
""":rtype: int"""
<|body_0|>
def rand10_... | 394e89fd1881f4aa32e2fd81abc72dbc9eeec7bf | <|skeleton|>
class Solution:
def rand10(self):
""":rtype: int"""
<|body_0|>
def rand10_1(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def rand10(self):
""":rtype: int"""
while True:
r = rand7()
c = rand7()
n = c + (r - 1) * 7
if n <= 40:
break
return 1 + (n - 1) % 10
def rand10_1(self):
""":rtype: int"""
while True:
... | the_stack_v2_python_sparse | Random/rand10.py | Miracle-cl/Algorithms | train | 1 | |
79642d78bdfc4b8895089edb0cd6edcda84ff165 | [
"key = a2b_p('2b7e151628aed2a6abf7158809cf4f3c')\npt = 'This is a test case'\nalg1 = CBC(Rijndael(key, blockSize=32))\nalg2 = CBC(Rijndael(key, blockSize=32))\nct1 = alg1.encrypt(pt)\nct2 = alg2.encrypt(pt)\nself.assertNotEqual(ct1, ct2)",
"key = a2b_p('2b7e151628aed2a6abf7158809cf4f3c')\npt = 'This is yet anothe... | <|body_start_0|>
key = a2b_p('2b7e151628aed2a6abf7158809cf4f3c')
pt = 'This is a test case'
alg1 = CBC(Rijndael(key, blockSize=32))
alg2 = CBC(Rijndael(key, blockSize=32))
ct1 = alg1.encrypt(pt)
ct2 = alg2.encrypt(pt)
self.assertNotEqual(ct1, ct2)
<|end_body_0|>
... | CBC IV tests | CBC_Auto_IV_Test | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CBC_Auto_IV_Test:
"""CBC IV tests"""
def testIVuniqueness(self):
"""Test that two different instances have different IVs"""
<|body_0|>
def testIVmultencryptUnique(self):
"""Test that two different encrypts have different IVs"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_004333 | 5,430 | permissive | [
{
"docstring": "Test that two different instances have different IVs",
"name": "testIVuniqueness",
"signature": "def testIVuniqueness(self)"
},
{
"docstring": "Test that two different encrypts have different IVs",
"name": "testIVmultencryptUnique",
"signature": "def testIVmultencryptUniq... | 2 | stack_v2_sparse_classes_30k_train_001263 | Implement the Python class `CBC_Auto_IV_Test` described below.
Class description:
CBC IV tests
Method signatures and docstrings:
- def testIVuniqueness(self): Test that two different instances have different IVs
- def testIVmultencryptUnique(self): Test that two different encrypts have different IVs | Implement the Python class `CBC_Auto_IV_Test` described below.
Class description:
CBC IV tests
Method signatures and docstrings:
- def testIVuniqueness(self): Test that two different instances have different IVs
- def testIVmultencryptUnique(self): Test that two different encrypts have different IVs
<|skeleton|>
cla... | ed4d80d1e6f09634c12c0c3096e39667c6642b95 | <|skeleton|>
class CBC_Auto_IV_Test:
"""CBC IV tests"""
def testIVuniqueness(self):
"""Test that two different instances have different IVs"""
<|body_0|>
def testIVmultencryptUnique(self):
"""Test that two different encrypts have different IVs"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CBC_Auto_IV_Test:
"""CBC IV tests"""
def testIVuniqueness(self):
"""Test that two different instances have different IVs"""
key = a2b_p('2b7e151628aed2a6abf7158809cf4f3c')
pt = 'This is a test case'
alg1 = CBC(Rijndael(key, blockSize=32))
alg2 = CBC(Rijndael(key, b... | the_stack_v2_python_sparse | script.module.cryptolib/lib/cryptopy/cipher/cbc_test.py | gacj22/WizardGacj22 | train | 4 |
8088bc5b2311607af3c9946eb29481f6881a7730 | [
"self._ctor_args = ctor_args\nself._ctor_kwargs = ctor_kwargs\nself._init_method = init_method\nif isinstance(instance_cls, str):\n instance_cls = DeferLoad(instance_cls)\nself._instance_cls = instance_cls",
"args = []\nfor arg in self._ctor_args:\n if isinstance(arg, ClassProvider.Inject):\n arg = i... | <|body_start_0|>
self._ctor_args = ctor_args
self._ctor_kwargs = ctor_kwargs
self._init_method = init_method
if isinstance(instance_cls, str):
instance_cls = DeferLoad(instance_cls)
self._instance_cls = instance_cls
<|end_body_0|>
<|body_start_1|>
args = []
... | Provider for a particular class. | ClassProvider | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassProvider:
"""Provider for a particular class."""
def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs):
"""Initialize the class provider."""
<|body_0|>
def provide(self, config: BaseSettings, injector: BaseInjector):
... | stack_v2_sparse_classes_36k_train_004334 | 4,857 | permissive | [
{
"docstring": "Initialize the class provider.",
"name": "__init__",
"signature": "def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs)"
},
{
"docstring": "Provide the object instance given a config and injector.",
"name": "provide",
"signa... | 2 | stack_v2_sparse_classes_30k_val_000303 | Implement the Python class `ClassProvider` described below.
Class description:
Provider for a particular class.
Method signatures and docstrings:
- def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs): Initialize the class provider.
- def provide(self, config: BaseSetti... | Implement the Python class `ClassProvider` described below.
Class description:
Provider for a particular class.
Method signatures and docstrings:
- def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs): Initialize the class provider.
- def provide(self, config: BaseSetti... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class ClassProvider:
"""Provider for a particular class."""
def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs):
"""Initialize the class provider."""
<|body_0|>
def provide(self, config: BaseSettings, injector: BaseInjector):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassProvider:
"""Provider for a particular class."""
def __init__(self, instance_cls: Union[str, type], *ctor_args, init_method: str=None, **ctor_kwargs):
"""Initialize the class provider."""
self._ctor_args = ctor_args
self._ctor_kwargs = ctor_kwargs
self._init_method = ... | the_stack_v2_python_sparse | aries_cloudagent/config/provider.py | hyperledger/aries-cloudagent-python | train | 370 |
96748a3bc73d3ec479c89c274e543ead6c08b71d | [
"self._embed_fn = get_embed_fn(model=model, checkpoint_dir=checkpoint_dir, domain=domain, output_head=output_head, reduce_fn=reduce_fn)\nself._batch_size = batch_size\nself._domain = domain\nself._length = length",
"if isinstance(sequences[0], str):\n sequences = _encode_string_sequences(sequences, domain=self... | <|body_start_0|>
self._embed_fn = get_embed_fn(model=model, checkpoint_dir=checkpoint_dir, domain=domain, output_head=output_head, reduce_fn=reduce_fn)
self._batch_size = batch_size
self._domain = domain
self._length = length
<|end_body_0|>
<|body_start_1|>
if isinstance(sequenc... | Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches. | ProteinLMEmbedder | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProteinLMEmbedder:
"""Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches."""
def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='output_emb', reduce_fn=None, length=None, batch_size=64):
"""Cr... | stack_v2_sparse_classes_36k_train_004335 | 8,676 | permissive | [
{
"docstring": "Creates an instance of this class.",
"name": "__init__",
"signature": "def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='output_emb', reduce_fn=None, length=None, batch_size=64)"
},
{
"docstring": "Embeds int or string sequences.",
"name": "__call_... | 2 | stack_v2_sparse_classes_30k_train_010411 | Implement the Python class `ProteinLMEmbedder` described below.
Class description:
Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches.
Method signatures and docstrings:
- def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='out... | Implement the Python class `ProteinLMEmbedder` described below.
Class description:
Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches.
Method signatures and docstrings:
- def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='out... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ProteinLMEmbedder:
"""Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches."""
def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='output_emb', reduce_fn=None, length=None, batch_size=64):
"""Cr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProteinLMEmbedder:
"""Embeddings from a pretrained language model. Stateful wrapper around get_embed_fn that calls the embed_fn on batches."""
def __init__(self, model=None, checkpoint_dir=None, domain=None, output_head='output_emb', reduce_fn=None, length=None, batch_size=64):
"""Creates an inst... | the_stack_v2_python_sparse | protein_lm/embed.py | Jimmy-INL/google-research | train | 1 |
1101252e4a0da3f106ed0c7355b191d927e73fc7 | [
"self.api = EnrollmentApi(self.locust.host, self.client)\nself.auto_auth()\nfor course_id in settings.data['COURSE_ID_LIST']:\n self.api.enroll(course_id)",
"course_id = random.choice(settings.data['COURSE_ID_LIST'])\ntry:\n self.api.get_user_enrollment_status(self.username, course_id)\nexcept NotAuthorized... | <|body_start_0|>
self.api = EnrollmentApi(self.locust.host, self.client)
self.auto_auth()
for course_id in settings.data['COURSE_ID_LIST']:
self.api.enroll(course_id)
<|end_body_0|>
<|body_start_1|>
course_id = random.choice(settings.data['COURSE_ID_LIST'])
try:
... | User scripts in which the user is already authenticated and enrolled. | AuthenticatedAndEnrolledTasks | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticatedAndEnrolledTasks:
"""User scripts in which the user is already authenticated and enrolled."""
def on_start(self):
"""Ensure the user is logged in and enrolled."""
<|body_0|>
def user_enrollment_status(self):
"""Check a user's enrollment status in a c... | stack_v2_sparse_classes_36k_train_004336 | 8,385 | permissive | [
{
"docstring": "Ensure the user is logged in and enrolled.",
"name": "on_start",
"signature": "def on_start(self)"
},
{
"docstring": "Check a user's enrollment status in a course.",
"name": "user_enrollment_status",
"signature": "def user_enrollment_status(self)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_val_000297 | Implement the Python class `AuthenticatedAndEnrolledTasks` described below.
Class description:
User scripts in which the user is already authenticated and enrolled.
Method signatures and docstrings:
- def on_start(self): Ensure the user is logged in and enrolled.
- def user_enrollment_status(self): Check a user's enr... | Implement the Python class `AuthenticatedAndEnrolledTasks` described below.
Class description:
User scripts in which the user is already authenticated and enrolled.
Method signatures and docstrings:
- def on_start(self): Ensure the user is logged in and enrolled.
- def user_enrollment_status(self): Check a user's enr... | 1a6dc891d2fb72575f354521988a531489f30032 | <|skeleton|>
class AuthenticatedAndEnrolledTasks:
"""User scripts in which the user is already authenticated and enrolled."""
def on_start(self):
"""Ensure the user is logged in and enrolled."""
<|body_0|>
def user_enrollment_status(self):
"""Check a user's enrollment status in a c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthenticatedAndEnrolledTasks:
"""User scripts in which the user is already authenticated and enrolled."""
def on_start(self):
"""Ensure the user is logged in and enrolled."""
self.api = EnrollmentApi(self.locust.host, self.client)
self.auto_auth()
for course_id in setting... | the_stack_v2_python_sparse | loadtests/enrollment/locustfile.py | kavithachandra/edx-load-tests | train | 0 |
dfc1a267b98c05c9155135be2b98fd70c9bc08d2 | [
"n = len(s)\ndp = [[False for _ in range(n)] for _ in range(n)]\nmax_len, left, right = (0, 0, 0)\nfor j in range(n):\n for i in range(j + 1):\n if s[i] != s[j]:\n continue\n dp[i][j] = j - i < 2 or dp[i + 1][j - 1]\n if dp[i][j] and j - i + 1 > max_len:\n max_len = j -... | <|body_start_0|>
n = len(s)
dp = [[False for _ in range(n)] for _ in range(n)]
max_len, left, right = (0, 0, 0)
for j in range(n):
for i in range(j + 1):
if s[i] != s[j]:
continue
dp[i][j] = j - i < 2 or dp[i + 1][j - 1]
... | Solution | [
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindromeDP(self, s: str) -> str:
"""动态规划，可用滚动数组进行空间优化"""
<|body_0|>
def longestPalindrome(self, s: str) -> str:
"""中心扩展"""
<|body_1|>
def longestPalindromeManacher(self, s: str) -> str:
"""Manacher 算法"""
<|body_2|>
... | stack_v2_sparse_classes_36k_train_004337 | 4,053 | permissive | [
{
"docstring": "动态规划，可用滚动数组进行空间优化",
"name": "longestPalindromeDP",
"signature": "def longestPalindromeDP(self, s: str) -> str"
},
{
"docstring": "中心扩展",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s: str) -> str"
},
{
"docstring": "Manacher 算法",
"na... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindromeDP(self, s: str) -> str: 动态规划，可用滚动数组进行空间优化
- def longestPalindrome(self, s: str) -> str: 中心扩展
- def longestPalindromeManacher(self, s: str) -> str: Manacher ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindromeDP(self, s: str) -> str: 动态规划，可用滚动数组进行空间优化
- def longestPalindrome(self, s: str) -> str: 中心扩展
- def longestPalindromeManacher(self, s: str) -> str: Manacher ... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def longestPalindromeDP(self, s: str) -> str:
"""动态规划，可用滚动数组进行空间优化"""
<|body_0|>
def longestPalindrome(self, s: str) -> str:
"""中心扩展"""
<|body_1|>
def longestPalindromeManacher(self, s: str) -> str:
"""Manacher 算法"""
<|body_2|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindromeDP(self, s: str) -> str:
"""动态规划，可用滚动数组进行空间优化"""
n = len(s)
dp = [[False for _ in range(n)] for _ in range(n)]
max_len, left, right = (0, 0, 0)
for j in range(n):
for i in range(j + 1):
if s[i] != s[j]:
... | the_stack_v2_python_sparse | 5.最长回文子串/solution.py | QtTao/daily_leetcode | train | 0 | |
a0d60c61b5522d1ef0d920f801b5aff443519660 | [
"super(FeatureExtractor, self).__init__()\nself.submodule = submodule\nself.extracted_layers = extracted_layers",
"outputs = []\nfor index, (name, module) in enumerate(self.submodule._modules.items()):\n if name is 'fc':\n x = x.view(x.size(0), -1)\n x = module(x)\n print(index, name)\n if name... | <|body_start_0|>
super(FeatureExtractor, self).__init__()
self.submodule = submodule
self.extracted_layers = extracted_layers
<|end_body_0|>
<|body_start_1|>
outputs = []
for index, (name, module) in enumerate(self.submodule._modules.items()):
if name is 'fc':
... | 中间特征提取 | FeatureExtractor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureExtractor:
"""中间特征提取"""
def __init__(self, submodule, extracted_layers):
""":param submodule: :param extracted_layers: extracted layer name or layer index list"""
<|body_0|>
def forward(self, x):
"""add fc layer adapter :param x: :return:"""
<|body... | stack_v2_sparse_classes_36k_train_004338 | 2,376 | no_license | [
{
"docstring": ":param submodule: :param extracted_layers: extracted layer name or layer index list",
"name": "__init__",
"signature": "def __init__(self, submodule, extracted_layers)"
},
{
"docstring": "add fc layer adapter :param x: :return:",
"name": "forward",
"signature": "def forwa... | 2 | null | Implement the Python class `FeatureExtractor` described below.
Class description:
中间特征提取
Method signatures and docstrings:
- def __init__(self, submodule, extracted_layers): :param submodule: :param extracted_layers: extracted layer name or layer index list
- def forward(self, x): add fc layer adapter :param x: :retu... | Implement the Python class `FeatureExtractor` described below.
Class description:
中间特征提取
Method signatures and docstrings:
- def __init__(self, submodule, extracted_layers): :param submodule: :param extracted_layers: extracted layer name or layer index list
- def forward(self, x): add fc layer adapter :param x: :retu... | d3e44fad42809f23762c9028d8b1d478acf42ab2 | <|skeleton|>
class FeatureExtractor:
"""中间特征提取"""
def __init__(self, submodule, extracted_layers):
""":param submodule: :param extracted_layers: extracted layer name or layer index list"""
<|body_0|>
def forward(self, x):
"""add fc layer adapter :param x: :return:"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureExtractor:
"""中间特征提取"""
def __init__(self, submodule, extracted_layers):
""":param submodule: :param extracted_layers: extracted layer name or layer index list"""
super(FeatureExtractor, self).__init__()
self.submodule = submodule
self.extracted_layers = extracted_l... | the_stack_v2_python_sparse | modules/featuremap/feature_extractor.py | CaravanPassenger/pytorch-learning-notes | train | 0 |
1c79e15ea360e66ac3deee6041a1a4408c861313 | [
"patch_data = {}\nfor f in self.editable_fields:\n patch_data[f] = f\ncourse_instance_id = self.test_settings['test_course_SB_ILE']['cid']\nself.api.patch_course_instance_details(course_instance_id, patch_data)\nself._load_test_course('test_course_SB_ILE')\nself.assertTrue(self.detail_page.is_loaded())\noriginal... | <|body_start_0|>
patch_data = {}
for f in self.editable_fields:
patch_data[f] = f
course_instance_id = self.test_settings['test_course_SB_ILE']['cid']
self.api.patch_course_instance_details(course_instance_id, patch_data)
self._load_test_course('test_course_SB_ILE')
... | CourseInfoDetailsEditTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CourseInfoDetailsEditTests:
def test_edit_fields(self):
"""TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify against original)"""
<|body_0|>
def test_reset_form(self):
"""TLT-2524 (AC 1, 2) TLT-2525 (AC 22... | stack_v2_sparse_classes_36k_train_004339 | 3,030 | no_license | [
{
"docstring": "TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify against original)",
"name": "test_edit_fields",
"signature": "def test_edit_fields(self)"
},
{
"docstring": "TLT-2524 (AC 1, 2) TLT-2525 (AC 22) verify edit form reset ... | 2 | null | Implement the Python class `CourseInfoDetailsEditTests` described below.
Class description:
Implement the CourseInfoDetailsEditTests class.
Method signatures and docstrings:
- def test_edit_fields(self): TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify ag... | Implement the Python class `CourseInfoDetailsEditTests` described below.
Class description:
Implement the CourseInfoDetailsEditTests class.
Method signatures and docstrings:
- def test_edit_fields(self): TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify ag... | c00f9af5bbe344d0cbf71bcdfe2c3af85ae4be4a | <|skeleton|>
class CourseInfoDetailsEditTests:
def test_edit_fields(self):
"""TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify against original)"""
<|body_0|>
def test_reset_form(self):
"""TLT-2524 (AC 1, 2) TLT-2525 (AC 22... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CourseInfoDetailsEditTests:
def test_edit_fields(self):
"""TLT-2523 (AC 2-11) verify editing fields in SB/ILE courses (capture original fields, edit, save, reload, verify against original)"""
patch_data = {}
for f in self.editable_fields:
patch_data[f] = f
course_in... | the_stack_v2_python_sparse | selenium_tests/course_info/course_info_details_edit_tests.py | Harvard-University-iCommons/canvas_account_admin_tools | train | 4 | |
33ec09ba13f6846d5027bb4199082f3bab99bd67 | [
"if not l or not r or r < l:\n return list()\nt = list()\nfor i in range(l, r + 1, 1):\n if self.is_self_dividing(i):\n t.append(i)\nreturn t",
"if not i:\n return False\np = i\nwhile p > 0:\n p, d = divmod(p, 10)\n if d == 0 or i % d != 0:\n return False\nreturn True"
] | <|body_start_0|>
if not l or not r or r < l:
return list()
t = list()
for i in range(l, r + 1, 1):
if self.is_self_dividing(i):
t.append(i)
return t
<|end_body_0|>
<|body_start_1|>
if not i:
return False
p = i
w... | Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range | Solution2 | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers... | stack_v2_sparse_classes_36k_train_004340 | 3,918 | permissive | [
{
"docstring": "Determines all self-dividing numbers within target limits (inclusive). :param int l: lower limit of target range :param int r: upper limit of target range :return: array of all self-dividing numbers in range :rtype: list[int]",
"name": "find_self_dividing_nums",
"signature": "def find_se... | 2 | stack_v2_sparse_classes_30k_train_018486 | Implement the Python class `Solution2` described below.
Class description:
Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range
Method signatures and docstrings:
- def find_self_dividi... | Implement the Python class `Solution2` described below.
Class description:
Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range
Method signatures and docstrings:
- def find_self_dividi... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution2:
"""Iteration over all integers in range. Time complexity: O(n ** m) - Amortized iterate over all integers and contained digits Space complexity: O(n) - Amortized store all integers in range"""
def find_self_dividing_nums(self, l, r):
"""Determines all self-dividing numbers within targe... | the_stack_v2_python_sparse | 0728_self_dividing_numbers/python_source.py | arthurdysart/LeetCode | train | 0 |
26790fe126a31a8310887306caaa4a3a8a218b1b | [
"self.lang = 'he'\nself.cache = {}\nself.tokenizer = Hebrew().tokenizer",
"if profession not in self.cache:\n self.cache[profession] = self._get_gender(profession)\nreturn self.cache[profession]",
"if not profession.strip():\n return GENDER.unknown\ntoks = [w.text for w in self.tokenizer(profession) if w.... | <|body_start_0|>
self.lang = 'he'
self.cache = {}
self.tokenizer = Hebrew().tokenizer
<|end_body_0|>
<|body_start_1|>
if profession not in self.cache:
self.cache[profession] = self._get_gender(profession)
return self.cache[profession]
<|end_body_1|>
<|body_start_2|>... | Hebrew morphology heurstics. | HebrewPredictor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HebrewPredictor:
"""Hebrew morphology heurstics."""
def __init__(self):
"""Init tokenizer for Hebrew."""
<|body_0|>
def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None) -> GENDER:
"""Predict gender of an input profession."... | stack_v2_sparse_classes_36k_train_004341 | 3,035 | permissive | [
{
"docstring": "Init tokenizer for Hebrew.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Predict gender of an input profession.",
"name": "get_gender",
"signature": "def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None)... | 3 | stack_v2_sparse_classes_30k_train_019907 | Implement the Python class `HebrewPredictor` described below.
Class description:
Hebrew morphology heurstics.
Method signatures and docstrings:
- def __init__(self): Init tokenizer for Hebrew.
- def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None) -> GENDER: Predict gender of ... | Implement the Python class `HebrewPredictor` described below.
Class description:
Hebrew morphology heurstics.
Method signatures and docstrings:
- def __init__(self): Init tokenizer for Hebrew.
- def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None) -> GENDER: Predict gender of ... | 586292861cf2efdda2dec03c69c3408995a8b293 | <|skeleton|>
class HebrewPredictor:
"""Hebrew morphology heurstics."""
def __init__(self):
"""Init tokenizer for Hebrew."""
<|body_0|>
def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None) -> GENDER:
"""Predict gender of an input profession."... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HebrewPredictor:
"""Hebrew morphology heurstics."""
def __init__(self):
"""Init tokenizer for Hebrew."""
self.lang = 'he'
self.cache = {}
self.tokenizer = Hebrew().tokenizer
def get_gender(self, profession: str, translated_sent=None, entity_index=None, ds_entry=None) ... | the_stack_v2_python_sparse | src/languages/semitic_languages.py | gabrielStanovsky/mt_gender | train | 42 |
19397c86fc47d3b7898c6c19774b885bbc921971 | [
"self.surface = pygame.Surface(dim)\nself.particles = []\nfor counter in range(count):\n pos = pygame.Vector2(random.randint(0, self.surface.get_width()), random.randint(0, self.surface.get_height()))\n direction = pygame.Vector2(10 * (random.random() - 0.5), 10 * (random.random() - 0.5))\n color = pygame.... | <|body_start_0|>
self.surface = pygame.Surface(dim)
self.particles = []
for counter in range(count):
pos = pygame.Vector2(random.randint(0, self.surface.get_width()), random.randint(0, self.surface.get_height()))
direction = pygame.Vector2(10 * (random.random() - 0.5), 10... | Particles | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Particles:
def __init__(self, dim: tuple, count: int):
"""clas to draw some particles :param surface: surface to draw on :param count: number of particles"""
<|body_0|>
def update(self):
"""update every frame"""
<|body_1|>
def collide(self, p1, p2):
... | stack_v2_sparse_classes_36k_train_004342 | 5,061 | no_license | [
{
"docstring": "clas to draw some particles :param surface: surface to draw on :param count: number of particles",
"name": "__init__",
"signature": "def __init__(self, dim: tuple, count: int)"
},
{
"docstring": "update every frame",
"name": "update",
"signature": "def update(self)"
},
... | 3 | stack_v2_sparse_classes_30k_train_017804 | Implement the Python class `Particles` described below.
Class description:
Implement the Particles class.
Method signatures and docstrings:
- def __init__(self, dim: tuple, count: int): clas to draw some particles :param surface: surface to draw on :param count: number of particles
- def update(self): update every fr... | Implement the Python class `Particles` described below.
Class description:
Implement the Particles class.
Method signatures and docstrings:
- def __init__(self, dim: tuple, count: int): clas to draw some particles :param surface: surface to draw on :param count: number of particles
- def update(self): update every fr... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class Particles:
def __init__(self, dim: tuple, count: int):
"""clas to draw some particles :param surface: surface to draw on :param count: number of particles"""
<|body_0|>
def update(self):
"""update every frame"""
<|body_1|>
def collide(self, p1, p2):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Particles:
def __init__(self, dim: tuple, count: int):
"""clas to draw some particles :param surface: surface to draw on :param count: number of particles"""
self.surface = pygame.Surface(dim)
self.particles = []
for counter in range(count):
pos = pygame.Vector2(ran... | the_stack_v2_python_sparse | effects/Particle.py | gunny26/pygame | train | 5 | |
62ba9181469bc68587bdf01abb40b86854fc38a4 | [
"rdd_rows = spark.sparkContext.parallelize([data])\nresult_df = DataWriter.df_from_rdd(rdd_rows, data, spark)\nresult_df.write.json(target_file, mode=write_mode)",
"if isinstance(rec, dict):\n return pst.StructType([pst.StructField(key, DataWriter.infer_schema(value), True) for key, value in sorted(rec.items()... | <|body_start_0|>
rdd_rows = spark.sparkContext.parallelize([data])
result_df = DataWriter.df_from_rdd(rdd_rows, data, spark)
result_df.write.json(target_file, mode=write_mode)
<|end_body_0|>
<|body_start_1|>
if isinstance(rec, dict):
return pst.StructType([pst.StructField(ke... | DataWriter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataWriter:
def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE):
"""TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of different data type"""
<|body_0|>
def infer_schema(rec):
"""infers dataframe schem... | stack_v2_sparse_classes_36k_train_004343 | 4,336 | no_license | [
{
"docstring": "TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of different data type",
"name": "write_dict_as_json",
"signature": "def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE)"
},
{
"docstring": "infers dataframe schema f... | 4 | stack_v2_sparse_classes_30k_train_001310 | Implement the Python class `DataWriter` described below.
Class description:
Implement the DataWriter class.
Method signatures and docstrings:
- def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE): TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of diff... | Implement the Python class `DataWriter` described below.
Class description:
Implement the DataWriter class.
Method signatures and docstrings:
- def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE): TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of diff... | 7d5d2faafcd0b2e5d35fa0e486bc3617f8e30a9e | <|skeleton|>
class DataWriter:
def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE):
"""TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of different data type"""
<|body_0|>
def infer_schema(rec):
"""infers dataframe schem... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataWriter:
def write_dict_as_json(spark, data, target_file, write_mode=WriteMode.OVERWRITE):
"""TODO: 1) failing on dict with non-string keys TODO: 2) failing on list with elements of different data type"""
rdd_rows = spark.sparkContext.parallelize([data])
result_df = DataWriter.df_fr... | the_stack_v2_python_sparse | bi/common/datawriter.py | Srinidhi-SA/mAdvisorProdML | train | 0 | |
972ef33f847a79b3b0f854d478ca1b1621895249 | [
"self.key = self._randomKeyOrIV()\nself.iv = self._randomKeyOrIV()\nself.org_msg = msg\nself.mode = self._randomMode()\nprependmsg = bytearray()\nappendmsg = bytearray()\nfor i in range(randint(5, 10)):\n prependmsg.append(randint(0, 255))\nfor i in range(randint(5, 10)):\n appendmsg.append(randint(0, 255))\n... | <|body_start_0|>
self.key = self._randomKeyOrIV()
self.iv = self._randomKeyOrIV()
self.org_msg = msg
self.mode = self._randomMode()
prependmsg = bytearray()
appendmsg = bytearray()
for i in range(randint(5, 10)):
prependmsg.append(randint(0, 255))
... | This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used? In order to check, need that info (for debug). That's why I will use an object with... | Encryption_Oracle | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encryption_Oracle:
"""This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used? In order to check, need that info (for... | stack_v2_sparse_classes_36k_train_004344 | 3,525 | permissive | [
{
"docstring": "Takes msg in bytes or bytearray to create randomly encrypted msg with a prepend of 5-10 bytes and a append of 5-10 bytes (both random). Standard is size 128.",
"name": "__init__",
"signature": "def __init__(self, msg, makeblock=128)"
},
{
"docstring": "Picks a random number for w... | 3 | stack_v2_sparse_classes_30k_train_011794 | Implement the Python class `Encryption_Oracle` described below.
Class description:
This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used?... | Implement the Python class `Encryption_Oracle` described below.
Class description:
This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used?... | 7da9d5b615183b9479ec4375c0c7b89bb2161b1d | <|skeleton|>
class Encryption_Oracle:
"""This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used? In order to check, need that info (for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encryption_Oracle:
"""This is a object that generates a random msg encrypted under AES 128 eBC or CBC. (Do I want to leave this as an object? Or just as a large funciton.) In msg (in bytes/bytearray) Out prepended and random. Where is the key and iv it used? In order to check, need that info (for debug). That... | the_stack_v2_python_sparse | Set2/Code/11-ECB-CBC-Oracle.py~ | Jason429/CryptoPalsChallenge | train | 0 |
0c80cbe1f913b936bb780d6c8ae9b16d2419b8f3 | [
"colors = [0, 255, 100]\nheight = 28\nsize = height * height\nrecords = bytes(bytearray([1] * 16 + [colors[0]] * size + [colors[1]] * size + [colors[2]] * size))\nexpecteds = [np.zeros((height, height)) + colors[0], np.zeros((height, height)) + colors[1], np.zeros((height, height)) + colors[2]]\nimage_filename = os... | <|body_start_0|>
colors = [0, 255, 100]
height = 28
size = height * height
records = bytes(bytearray([1] * 16 + [colors[0]] * size + [colors[1]] * size + [colors[2]] * size))
expecteds = [np.zeros((height, height)) + colors[0], np.zeros((height, height)) + colors[1], np.zeros((he... | MnistShiftTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MnistShiftTest:
def testReadImage(self):
"""Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file function with the temporary file. Checks whether the order and value of pixels are correct for all 3 images.... | stack_v2_sparse_classes_36k_train_004345 | 4,763 | permissive | [
{
"docstring": "Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file function with the temporary file. Checks whether the order and value of pixels are correct for all 3 images.",
"name": "testReadImage",
"signature": "de... | 4 | stack_v2_sparse_classes_30k_train_002893 | Implement the Python class `MnistShiftTest` described below.
Class description:
Implement the MnistShiftTest class.
Method signatures and docstrings:
- def testReadImage(self): Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file funct... | Implement the Python class `MnistShiftTest` described below.
Class description:
Implement the MnistShiftTest class.
Method signatures and docstrings:
- def testReadImage(self): Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file funct... | 5b98fbb84408d566ae4ef0878008931a65832386 | <|skeleton|>
class MnistShiftTest:
def testReadImage(self):
"""Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file function with the temporary file. Checks whether the order and value of pixels are correct for all 3 images.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MnistShiftTest:
def testReadImage(self):
"""Tests if the records are read in the expected order and value. Writes 3 images of size 28*28 into a temporary file. Calls the read_file function with the temporary file. Checks whether the order and value of pixels are correct for all 3 images."""
co... | the_stack_v2_python_sparse | input_data/mnist/mnist_shift_test.py | Cerenaut/sparse-unsupervised-capsules | train | 5 | |
f43563b7f9b406c875811917b9f207132a84795e | [
"argv = splitargs(line)\nif len(argv) != 3:\n return self.do_help('memcpy')\ndst = self.parseExpression(argv[0])\nsrc = self.parseExpression(argv[1])\nsiz = self.parseExpression(argv[2])\nmem = self.memobj.readMemory(src, siz)\nself.memobj.writeMemory(dst, mem)",
"if len(line) == 0:\n return self.do_help('m... | <|body_start_0|>
argv = splitargs(line)
if len(argv) != 3:
return self.do_help('memcpy')
dst = self.parseExpression(argv[0])
src = self.parseExpression(argv[1])
siz = self.parseExpression(argv[2])
mem = self.memobj.readMemory(src, siz)
self.memobj.writ... | Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace) | EnviMutableCli | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnviMutableCli:
"""Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace)"""
def do_memcpy(self, line):
"""Copy memory from one location to another... Usage: memcpy <dest_expr> <src_expr> <size_expr>"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_004346 | 29,731 | permissive | [
{
"docstring": "Copy memory from one location to another... Usage: memcpy <dest_expr> <src_expr> <size_expr>",
"name": "do_memcpy",
"signature": "def do_memcpy(self, line)"
},
{
"docstring": "Change the memory permissions of a given page/map. Usage: memprotect [options] <addr_expr> <perms> -S <s... | 3 | null | Implement the Python class `EnviMutableCli` described below.
Class description:
Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace)
Method signatures and docstrings:
- def do_memcpy(self, line): Copy memory from one location to another... Usage: memcpy <dest_... | Implement the Python class `EnviMutableCli` described below.
Class description:
Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace)
Method signatures and docstrings:
- def do_memcpy(self, line): Copy memory from one location to another... Usage: memcpy <dest_... | b07e161cc28b19fdda0d047eefafed22c5b00f15 | <|skeleton|>
class EnviMutableCli:
"""Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace)"""
def do_memcpy(self, line):
"""Copy memory from one location to another... Usage: memcpy <dest_expr> <src_expr> <size_expr>"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EnviMutableCli:
"""Cli extensions which require a mutable memory object (emulator/trace) rather than a static one (viv workspace)"""
def do_memcpy(self, line):
"""Copy memory from one location to another... Usage: memcpy <dest_expr> <src_expr> <size_expr>"""
argv = splitargs(line)
... | the_stack_v2_python_sparse | envi/cli.py | vivisect/vivisect | train | 833 |
578f25cf0f64c96b315aba529fc3c20b577734b6 | [
"if len(np.shape(x_t)) > 1 and np.shape(x_t)[1] > 1:\n x_next_mean = x_t.dot(self.parameters.A.T)\n x_next = np.linalg.solve(self.parameters.LQinv.T, np.random.normal(size=x_t.shape).T).T + x_next_mean\n return x_next\nelse:\n x_next_mean = x_t * self.parameters.A\n x_next = self.parameters.LQinv ** ... | <|body_start_0|>
if len(np.shape(x_t)) > 1 and np.shape(x_t)[1] > 1:
x_next_mean = x_t.dot(self.parameters.A.T)
x_next = np.linalg.solve(self.parameters.LQinv.T, np.random.normal(size=x_t.shape).T).T + x_next_mean
return x_next
else:
x_next_mean = x_t * se... | Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters) | LGSSMPriorKernel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LGSSMPriorKernel:
"""Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters)"""
def rv(self, x_t, **kwargs):
"""Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, x_t Return: x_next (ndarray): N by n, x_{t+1}"""
... | stack_v2_sparse_classes_36k_train_004347 | 7,345 | permissive | [
{
"docstring": "Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, x_t Return: x_next (ndarray): N by n, x_{t+1}",
"name": "rv",
"signature": "def rv(self, x_t, **kwargs)"
},
{
"docstring": "Reweight function for Prior Kernel for LGSSM weight_t = P... | 2 | stack_v2_sparse_classes_30k_train_020962 | Implement the Python class `LGSSMPriorKernel` described below.
Class description:
Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters)
Method signatures and docstrings:
- def rv(self, x_t, **kwargs): Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, ... | Implement the Python class `LGSSMPriorKernel` described below.
Class description:
Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters)
Method signatures and docstrings:
- def rv(self, x_t, **kwargs): Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, ... | b4f04637165c13fd7b3e042b36ad9b77d2528733 | <|skeleton|>
class LGSSMPriorKernel:
"""Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters)"""
def rv(self, x_t, **kwargs):
"""Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, x_t Return: x_next (ndarray): N by n, x_{t+1}"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LGSSMPriorKernel:
"""Prior Kernel for LGSSM K(x_{t+1} | x_t) = Pr(x_{t+1} | x_t, parameters)"""
def rv(self, x_t, **kwargs):
"""Prior Kernel for LGSSM Sample x_{t+1} ~ Pr(x_{t+1} | x_t, parameters) Args: x_t (ndarray): N by n, x_t Return: x_next (ndarray): N by n, x_{t+1}"""
if len(np.sha... | the_stack_v2_python_sparse | sgmcmc_ssm/models/lgssm/kernels.py | PeiKaLunCi/sgmcmc_ssm_code | train | 0 |
1dee58ad853b27fa553e17ac68436433645def6b | [
"stack = []\npreorder = ''\ncur = root\nstack.append(root)\nwhile cur or stack:\n cur = stack.pop()\n if cur:\n preorder += str(cur.val) + ','\n else:\n preorder += 'null' + ','\n if cur:\n stack.append(cur.right)\n stack.append(cur.left)\nreturn preorder",
"preorder_list =... | <|body_start_0|>
stack = []
preorder = ''
cur = root
stack.append(root)
while cur or stack:
cur = stack.pop()
if cur:
preorder += str(cur.val) + ','
else:
preorder += 'null' + ','
if cur:
... | 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_004348 | 2,047 | 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_009310 | 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:... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|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"""
stack = []
preorder = ''
cur = root
stack.append(root)
while cur or stack:
cur = stack.pop()
if cur:
preorder += s... | the_stack_v2_python_sparse | 剑指 Offer 37. 序列化二叉树.py | yangyuxiang1996/leetcode | train | 0 | |
3cdfdf40f3c526c20256a645b08f0a15b337929e | [
"self.enter_mtz()\nself.swipe_to_up(1)\nself.enter_collect()\nself.myClick(self.find_element('第一个商品', *self.by_first_collected_goods_id))\nself.assertTrue(self.is_collected('普通团'))\nself.myClick(self.find_element('收藏', *self.by_collect_id))\nself.assertTrue(not self.is_collected('普通团'))",
"self.enter_mtz()\nself.... | <|body_start_0|>
self.enter_mtz()
self.swipe_to_up(1)
self.enter_collect()
self.myClick(self.find_element('第一个商品', *self.by_first_collected_goods_id))
self.assertTrue(self.is_collected('普通团'))
self.myClick(self.find_element('收藏', *self.by_collect_id))
self.assertT... | MyCollect | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyCollect:
def test_buy_collect(self):
"""萌团长_购买商品_收藏切换"""
<|body_0|>
def test_distribution_collect(self):
"""萌团长_分销商品_收藏切换"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.enter_mtz()
self.swipe_to_up(1)
self.enter_collect()
... | stack_v2_sparse_classes_36k_train_004349 | 1,433 | no_license | [
{
"docstring": "萌团长_购买商品_收藏切换",
"name": "test_buy_collect",
"signature": "def test_buy_collect(self)"
},
{
"docstring": "萌团长_分销商品_收藏切换",
"name": "test_distribution_collect",
"signature": "def test_distribution_collect(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013164 | Implement the Python class `MyCollect` described below.
Class description:
Implement the MyCollect class.
Method signatures and docstrings:
- def test_buy_collect(self): 萌团长_购买商品_收藏切换
- def test_distribution_collect(self): 萌团长_分销商品_收藏切换 | Implement the Python class `MyCollect` described below.
Class description:
Implement the MyCollect class.
Method signatures and docstrings:
- def test_buy_collect(self): 萌团长_购买商品_收藏切换
- def test_distribution_collect(self): 萌团长_分销商品_收藏切换
<|skeleton|>
class MyCollect:
def test_buy_collect(self):
"""萌团长_购买... | b2066139eb0723eff69d971589b283b4b776c84c | <|skeleton|>
class MyCollect:
def test_buy_collect(self):
"""萌团长_购买商品_收藏切换"""
<|body_0|>
def test_distribution_collect(self):
"""萌团长_分销商品_收藏切换"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyCollect:
def test_buy_collect(self):
"""萌团长_购买商品_收藏切换"""
self.enter_mtz()
self.swipe_to_up(1)
self.enter_collect()
self.myClick(self.find_element('第一个商品', *self.by_first_collected_goods_id))
self.assertTrue(self.is_collected('普通团'))
self.myClick(self.f... | the_stack_v2_python_sparse | TestCase/4_5/TC_Meng_TZ/test_collect_goods.py | testerSunshine/auto_md | train | 4 | |
83c0b70fcf56401f49bfb8cc4801d338245a861e | [
"parser = reqparse.RequestParser()\nparser.add_argument('name', type=str, required=True, help='This field cannot be left blank!')\nparser.add_argument('organization_ids', type=int, required=True, action='append')\nparser.add_argument('encrypted', type=int, required=False)\ndata = parser.parse_args()\nname = data['n... | <|body_start_0|>
parser = reqparse.RequestParser()
parser.add_argument('name', type=str, required=True, help='This field cannot be left blank!')
parser.add_argument('organization_ids', type=int, required=True, action='append')
parser.add_argument('encrypted', type=int, required=False)
... | Collaboration | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Collaboration:
def post(self):
"""create a new collaboration"""
<|body_0|>
def get(self, id=None):
"""collaboration or list of collaborations in case no id is provided"""
<|body_1|>
def patch(self, id):
"""update a collaboration"""
<|body... | stack_v2_sparse_classes_36k_train_004350 | 14,133 | permissive | [
{
"docstring": "create a new collaboration",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "collaboration or list of collaborations in case no id is provided",
"name": "get",
"signature": "def get(self, id=None)"
},
{
"docstring": "update a collaboration",
"... | 4 | stack_v2_sparse_classes_30k_train_012563 | Implement the Python class `Collaboration` described below.
Class description:
Implement the Collaboration class.
Method signatures and docstrings:
- def post(self): create a new collaboration
- def get(self, id=None): collaboration or list of collaborations in case no id is provided
- def patch(self, id): update a c... | Implement the Python class `Collaboration` described below.
Class description:
Implement the Collaboration class.
Method signatures and docstrings:
- def post(self): create a new collaboration
- def get(self, id=None): collaboration or list of collaborations in case no id is provided
- def patch(self, id): update a c... | a64827981db26b34dd1dcea1cb2282d03dd4545d | <|skeleton|>
class Collaboration:
def post(self):
"""create a new collaboration"""
<|body_0|>
def get(self, id=None):
"""collaboration or list of collaborations in case no id is provided"""
<|body_1|>
def patch(self, id):
"""update a collaboration"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Collaboration:
def post(self):
"""create a new collaboration"""
parser = reqparse.RequestParser()
parser.add_argument('name', type=str, required=True, help='This field cannot be left blank!')
parser.add_argument('organization_ids', type=int, required=True, action='append')
... | the_stack_v2_python_sparse | vantage6/server/resource/collaboration.py | mindrenee/vantage6-server | train | 0 | |
b02426f09e4c9a8b9fb5962d3e4dec3601109fda | [
"i, j = (0, num)\nwhile i <= j:\n mid = (i + j) // 2\n s = mid ** 2\n if s == num:\n return True\n elif s < num:\n i = mid + 1\n else:\n j = mid - 1\nreturn False",
"if num < 0:\n return False\nelif num == 1:\n return True\ni, j, last = (0, num, -1)\nwhile i <= j:\n mi... | <|body_start_0|>
i, j = (0, num)
while i <= j:
mid = (i + j) // 2
s = mid ** 2
if s == num:
return True
elif s < num:
i = mid + 1
else:
j = mid - 1
return False
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
<|body_0|>
def isPerfectSquare2(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i, j = (0, num)
while i <= j:
... | stack_v2_sparse_classes_36k_train_004351 | 1,736 | no_license | [
{
"docstring": ":type num: int :rtype: bool",
"name": "isPerfectSquare",
"signature": "def isPerfectSquare(self, num)"
},
{
"docstring": ":type num: int :rtype: bool",
"name": "isPerfectSquare2",
"signature": "def isPerfectSquare2(self, num)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPerfectSquare(self, num): :type num: int :rtype: bool
- def isPerfectSquare2(self, num): :type num: int :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPerfectSquare(self, num): :type num: int :rtype: bool
- def isPerfectSquare2(self, num): :type num: int :rtype: bool
<|skeleton|>
class Solution:
def isPerfectSquare(... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
<|body_0|>
def isPerfectSquare2(self, num):
""":type num: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPerfectSquare(self, num):
""":type num: int :rtype: bool"""
i, j = (0, num)
while i <= j:
mid = (i + j) // 2
s = mid ** 2
if s == num:
return True
elif s < num:
i = mid + 1
else:... | the_stack_v2_python_sparse | code367ValidPerfectSquare.py | cybelewang/leetcode-python | train | 0 | |
85e7427e530ede4a43da2a2ee54dd9a962d3faef | [
"if await self.check_user_guild(guild_id, user.id):\n return\nasync with aiosqlite.connect(self.resolved_db_path) as db:\n if not await self.check_global_user(user.id):\n await db.execute('INSERT INTO Users (id, name) VALUES (?, ?)', (user.id, user.name))\n await db.execute('INSERT INTO Users_Guilds... | <|body_start_0|>
if await self.check_user_guild(guild_id, user.id):
return
async with aiosqlite.connect(self.resolved_db_path) as db:
if not await self.check_global_user(user.id):
await db.execute('INSERT INTO Users (id, name) VALUES (?, ?)', (user.id, user.name))... | UserRepository | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
<|body_0|>
async def check_global_user(self, user_id: int) -... | stack_v2_sparse_classes_36k_train_004352 | 1,912 | permissive | [
{
"docstring": "Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)",
"name": "add_user",
"signature": "async def add_user(self, user: discord.Member, guild_id: int) -> None"
},
{
"docstring": "Checks if the user is in the glo... | 3 | stack_v2_sparse_classes_30k_val_000045 | Implement the Python class `UserRepository` described below.
Class description:
Implement the UserRepository class.
Method signatures and docstrings:
- async def add_user(self, user: discord.Member, guild_id: int) -> None: Adds a User to the global users table and/or to the guild specific user tables Args: user (disc... | Implement the Python class `UserRepository` described below.
Class description:
Implement the UserRepository class.
Method signatures and docstrings:
- async def add_user(self, user: discord.Member, guild_id: int) -> None: Adds a User to the global users table and/or to the guild specific user tables Args: user (disc... | 2f8b45f06abb510029f3461ab5e39535a5eb3385 | <|skeleton|>
class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
<|body_0|>
async def check_global_user(self, user_id: int) -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRepository:
async def add_user(self, user: discord.Member, guild_id: int) -> None:
"""Adds a User to the global users table and/or to the guild specific user tables Args: user (discord.Member) guild_id (int)"""
if await self.check_user_guild(guild_id, user.id):
return
a... | the_stack_v2_python_sparse | bot/data/user_repository.py | new-zelind/ClemBot | train | 1 | |
a0b85a31c6090a584bf576bf678c06cd442c297c | [
"self.screen_width = 1200\nself.screen_height = 600\nself.bg_color = (230, 230, 230)\nself.ship_limit = 3\nself.bullet_width = 3\nself.bullet_height = 15\nself.bullet_color = (60, 60, 60)\nself.bullets_allowed = 3\nself.fleet_drop_speed = 10\nself.speedup_scale = 1.1\nself.score_scale = 1.5\nself.initialize_dynamic... | <|body_start_0|>
self.screen_width = 1200
self.screen_height = 600
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 3
self.bullet_height = 15
self.bullet_color = (60, 60, 60)
self.bullets_allowed = 3
self.fleet_drop_speed = 1... | 存储《外星人入侵》的所有设置的类 | Settings | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置和外星人点数"""
<|body_2|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_004353 | 1,940 | no_license | [
{
"docstring": "初始化游戏的设置",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "初始化随游戏进行而变化的设置",
"name": "initialize_dynamic_settings",
"signature": "def initialize_dynamic_settings(self)"
},
{
"docstring": "提高速度设置和外星人点数",
"name": "increase_speed",
"si... | 3 | stack_v2_sparse_classes_30k_train_006134 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置和外星人点数 | Implement the Python class `Settings` described below.
Class description:
存储《外星人入侵》的所有设置的类
Method signatures and docstrings:
- def __init__(self): 初始化游戏的设置
- def initialize_dynamic_settings(self): 初始化随游戏进行而变化的设置
- def increase_speed(self): 提高速度设置和外星人点数
<|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def... | 0971e5f21a3d3ae9c2e22c87cf1f654be779abef | <|skeleton|>
class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
<|body_0|>
def initialize_dynamic_settings(self):
"""初始化随游戏进行而变化的设置"""
<|body_1|>
def increase_speed(self):
"""提高速度设置和外星人点数"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Settings:
"""存储《外星人入侵》的所有设置的类"""
def __init__(self):
"""初始化游戏的设置"""
self.screen_width = 1200
self.screen_height = 600
self.bg_color = (230, 230, 230)
self.ship_limit = 3
self.bullet_width = 3
self.bullet_height = 15
self.bullet_color = (60, ... | the_stack_v2_python_sparse | chapter_12-14_项目_外星人入侵/chapter_14_记分/settings.py | wenyoufu/Python-Programming | train | 0 |
42a06c332639e08a0dc6af1f9dfa9fb90babbd21 | [
"form_classes = self.get_form_classes()\nforms = self.get_forms(form_classes)\nkwargs = forms\nkwargs['forms'] = [form_class for form_class in forms.itervalues() if isinstance(form_class, BaseForm)]\nreturn self.render_to_response(self.get_context_data(**kwargs))",
"kwargs = forms\nkwargs['forms'] = [form_class f... | <|body_start_0|>
form_classes = self.get_form_classes()
forms = self.get_forms(form_classes)
kwargs = forms
kwargs['forms'] = [form_class for form_class in forms.itervalues() if isinstance(form_class, BaseForm)]
return self.render_to_response(self.get_context_data(**kwargs))
<|en... | A mixin that processes forms on POST. | ProcessMultipleFormsView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessMultipleFormsView:
"""A mixin that processes forms on POST."""
def get(self, request, *args, **kwargs):
"""Process a get request."""
<|body_0|>
def render_invalid_response(self, forms):
"""Renders a response if forms don't validate."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_004354 | 6,333 | permissive | [
{
"docstring": "Process a get request.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "Renders a response if forms don't validate.",
"name": "render_invalid_response",
"signature": "def render_invalid_response(self, forms)"
},
{
"docstri... | 3 | null | Implement the Python class `ProcessMultipleFormsView` described below.
Class description:
A mixin that processes forms on POST.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Process a get request.
- def render_invalid_response(self, forms): Renders a response if forms don't validate.
- ... | Implement the Python class `ProcessMultipleFormsView` described below.
Class description:
A mixin that processes forms on POST.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): Process a get request.
- def render_invalid_response(self, forms): Renders a response if forms don't validate.
- ... | a56c0f89df82694bf5db32a04d8b092974791972 | <|skeleton|>
class ProcessMultipleFormsView:
"""A mixin that processes forms on POST."""
def get(self, request, *args, **kwargs):
"""Process a get request."""
<|body_0|>
def render_invalid_response(self, forms):
"""Renders a response if forms don't validate."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessMultipleFormsView:
"""A mixin that processes forms on POST."""
def get(self, request, *args, **kwargs):
"""Process a get request."""
form_classes = self.get_form_classes()
forms = self.get_forms(form_classes)
kwargs = forms
kwargs['forms'] = [form_class for ... | the_stack_v2_python_sparse | open_connect/connect_core/utils/views.py | ofa/connect | train | 66 |
1d71985dc140a6123aeba97fdd3fd395b24fd851 | [
"dummy = ListNode(-1)\nl3 = dummy\nwhile l1 and l2:\n if l1.val <= l2.val:\n l3.next = ListNode(l1.val)\n l1 = l1.next\n else:\n l3.next = ListNode(l2.val)\n l2 = l2.next\n l3 = l3.next\nif l1:\n l3.next = l1\nelif l2:\n l3.next = l2\nreturn dummy.next",
"if not l1:\n ... | <|body_start_0|>
dummy = ListNode(-1)
l3 = dummy
while l1 and l2:
if l1.val <= l2.val:
l3.next = ListNode(l1.val)
l1 = l1.next
else:
l3.next = ListNode(l2.val)
l2 = l2.next
l3 = l3.next
if... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""迭代遍历"""
<|body_0|>
def mergeTwoLists_v2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""递归"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dummy = ListNode(-1)
... | stack_v2_sparse_classes_36k_train_004355 | 2,584 | no_license | [
{
"docstring": "迭代遍历",
"name": "mergeTwoLists_v1",
"signature": "def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode"
},
{
"docstring": "递归",
"name": "mergeTwoLists_v2",
"signature": "def mergeTwoLists_v2(self, l1: ListNode, l2: ListNode) -> ListNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_011170 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode: 迭代遍历
- def mergeTwoLists_v2(self, l1: ListNode, l2: ListNode) -> ListNode: 递归 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode: 迭代遍历
- def mergeTwoLists_v2(self, l1: ListNode, l2: ListNode) -> ListNode: 递归
<|skeleton|>
class Solution:
... | 7bf9b992acb5c3db22b52f1ee70816296a41af9d | <|skeleton|>
class Solution:
def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""迭代遍历"""
<|body_0|>
def mergeTwoLists_v2(self, l1: ListNode, l2: ListNode) -> ListNode:
"""递归"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists_v1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""迭代遍历"""
dummy = ListNode(-1)
l3 = dummy
while l1 and l2:
if l1.val <= l2.val:
l3.next = ListNode(l1.val)
l1 = l1.next
else:
l... | the_stack_v2_python_sparse | 021mergeTwoSortedLists.py | slsefe/leetcode | train | 0 | |
3077088e5e3a6ce5ab65a0e1aaa97dc97975f27a | [
"super(DynamicNet, self).__init__()\nself.input_linear = torch.nn.Linear(D_in, H)\nself.middle_linear = torch.nn.Linear(H, H)\nself.output_linear = torch.nn.Linear(H, D_out)",
"h_relu = self.input_linear(x).clamp(min=0)\nfor _ in range(random.randint(0, 3)):\n h_relu = self.middle_linear(h_relu).clamp(min=0)\n... | <|body_start_0|>
super(DynamicNet, self).__init__()
self.input_linear = torch.nn.Linear(D_in, H)
self.middle_linear = torch.nn.Linear(H, H)
self.output_linear = torch.nn.Linear(H, D_out)
<|end_body_0|>
<|body_start_1|>
h_relu = self.input_linear(x).clamp(min=0)
for _ in ... | DynamicNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamicNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。"""
<|body_0|>
def forward(self, x):
"""对于模型的前向传播，我们随机选择0、1、2、3， 并重用了多次计算隐藏层的middle_linear模块。 由于每个前向传播构建一个动态计算图， 我们可以在定义模型的前向传播时使用常规Python控制流运算符，如循环或条件语句。 在这里，我们还看到，在定义计算图形时多次重用... | stack_v2_sparse_classes_36k_train_004356 | 16,194 | no_license | [
{
"docstring": "在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。",
"name": "__init__",
"signature": "def __init__(self, D_in, H, D_out)"
},
{
"docstring": "对于模型的前向传播，我们随机选择0、1、2、3， 并重用了多次计算隐藏层的middle_linear模块。 由于每个前向传播构建一个动态计算图， 我们可以在定义模型的前向传播时使用常规Python控制流运算符，如循环或条件语句。 在这里，我们还看到，在定义计算图形时多次重用同一个模块是完全安全的。... | 2 | stack_v2_sparse_classes_30k_train_003119 | Implement the Python class `DynamicNet` described below.
Class description:
Implement the DynamicNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。
- def forward(self, x): 对于模型的前向传播，我们随机选择0、1、2、3， 并重用了多次计算隐藏层的middle_linear模块。 由于每个前向传播构建一个动态计算图， 我... | Implement the Python class `DynamicNet` described below.
Class description:
Implement the DynamicNet class.
Method signatures and docstrings:
- def __init__(self, D_in, H, D_out): 在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。
- def forward(self, x): 对于模型的前向传播，我们随机选择0、1、2、3， 并重用了多次计算隐藏层的middle_linear模块。 由于每个前向传播构建一个动态计算图， 我... | 272e0b674f2d8ebdca9eea0a35909d2c420212ae | <|skeleton|>
class DynamicNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。"""
<|body_0|>
def forward(self, x):
"""对于模型的前向传播，我们随机选择0、1、2、3， 并重用了多次计算隐藏层的middle_linear模块。 由于每个前向传播构建一个动态计算图， 我们可以在定义模型的前向传播时使用常规Python控制流运算符，如循环或条件语句。 在这里，我们还看到，在定义计算图形时多次重用... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynamicNet:
def __init__(self, D_in, H, D_out):
"""在构造函数中，我们构造了三个nn.Linear实例，它们将在前向传播时被使用。"""
super(DynamicNet, self).__init__()
self.input_linear = torch.nn.Linear(D_in, H)
self.middle_linear = torch.nn.Linear(H, H)
self.output_linear = torch.nn.Linear(H, D_out)
d... | the_stack_v2_python_sparse | PyTorch/quick_start_2/function_try.py | StarkTan/Python | train | 0 | |
fc6bd61e293ec0c389a6b1539fe2afc611cf4f9f | [
"super(ExternalMadSpin, self).__init__('MadSpin', os.environ['MADPATH'], 'MadSpin', 'madspin')\nself.add_keyword('alphaem_inv')\nself.add_keyword('alphaqcd')\nself.add_keyword('BR_t_to_Wb')\nself.add_keyword('BR_t_to_Wd')\nself.add_keyword('BR_t_to_Ws')\nself.add_keyword('BR_W_to_hadrons')\nself.add_keyword('BR_W_t... | <|body_start_0|>
super(ExternalMadSpin, self).__init__('MadSpin', os.environ['MADPATH'], 'MadSpin', 'madspin')
self.add_keyword('alphaem_inv')
self.add_keyword('alphaqcd')
self.add_keyword('BR_t_to_Wb')
self.add_keyword('BR_t_to_Wd')
self.add_keyword('BR_t_to_Ws')
... | ! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch> | ExternalMadSpin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExternalMadSpin:
"""! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch>"""
def __init__(self, process):
"""! Constructor. @param process MadSpin process description string."""
<|body_0|>
def needs_scheduling(self, process):
... | stack_v2_sparse_classes_36k_train_004357 | 3,129 | no_license | [
{
"docstring": "! Constructor. @param process MadSpin process description string.",
"name": "__init__",
"signature": "def __init__(self, process)"
},
{
"docstring": "! Report whether the MadSpin process should be scheduled. @param process PowhegBox process.",
"name": "needs_scheduling",
... | 2 | stack_v2_sparse_classes_30k_train_002299 | Implement the Python class `ExternalMadSpin` described below.
Class description:
! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch>
Method signatures and docstrings:
- def __init__(self, process): ! Constructor. @param process MadSpin process description string.
- def needs_... | Implement the Python class `ExternalMadSpin` described below.
Class description:
! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch>
Method signatures and docstrings:
- def __init__(self, process): ! Constructor. @param process MadSpin process description string.
- def needs_... | 22df23187ef85e9c3120122c8375ea0e7d8ea440 | <|skeleton|>
class ExternalMadSpin:
"""! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch>"""
def __init__(self, process):
"""! Constructor. @param process MadSpin process description string."""
<|body_0|>
def needs_scheduling(self, process):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExternalMadSpin:
"""! Class for running external MadSpin process. @author James Robinson <james.robinson@cern.ch>"""
def __init__(self, process):
"""! Constructor. @param process MadSpin process description string."""
super(ExternalMadSpin, self).__init__('MadSpin', os.environ['MADPATH'],... | the_stack_v2_python_sparse | athena/Generators/PowhegControl/python/processes/external/external_madspin.py | rushioda/PIXELVALID_athena | train | 1 |
eae3d8e1993c82cc8cf603ccbc3134aadaafc779 | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn OAuth2PermissionGrant()",
"from .entity import Entity\nfrom .entity import Entity\nfields: Dict[str, Callable[[Any], None]] = {'clientId': lambda n: setattr(self, 'client_id', n.get_str_value()), 'consentType': lambda n: setattr(self, ... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return OAuth2PermissionGrant()
<|end_body_0|>
<|body_start_1|>
from .entity import Entity
from .entity import Entity
fields: Dict[str, Callable[[Any], None]] = {'clientId': lambda n: se... | OAuth2PermissionGrant | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OAuth2PermissionGrant:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OAuth2PermissionGrant:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create th... | stack_v2_sparse_classes_36k_train_004358 | 4,239 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: OAuth2PermissionGrant",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminat... | 3 | null | Implement the Python class `OAuth2PermissionGrant` described below.
Class description:
Implement the OAuth2PermissionGrant class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OAuth2PermissionGrant: Creates a new instance of the appropriate class base... | Implement the Python class `OAuth2PermissionGrant` described below.
Class description:
Implement the OAuth2PermissionGrant class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OAuth2PermissionGrant: Creates a new instance of the appropriate class base... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class OAuth2PermissionGrant:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OAuth2PermissionGrant:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OAuth2PermissionGrant:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> OAuth2PermissionGrant:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Retur... | the_stack_v2_python_sparse | msgraph/generated/models/o_auth2_permission_grant.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
75df55ae946f3f3a6382acb0eac52c4e99b17abe | [
"inputs = tf.keras.Input(shape=(128,) * rank + (32,), batch_size=1)\nblock = conv_blocks.ConvBlock(filters=filters, kernel_size=kernel_size)\nfeatures = block(inputs)\nself.assertAllEqual(features.shape, [1] + [128] * rank + [filters])",
"config = dict(filters=[32], kernel_size=3, strides=1, rank=2, activation='t... | <|body_start_0|>
inputs = tf.keras.Input(shape=(128,) * rank + (32,), batch_size=1)
block = conv_blocks.ConvBlock(filters=filters, kernel_size=kernel_size)
features = block(inputs)
self.assertAllEqual(features.shape, [1] + [128] * rank + [filters])
<|end_body_0|>
<|body_start_1|>
... | Tests for `ConvBlock`. | ConvBlockTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvBlockTest:
"""Tests for `ConvBlock`."""
def test_conv_block_creation(self, filters, kernel_size, rank):
"""Test object creation."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_004359 | 2,425 | permissive | [
{
"docstring": "Test object creation.",
"name": "test_conv_block_creation",
"signature": "def test_conv_block_creation(self, filters, kernel_size, rank)"
},
{
"docstring": "Test de/serialization.",
"name": "test_serialize_deserialize",
"signature": "def test_serialize_deserialize(self)"
... | 2 | stack_v2_sparse_classes_30k_train_019442 | Implement the Python class `ConvBlockTest` described below.
Class description:
Tests for `ConvBlock`.
Method signatures and docstrings:
- def test_conv_block_creation(self, filters, kernel_size, rank): Test object creation.
- def test_serialize_deserialize(self): Test de/serialization. | Implement the Python class `ConvBlockTest` described below.
Class description:
Tests for `ConvBlock`.
Method signatures and docstrings:
- def test_conv_block_creation(self, filters, kernel_size, rank): Test object creation.
- def test_serialize_deserialize(self): Test de/serialization.
<|skeleton|>
class ConvBlockTe... | cfd8930ee5281e7f6dceb17c4a5acaf625fd3243 | <|skeleton|>
class ConvBlockTest:
"""Tests for `ConvBlock`."""
def test_conv_block_creation(self, filters, kernel_size, rank):
"""Test object creation."""
<|body_0|>
def test_serialize_deserialize(self):
"""Test de/serialization."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConvBlockTest:
"""Tests for `ConvBlock`."""
def test_conv_block_creation(self, filters, kernel_size, rank):
"""Test object creation."""
inputs = tf.keras.Input(shape=(128,) * rank + (32,), batch_size=1)
block = conv_blocks.ConvBlock(filters=filters, kernel_size=kernel_size)
... | the_stack_v2_python_sparse | tensorflow_mri/python/layers/conv_blocks_test.py | mrphys/tensorflow-mri | train | 29 |
199980693b32280f54661faa947f35ab5b3c02dd | [
"super().__init__()\nself.conv1 = torch.nn.Sequential(torch.nn.Conv2d(in_channels, 64, kernel_size=9, stride=1, padding=4), torch.nn.PReLU())\nres_blocks = []\nfor _ in range(n_residual_blocks):\n res_blocks.append(ResidualBlock(64))\nself.res_blocks = torch.nn.Sequential(*res_blocks)\nself.conv2 = torch.nn.Sequ... | <|body_start_0|>
super().__init__()
self.conv1 = torch.nn.Sequential(torch.nn.Conv2d(in_channels, 64, kernel_size=9, stride=1, padding=4), torch.nn.PReLU())
res_blocks = []
for _ in range(n_residual_blocks):
res_blocks.append(ResidualBlock(64))
self.res_blocks = torch... | Residual Generator Network | GeneratorResNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneratorResNet:
"""Residual Generator Network"""
def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16):
"""Parameters ---------- in_channels : int number of input channels out_channels : int number of output channels n_residual_blocks : int number of residual block... | stack_v2_sparse_classes_36k_train_004360 | 6,183 | permissive | [
{
"docstring": "Parameters ---------- in_channels : int number of input channels out_channels : int number of output channels n_residual_blocks : int number of residual blocks inside this generator",
"name": "__init__",
"signature": "def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16... | 2 | null | Implement the Python class `GeneratorResNet` described below.
Class description:
Residual Generator Network
Method signatures and docstrings:
- def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16): Parameters ---------- in_channels : int number of input channels out_channels : int number of output ... | Implement the Python class `GeneratorResNet` described below.
Class description:
Residual Generator Network
Method signatures and docstrings:
- def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16): Parameters ---------- in_channels : int number of input channels out_channels : int number of output ... | 1078f5030b8aac2bf022daf5fa14d66f74c3c893 | <|skeleton|>
class GeneratorResNet:
"""Residual Generator Network"""
def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16):
"""Parameters ---------- in_channels : int number of input channels out_channels : int number of output channels n_residual_blocks : int number of residual block... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeneratorResNet:
"""Residual Generator Network"""
def __init__(self, in_channels=3, out_channels=3, n_residual_blocks=16):
"""Parameters ---------- in_channels : int number of input channels out_channels : int number of output channels n_residual_blocks : int number of residual blocks inside this... | the_stack_v2_python_sparse | dlutils/models/gans/super_resolution/models.py | justusschock/dl-utils | train | 15 |
549db5b6fa5f9904e3e95f8d1199386e6f8a64ee | [
"self.__dict__['FILEORHASH'] = {'value': FILEORHASH, 'required': True, 'description': 'File to verify'}\nself.__dict__['APIKEY'] = {'value': APIKEY, 'required': True, 'description': 'VT API key'}\nself.__dict__['REPORT'] = {'value': REPORT, 'required': False, 'description': 'Return report for File or MD5'}\nself.__... | <|body_start_0|>
self.__dict__['FILEORHASH'] = {'value': FILEORHASH, 'required': True, 'description': 'File to verify'}
self.__dict__['APIKEY'] = {'value': APIKEY, 'required': True, 'description': 'VT API key'}
self.__dict__['REPORT'] = {'value': REPORT, 'required': False, 'description': 'Return... | Module Class | Module | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Module:
"""Module Class"""
def __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False, APIKEY=None):
"""__init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False,APIKEY=... | stack_v2_sparse_classes_36k_train_004361 | 7,816 | no_license | [
{
"docstring": "__init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False,APIKEY=None) :param FILEORHASH: :param REPORT: :param JSON: :param DOWNLOAD: :param PCAP: :param VERBOSE: :param RESCAN: :param APIKEY: Initialize the module with the module's desire... | 2 | stack_v2_sparse_classes_30k_train_013496 | Implement the Python class `Module` described below.
Class description:
Module Class
Method signatures and docstrings:
- def __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False, APIKEY=None): __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLO... | Implement the Python class `Module` described below.
Class description:
Module Class
Method signatures and docstrings:
- def __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False, APIKEY=None): __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLO... | 99e1d75b3d1af2e44740584be6c2ef1c1601c43c | <|skeleton|>
class Module:
"""Module Class"""
def __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False, APIKEY=None):
"""__init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False,APIKEY=... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Module:
"""Module Class"""
def __init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False, APIKEY=None):
"""__init__(self, FILEORHASH=None, REPORT=False, JSON=False, DOWNLOAD=False, PCAP=False, VERBOSE=False, RESCAN=False,APIKEY=None) :param ... | the_stack_v2_python_sparse | modules/intel/virus_total.py | h4cklife/intrukit | train | 3 |
2442b353ebb9395c5db7855d5cec451e8d0b957f | [
"total_len = len(nums1) + len(nums2)\nk = total_len // 2\nif total_len % 2 == 0:\n return (self.findKth(nums1, nums2, k) + self.findKth(nums1, nums2, k + 1)) / 2.0\nreturn self.findKth(nums1, nums2, k + 1) * 1.0",
"if kth > len(nums1) + len(nums2):\n raise ValueError('kth should be lower than the total leng... | <|body_start_0|>
total_len = len(nums1) + len(nums2)
k = total_len // 2
if total_len % 2 == 0:
return (self.findKth(nums1, nums2, k) + self.findKth(nums1, nums2, k + 1)) / 2.0
return self.findKth(nums1, nums2, k + 1) * 1.0
<|end_body_0|>
<|body_start_1|>
if kth > len... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def findKth(self, nums1, nums2, kth):
"""find kth element of two sorted list"""
<|body_1|>
<|end_skeleton|>
<|body_start_0... | stack_v2_sparse_classes_36k_train_004362 | 1,741 | no_license | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: float",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, nums1, nums2)"
},
{
"docstring": "find kth element of two sorted list",
"name": "findKth",
"signature": "def findKth(self, nums1,... | 2 | stack_v2_sparse_classes_30k_train_013224 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def findKth(self, nums1, nums2, kth): find kth element of two sorted... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def findKth(self, nums1, nums2, kth): find kth element of two sorted... | 7e3929a4b5bd0344f93373979c9d1acc4ae192a7 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def findKth(self, nums1, nums2, kth):
"""find kth element of two sorted list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
total_len = len(nums1) + len(nums2)
k = total_len // 2
if total_len % 2 == 0:
return (self.findKth(nums1, nums2, k) + self.findKth(nums1, nums... | the_stack_v2_python_sparse | median_of_two_sorted_arrays.py | xartisan/leetcode-solutions-in-python | train | 1 | |
92a023b85d6e7609e1d68e60476b0b0696823790 | [
"if 'price' in data and 'end_time' not in data:\n raise ValidationError('If the price is included, you must also include the end time.')\nelif 'price' not in data and 'end_time' in data:\n raise ValidationError('If the end time is included, you must also include the price.')\nif 'price' in data and 'estimated... | <|body_start_0|>
if 'price' in data and 'end_time' not in data:
raise ValidationError('If the price is included, you must also include the end time.')
elif 'price' not in data and 'end_time' in data:
raise ValidationError('If the end time is included, you must also include the pr... | RentalSchema | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RentalSchema:
def assert_end_time_with_price(self, data, **kwargs):
"""Asserts that when a rental is complete both the price and end time are included."""
<|body_0|>
def assert_url_included_with_foreign_key(self, data, **kwargs):
"""Asserts that when a user_id or bik... | stack_v2_sparse_classes_36k_train_004363 | 6,177 | permissive | [
{
"docstring": "Asserts that when a rental is complete both the price and end time are included.",
"name": "assert_end_time_with_price",
"signature": "def assert_end_time_with_price(self, data, **kwargs)"
},
{
"docstring": "Asserts that when a user_id or bike_id is sent that a user_url or bike_u... | 2 | stack_v2_sparse_classes_30k_train_012926 | Implement the Python class `RentalSchema` described below.
Class description:
Implement the RentalSchema class.
Method signatures and docstrings:
- def assert_end_time_with_price(self, data, **kwargs): Asserts that when a rental is complete both the price and end time are included.
- def assert_url_included_with_fore... | Implement the Python class `RentalSchema` described below.
Class description:
Implement the RentalSchema class.
Method signatures and docstrings:
- def assert_end_time_with_price(self, data, **kwargs): Asserts that when a rental is complete both the price and end time are included.
- def assert_url_included_with_fore... | fc6f9230e4701cbddcb16d7257fddb9ff08bddb9 | <|skeleton|>
class RentalSchema:
def assert_end_time_with_price(self, data, **kwargs):
"""Asserts that when a rental is complete both the price and end time are included."""
<|body_0|>
def assert_url_included_with_foreign_key(self, data, **kwargs):
"""Asserts that when a user_id or bik... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RentalSchema:
def assert_end_time_with_price(self, data, **kwargs):
"""Asserts that when a rental is complete both the price and end time are included."""
if 'price' in data and 'end_time' not in data:
raise ValidationError('If the price is included, you must also include the end t... | the_stack_v2_python_sparse | server/serializer/models.py | dragorhast/server | train | 6 | |
695cee99cf12c7c750bdd02cbb215e58afb2e2f2 | [
"super().__init__()\nout_channels = channels * self.expansion\nif cardinality == 1:\n rc = channels\nelse:\n width_ratio = channels * (width / self.start_filts)\n rc = cardinality * math.floor(width_ratio)\nself.conv_reduce = ConvNdTorch(n_dim, in_channels, rc, kernel_size=1, stride=1, padding=0, bias=Fals... | <|body_start_0|>
super().__init__()
out_channels = channels * self.expansion
if cardinality == 1:
rc = channels
else:
width_ratio = channels * (width / self.start_filts)
rc = cardinality * math.floor(width_ratio)
self.conv_reduce = ConvNdTorch(... | SEBottleneckXTorch | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SEBottleneckXTorch:
def __init__(self, in_channels, channels, stride, cardinality, width, n_dim, norm_layer, avg_down, reduction=16):
"""Squeeze and Excitation ResNeXt Block Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer card... | stack_v2_sparse_classes_36k_train_004364 | 8,979 | permissive | [
{
"docstring": "Squeeze and Excitation ResNeXt Block Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : int number of convolution groups width : int width of resnext block n_dim : int dimensionality of convolutions norm_layer : str type of... | 2 | stack_v2_sparse_classes_30k_train_002489 | Implement the Python class `SEBottleneckXTorch` described below.
Class description:
Implement the SEBottleneckXTorch class.
Method signatures and docstrings:
- def __init__(self, in_channels, channels, stride, cardinality, width, n_dim, norm_layer, avg_down, reduction=16): Squeeze and Excitation ResNeXt Block Paramet... | Implement the Python class `SEBottleneckXTorch` described below.
Class description:
Implement the SEBottleneckXTorch class.
Method signatures and docstrings:
- def __init__(self, in_channels, channels, stride, cardinality, width, n_dim, norm_layer, avg_down, reduction=16): Squeeze and Excitation ResNeXt Block Paramet... | d944aa67d319bd63a2add5cb89e8308413943de6 | <|skeleton|>
class SEBottleneckXTorch:
def __init__(self, in_channels, channels, stride, cardinality, width, n_dim, norm_layer, avg_down, reduction=16):
"""Squeeze and Excitation ResNeXt Block Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer card... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SEBottleneckXTorch:
def __init__(self, in_channels, channels, stride, cardinality, width, n_dim, norm_layer, avg_down, reduction=16):
"""Squeeze and Excitation ResNeXt Block Parameters ---------- in_channels : int number of input channels stride : int stride of 3x3 convolution layer cardinality : int ... | the_stack_v2_python_sparse | deliravision/torch/models/backbones/seblocks.py | delira-dev/vision_torch | train | 5 | |
fe04e5a34d94e13c95efc112b9006f018639fa9c | [
"tmp = head\nwhile head:\n if head.next:\n if head.val == head.next.val:\n head.next = head.next.next\n continue\n head = head.next\nreturn tmp",
"ohead = head\nwhile head:\n if head.next and head.val == head.next.val:\n head.next = head.next.next\n else:\n h... | <|body_start_0|>
tmp = head
while head:
if head.next:
if head.val == head.next.val:
head.next = head.next.next
continue
head = head.next
return tmp
<|end_body_0|>
<|body_start_1|>
ohead = head
while ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def rewrite(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
tmp = head
while head:
... | stack_v2_sparse_classes_36k_train_004365 | 1,698 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "deleteDuplicates",
"signature": "def deleteDuplicates(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "rewrite",
"signature": "def rewrite(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head): :type head: ListNode :rtype: ListNode
- def rewrite(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head): :type head: ListNode :rtype: ListNode
- def rewrite(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def de... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def rewrite(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteDuplicates(self, head):
""":type head: ListNode :rtype: ListNode"""
tmp = head
while head:
if head.next:
if head.val == head.next.val:
head.next = head.next.next
continue
head = head.nex... | the_stack_v2_python_sparse | linked/83_Remove_Duplicates_from_Sorted_List.py | vsdrun/lc_public | train | 6 | |
b24c2b30e3327ab3831f87abf15dd7b691b3a8b3 | [
"APIAdminCommon.verifySecurityOfAdminAPICall(appObj, request, tenant)\n\ndef dbfn(storeConnection):\n ticketTypeObj = appObj.TicketManager.getTicketType(tenantName=tenantName, tickettypeID=tickettypeID, storeConnection=storeConnection)\n if ticketTypeObj is None:\n return (NotFound, 404)\n return (t... | <|body_start_0|>
APIAdminCommon.verifySecurityOfAdminAPICall(appObj, request, tenant)
def dbfn(storeConnection):
ticketTypeObj = appObj.TicketManager.getTicketType(tenantName=tenantName, tickettypeID=tickettypeID, storeConnection=storeConnection)
if ticketTypeObj is None:
... | Ticket Type | tickettypeInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class tickettypeInfo:
"""Ticket Type"""
def get(self, tenant, tenantName, tickettypeID):
"""Get Ticket Type"""
<|body_0|>
def post(self, tenant, tenantName, tickettypeID):
"""Update Ticket Type"""
<|body_1|>
def delete(self, tenant, tenantName, tickettypeI... | stack_v2_sparse_classes_36k_train_004366 | 12,942 | permissive | [
{
"docstring": "Get Ticket Type",
"name": "get",
"signature": "def get(self, tenant, tenantName, tickettypeID)"
},
{
"docstring": "Update Ticket Type",
"name": "post",
"signature": "def post(self, tenant, tenantName, tickettypeID)"
},
{
"docstring": "Delete Ticket Type",
"nam... | 3 | null | Implement the Python class `tickettypeInfo` described below.
Class description:
Ticket Type
Method signatures and docstrings:
- def get(self, tenant, tenantName, tickettypeID): Get Ticket Type
- def post(self, tenant, tenantName, tickettypeID): Update Ticket Type
- def delete(self, tenant, tenantName, tickettypeID): ... | Implement the Python class `tickettypeInfo` described below.
Class description:
Ticket Type
Method signatures and docstrings:
- def get(self, tenant, tenantName, tickettypeID): Get Ticket Type
- def post(self, tenant, tenantName, tickettypeID): Update Ticket Type
- def delete(self, tenant, tenantName, tickettypeID): ... | d3908c46614fb1b638553282cd72ba3634277495 | <|skeleton|>
class tickettypeInfo:
"""Ticket Type"""
def get(self, tenant, tenantName, tickettypeID):
"""Get Ticket Type"""
<|body_0|>
def post(self, tenant, tenantName, tickettypeID):
"""Update Ticket Type"""
<|body_1|>
def delete(self, tenant, tenantName, tickettypeI... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class tickettypeInfo:
"""Ticket Type"""
def get(self, tenant, tenantName, tickettypeID):
"""Get Ticket Type"""
APIAdminCommon.verifySecurityOfAdminAPICall(appObj, request, tenant)
def dbfn(storeConnection):
ticketTypeObj = appObj.TicketManager.getTicketType(tenantName=tenan... | the_stack_v2_python_sparse | services/src/APIadmin_Tickets.py | rmetcalf9/saas_user_management_system | train | 1 |
5235f84ded4237e6116e78dbea05af5a5e122150 | [
"self.open(base_url)\nself.login_test_user()\nself.open(base_url + '/logout')\nassert self.get_current_url() == base_url + '/login'\nmessage = self.driver.find_element_by_id('login_message')\nassert 'Please Login' in message.text",
"self.login_test_user()\nself.open(base_url + '/logout')\nassert self.get_current_... | <|body_start_0|>
self.open(base_url)
self.login_test_user()
self.open(base_url + '/logout')
assert self.get_current_url() == base_url + '/login'
message = self.driver.find_element_by_id('login_message')
assert 'Please Login' in message.text
<|end_body_0|>
<|body_start_1|... | Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values | R7Test | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class R7Test:
"""Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values"""
def test_logout_redirect(self, *_):
"""see r7.1"""
<|body_0|>
def test_logout_restricted(self, *_):
"""see r7.2"""
<|body_1|>... | stack_v2_sparse_classes_36k_train_004367 | 1,272 | permissive | [
{
"docstring": "see r7.1",
"name": "test_logout_redirect",
"signature": "def test_logout_redirect(self, *_)"
},
{
"docstring": "see r7.2",
"name": "test_logout_restricted",
"signature": "def test_logout_restricted(self, *_)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000484 | Implement the Python class `R7Test` described below.
Class description:
Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values
Method signatures and docstrings:
- def test_logout_redirect(self, *_): see r7.1
- def test_logout_restricted(self, *_): see r7.2 | Implement the Python class `R7Test` described below.
Class description:
Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values
Method signatures and docstrings:
- def test_logout_redirect(self, *_): see r7.1
- def test_logout_restricted(self, *_): see r7.2
... | 73f6bdcbd2f382a54dfec3e0e79120bd60c9513f | <|skeleton|>
class R7Test:
"""Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values"""
def test_logout_redirect(self, *_):
"""see r7.1"""
<|body_0|>
def test_logout_restricted(self, *_):
"""see r7.2"""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class R7Test:
"""Contains test cases specific to R7. Test only test the frontend portion, and will patch the backend specific values"""
def test_logout_redirect(self, *_):
"""see r7.1"""
self.open(base_url)
self.login_test_user()
self.open(base_url + '/logout')
assert se... | the_stack_v2_python_sparse | qa327_test/frontend/test_r7.py | nicoleooi/cmpe327 | train | 0 |
02e02be3dfcd20175687236b47ceb2865eca6f2f | [
"x_data, y_data, vectorizer, clf = load_all(model, language=language, preprocessing=preprocessing, categories=categories, encoding=encoding, vectorizer=vectorizer, vectorizer_method=vectorizer_method, clf=clf, clf_method=clf_method, x_data=x_data, y_data=y_data)\nTrainer._train(vectorizer, clf, x_data, y_data)\nwri... | <|body_start_0|>
x_data, y_data, vectorizer, clf = load_all(model, language=language, preprocessing=preprocessing, categories=categories, encoding=encoding, vectorizer=vectorizer, vectorizer_method=vectorizer_method, clf=clf, clf_method=clf_method, x_data=x_data, y_data=y_data)
Trainer._train(vectorizer... | Trainer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trainer:
def __init__(self, model, language=None, preprocessing=None, categories=None, encoding=None, vectorizer=None, vectorizer_method=None, clf=None, clf_method=None, x_data=None, y_data=None):
"""Data should be stored in a two levels folder structure like this: datasets/ model_name/ ... | stack_v2_sparse_classes_36k_train_004368 | 1,972 | permissive | [
{
"docstring": "Data should be stored in a two levels folder structure like this: datasets/ model_name/ category1/ file_1.txt file_2.txt file_42.txt category2/ file_43.txt file_44.txt",
"name": "__init__",
"signature": "def __init__(self, model, language=None, preprocessing=None, categories=None, encodi... | 2 | stack_v2_sparse_classes_30k_test_001050 | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, model, language=None, preprocessing=None, categories=None, encoding=None, vectorizer=None, vectorizer_method=None, clf=None, clf_method=None, x_data=None, y_data... | Implement the Python class `Trainer` described below.
Class description:
Implement the Trainer class.
Method signatures and docstrings:
- def __init__(self, model, language=None, preprocessing=None, categories=None, encoding=None, vectorizer=None, vectorizer_method=None, clf=None, clf_method=None, x_data=None, y_data... | 8246824e7b50b84be6697bb4cc2a6381ddcd0ca9 | <|skeleton|>
class Trainer:
def __init__(self, model, language=None, preprocessing=None, categories=None, encoding=None, vectorizer=None, vectorizer_method=None, clf=None, clf_method=None, x_data=None, y_data=None):
"""Data should be stored in a two levels folder structure like this: datasets/ model_name/ ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trainer:
def __init__(self, model, language=None, preprocessing=None, categories=None, encoding=None, vectorizer=None, vectorizer_method=None, clf=None, clf_method=None, x_data=None, y_data=None):
"""Data should be stored in a two levels folder structure like this: datasets/ model_name/ category1/ fil... | the_stack_v2_python_sparse | cherry/trainer.py | Windsooon/cherry | train | 444 | |
2524af858811a275b69a2020ec697402f7ef06bc | [
"super(Cycle, self).__init__(name=name, **kwargs)\nself.add_module('f', f)\nself.add_module('g', g)",
"y = self.f(x, s)\nx_inv = self.g(y if not detach else y.detach(), s)\nreturn (y, x_inv)"
] | <|body_start_0|>
super(Cycle, self).__init__(name=name, **kwargs)
self.add_module('f', f)
self.add_module('g', g)
<|end_body_0|>
<|body_start_1|>
y = self.f(x, s)
x_inv = self.g(y if not detach else y.detach(), s)
return (y, x_inv)
<|end_body_1|>
| A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.Module the inverse decoder architecture Methods ------- forward(x, s) ret... | Cycle | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cycle:
"""A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.Module the inverse decoder architecture ... | stack_v2_sparse_classes_36k_train_004369 | 1,885 | permissive | [
{
"docstring": "Parameters ---------- f : torch.nn.Module the decoder architecture g : torch.nn.Module the inverse decoder architecture name : str (optional) the name of the model",
"name": "__init__",
"signature": "def __init__(self, f, g, name='Cycle', **kwargs)"
},
{
"docstring": "Returns the... | 2 | null | Implement the Python class `Cycle` described below.
Class description:
A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.M... | Implement the Python class `Cycle` described below.
Class description:
A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.M... | 2615b66dd4addfd5c03d9d91a24c7da414294308 | <|skeleton|>
class Cycle:
"""A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.Module the inverse decoder architecture ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cycle:
"""A class representing the cycle model from: "Preventing self-intersection with cycle regularization in neural networks for mesh reconstruction from a single RGB image" Attributes ---------- f : torch.nn.Module the decoder architecture g : torch.nn.Module the inverse decoder architecture Methods -----... | the_stack_v2_python_sparse | ACME/model/cycle.py | mauriziokovacic/ACME | train | 3 |
26160abe03ea6b85ae3fd7a74cd3f013f77ea640 | [
"dataDtypes = dataForPreprocess.dtypes.reset_index(level=0)\ndataDtypes.rename(columns={'index': '变量名称', 0: '数据类型'}, inplace=True)\ndata_describe = dataForPreprocess.describe().T.reset_index(level=0)\ndata_describe.rename(columns={'index': '变量名称'}, inplace=True)\ndataTypes = pd.merge(dataDtypes, data_describe, on='... | <|body_start_0|>
dataDtypes = dataForPreprocess.dtypes.reset_index(level=0)
dataDtypes.rename(columns={'index': '变量名称', 0: '数据类型'}, inplace=True)
data_describe = dataForPreprocess.describe().T.reset_index(level=0)
data_describe.rename(columns={'index': '变量名称'}, inplace=True)
data... | 功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1. edited by 王文丹 2021/07/02 | TransformValueClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransformValueClass:
"""功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1. edited by 王文丹 2021/07/02"""
def ... | stack_v2_sparse_classes_36k_train_004370 | 4,082 | no_license | [
{
"docstring": "功能描述：主要功能识别字符型变量",
"name": "output_var_type",
"signature": "def output_var_type(self, dataForPreprocess)"
},
{
"docstring": "功能描述：主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 输入： dataForPreprocess：预处理前的数据集 DataFrame listNeedTransform: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： dict... | 3 | stack_v2_sparse_classes_30k_train_019451 | Implement the Python class `TransformValueClass` described below.
Class description:
功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1... | Implement the Python class `TransformValueClass` described below.
Class description:
功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1... | e1f7d1229ee82fb5cf7e5f969f24f8c61568c2c9 | <|skeleton|>
class TransformValueClass:
"""功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1. edited by 王文丹 2021/07/02"""
def ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TransformValueClass:
"""功能描述：字符型变量向数值型变量转换 输入： dataForPreprocess：预处理前的数据集 DataFrame listObject: 需要数据类型转换的字符型变量 list ylabel: 坏样本率对应的特征名称 （如：'y') 输出： 函数transform_object_dict: 主要用于字符型变量转换为数值型变量，依照坏样本率排序，形成映射字典 函数transform_object_type：将数据集众的字符型变量转换为数值型变量 管理记录： 1. edited by 王文丹 2021/07/02"""
def output_var_ty... | the_stack_v2_python_sparse | C_PreprocessData/TransformValueModule/TransformValueHandle.py | wenhui0331/Basic_Model_V1 | train | 0 |
493261cde245759e7df2fbb5f272975759c5b730 | [
"self.name = 'static'\nself.options = {'hue': 'hue', 'brightness': 'brightness', 'saturation': 'saturation', 'start': 'start', 'end': 'start', 'blend': 'blend'}\nself.start = kwargs.get('start', 0)\nself.end = kwargs.get('end', -1)\nself.hue = kwargs.get('hue', True)\nself.saturation = kwargs.get('saturation', None... | <|body_start_0|>
self.name = 'static'
self.options = {'hue': 'hue', 'brightness': 'brightness', 'saturation': 'saturation', 'start': 'start', 'end': 'start', 'blend': 'blend'}
self.start = kwargs.get('start', 0)
self.end = kwargs.get('end', -1)
self.hue = kwargs.get('hue', True)
... | DocString | StaticEffect | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StaticEffect:
"""DocString"""
def __init__(self, **kwargs):
"""DocString"""
<|body_0|>
def iterate(self):
"""DocString"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.name = 'static'
self.options = {'hue': 'hue', 'brightness': 'brig... | stack_v2_sparse_classes_36k_train_004371 | 1,154 | permissive | [
{
"docstring": "DocString",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "DocString",
"name": "iterate",
"signature": "def iterate(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021416 | Implement the Python class `StaticEffect` described below.
Class description:
DocString
Method signatures and docstrings:
- def __init__(self, **kwargs): DocString
- def iterate(self): DocString | Implement the Python class `StaticEffect` described below.
Class description:
DocString
Method signatures and docstrings:
- def __init__(self, **kwargs): DocString
- def iterate(self): DocString
<|skeleton|>
class StaticEffect:
"""DocString"""
def __init__(self, **kwargs):
"""DocString"""
<|... | b5cc2fb036d283b4ebd975ed6ba0df98bb6b5169 | <|skeleton|>
class StaticEffect:
"""DocString"""
def __init__(self, **kwargs):
"""DocString"""
<|body_0|>
def iterate(self):
"""DocString"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StaticEffect:
"""DocString"""
def __init__(self, **kwargs):
"""DocString"""
self.name = 'static'
self.options = {'hue': 'hue', 'brightness': 'brightness', 'saturation': 'saturation', 'start': 'start', 'end': 'start', 'blend': 'blend'}
self.start = kwargs.get('start', 0)
... | the_stack_v2_python_sparse | effects/static.py | fernandoeng/OmegaLed | train | 0 |
139f77e12fa08bf14b8abc77dfcd26eeb2e248cb | [
"dic = dict()\nfor num in nums:\n if num in dic:\n return [num, dic[num]]\n dic[target - num] = num\nreturn []",
"res, n = ([], len(nums))\nif n < 3:\n return res\nnums.sort()\nfor p1 in range(n):\n if p1 > 0 and nums[p1] == nums[p1 - 1]:\n continue\n p3 = n - 1\n t = target - nums... | <|body_start_0|>
dic = dict()
for num in nums:
if num in dic:
return [num, dic[num]]
dic[target - num] = num
return []
<|end_body_0|>
<|body_start_1|>
res, n = ([], len(nums))
if n < 3:
return res
nums.sort()
fo... | N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。 | NSum | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NSum:
"""N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。"""
def twoSum1(self, nums, target) -> List[int]:
"""无序的数组找一个直接用哈希表"""
<|body_0|>
def threeSum(self, nums: List[int], target: int) -> List[List[int]]:
"""三数之和，返回所有可能的不重复的结果"""
<|body_1|>
def fourSum(self, nums: ... | stack_v2_sparse_classes_36k_train_004372 | 4,219 | no_license | [
{
"docstring": "无序的数组找一个直接用哈希表",
"name": "twoSum1",
"signature": "def twoSum1(self, nums, target) -> List[int]"
},
{
"docstring": "三数之和，返回所有可能的不重复的结果",
"name": "threeSum",
"signature": "def threeSum(self, nums: List[int], target: int) -> List[List[int]]"
},
{
"docstring": "四数之和，返... | 3 | stack_v2_sparse_classes_30k_train_006817 | Implement the Python class `NSum` described below.
Class description:
N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。
Method signatures and docstrings:
- def twoSum1(self, nums, target) -> List[int]: 无序的数组找一个直接用哈希表
- def threeSum(self, nums: List[int], target: int) -> List[List[int]]: 三数之和，返回所有可能的不重复的结果
- def fourSum(self, nums: List... | Implement the Python class `NSum` described below.
Class description:
N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。
Method signatures and docstrings:
- def twoSum1(self, nums, target) -> List[int]: 无序的数组找一个直接用哈希表
- def threeSum(self, nums: List[int], target: int) -> List[List[int]]: 三数之和，返回所有可能的不重复的结果
- def fourSum(self, nums: List... | 330330ef6bc42eeb17f4dea53c30d230506b4e8f | <|skeleton|>
class NSum:
"""N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。"""
def twoSum1(self, nums, target) -> List[int]:
"""无序的数组找一个直接用哈希表"""
<|body_0|>
def threeSum(self, nums: List[int], target: int) -> List[List[int]]:
"""三数之和，返回所有可能的不重复的结果"""
<|body_1|>
def fourSum(self, nums: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NSum:
"""N-Sum问题系统来一遍 问题分类为找一个和找不重复的所有。"""
def twoSum1(self, nums, target) -> List[int]:
"""无序的数组找一个直接用哈希表"""
dic = dict()
for num in nums:
if num in dic:
return [num, dic[num]]
dic[target - num] = num
return []
def threeSum(sel... | the_stack_v2_python_sparse | Code/leetcode_everyday/0313.py | NiceToMeeetU/ToGetReady | train | 0 |
fa03eb978f72ad075abdc2637a5dca7e5bff5ef8 | [
"self.minheap = []\nself.maxheap = []\nself.len_min = self.len_max = 0",
"if self.len_max == 0:\n heapq.heappush(self.maxheap, num)\n self.len_max += 1\n return\nif self.len_max == self.len_min:\n if num >= self.maxheap[0]:\n heapq.heappush(self.maxheap, num)\n else:\n heapq.heappush(... | <|body_start_0|>
self.minheap = []
self.maxheap = []
self.len_min = self.len_max = 0
<|end_body_0|>
<|body_start_1|>
if self.len_max == 0:
heapq.heappush(self.maxheap, num)
self.len_max += 1
return
if self.len_max == self.len_min:
... | MedianFinder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_004373 | 1,807 | permissive | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: None",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | stack_v2_sparse_classes_30k_train_020712 | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: None
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | c5e7777e6a5b691bb410c25f29ae0f51a6598a12 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: None"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
self.minheap = []
self.maxheap = []
self.len_min = self.len_max = 0
def addNum(self, num):
""":type num: int :rtype: None"""
if self.len_max == 0:
heapq.heappush(self.m... | the_stack_v2_python_sparse | 剑指offer/41-Stream-Median.py | xizhang77/CodingInterview | train | 1 | |
1c4e2fd34033973c51d13e82d5ea3f5609ce3716 | [
"try:\n return AccountInformation.objects.get(pk=pk)\nexcept AccountInformation.DoesNotExist:\n raise Http404",
"account_info = self.get_object(pk)\nserializer = AccountInformationSerializer(account_info)\nreturn Response(serializer.data)",
"account_info = self.get_object(pk)\nserializer = AccountInformat... | <|body_start_0|>
try:
return AccountInformation.objects.get(pk=pk)
except AccountInformation.DoesNotExist:
raise Http404
<|end_body_0|>
<|body_start_1|>
account_info = self.get_object(pk)
serializer = AccountInformationSerializer(account_info)
return Resp... | Retrieve, update or delete a AccountInformation instance. | AccountInformationDetails | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountInformationDetails:
"""Retrieve, update or delete a AccountInformation instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
<|body_0|>
def get(self, request, pk, format=None):
"""We are going to add the account info content a... | stack_v2_sparse_classes_36k_train_004374 | 15,222 | permissive | [
{
"docstring": "Get the particular row from the table.",
"name": "get_object",
"signature": "def get_object(self, pk)"
},
{
"docstring": "We are going to add the account info content along with this pull request",
"name": "get",
"signature": "def get(self, request, pk, format=None)"
},... | 4 | stack_v2_sparse_classes_30k_train_012117 | Implement the Python class `AccountInformationDetails` described below.
Class description:
Retrieve, update or delete a AccountInformation instance.
Method signatures and docstrings:
- def get_object(self, pk): Get the particular row from the table.
- def get(self, request, pk, format=None): We are going to add the a... | Implement the Python class `AccountInformationDetails` described below.
Class description:
Retrieve, update or delete a AccountInformation instance.
Method signatures and docstrings:
- def get_object(self, pk): Get the particular row from the table.
- def get(self, request, pk, format=None): We are going to add the a... | b0635e72338e14dad24f1ee0329212cd60a3e83a | <|skeleton|>
class AccountInformationDetails:
"""Retrieve, update or delete a AccountInformation instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
<|body_0|>
def get(self, request, pk, format=None):
"""We are going to add the account info content a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountInformationDetails:
"""Retrieve, update or delete a AccountInformation instance."""
def get_object(self, pk):
"""Get the particular row from the table."""
try:
return AccountInformation.objects.get(pk=pk)
except AccountInformation.DoesNotExist:
raise... | the_stack_v2_python_sparse | environment/views.py | faisaltheparttimecoder/carelogBackend | train | 1 |
b70b7ca56edcd4b3307aafcf50c12b0e0c1de26d | [
"if entry['population'] and entry['population'] != 0:\n return 1000000.0 * entry['weekly_avg_cases'] / entry['population']\nreturn 0",
"if entry['population'] and entry['population'] != 0:\n return 1000000.0 * entry['summed_avg_cases'] / entry['population']\nreturn 0"
] | <|body_start_0|>
if entry['population'] and entry['population'] != 0:
return 1000000.0 * entry['weekly_avg_cases'] / entry['population']
return 0
<|end_body_0|>
<|body_start_1|>
if entry['population'] and entry['population'] != 0:
return 1000000.0 * entry['summed_avg_cas... | Serializer for counterfactual daily normalised cases | CasesCounterfactualDailyNormalisedSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CasesCounterfactualDailyNormalisedSerializer:
"""Serializer for counterfactual daily normalised cases"""
def get_weekly_avg_cases_per_million(self, entry):
"""Getter for weekly_avg_cases_per_million field"""
<|body_0|>
def get_summed_avg_cases_per_million(self, entry):
... | stack_v2_sparse_classes_36k_train_004375 | 2,322 | no_license | [
{
"docstring": "Getter for weekly_avg_cases_per_million field",
"name": "get_weekly_avg_cases_per_million",
"signature": "def get_weekly_avg_cases_per_million(self, entry)"
},
{
"docstring": "Getter for summed_avg_cases_per_million field",
"name": "get_summed_avg_cases_per_million",
"sig... | 2 | stack_v2_sparse_classes_30k_train_018081 | Implement the Python class `CasesCounterfactualDailyNormalisedSerializer` described below.
Class description:
Serializer for counterfactual daily normalised cases
Method signatures and docstrings:
- def get_weekly_avg_cases_per_million(self, entry): Getter for weekly_avg_cases_per_million field
- def get_summed_avg_c... | Implement the Python class `CasesCounterfactualDailyNormalisedSerializer` described below.
Class description:
Serializer for counterfactual daily normalised cases
Method signatures and docstrings:
- def get_weekly_avg_cases_per_million(self, entry): Getter for weekly_avg_cases_per_million field
- def get_summed_avg_c... | af8d6e351a1890403d8d41dca530ddb6ba601dc3 | <|skeleton|>
class CasesCounterfactualDailyNormalisedSerializer:
"""Serializer for counterfactual daily normalised cases"""
def get_weekly_avg_cases_per_million(self, entry):
"""Getter for weekly_avg_cases_per_million field"""
<|body_0|>
def get_summed_avg_cases_per_million(self, entry):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CasesCounterfactualDailyNormalisedSerializer:
"""Serializer for counterfactual daily normalised cases"""
def get_weekly_avg_cases_per_million(self, entry):
"""Getter for weekly_avg_cases_per_million field"""
if entry['population'] and entry['population'] != 0:
return 1000000.0... | the_stack_v2_python_sparse | backend/cases/serializers/ephemeral.py | alan-turing-institute/CounterfactualCovid19 | train | 3 |
c42e3c3ba0683603dd404141af21a351782a3690 | [
"ordered_uuids = [(k, v) for k, v in value.items()]\nordered_uuids.sort(key=lambda x: x[1]['order'])\nreturn '\\r\\n'.join([i[0] for i in ordered_uuids])",
"if not len(value) or not isinstance(value, dict):\n return self.field.missing_value\nreturn value"
] | <|body_start_0|>
ordered_uuids = [(k, v) for k, v in value.items()]
ordered_uuids.sort(key=lambda x: x[1]['order'])
return '\r\n'.join([i[0] for i in ordered_uuids])
<|end_body_0|>
<|body_start_1|>
if not len(value) or not isinstance(value, dict):
return self.field.missing_v... | A data converter using the field's ``fromUnicode()`` method. | UUIDSFieldDataConverter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UUIDSFieldDataConverter:
"""A data converter using the field's ``fromUnicode()`` method."""
def toWidgetValue(self, value):
"""Converts the internal stored value into something that a z3c.form widget understands :param value: [required] The internally stored value :type value: Dict :... | stack_v2_sparse_classes_36k_train_004376 | 4,915 | no_license | [
{
"docstring": "Converts the internal stored value into something that a z3c.form widget understands :param value: [required] The internally stored value :type value: Dict :returns: A string with UUIDs separated by",
"name": "toWidgetValue",
"signature": "def toWidgetValue(self, value)"
},
{
"do... | 2 | stack_v2_sparse_classes_30k_val_000825 | Implement the Python class `UUIDSFieldDataConverter` described below.
Class description:
A data converter using the field's ``fromUnicode()`` method.
Method signatures and docstrings:
- def toWidgetValue(self, value): Converts the internal stored value into something that a z3c.form widget understands :param value: [... | Implement the Python class `UUIDSFieldDataConverter` described below.
Class description:
A data converter using the field's ``fromUnicode()`` method.
Method signatures and docstrings:
- def toWidgetValue(self, value): Converts the internal stored value into something that a z3c.form widget understands :param value: [... | 55e273528cd5db4bbd1929a23ef74c3d873ec690 | <|skeleton|>
class UUIDSFieldDataConverter:
"""A data converter using the field's ``fromUnicode()`` method."""
def toWidgetValue(self, value):
"""Converts the internal stored value into something that a z3c.form widget understands :param value: [required] The internally stored value :type value: Dict :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UUIDSFieldDataConverter:
"""A data converter using the field's ``fromUnicode()`` method."""
def toWidgetValue(self, value):
"""Converts the internal stored value into something that a z3c.form widget understands :param value: [required] The internally stored value :type value: Dict :returns: A st... | the_stack_v2_python_sparse | buildout-cache/eggs/collective.cover-1.0a10-py2.7.egg/collective/cover/tiles/carousel.py | Vinsurya/Plone | train | 0 |
600fb6e7f7b30b17903933e01785f6081a15ae99 | [
"message = f'{level}: No {resource} has been specified.'\nLog.msg(msg=message, print_msg=True)\nreturn message",
"if additional_notes is None:\n notes = ''\nelse:\n notes = additional_notes\nmessage = f\"Support for {resource_name} is now in the '{feature_state}' stage. Please use with caution. {notes}\"\nL... | <|body_start_0|>
message = f'{level}: No {resource} has been specified.'
Log.msg(msg=message, print_msg=True)
return message
<|end_body_0|>
<|body_start_1|>
if additional_notes is None:
notes = ''
else:
notes = additional_notes
message = f"Support... | Errors | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Errors:
def not_specified(resource=None, level='Warning'):
"""Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in error message. (default None) level (str): string with desired warning level (default 'Warning'... | stack_v2_sparse_classes_36k_train_004377 | 2,667 | permissive | [
{
"docstring": "Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in error message. (default None) level (str): string with desired warning level (default 'Warning')",
"name": "not_specified",
"signature": "def not_specified(r... | 2 | stack_v2_sparse_classes_30k_train_020419 | Implement the Python class `Errors` described below.
Class description:
Implement the Errors class.
Method signatures and docstrings:
- def not_specified(resource=None, level='Warning'): Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in ... | Implement the Python class `Errors` described below.
Class description:
Implement the Errors class.
Method signatures and docstrings:
- def not_specified(resource=None, level='Warning'): Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in ... | 53a5dc2d1006ada20911f672daf2e3827296a4fd | <|skeleton|>
class Errors:
def not_specified(resource=None, level='Warning'):
"""Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in error message. (default None) level (str): string with desired warning level (default 'Warning'... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Errors:
def not_specified(resource=None, level='Warning'):
"""Throw an error warning the user that a specified resource has not been specified. Args: resource (str): name of resource to use in error message. (default None) level (str): string with desired warning level (default 'Warning')"""
m... | the_stack_v2_python_sparse | qbitkit/error/error.py | qbitkit/qbitkit | train | 5 | |
9082c4db34b78862d8fe310fdc52ab21b705f106 | [
"super().__init__(*args, **kwargs)\nif log_level is not None:\n self.log_level = log_level\nelse:\n self.log_level = logging.INFO\nself.log = self.setup_logger()",
"formatter = ColoredFormatter('%(log_color)s[%(asctime)s.%(msecs)03d][%(levelname)-8s] %(name)-20s: %(reset)s%(white)s%(message)s', datefmt='%d-... | <|body_start_0|>
super().__init__(*args, **kwargs)
if log_level is not None:
self.log_level = log_level
else:
self.log_level = logging.INFO
self.log = self.setup_logger()
<|end_body_0|>
<|body_start_1|>
formatter = ColoredFormatter('%(log_color)s[%(asctim... | Log class | Logger | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Logger:
"""Log class"""
def __init__(self, *args, log_level=None, **kwargs):
"""Initialisation method"""
<|body_0|>
def setup_logger(self):
"""Return a logger with a default ColoredFormatter."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super... | stack_v2_sparse_classes_36k_train_004378 | 1,672 | permissive | [
{
"docstring": "Initialisation method",
"name": "__init__",
"signature": "def __init__(self, *args, log_level=None, **kwargs)"
},
{
"docstring": "Return a logger with a default ColoredFormatter.",
"name": "setup_logger",
"signature": "def setup_logger(self)"
}
] | 2 | null | Implement the Python class `Logger` described below.
Class description:
Log class
Method signatures and docstrings:
- def __init__(self, *args, log_level=None, **kwargs): Initialisation method
- def setup_logger(self): Return a logger with a default ColoredFormatter. | Implement the Python class `Logger` described below.
Class description:
Log class
Method signatures and docstrings:
- def __init__(self, *args, log_level=None, **kwargs): Initialisation method
- def setup_logger(self): Return a logger with a default ColoredFormatter.
<|skeleton|>
class Logger:
"""Log class"""
... | 836498b210d2f921e76292df8046cd79006b458a | <|skeleton|>
class Logger:
"""Log class"""
def __init__(self, *args, log_level=None, **kwargs):
"""Initialisation method"""
<|body_0|>
def setup_logger(self):
"""Return a logger with a default ColoredFormatter."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Logger:
"""Log class"""
def __init__(self, *args, log_level=None, **kwargs):
"""Initialisation method"""
super().__init__(*args, **kwargs)
if log_level is not None:
self.log_level = log_level
else:
self.log_level = logging.INFO
self.log = se... | the_stack_v2_python_sparse | src/pyndf/logbook.py | Guillaume-Guardia/ndf-python | train | 0 |
531bb58ffebad8281adbfe949894424581114e1c | [
"super().__init__(name=name, id=id, classes=classes, disabled=disabled)\nself.data = data\nif summary_function is not None:\n self.summary_function = summary_function",
"if not self.data:\n return '<empty sparkline>'\n_, base = self.background_colors\nreturn SparklineRenderable(self.data, width=self.size.wi... | <|body_start_0|>
super().__init__(name=name, id=id, classes=classes, disabled=disabled)
self.data = data
if summary_function is not None:
self.summary_function = summary_function
<|end_body_0|>
<|body_start_1|>
if not self.data:
return '<empty sparkline>'
... | A sparkline widget to display numerical data. | Sparkline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sparkline:
"""A sparkline widget to display numerical data."""
def __init__(self, data: Sequence[float] | None=None, *, summary_function: Callable[[Sequence[float]], float] | None=None, name: str | None=None, id: str | None=None, classes: str | None=None, disabled: bool=False) -> None:
... | stack_v2_sparse_classes_36k_train_004379 | 3,229 | permissive | [
{
"docstring": "Initialize a sparkline widget. Args: data: The initial data to populate the sparkline with. summary_function: Summarises bar values into a single value used to represent each bar. name: The name of the widget. id: The ID of the widget in the DOM. classes: The CSS classes for the widget. disabled... | 2 | stack_v2_sparse_classes_30k_train_002675 | Implement the Python class `Sparkline` described below.
Class description:
A sparkline widget to display numerical data.
Method signatures and docstrings:
- def __init__(self, data: Sequence[float] | None=None, *, summary_function: Callable[[Sequence[float]], float] | None=None, name: str | None=None, id: str | None=... | Implement the Python class `Sparkline` described below.
Class description:
A sparkline widget to display numerical data.
Method signatures and docstrings:
- def __init__(self, data: Sequence[float] | None=None, *, summary_function: Callable[[Sequence[float]], float] | None=None, name: str | None=None, id: str | None=... | b74ac1e47fdd16133ca567390c99ea19de278c5a | <|skeleton|>
class Sparkline:
"""A sparkline widget to display numerical data."""
def __init__(self, data: Sequence[float] | None=None, *, summary_function: Callable[[Sequence[float]], float] | None=None, name: str | None=None, id: str | None=None, classes: str | None=None, disabled: bool=False) -> None:
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sparkline:
"""A sparkline widget to display numerical data."""
def __init__(self, data: Sequence[float] | None=None, *, summary_function: Callable[[Sequence[float]], float] | None=None, name: str | None=None, id: str | None=None, classes: str | None=None, disabled: bool=False) -> None:
"""Initial... | the_stack_v2_python_sparse | src/textual/widgets/_sparkline.py | Textualize/textual | train | 14,818 |
9bddf3dc21aed011de2bf79da434b0ade00c3668 | [
"words = re.split('\\\\W+', self.name)\nwords = list(filter(lambda word: len(word) > 3, words))\nreturn ' '.join(words).lower()",
"if not self.tags:\n tags = self._create_tags()\n if tags:\n self.tags = self._create_tags()\n'If no set meta-parameters html - title or description then\\n generat... | <|body_start_0|>
words = re.split('\\W+', self.name)
words = list(filter(lambda word: len(word) > 3, words))
return ' '.join(words).lower()
<|end_body_0|>
<|body_start_1|>
if not self.tags:
tags = self._create_tags()
if tags:
self.tags = self._cre... | Article | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Article:
def _create_tags(self):
"""Create tags from name of article"""
<|body_0|>
def save(self, *args, **kwargs):
"""If tags not determinated then generating their"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
words = re.split('\\W+', self.name)... | stack_v2_sparse_classes_36k_train_004380 | 5,531 | no_license | [
{
"docstring": "Create tags from name of article",
"name": "_create_tags",
"signature": "def _create_tags(self)"
},
{
"docstring": "If tags not determinated then generating their",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010543 | Implement the Python class `Article` described below.
Class description:
Implement the Article class.
Method signatures and docstrings:
- def _create_tags(self): Create tags from name of article
- def save(self, *args, **kwargs): If tags not determinated then generating their | Implement the Python class `Article` described below.
Class description:
Implement the Article class.
Method signatures and docstrings:
- def _create_tags(self): Create tags from name of article
- def save(self, *args, **kwargs): If tags not determinated then generating their
<|skeleton|>
class Article:
def _cr... | c4bb84cd3f3addf40cc27f0a8ee22fb77eff5456 | <|skeleton|>
class Article:
def _create_tags(self):
"""Create tags from name of article"""
<|body_0|>
def save(self, *args, **kwargs):
"""If tags not determinated then generating their"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Article:
def _create_tags(self):
"""Create tags from name of article"""
words = re.split('\\W+', self.name)
words = list(filter(lambda word: len(word) > 3, words))
return ' '.join(words).lower()
def save(self, *args, **kwargs):
"""If tags not determinated then gene... | the_stack_v2_python_sparse | src/apps/posts/models.py | artempy/tourism_django | train | 3 | |
fcbc4a2489d6549fee91091cbb90edd04ae1cd33 | [
"if not isinstance(condition, PassPredicate):\n raise TypeError('Expected PassPredicate, got %s.' % type(condition))\nif not is_sequence(loop_body) and (not isinstance(loop_body, BasePass)):\n raise TypeError('Expected Pass or sequence of Passes, got %s.' % type(loop_body))\nif is_sequence(loop_body):\n tr... | <|body_start_0|>
if not isinstance(condition, PassPredicate):
raise TypeError('Expected PassPredicate, got %s.' % type(condition))
if not is_sequence(loop_body) and (not isinstance(loop_body, BasePass)):
raise TypeError('Expected Pass or sequence of Passes, got %s.' % type(loop_b... | The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop. | DoWhileLoopPass | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoWhileLoopPass:
"""The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop."""
def __init__(self, condition: PassPredicate, loop_body: BasePass | Sequence[BasePass]) -> None:
"""Construct a DoWhileLoopPass. Args: cond... | stack_v2_sparse_classes_36k_train_004381 | 2,452 | permissive | [
{
"docstring": "Construct a DoWhileLoopPass. Args: condition (PassPredicate): The condition checked. loop_body (BasePass | Sequence[BasePass]): The pass or passes to execute while `condition` is true. Raises: ValueError: If a Sequence[BasePass] is given, but it is empty.",
"name": "__init__",
"signature... | 2 | null | Implement the Python class `DoWhileLoopPass` described below.
Class description:
The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop.
Method signatures and docstrings:
- def __init__(self, condition: PassPredicate, loop_body: BasePass | Sequence[Ba... | Implement the Python class `DoWhileLoopPass` described below.
Class description:
The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop.
Method signatures and docstrings:
- def __init__(self, condition: PassPredicate, loop_body: BasePass | Sequence[Ba... | 3083218c2f4e3c3ce4ba027d12caa30c384d7665 | <|skeleton|>
class DoWhileLoopPass:
"""The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop."""
def __init__(self, condition: PassPredicate, loop_body: BasePass | Sequence[BasePass]) -> None:
"""Construct a DoWhileLoopPass. Args: cond... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoWhileLoopPass:
"""The DoWhileLoopPass class. This is a control pass that executes a pass and then conditionally executes it again in a loop."""
def __init__(self, condition: PassPredicate, loop_body: BasePass | Sequence[BasePass]) -> None:
"""Construct a DoWhileLoopPass. Args: condition (PassPr... | the_stack_v2_python_sparse | bqskit/compiler/passes/control/dowhileloop.py | mtreinish/bqskit | train | 0 |
c90787940a19bfc132b6bbaa5e64204c2b4a20a2 | [
"env = {}\nif node_env is not None:\n env = node_env\nlegacy_dirpath = ccmlib.repository.directory_name(legacy_version)\nenv['CASSANDRA_HOME'] = legacy_dirpath\nbinpaths = [legacy_dirpath, os.path.join(legacy_dirpath, 'build', 'classes', 'main'), os.path.join(legacy_dirpath, 'build', 'classes', 'thrift')]\nenv['... | <|body_start_0|>
env = {}
if node_env is not None:
env = node_env
legacy_dirpath = ccmlib.repository.directory_name(legacy_version)
env['CASSANDRA_HOME'] = legacy_dirpath
binpaths = [legacy_dirpath, os.path.join(legacy_dirpath, 'build', 'classes', 'main'), os.path.joi... | * @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs. | TestDeprecatedRepairNotifications | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDeprecatedRepairNotifications:
"""* @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs."""
def get_legacy_environment(se... | stack_v2_sparse_classes_36k_train_004382 | 14,147 | permissive | [
{
"docstring": "* Set up an environment to run nodetool from cassandra-2.1.",
"name": "get_legacy_environment",
"signature": "def get_legacy_environment(self, legacy_version, node_env=None)"
},
{
"docstring": "* Check whether a legacy JMX nodetool understands the * notification for a failed repa... | 2 | stack_v2_sparse_classes_30k_train_021454 | Implement the Python class `TestDeprecatedRepairNotifications` described below.
Class description:
* @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs... | Implement the Python class `TestDeprecatedRepairNotifications` described below.
Class description:
* @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs... | 738d5de93def153338003a26e304a77463a7fd2a | <|skeleton|>
class TestDeprecatedRepairNotifications:
"""* @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs."""
def get_legacy_environment(se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDeprecatedRepairNotifications:
"""* @jira_ticket CASSANDRA-13121 * Test if legacy JMX detects failures in repair jobs launched with the deprecated API. * Affects cassandra-3.x clusters when users run JMX from cassandra-2.1 and older to submit repair jobs."""
def get_legacy_environment(self, legacy_ve... | the_stack_v2_python_sparse | repair_tests/deprecated_repair_test.py | apache/cassandra-dtest | train | 52 |
46fd1e9eb7847f29b8e19ff7989d01e36dcb535a | [
"patient = Patient.objects.get_patient_by_id(domain_id, patient_id)\nif patient is not None:\n serializer = self.get_serializer(patient)\n patient_data = serializer.data\n return Response(patient_data, status=status.HTTP_200_OK)",
"data = request.data\ndata['cohort'] = domain_id\ndata['updated_by'] = req... | <|body_start_0|>
patient = Patient.objects.get_patient_by_id(domain_id, patient_id)
if patient is not None:
serializer = self.get_serializer(patient)
patient_data = serializer.data
return Response(patient_data, status=status.HTTP_200_OK)
<|end_body_0|>
<|body_start_1... | CohortPatientsDetailView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CohortPatientsDetailView:
def get(self, request, domain_id, patient_id):
"""Get information about a patient in the domain"""
<|body_0|>
def put(self, request, domain_id, patient_id):
"""Update a patient in a domain"""
<|body_1|>
def delete(self, request,... | stack_v2_sparse_classes_36k_train_004383 | 3,780 | no_license | [
{
"docstring": "Get information about a patient in the domain",
"name": "get",
"signature": "def get(self, request, domain_id, patient_id)"
},
{
"docstring": "Update a patient in a domain",
"name": "put",
"signature": "def put(self, request, domain_id, patient_id)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_train_021039 | Implement the Python class `CohortPatientsDetailView` described below.
Class description:
Implement the CohortPatientsDetailView class.
Method signatures and docstrings:
- def get(self, request, domain_id, patient_id): Get information about a patient in the domain
- def put(self, request, domain_id, patient_id): Upda... | Implement the Python class `CohortPatientsDetailView` described below.
Class description:
Implement the CohortPatientsDetailView class.
Method signatures and docstrings:
- def get(self, request, domain_id, patient_id): Get information about a patient in the domain
- def put(self, request, domain_id, patient_id): Upda... | 5d5bc4c1eecbf627d38260e4d314d8451d67a4f5 | <|skeleton|>
class CohortPatientsDetailView:
def get(self, request, domain_id, patient_id):
"""Get information about a patient in the domain"""
<|body_0|>
def put(self, request, domain_id, patient_id):
"""Update a patient in a domain"""
<|body_1|>
def delete(self, request,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CohortPatientsDetailView:
def get(self, request, domain_id, patient_id):
"""Get information about a patient in the domain"""
patient = Patient.objects.get_patient_by_id(domain_id, patient_id)
if patient is not None:
serializer = self.get_serializer(patient)
pati... | the_stack_v2_python_sparse | curation-api/src/patients/views/cohort_patient.py | mohanj1919/django_app_test | train | 0 | |
1f2d00683ef59323cd6789f61f922229dabd7576 | [
"if isinstance(request.auth, ProjectKey):\n return self.respond(status=401)\nif organization_slug:\n if project.organization.slug != organization_slug:\n return self.respond_invalid()\nqueryset = MonitorCheckIn.objects.filter(monitor_id=monitor.id)\nreturn self.paginate(request=request, queryset=querys... | <|body_start_0|>
if isinstance(request.auth, ProjectKey):
return self.respond(status=401)
if organization_slug:
if project.organization.slug != organization_slug:
return self.respond_invalid()
queryset = MonitorCheckIn.objects.filter(monitor_id=monitor.id)... | MonitorCheckInsEndpoint | [
"Apache-2.0",
"BUSL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonitorCheckInsEndpoint:
def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response:
"""Retrieve a list of check-ins for a monitor"""
<|body_0|>
def post(self, request: Request, project, monitor, organization_slug: str | None=None) -> R... | stack_v2_sparse_classes_36k_train_004384 | 6,229 | permissive | [
{
"docstring": "Retrieve a list of check-ins for a monitor",
"name": "get",
"signature": "def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response"
},
{
"docstring": "Creates a new check-in for a monitor. If `status` is not present, it will be assumed tha... | 2 | stack_v2_sparse_classes_30k_train_010757 | Implement the Python class `MonitorCheckInsEndpoint` described below.
Class description:
Implement the MonitorCheckInsEndpoint class.
Method signatures and docstrings:
- def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response: Retrieve a list of check-ins for a monitor
- def ... | Implement the Python class `MonitorCheckInsEndpoint` described below.
Class description:
Implement the MonitorCheckInsEndpoint class.
Method signatures and docstrings:
- def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response: Retrieve a list of check-ins for a monitor
- def ... | d9dd4f382f96b5c4576b64cbf015db651556c18b | <|skeleton|>
class MonitorCheckInsEndpoint:
def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response:
"""Retrieve a list of check-ins for a monitor"""
<|body_0|>
def post(self, request: Request, project, monitor, organization_slug: str | None=None) -> R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MonitorCheckInsEndpoint:
def get(self, request: Request, project, monitor, organization_slug: str | None=None) -> Response:
"""Retrieve a list of check-ins for a monitor"""
if isinstance(request.auth, ProjectKey):
return self.respond(status=401)
if organization_slug:
... | the_stack_v2_python_sparse | src/sentry/api/endpoints/monitor_checkins.py | nagyist/sentry | train | 0 | |
f36f2395d5a4882c06dd2891e7c7d5faf9df7e8d | [
"res = []\ni, j = (1, n)\nwhile i <= j:\n if k > 1:\n if k & 1:\n res.append(i)\n i += 1\n else:\n res.append(j)\n j -= 1\n k -= 1\n else:\n res.append(i)\n i += 1\nreturn res",
"i, j = (1, n)\nres = []\nflag = 1\nfor _ in range(... | <|body_start_0|>
res = []
i, j = (1, n)
while i <= j:
if k > 1:
if k & 1:
res.append(i)
i += 1
else:
res.append(j)
j -= 1
k -= 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_0|>
def constructArray_WRONG(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
... | stack_v2_sparse_classes_36k_train_004385 | 2,757 | no_license | [
{
"docstring": ":type n: int :type k: int :rtype: List[int]",
"name": "constructArray",
"signature": "def constructArray(self, n, k)"
},
{
"docstring": ":type n: int :type k: int :rtype: List[int]",
"name": "constructArray_WRONG",
"signature": "def constructArray_WRONG(self, n, k)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructArray(self, n, k): :type n: int :type k: int :rtype: List[int]
- def constructArray_WRONG(self, n, k): :type n: int :type k: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def constructArray(self, n, k): :type n: int :type k: int :rtype: List[int]
- def constructArray_WRONG(self, n, k): :type n: int :type k: int :rtype: List[int]
<|skeleton|>
clas... | 635af6e22aa8eef8e7920a585d43a45a891a8157 | <|skeleton|>
class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_0|>
def constructArray_WRONG(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def constructArray(self, n, k):
""":type n: int :type k: int :rtype: List[int]"""
res = []
i, j = (1, n)
while i <= j:
if k > 1:
if k & 1:
res.append(i)
i += 1
else:
... | the_stack_v2_python_sparse | code667BeautifulArrangementII.py | cybelewang/leetcode-python | train | 0 | |
736a9fde6c084d8c7280cdfff2befa90245772da | [
"self.privilege_id = privilege_id\nself.additional_categories = additional_categories\nself.category = category\nself.description = description\nself.is_available_on_helios = is_available_on_helios\nself.is_custom_role_default = is_custom_role_default\nself.is_saa_s_only = is_saa_s_only\nself.is_special = is_specia... | <|body_start_0|>
self.privilege_id = privilege_id
self.additional_categories = additional_categories
self.category = category
self.description = description
self.is_available_on_helios = is_available_on_helios
self.is_custom_role_default = is_custom_role_default
s... | Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for unique privilege Id values. All below enum va... | PrivilegeInfo | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for uniq... | stack_v2_sparse_classes_36k_train_004386 | 5,145 | permissive | [
{
"docstring": "Constructor for the PrivilegeInfo class",
"name": "__init__",
"signature": "def __init__(self, privilege_id=None, additional_categories=None, category=None, description=None, is_available_on_helios=None, is_custom_role_default=None, is_saa_s_only=None, is_special=None, is_view_only=None,... | 2 | stack_v2_sparse_classes_30k_test_001156 | Implement the Python class `PrivilegeInfo` described below.
Class description:
Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when ... | Implement the Python class `PrivilegeInfo` described below.
Class description:
Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for uniq... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PrivilegeInfo:
"""Implementation of the 'PrivilegeInfo' model. Specifies details about a privilege such as the category, description, name, etc. Attributes: privilege_id (PrivilegeIdEnum): Specifies unique id for a privilege. This number must be unique when creating a new privilege. Type for unique privilege ... | the_stack_v2_python_sparse | cohesity_management_sdk/models/privilege_info.py | cohesity/management-sdk-python | train | 24 |
21790df1a4bc34589c2f8b438ac17a548ce5ff2b | [
"node = TestNode(names=[('logging', None)], lineno=15)\nself.checker.visit_import(node)\nself.assertEqual(self.results, [('R9301', '', 15, None)])",
"node = TestNode(names=[('myModule', None)], lineno=15)\nself.checker.visit_import(node)\nself.assertEqual(self.results, [])"
] | <|body_start_0|>
node = TestNode(names=[('logging', None)], lineno=15)
self.checker.visit_import(node)
self.assertEqual(self.results, [('R9301', '', 15, None)])
<|end_body_0|>
<|body_start_1|>
node = TestNode(names=[('myModule', None)], lineno=15)
self.checker.visit_import(node)... | Tests for ChromiteLoggingChecker module | ChromiteLoggingCheckerTest | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.0-or-later",
"GPL-1.0-or-later",
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChromiteLoggingCheckerTest:
"""Tests for ChromiteLoggingChecker module"""
def testLoggingImported(self):
"""Test that import logging is flagged."""
<|body_0|>
def testLoggingNotImported(self):
"""Test that importing something else (not logging) is not flagged."""... | stack_v2_sparse_classes_36k_train_004387 | 11,497 | permissive | [
{
"docstring": "Test that import logging is flagged.",
"name": "testLoggingImported",
"signature": "def testLoggingImported(self)"
},
{
"docstring": "Test that importing something else (not logging) is not flagged.",
"name": "testLoggingNotImported",
"signature": "def testLoggingNotImpor... | 2 | null | Implement the Python class `ChromiteLoggingCheckerTest` described below.
Class description:
Tests for ChromiteLoggingChecker module
Method signatures and docstrings:
- def testLoggingImported(self): Test that import logging is flagged.
- def testLoggingNotImported(self): Test that importing something else (not loggin... | Implement the Python class `ChromiteLoggingCheckerTest` described below.
Class description:
Tests for ChromiteLoggingChecker module
Method signatures and docstrings:
- def testLoggingImported(self): Test that import logging is flagged.
- def testLoggingNotImported(self): Test that importing something else (not loggin... | 72a05af97787001756bae2511b7985e61498c965 | <|skeleton|>
class ChromiteLoggingCheckerTest:
"""Tests for ChromiteLoggingChecker module"""
def testLoggingImported(self):
"""Test that import logging is flagged."""
<|body_0|>
def testLoggingNotImported(self):
"""Test that importing something else (not logging) is not flagged."""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChromiteLoggingCheckerTest:
"""Tests for ChromiteLoggingChecker module"""
def testLoggingImported(self):
"""Test that import logging is flagged."""
node = TestNode(names=[('logging', None)], lineno=15)
self.checker.visit_import(node)
self.assertEqual(self.results, [('R9301... | the_stack_v2_python_sparse | third_party/chromite/cli/cros/lint_unittest.py | metux/chromium-suckless | train | 5 |
150889e01da1f226bdc2e47e8d0f9ffe126531c4 | [
"this_object = self.model_object\nif hasattr(this_object, self.group_required_field):\n if hasattr(getattr(this_object, self.group_required_field), 'name'):\n return [getattr(this_object, self.group_required_field).name]\nreturn ['']",
"if not groups or groups == ['']:\n return True\nif self.request.... | <|body_start_0|>
this_object = self.model_object
if hasattr(this_object, self.group_required_field):
if hasattr(getattr(this_object, self.group_required_field), 'name'):
return [getattr(this_object, self.group_required_field).name]
return ['']
<|end_body_0|>
<|body_s... | This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey responses that are optionally restricted. | GroupRequiredByFieldMixin | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GroupRequiredByFieldMixin:
"""This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey responses that are optionally restricted.""... | stack_v2_sparse_classes_36k_train_004388 | 30,664 | permissive | [
{
"docstring": "Get the group_required value from the object",
"name": "get_group_required",
"signature": "def get_group_required(self)"
},
{
"docstring": "Allows for objects with no required groups",
"name": "check_membership",
"signature": "def check_membership(self, groups)"
},
{
... | 3 | null | Implement the Python class `GroupRequiredByFieldMixin` described below.
Class description:
This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey resp... | Implement the Python class `GroupRequiredByFieldMixin` described below.
Class description:
This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey resp... | 19db3e83e76ea2002ee841989410d12d1e601023 | <|skeleton|>
class GroupRequiredByFieldMixin:
"""This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey responses that are optionally restricted.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GroupRequiredByFieldMixin:
"""This subclass of the GroupRequiredMixin checks if a specified model field identifies a group that is required. If so, then require this group. If not, then no permissions are required. This can be used for thing like survey responses that are optionally restricted."""
def ge... | the_stack_v2_python_sparse | danceschool/core/mixins.py | django-danceschool/django-danceschool | train | 40 |
e3cdd6449c6652fe070a5e258973c4cf68ef85e5 | [
"testcases: List[TestCase] = TestCase.query.all()\nres = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]\nreturn {'body': res}",
"testcase = TestCase(name=request.json.get('name'), description=request.json.get('descri... | <|body_start_0|>
testcases: List[TestCase] = TestCase.query.all()
res = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]
return {'body': res}
<|end_body_0|>
<|body_start_1|>
testcase = TestCa... | TestCaseService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
<|body_0|>
def post(self):
"""上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
testcases: L... | stack_v2_sparse_classes_36k_train_004389 | 4,613 | no_license | [
{
"docstring": "测试用例的浏览获取 /testcase.json /testcase.json?id=1",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004972 | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 测试用例的浏览获取 /testcase.json /testcase.json?id=1
- def post(self): 上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []} | Implement the Python class `TestCaseService` described below.
Class description:
Implement the TestCaseService class.
Method signatures and docstrings:
- def get(self): 测试用例的浏览获取 /testcase.json /testcase.json?id=1
- def post(self): 上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}
<|skeleto... | bd8bce8160c458bf49970dbf94dadb3c822fdd53 | <|skeleton|>
class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
<|body_0|>
def post(self):
"""上传用例， 更新用例 /testcase.json {'name': 'xx', 'description': 'xxx', 'steps': []}"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCaseService:
def get(self):
"""测试用例的浏览获取 /testcase.json /testcase.json?id=1"""
testcases: List[TestCase] = TestCase.query.all()
res = [{'id': testcase.id, 'name': testcase.name, 'description': testcase.description, 'steps': json.loads(testcase.steps)} for testcase in testcases]
... | the_stack_v2_python_sparse | platform/src/backend.py | baihongliang/HogwartsLG4 | train | 0 | |
4f63c3fac3e53319b2fe3e8ca84e76be02d7d6bd | [
"self.perms = perms\nself.event_param = event_param\nself.require_all = require_all",
"def wrapped_f(*args, **kwargs):\n from ezreg.models import Event\n event = Event.objects.get(id=kwargs[self.event_param])\n kwargs[self.event_param] = event\n request = args[0]\n if not request.user.is_authentica... | <|body_start_0|>
self.perms = perms
self.event_param = event_param
self.require_all = require_all
<|end_body_0|>
<|body_start_1|>
def wrapped_f(*args, **kwargs):
from ezreg.models import Event
event = Event.objects.get(id=kwargs[self.event_param])
kwa... | event_access_decorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class event_access_decorator:
def __init__(self, perms, event_param='event', require_all=True):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __c... | stack_v2_sparse_classes_36k_train_004390 | 5,101 | no_license | [
{
"docstring": "If there are decorator arguments, the function to be decorated is not passed to the constructor!",
"name": "__init__",
"signature": "def __init__(self, perms, event_param='event', require_all=True)"
},
{
"docstring": "If there are decorator arguments, __call__() is only called on... | 2 | stack_v2_sparse_classes_30k_train_001415 | Implement the Python class `event_access_decorator` described below.
Class description:
Implement the event_access_decorator class.
Method signatures and docstrings:
- def __init__(self, perms, event_param='event', require_all=True): If there are decorator arguments, the function to be decorated is not passed to the ... | Implement the Python class `event_access_decorator` described below.
Class description:
Implement the event_access_decorator class.
Method signatures and docstrings:
- def __init__(self, perms, event_param='event', require_all=True): If there are decorator arguments, the function to be decorated is not passed to the ... | 3862986f908e3d2dd4c4b9a485cd9ebfdcafcd1b | <|skeleton|>
class event_access_decorator:
def __init__(self, perms, event_param='event', require_all=True):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
<|body_0|>
def __call__(self, f):
"""If there are decorator arguments, __c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class event_access_decorator:
def __init__(self, perms, event_param='event', require_all=True):
"""If there are decorator arguments, the function to be decorated is not passed to the constructor!"""
self.perms = perms
self.event_param = event_param
self.require_all = require_all
... | the_stack_v2_python_sparse | ezreg/decorators.py | amschaal/django-ezreg | train | 5 | |
90440a115a89573161e2cb6b70aaed035a785c0c | [
"if not self.ssh_accessible:\n logger.info('You do not have SSH access to the Archivematica server')\n return None\nfilename = os.path.basename(server_file_path)\nlocal_path = os.path.join(self.tmp_path, filename)\nif self.server_user and self.ssh_identity_file:\n cmd = 'scp -o StrictHostKeyChecking=no -i ... | <|body_start_0|>
if not self.ssh_accessible:
logger.info('You do not have SSH access to the Archivematica server')
return None
filename = os.path.basename(server_file_path)
local_path = os.path.join(self.tmp_path, filename)
if self.server_user and self.ssh_identit... | Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica. | ArchivematicaSSHAbility | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArchivematicaSSHAbility:
"""Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica."""
def scp_server_file_to_local(self, server_file_path, retries=5):
"""Use scp to copy a file from the server to our local tmp directory."""
... | stack_v2_sparse_classes_36k_train_004391 | 7,018 | no_license | [
{
"docstring": "Use scp to copy a file from the server to our local tmp directory.",
"name": "scp_server_file_to_local",
"signature": "def scp_server_file_to_local(self, server_file_path, retries=5)"
},
{
"docstring": "Use scp to copy a directory from the server to our local tmp directory.",
... | 3 | stack_v2_sparse_classes_30k_train_009103 | Implement the Python class `ArchivematicaSSHAbility` described below.
Class description:
Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica.
Method signatures and docstrings:
- def scp_server_file_to_local(self, server_file_path, retries=5): Use scp to co... | Implement the Python class `ArchivematicaSSHAbility` described below.
Class description:
Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica.
Method signatures and docstrings:
- def scp_server_file_to_local(self, server_file_path, retries=5): Use scp to co... | 96fe940a9e18f97aae5868fe4c7c6d0b389814d0 | <|skeleton|>
class ArchivematicaSSHAbility:
"""Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica."""
def scp_server_file_to_local(self, server_file_path, retries=5):
"""Use scp to copy a file from the server to our local tmp directory."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ArchivematicaSSHAbility:
"""Archivematica SSH Ability: the ability of an Archivematica user to use SSH and scp to interact with Archivematica."""
def scp_server_file_to_local(self, server_file_path, retries=5):
"""Use scp to copy a file from the server to our local tmp directory."""
if no... | the_stack_v2_python_sparse | amuser/am_ssh_ability.py | artefactual-labs/archivematica-acceptance-tests | train | 3 |
2c9bf243b9a9bc8da42d91357547c36be57ce25b | [
"db_name = 'Brain'\ndb_table = 'Targets'\nquery_plugin_names = rtdb.db(db_name).table(db_table).pluck('PluginName', 'Location').run(connect())\nfor plugin_item in query_plugin_names:\n assert isinstance(plugin_item, dict)",
"home_url = '/'\nif check_dev_env() is not None:\n request = rf.get(home_url)\n r... | <|body_start_0|>
db_name = 'Brain'
db_table = 'Targets'
query_plugin_names = rtdb.db(db_name).table(db_table).pluck('PluginName', 'Location').run(connect())
for plugin_item in query_plugin_names:
assert isinstance(plugin_item, dict)
<|end_body_0|>
<|body_start_1|>
ho... | TestIndex | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestIndex:
def test_target_list(self):
"""This test queries all the targets in Brain.Targets to be displayed in W1."""
<|body_0|>
def test_home_page(self, rf):
"""This test checks if the web server displays the home page. :param rf: RequestFactory"""
<|body_1... | stack_v2_sparse_classes_36k_train_004392 | 966 | permissive | [
{
"docstring": "This test queries all the targets in Brain.Targets to be displayed in W1.",
"name": "test_target_list",
"signature": "def test_target_list(self)"
},
{
"docstring": "This test checks if the web server displays the home page. :param rf: RequestFactory",
"name": "test_home_page"... | 2 | stack_v2_sparse_classes_30k_train_001114 | Implement the Python class `TestIndex` described below.
Class description:
Implement the TestIndex class.
Method signatures and docstrings:
- def test_target_list(self): This test queries all the targets in Brain.Targets to be displayed in W1.
- def test_home_page(self, rf): This test checks if the web server display... | Implement the Python class `TestIndex` described below.
Class description:
Implement the TestIndex class.
Method signatures and docstrings:
- def test_target_list(self): This test queries all the targets in Brain.Targets to be displayed in W1.
- def test_home_page(self, rf): This test checks if the web server display... | f9cb9d358777f8cdf396264cc9cd759ce010472b | <|skeleton|>
class TestIndex:
def test_target_list(self):
"""This test queries all the targets in Brain.Targets to be displayed in W1."""
<|body_0|>
def test_home_page(self, rf):
"""This test checks if the web server displays the home page. :param rf: RequestFactory"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestIndex:
def test_target_list(self):
"""This test queries all the targets in Brain.Targets to be displayed in W1."""
db_name = 'Brain'
db_table = 'Targets'
query_plugin_names = rtdb.db(db_name).table(db_table).pluck('PluginName', 'Location').run(connect())
for plugin_... | the_stack_v2_python_sparse | pcp_alpha/Backend/index_app/tests.py | ramrod-project/frontend-ui | train | 0 | |
35f62cef9101337ed9ba64411ad848447a7b3c3e | [
"self.field_config = field_config\nself.tokenizer = None\nself.token_embedding = None\nif field_config.vocab_path and field_config.need_convert:\n self.tokenizer = CustomTokenizer(vocab_file=self.field_config.vocab_path)",
"src_ids = []\nfor text in batch_text:\n src_id = text.split(' ')\n if self.tokeni... | <|body_start_0|>
self.field_config = field_config
self.tokenizer = None
self.token_embedding = None
if field_config.vocab_path and field_config.need_convert:
self.tokenizer = CustomTokenizer(vocab_file=self.field_config.vocab_path)
<|end_body_0|>
<|body_start_1|>
src... | return shape= [batch_size,1] | ScalarFieldReader | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
<|body_0|>
def convert_texts_to_ids(self, batch_text):
""":param batch_text: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_004393 | 2,055 | permissive | [
{
"docstring": ":param field_config:",
"name": "__init__",
"signature": "def __init__(self, field_config)"
},
{
"docstring": ":param batch_text: :return:",
"name": "convert_texts_to_ids",
"signature": "def convert_texts_to_ids(self, batch_text)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013169 | Implement the Python class `ScalarFieldReader` described below.
Class description:
return shape= [batch_size,1]
Method signatures and docstrings:
- def __init__(self, field_config): :param field_config:
- def convert_texts_to_ids(self, batch_text): :param batch_text: :return: | Implement the Python class `ScalarFieldReader` described below.
Class description:
return shape= [batch_size,1]
Method signatures and docstrings:
- def __init__(self, field_config): :param field_config:
- def convert_texts_to_ids(self, batch_text): :param batch_text: :return:
<|skeleton|>
class ScalarFieldReader:
... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
<|body_0|>
def convert_texts_to_ids(self, batch_text):
""":param batch_text: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScalarFieldReader:
"""return shape= [batch_size,1]"""
def __init__(self, field_config):
""":param field_config:"""
self.field_config = field_config
self.tokenizer = None
self.token_embedding = None
if field_config.vocab_path and field_config.need_convert:
... | the_stack_v2_python_sparse | research/nlp/senta/src/data/field_reader/scalar_field_reader.py | mindspore-ai/models | train | 301 |
08a8d852fa8879dd900fabc2b1046c391d078784 | [
"capture_output = []\nif interface is None:\n raise Exception('Please provide the interface used.')\nelse:\n capture = pyshark.LiveCapture(interface=interface, bpf_filter=bpf_filter, tshark_path=tshark_path, output_file=output_file)\n capture.sniff(timeout=timeout)\n length = len(capture)\n return (c... | <|body_start_0|>
capture_output = []
if interface is None:
raise Exception('Please provide the interface used.')
else:
capture = pyshark.LiveCapture(interface=interface, bpf_filter=bpf_filter, tshark_path=tshark_path, output_file=output_file)
capture.sniff(tim... | Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user. | NetworkMonitor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkMonitor:
"""Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user."""
def get_packets(timeout=50, interface=None, bpf_filter=None, display_filter='tcp.port == 80', tshark_path=None, output_file=None):
"""R... | stack_v2_sparse_classes_36k_train_004394 | 3,625 | permissive | [
{
"docstring": "Returns the captured packets of the transmitted data using Wireshark. Args: timeout: An integer. Set for sniffing with tshark. Default to 50 seconds in this setup. interface: A string. Name of the interface to sniff on. bpf_filter: A string. The capture filter in bpf syntax 'tcp port 80'. Needs ... | 2 | null | Implement the Python class `NetworkMonitor` described below.
Class description:
Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user.
Method signatures and docstrings:
- def get_packets(timeout=50, interface=None, bpf_filter=None, display_filter... | Implement the Python class `NetworkMonitor` described below.
Class description:
Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user.
Method signatures and docstrings:
- def get_packets(timeout=50, interface=None, bpf_filter=None, display_filter... | cc4765bed880ad38a02505834f63df39e0815328 | <|skeleton|>
class NetworkMonitor:
"""Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user."""
def get_packets(timeout=50, interface=None, bpf_filter=None, display_filter='tcp.port == 80', tshark_path=None, output_file=None):
"""R... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkMonitor:
"""Provides utility for the monitoring of network traffic, measuring the packets sent through specific filters as passed by user."""
def get_packets(timeout=50, interface=None, bpf_filter=None, display_filter='tcp.port == 80', tshark_path=None, output_file=None):
"""Returns the ca... | the_stack_v2_python_sparse | syft/generic/metrics.py | tudorcebere/PySyft | train | 2 |
655c2580b2659820a0b3813b92e4706bbc4fad80 | [
"try:\n event.data = _event_mappings[event_type].deserialize(event.data)\nexcept KeyError:\n event.data = None",
"if isinstance(event, six.binary_type):\n event = json.loads(event.decode(encode))\nelif isinstance(event, six.string_types):\n event = json.loads(event)\nreturn event"
] | <|body_start_0|>
try:
event.data = _event_mappings[event_type].deserialize(event.data)
except KeyError:
event.data = None
<|end_body_0|>
<|body_start_1|>
if isinstance(event, six.binary_type):
event = json.loads(event.decode(encode))
elif isinstance(e... | Mixin for the event models comprising of some helper methods. | EventMixin | [
"LicenseRef-scancode-generic-cla",
"LGPL-2.1-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EventMixin:
"""Mixin for the event models comprising of some helper methods."""
def _deserialize_data(event, event_type):
"""Sets the data of the desrialized event to strongly typed event object if event type exists in _event_mappings. Otherwise, sets it to None. :param str event_typ... | stack_v2_sparse_classes_36k_train_004395 | 7,532 | permissive | [
{
"docstring": "Sets the data of the desrialized event to strongly typed event object if event type exists in _event_mappings. Otherwise, sets it to None. :param str event_type: The event_type of the EventGridEvent object or the type of the CloudEvent object.",
"name": "_deserialize_data",
"signature": ... | 2 | null | Implement the Python class `EventMixin` described below.
Class description:
Mixin for the event models comprising of some helper methods.
Method signatures and docstrings:
- def _deserialize_data(event, event_type): Sets the data of the desrialized event to strongly typed event object if event type exists in _event_m... | Implement the Python class `EventMixin` described below.
Class description:
Mixin for the event models comprising of some helper methods.
Method signatures and docstrings:
- def _deserialize_data(event, event_type): Sets the data of the desrialized event to strongly typed event object if event type exists in _event_m... | f779de8e53dbec033f98f976284e6d9491fd60b3 | <|skeleton|>
class EventMixin:
"""Mixin for the event models comprising of some helper methods."""
def _deserialize_data(event, event_type):
"""Sets the data of the desrialized event to strongly typed event object if event type exists in _event_mappings. Otherwise, sets it to None. :param str event_typ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EventMixin:
"""Mixin for the event models comprising of some helper methods."""
def _deserialize_data(event, event_type):
"""Sets the data of the desrialized event to strongly typed event object if event type exists in _event_mappings. Otherwise, sets it to None. :param str event_type: The event_... | the_stack_v2_python_sparse | sdk/eventgrid/azure-eventgrid/azure/eventgrid/_models.py | YijunXieMS/azure-sdk-for-python | train | 1 |
c255ec6f58a666e9ed62024a798ec158a6ea10ca | [
"self.decimal_places = decimal_places\nself.decimal_separator = decimal_separator\nself.thousands_separator = thousands_separator\nself.dynamic_decimals = dynamic_decimals",
"log.debug('DYNAMIC_DECIMALS: %s', ('off', 'on')[self.dynamic_decimals])\nif not self.dynamic_decimals or n == 0.0:\n return self.decimal... | <|body_start_0|>
self.decimal_places = decimal_places
self.decimal_separator = decimal_separator
self.thousands_separator = thousands_separator
self.dynamic_decimals = dynamic_decimals
<|end_body_0|>
<|body_start_1|>
log.debug('DYNAMIC_DECIMALS: %s', ('off', 'on')[self.dynamic_d... | Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator | Formatter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Formatter:
"""Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator"""
def __init__(self, decimal_places=2, decimal_sep... | stack_v2_sparse_classes_36k_train_004396 | 20,753 | permissive | [
{
"docstring": "Create a new `Formatter`.",
"name": "__init__",
"signature": "def __init__(self, decimal_places=2, decimal_separator='.', thousands_separator='', dynamic_decimals=True)"
},
{
"docstring": "Calculate the number of decimal places the result should have. If :attr:`dynamic_decimals` ... | 4 | stack_v2_sparse_classes_30k_train_000111 | Implement the Python class `Formatter` described below.
Class description:
Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator
Method signature... | Implement the Python class `Formatter` described below.
Class description:
Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator
Method signature... | 97407f4ec8dbca5abbc6952b2b56cf3918624177 | <|skeleton|>
class Formatter:
"""Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator"""
def __init__(self, decimal_places=2, decimal_sep... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Formatter:
"""Format a number. Attributes: decimal_places (int): Number of decimal places in formatted numbers decimal_separator (str): Character to use as decimal separator thousands_separator (str): Character to use as thousands separator"""
def __init__(self, decimal_places=2, decimal_separator='.', t... | the_stack_v2_python_sparse | src/convert.py | deanishe/alfred-convert | train | 781 |
9e4d85dac196005cbda81b25c1baff7073a87e25 | [
"if not hasattr(request, 'user'):\n raise ImproperlyConfigured(\"The Django Bluestem auth middleware requires the authentication middleware to be installed. Edit your MIDDLEWARE_CLASSES setting to insert 'django.contrib.auth.middleware.AuthenticationMiddleware' before the BluestemMiddleware class. Also, you must... | <|body_start_0|>
if not hasattr(request, 'user'):
raise ImproperlyConfigured("The Django Bluestem auth middleware requires the authentication middleware to be installed. Edit your MIDDLEWARE_CLASSES setting to insert 'django.contrib.auth.middleware.AuthenticationMiddleware' before the BluestemMiddle... | Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and attempts to authenticate the user via the BLUESTEM_ID_USER, BLUESTEM_ID_DOMAIN, and B... | BluestemMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BluestemMiddleware:
"""Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and attempts to authenticate the user via t... | stack_v2_sparse_classes_36k_train_004397 | 13,103 | no_license | [
{
"docstring": "Perform Bluestem authentication on request object.",
"name": "_bluestem_authenticate",
"signature": "def _bluestem_authenticate(self, request)"
},
{
"docstring": "Manage a cached object consisting of a set of object references to view functions that are excluded from Bluestem aut... | 5 | stack_v2_sparse_classes_30k_val_000278 | Implement the Python class `BluestemMiddleware` described below.
Class description:
Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and ... | Implement the Python class `BluestemMiddleware` described below.
Class description:
Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and ... | c453759c1b89ae269339fb8fb89dde370af590f3 | <|skeleton|>
class BluestemMiddleware:
"""Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and attempts to authenticate the user via t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BluestemMiddleware:
"""Middleware class for utilizing the Bluestem authentication backend in a Django application. If the request.user object is not already authenticated to Django, this middleware component uses the SDG Bluestem authentication backend, and attempts to authenticate the user via the BLUESTEM_I... | the_stack_v2_python_sparse | server_proj/sdg/django/auth/middleware.py | sbutler/spacescout_builds | train | 0 |
75976c5818ff223290bbf4e157ee1b3a66672853 | [
"self.directory = directory\nself.config_file = os.path.join(self.directory, TRIAL_YAML)\nif not os.path.isdir(directory):\n logging.fatal(f'trial directory {self.directory} not found')\n exit(1)\nif not os.path.isfile(self.config_file):\n logging.fatal(f'config file {self.config_file} not found')\n exi... | <|body_start_0|>
self.directory = directory
self.config_file = os.path.join(self.directory, TRIAL_YAML)
if not os.path.isdir(directory):
logging.fatal(f'trial directory {self.directory} not found')
exit(1)
if not os.path.isfile(self.config_file):
loggi... | Data structure to hold the trial config and its experiment objects | Trial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trial:
"""Data structure to hold the trial config and its experiment objects"""
def __init__(self, directory):
"""Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the config file expected in the directory"""
<|body_0|>... | stack_v2_sparse_classes_36k_train_004398 | 2,211 | no_license | [
{
"docstring": "Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the config file expected in the directory",
"name": "__init__",
"signature": "def __init__(self, directory)"
},
{
"docstring": "Will compare output files against a regressio... | 2 | stack_v2_sparse_classes_30k_train_021371 | Implement the Python class `Trial` described below.
Class description:
Data structure to hold the trial config and its experiment objects
Method signatures and docstrings:
- def __init__(self, directory): Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the co... | Implement the Python class `Trial` described below.
Class description:
Data structure to hold the trial config and its experiment objects
Method signatures and docstrings:
- def __init__(self, directory): Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the co... | f8fde00f69a4e3d8d4cf113dbb8f3f8db5e498d5 | <|skeleton|>
class Trial:
"""Data structure to hold the trial config and its experiment objects"""
def __init__(self, directory):
"""Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the config file expected in the directory"""
<|body_0|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trial:
"""Data structure to hold the trial config and its experiment objects"""
def __init__(self, directory):
"""Construct the trial and its experiment objects :param directory: for the trial :param config_file: name of the config file expected in the directory"""
self.directory = direct... | the_stack_v2_python_sparse | src/trial.py | trubens71/verde | train | 0 |
f4cc49a6153b9d5fda25a7386ea34942d3d96557 | [
"sql = \"\\n SELECT name, SUM(scount) FROM\\n (SELECT sf.name, COUNT(si.server_id) scount FROM\\n cmdb.cmdb_installedsoftlist si, cmdb.cmdb_basesofttype st, cmdb.cmdb_basesoft sf\\n WHERE si.soft_id = sf.id AND sf.type_id = st.id AND st.name in ('操作系统','OS')\\n... | <|body_start_0|>
sql = "\n SELECT name, SUM(scount) FROM\n (SELECT sf.name, COUNT(si.server_id) scount FROM\n cmdb.cmdb_installedsoftlist si, cmdb.cmdb_basesofttype st, cmdb.cmdb_basesoft sf\n WHERE si.soft_id = sf.id AND sf.type_id = st.id AND st.name in (... | HostManage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HostManage:
def os_group_count(self, custid=None):
"""获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:"""
<|body_0|>
def month_group_count(self, month_value_dict, custid=None):
"""获取当前月份以及之前12月内所有设备数量统计 :param custid:客户id :param month_value_dict: 要显示的所有月记录初始列表[{'201... | stack_v2_sparse_classes_36k_train_004399 | 7,277 | permissive | [
{
"docstring": "获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:",
"name": "os_group_count",
"signature": "def os_group_count(self, custid=None)"
},
{
"docstring": "获取当前月份以及之前12月内所有设备数量统计 :param custid:客户id :param month_value_dict: 要显示的所有月记录初始列表[{'2016-12':0},{'2016-11':0},.....] :return:",
... | 2 | stack_v2_sparse_classes_30k_train_010551 | Implement the Python class `HostManage` described below.
Class description:
Implement the HostManage class.
Method signatures and docstrings:
- def os_group_count(self, custid=None): 获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:
- def month_group_count(self, month_value_dict, custid=None): 获取当前月份以及之前12月内所有设备数量统计 ... | Implement the Python class `HostManage` described below.
Class description:
Implement the HostManage class.
Method signatures and docstrings:
- def os_group_count(self, custid=None): 获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:
- def month_group_count(self, month_value_dict, custid=None): 获取当前月份以及之前12月内所有设备数量统计 ... | 002f80dcc07e3502610b0a0be1e91fe61bcfc42c | <|skeleton|>
class HostManage:
def os_group_count(self, custid=None):
"""获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:"""
<|body_0|>
def month_group_count(self, month_value_dict, custid=None):
"""获取当前月份以及之前12月内所有设备数量统计 :param custid:客户id :param month_value_dict: 要显示的所有月记录初始列表[{'201... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HostManage:
def os_group_count(self, custid=None):
"""获取主机的报表数据,通过操作系统进行分类 :param custid: 客户id :return:"""
sql = "\n SELECT name, SUM(scount) FROM\n (SELECT sf.name, COUNT(si.server_id) scount FROM\n cmdb.cmdb_installedsoftlist si, cmdb.cmdb_basesofttype... | the_stack_v2_python_sparse | cmdb/afcat/cmdb/custmanage.py | tonglinge/MyProjects | train | 4 |
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