blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
d2f3d49bf5f78ff8cb305248996145feb19f8f8a | [
"commission_df = self.capital.commission.commission_df\ncommission_df['commission'] = commission_df.commission.astype(float)\ncommission_df['cumsum'] = commission_df.commission.cumsum()\n'\\n eg:\\n type\\tdate\\tsymbol\\tcommission\\tcumsum\\n 0\\tbuy\\t20141024\\tusAAPL\\t19.0... | <|body_start_0|>
commission_df = self.capital.commission.commission_df
commission_df['commission'] = commission_df.commission.astype(float)
commission_df['cumsum'] = commission_df.commission.cumsum()
'\n eg:\n type\tdate\tsymbol\tcommission\tcumsum\n ... | 扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission() | MetricsDemo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetricsDemo:
"""扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission()"""
def _metrics_extend_stats(self):
"""子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比"""
<|body_0|>
def plot_commission(self):
""... | stack_v2_sparse_classes_10k_train_007800 | 27,337 | permissive | [
{
"docstring": "子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比",
"name": "_metrics_extend_stats",
"signature": "def _metrics_extend_stats(self)"
},
{
"docstring": "使用计算好的首先费cumsum序列和策略收益cumsum序列进行可视化对比 可视化收益曲线和手续费曲线之前的关系",
"name": "plot_commission",
"signature": "def plot_c... | 2 | null | Implement the Python class `MetricsDemo` described below.
Class description:
扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission()
Method signatures and docstrings:
- def _metrics_extend_stats(self): 子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比
- def p... | Implement the Python class `MetricsDemo` described below.
Class description:
扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission()
Method signatures and docstrings:
- def _metrics_extend_stats(self): 子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比
- def p... | 2e5ab17f2d20deb3c68c927f6208ea89db7c639d | <|skeleton|>
class MetricsDemo:
"""扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission()"""
def _metrics_extend_stats(self):
"""子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比"""
<|body_0|>
def plot_commission(self):
""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MetricsDemo:
"""扩展自定义度量类示例 eg: metrics = MetricsDemo(*abu_result_tuple) metrics.fit_metrics() metrics.plot_commission()"""
def _metrics_extend_stats(self):
"""子类可扩展的metrics方法，子类在此方法中可定义自己需要度量的值: 本demo示例交易手续费和策略收益之间的度量对比"""
commission_df = self.capital.commission.commission_df
comm... | the_stack_v2_python_sparse | abupy/MetricsBu/ABuMetricsBase.py | luqin/firefly | train | 1 |
93c94f963dd159afc1f0022f299cde4d76d96c02 | [
"base_env = _DiscreteEnvironmentOneReward(action_dtype=np.int64, reward_spec=specs.Array(dtype=np.float32, shape=()))\nwrapped_env = wrappers.DelayedRewardWrapper(base_env, accumulation_period=1)\nbase_episode_reward = _episode_reward(base_env)\nwrapped_episode_reward = _episode_reward(wrapped_env)\nself.assertEqua... | <|body_start_0|>
base_env = _DiscreteEnvironmentOneReward(action_dtype=np.int64, reward_spec=specs.Array(dtype=np.float32, shape=()))
wrapped_env = wrappers.DelayedRewardWrapper(base_env, accumulation_period=1)
base_episode_reward = _episode_reward(base_env)
wrapped_episode_reward = _epi... | DelayedRewardTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DelayedRewardTest:
def test_noop(self):
"""Ensure when accumulation_period=1 it does not change anything."""
<|body_0|>
def test_noop_composite_reward(self):
"""No-op test with composite rewards."""
<|body_1|>
def test_same_episode_composite_reward(self,... | stack_v2_sparse_classes_10k_train_007801 | 3,312 | permissive | [
{
"docstring": "Ensure when accumulation_period=1 it does not change anything.",
"name": "test_noop",
"signature": "def test_noop(self)"
},
{
"docstring": "No-op test with composite rewards.",
"name": "test_noop_composite_reward",
"signature": "def test_noop_composite_reward(self)"
},
... | 3 | stack_v2_sparse_classes_30k_train_000031 | Implement the Python class `DelayedRewardTest` described below.
Class description:
Implement the DelayedRewardTest class.
Method signatures and docstrings:
- def test_noop(self): Ensure when accumulation_period=1 it does not change anything.
- def test_noop_composite_reward(self): No-op test with composite rewards.
-... | Implement the Python class `DelayedRewardTest` described below.
Class description:
Implement the DelayedRewardTest class.
Method signatures and docstrings:
- def test_noop(self): Ensure when accumulation_period=1 it does not change anything.
- def test_noop_composite_reward(self): No-op test with composite rewards.
-... | 97c50eaa62c039d8f4b9efa3e80c4d80e6f40c4c | <|skeleton|>
class DelayedRewardTest:
def test_noop(self):
"""Ensure when accumulation_period=1 it does not change anything."""
<|body_0|>
def test_noop_composite_reward(self):
"""No-op test with composite rewards."""
<|body_1|>
def test_same_episode_composite_reward(self,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DelayedRewardTest:
def test_noop(self):
"""Ensure when accumulation_period=1 it does not change anything."""
base_env = _DiscreteEnvironmentOneReward(action_dtype=np.int64, reward_spec=specs.Array(dtype=np.float32, shape=()))
wrapped_env = wrappers.DelayedRewardWrapper(base_env, accumu... | the_stack_v2_python_sparse | acme/wrappers/delayed_reward_test.py | RaoulDrake/acme | train | 0 | |
eb203bc93476b7b993df8e1b31c573a6242be77d | [
"sum_1 = 0\nstack = []\nfor i, h in enumerate(height):\n if not stack and h == 0:\n continue\n elif not stack or stack[-1][-1] > h:\n stack.append([i, h])\n else:\n lists = []\n while stack and stack[-1][-1] <= h:\n lists.append(stack.pop())\n if not stack:\n ... | <|body_start_0|>
sum_1 = 0
stack = []
for i, h in enumerate(height):
if not stack and h == 0:
continue
elif not stack or stack[-1][-1] > h:
stack.append([i, h])
else:
lists = []
while stack and st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 68ms"""
<|body_0|>
def trap_1(self, height):
""":type height: List[int] :rtype: int 59ms"""
<|body_1|>
def trap_2(self, height):
""":type height: List[int] :rtype: int 49ms"... | stack_v2_sparse_classes_10k_train_007802 | 2,988 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int 68ms",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int 59ms",
"name": "trap_1",
"signature": "def trap_1(self, height)"
},
{
"docstring": ":type height: List[int] :rty... | 3 | 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 68ms
- def trap_1(self, height): :type height: List[int] :rtype: int 59ms
- def trap_2(self, height): :type height: Li... | 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 68ms
- def trap_1(self, height): :type height: List[int] :rtype: int 59ms
- def trap_2(self, height): :type height: Li... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 68ms"""
<|body_0|>
def trap_1(self, height):
""":type height: List[int] :rtype: int 59ms"""
<|body_1|>
def trap_2(self, height):
""":type height: List[int] :rtype: int 49ms"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int 68ms"""
sum_1 = 0
stack = []
for i, h in enumerate(height):
if not stack and h == 0:
continue
elif not stack or stack[-1][-1] > h:
stack.append([i, h... | the_stack_v2_python_sparse | TrappingRainWater_HARD_42.py | 953250587/leetcode-python | train | 2 | |
419312cb8dc2220351eab71ae3594c7d722cba4b | [
"n_features = self.n_features\nplaceholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes)\nwith graph.as_default():\n with placeholder_scope:\n self.mol_features = tf.placeholder(tf.float32, shape=[None, n_features], name='mol_features')\n layer_sizes = self.layer_sizes\n weight_i... | <|body_start_0|>
n_features = self.n_features
placeholder_scope = TensorflowGraph.get_placeholder_scope(graph, name_scopes)
with graph.as_default():
with placeholder_scope:
self.mol_features = tf.placeholder(tf.float32, shape=[None, n_features], name='mol_features')
... | Implements an icml model as configured in a model_config.proto. | TensorflowMultiTaskRegressor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule d... | stack_v2_sparse_classes_10k_train_007803 | 32,492 | permissive | [
{
"docstring": "Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule descriptor (e.g. fingerprint) tensor with shape batch_size x n_features.",
"name": "build",
"signature": "def build(self, graph, name_scopes, training)"
... | 2 | stack_v2_sparse_classes_30k_train_000446 | Implement the Python class `TensorflowMultiTaskRegressor` described below.
Class description:
Implements an icml model as configured in a model_config.proto.
Method signatures and docstrings:
- def build(self, graph, name_scopes, training): Constructs the graph architecture as specified in its config. This method cre... | Implement the Python class `TensorflowMultiTaskRegressor` described below.
Class description:
Implements an icml model as configured in a model_config.proto.
Method signatures and docstrings:
- def build(self, graph, name_scopes, training): Constructs the graph architecture as specified in its config. This method cre... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TensorflowMultiTaskRegressor:
"""Implements an icml model as configured in a model_config.proto."""
def build(self, graph, name_scopes, training):
"""Constructs the graph architecture as specified in its config. This method creates the following Placeholders: mol_features: Molecule descriptor (e.... | the_stack_v2_python_sparse | contrib/atomicconv/models/legacy.py | deepchem/deepchem | train | 4,876 |
98146c796c1d61f4f9a8de0d548ecabe5c3284b9 | [
"super(NeRFNetwork, self).__init__()\nself.device = device\nself.in_dim = in_dim\nself.hidden_dim = hidden_dim\nself.rgb_dim = rgb_dim\nself.style_dim = style_dim\nself.hidden_layers = hidden_layers\nself.name_prefix = name_prefix\nself.style_dim_dict = {}\nself.network = nn.ModuleList()\n_out_dim = in_dim\nfor idx... | <|body_start_0|>
super(NeRFNetwork, self).__init__()
self.device = device
self.in_dim = in_dim
self.hidden_dim = hidden_dim
self.rgb_dim = rgb_dim
self.style_dim = style_dim
self.hidden_layers = hidden_layers
self.name_prefix = name_prefix
self.sty... | Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1 | NeRFNetwork_Small | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeRFNetwork_Small:
"""Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1"""
def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix='nerf', **kwargs):
""":param z_dim: :param hidden_dim: :para... | stack_v2_sparse_classes_10k_train_007804 | 22,624 | permissive | [
{
"docstring": ":param z_dim: :param hidden_dim: :param rgb_dim: :param device: :param kwargs:",
"name": "__init__",
"signature": "def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix='nerf', **kwargs)"
},
{
"docstring": ":param input: ... | 2 | stack_v2_sparse_classes_30k_train_001258 | Implement the Python class `NeRFNetwork_Small` described below.
Class description:
Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1
Method signatures and docstrings:
- def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix=... | Implement the Python class `NeRFNetwork_Small` described below.
Class description:
Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1
Method signatures and docstrings:
- def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix=... | 9244193048c73f55270d2df28fb160f42d5953ad | <|skeleton|>
class NeRFNetwork_Small:
"""Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1"""
def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix='nerf', **kwargs):
""":param z_dim: :param hidden_dim: :para... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NeRFNetwork_Small:
"""Same architecture as TALLSIREN but adds a UniformBoxWarp to map input points to -1, 1"""
def __init__(self, in_dim=3, hidden_dim=256, rgb_dim=3, style_dim=512, hidden_layers=2, device=None, name_prefix='nerf', **kwargs):
""":param z_dim: :param hidden_dim: :param rgb_dim: :p... | the_stack_v2_python_sparse | exp/comm/models/nerf_network.py | tonywork/CIPS-3D | train | 0 |
5f5a88a059fd3d6df54ff8a0e4454da822710f3d | [
"super().__init__(self.PARAMS, parameters)\nself.column_order = parameters['column_order']\nself.ignore_missing = parameters['ignore_missing']\nself.keep_others = parameters['keep_others']",
"df_new = df.copy()\ncurrent_columns = list(df_new.columns)\nmissing_columns = set(self.column_order).difference(set(df_new... | <|body_start_0|>
super().__init__(self.PARAMS, parameters)
self.column_order = parameters['column_order']
self.ignore_missing = parameters['ignore_missing']
self.keep_others = parameters['keep_others']
<|end_body_0|>
<|body_start_1|>
df_new = df.copy()
current_columns = ... | Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): If true, columns not in column_order are placed at end. | ReorderColumnsOp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReorderColumnsOp:
"""Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): If true, columns not in column_order are... | stack_v2_sparse_classes_10k_train_007805 | 2,847 | permissive | [
{
"docstring": "Constructor for reorder columns operation. Parameters: parameters (dict): Dictionary with the parameter values for required and optional parameters. :raises KeyError: - If a required parameter is missing. - If an unexpected parameter is provided. :raises TypeError: - If a parameter has the wrong... | 2 | stack_v2_sparse_classes_30k_train_004021 | Implement the Python class `ReorderColumnsOp` described below.
Class description:
Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): I... | Implement the Python class `ReorderColumnsOp` described below.
Class description:
Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): I... | b871cae44bdf0ee68c688562c3b0af50b93343f5 | <|skeleton|>
class ReorderColumnsOp:
"""Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): If true, columns not in column_order are... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ReorderColumnsOp:
"""Reorder columns in a tabular file. Required parameters: column_order (*list*): The names of the columns to be reordered. ignore_missing (*bool*): If false and a column in column_order is not in df, skip the column keep_others (*bool*): If true, columns not in column_order are placed at en... | the_stack_v2_python_sparse | hed/tools/remodeling/operations/reorder_columns_op.py | hed-standard/hed-python | train | 5 |
8776a9446a8a462749edef1bf6a99285c3096a2b | [
"for label, item in cls.labels.items():\n if item == cls:\n return label\nraise NotImplementedError(f'Class {cls} is not implemented.')",
"def decorator(obj):\n if label in cls.labels:\n print(f\"registering duplicate label '{label}' for {cls.__name__}.\")\n cls.labels[label] = obj\n ret... | <|body_start_0|>
for label, item in cls.labels.items():
if item == cls:
return label
raise NotImplementedError(f'Class {cls} is not implemented.')
<|end_body_0|>
<|body_start_1|>
def decorator(obj):
if label in cls.labels:
print(f"register... | CustomABC | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomABC:
def get_label(cls):
"""Returns the string label of a class object."""
<|body_0|>
def register(cls, label):
"""Decorator to register new classes."""
<|body_1|>
def __class_getitem__(cls, item):
"""Returns the child."""
<|body_2|... | stack_v2_sparse_classes_10k_train_007806 | 912 | permissive | [
{
"docstring": "Returns the string label of a class object.",
"name": "get_label",
"signature": "def get_label(cls)"
},
{
"docstring": "Decorator to register new classes.",
"name": "register",
"signature": "def register(cls, label)"
},
{
"docstring": "Returns the child.",
"na... | 3 | stack_v2_sparse_classes_30k_train_006880 | Implement the Python class `CustomABC` described below.
Class description:
Implement the CustomABC class.
Method signatures and docstrings:
- def get_label(cls): Returns the string label of a class object.
- def register(cls, label): Decorator to register new classes.
- def __class_getitem__(cls, item): Returns the c... | Implement the Python class `CustomABC` described below.
Class description:
Implement the CustomABC class.
Method signatures and docstrings:
- def get_label(cls): Returns the string label of a class object.
- def register(cls, label): Decorator to register new classes.
- def __class_getitem__(cls, item): Returns the c... | 29f37740bacc9a77b94daf6fbae769c003ee9349 | <|skeleton|>
class CustomABC:
def get_label(cls):
"""Returns the string label of a class object."""
<|body_0|>
def register(cls, label):
"""Decorator to register new classes."""
<|body_1|>
def __class_getitem__(cls, item):
"""Returns the child."""
<|body_2|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CustomABC:
def get_label(cls):
"""Returns the string label of a class object."""
for label, item in cls.labels.items():
if item == cls:
return label
raise NotImplementedError(f'Class {cls} is not implemented.')
def register(cls, label):
"""Decor... | the_stack_v2_python_sparse | profit/util/base_class.py | redmod-team/profit | train | 19 | |
df41760ce3fc0766e3850579bba67334c61f428b | [
"stops = set(stopwords.words('english'))\nstops.update(set(punctuation))\nself.stops = stops",
"text = text.lower()\ntext = re.sub('\\\\. \\\\. \\\\.', '\\\\.', text)\ntext = re.sub(\"[^A-Za-z0-9(),!?\\\\'\\\\`\\\\.]\", ' ', text)\ntext = re.sub('[0-9]+', '', text)\ntext = re.sub(\"\\\\'s\", \" 's\", text)\ntext ... | <|body_start_0|>
stops = set(stopwords.words('english'))
stops.update(set(punctuation))
self.stops = stops
<|end_body_0|>
<|body_start_1|>
text = text.lower()
text = re.sub('\\. \\. \\.', '\\.', text)
text = re.sub("[^A-Za-z0-9(),!?\\'\\`\\.]", ' ', text)
text = ... | TextCleaning | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextCleaning:
def __init__(self):
"""Define Your stop word List here"""
<|body_0|>
def text_cleaning(self, text):
"""Define your Text Cleaning Rules here"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
stops = set(stopwords.words('english'))
... | stack_v2_sparse_classes_10k_train_007807 | 4,058 | permissive | [
{
"docstring": "Define Your stop word List here",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Define your Text Cleaning Rules here",
"name": "text_cleaning",
"signature": "def text_cleaning(self, text)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004502 | Implement the Python class `TextCleaning` described below.
Class description:
Implement the TextCleaning class.
Method signatures and docstrings:
- def __init__(self): Define Your stop word List here
- def text_cleaning(self, text): Define your Text Cleaning Rules here | Implement the Python class `TextCleaning` described below.
Class description:
Implement the TextCleaning class.
Method signatures and docstrings:
- def __init__(self): Define Your stop word List here
- def text_cleaning(self, text): Define your Text Cleaning Rules here
<|skeleton|>
class TextCleaning:
def __ini... | b4883024da899f7e921583bd0b4fb952f53914cb | <|skeleton|>
class TextCleaning:
def __init__(self):
"""Define Your stop word List here"""
<|body_0|>
def text_cleaning(self, text):
"""Define your Text Cleaning Rules here"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TextCleaning:
def __init__(self):
"""Define Your stop word List here"""
stops = set(stopwords.words('english'))
stops.update(set(punctuation))
self.stops = stops
def text_cleaning(self, text):
"""Define your Text Cleaning Rules here"""
text = text.lower()
... | the_stack_v2_python_sparse | common/utils/utils.py | anishacharya/NLP-CS388-UT | train | 2 | |
02487ae040fbe9a689f5ace0bfb461e9690e605b | [
"super(Organization, self).__init__(resource_id=organization_id, resource_type=resource.ResourceType.ORGANIZATION, name=name, display_name=display_name, lifecycle_state=lifecycle_state)\nself.full_name = full_name\nself.data = data",
"del parent\norg_dict = json.loads(json_string)\norg_name = org_dict['name']\nor... | <|body_start_0|>
super(Organization, self).__init__(resource_id=organization_id, resource_type=resource.ResourceType.ORGANIZATION, name=name, display_name=display_name, lifecycle_state=lifecycle_state)
self.full_name = full_name
self.data = data
<|end_body_0|>
<|body_start_1|>
del paren... | Organization resource. | Organization | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Organization:
"""Organization resource."""
def __init__(self, organization_id, full_name=None, data=None, name=None, display_name=None, lifecycle_state=OrgLifecycleState.UNSPECIFIED):
"""Initialize. Args: organization_id (int): The organization id. full_name (str): The full resource ... | stack_v2_sparse_classes_10k_train_007808 | 3,000 | permissive | [
{
"docstring": "Initialize. Args: organization_id (int): The organization id. full_name (str): The full resource name and ancestory. data (str): Resource representation of the organization. name (str): The organization's unique GCP name, with the format \"organizations/{id}\". display_name (str): The organizati... | 2 | stack_v2_sparse_classes_30k_train_004683 | Implement the Python class `Organization` described below.
Class description:
Organization resource.
Method signatures and docstrings:
- def __init__(self, organization_id, full_name=None, data=None, name=None, display_name=None, lifecycle_state=OrgLifecycleState.UNSPECIFIED): Initialize. Args: organization_id (int):... | Implement the Python class `Organization` described below.
Class description:
Organization resource.
Method signatures and docstrings:
- def __init__(self, organization_id, full_name=None, data=None, name=None, display_name=None, lifecycle_state=OrgLifecycleState.UNSPECIFIED): Initialize. Args: organization_id (int):... | d4421afa50a17ed47cbebe942044ebab3720e0f5 | <|skeleton|>
class Organization:
"""Organization resource."""
def __init__(self, organization_id, full_name=None, data=None, name=None, display_name=None, lifecycle_state=OrgLifecycleState.UNSPECIFIED):
"""Initialize. Args: organization_id (int): The organization id. full_name (str): The full resource ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Organization:
"""Organization resource."""
def __init__(self, organization_id, full_name=None, data=None, name=None, display_name=None, lifecycle_state=OrgLifecycleState.UNSPECIFIED):
"""Initialize. Args: organization_id (int): The organization id. full_name (str): The full resource name and ance... | the_stack_v2_python_sparse | google/cloud/forseti/common/gcp_type/organization.py | kevensen/forseti-security | train | 1 |
474494ce13b5e3f8aa507558a741d146df6d4982 | [
"urls = super().get_urls()\nnew_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('export-elastic/', ElasticActions.export_to_elastic)]\nreturn new_urls + urls",
"if request.method == 'POST':\n csv_file = request.FILES['importer_un_fichier']\n if not ... | <|body_start_0|>
urls = super().get_urls()
new_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('export-elastic/', ElasticActions.export_to_elastic)]
return new_urls + urls
<|end_body_0|>
<|body_start_1|>
if request.method == 'PO... | Modèle de l'administration des structures | StructureAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructureAdmin:
"""Modèle de l'administration des structures"""
def get_urls(self):
"""Initialise les urls du modèle StructureAdmin"""
<|body_0|>
def upload_csv(request):
"""Permet de charger un fichier CSV dans la base de données du modèle Structure"""
<... | stack_v2_sparse_classes_10k_train_007809 | 12,279 | no_license | [
{
"docstring": "Initialise les urls du modèle StructureAdmin",
"name": "get_urls",
"signature": "def get_urls(self)"
},
{
"docstring": "Permet de charger un fichier CSV dans la base de données du modèle Structure",
"name": "upload_csv",
"signature": "def upload_csv(request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003218 | Implement the Python class `StructureAdmin` described below.
Class description:
Modèle de l'administration des structures
Method signatures and docstrings:
- def get_urls(self): Initialise les urls du modèle StructureAdmin
- def upload_csv(request): Permet de charger un fichier CSV dans la base de données du modèle S... | Implement the Python class `StructureAdmin` described below.
Class description:
Modèle de l'administration des structures
Method signatures and docstrings:
- def get_urls(self): Initialise les urls du modèle StructureAdmin
- def upload_csv(request): Permet de charger un fichier CSV dans la base de données du modèle S... | 0471d2de17597d97f3209099aff3edc72d615fa2 | <|skeleton|>
class StructureAdmin:
"""Modèle de l'administration des structures"""
def get_urls(self):
"""Initialise les urls du modèle StructureAdmin"""
<|body_0|>
def upload_csv(request):
"""Permet de charger un fichier CSV dans la base de données du modèle Structure"""
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class StructureAdmin:
"""Modèle de l'administration des structures"""
def get_urls(self):
"""Initialise les urls du modèle StructureAdmin"""
urls = super().get_urls()
new_urls = [path('upload-csv/', self.upload_csv), path('update_elastic/', ElasticActions.update_elastic), path('export-e... | the_stack_v2_python_sparse | elasticHal/admin.py | Patent2net/SoVisu | train | 1 |
0101cb4e170a8d168a24134fee231c0d44274d44 | [
"LOG.debug('Plug or unplug networks for amphora id: %s', amphora[constants.ID])\nif not delta:\n LOG.debug('No network deltas for amphora id: %s', amphora[constants.ID])\n return\nfor nic in delta[constants.ADD_NICS]:\n self.network_driver.plug_network(amphora[constants.COMPUTE_ID], nic[constants.NETWORK_I... | <|body_start_0|>
LOG.debug('Plug or unplug networks for amphora id: %s', amphora[constants.ID])
if not delta:
LOG.debug('No network deltas for amphora id: %s', amphora[constants.ID])
return
for nic in delta[constants.ADD_NICS]:
self.network_driver.plug_network... | Task to plug the networks. This uses the delta to add all missing networks/nics | PlugNetworks | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlugNetworks:
"""Task to plug the networks. This uses the delta to add all missing networks/nics"""
def execute(self, amphora, delta):
"""Update the amphora networks for the delta."""
<|body_0|>
def revert(self, amphora, delta, *args, **kwargs):
"""Handle a faile... | stack_v2_sparse_classes_10k_train_007810 | 44,034 | permissive | [
{
"docstring": "Update the amphora networks for the delta.",
"name": "execute",
"signature": "def execute(self, amphora, delta)"
},
{
"docstring": "Handle a failed network plug by removing all nics added.",
"name": "revert",
"signature": "def revert(self, amphora, delta, *args, **kwargs)... | 2 | null | Implement the Python class `PlugNetworks` described below.
Class description:
Task to plug the networks. This uses the delta to add all missing networks/nics
Method signatures and docstrings:
- def execute(self, amphora, delta): Update the amphora networks for the delta.
- def revert(self, amphora, delta, *args, **kw... | Implement the Python class `PlugNetworks` described below.
Class description:
Task to plug the networks. This uses the delta to add all missing networks/nics
Method signatures and docstrings:
- def execute(self, amphora, delta): Update the amphora networks for the delta.
- def revert(self, amphora, delta, *args, **kw... | 0426285a41464a5015494584f109eed35a0d44db | <|skeleton|>
class PlugNetworks:
"""Task to plug the networks. This uses the delta to add all missing networks/nics"""
def execute(self, amphora, delta):
"""Update the amphora networks for the delta."""
<|body_0|>
def revert(self, amphora, delta, *args, **kwargs):
"""Handle a faile... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PlugNetworks:
"""Task to plug the networks. This uses the delta to add all missing networks/nics"""
def execute(self, amphora, delta):
"""Update the amphora networks for the delta."""
LOG.debug('Plug or unplug networks for amphora id: %s', amphora[constants.ID])
if not delta:
... | the_stack_v2_python_sparse | octavia/controller/worker/v2/tasks/network_tasks.py | openstack/octavia | train | 147 |
aa6953f701a6695492254eaf213c58ed26689ed6 | [
"sexy.IconEntry.__init__(self)\nself.__gobject_init__()\nself._handler_changed = self.connect_after('changed', self._on_changed)\nself.connect('icon-pressed', self._on_icon_pressed)\nimage = gtk.Image()\npixbuf = icon_theme.load_icon(gtk.STOCK_CLEAR, gtk.ICON_SIZE_MENU, 0)\nimage.set_from_pixbuf(pixbuf)\nself.set_i... | <|body_start_0|>
sexy.IconEntry.__init__(self)
self.__gobject_init__()
self._handler_changed = self.connect_after('changed', self._on_changed)
self.connect('icon-pressed', self._on_icon_pressed)
image = gtk.Image()
pixbuf = icon_theme.load_icon(gtk.STOCK_CLEAR, gtk.ICON_S... | SearchEntry | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SearchEntry:
def __init__(self, icon_theme):
"""Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active"""
<|body_0|>
def _on_icon_pressed(self, widget, icon, mouse_button):
"""Emit the terms... | stack_v2_sparse_classes_10k_train_007811 | 4,000 | no_license | [
{
"docstring": "Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active",
"name": "__init__",
"signature": "def __init__(self, icon_theme)"
},
{
"docstring": "Emit the terms-changed signal without any time out when the c... | 4 | stack_v2_sparse_classes_30k_train_000785 | Implement the Python class `SearchEntry` described below.
Class description:
Implement the SearchEntry class.
Method signatures and docstrings:
- def __init__(self, icon_theme): Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active
- def _o... | Implement the Python class `SearchEntry` described below.
Class description:
Implement the SearchEntry class.
Method signatures and docstrings:
- def __init__(self, icon_theme): Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active
- def _o... | d08f7bf370a82b6970387bb9f165d374a9d9092b | <|skeleton|>
class SearchEntry:
def __init__(self, icon_theme):
"""Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active"""
<|body_0|>
def _on_icon_pressed(self, widget, icon, mouse_button):
"""Emit the terms... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SearchEntry:
def __init__(self, icon_theme):
"""Creates an enhanced IconEntry that supports a time out when typing and uses a different background colour when the search is active"""
sexy.IconEntry.__init__(self)
self.__gobject_init__()
self._handler_changed = self.connect_afte... | the_stack_v2_python_sparse | usr/share/pyshared/AppInstall/widgets/SearchEntry.py | haniokasai/netwalker-rootfs | train | 2 | |
59b7ed8442af60c91213b2cc65e3be37dcd03031 | [
"if len(matrix) == 0 or len(matrix[0]) == 0:\n return\nlength = len(matrix)\nwidth = len(matrix[0])\nself.cache = [[0] * (width + 1) for i in range(length)]\nfor i in range(length):\n for j in range(width):\n self.cache[i][j + 1] = self.cache[i][j] + matrix[i][j]",
"res = 0\nfor i in range(row1, row2... | <|body_start_0|>
if len(matrix) == 0 or len(matrix[0]) == 0:
return
length = len(matrix)
width = len(matrix[0])
self.cache = [[0] * (width + 1) for i in range(length)]
for i in range(length):
for j in range(width):
self.cache[i][j + 1] = se... | 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_10k_train_007812 | 929 | 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_train_001945 | 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:... | 48196dedf60076bbc3769e067f1ecbaa36ca0b5f | <|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_10k | data/stack_v2_sparse_classes_30k | class NumMatrix:
def __init__(self, matrix):
""":type matrix: List[List[int]]"""
if len(matrix) == 0 or len(matrix[0]) == 0:
return
length = len(matrix)
width = len(matrix[0])
self.cache = [[0] * (width + 1) for i in range(length)]
for i in range(length):
... | the_stack_v2_python_sparse | Range Sum Query 2D - Immutable.py | xukaiyuan/leetcode-medium | train | 0 | |
91241417e91b8a06b56036d2f108d1473c1acd95 | [
"super().__init__(fmc, **kwargs)\nlogging.debug('In __init__() for DNSServerGroups class.')\nself.parse_kwargs(**kwargs)\nself.type = 'DNSServerGroupObject'",
"logging.debug('In servers() for DNSServerGroups class.')\nif action == 'add':\n for name_server in name_servers:\n if 'dnsservers' in self.__dic... | <|body_start_0|>
super().__init__(fmc, **kwargs)
logging.debug('In __init__() for DNSServerGroups class.')
self.parse_kwargs(**kwargs)
self.type = 'DNSServerGroupObject'
<|end_body_0|>
<|body_start_1|>
logging.debug('In servers() for DNSServerGroups class.')
if action ==... | The DNSServerGroups Object in the FMC. | DNSServerGroups | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DNSServerGroups:
"""The DNSServerGroups Object in the FMC."""
def __init__(self, fmc, **kwargs):
"""Initialize DNSServerGroups object. Set self.type to "DNSServerGroupObject" and parse the kwargs. :param fmc: (object) FMC object :param kwargs: Any other values passed during instantia... | stack_v2_sparse_classes_10k_train_007813 | 2,479 | permissive | [
{
"docstring": "Initialize DNSServerGroups object. Set self.type to \"DNSServerGroupObject\" and parse the kwargs. :param fmc: (object) FMC object :param kwargs: Any other values passed during instantiation. :return: None",
"name": "__init__",
"signature": "def __init__(self, fmc, **kwargs)"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_002436 | Implement the Python class `DNSServerGroups` described below.
Class description:
The DNSServerGroups Object in the FMC.
Method signatures and docstrings:
- def __init__(self, fmc, **kwargs): Initialize DNSServerGroups object. Set self.type to "DNSServerGroupObject" and parse the kwargs. :param fmc: (object) FMC objec... | Implement the Python class `DNSServerGroups` described below.
Class description:
The DNSServerGroups Object in the FMC.
Method signatures and docstrings:
- def __init__(self, fmc, **kwargs): Initialize DNSServerGroups object. Set self.type to "DNSServerGroupObject" and parse the kwargs. :param fmc: (object) FMC objec... | fd924de96e200ca8e0d5088b27a5abaf6f915bc6 | <|skeleton|>
class DNSServerGroups:
"""The DNSServerGroups Object in the FMC."""
def __init__(self, fmc, **kwargs):
"""Initialize DNSServerGroups object. Set self.type to "DNSServerGroupObject" and parse the kwargs. :param fmc: (object) FMC object :param kwargs: Any other values passed during instantia... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DNSServerGroups:
"""The DNSServerGroups Object in the FMC."""
def __init__(self, fmc, **kwargs):
"""Initialize DNSServerGroups object. Set self.type to "DNSServerGroupObject" and parse the kwargs. :param fmc: (object) FMC object :param kwargs: Any other values passed during instantiation. :return... | the_stack_v2_python_sparse | fmcapi/api_objects/object_services/dnsservergroups.py | banzigaga/fmcapi | train | 1 |
5516452a231a947d42ced06ffa7d69be4605bd97 | [
"if len(nums) == 0:\n return 0\nmax_length = 1\nfor i in range(len(nums)):\n count = 1\n cur = nums[i]\n pre = None\n for j in range(i + 1, len(nums)):\n if cur < nums[j]:\n count += 1\n pre = cur\n cur = nums[j]\n elif cur > nums[j]:\n if pre... | <|body_start_0|>
if len(nums) == 0:
return 0
max_length = 1
for i in range(len(nums)):
count = 1
cur = nums[i]
pre = None
for j in range(i + 1, len(nums)):
if cur < nums[j]:
count += 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(nums) == 0:
return 0
... | stack_v2_sparse_classes_10k_train_007814 | 1,182 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "lengthOfLIS",
"signature": "def lengthOfLIS(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
- def lengthOfLIS(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def lengthOfLIS... | d8ed762d1005975f0de4f07760c9671195621c88 | <|skeleton|>
class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def lengthOfLIS(self, nums):
""":type nums: List[int] :rtype: int"""
if len(nums) == 0:
return 0
max_length = 1
for i in range(len(nums)):
count = 1
cur = nums[i]
pre = None
for j in range(i + 1, len(nums)):
... | the_stack_v2_python_sparse | longest-increasing-subsequence/solution.py | uxlsl/leetcode_practice | train | 0 | |
5517b21befbc475c798db26286b46a79e8f7b66b | [
"self.n = ZZ(n)\nself.m = m\nself.__i = 0\nself.K = IntegerModRing(q)\nself.FM = FreeModule(self.K, n)\nself.D = D\nself.secret_dist = secret_dist\nif secret_dist == 'uniform':\n self.__s = random_vector(self.K, self.n)\nelif secret_dist == 'noise':\n self.__s = vector(self.K, self.n, [self.D() for _ in range... | <|body_start_0|>
self.n = ZZ(n)
self.m = m
self.__i = 0
self.K = IntegerModRing(q)
self.FM = FreeModule(self.K, n)
self.D = D
self.secret_dist = secret_dist
if secret_dist == 'uniform':
self.__s = random_vector(self.K, self.n)
elif secr... | Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__ | LWE | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LWE:
"""Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__"""
def __init__(self, n, q, D, secret_dist='uniform', m=None):
"""Construct an LWE oracle in dimension ``n`` over a ring of order ``q`` with noise distribution ``D``. INPUT: - ``n`` - dimensi... | stack_v2_sparse_classes_10k_train_007815 | 31,769 | no_license | [
{
"docstring": "Construct an LWE oracle in dimension ``n`` over a ring of order ``q`` with noise distribution ``D``. INPUT: - ``n`` - dimension (integer > 0) - ``q`` - modulus typically > n (integer > 0) - ``D`` - an error distribution such as an instance of :class:`DiscreteGaussianDistributionIntegerSampler` o... | 3 | null | Implement the Python class `LWE` described below.
Class description:
Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__
Method signatures and docstrings:
- def __init__(self, n, q, D, secret_dist='uniform', m=None): Construct an LWE oracle in dimension ``n`` over a ring of order ``q`... | Implement the Python class `LWE` described below.
Class description:
Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__
Method signatures and docstrings:
- def __init__(self, n, q, D, secret_dist='uniform', m=None): Construct an LWE oracle in dimension ``n`` over a ring of order ``q`... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class LWE:
"""Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__"""
def __init__(self, n, q, D, secret_dist='uniform', m=None):
"""Construct an LWE oracle in dimension ``n`` over a ring of order ``q`` with noise distribution ``D``. INPUT: - ``n`` - dimensi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LWE:
"""Learning with Errors (LWE) oracle. .. automethod:: __init__ .. automethod:: __call__"""
def __init__(self, n, q, D, secret_dist='uniform', m=None):
"""Construct an LWE oracle in dimension ``n`` over a ring of order ``q`` with noise distribution ``D``. INPUT: - ``n`` - dimension (integer >... | the_stack_v2_python_sparse | sage/src/sage/crypto/lwe.py | bopopescu/geosci | train | 0 |
052a09159bd663e80b96e8d6a2d98efed53b1ae7 | [
"lowest = float('inf')\nmaxc = 0\nfor i in xrange(1, len(prices)):\n lowest = min(lowest, prices[i - 1])\n maxc = max(maxc, prices[i] - lowest)\nreturn maxc",
"local_max = 0\nmmax = 0\nfor i in xrange(1, len(prices)):\n local_max += prices[i] - prices[i - 1]\n local_max = max(0, local_max)\n mmax =... | <|body_start_0|>
lowest = float('inf')
maxc = 0
for i in xrange(1, len(prices)):
lowest = min(lowest, prices[i - 1])
maxc = max(maxc, prices[i] - lowest)
return maxc
<|end_body_0|>
<|body_start_1|>
local_max = 0
mmax = 0
for i in xrange(1,... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit_2(self, prices):
""":type prices: List[int] :rtype: int kadane algorithm 利用差具有累加性的特性."""
<|body_1|>
def rewrite(self, prices):
""":type pric... | stack_v2_sparse_classes_10k_train_007816 | 2,506 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int kadane algorithm 利用差具有累加性的特性.",
"name": "maxProfit_2",
"signature": "def maxProfit_2(self, prices)"
},
{
"d... | 3 | stack_v2_sparse_classes_30k_train_002173 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit_2(self, prices): :type prices: List[int] :rtype: int kadane algorithm 利用差具有累加性的特性.
- def rewrite(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit_2(self, prices): :type prices: List[int] :rtype: int kadane algorithm 利用差具有累加性的特性.
- def rewrite(... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit_2(self, prices):
""":type prices: List[int] :rtype: int kadane algorithm 利用差具有累加性的特性."""
<|body_1|>
def rewrite(self, prices):
""":type pric... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
lowest = float('inf')
maxc = 0
for i in xrange(1, len(prices)):
lowest = min(lowest, prices[i - 1])
maxc = max(maxc, prices[i] - lowest)
return maxc
def maxProf... | the_stack_v2_python_sparse | co_fb/121_Best_Time_to_Buy_and_Sell_Stock.py | vsdrun/lc_public | train | 6 | |
97d7075e8c0b4ca6e0fdaf532815263357586f56 | [
"Win._load()\nbufferSize = (len(text) + 1) * 2\nhGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))\nlpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))\nWin.memcpy(lpGlobalMem, ctypes.c_wchar_p(text), ctypes.c_int(bufferSize))\nWin.GlobalUnlock(ctypes.c_int(hGlobalMem))\nif Win.OpenClipbo... | <|body_start_0|>
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))
lpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))
Win.memcpy(lpGlobalMem, ctypes.c_wchar_p(text), ctypes.c_int(bufferSize))
Win.Gl... | Exports | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
<|body_0|>
def clipboard_paste():
"""クリップボードからテキストをはり付ける"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.Global... | stack_v2_sparse_classes_10k_train_007817 | 2,348 | permissive | [
{
"docstring": "クリップボードにテキストをコピーする",
"name": "clipboard_copy",
"signature": "def clipboard_copy(text)"
},
{
"docstring": "クリップボードからテキストをはり付ける",
"name": "clipboard_paste",
"signature": "def clipboard_paste()"
}
] | 2 | stack_v2_sparse_classes_30k_train_004424 | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def clipboard_copy(text): クリップボードにテキストをコピーする
- def clipboard_paste(): クリップボードからテキストをはり付ける | Implement the Python class `Exports` described below.
Class description:
Implement the Exports class.
Method signatures and docstrings:
- def clipboard_copy(text): クリップボードにテキストをコピーする
- def clipboard_paste(): クリップボードからテキストをはり付ける
<|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"... | f3d89b4449b04e5e587915f3b3623dfbe5ba01d8 | <|skeleton|>
class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
<|body_0|>
def clipboard_paste():
"""クリップボードからテキストをはり付ける"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Exports:
def clipboard_copy(text):
"""クリップボードにテキストをコピーする"""
Win._load()
bufferSize = (len(text) + 1) * 2
hGlobalMem = Win.GlobalAlloc(ctypes.c_int(GHND), ctypes.c_int(bufferSize))
lpGlobalMem = Win.GlobalLock(ctypes.c_int(hGlobalMem))
Win.memcpy(lpGlobalMem, cty... | the_stack_v2_python_sparse | machaon/platforms/windows/clipboard.py | betasewer/machaon | train | 4 | |
cd9b5f8dcd286dfd43ee4a0d73d79bbb7fd15e1d | [
"QDialog.__init__(self, parent)\nself.setupUi(self)\nself.method = method\nif method == 0:\n self.label_4.setText(u'默认模型')\nelif method == 1:\n self.label_4.setText(u'CNN')\nelse:\n pass\nself.imgPath = None\nself.resultPath = None",
"self.imgPath = QtGui.QFileDialog.getOpenFileName(self, u'选择图片', '/', u... | <|body_start_0|>
QDialog.__init__(self, parent)
self.setupUi(self)
self.method = method
if method == 0:
self.label_4.setText(u'默认模型')
elif method == 1:
self.label_4.setText(u'CNN')
else:
pass
self.imgPath = None
self.res... | Class documentation goes here. | FaceDetectDialog | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FaceDetectDialog:
"""Class documentation goes here."""
def __init__(self, method=0, parent=None):
"""Constructor"""
<|body_0|>
def on_pushButton_clicked(self):
"""打开图片"""
<|body_1|>
def on_pushButton_2_clicked(self):
"""人脸检测"""
<|body... | stack_v2_sparse_classes_10k_train_007818 | 3,210 | permissive | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, method=0, parent=None)"
},
{
"docstring": "打开图片",
"name": "on_pushButton_clicked",
"signature": "def on_pushButton_clicked(self)"
},
{
"docstring": "人脸检测",
"name": "on_pushButton_2_clicked",
... | 3 | stack_v2_sparse_classes_30k_train_005979 | Implement the Python class `FaceDetectDialog` described below.
Class description:
Class documentation goes here.
Method signatures and docstrings:
- def __init__(self, method=0, parent=None): Constructor
- def on_pushButton_clicked(self): 打开图片
- def on_pushButton_2_clicked(self): 人脸检测 | Implement the Python class `FaceDetectDialog` described below.
Class description:
Class documentation goes here.
Method signatures and docstrings:
- def __init__(self, method=0, parent=None): Constructor
- def on_pushButton_clicked(self): 打开图片
- def on_pushButton_2_clicked(self): 人脸检测
<|skeleton|>
class FaceDetectDi... | c3cb07f83642873a3460ffe489c82505923c3c1a | <|skeleton|>
class FaceDetectDialog:
"""Class documentation goes here."""
def __init__(self, method=0, parent=None):
"""Constructor"""
<|body_0|>
def on_pushButton_clicked(self):
"""打开图片"""
<|body_1|>
def on_pushButton_2_clicked(self):
"""人脸检测"""
<|body... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FaceDetectDialog:
"""Class documentation goes here."""
def __init__(self, method=0, parent=None):
"""Constructor"""
QDialog.__init__(self, parent)
self.setupUi(self)
self.method = method
if method == 0:
self.label_4.setText(u'默认模型')
elif method ... | the_stack_v2_python_sparse | dlib_face_detection/gui/FaceDetectGui.py | rickding/HelloPython | train | 2 |
8301df83c054ad3e6341b3c5da1b8d9c9f5c7868 | [
"self.drone_connection.disconnect()\nif self.groundcam is not None:\n self.groundcam._close()",
"if self.use_wifi:\n return False\ncommand_tuple, enum_tuple = self.command_parser.get_command_tuple_with_enum('minidrone', 'UsbAccessory', 'GunControl', 'FIRE')\nreturn self.drone_connection.send_enum_command_pa... | <|body_start_0|>
self.drone_connection.disconnect()
if self.groundcam is not None:
self.groundcam._close()
<|end_body_0|>
<|body_start_1|>
if self.use_wifi:
return False
command_tuple, enum_tuple = self.command_parser.get_command_tuple_with_enum('minidrone', 'Usb... | Mambo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
<|body_0|>
def fire_gun(self):
"""Fire the gun (assumes it is attached) - note not supposed under wifi since the camera... | stack_v2_sparse_classes_10k_train_007819 | 31,062 | permissive | [
{
"docstring": "Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void",
"name": "disconnect",
"signature": "def disconnect(self)"
},
{
"docstring": "Fire the gun (assumes it is attached) - note not supposed under wifi since the camera ta... | 2 | stack_v2_sparse_classes_30k_val_000208 | Implement the Python class `Mambo` described below.
Class description:
Implement the Mambo class.
Method signatures and docstrings:
- def disconnect(self): Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void
- def fire_gun(self): Fire the gun (assumes it is... | Implement the Python class `Mambo` described below.
Class description:
Implement the Mambo class.
Method signatures and docstrings:
- def disconnect(self): Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void
- def fire_gun(self): Fire the gun (assumes it is... | 99ab19f7896bc30cf059244962a7da318d4672bf | <|skeleton|>
class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
<|body_0|>
def fire_gun(self):
"""Fire the gun (assumes it is attached) - note not supposed under wifi since the camera... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mambo:
def disconnect(self):
"""Disconnect the BLE connection. Always call this at the end of your programs to cleanly disconnect. :return: void"""
self.drone_connection.disconnect()
if self.groundcam is not None:
self.groundcam._close()
def fire_gun(self):
"""... | the_stack_v2_python_sparse | Madrid/July2022/ProfessorX-BCI/src/drone/vendor/Minidrone.py | SaturdaysAI/Projects | train | 35 | |
6b1bd643f5b63c2aeaf1fbae0d86b98e6914dead | [
"result = []\nleft, right = (0, 0)\n\ndef backtracking(partial, left, right, n):\n if left >= right >= 0:\n if len(partial) == n * 2:\n result.append(partial)\n if left < n:\n backtracking(partial + '(', left + 1, right, n)\n if right < left:\n backtracking(p... | <|body_start_0|>
result = []
left, right = (0, 0)
def backtracking(partial, left, right, n):
if left >= right >= 0:
if len(partial) == n * 2:
result.append(partial)
if left < n:
backtracking(partial + '(', left ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis_minus_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
def generateParenthesis_refer(self, n):
""":type n: int :r... | stack_v2_sparse_classes_10k_train_007820 | 3,026 | no_license | [
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis_add_1",
"signature": "def generateParenthesis_add_1(self, n)"
},
{
"docstring": ":type n: int :rtype: List[str]",
"name": "generateParenthesis_minus_1",
"signature": "def generateParenthesis_minus_1(self, n)"
... | 3 | stack_v2_sparse_classes_30k_train_005914 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis_add_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_minus_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_refer(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def generateParenthesis_add_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_minus_1(self, n): :type n: int :rtype: List[str]
- def generateParenthesis_refer(... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_0|>
def generateParenthesis_minus_1(self, n):
""":type n: int :rtype: List[str]"""
<|body_1|>
def generateParenthesis_refer(self, n):
""":type n: int :r... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def generateParenthesis_add_1(self, n):
""":type n: int :rtype: List[str]"""
result = []
left, right = (0, 0)
def backtracking(partial, left, right, n):
if left >= right >= 0:
if len(partial) == n * 2:
result.append(par... | the_stack_v2_python_sparse | 22_generateParenthesis.py | jennyChing/leetCode | train | 2 | |
bf52cdb366bf2827c2168f9a33a80c59443be497 | [
"super().__init__()\nself._use_condition = use_condition\nself._model = self._get_coupling_layers(num_layers=5, hidden_size=1024)",
"mask = tf.range(784, dtype=tf.float32)\nmask = tf.expand_dims(mask, axis=0)\nmask = mask % 2\nlayers = []\nfor _ in range(num_layers):\n layers.append(ClassConditionedAffineCoupl... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = self._get_coupling_layers(num_layers=5, hidden_size=1024)
<|end_body_0|>
<|body_start_1|>
mask = tf.range(784, dtype=tf.float32)
mask = tf.expand_dims(mask, axis=0)
mask = mask % 2
... | Class conditioned flow model. Attributes: _use_condition: _model: | ClassConditionedFlow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassConditionedFlow:
"""Class conditioned flow model. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, hidden_size):
"""Returns a li... | stack_v2_sparse_classes_10k_train_007821 | 12,897 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition:",
"name": "__init__",
"signature": "def __init__(self, use_condition)"
},
{
"docstring": "Returns a list of convolutional affine coupling layers. Args: num_layers: hidden_size: Returns:",
"name": "_get_coupling_layers",
"signat... | 3 | stack_v2_sparse_classes_30k_train_004539 | Implement the Python class `ClassConditionedFlow` described below.
Class description:
Class conditioned flow model. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condition:
- def _get_coupling_layers(self, num_layers, hidde... | Implement the Python class `ClassConditionedFlow` described below.
Class description:
Class conditioned flow model. Attributes: _use_condition: _model:
Method signatures and docstrings:
- def __init__(self, use_condition): Initializes the object. Args: use_condition:
- def _get_coupling_layers(self, num_layers, hidde... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class ClassConditionedFlow:
"""Class conditioned flow model. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, hidden_size):
"""Returns a li... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ClassConditionedFlow:
"""Class conditioned flow model. Attributes: _use_condition: _model:"""
def __init__(self, use_condition):
"""Initializes the object. Args: use_condition:"""
super().__init__()
self._use_condition = use_condition
self._model = self._get_coupling_layer... | the_stack_v2_python_sparse | flow.py | gaotianxiang/text-to-image-synthesis | train | 0 |
eab8d70075f45def13faec0ba3fbb2c7ebb199dd | [
"mod_obj = self.pool.get('ir.model.data')\npicking_type = context.get('picking_type')\nlocation_id = False\nif context is None:\n context = {}\nif 'default_maintenance' in context and context['default_maintenance'] == True:\n return False\nelse:\n return super(stock_move, self)._default_location_destinatio... | <|body_start_0|>
mod_obj = self.pool.get('ir.model.data')
picking_type = context.get('picking_type')
location_id = False
if context is None:
context = {}
if 'default_maintenance' in context and context['default_maintenance'] == True:
return False
e... | stock_move | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_move:
def _default_location_destination(self, cr, uid, context=None):
"""Gets default address of partner for destination location @return: Address id or False"""
<|body_0|>
def _default_location_source(self, cr, uid, context=None):
"""Gets default address of pa... | stack_v2_sparse_classes_10k_train_007822 | 36,987 | no_license | [
{
"docstring": "Gets default address of partner for destination location @return: Address id or False",
"name": "_default_location_destination",
"signature": "def _default_location_destination(self, cr, uid, context=None)"
},
{
"docstring": "Gets default address of partner for source location @r... | 2 | null | Implement the Python class `stock_move` described below.
Class description:
Implement the stock_move class.
Method signatures and docstrings:
- def _default_location_destination(self, cr, uid, context=None): Gets default address of partner for destination location @return: Address id or False
- def _default_location_... | Implement the Python class `stock_move` described below.
Class description:
Implement the stock_move class.
Method signatures and docstrings:
- def _default_location_destination(self, cr, uid, context=None): Gets default address of partner for destination location @return: Address id or False
- def _default_location_... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class stock_move:
def _default_location_destination(self, cr, uid, context=None):
"""Gets default address of partner for destination location @return: Address id or False"""
<|body_0|>
def _default_location_source(self, cr, uid, context=None):
"""Gets default address of pa... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class stock_move:
def _default_location_destination(self, cr, uid, context=None):
"""Gets default address of partner for destination location @return: Address id or False"""
mod_obj = self.pool.get('ir.model.data')
picking_type = context.get('picking_type')
location_id = False
... | the_stack_v2_python_sparse | v_7/NISS/shamil_v3/vehicles_maintenance/models/stock_exchange.py | musabahmed/baba | train | 0 | |
e8aaf07a3952cb7f728fe5a5270a84a05bb0bce0 | [
"self.device = config['device']\nloss_scales = config['losses_and_scales']\nif 'fvd' in loss_scales.keys() and config['img_c'] not in [2, 3]:\n warnings.warn(\"'FVD' measure won't be used since image channels needs to be in [2, 3]\")\n loss_scales.pop('fvd')\nself.losses = {k: (LOSS_CLASSES[k](device=self.dev... | <|body_start_0|>
self.device = config['device']
loss_scales = config['losses_and_scales']
if 'fvd' in loss_scales.keys() and config['img_c'] not in [2, 3]:
warnings.warn("'FVD' measure won't be used since image channels needs to be in [2, 3]")
loss_scales.pop('fvd')
... | This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string specifying whether to use the GPU for calculations (`cuda`) or the CPU (`cpu`). losses (dict):... | PredictionLossProvider | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PredictionLossProvider:
"""This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string specifying whether to use the GPU for calcul... | stack_v2_sparse_classes_10k_train_007823 | 2,547 | permissive | [
{
"docstring": "Initializes the provider by extracting device and loss IDs from the provided config dict and instantiating the losses that shall be used. Args: config (dict): A dictionary containing the devices and losses to use. The provided losses come with the scales that should be multiplied by the respecti... | 2 | stack_v2_sparse_classes_30k_train_003352 | Implement the Python class `PredictionLossProvider` described below.
Class description:
This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string speci... | Implement the Python class `PredictionLossProvider` described below.
Class description:
This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string speci... | 391570121b5bd9e3fd23aca9a0945a63c4173a24 | <|skeleton|>
class PredictionLossProvider:
"""This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string specifying whether to use the GPU for calcul... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PredictionLossProvider:
"""This class provides bundled access to multiple losses. With this class's :meth:`get_losses()` method, all specified loss values are calculated on the same input prediction and target tensor. Attributes: device (str): A string specifying whether to use the GPU for calculations (`cuda... | the_stack_v2_python_sparse | vp_suite/measure/loss_provider.py | AIS-Bonn/vp-suite | train | 18 |
5cca1ac2fe7164c920ed2acad40200bc8ac45e37 | [
"super(EncoderDecoder, self).__init__(conf, output_dim, name)\nself.encoder = encoder_factory.factory(conf)\nself.decoder = asr_decoder_factory.factory(conf, self.output_dim)",
"std_input_noise = float(self.conf['std_input_noise'])\nif is_training and std_input_noise > 0:\n noisy_inputs = inputs + tf.random_no... | <|body_start_0|>
super(EncoderDecoder, self).__init__(conf, output_dim, name)
self.encoder = encoder_factory.factory(conf)
self.decoder = asr_decoder_factory.factory(conf, self.output_dim)
<|end_body_0|>
<|body_start_1|>
std_input_noise = float(self.conf['std_input_noise'])
if i... | a general class for an encoder decoder system | EncoderDecoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
<|body_0|>
def _get_o... | stack_v2_sparse_classes_10k_train_007824 | 3,642 | permissive | [
{
"docstring": "LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name",
"name": "__init__",
"signature": "def __init__(self, conf, output_dim, name=None)"
},
{
"docstring": "Add the neural net variables and operations to th... | 2 | stack_v2_sparse_classes_30k_train_001556 | Implement the Python class `EncoderDecoder` described below.
Class description:
a general class for an encoder decoder system
Method signatures and docstrings:
- def __init__(self, conf, output_dim, name=None): LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: ... | Implement the Python class `EncoderDecoder` described below.
Class description:
a general class for an encoder decoder system
Method signatures and docstrings:
- def __init__(self, conf, output_dim, name=None): LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: ... | 09586e57bf4c6d29a6679e9bb3a488e09451f08e | <|skeleton|>
class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
<|body_0|>
def _get_o... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EncoderDecoder:
"""a general class for an encoder decoder system"""
def __init__(self, conf, output_dim, name=None):
"""LAS constructor Args: conf: The classifier configuration output_dim: the classifier output dimension name: the classifier name"""
super(EncoderDecoder, self).__init__(co... | the_stack_v2_python_sparse | nabu/neuralnetworks/classifiers/asr/encoder_decoder.py | chenxinglili/nabu | train | 0 |
a001bc8ff039637f1c41cf1d0d4b1381fc1f5945 | [
"self.__detailed_help = kwargs.pop('detailed_help', None)\nself.__args = args\nself.__kwargs = kwargs",
"name = self.__args[0]\nfor flag in parser.flag_args:\n if name in flag.option_strings:\n return flag\nreturn None",
"arg = parser.add_argument(*self.__args, **self.__kwargs)\nif self.__detailed_hel... | <|body_start_0|>
self.__detailed_help = kwargs.pop('detailed_help', None)
self.__args = args
self.__kwargs = kwargs
<|end_body_0|>
<|body_start_1|>
name = self.__args[0]
for flag in parser.flag_args:
if name in flag.option_strings:
return flag
... | A class that allows you to save an argument configuration for reuse. | Argument | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Argument:
"""A class that allows you to save an argument configuration for reuse."""
def __init__(self, *args, **kwargs):
"""Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword args to parser.add_argument."""
<|body_0|>
de... | stack_v2_sparse_classes_10k_train_007825 | 25,896 | permissive | [
{
"docstring": "Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword args to parser.add_argument.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Returns the flag object in parser.",
"name": "__GetFla... | 5 | stack_v2_sparse_classes_30k_train_001683 | Implement the Python class `Argument` described below.
Class description:
A class that allows you to save an argument configuration for reuse.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword a... | Implement the Python class `Argument` described below.
Class description:
A class that allows you to save an argument configuration for reuse.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword a... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Argument:
"""A class that allows you to save an argument configuration for reuse."""
def __init__(self, *args, **kwargs):
"""Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword args to parser.add_argument."""
<|body_0|>
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Argument:
"""A class that allows you to save an argument configuration for reuse."""
def __init__(self, *args, **kwargs):
"""Creates the argument. Args: *args: The positional args to parser.add_argument. **kwargs: The keyword args to parser.add_argument."""
self.__detailed_help = kwargs.p... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/googlecloudsdk/calliope/base.py | KaranToor/MA450 | train | 1 |
05cbeb00c30676f18d007c89255d8e39011280e3 | [
"self.request = None\nif isinstance(page, bytes):\n self.src = page\nelif _os.path.exists(page):\n with open(page, 'rb') as fp:\n self.src = fp.read()\nelse:\n better_headers = headers if headers else HEADERS.copy()\n self.request = _requests.get(page, headers=better_headers)\n if not self.req... | <|body_start_0|>
self.request = None
if isinstance(page, bytes):
self.src = page
elif _os.path.exists(page):
with open(page, 'rb') as fp:
self.src = fp.read()
else:
better_headers = headers if headers else HEADERS.copy()
sel... | Class TagFinder can be used to find and store elements from a given web page or markup | TagFinder | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagFinder:
"""Class TagFinder can be used to find and store elements from a given web page or markup"""
def __init__(self, page, headers=None):
"""Initializes this tag finder"""
<|body_0|>
def find(self, tag, method='find_all'):
"""Returns a list of found tags fo... | stack_v2_sparse_classes_10k_train_007826 | 31,809 | permissive | [
{
"docstring": "Initializes this tag finder",
"name": "__init__",
"signature": "def __init__(self, page, headers=None)"
},
{
"docstring": "Returns a list of found tags for the given search method",
"name": "find",
"signature": "def find(self, tag, method='find_all')"
},
{
"docstr... | 5 | stack_v2_sparse_classes_30k_test_000138 | Implement the Python class `TagFinder` described below.
Class description:
Class TagFinder can be used to find and store elements from a given web page or markup
Method signatures and docstrings:
- def __init__(self, page, headers=None): Initializes this tag finder
- def find(self, tag, method='find_all'): Returns a ... | Implement the Python class `TagFinder` described below.
Class description:
Class TagFinder can be used to find and store elements from a given web page or markup
Method signatures and docstrings:
- def __init__(self, page, headers=None): Initializes this tag finder
- def find(self, tag, method='find_all'): Returns a ... | f8773b630cc1f81b85a7fd385e4b91c29573d84d | <|skeleton|>
class TagFinder:
"""Class TagFinder can be used to find and store elements from a given web page or markup"""
def __init__(self, page, headers=None):
"""Initializes this tag finder"""
<|body_0|>
def find(self, tag, method='find_all'):
"""Returns a list of found tags fo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TagFinder:
"""Class TagFinder can be used to find and store elements from a given web page or markup"""
def __init__(self, page, headers=None):
"""Initializes this tag finder"""
self.request = None
if isinstance(page, bytes):
self.src = page
elif _os.path.exist... | the_stack_v2_python_sparse | net/core.py | claywahlstrom/clay | train | 2 |
8a51f3dc2d318d2df430b3033bc3b90db581a878 | [
"progbar = training_utils.get_progbar(model, 'samples' if use_samples else 'steps')\nprogbar.params = callbacks.params\nprogbar.params['verbose'] = verbose\ncallbacks.model.stop_training = False\ncallbacks._call_begin_hook(mode)\nprogbar.on_train_begin()\nself.callbacks = callbacks\nself.progbar = progbar\ntry:\n ... | <|body_start_0|>
progbar = training_utils.get_progbar(model, 'samples' if use_samples else 'steps')
progbar.params = callbacks.params
progbar.params['verbose'] = verbose
callbacks.model.stop_training = False
callbacks._call_begin_hook(mode)
progbar.on_train_begin()
... | Utility object that wrap around callbacks and progress bars. | TrainingContext | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrainingContext:
"""Utility object that wrap around callbacks and progress bars."""
def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN):
"""Provide a scope for the whole training process."""
<|body_0|>
def on_epoch(self, epoch=0, ... | stack_v2_sparse_classes_10k_train_007827 | 28,479 | permissive | [
{
"docstring": "Provide a scope for the whole training process.",
"name": "on_start",
"signature": "def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN)"
},
{
"docstring": "Provide a scope for running one epoch.",
"name": "on_epoch",
"signature": "... | 3 | null | Implement the Python class `TrainingContext` described below.
Class description:
Utility object that wrap around callbacks and progress bars.
Method signatures and docstrings:
- def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN): Provide a scope for the whole training process... | Implement the Python class `TrainingContext` described below.
Class description:
Utility object that wrap around callbacks and progress bars.
Method signatures and docstrings:
- def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN): Provide a scope for the whole training process... | 7cbba04a2ee16d21309eefad5be6585183a2d5a9 | <|skeleton|>
class TrainingContext:
"""Utility object that wrap around callbacks and progress bars."""
def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN):
"""Provide a scope for the whole training process."""
<|body_0|>
def on_epoch(self, epoch=0, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TrainingContext:
"""Utility object that wrap around callbacks and progress bars."""
def on_start(self, model, callbacks=None, use_samples=False, verbose=0, mode=ModeKeys.TRAIN):
"""Provide a scope for the whole training process."""
progbar = training_utils.get_progbar(model, 'samples' if ... | the_stack_v2_python_sparse | tensorflow/python/keras/engine/training_v2.py | NVIDIA/tensorflow | train | 763 |
c7ebeb7082d5ebac1e4aca2f8b739b0b030e0694 | [
"try:\n payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])\nexcept jwt.ExpiredSignatureError:\n raise serializers.ValidationError('Verificacion link has expired')\nexcept jwt.PyJWTError:\n raise serializers.ValidationError('Invalid token')\nif payload['type'] != 'email_confirmation':\n ... | <|body_start_0|>
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.ValidationError('Verificacion link has expired')
except jwt.PyJWTError:
raise serializers.ValidationError('Invalid to... | Account verification serializer | AccountVerificationSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
<|body_0|>
def save(self):
"""Update users verified status"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_10k_train_007828 | 5,109 | no_license | [
{
"docstring": "Verify token is valid",
"name": "validate_token",
"signature": "def validate_token(self, data)"
},
{
"docstring": "Update users verified status",
"name": "save",
"signature": "def save(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000438 | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification serializer
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid
- def save(self): Update users verified status | Implement the Python class `AccountVerificationSerializer` described below.
Class description:
Account verification serializer
Method signatures and docstrings:
- def validate_token(self, data): Verify token is valid
- def save(self): Update users verified status
<|skeleton|>
class AccountVerificationSerializer:
... | 0cede53169041667bd40bbce3c4774af84ffc2fa | <|skeleton|>
class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
<|body_0|>
def save(self):
"""Update users verified status"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AccountVerificationSerializer:
"""Account verification serializer"""
def validate_token(self, data):
"""Verify token is valid"""
try:
payload = jwt.decode(data, settings.SECRET_KEY, algorithm=['HS256'])
except jwt.ExpiredSignatureError:
raise serializers.Va... | the_stack_v2_python_sparse | users/serializers/users.py | KrystellCR/DjangoRF | train | 0 |
df8a70864db222d8fddd04e3ab2491a2a178eb39 | [
"res = 0\ns = []\nfor i in range(len(height)):\n while s and height[i] > height[s[-1]]:\n top = s.pop()\n if s:\n w = i - s[-1] - 1\n l = min(height[s[-1]], height[i]) - height[top]\n res += w * l\n s.append(i)\nreturn res",
"res = 0\nn = len(height)\nfor i in ... | <|body_start_0|>
res = 0
s = []
for i in range(len(height)):
while s and height[i] > height[s[-1]]:
top = s.pop()
if s:
w = i - s[-1] - 1
l = min(height[s[-1]], height[i]) - height[top]
res +=... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
<|body_0|>
def trap1(self, height):
""":type height: List[int] :rtype: int brute forth"""
<|body_1|>
def trap2(self, height):
""":type height: List[int] :rtyp... | stack_v2_sparse_classes_10k_train_007829 | 3,225 | no_license | [
{
"docstring": ":type height: List[int] :rtype: int using stack",
"name": "trap",
"signature": "def trap(self, height)"
},
{
"docstring": ":type height: List[int] :rtype: int brute forth",
"name": "trap1",
"signature": "def trap1(self, height)"
},
{
"docstring": ":type height: Li... | 5 | stack_v2_sparse_classes_30k_train_001286 | 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 using stack
- def trap1(self, height): :type height: List[int] :rtype: int brute forth
- def trap2(self, height): :typ... | 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 using stack
- def trap1(self, height): :type height: List[int] :rtype: int brute forth
- def trap2(self, height): :typ... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
<|body_0|>
def trap1(self, height):
""":type height: List[int] :rtype: int brute forth"""
<|body_1|>
def trap2(self, height):
""":type height: List[int] :rtyp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def trap(self, height):
""":type height: List[int] :rtype: int using stack"""
res = 0
s = []
for i in range(len(height)):
while s and height[i] > height[s[-1]]:
top = s.pop()
if s:
w = i - s[-1] - 1
... | the_stack_v2_python_sparse | PythonCode/src/0042_Trapping_Rain_Water.py | oneyuan/CodeforFun | train | 0 | |
e0515a9bbb57efc7f7b8542f1e56849e20c2a45f | [
"if not root:\n return ''\nque = deque()\nque.append(root)\nres = []\nwhile que:\n node = que.popleft()\n if not node:\n res.append('')\n continue\n res.append(str(node.val))\n que.append(node.left)\n que.append(node.right)\nlasti = len(res)\nfor i in range(len(res) - 1, -1, -1):\n ... | <|body_start_0|>
if not root:
return ''
que = deque()
que.append(root)
res = []
while que:
node = que.popleft()
if not node:
res.append('')
continue
res.append(str(node.val))
que.append(no... | 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_10k_train_007830 | 2,396 | 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_003556 | 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:... | 2a29426be1d690b6f90bc45b437900deee46d832 | <|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_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if not root:
return ''
que = deque()
que.append(root)
res = []
while que:
node = que.popleft()
if not node:
... | the_stack_v2_python_sparse | src/leet/449-Serialize and Deserialize BST.py | sevenseablue/leetcode | train | 0 | |
eae7869fdc8163dce9c31051a4e39b7f98cc0330 | [
"self.main_window = QtGui.QWidget()\nself.gui = Gui()\nself.gui.setupUi(self.main_window)\nself.gui.drawing_widget.mousePressEvent = self.mouse_press\nself.gui.drawing_widget.paintEvent = self.paint_event\nself.ttt = TicTacToeModel()",
"w = self.gui.drawing_widget.width() // 3\nh = self.gui.drawing_widget.height(... | <|body_start_0|>
self.main_window = QtGui.QWidget()
self.gui = Gui()
self.gui.setupUi(self.main_window)
self.gui.drawing_widget.mousePressEvent = self.mouse_press
self.gui.drawing_widget.paintEvent = self.paint_event
self.ttt = TicTacToeModel()
<|end_body_0|>
<|body_star... | Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget. | App | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class App:
"""Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget."""
def __init__(self):
"""Initialize the gui."""
<|body_0|>
def mouse_press(self, event):
"""Called automatically whenever the drawing wi... | stack_v2_sparse_classes_10k_train_007831 | 4,727 | no_license | [
{
"docstring": "Initialize the gui.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Called automatically whenever the drawing widget is clicked. :param PyQt.QtGui.QMouseEvent event: The event object from PyQt. :return: None",
"name": "mouse_press",
"signature":... | 3 | stack_v2_sparse_classes_30k_train_007288 | Implement the Python class `App` described below.
Class description:
Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget.
Method signatures and docstrings:
- def __init__(self): Initialize the gui.
- def mouse_press(self, event): Called automatically wh... | Implement the Python class `App` described below.
Class description:
Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget.
Method signatures and docstrings:
- def __init__(self): Initialize the gui.
- def mouse_press(self, event): Called automatically wh... | 0e3470085083012f893adb22aa46d46039016965 | <|skeleton|>
class App:
"""Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget."""
def __init__(self):
"""Initialize the gui."""
<|body_0|>
def mouse_press(self, event):
"""Called automatically whenever the drawing wi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class App:
"""Application class to create and control the gui. This version implements the Tic Tac Toe game using a drawing widget."""
def __init__(self):
"""Initialize the gui."""
self.main_window = QtGui.QWidget()
self.gui = Gui()
self.gui.setupUi(self.main_window)
sel... | the_stack_v2_python_sparse | CS_210 (Introduction to Programming)/TicTacToe/DrawApp.py | JacobOrner/USAFA | train | 0 |
4e42e313b4e8f4517cca59865a67badc6b525b39 | [
"n = len(grid)\np = [[(i, j) for j in range(n)] for i in range(n)]\nh = sorted([[grid[i][j], i, j] for j in range(n) for i in range(n)])\n\ndef f(a, b):\n if (a, b) != p[a][b]:\n p[a][b] = f(*p[a][b])\n return p[a][b]\nk = 0\nfor t in range(max(grid[0][0], grid[-1][-1]), h[-1][0]):\n while h[k][0] <... | <|body_start_0|>
n = len(grid)
p = [[(i, j) for j in range(n)] for i in range(n)]
h = sorted([[grid[i][j], i, j] for j in range(n) for i in range(n)])
def f(a, b):
if (a, b) != p[a][b]:
p[a][b] = f(*p[a][b])
return p[a][b]
k = 0
fo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def swim_in_water(grid: List[List[int]]) -> int:
"""并查集 @param grid: @return:"""
<|body_0|>
def swim_in_water_v2(grid: List[List[int]]) -> int:
"""BFS @param grid: @return:"""
<|body_1|>
def swim_in_water_v3(grid: List[List[int]]) -> int:
... | stack_v2_sparse_classes_10k_train_007832 | 6,600 | no_license | [
{
"docstring": "并查集 @param grid: @return:",
"name": "swim_in_water",
"signature": "def swim_in_water(grid: List[List[int]]) -> int"
},
{
"docstring": "BFS @param grid: @return:",
"name": "swim_in_water_v2",
"signature": "def swim_in_water_v2(grid: List[List[int]]) -> int"
},
{
"d... | 4 | stack_v2_sparse_classes_30k_train_004975 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swim_in_water(grid: List[List[int]]) -> int: 并查集 @param grid: @return:
- def swim_in_water_v2(grid: List[List[int]]) -> int: BFS @param grid: @return:
- def swim_in_water_v3(... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def swim_in_water(grid: List[List[int]]) -> int: 并查集 @param grid: @return:
- def swim_in_water_v2(grid: List[List[int]]) -> int: BFS @param grid: @return:
- def swim_in_water_v3(... | 1d1876620a55ff88af7bc390cf1a4fd4350d8d16 | <|skeleton|>
class Solution:
def swim_in_water(grid: List[List[int]]) -> int:
"""并查集 @param grid: @return:"""
<|body_0|>
def swim_in_water_v2(grid: List[List[int]]) -> int:
"""BFS @param grid: @return:"""
<|body_1|>
def swim_in_water_v3(grid: List[List[int]]) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def swim_in_water(grid: List[List[int]]) -> int:
"""并查集 @param grid: @return:"""
n = len(grid)
p = [[(i, j) for j in range(n)] for i in range(n)]
h = sorted([[grid[i][j], i, j] for j in range(n) for i in range(n)])
def f(a, b):
if (a, b) != p[a][b... | the_stack_v2_python_sparse | 02-算法思想/广度优先搜索/778.水位上升的泳池中游泳(H).py | jh-lau/leetcode_in_python | train | 0 | |
5109d6ebed0e8b17a1640b293a7dd4b9a065b036 | [
"datafile_empty = self.get_file('empty.csv')\nschema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]\nframe = self.context.frame.import_csv(datafile_empty, schema=schema_empty)\nself.assertEqual(frame.count(), 0)\nnull2 = frame.copy()\nself.assertEqual(nu... | <|body_start_0|>
datafile_empty = self.get_file('empty.csv')
schema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]
frame = self.context.frame.import_csv(datafile_empty, schema=schema_empty)
self.assertEqual(frame.count(), 0)
... | FileLoadTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
<|body_0|>
def test_import_whitespace(self):
"""Build frame with complex quoting and whitespace"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
datafile_empty = self.get_file('em... | stack_v2_sparse_classes_10k_train_007833 | 2,116 | permissive | [
{
"docstring": "Import an empty file.",
"name": "test_import_empty",
"signature": "def test_import_empty(self)"
},
{
"docstring": "Build frame with complex quoting and whitespace",
"name": "test_import_whitespace",
"signature": "def test_import_whitespace(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001351 | Implement the Python class `FileLoadTest` described below.
Class description:
Implement the FileLoadTest class.
Method signatures and docstrings:
- def test_import_empty(self): Import an empty file.
- def test_import_whitespace(self): Build frame with complex quoting and whitespace | Implement the Python class `FileLoadTest` described below.
Class description:
Implement the FileLoadTest class.
Method signatures and docstrings:
- def test_import_empty(self): Import an empty file.
- def test_import_whitespace(self): Build frame with complex quoting and whitespace
<|skeleton|>
class FileLoadTest:
... | 5548fc925b5c278263cbdebbd9e8c7593320c2f4 | <|skeleton|>
class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
<|body_0|>
def test_import_whitespace(self):
"""Build frame with complex quoting and whitespace"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FileLoadTest:
def test_import_empty(self):
"""Import an empty file."""
datafile_empty = self.get_file('empty.csv')
schema_empty = [('col_A', int), ('col_B', int), ('col_C', str), ('col_D', float), ('col_E', float), ('col_F', str)]
frame = self.context.frame.import_csv(datafile_... | the_stack_v2_python_sparse | regression-tests/sparktkregtests/testcases/frames/file_load_test.py | trustedanalytics/spark-tk | train | 35 | |
d53123f8286514231614dc17e6d3e1e9956f4de2 | [
"print(validated_data)\nquiz = Quiz.objects.create(**validated_data)\nreturn quiz\n'\\n answers_data = validated_data.pop(\"answers\")\\n question = Question.objects.create(**validated_data)\\n for answer in answers_data:\\n answer = Answer.objects.create(question=question, **answer... | <|body_start_0|>
print(validated_data)
quiz = Quiz.objects.create(**validated_data)
return quiz
'\n answers_data = validated_data.pop("answers")\n question = Question.objects.create(**validated_data)\n for answer in answers_data:\n answer = Answer.objects... | QuizSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuizSerializer:
def create(self, validated_data, *args, **kwargs):
"""we can override the create method"""
<|body_0|>
def update(self, instance, validated_data):
"""update or put the exsiting value"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
pri... | stack_v2_sparse_classes_10k_train_007834 | 2,460 | permissive | [
{
"docstring": "we can override the create method",
"name": "create",
"signature": "def create(self, validated_data, *args, **kwargs)"
},
{
"docstring": "update or put the exsiting value",
"name": "update",
"signature": "def update(self, instance, validated_data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_005354 | Implement the Python class `QuizSerializer` described below.
Class description:
Implement the QuizSerializer class.
Method signatures and docstrings:
- def create(self, validated_data, *args, **kwargs): we can override the create method
- def update(self, instance, validated_data): update or put the exsiting value | Implement the Python class `QuizSerializer` described below.
Class description:
Implement the QuizSerializer class.
Method signatures and docstrings:
- def create(self, validated_data, *args, **kwargs): we can override the create method
- def update(self, instance, validated_data): update or put the exsiting value
<... | bebeff8d055ea769773cd1c749f42408aa83f5b9 | <|skeleton|>
class QuizSerializer:
def create(self, validated_data, *args, **kwargs):
"""we can override the create method"""
<|body_0|>
def update(self, instance, validated_data):
"""update or put the exsiting value"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class QuizSerializer:
def create(self, validated_data, *args, **kwargs):
"""we can override the create method"""
print(validated_data)
quiz = Quiz.objects.create(**validated_data)
return quiz
'\n answers_data = validated_data.pop("answers")\n question = Questio... | the_stack_v2_python_sparse | backend/quiz/api/serializers/quizes.py | mahmoud-batman/quizz-app | train | 0 | |
d5892a599f3213e345f0cc6bc337f4ef00140653 | [
"if user_id is None or type(user_id) is not str:\n return None\nsession_id = str(uuid.uuid4())\nuser_session = UserSession()\nuser_session.user_id = user_id\nuser_session.session_id = session_id\nuser_session.save()\nreturn session_id",
"if type(session_id) is not str:\n return None\ntry:\n users_session... | <|body_start_0|>
if user_id is None or type(user_id) is not str:
return None
session_id = str(uuid.uuid4())
user_session = UserSession()
user_session.user_id = user_id
user_session.session_id = session_id
user_session.save()
return session_id
<|end_bod... | SessionAuth | SessionDBAuth | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionDBAuth:
"""SessionAuth"""
def create_session(self, user_id=None):
"""Create a session"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""returns the User ID by requesting UserSession in the database based on session_id"""
<|body_1|... | stack_v2_sparse_classes_10k_train_007835 | 2,106 | no_license | [
{
"docstring": "Create a session",
"name": "create_session",
"signature": "def create_session(self, user_id=None)"
},
{
"docstring": "returns the User ID by requesting UserSession in the database based on session_id",
"name": "user_id_for_session_id",
"signature": "def user_id_for_sessio... | 3 | stack_v2_sparse_classes_30k_val_000346 | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionAuth
Method signatures and docstrings:
- def create_session(self, user_id=None): Create a session
- def user_id_for_session_id(self, session_id=None): returns the User ID by requesting UserSession in the database based on session_id... | Implement the Python class `SessionDBAuth` described below.
Class description:
SessionAuth
Method signatures and docstrings:
- def create_session(self, user_id=None): Create a session
- def user_id_for_session_id(self, session_id=None): returns the User ID by requesting UserSession in the database based on session_id... | ef832164444a3c134851251655a408abd6369a11 | <|skeleton|>
class SessionDBAuth:
"""SessionAuth"""
def create_session(self, user_id=None):
"""Create a session"""
<|body_0|>
def user_id_for_session_id(self, session_id=None):
"""returns the User ID by requesting UserSession in the database based on session_id"""
<|body_1|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SessionDBAuth:
"""SessionAuth"""
def create_session(self, user_id=None):
"""Create a session"""
if user_id is None or type(user_id) is not str:
return None
session_id = str(uuid.uuid4())
user_session = UserSession()
user_session.user_id = user_id
... | the_stack_v2_python_sparse | 0x07-Session_authentication/api/v1/auth/session_db_auth.py | DiegoOrejuela/holbertonschool-web_back_end | train | 0 |
2118b8a15c3323094bff2c346d735801031ad7ef | [
"diff = [float('inf')]\n\ndef dfs(root):\n \"\"\"\n :ret: min, max\n \"\"\"\n if not root:\n return\n lsmall = llarge = rsmall = rlarge = None\n if root.left:\n lsmall, llarge = dfs(root.left)\n diff[0] = min(diff[0], root.val - llarge.val)\n if root.right:\... | <|body_start_0|>
diff = [float('inf')]
def dfs(root):
"""
:ret: min, max
"""
if not root:
return
lsmall = llarge = rsmall = rlarge = None
if root.left:
lsmall, llarge = dfs(root.left)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDiffInBST(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def rewrite(self, root):
""":type root: TreeNode :rtype: int using yield, inorder to trigger it, use for loop"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d... | stack_v2_sparse_classes_10k_train_007836 | 2,714 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "minDiffInBST",
"signature": "def minDiffInBST(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int using yield, inorder to trigger it, use for loop",
"name": "rewrite",
"signature": "def rewrite(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDiffInBST(self, root): :type root: TreeNode :rtype: int
- def rewrite(self, root): :type root: TreeNode :rtype: int using yield, inorder to trigger it, use for loop | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDiffInBST(self, root): :type root: TreeNode :rtype: int
- def rewrite(self, root): :type root: TreeNode :rtype: int using yield, inorder to trigger it, use for loop
<|ske... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def minDiffInBST(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def rewrite(self, root):
""":type root: TreeNode :rtype: int using yield, inorder to trigger it, use for loop"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def minDiffInBST(self, root):
""":type root: TreeNode :rtype: int"""
diff = [float('inf')]
def dfs(root):
"""
:ret: min, max
"""
if not root:
return
lsmall = llarge = rsmall = rlarge ... | the_stack_v2_python_sparse | co_google/783_Minimum_Distance_Between_BST_Nodes.py | vsdrun/lc_public | train | 6 | |
4b32221dfa2b66dee5fc2d2a8c86501d22d7ed04 | [
"if sociallogin.is_existing:\n return\nif 'email' not in sociallogin.account.extra_data:\n return\ntry:\n email = sociallogin.account.extra_data['email'].lower()\n email_address = EmailAddress.objects.get(email__iexact=email)\nexcept EmailAddress.DoesNotExist:\n return\nuser = email_address.user\nsoc... | <|body_start_0|>
if sociallogin.is_existing:
return
if 'email' not in sociallogin.account.extra_data:
return
try:
email = sociallogin.account.extra_data['email'].lower()
email_address = EmailAddress.objects.get(email__iexact=email)
except E... | SocialAccountAdapter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocialAccountAdapter:
def pre_social_login(self, request, sociallogin):
"""Invoked just after a user successfully authenticates via a social provider, but before the login is actually processed (and before the pre_social_login signal is emitted). We're trying to solve different use cases... | stack_v2_sparse_classes_10k_train_007837 | 2,719 | permissive | [
{
"docstring": "Invoked just after a user successfully authenticates via a social provider, but before the login is actually processed (and before the pre_social_login signal is emitted). We're trying to solve different use cases: - social account already exists, just go on - social account has no email or emai... | 2 | stack_v2_sparse_classes_30k_train_000253 | Implement the Python class `SocialAccountAdapter` described below.
Class description:
Implement the SocialAccountAdapter class.
Method signatures and docstrings:
- def pre_social_login(self, request, sociallogin): Invoked just after a user successfully authenticates via a social provider, but before the login is actu... | Implement the Python class `SocialAccountAdapter` described below.
Class description:
Implement the SocialAccountAdapter class.
Method signatures and docstrings:
- def pre_social_login(self, request, sociallogin): Invoked just after a user successfully authenticates via a social provider, but before the login is actu... | bfb335d70733130eaecb026d38e23a5ac01e50ea | <|skeleton|>
class SocialAccountAdapter:
def pre_social_login(self, request, sociallogin):
"""Invoked just after a user successfully authenticates via a social provider, but before the login is actually processed (and before the pre_social_login signal is emitted). We're trying to solve different use cases... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SocialAccountAdapter:
def pre_social_login(self, request, sociallogin):
"""Invoked just after a user successfully authenticates via a social provider, but before the login is actually processed (and before the pre_social_login signal is emitted). We're trying to solve different use cases: - social acc... | the_stack_v2_python_sparse | server/comidaimigrante/account/adapter.py | LabHackerSP/comidaimigrante | train | 1 | |
25ef1810a8467e40ce9d8392172d9eec9d5db51c | [
"super(SDPOSMenu, self).__init__(location, use_cache)\nself._location = location\nself.items = []\nself.categories = swagger_pos_menu\nself._item_name_dict = {}\nself._item_id_dict = {}\nself._category_name_dict = {}\nself._category_id_dict = {}\nfor category in swagger_pos_menu:\n for index, item in enumerate(c... | <|body_start_0|>
super(SDPOSMenu, self).__init__(location, use_cache)
self._location = location
self.items = []
self.categories = swagger_pos_menu
self._item_name_dict = {}
self._item_id_dict = {}
self._category_name_dict = {}
self._category_id_dict = {}
... | SDPOSMenu | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SDPOSMenu:
def __init__(self, location, swagger_pos_menu, use_cache=True):
""":param location: :param swagger_menu: :param use_cache:"""
<|body_0|>
def get_category(self, category_id=None, category_name=None):
""":param category_id: :param category_name: :return:"""
... | stack_v2_sparse_classes_10k_train_007838 | 2,292 | permissive | [
{
"docstring": ":param location: :param swagger_menu: :param use_cache:",
"name": "__init__",
"signature": "def __init__(self, location, swagger_pos_menu, use_cache=True)"
},
{
"docstring": ":param category_id: :param category_name: :return:",
"name": "get_category",
"signature": "def ge... | 3 | stack_v2_sparse_classes_30k_test_000206 | Implement the Python class `SDPOSMenu` described below.
Class description:
Implement the SDPOSMenu class.
Method signatures and docstrings:
- def __init__(self, location, swagger_pos_menu, use_cache=True): :param location: :param swagger_menu: :param use_cache:
- def get_category(self, category_id=None, category_name... | Implement the Python class `SDPOSMenu` described below.
Class description:
Implement the SDPOSMenu class.
Method signatures and docstrings:
- def __init__(self, location, swagger_pos_menu, use_cache=True): :param location: :param swagger_menu: :param use_cache:
- def get_category(self, category_id=None, category_name... | 7c24492dcc06b66aea3fd040c82152d2c3fdf719 | <|skeleton|>
class SDPOSMenu:
def __init__(self, location, swagger_pos_menu, use_cache=True):
""":param location: :param swagger_menu: :param use_cache:"""
<|body_0|>
def get_category(self, category_id=None, category_name=None):
""":param category_id: :param category_name: :return:"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SDPOSMenu:
def __init__(self, location, swagger_pos_menu, use_cache=True):
""":param location: :param swagger_menu: :param use_cache:"""
super(SDPOSMenu, self).__init__(location, use_cache)
self._location = location
self.items = []
self.categories = swagger_pos_menu
... | the_stack_v2_python_sparse | subtledata/sd_pos_menu.py | jakeharding/subtledata_python | train | 0 | |
b1d88b1b73c3eac45e4a80b8428c5aeaec4aae90 | [
"has_cycle = False\none_step = head\ntwo_step = head\nwhile two_step and two_step.next:\n one_step = one_step.next\n two_step = two_step.next.next\n if one_step == two_step:\n has_cycle = True\n break\nif not has_cycle:\n return None\np = head\nstart = one_step.next\nwhile start:\n if s... | <|body_start_0|>
has_cycle = False
one_step = head
two_step = head
while two_step and two_step.next:
one_step = one_step.next
two_step = two_step.next.next
if one_step == two_step:
has_cycle = True
break
if not h... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
has_cycle = False
one_step =... | stack_v2_sparse_classes_10k_train_007839 | 1,566 | no_license | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle1",
"signature": "def detectCycle1(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "detectCycle",
"signature": "def detectCycle(self, head)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def detectCycle1(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle(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 detectCycle1(self, head): :type head: ListNode :rtype: ListNode
- def detectCycle(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
def de... | e5b018493bbd12edcdcd0434f35d9c358106d391 | <|skeleton|>
class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def detectCycle(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def detectCycle1(self, head):
""":type head: ListNode :rtype: ListNode"""
has_cycle = False
one_step = head
two_step = head
while two_step and two_step.next:
one_step = one_step.next
two_step = two_step.next.next
if one_step... | the_stack_v2_python_sparse | py/leetcode/142.py | wfeng1991/learnpy | train | 0 | |
dd505beeab289a88129187e103c67ad510c5a85f | [
"if path is None:\n outpath = os.path.dirname(os.path.abspath(configfile))\nelse:\n outpath = path\nself.config = Configuration(configfile, outpath=path)\nself.pixel = pixel\nself.nside = nside",
"if not self.config.galfile_pixelized:\n raise ValueError('Code only runs with pixelized galfile.')\nself.con... | <|body_start_0|>
if path is None:
outpath = os.path.dirname(os.path.abspath(configfile))
else:
outpath = path
self.config = Configuration(configfile, outpath=path)
self.pixel = pixel
self.nside = nside
<|end_body_0|>
<|body_start_1|>
if not self.c... | Class to run richness computation (runcat) on a single healpix pixel, for distributed runs. | RuncatPixelTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RuncatPixelTask:
"""Class to run richness computation (runcat) on a single healpix pixel, for distributed runs."""
def __init__(self, configfile, pixel, nside, path=None):
"""Instantiate a RuncatPixelTask. Parameters ---------- configfile: `str` Configuration yaml filename. pixel: `i... | stack_v2_sparse_classes_10k_train_007840 | 10,033 | permissive | [
{
"docstring": "Instantiate a RuncatPixelTask. Parameters ---------- configfile: `str` Configuration yaml filename. pixel: `int` Healpix pixel to run on. nside: `int` Healpix nside associated with pixel. path: `str`, optional Output path. Default is None, use same absolute path as configfile. percolation_maskin... | 2 | stack_v2_sparse_classes_30k_train_007317 | Implement the Python class `RuncatPixelTask` described below.
Class description:
Class to run richness computation (runcat) on a single healpix pixel, for distributed runs.
Method signatures and docstrings:
- def __init__(self, configfile, pixel, nside, path=None): Instantiate a RuncatPixelTask. Parameters ----------... | Implement the Python class `RuncatPixelTask` described below.
Class description:
Class to run richness computation (runcat) on a single healpix pixel, for distributed runs.
Method signatures and docstrings:
- def __init__(self, configfile, pixel, nside, path=None): Instantiate a RuncatPixelTask. Parameters ----------... | d3a8b432c2f3a20aa518a7781c0f2aa315624855 | <|skeleton|>
class RuncatPixelTask:
"""Class to run richness computation (runcat) on a single healpix pixel, for distributed runs."""
def __init__(self, configfile, pixel, nside, path=None):
"""Instantiate a RuncatPixelTask. Parameters ---------- configfile: `str` Configuration yaml filename. pixel: `i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RuncatPixelTask:
"""Class to run richness computation (runcat) on a single healpix pixel, for distributed runs."""
def __init__(self, configfile, pixel, nside, path=None):
"""Instantiate a RuncatPixelTask. Parameters ---------- configfile: `str` Configuration yaml filename. pixel: `int` Healpix p... | the_stack_v2_python_sparse | redmapper/pipeline/redmappertask.py | erykoff/redmapper | train | 20 |
3be1e5861745c2424fd1a24a0940da6c1211a46e | [
"base.LIMIT_FLAG.AddToParser(parser)\nf = parser.add_argument('--where', default='', type=str, help='A filter spec for what operations to display.')\nf.detailed_help = ' A string for filtering operations. The following filter fields are\\n supported:\\n\\n createTime - The time this job was... | <|body_start_0|>
base.LIMIT_FLAG.AddToParser(parser)
f = parser.add_argument('--where', default='', type=str, help='A filter spec for what operations to display.')
f.detailed_help = ' A string for filtering operations. The following filter fields are\n supported:\n\n cre... | List Genomics operations in a project. Prints a table with summary information on operations in the project. | List | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class List:
"""List Genomics operations in a project. Prints a table with summary information on operations in the project."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on... | stack_v2_sparse_classes_10k_train_007841 | 3,324 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | null | Implement the Python class `List` described below.
Class description:
List Genomics operations in a project. Prints a table with summary information on operations in the project.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An arg... | Implement the Python class `List` described below.
Class description:
List Genomics operations in a project. Prints a table with summary information on operations in the project.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An arg... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class List:
"""List Genomics operations in a project. Prints a table with summary information on operations in the project."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class List:
"""List Genomics operations in a project. Prints a table with summary information on operations in the project."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command ... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/surface/genomics/operations/list.py | KaranToor/MA450 | train | 1 |
9649de1fa39eeba6ff22ee66fe7f8285b650c110 | [
"self._K_P = K_P\nself._K_D = K_D\nself._K_I = K_I\nself.error = 0.0\nself.error_integral = 0.0\nself.error_derivative = 0.0",
"previous_error = self.error\nself.error = target_speed - current_speed\nself.error_integral = np.clip(self.error_integral + self.error, -40.0, 40.0)\nself.error_derivative = self.error -... | <|body_start_0|>
self._K_P = K_P
self._K_D = K_D
self._K_I = K_I
self.error = 0.0
self.error_integral = 0.0
self.error_derivative = 0.0
<|end_body_0|>
<|body_start_1|>
previous_error = self.error
self.error = target_speed - current_speed
self.erro... | PIDLongitudinalController implements longitudinal control using a PID. | PIDLongitudinalController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PIDLongitudinalController:
"""PIDLongitudinalController implements longitudinal control using a PID."""
def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0):
""":param vehicle: actor to apply to local planner logic onto :param K_P: Proportional term :param K_D: Differential term :param K_I:... | stack_v2_sparse_classes_10k_train_007842 | 6,324 | permissive | [
{
"docstring": ":param vehicle: actor to apply to local planner logic onto :param K_P: Proportional term :param K_D: Differential term :param K_I: Integral term",
"name": "__init__",
"signature": "def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0)"
},
{
"docstring": "Estimate the throttle of the vehi... | 2 | stack_v2_sparse_classes_30k_train_004866 | Implement the Python class `PIDLongitudinalController` described below.
Class description:
PIDLongitudinalController implements longitudinal control using a PID.
Method signatures and docstrings:
- def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0): :param vehicle: actor to apply to local planner logic onto :param K_P: Pr... | Implement the Python class `PIDLongitudinalController` described below.
Class description:
PIDLongitudinalController implements longitudinal control using a PID.
Method signatures and docstrings:
- def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0): :param vehicle: actor to apply to local planner logic onto :param K_P: Pr... | e9063d97ff5a724f76adbb1b852dc71da1dcfeec | <|skeleton|>
class PIDLongitudinalController:
"""PIDLongitudinalController implements longitudinal control using a PID."""
def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0):
""":param vehicle: actor to apply to local planner logic onto :param K_P: Proportional term :param K_D: Differential term :param K_I:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PIDLongitudinalController:
"""PIDLongitudinalController implements longitudinal control using a PID."""
def __init__(self, K_P=1.0, K_D=0.0, K_I=0.0):
""":param vehicle: actor to apply to local planner logic onto :param K_P: Proportional term :param K_D: Differential term :param K_I: Integral ter... | the_stack_v2_python_sparse | carla_ad_agent/src/carla_ad_agent/vehicle_pid_controller.py | carla-simulator/ros-bridge | train | 448 |
22b892923124f6f7b7432370b83ad91b0c545419 | [
"super(MaskNet, self).__init__()\nself.prep_block_1 = nn.Sequential(nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=3, padding=1), nn.ReLU(), nn.BatchNorm2d(32), nn.Dropout(dropout_rate))\nself.prep_block_2 = nn.Sequential(nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=3, padding=1)... | <|body_start_0|>
super(MaskNet, self).__init__()
self.prep_block_1 = nn.Sequential(nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=3, padding=1), nn.ReLU(), nn.BatchNorm2d(32), nn.Dropout(dropout_rate))
self.prep_block_2 = nn.Sequential(nn.Conv2d(in_channels=in_channels, out_chan... | MaskNet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaskNet:
def __init__(self, dropout_rate=0.0, in_channels=3):
"""This function instantiates all the model layers."""
<|body_0|>
def forward(self, x):
"""This function defines the forward pass of the model. Args: x: Input. Returns: Model output."""
<|body_1|>
... | stack_v2_sparse_classes_10k_train_007843 | 1,855 | permissive | [
{
"docstring": "This function instantiates all the model layers.",
"name": "__init__",
"signature": "def __init__(self, dropout_rate=0.0, in_channels=3)"
},
{
"docstring": "This function defines the forward pass of the model. Args: x: Input. Returns: Model output.",
"name": "forward",
"s... | 2 | stack_v2_sparse_classes_30k_train_002768 | Implement the Python class `MaskNet` described below.
Class description:
Implement the MaskNet class.
Method signatures and docstrings:
- def __init__(self, dropout_rate=0.0, in_channels=3): This function instantiates all the model layers.
- def forward(self, x): This function defines the forward pass of the model. A... | Implement the Python class `MaskNet` described below.
Class description:
Implement the MaskNet class.
Method signatures and docstrings:
- def __init__(self, dropout_rate=0.0, in_channels=3): This function instantiates all the model layers.
- def forward(self, x): This function defines the forward pass of the model. A... | 2eea883c96bf106774ea94464fc16c6baea86a95 | <|skeleton|>
class MaskNet:
def __init__(self, dropout_rate=0.0, in_channels=3):
"""This function instantiates all the model layers."""
<|body_0|>
def forward(self, x):
"""This function defines the forward pass of the model. Args: x: Input. Returns: Model output."""
<|body_1|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MaskNet:
def __init__(self, dropout_rate=0.0, in_channels=3):
"""This function instantiates all the model layers."""
super(MaskNet, self).__init__()
self.prep_block_1 = nn.Sequential(nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=3, padding=1), nn.ReLU(), nn.BatchNorm2... | the_stack_v2_python_sparse | tensornet/model/masknet.py | shan18/Depth-Estimation-Segmentation | train | 7 | |
a63fcd94ca0865893d29f0e633366c85e521b29c | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ScheduleInformation()",
"from .free_busy_error import FreeBusyError\nfrom .schedule_item import ScheduleItem\nfrom .working_hours import WorkingHours\nfrom .free_busy_error import FreeBusyError\nfrom .schedule_item import ScheduleItem\... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ScheduleInformation()
<|end_body_0|>
<|body_start_1|>
from .free_busy_error import FreeBusyError
from .schedule_item import ScheduleItem
from .working_hours import WorkingHours
... | ScheduleInformation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScheduleInformation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ScheduleInformation:
"""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 ob... | stack_v2_sparse_classes_10k_train_007844 | 4,465 | 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: ScheduleInformation",
"name": "create_from_discriminator_value",
"signature": "def create_from_discriminator... | 3 | null | Implement the Python class `ScheduleInformation` described below.
Class description:
Implement the ScheduleInformation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ScheduleInformation: Creates a new instance of the appropriate class based on d... | Implement the Python class `ScheduleInformation` described below.
Class description:
Implement the ScheduleInformation class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ScheduleInformation: Creates a new instance of the appropriate class based on d... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ScheduleInformation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ScheduleInformation:
"""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 ob... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ScheduleInformation:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ScheduleInformation:
"""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: ... | the_stack_v2_python_sparse | msgraph/generated/models/schedule_information.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
e71e7cac4c12355acd936e4d145765c87fe6ec08 | [
"torch.nn.Module.__init__(self)\nself._is_all = is_all\nif self._is_all:\n self.features = torchvision.models.vgg16(pretrained=True).features\n self.features = torch.nn.Sequential(*list(self.features.children())[:-2])\nself.relu5_3 = torch.nn.ReLU(inplace=False)\nself.fc = torch.nn.Linear(in_features=512 * 51... | <|body_start_0|>
torch.nn.Module.__init__(self)
self._is_all = is_all
if self._is_all:
self.features = torchvision.models.vgg16(pretrained=True).features
self.features = torch.nn.Sequential(*list(self.features.children())[:-2])
self.relu5_3 = torch.nn.ReLU(inplace... | Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448*448 input, and the relu5-3 activation has shape 512*28*28 since we dow... | BCNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BCNN:
"""Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448*448 input, and the relu5-3 activation ... | stack_v2_sparse_classes_10k_train_007845 | 3,951 | no_license | [
{
"docstring": "Declare all needed layers. Args: num_classes, int. is_all, bool: In the all/fc phase.",
"name": "__init__",
"signature": "def __init__(self, num_classes, is_all)"
},
{
"docstring": "Initialize the weight and bias for each module. Args: module, torch.nn.Module.",
"name": "_ini... | 3 | null | Implement the Python class `BCNN` described below.
Class description:
Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448... | Implement the Python class `BCNN` described below.
Class description:
Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class BCNN:
"""Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448*448 input, and the relu5-3 activation ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BCNN:
"""Mean field B-CNN model. The B-CNN model is illustrated as follows. conv1^2 (64) -> pool1 -> conv2^2 (128) -> pool2 -> conv3^3 (256) -> pool3 -> conv4^3 (512) -> pool4 -> conv5^3 (512) -> mean field bilinear pooling -> fc. The network accepts a 3*448*448 input, and the relu5-3 activation has shape 512... | the_stack_v2_python_sparse | generated/test_HaoMood_blinear_cnn_faster.py | jansel/pytorch-jit-paritybench | train | 35 |
b32b0a4215af658ed83ab312436444e2f3ed0602 | [
"n = [x * x for x in nums]\nn.sort()\nreturn n",
"res = [0 for _ in range(len(nums))]\nl, r = (0, len(nums) - 1)\nfor idx in reversed(range(len(nums))):\n l_v = nums[l]\n r_v = nums[r]\n if abs(l_v) >= abs(r_v):\n res[idx] = l_v * l_v\n l += 1\n else:\n res[idx] = r_v * r_v\n ... | <|body_start_0|>
n = [x * x for x in nums]
n.sort()
return n
<|end_body_0|>
<|body_start_1|>
res = [0 for _ in range(len(nums))]
l, r = (0, len(nums) - 1)
for idx in reversed(range(len(nums))):
l_v = nums[l]
r_v = nums[r]
if abs(l_v) >... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def sortedSquares_1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = [x * x for x in nums]
... | stack_v2_sparse_classes_10k_train_007846 | 931 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "sortedSquares",
"signature": "def sortedSquares(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "sortedSquares_1",
"signature": "def sortedSquares_1(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000341 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedSquares(self, nums): :type nums: List[int] :rtype: List[int]
- def sortedSquares_1(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortedSquares(self, nums): :type nums: List[int] :rtype: List[int]
- def sortedSquares_1(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
class Solution:
... | 8cdb97bc7588b96b91b1c550afd84e976c1926e0 | <|skeleton|>
class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def sortedSquares_1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def sortedSquares(self, nums):
""":type nums: List[int] :rtype: List[int]"""
n = [x * x for x in nums]
n.sort()
return n
def sortedSquares_1(self, nums):
""":type nums: List[int] :rtype: List[int]"""
res = [0 for _ in range(len(nums))]
l, ... | the_stack_v2_python_sparse | Array/977_SquaresofSortedArray.py | ZhengLiangliang1996/Leetcode_ML_Daily | train | 1 | |
f90c0ea36d3fa13212380b15cadb34035cd80dc5 | [
"wave = numpy.convolve(one.waveform, two.waveform, mode)\nwave.resize(len(one.waveform))\nsuper().__init__(name, one.times, wave)\nself.one = one\nself.two = two",
"if key in ('', 'both', 'whole', 'self', 0, 3):\n return self\nif key in ('one', 1, self.one.name):\n return self.one\nif key in ('two', 2, self... | <|body_start_0|>
wave = numpy.convolve(one.waveform, two.waveform, mode)
wave.resize(len(one.waveform))
super().__init__(name, one.times, wave)
self.one = one
self.two = two
<|end_body_0|>
<|body_start_1|>
if key in ('', 'both', 'whole', 'self', 0, 3):
return... | A signal formed from the convolution of two signals. | Convolution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Convolution:
"""A signal formed from the convolution of two signals."""
def __init__(self, name, one, two, mode='full'):
"""Create measure from two signals."""
<|body_0|>
def component(self, key):
"""Return component by identifying key."""
<|body_1|>
<|e... | stack_v2_sparse_classes_10k_train_007847 | 25,189 | no_license | [
{
"docstring": "Create measure from two signals.",
"name": "__init__",
"signature": "def __init__(self, name, one, two, mode='full')"
},
{
"docstring": "Return component by identifying key.",
"name": "component",
"signature": "def component(self, key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004481 | Implement the Python class `Convolution` described below.
Class description:
A signal formed from the convolution of two signals.
Method signatures and docstrings:
- def __init__(self, name, one, two, mode='full'): Create measure from two signals.
- def component(self, key): Return component by identifying key. | Implement the Python class `Convolution` described below.
Class description:
A signal formed from the convolution of two signals.
Method signatures and docstrings:
- def __init__(self, name, one, two, mode='full'): Create measure from two signals.
- def component(self, key): Return component by identifying key.
<|sk... | bfaea8464a9f777e5b59216b265fd68fb22564ae | <|skeleton|>
class Convolution:
"""A signal formed from the convolution of two signals."""
def __init__(self, name, one, two, mode='full'):
"""Create measure from two signals."""
<|body_0|>
def component(self, key):
"""Return component by identifying key."""
<|body_1|>
<|e... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Convolution:
"""A signal formed from the convolution of two signals."""
def __init__(self, name, one, two, mode='full'):
"""Create measure from two signals."""
wave = numpy.convolve(one.waveform, two.waveform, mode)
wave.resize(len(one.waveform))
super().__init__(name, one... | the_stack_v2_python_sparse | wirecell/sigproc/fwd.py | WireCell/wire-cell-python | train | 0 |
0610dc5dbcbf1f512f6285bdb1beff7f96cdd032 | [
"self.db = db\nself.verbose = verbose\nself.notification_type = notification_type\nself.notification_origin = notification_origin\nself.process_id = process_id",
"type_id = self.db.grep_id_from_lookup_table(id_field_name='NotificationTypeID', table_name='notification_types', where_field_name='Type', where_value=s... | <|body_start_0|>
self.db = db
self.verbose = verbose
self.notification_type = notification_type
self.notification_origin = notification_origin
self.process_id = process_id
<|end_body_0|>
<|body_start_1|>
type_id = self.db.grep_id_from_lookup_table(id_field_name='Notifica... | Notification | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Notification:
def __init__(self, db, verbose, notification_type, notification_origin, process_id):
"""Constructor method for the Notification class. :param db : Database class object :type db : object :param verbose : whether to be verbose :type verbose : bool :param notification_type : ... | stack_v2_sparse_classes_10k_train_007848 | 2,669 | no_license | [
{
"docstring": "Constructor method for the Notification class. :param db : Database class object :type db : object :param verbose : whether to be verbose :type verbose : bool :param notification_type : notification type to use for the notification_spool table :type notification_type : str :param notification_or... | 2 | stack_v2_sparse_classes_30k_train_000614 | Implement the Python class `Notification` described below.
Class description:
Implement the Notification class.
Method signatures and docstrings:
- def __init__(self, db, verbose, notification_type, notification_origin, process_id): Constructor method for the Notification class. :param db : Database class object :typ... | Implement the Python class `Notification` described below.
Class description:
Implement the Notification class.
Method signatures and docstrings:
- def __init__(self, db, verbose, notification_type, notification_origin, process_id): Constructor method for the Notification class. :param db : Database class object :typ... | f9df1b78cd96882009264d7fba122b294c7c6329 | <|skeleton|>
class Notification:
def __init__(self, db, verbose, notification_type, notification_origin, process_id):
"""Constructor method for the Notification class. :param db : Database class object :type db : object :param verbose : whether to be verbose :type verbose : bool :param notification_type : ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Notification:
def __init__(self, db, verbose, notification_type, notification_origin, process_id):
"""Constructor method for the Notification class. :param db : Database class object :type db : object :param verbose : whether to be verbose :type verbose : bool :param notification_type : notification t... | the_stack_v2_python_sparse | python/lib/database_lib/notification.py | gdevenyi/Loris-MRI | train | 0 | |
d9f34536eca44349f6a7c0bf12d4855b55c7f585 | [
"self.describer_model = _load_model(name)\nif level is None:\n n_layers = sum((i.startswith(('meg_net', 'megnet')) for i in self.describer_model.valid_names)) // 3\n level = n_layers\nself.name = name\nself.level = level\nself.mode = mode\nif stats is None:\n stats = ['min', 'max', 'range', 'mean', 'mean_a... | <|body_start_0|>
self.describer_model = _load_model(name)
if level is None:
n_layers = sum((i.startswith(('meg_net', 'megnet')) for i in self.describer_model.valid_names)) // 3
level = n_layers
self.name = name
self.level = level
self.mode = mode
i... | Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the feature-wise statistics. This requires the specification of level 'site_readout': ... | MEGNetStructure | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MEGNetStructure:
"""Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the feature-wise statistics. This requires ... | stack_v2_sparse_classes_10k_train_007849 | 7,639 | permissive | [
{
"docstring": "Args:s name (str or megnet.models.GraphModel): models name keys, megnet models path or a MEGNet GraphModel, if no name is provided, the models will be Eform_MP_2019. mode (str): choose one from ['site_stats', 'site_readout', 'final']. 'site_stats': Calculate the site features, and then use maml.... | 4 | stack_v2_sparse_classes_30k_train_005996 | Implement the Python class `MEGNetStructure` described below.
Class description:
Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the ... | Implement the Python class `MEGNetStructure` described below.
Class description:
Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the ... | 6ae3c7029b939e1183684358a3ae2fef41053be5 | <|skeleton|>
class MEGNetStructure:
"""Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the feature-wise statistics. This requires ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MEGNetStructure:
"""Use megnet pre-trained models as featurizer to get structural features. There are two methods to get structural descriptors from megnet models. mode: 'site_stats': Calculate the site features, and then use maml.utils.stats to compute the feature-wise statistics. This requires the specifica... | the_stack_v2_python_sparse | maml/describers/_megnet.py | materialsvirtuallab/maml | train | 266 |
1a443b76c13e15eed4842416b38f2faae4813523 | [
"while True:\n logger.info('extracting movies from postgres')\n df = (yield)\n if not df.empty:\n genres_ids = id_list(df['id'])\n query = f'\\n SELECT movie_id, array_agg(name) as genre\\n FROM genre\\n JOIN (SELECT * FROM ... | <|body_start_0|>
while True:
logger.info('extracting movies from postgres')
df = (yield)
if not df.empty:
genres_ids = id_list(df['id'])
query = f'\n SELECT movie_id, array_agg(name) as genre\n FROM... | Class for etl process, which moves data from postgres DB to elasticsearch | GenreETL | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenreETL:
"""Class for etl process, which moves data from postgres DB to elasticsearch"""
def extract_first_level_connections(self, data):
"""Coroutine that queries postgres to get genres based on the movies ids gotten in the previous step :param data: :return: dataframe with genres ... | stack_v2_sparse_classes_10k_train_007850 | 2,866 | no_license | [
{
"docstring": "Coroutine that queries postgres to get genres based on the movies ids gotten in the previous step :param data: :return: dataframe with genres data + movies",
"name": "extract_first_level_connections",
"signature": "def extract_first_level_connections(self, data)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_001318 | Implement the Python class `GenreETL` described below.
Class description:
Class for etl process, which moves data from postgres DB to elasticsearch
Method signatures and docstrings:
- def extract_first_level_connections(self, data): Coroutine that queries postgres to get genres based on the movies ids gotten in the p... | Implement the Python class `GenreETL` described below.
Class description:
Class for etl process, which moves data from postgres DB to elasticsearch
Method signatures and docstrings:
- def extract_first_level_connections(self, data): Coroutine that queries postgres to get genres based on the movies ids gotten in the p... | 4ddc8a77e5a9e9bc2a900c7bb6ffbcf5999e8c89 | <|skeleton|>
class GenreETL:
"""Class for etl process, which moves data from postgres DB to elasticsearch"""
def extract_first_level_connections(self, data):
"""Coroutine that queries postgres to get genres based on the movies ids gotten in the previous step :param data: :return: dataframe with genres ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GenreETL:
"""Class for etl process, which moves data from postgres DB to elasticsearch"""
def extract_first_level_connections(self, data):
"""Coroutine that queries postgres to get genres based on the movies ids gotten in the previous step :param data: :return: dataframe with genres data + movies... | the_stack_v2_python_sparse | postgres_to_es/etl_genre.py | maffka123/Admin_panel_sprint_2 | train | 0 |
9e3e9c30f9b8440388e8e6677e1d7cc7b14c7f91 | [
"e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')\nself.assertEqual(e.product_code, 'test product code')\nself.assertEqual(e.description, 'test description')\nself.assertEqual(e.market_price, 'test market price')\nself.assertEqual(e.renta... | <|body_start_0|>
e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')
self.assertEqual(e.product_code, 'test product code')
self.assertEqual(e.description, 'test description')
self.assertEqual(e.market_price, 'test... | FurnitureTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
<|body_0|>
def test_furniture_return(self):
"""Tests Furniture return_as_dictionary"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
e = Furniture('test product... | stack_v2_sparse_classes_10k_train_007851 | 9,076 | no_license | [
{
"docstring": "Tests that Furniture can be initiated",
"name": "test_furniture_init",
"signature": "def test_furniture_init(self)"
},
{
"docstring": "Tests Furniture return_as_dictionary",
"name": "test_furniture_return",
"signature": "def test_furniture_return(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003075 | Implement the Python class `FurnitureTest` described below.
Class description:
Implement the FurnitureTest class.
Method signatures and docstrings:
- def test_furniture_init(self): Tests that Furniture can be initiated
- def test_furniture_return(self): Tests Furniture return_as_dictionary | Implement the Python class `FurnitureTest` described below.
Class description:
Implement the FurnitureTest class.
Method signatures and docstrings:
- def test_furniture_init(self): Tests that Furniture can be initiated
- def test_furniture_return(self): Tests Furniture return_as_dictionary
<|skeleton|>
class Furnitu... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
<|body_0|>
def test_furniture_return(self):
"""Tests Furniture return_as_dictionary"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class FurnitureTest:
def test_furniture_init(self):
"""Tests that Furniture can be initiated"""
e = Furniture('test product code', 'test description', 'test market price', 'test rental price', 'test material', 'test size')
self.assertEqual(e.product_code, 'test product code')
self.as... | the_stack_v2_python_sparse | students/kyle_lehning/Lesson01/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 | |
162d0fdc1f6466634341acc039c5baca02ec03f3 | [
"self.prob = prob\nself.flip_axis = flip_axis\nsuper().__init__()",
"if isinstance(self.flip_axis, (tuple, list)):\n flip_axis = self.flip_axis[random.randint(0, len(self.flip_axis) - 1)]\nelse:\n flip_axis = self.flip_axis\nif random.random() < self.prob:\n img = F.flip_3d(img, axis=flip_axis)\n if l... | <|body_start_0|>
self.prob = prob
self.flip_axis = flip_axis
super().__init__()
<|end_body_0|>
<|body_start_1|>
if isinstance(self.flip_axis, (tuple, list)):
flip_axis = self.flip_axis[random.randint(0, len(self.flip_axis) - 1)]
else:
flip_axis = self.fli... | Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1. | RandomFlip4D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomFlip4D:
"""Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1."""
def __init__(self, prob=0.5, flip_axis=[0, 1, 2]):
"""init"""
<|body_0|>
def __call__(self, img, label=None):
"""Args:... | stack_v2_sparse_classes_10k_train_007852 | 34,927 | permissive | [
{
"docstring": "init",
"name": "__init__",
"signature": "def __init__(self, prob=0.5, flip_axis=[0, 1, 2])"
},
{
"docstring": "Args: img (numpy ndarray): 4D Image to be flipped. label (numpy ndarray): 4D Label to be flipped. Returns: (np.array). Image after transformation.",
"name": "__call_... | 2 | null | Implement the Python class `RandomFlip4D` described below.
Class description:
Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1.
Method signatures and docstrings:
- def __init__(self, prob=0.5, flip_axis=[0, 1, 2]): init
- def __call__(self, im... | Implement the Python class `RandomFlip4D` described below.
Class description:
Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1.
Method signatures and docstrings:
- def __init__(self, prob=0.5, flip_axis=[0, 1, 2]): init
- def __call__(self, im... | 2c8c35a8949fef74599f5ec557d340a14415f20d | <|skeleton|>
class RandomFlip4D:
"""Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1."""
def __init__(self, prob=0.5, flip_axis=[0, 1, 2]):
"""init"""
<|body_0|>
def __call__(self, img, label=None):
"""Args:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RandomFlip4D:
"""Flip an 4D image with a certain probability. Args: prob (float, optional): A probability of vertical flipping. Default: 0.1."""
def __init__(self, prob=0.5, flip_axis=[0, 1, 2]):
"""init"""
self.prob = prob
self.flip_axis = flip_axis
super().__init__()
... | the_stack_v2_python_sparse | contrib/MedicalSeg/medicalseg/transforms/transform.py | PaddlePaddle/PaddleSeg | train | 8,531 |
3db427bc4e54fae296e6d7dc252b4bb05b8fa09b | [
"name = 'RandomSampling'\nsuper(RandomSampling, self).__init__(name, xmin, xmax, use_logger)\nif self.use_logger:\n self.logger = ml.SciopeLogger().get_logger()\n self.logger.info('Random design in {0} dimensions initialized'.format(len(self.xmin)))",
"num_variables = len(self.xmin)\nx = np.random.rand(n, n... | <|body_start_0|>
name = 'RandomSampling'
super(RandomSampling, self).__init__(name, xmin, xmax, use_logger)
if self.use_logger:
self.logger = ml.SciopeLogger().get_logger()
self.logger.info('Random design in {0} dimensions initialized'.format(len(self.xmin)))
<|end_body_0... | Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated points) * logger (a logging object to display/save events - set by derived class... | RandomSampling | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomSampling:
"""Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated points) * logger (a logging object to ... | stack_v2_sparse_classes_10k_train_007853 | 2,961 | permissive | [
{
"docstring": "[summary] Parameters ---------- xmin : vector or 1D array Specifies the lower bound of the hypercube within which the design is generated xmax : vector or 1D array Specifies the upper bound of the hypercube within which the design is generated use_logger : bool, optional controls whether logging... | 2 | stack_v2_sparse_classes_30k_train_001393 | Implement the Python class `RandomSampling` described below.
Class description:
Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated... | Implement the Python class `RandomSampling` described below.
Class description:
Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated... | 5122107dedcee9c39458e83d853ec35f91268780 | <|skeleton|>
class RandomSampling:
"""Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated points) * logger (a logging object to ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RandomSampling:
"""Random Sampling implemented through gpflowopt Properties/variables: * name (RandomSampling) * xmin (lower bound of multi-dimensional space encompassing generated points) * xmax (upper bound of multi-dimensional space encompassing generated points) * logger (a logging object to display/save ... | the_stack_v2_python_sparse | sciope/designs/random_sampling.py | rmjiang7/sciope | train | 0 |
f7567c1aa357965ae781c491098554bbf05d8124 | [
"self.food = food[::-1]\nself.snake = collections.deque([[0, 0]])\nself.dim = [height, width]\nself.score = 0",
"dis = {'U': [-1, 0], 'L': [0, -1], 'R': [0, 1], 'D': [1, 0]}\nnext_pos = [self.snake[-1][0] + dis[direction][0], self.snake[-1][1] + dis[direction][1]]\nif not (0 <= next_pos[0] < self.dim[0] and 0 <= ... | <|body_start_0|>
self.food = food[::-1]
self.snake = collections.deque([[0, 0]])
self.dim = [height, width]
self.score = 0
<|end_body_0|>
<|body_start_1|>
dis = {'U': [-1, 0], 'L': [0, -1], 'R': [0, 1], 'D': [1, 0]}
next_pos = [self.snake[-1][0] + dis[direction][0], self... | SnakeGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_10k_train_007854 | 1,880 | no_license | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :type height: int :type food: List[List[int]]",
... | 2 | stack_v2_sparse_classes_30k_train_002800 | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width, height, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E... | c33559dc5e0bf6879bb3462ab65a9446a66d19f6 | <|skeleton|>
class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :typ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width, height, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]. :type width: int :... | the_stack_v2_python_sparse | 353.py | htl1126/leetcode | train | 7 | |
eda308e80ef9f67f76eb58bcff984e82e9b8b21f | [
"super(lsf_sm, self).check()\nif 'WALLTIME' not in PAR:\n setattr(PAR, 'WALLTIME', 30.0)\nif 'LSFARGS' not in PAR:\n setattr(PAR, 'LSFARGS', '')",
"unix.mkdir(PATH.OUTPUT)\nunix.cd(PATH.OUTPUT)\nunix.mkdir(PATH.SUBMIT + '/' + 'output.lsf')\nself.checkpoint()\nunix.run('bsub ' + '%s ' % PAR.LSFARGS + '-J %s ... | <|body_start_0|>
super(lsf_sm, self).check()
if 'WALLTIME' not in PAR:
setattr(PAR, 'WALLTIME', 30.0)
if 'LSFARGS' not in PAR:
setattr(PAR, 'LSFARGS', '')
<|end_body_0|>
<|body_start_1|>
unix.mkdir(PATH.OUTPUT)
unix.cd(PATH.OUTPUT)
unix.mkdir(PATH... | An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different computing environments. Intermediate files are written to a global scratch p... | lsf_sm | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class lsf_sm:
"""An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different computing environments. Intermediate files... | stack_v2_sparse_classes_10k_train_007855 | 2,039 | permissive | [
{
"docstring": "Checks parameters and paths",
"name": "check",
"signature": "def check(self)"
},
{
"docstring": "Submits workflow",
"name": "submit",
"signature": "def submit(self, workflow)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000607 | Implement the Python class `lsf_sm` described below.
Class description:
An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different com... | Implement the Python class `lsf_sm` described below.
Class description:
An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different com... | 47725866ac516767c9eb536f4a0e86c7c0b97482 | <|skeleton|>
class lsf_sm:
"""An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different computing environments. Intermediate files... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class lsf_sm:
"""An interface through which to submit workflows, run tasks in serial or parallel, and perform other system functions. By hiding environment details behind a python interface layer, these classes provide a consistent command set across different computing environments. Intermediate files are written ... | the_stack_v2_python_sparse | seisflows/system/lsf_sm.py | yanhuay/seisflows | train | 1 |
8d7b3cf0b1e2a111e3d8a82569e91076c37a4e87 | [
"objs = IndivRecord.objects.distinct('discipline').order_by('discipline')\nfor obj in objs:\n obj.titel = disc2str[obj.discipline]\n obj.img_src = DISCIPLINE_TO_ICON[obj.discipline]\n obj.tekst = 'Toon alle verbeterbare records van de discipline %s.' % obj.titel\n url_disc = disc2url[obj.discipline]\n ... | <|body_start_0|>
objs = IndivRecord.objects.distinct('discipline').order_by('discipline')
for obj in objs:
obj.titel = disc2str[obj.discipline]
obj.img_src = DISCIPLINE_TO_ICON[obj.discipline]
obj.tekst = 'Toon alle verbeterbare records van de discipline %s.' % obj.ti... | Deze view laat de gebruiker een discipline kiezen | RecordsVerbeterbaarKiesDisc | [
"BSD-3-Clause-Clear"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecordsVerbeterbaarKiesDisc:
"""Deze view laat de gebruiker een discipline kiezen"""
def get_queryset(self):
"""called by the template system to get the queryset or list of objects for the template"""
<|body_0|>
def get_context_data(self, **kwargs):
"""called by ... | stack_v2_sparse_classes_10k_train_007856 | 8,410 | permissive | [
{
"docstring": "called by the template system to get the queryset or list of objects for the template",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "called by the template system to get the context data for the template",
"name": "get_context_data",
"s... | 2 | null | Implement the Python class `RecordsVerbeterbaarKiesDisc` described below.
Class description:
Deze view laat de gebruiker een discipline kiezen
Method signatures and docstrings:
- def get_queryset(self): called by the template system to get the queryset or list of objects for the template
- def get_context_data(self, ... | Implement the Python class `RecordsVerbeterbaarKiesDisc` described below.
Class description:
Deze view laat de gebruiker een discipline kiezen
Method signatures and docstrings:
- def get_queryset(self): called by the template system to get the queryset or list of objects for the template
- def get_context_data(self, ... | 5ed38165a231f0caa56f67e8faf2dd074916e500 | <|skeleton|>
class RecordsVerbeterbaarKiesDisc:
"""Deze view laat de gebruiker een discipline kiezen"""
def get_queryset(self):
"""called by the template system to get the queryset or list of objects for the template"""
<|body_0|>
def get_context_data(self, **kwargs):
"""called by ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RecordsVerbeterbaarKiesDisc:
"""Deze view laat de gebruiker een discipline kiezen"""
def get_queryset(self):
"""called by the template system to get the queryset or list of objects for the template"""
objs = IndivRecord.objects.distinct('discipline').order_by('discipline')
for obj... | the_stack_v2_python_sparse | Records/views_verbeterbaar.py | RamonvdW/nhb-apps | train | 2 |
99e795009b80a64a729c3884b487c1440dd383c0 | [
"db_session = get_db_session(db_session)\nif status is UserStatuses.Pending:\n return db_session.query(UserPending)\nif status is None:\n return db_session.query(cls.model)\nquery = db_session.query(cls.model)\nusers = []\nif UserStatuses.Pending in status:\n users = list(db_session.query(UserPending))\n ... | <|body_start_0|>
db_session = get_db_session(db_session)
if status is UserStatuses.Pending:
return db_session.query(UserPending)
if status is None:
return db_session.query(cls.model)
query = db_session.query(cls.model)
users = []
if UserStatuses.Pe... | Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with any other :class:`UserStatuses` members, or through the *all* representation, the retu... | UserSearchService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserSearchService:
"""Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with any other :class:`UserStatuses` members, ... | stack_v2_sparse_classes_10k_train_007857 | 42,346 | permissive | [
{
"docstring": "Search for appropriate :class:`User` and/or :class:`UserPending` according to specified :class:`UserStatuses`. When the :paramref:`status` is ``None``, *normal* retrieval of all non-pending :class:`User` is executed, as if directly using the :class:`UserService` implementation. Otherwise, a comb... | 3 | stack_v2_sparse_classes_30k_test_000012 | Implement the Python class `UserSearchService` described below.
Class description:
Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with an... | Implement the Python class `UserSearchService` described below.
Class description:
Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with an... | f9b00c6142372aff96fd0edf0537c8b383fd5ee9 | <|skeleton|>
class UserSearchService:
"""Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with any other :class:`UserStatuses` members, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class UserSearchService:
"""Extends the :mod:`ziggurat_foundations` :class:`UserService` with additional features provided by `Magpie`. .. note:: For any search result where parameter ``status`` is equal to or contains :attr:`UserStatuses.Pending` combined with any other :class:`UserStatuses` members, or through th... | the_stack_v2_python_sparse | magpie/models.py | Ouranosinc/Magpie | train | 2 |
3312127a5ca9af17720696d0f5af8e7cc56b1034 | [
"res = []\n\ndef preOrder(root):\n if not root:\n res.append('#')\n else:\n res.append(str(root.val))\n preOrder(root.left)\n preOrder(root.right)\npreOrder(root)\nreturn ','.join(res)",
"def helper(l):\n if l[0] == '#':\n l.pop(0)\n return None\n root = TreeN... | <|body_start_0|>
res = []
def preOrder(root):
if not root:
res.append('#')
else:
res.append(str(root.val))
preOrder(root.left)
preOrder(root.right)
preOrder(root)
return ','.join(res)
<|end_body_0|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res = []
def preOrder(root):
... | stack_v2_sparse_classes_10k_train_007858 | 1,827 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data)"
}
] | 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.
- def deserialize(self, data): Decodes your encoded data to tree. | 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.
- def deserialize(self, data): Decodes your encoded data to tree.
<|skeleton|>
class Codec:
def serialize(self, root... | 44765a7d89423b7ec2c159f70b1a6f6e446523c2 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string."""
res = []
def preOrder(root):
if not root:
res.append('#')
else:
res.append(str(root.val))
preOrder(root.left)
preOrder(roo... | the_stack_v2_python_sparse | python/CodingInterviews_2/37_xu-lie-hua-er-cha-shu-lcof.py | Wang-Yann/LeetCodeMe | train | 0 | |
ca29d42d1bed4bac7ffb6edb0e8ab94fd5891b5f | [
"super().__init__()\nself.pos_iou_thr = desc['pos_iou_thr']\nself.neg_iou_thr = desc['neg_iou_thr']\nself.min_pos_iou = desc['min_pos_iou'] if 'min_pos_iou' in desc else 0.0\nself.gt_max_assign_all = desc['gt_max_assign_all'] if 'gt_max_assign_all' in desc else True\nself.ignore_iof_thr = desc['ignore_iof_thr'] if ... | <|body_start_0|>
super().__init__()
self.pos_iou_thr = desc['pos_iou_thr']
self.neg_iou_thr = desc['neg_iou_thr']
self.min_pos_iou = desc['min_pos_iou'] if 'min_pos_iou' in desc else 0.0
self.gt_max_assign_all = desc['gt_max_assign_all'] if 'gt_max_assign_all' in desc else True
... | All negative assigner use max iou. | MaxIoUAllNegAssigner | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MaxIoUAllNegAssigner:
"""All negative assigner use max iou."""
def __init__(self, desc):
"""Init Max iou all neg assigner. :param desc: config dict"""
<|body_0|>
def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None):
"""Assign. :param bboxes:... | stack_v2_sparse_classes_10k_train_007859 | 5,437 | permissive | [
{
"docstring": "Init Max iou all neg assigner. :param desc: config dict",
"name": "__init__",
"signature": "def __init__(self, desc)"
},
{
"docstring": "Assign. :param bboxes: bboxes :param gt_bboxes: ground truth boxes :param gt_bboxes_ignore: ground truth boxes need to be ignored :param gt_lab... | 3 | null | Implement the Python class `MaxIoUAllNegAssigner` described below.
Class description:
All negative assigner use max iou.
Method signatures and docstrings:
- def __init__(self, desc): Init Max iou all neg assigner. :param desc: config dict
- def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None): A... | Implement the Python class `MaxIoUAllNegAssigner` described below.
Class description:
All negative assigner use max iou.
Method signatures and docstrings:
- def __init__(self, desc): Init Max iou all neg assigner. :param desc: config dict
- def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None): A... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class MaxIoUAllNegAssigner:
"""All negative assigner use max iou."""
def __init__(self, desc):
"""Init Max iou all neg assigner. :param desc: config dict"""
<|body_0|>
def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=None):
"""Assign. :param bboxes:... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MaxIoUAllNegAssigner:
"""All negative assigner use max iou."""
def __init__(self, desc):
"""Init Max iou all neg assigner. :param desc: config dict"""
super().__init__()
self.pos_iou_thr = desc['pos_iou_thr']
self.neg_iou_thr = desc['neg_iou_thr']
self.min_pos_iou ... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/utils/bbox_utils/assigner/all_neg_assigner.py | Huawei-Ascend/modelzoo | train | 1 |
0e854a71321f5444b3a2f992ed4427f0f0f830c8 | [
"self.run.start()\ncurrent_stage = self.run.start_stage\ntry:\n intent_input = self.intent_input\n if current_stage == PipelineStage.STT:\n assert self.stt_metadata is not None\n assert self.stt_stream is not None\n intent_input = await self.run.speech_to_text(self.stt_metadata, self.stt_... | <|body_start_0|>
self.run.start()
current_stage = self.run.start_stage
try:
intent_input = self.intent_input
if current_stage == PipelineStage.STT:
assert self.stt_metadata is not None
assert self.stt_stream is not None
inte... | Input to a pipeline run. | PipelineInput | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineInput:
"""Input to a pipeline run."""
async def execute(self) -> None:
"""Run pipeline."""
<|body_0|>
async def validate(self) -> None:
"""Validate pipeline input against start stage."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_10k_train_007860 | 31,871 | permissive | [
{
"docstring": "Run pipeline.",
"name": "execute",
"signature": "async def execute(self) -> None"
},
{
"docstring": "Validate pipeline input against start stage.",
"name": "validate",
"signature": "async def validate(self) -> None"
}
] | 2 | stack_v2_sparse_classes_30k_train_000164 | Implement the Python class `PipelineInput` described below.
Class description:
Input to a pipeline run.
Method signatures and docstrings:
- async def execute(self) -> None: Run pipeline.
- async def validate(self) -> None: Validate pipeline input against start stage. | Implement the Python class `PipelineInput` described below.
Class description:
Input to a pipeline run.
Method signatures and docstrings:
- async def execute(self) -> None: Run pipeline.
- async def validate(self) -> None: Validate pipeline input against start stage.
<|skeleton|>
class PipelineInput:
"""Input to... | 2e65b77b2b5c17919939481f327963abdfdc53f0 | <|skeleton|>
class PipelineInput:
"""Input to a pipeline run."""
async def execute(self) -> None:
"""Run pipeline."""
<|body_0|>
async def validate(self) -> None:
"""Validate pipeline input against start stage."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PipelineInput:
"""Input to a pipeline run."""
async def execute(self) -> None:
"""Run pipeline."""
self.run.start()
current_stage = self.run.start_stage
try:
intent_input = self.intent_input
if current_stage == PipelineStage.STT:
ass... | the_stack_v2_python_sparse | homeassistant/components/assist_pipeline/pipeline.py | konnected-io/home-assistant | train | 24 |
0dede8582813858998aafa1921f7aa86ed0d54e4 | [
"invalid = u'! # $ % ^ & * ( ) = + , : ; \" | ~ / \\\\ \\x00 \\u202a'.split()\nbase = u'User%sName'\nfor c in invalid:\n name = base % c\n assert not user.isValidName(self.request, name)",
"cases = (u' User Name', u'User Name ', u'User Name')\nfor test in cases:\n assert not user.isValidName(self.reque... | <|body_start_0|>
invalid = u'! # $ % ^ & * ( ) = + , : ; " | ~ / \\ \x00 \u202a'.split()
base = u'User%sName'
for c in invalid:
name = base % c
assert not user.isValidName(self.request, name)
<|end_body_0|>
<|body_start_1|>
cases = (u' User Name', u'User Name ', ... | TestIsValidName | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestIsValidName:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
<|body_0|>
def testWhitespace(self):
"""user: isValidName: reject leading, t... | stack_v2_sparse_classes_10k_train_007861 | 11,347 | no_license | [
{
"docstring": "user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax.",
"name": "testNonAlnumCharacters",
"signature": "def testNonAlnumCharacters(self)"
},
{
"docstring": "user: isValidName: reject leading, trailing... | 3 | stack_v2_sparse_classes_30k_train_002415 | Implement the Python class `TestIsValidName` described below.
Class description:
Implement the TestIsValidName class.
Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the synt... | Implement the Python class `TestIsValidName` described below.
Class description:
Implement the TestIsValidName class.
Method signatures and docstrings:
- def testNonAlnumCharacters(self): user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the synt... | d6e801402c4538bdfb34a97cf07153101167c1ec | <|skeleton|>
class TestIsValidName:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
<|body_0|>
def testWhitespace(self):
"""user: isValidName: reject leading, t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestIsValidName:
def testNonAlnumCharacters(self):
"""user: isValidName: reject unicode non alpha numeric characters : and , used in acl rules, we might add more characters to the syntax."""
invalid = u'! # $ % ^ & * ( ) = + , : ; " | ~ / \\ \x00 \u202a'.split()
base = u'User%sName'
... | the_stack_v2_python_sparse | MoinMoin/_tests/test_user.py | happytk/jardin | train | 0 | |
e8e05023d5d3a4d7d689422fe3aae4b55299e097 | [
"new_names_dict = {'old_name_1': 'new_name_1', 'old_name_2': 'new_name_2'}\ndict_to_change = {'old_name_1': 'some_value_1', 'old_name_2': 'some_value_2'}\nchanged_dict = change_dict_keys(new_names_dict, dict_to_change)\nassert changed_dict['new_name_1']\nassert changed_dict['new_name_2']\nassert 'old_name_1' not in... | <|body_start_0|>
new_names_dict = {'old_name_1': 'new_name_1', 'old_name_2': 'new_name_2'}
dict_to_change = {'old_name_1': 'some_value_1', 'old_name_2': 'some_value_2'}
changed_dict = change_dict_keys(new_names_dict, dict_to_change)
assert changed_dict['new_name_1']
assert change... | TestChangeDictKeys | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestChangeDictKeys:
def test_change_dict_keys_expected_format(self):
"""Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted Then - return the dictionary with the new keys"""
<|body_0|>
def test_change_dict_keys_missin... | stack_v2_sparse_classes_10k_train_007862 | 44,285 | permissive | [
{
"docstring": "Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted Then - return the dictionary with the new keys",
"name": "test_change_dict_keys_expected_format",
"signature": "def test_change_dict_keys_expected_format(self)"
},
{
"doc... | 3 | null | Implement the Python class `TestChangeDictKeys` described below.
Class description:
Implement the TestChangeDictKeys class.
Method signatures and docstrings:
- def test_change_dict_keys_expected_format(self): Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted... | Implement the Python class `TestChangeDictKeys` described below.
Class description:
Implement the TestChangeDictKeys class.
Method signatures and docstrings:
- def test_change_dict_keys_expected_format(self): Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestChangeDictKeys:
def test_change_dict_keys_expected_format(self):
"""Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted Then - return the dictionary with the new keys"""
<|body_0|>
def test_change_dict_keys_missin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestChangeDictKeys:
def test_change_dict_keys_expected_format(self):
"""Given - dictionary to be changed - dictionary with new keys' names When - the dictionaries are well formatted Then - return the dictionary with the new keys"""
new_names_dict = {'old_name_1': 'new_name_1', 'old_name_2': 'n... | the_stack_v2_python_sparse | Packs/qualys/Integrations/Qualysv2/Qualysv2_test.py | demisto/content | train | 1,023 | |
e7dbab7330e823a635f7d49d0565782b92884f1f | [
"def gen_next(x, y):\n yield (y, n - 1 - x)\n yield (n - 1 - x, n - 1 - y)\n yield (n - 1 - y, x)\nn = len(matrix)\nif n <= 1:\n return\nfor d in range(0, n // 2):\n for i in range(d, n - d - 1):\n tmp = matrix[d][i]\n for a, b in gen_next(d, i):\n matrix[a][b], tmp = (tmp, m... | <|body_start_0|>
def gen_next(x, y):
yield (y, n - 1 - x)
yield (n - 1 - x, n - 1 - y)
yield (n - 1 - y, x)
n = len(matrix)
if n <= 1:
return
for d in range(0, n // 2):
for i in range(d, n - d - 1):
tmp = matrix[... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace"""
<|body_0|>
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, ... | stack_v2_sparse_classes_10k_train_007863 | 2,631 | no_license | [
{
"docstring": "Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace",
"name": "rotate",
"signature": "def rotate(self, matrix: List[List[int]]) -> None"
},
{
"docstring": "Do not return anything, modify matrix in-place instead.",
"na... | 2 | stack_v2_sparse_classes_30k_train_006928 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace
- def rotate(sel... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotate(self, matrix: List[List[int]]) -> None: Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace
- def rotate(sel... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace"""
<|body_0|>
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def rotate(self, matrix: List[List[int]]) -> None:
"""Do not return anything, modify matrix in-place instead. Time complexity: O(n^2) Space complexity: O(1) inplace"""
def gen_next(x, y):
yield (y, n - 1 - x)
yield (n - 1 - x, n - 1 - y)
yield (n -... | the_stack_v2_python_sparse | leetcode/solved/48_Rotate_Image/solution.py | sungminoh/algorithms | train | 0 | |
7c41143c55293f904525ce0bf5eb7734c14cb5f2 | [
"self.n = n\nself.discount = discount\nself.products = products\nself.f = {}\nfor i in range(len(self.products)):\n self.f[self.products[i]] = i\nself.prices = prices\nself.cnt = 1",
"ans = 0\nfor i in range(len(amount)):\n ans += self.prices[self.f[product[i]]] * amount[i]\nprint(self.cnt)\nif self.cnt % s... | <|body_start_0|>
self.n = n
self.discount = discount
self.products = products
self.f = {}
for i in range(len(self.products)):
self.f[self.products[i]] = i
self.prices = prices
self.cnt = 1
<|end_body_0|>
<|body_start_1|>
ans = 0
for i ... | Cashier | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_10k_train_007864 | 1,021 | no_license | [
{
"docstring": ":type n: int :type discount: int :type products: List[int] :type prices: List[int]",
"name": "__init__",
"signature": "def __init__(self, n, discount, products, prices)"
},
{
"docstring": ":type product: List[int] :type amount: List[int] :rtype: float",
"name": "getBill",
... | 2 | null | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | Implement the Python class `Cashier` described below.
Class description:
Implement the Cashier class.
Method signatures and docstrings:
- def __init__(self, n, discount, products, prices): :type n: int :type discount: int :type products: List[int] :type prices: List[int]
- def getBill(self, product, amount): :type pr... | 67e9daecb7ffd8f7bcb2f120ad892498b1219327 | <|skeleton|>
class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
<|body_0|>
def getBill(self, product, amount):
""":type product: List[int] :type amount: List[int] :rtype: float"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Cashier:
def __init__(self, n, discount, products, prices):
""":type n: int :type discount: int :type products: List[int] :type prices: List[int]"""
self.n = n
self.discount = discount
self.products = products
self.f = {}
for i in range(len(self.products)):
... | the_stack_v2_python_sparse | 比赛/1357. 每隔 n 个顾客打折.py | Comyn-Echo/leeCode | train | 0 | |
8f09ded99e1de928e0f7f0e92dc31a778d31605d | [
"query = '\\n select distinct * where {\\n\\n BIND (\"%s\" AS ?pid)\\n BIND (%s as ?sessionid)\\n BIND (\"%s\" as ?shortname)\\n \\n ?participant austalk:id ?pid .\\n ?rc rdf:type austalk:RecordedComponent .\\n ?rc... | <|body_start_0|>
query = '\n select distinct * where {\n\n BIND ("%s" AS ?pid)\n BIND (%s as ?sessionid)\n BIND ("%s" as ?shortname)\n \n ?participant austalk:id ?pid .\n ?rc rdf:type austalk:RecordedComponent .\n ... | ComponentManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComponentManager:
def get(self, participant_id, session_id, component_id):
"""Return the component for this participant/session/component id or None if none exists participant_id is like 1_123 session_id is 1, 2, 3 component_id is shortname words-1, conversation"""
<|body_0|>
... | stack_v2_sparse_classes_10k_train_007865 | 6,817 | no_license | [
{
"docstring": "Return the component for this participant/session/component id or None if none exists participant_id is like 1_123 session_id is 1, 2, 3 component_id is shortname words-1, conversation",
"name": "get",
"signature": "def get(self, participant_id, session_id, component_id)"
},
{
"d... | 2 | stack_v2_sparse_classes_30k_train_000603 | Implement the Python class `ComponentManager` described below.
Class description:
Implement the ComponentManager class.
Method signatures and docstrings:
- def get(self, participant_id, session_id, component_id): Return the component for this participant/session/component id or None if none exists participant_id is l... | Implement the Python class `ComponentManager` described below.
Class description:
Implement the ComponentManager class.
Method signatures and docstrings:
- def get(self, participant_id, session_id, component_id): Return the component for this participant/session/component id or None if none exists participant_id is l... | 88000a79f0a18c92de0092814de3dbb2409f5515 | <|skeleton|>
class ComponentManager:
def get(self, participant_id, session_id, component_id):
"""Return the component for this participant/session/component id or None if none exists participant_id is like 1_123 session_id is 1, 2, 3 component_id is shortname words-1, conversation"""
<|body_0|>
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ComponentManager:
def get(self, participant_id, session_id, component_id):
"""Return the component for this participant/session/component id or None if none exists participant_id is like 1_123 session_id is 1, 2, 3 component_id is shortname words-1, conversation"""
query = '\n selec... | the_stack_v2_python_sparse | browse/modelspackage/components.py | Alveo/smallasc | train | 0 | |
fd8c7c5eaf409a616faa419c351c99a95f78e6c8 | [
"import itertools\nret = 0\nfor a, b, c in itertools.permutations(A, 3):\n if a < b + c and b < a + c and (c < a + b):\n ret = max(ret, a + b + c)\nreturn ret",
"ret = 0\nA = sorted(A, reverse=True)\nfor i in range(0, len(A)):\n a = A[i]\n for j in range(i + 1, len(A)):\n b = A[j]\n ... | <|body_start_0|>
import itertools
ret = 0
for a, b, c in itertools.permutations(A, 3):
if a < b + c and b < a + c and (c < a + b):
ret = max(ret, a + b + c)
return ret
<|end_body_0|>
<|body_start_1|>
ret = 0
A = sorted(A, reverse=True)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def largestPerimeter(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def largestPerimeter(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
import itertools
ret = 0
for a,... | stack_v2_sparse_classes_10k_train_007866 | 1,183 | no_license | [
{
"docstring": ":type A: List[int] :rtype: int",
"name": "largestPerimeter",
"signature": "def largestPerimeter(self, A)"
},
{
"docstring": ":type A: List[int] :rtype: int",
"name": "largestPerimeter",
"signature": "def largestPerimeter(self, A)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestPerimeter(self, A): :type A: List[int] :rtype: int
- def largestPerimeter(self, A): :type A: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def largestPerimeter(self, A): :type A: List[int] :rtype: int
- def largestPerimeter(self, A): :type A: List[int] :rtype: int
<|skeleton|>
class Solution:
def largestPerime... | d8ed762d1005975f0de4f07760c9671195621c88 | <|skeleton|>
class Solution:
def largestPerimeter(self, A):
""":type A: List[int] :rtype: int"""
<|body_0|>
def largestPerimeter(self, A):
""":type A: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def largestPerimeter(self, A):
""":type A: List[int] :rtype: int"""
import itertools
ret = 0
for a, b, c in itertools.permutations(A, 3):
if a < b + c and b < a + c and (c < a + b):
ret = max(ret, a + b + c)
return ret
def larg... | the_stack_v2_python_sparse | largest-perimeter-triangle/solution.py | uxlsl/leetcode_practice | train | 0 | |
d855ea2ef9fcb7c557bc3e28a610f3d96bb5651a | [
"self._rules = tuple()\nfor rule in rules:\n if rule.matcher is None:\n matcher = BaseMatcher()\n elif isinstance(rule.matcher, BaseMatcher):\n matcher = rule.matcher\n elif isinstance(rule.matcher, basestring):\n matcher = default_matcher(rule.matcher)\n else:\n raise ValueE... | <|body_start_0|>
self._rules = tuple()
for rule in rules:
if rule.matcher is None:
matcher = BaseMatcher()
elif isinstance(rule.matcher, BaseMatcher):
matcher = rule.matcher
elif isinstance(rule.matcher, basestring):
mat... | Rules Manager | RulesManager | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RulesManager:
"""Rules Manager"""
def __init__(self, rules, spider, default_matcher=UrlRegexMatcher):
"""Initialize rules using spider and default matcher"""
<|body_0|>
def get_rule_from_request(self, request):
"""Returns first rule that matches given Request"""
... | stack_v2_sparse_classes_10k_train_007867 | 3,671 | permissive | [
{
"docstring": "Initialize rules using spider and default matcher",
"name": "__init__",
"signature": "def __init__(self, rules, spider, default_matcher=UrlRegexMatcher)"
},
{
"docstring": "Returns first rule that matches given Request",
"name": "get_rule_from_request",
"signature": "def ... | 3 | stack_v2_sparse_classes_30k_train_001332 | Implement the Python class `RulesManager` described below.
Class description:
Rules Manager
Method signatures and docstrings:
- def __init__(self, rules, spider, default_matcher=UrlRegexMatcher): Initialize rules using spider and default matcher
- def get_rule_from_request(self, request): Returns first rule that matc... | Implement the Python class `RulesManager` described below.
Class description:
Rules Manager
Method signatures and docstrings:
- def __init__(self, rules, spider, default_matcher=UrlRegexMatcher): Initialize rules using spider and default matcher
- def get_rule_from_request(self, request): Returns first rule that matc... | 6f82ea19de1e61ef71373817f2ca9687b900744d | <|skeleton|>
class RulesManager:
"""Rules Manager"""
def __init__(self, rules, spider, default_matcher=UrlRegexMatcher):
"""Initialize rules using spider and default matcher"""
<|body_0|>
def get_rule_from_request(self, request):
"""Returns first rule that matches given Request"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RulesManager:
"""Rules Manager"""
def __init__(self, rules, spider, default_matcher=UrlRegexMatcher):
"""Initialize rules using spider and default matcher"""
self._rules = tuple()
for rule in rules:
if rule.matcher is None:
matcher = BaseMatcher()
... | the_stack_v2_python_sparse | scrapy/contrib_exp/crawlspider/rules.py | herberthamaral/scrapy | train | 1 |
63261ab45cee431839087451197539845792fd7a | [
"self.mapping = collections.defaultdict(set)\nfor op in (op for op in graph.get_operations()):\n if op.name.startswith(common.SKIPPED_PREFIXES):\n continue\n for op_input in op.inputs:\n self.mapping[op_input].add(op)",
"result = set()\nfor inp in producer_op.outputs:\n result.update(self.m... | <|body_start_0|>
self.mapping = collections.defaultdict(set)
for op in (op for op in graph.get_operations()):
if op.name.startswith(common.SKIPPED_PREFIXES):
continue
for op_input in op.inputs:
self.mapping[op_input].add(op)
<|end_body_0|>
<|body_... | Holds a mapping from tensor's name to ops that take it as input. | InputToOps | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputToOps:
"""Holds a mapping from tensor's name to ops that take it as input."""
def __init__(self, graph):
"""Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterating over the whole graph. The mapping is of type Dict[str,... | stack_v2_sparse_classes_10k_train_007868 | 2,232 | permissive | [
{
"docstring": "Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterating over the whole graph. The mapping is of type Dict[str, Set[tf.Operation]]. Note: while inserting operations into the graph, we do not update the mapping, assuming that insertion p... | 2 | null | Implement the Python class `InputToOps` described below.
Class description:
Holds a mapping from tensor's name to ops that take it as input.
Method signatures and docstrings:
- def __init__(self, graph): Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterati... | Implement the Python class `InputToOps` described below.
Class description:
Holds a mapping from tensor's name to ops that take it as input.
Method signatures and docstrings:
- def __init__(self, graph): Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterati... | cabf6e4f1970dc14302f87414f170de19944bac2 | <|skeleton|>
class InputToOps:
"""Holds a mapping from tensor's name to ops that take it as input."""
def __init__(self, graph):
"""Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterating over the whole graph. The mapping is of type Dict[str,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InputToOps:
"""Holds a mapping from tensor's name to ops that take it as input."""
def __init__(self, graph):
"""Initializes mapping from tensor's name to ops that take it. Helps find edges between ops faster and avoids iterating over the whole graph. The mapping is of type Dict[str, Set[tf.Opera... | the_stack_v2_python_sparse | Tensorflow/source/tensorflow/contrib/quantize/python/input_to_ops.py | ryfeus/lambda-packs | train | 1,283 |
7f3a0ca70b1fb5927cc4bdf3e35c98b19524a42b | [
"if not root:\n return [None for _ in range(k)]\nn, cur = (0, root)\nwhile cur:\n n += 1\n cur = cur.next\nnums = [n // k] * k\nfor i in range(n % k):\n nums[i] += 1\ncur, res, i = (root, [], 0)\nwhile i < k:\n j, prev = (0, cur)\n res.append(cur)\n while j < nums[i]:\n prev, cur = (cur,... | <|body_start_0|>
if not root:
return [None for _ in range(k)]
n, cur = (0, root)
while cur:
n += 1
cur = cur.next
nums = [n // k] * k
for i in range(n % k):
nums[i] += 1
cur, res, i = (root, [], 0)
while i < k:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def splitListToParts(self, root, k):
""":type root: ListNode :type k: int :rtype: List[ListNode]"""
<|body_0|>
def splitListToPartsCleanCode(self, root, k):
""":type root: ListNode :type k: int :rtype: List[ListNode]"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_10k_train_007869 | 3,965 | no_license | [
{
"docstring": ":type root: ListNode :type k: int :rtype: List[ListNode]",
"name": "splitListToParts",
"signature": "def splitListToParts(self, root, k)"
},
{
"docstring": ":type root: ListNode :type k: int :rtype: List[ListNode]",
"name": "splitListToPartsCleanCode",
"signature": "def s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitListToParts(self, root, k): :type root: ListNode :type k: int :rtype: List[ListNode]
- def splitListToPartsCleanCode(self, root, k): :type root: ListNode :type k: int :r... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitListToParts(self, root, k): :type root: ListNode :type k: int :rtype: List[ListNode]
- def splitListToPartsCleanCode(self, root, k): :type root: ListNode :type k: int :r... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def splitListToParts(self, root, k):
""":type root: ListNode :type k: int :rtype: List[ListNode]"""
<|body_0|>
def splitListToPartsCleanCode(self, root, k):
""":type root: ListNode :type k: int :rtype: List[ListNode]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def splitListToParts(self, root, k):
""":type root: ListNode :type k: int :rtype: List[ListNode]"""
if not root:
return [None for _ in range(k)]
n, cur = (0, root)
while cur:
n += 1
cur = cur.next
nums = [n // k] * k
... | the_stack_v2_python_sparse | S/SplitLinkedListinParts.py | bssrdf/pyleet | train | 2 | |
39f01ab1643286d0d10778342d7146f85a3ca685 | [
"self.d = collections.defaultdict(int)\nself.partial = ''\nself.matches = []\nfor s, t in zip(sentences, times):\n self.d[s] = t",
"if c == '#':\n self.d[self.partial] += 1\n self.partial = ''\n self.matches = []\n return []\nif self.partial == '':\n self.matches = [(-count, s) for s, count in s... | <|body_start_0|>
self.d = collections.defaultdict(int)
self.partial = ''
self.matches = []
for s, t in zip(sentences, times):
self.d[s] = t
<|end_body_0|>
<|body_start_1|>
if c == '#':
self.d[self.partial] += 1
self.partial = ''
se... | AutocompleteSystem | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.d = collections.d... | stack_v2_sparse_classes_10k_train_007870 | 1,219 | no_license | [
{
"docstring": ":type sentences: List[str] :type times: List[int]",
"name": "__init__",
"signature": "def __init__(self, sentences, times)"
},
{
"docstring": ":type c: str :rtype: List[str]",
"name": "input",
"signature": "def input(self, c)"
}
] | 2 | null | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str] | Implement the Python class `AutocompleteSystem` described below.
Class description:
Implement the AutocompleteSystem class.
Method signatures and docstrings:
- def __init__(self, sentences, times): :type sentences: List[str] :type times: List[int]
- def input(self, c): :type c: str :rtype: List[str]
<|skeleton|>
cla... | fe5c6936627c2459731ddda6f67422c217b3cc91 | <|skeleton|>
class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
<|body_0|>
def input(self, c):
""":type c: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AutocompleteSystem:
def __init__(self, sentences, times):
""":type sentences: List[str] :type times: List[int]"""
self.d = collections.defaultdict(int)
self.partial = ''
self.matches = []
for s, t in zip(sentences, times):
self.d[s] = t
def input(self, ... | the_stack_v2_python_sparse | 642. Design Search Autocomplete System/Python 2/solution.py | HarrrrryLi/LeetCode | train | 0 | |
4245fbe8e84e590f9869f8bb546c1a979c22217b | [
"self.height = height\nself.width = width\nself.food = deque()\nself.score = 0\nself.snake = deque()\nself.snake.appendleft([0, 0])\nfor r, c in food:\n self.food.appendleft((r, c))",
"dir = {'U': [-1, 0], 'D': [1, 0], 'L': [0, -1], 'R': [0, 1]}\ncurRow, curCol = self.snake[0]\nnextRow, nextCol = (curRow + dir... | <|body_start_0|>
self.height = height
self.width = width
self.food = deque()
self.score = 0
self.snake = deque()
self.snake.appendleft([0, 0])
for r, c in food:
self.food.appendleft((r, c))
<|end_body_0|>
<|body_start_1|>
dir = {'U': [-1, 0], ... | SnakeGame | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [... | stack_v2_sparse_classes_10k_train_007871 | 3,642 | permissive | [
{
"docstring": "Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0].",
"name": "__init__",
"signature": "def __init__(self, widt... | 2 | stack_v2_sparse_classes_30k_train_005332 | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food p... | Implement the Python class `SnakeGame` described below.
Class description:
Implement the SnakeGame class.
Method signatures and docstrings:
- def __init__(self, width: int, height: int, food): Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food p... | 6a83cb798cc317d1e4357ac6b2b1fbf76fa034fb | <|skeleton|>
class SnakeGame:
def __init__(self, width: int, height: int, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SnakeGame:
def __init__(self, width: int, height: int, food):
"""Initialize your data structure here. @param width - screen width @param height - screen height @param food - A list of food positions E.g food = [[1,1], [1,0]] means the first food is positioned at [1,1], the second is at [1,0]."""
... | the_stack_v2_python_sparse | Month 01/Week 03/Day 07/a.py | KevinKnott/Coding-Review | train | 0 | |
b468362ab150b41326c9f328203652541a2d3b9d | [
"while left >= 0 and right < len(s) and (s[left] == s[right]):\n left -= 1\n right += 1\nreturn right - left - 1",
"if not s or len(s) < 1:\n return ''\nleft = right = 0\nfor index in range(len(s)):\n odd_len = self.expand_center(s, index, index)\n even_len = self.expand_center(s, index, index + 1)... | <|body_start_0|>
while left >= 0 and right < len(s) and (s[left] == s[right]):
left -= 1
right += 1
return right - left - 1
<|end_body_0|>
<|body_start_1|>
if not s or len(s) < 1:
return ''
left = right = 0
for index in range(len(s)):
... | String | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class String:
def expand_center(self, s: str, left: int, right: int) -> int:
""":param s: :param l: :param r: :return:"""
<|body_0|>
def longest_palindromic_substring(self, s: str) -> str:
"""Approach: Expand Center Time Complexity: O(N^2) Space Complexity: O(1) :param s: ... | stack_v2_sparse_classes_10k_train_007872 | 1,441 | no_license | [
{
"docstring": ":param s: :param l: :param r: :return:",
"name": "expand_center",
"signature": "def expand_center(self, s: str, left: int, right: int) -> int"
},
{
"docstring": "Approach: Expand Center Time Complexity: O(N^2) Space Complexity: O(1) :param s: :return:",
"name": "longest_palin... | 2 | null | Implement the Python class `String` described below.
Class description:
Implement the String class.
Method signatures and docstrings:
- def expand_center(self, s: str, left: int, right: int) -> int: :param s: :param l: :param r: :return:
- def longest_palindromic_substring(self, s: str) -> str: Approach: Expand Cente... | Implement the Python class `String` described below.
Class description:
Implement the String class.
Method signatures and docstrings:
- def expand_center(self, s: str, left: int, right: int) -> int: :param s: :param l: :param r: :return:
- def longest_palindromic_substring(self, s: str) -> str: Approach: Expand Cente... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class String:
def expand_center(self, s: str, left: int, right: int) -> int:
""":param s: :param l: :param r: :return:"""
<|body_0|>
def longest_palindromic_substring(self, s: str) -> str:
"""Approach: Expand Center Time Complexity: O(N^2) Space Complexity: O(1) :param s: ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class String:
def expand_center(self, s: str, left: int, right: int) -> int:
""":param s: :param l: :param r: :return:"""
while left >= 0 and right < len(s) and (s[left] == s[right]):
left -= 1
right += 1
return right - left - 1
def longest_palindromic_substring(... | the_stack_v2_python_sparse | revisited__2021/math_and_string/longest_palindromic_substring.py | Shiv2157k/leet_code | train | 1 | |
662acf7cea9d6a7993a3f426fac76ac994df8912 | [
"request = request._request\nuser = getattr(request, 'user', None)\nif not user or user.is_anonymous:\n return None\nself.enforce_csrf(request)\nreturn (user, None)",
"def get_response(request):\n return HttpResponse()\nreason = CSRFCheck(get_response).process_view(request, None, (), {})\nif reason:\n ra... | <|body_start_0|>
request = request._request
user = getattr(request, 'user', None)
if not user or user.is_anonymous:
return None
self.enforce_csrf(request)
return (user, None)
<|end_body_0|>
<|body_start_1|>
def get_response(request):
return HttpRe... | Use Django's session framework for authentication. Allows inactive users. | InactiveSessionAuthentication | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InactiveSessionAuthentication:
"""Use Django's session framework for authentication. Allows inactive users."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
<|body_0|>
def enforce_... | stack_v2_sparse_classes_10k_train_007873 | 11,718 | permissive | [
{
"docstring": "Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`.",
"name": "authenticate",
"signature": "def authenticate(self, request)"
},
{
"docstring": "Enforce CSRF validation for session based authentication.",
"name": "enforce_csrf",
... | 2 | null | Implement the Python class `InactiveSessionAuthentication` described below.
Class description:
Use Django's session framework for authentication. Allows inactive users.
Method signatures and docstrings:
- def authenticate(self, request): Returns a `User` if the request session currently has a logged in user. Otherwis... | Implement the Python class `InactiveSessionAuthentication` described below.
Class description:
Use Django's session framework for authentication. Allows inactive users.
Method signatures and docstrings:
- def authenticate(self, request): Returns a `User` if the request session currently has a logged in user. Otherwis... | 67ec527bfc32c715bf9f29d5e01362c4903aebd2 | <|skeleton|>
class InactiveSessionAuthentication:
"""Use Django's session framework for authentication. Allows inactive users."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
<|body_0|>
def enforce_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InactiveSessionAuthentication:
"""Use Django's session framework for authentication. Allows inactive users."""
def authenticate(self, request):
"""Returns a `User` if the request session currently has a logged in user. Otherwise returns `None`."""
request = request._request
user =... | the_stack_v2_python_sparse | kitsune/sumo/api_utils.py | mozilla/kitsune | train | 1,218 |
07a203c157e3207352b4542eedc76eb993a5dbad | [
"self.entity_description = description\nself._attr_unique_id = f'{DOMAIN}-{description.key}-{inverter.serial_number}'\nself._attr_device_info = device_info\nself._attr_native_value = float(current_value)\nself._inverter: Inverter = inverter",
"await self.entity_description.setter(self._inverter, int(value))\nself... | <|body_start_0|>
self.entity_description = description
self._attr_unique_id = f'{DOMAIN}-{description.key}-{inverter.serial_number}'
self._attr_device_info = device_info
self._attr_native_value = float(current_value)
self._inverter: Inverter = inverter
<|end_body_0|>
<|body_star... | Inverter numeric setting entity. | InverterNumberEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
<|body_0|>
async def... | stack_v2_sparse_classes_10k_train_007874 | 5,018 | permissive | [
{
"docstring": "Initialize the number inverter setting entity.",
"name": "__init__",
"signature": "def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None"
},
{
"docstring": "Set new value.",
"name": "async_set_n... | 2 | null | Implement the Python class `InverterNumberEntity` described below.
Class description:
Inverter numeric setting entity.
Method signatures and docstrings:
- def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None: Initialize the number inve... | Implement the Python class `InverterNumberEntity` described below.
Class description:
Inverter numeric setting entity.
Method signatures and docstrings:
- def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None: Initialize the number inve... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
<|body_0|>
async def... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InverterNumberEntity:
"""Inverter numeric setting entity."""
def __init__(self, device_info: DeviceInfo, description: GoodweNumberEntityDescription, inverter: Inverter, current_value: int) -> None:
"""Initialize the number inverter setting entity."""
self.entity_description = description
... | the_stack_v2_python_sparse | homeassistant/components/goodwe/number.py | home-assistant/core | train | 35,501 |
e273e77b604f23b055b2fa7d8c25d16df4986e8c | [
"for patient in patientDao.fetchAllPatients():\n if patient['id'] == id:\n return patient\napi.abort(404, \"Patient {} doesn't exist\".format(id))",
"patient = self.get(id)\npatientDao.deletePatient(id)\nreturn ('patient {} deleted successfully'.format(id), 200)",
"currPatient = self.get(id)\nupdatedP... | <|body_start_0|>
for patient in patientDao.fetchAllPatients():
if patient['id'] == id:
return patient
api.abort(404, "Patient {} doesn't exist".format(id))
<|end_body_0|>
<|body_start_1|>
patient = self.get(id)
patientDao.deletePatient(id)
return ('pa... | Patient | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Patient:
def get(self, id):
"""get patient by input id"""
<|body_0|>
def delete(self, id):
"""delete a specific patient"""
<|body_1|>
def put(self, id):
"""Update a patient record"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_007875 | 2,957 | no_license | [
{
"docstring": "get patient by input id",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "delete a specific patient",
"name": "delete",
"signature": "def delete(self, id)"
},
{
"docstring": "Update a patient record",
"name": "put",
"signature": "def put... | 3 | stack_v2_sparse_classes_30k_train_003927 | Implement the Python class `Patient` described below.
Class description:
Implement the Patient class.
Method signatures and docstrings:
- def get(self, id): get patient by input id
- def delete(self, id): delete a specific patient
- def put(self, id): Update a patient record | Implement the Python class `Patient` described below.
Class description:
Implement the Patient class.
Method signatures and docstrings:
- def get(self, id): get patient by input id
- def delete(self, id): delete a specific patient
- def put(self, id): Update a patient record
<|skeleton|>
class Patient:
def get(... | d5aa7d822fa6b729a699cccad5a3f83f2d2a3bdb | <|skeleton|>
class Patient:
def get(self, id):
"""get patient by input id"""
<|body_0|>
def delete(self, id):
"""delete a specific patient"""
<|body_1|>
def put(self, id):
"""Update a patient record"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Patient:
def get(self, id):
"""get patient by input id"""
for patient in patientDao.fetchAllPatients():
if patient['id'] == id:
return patient
api.abort(404, "Patient {} doesn't exist".format(id))
def delete(self, id):
"""delete a specific patie... | the_stack_v2_python_sparse | apis/patient.py | Manik-Jain/EMR_API | train | 0 | |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.weight, whisper_layer.self_attn.k_proj.weight, whisper_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.bias, torch.zeros_like(whisper_layer.self_attn.q... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.weight, whisper_layer.self_attn.k_proj.weight, whisper_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([whisper_layer.self_attn.q_proj.bias, torch.ze... | WhisperEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieve... | stack_v2_sparse_classes_10k_train_007876 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, whisper_layer, config)"
... | 2 | stack_v2_sparse_classes_30k_train_006789 | Implement the Python class `WhisperEncoderLayerBetterTransformer` described below.
Class description:
Implement the WhisperEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, whisper_layer, config): A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` imple... | Implement the Python class `WhisperEncoderLayerBetterTransformer` described below.
Class description:
Implement the WhisperEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, whisper_layer, config): A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` imple... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieve... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WhisperEncoderLayerBetterTransformer:
def __init__(self, whisper_layer, config):
"""A simple conversion of the WhisperEncoderLayer to its `BetterTransformer` implementation. Args: whisper_layer (`torch.nn.Module`): The original `WhisperEncoderLayer` where the weights needs to be retrieved."""
... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
ee8f359bb640c4a031ca203cfef6555d929d38ee | [
"super(PreTwoStem, self).__init__()\nself._C = desc.C\nself.stems = nn.ModuleList()\nstem0 = nn.Sequential(nn.Conv2d(3, self._C // 2, kernel_size=3, stride=2, padding=1, bias=False), nn.BatchNorm2d(self._C // 2), nn.ReLU(inplace=True), nn.Conv2d(self._C // 2, self._C, 3, stride=2, padding=1, bias=False), nn.BatchNo... | <|body_start_0|>
super(PreTwoStem, self).__init__()
self._C = desc.C
self.stems = nn.ModuleList()
stem0 = nn.Sequential(nn.Conv2d(3, self._C // 2, kernel_size=3, stride=2, padding=1, bias=False), nn.BatchNorm2d(self._C // 2), nn.ReLU(inplace=True), nn.Conv2d(self._C // 2, self._C, 3, str... | Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config | PreTwoStem | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreTwoStem:
"""Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config"""
def __init__(self, desc):
"""Init PreTwoStem."""
<|body_0|>
def forward(self, x):
"""Forward function of PreTwoStem."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_007877 | 7,297 | permissive | [
{
"docstring": "Init PreTwoStem.",
"name": "__init__",
"signature": "def __init__(self, desc)"
},
{
"docstring": "Forward function of PreTwoStem.",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000830 | Implement the Python class `PreTwoStem` described below.
Class description:
Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config
Method signatures and docstrings:
- def __init__(self, desc): Init PreTwoStem.
- def forward(self, x): Forward function of PreTwoStem. | Implement the Python class `PreTwoStem` described below.
Class description:
Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config
Method signatures and docstrings:
- def __init__(self, desc): Init PreTwoStem.
- def forward(self, x): Forward function of PreTwoStem.
<|skeleton|>
cla... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class PreTwoStem:
"""Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config"""
def __init__(self, desc):
"""Init PreTwoStem."""
<|body_0|>
def forward(self, x):
"""Forward function of PreTwoStem."""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PreTwoStem:
"""Class of two stems convolution. :param desc: description of PreTwoStem :type desc: Config"""
def __init__(self, desc):
"""Init PreTwoStem."""
super(PreTwoStem, self).__init__()
self._C = desc.C
self.stems = nn.ModuleList()
stem0 = nn.Sequential(nn.Co... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/cv/image_classification/Darts_for_TensorFlow/automl/vega/search_space/networks/pytorch/blocks/darts_ops.py | Huawei-Ascend/modelzoo | train | 1 |
5d92ba635398479a1097ad5d99b63cbce43fec2e | [
"try:\n return (ApplicationService.apply_custom_attributes(ApplicationService.get_application(application_id=application_id)), HTTPStatus.OK)\nexcept BusinessException as err:\n return (err.error, err.status_code)",
"application_json = request.get_json()\ntry:\n application_schema = ApplicationUpdateSche... | <|body_start_0|>
try:
return (ApplicationService.apply_custom_attributes(ApplicationService.get_application(application_id=application_id)), HTTPStatus.OK)
except BusinessException as err:
return (err.error, err.status_code)
<|end_body_0|>
<|body_start_1|>
application_js... | Resource for submissions. | ApplicationResourceById | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApplicationResourceById:
"""Resource for submissions."""
def get(application_id):
"""Get application by id."""
<|body_0|>
def put(application_id):
"""Update application details."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
re... | stack_v2_sparse_classes_10k_train_007878 | 12,166 | permissive | [
{
"docstring": "Get application by id.",
"name": "get",
"signature": "def get(application_id)"
},
{
"docstring": "Update application details.",
"name": "put",
"signature": "def put(application_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003074 | Implement the Python class `ApplicationResourceById` described below.
Class description:
Resource for submissions.
Method signatures and docstrings:
- def get(application_id): Get application by id.
- def put(application_id): Update application details. | Implement the Python class `ApplicationResourceById` described below.
Class description:
Resource for submissions.
Method signatures and docstrings:
- def get(application_id): Get application by id.
- def put(application_id): Update application details.
<|skeleton|>
class ApplicationResourceById:
"""Resource for... | a1a447f364d1e7414ccb073b0749920ec3523e4a | <|skeleton|>
class ApplicationResourceById:
"""Resource for submissions."""
def get(application_id):
"""Get application by id."""
<|body_0|>
def put(application_id):
"""Update application details."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ApplicationResourceById:
"""Resource for submissions."""
def get(application_id):
"""Get application by id."""
try:
return (ApplicationService.apply_custom_attributes(ApplicationService.get_application(application_id=application_id)), HTTPStatus.OK)
except BusinessExce... | the_stack_v2_python_sparse | forms-flow-api/src/api/resources/application.py | sumathi-thirumani-aot/forms-flow-ai | train | 0 |
8016ab8ec88e7fd8e3b377e204d83b4949469fb6 | [
"self.server_is_running = server_is_running(port, hostname)\nself.viz = Visdom(port=port) if self.server_is_running else None\nself.env = env_name\nself.plots = {}\nself.plots_ic = defaultdict(int)",
"if not self.server_is_running:\n return\nif x is None:\n x = self.plots_ic[var_name]\n self.plots_ic[var... | <|body_start_0|>
self.server_is_running = server_is_running(port, hostname)
self.viz = Visdom(port=port) if self.server_is_running else None
self.env = env_name
self.plots = {}
self.plots_ic = defaultdict(int)
<|end_body_0|>
<|body_start_1|>
if not self.server_is_running... | VisdomPlotter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VisdomPlotter:
def __init__(self, env_name='main', port=8097, hostname='localhost'):
"""Params: * env_name : str * port : int * hostname : str"""
<|body_0|>
def line_plot(self, var_name, split_name, title_name, x, y, x_label='Epochs'):
"""Params: * var_name : variabl... | stack_v2_sparse_classes_10k_train_007879 | 33,326 | no_license | [
{
"docstring": "Params: * env_name : str * port : int * hostname : str",
"name": "__init__",
"signature": "def __init__(self, env_name='main', port=8097, hostname='localhost')"
},
{
"docstring": "Params: * var_name : variable name (e.g. loss, acc) * split_name : split name (e.g. train, val) * ti... | 5 | stack_v2_sparse_classes_30k_train_004473 | Implement the Python class `VisdomPlotter` described below.
Class description:
Implement the VisdomPlotter class.
Method signatures and docstrings:
- def __init__(self, env_name='main', port=8097, hostname='localhost'): Params: * env_name : str * port : int * hostname : str
- def line_plot(self, var_name, split_name,... | Implement the Python class `VisdomPlotter` described below.
Class description:
Implement the VisdomPlotter class.
Method signatures and docstrings:
- def __init__(self, env_name='main', port=8097, hostname='localhost'): Params: * env_name : str * port : int * hostname : str
- def line_plot(self, var_name, split_name,... | 0eebc122396583eccb05fc2fd9a595cbb554b0de | <|skeleton|>
class VisdomPlotter:
def __init__(self, env_name='main', port=8097, hostname='localhost'):
"""Params: * env_name : str * port : int * hostname : str"""
<|body_0|>
def line_plot(self, var_name, split_name, title_name, x, y, x_label='Epochs'):
"""Params: * var_name : variabl... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VisdomPlotter:
def __init__(self, env_name='main', port=8097, hostname='localhost'):
"""Params: * env_name : str * port : int * hostname : str"""
self.server_is_running = server_is_running(port, hostname)
self.viz = Visdom(port=port) if self.server_is_running else None
self.env... | the_stack_v2_python_sparse | apop/utils.py | thbeucher/ML_pytorch | train | 0 | |
4931febcdd902851eca7b9ac2810955bfea2edd7 | [
"if general_md is None:\n general_md = metadata_info.GeneralMd(name=_MODEL_NAME, description=_MODEL_DESCRIPTION)\nif input_md is None:\n input_md = metadata_info.BertInputTensorsMd(model_buffer, _DEFAULT_ID_NAME, _DEFAULT_MASK_NAME, _DEFAULT_SEGMENT_ID_NAME)\nif output_md is None:\n output_md = metadata_in... | <|body_start_0|>
if general_md is None:
general_md = metadata_info.GeneralMd(name=_MODEL_NAME, description=_MODEL_DESCRIPTION)
if input_md is None:
input_md = metadata_info.BertInputTensorsMd(model_buffer, _DEFAULT_ID_NAME, _DEFAULT_MASK_NAME, _DEFAULT_SEGMENT_ID_NAME)
if... | Writes metadata into the Bert NL classifier. | MetadataWriter | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"GPL-1.0-or-later",
"MIT",
"LGPL-2.0-or-later",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetadataWriter:
"""Writes metadata into the Bert NL classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.BertInputTensorsMd]=None, output_md: Optional[metadata_info.ClassificationTensor... | stack_v2_sparse_classes_10k_train_007880 | 6,756 | permissive | [
{
"docstring": "Creates MetadataWriter based on general/input/output information. Args: model_buffer: valid buffer of the model file. general_md: general information about the model. If not specified, default general metadata will be generated. input_md: input tensor information. If not specified, default input... | 2 | null | Implement the Python class `MetadataWriter` described below.
Class description:
Writes metadata into the Bert NL classifier.
Method signatures and docstrings:
- def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.BertInputTen... | Implement the Python class `MetadataWriter` described below.
Class description:
Writes metadata into the Bert NL classifier.
Method signatures and docstrings:
- def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.BertInputTen... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class MetadataWriter:
"""Writes metadata into the Bert NL classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.BertInputTensorsMd]=None, output_md: Optional[metadata_info.ClassificationTensor... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MetadataWriter:
"""Writes metadata into the Bert NL classifier."""
def create_from_metadata_info(cls, model_buffer: bytearray, general_md: Optional[metadata_info.GeneralMd]=None, input_md: Optional[metadata_info.BertInputTensorsMd]=None, output_md: Optional[metadata_info.ClassificationTensorMd]=None):
... | the_stack_v2_python_sparse | third_party/tflite_support/src/tensorflow_lite_support/metadata/python/metadata_writers/bert_nl_classifier.py | chromium/chromium | train | 17,408 |
dcad37a8101e1054ceb0404e5dcec42041a1f2a3 | [
"BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)\nself.v0 = v0\nself.T = T\nself.a = a\nself.b = b\nself.delta = delta\nself.s0 = s0",
"v = env.k.vehicle.get_speed(self.veh_id)\nlead_id = env.k.vehicle.get_leader(self.veh_id)\nh = env.k.vehicle.get_h... | <|body_start_0|>
BaseController.__init__(self, veh_id, car_following_params, delay=time_delay, fail_safe=fail_safe, noise=noise)
self.v0 = v0
self.T = T
self.a = a
self.b = b
self.delta = delta
self.s0 = s0
<|end_body_0|>
<|body_start_1|>
v = env.k.vehicl... | Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E 62.2 (2000): 1805. Usage ----- See BaseController for usage example. Attributes... | IDMController | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IDMController:
"""Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E 62.2 (2000): 1805. Usage ----- See Bas... | stack_v2_sparse_classes_10k_train_007881 | 17,548 | permissive | [
{
"docstring": "Instantiate an IDM controller.",
"name": "__init__",
"signature": "def __init__(self, veh_id, v0=30, T=1, a=1, b=1.5, delta=4, s0=2, time_delay=0.0, noise=0, fail_safe=None, car_following_params=None)"
},
{
"docstring": "See parent class.",
"name": "get_accel",
"signature... | 2 | stack_v2_sparse_classes_30k_train_003102 | Implement the Python class `IDMController` described below.
Class description:
Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E... | Implement the Python class `IDMController` described below.
Class description:
Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E... | badac3da17f04d8d8ae5691ee8ba2af9d56fac35 | <|skeleton|>
class IDMController:
"""Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E 62.2 (2000): 1805. Usage ----- See Bas... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class IDMController:
"""Intelligent Driver Model (IDM) controller. For more information on this controller, see: Treiber, Martin, Ansgar Hennecke, and Dirk Helbing. "Congested traffic states in empirical observations and microscopic simulations." Physical review E 62.2 (2000): 1805. Usage ----- See BaseController f... | the_stack_v2_python_sparse | flow/controllers/car_following_models.py | parthjaggi/flow | train | 6 |
6f1f6f9c2481a22512d07360ff62d3ee4ff15cd5 | [
"total = sum(nums)\nif total % 2 == 1:\n return False\ntarget = int(total / 2)\ndp = [0] * (total + 1)\nfor num in nums:\n i = target\n while i >= num:\n dp[i] = max(dp[i], dp[i - num] + num)\n i -= 1\n if dp[i] == target:\n return True\nreturn False",
"total = sum(nums)\n... | <|body_start_0|>
total = sum(nums)
if total % 2 == 1:
return False
target = int(total / 2)
dp = [0] * (total + 1)
for num in nums:
i = target
while i >= num:
dp[i] = max(dp[i], dp[i - num] + num)
i -= 1
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def can_partition(self, nums: List[int]) -> bool:
"""数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值"""
<|body_0|>
def can_partition2(self, nums: List[int]) -> bool:
"""数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值"""
<|body_1|>
def partition_helper(self, nums... | stack_v2_sparse_classes_10k_train_007882 | 2,791 | permissive | [
{
"docstring": "数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值",
"name": "can_partition",
"signature": "def can_partition(self, nums: List[int]) -> bool"
},
{
"docstring": "数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值",
"name": "can_partition2",
"signature": "def can_partition2(self, nums: List[int]) ... | 3 | stack_v2_sparse_classes_30k_train_007223 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def can_partition(self, nums: List[int]) -> bool: 数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值
- def can_partition2(self, nums: List[int]) -> bool: 数组是否可以分为两半 Args: nums: 数组 Returns: 布... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def can_partition(self, nums: List[int]) -> bool: 数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值
- def can_partition2(self, nums: List[int]) -> bool: 数组是否可以分为两半 Args: nums: 数组 Returns: 布... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def can_partition(self, nums: List[int]) -> bool:
"""数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值"""
<|body_0|>
def can_partition2(self, nums: List[int]) -> bool:
"""数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值"""
<|body_1|>
def partition_helper(self, nums... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def can_partition(self, nums: List[int]) -> bool:
"""数组是否可以分为两半 Args: nums: 数组 Returns: 布尔值"""
total = sum(nums)
if total % 2 == 1:
return False
target = int(total / 2)
dp = [0] * (total + 1)
for num in nums:
i = target
... | the_stack_v2_python_sparse | src/leetcodepython/array/partition_equal_subset_sum_416.py | zhangyu345293721/leetcode | train | 101 | |
faaabaeb71d1e73aed74372579eb77123fce9c8d | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('bohorqux_peterg04_rocksdan_yfchen', 'bohorqux_peterg04_rocksdan_yfchen')\nurl = 'http://datamechanics.io/data/eileenli_yidingou/Restaurant.json'\nresponse = urllib.request.urlopen(url).read().decode('utf... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bohorqux_peterg04_rocksdan_yfchen', 'bohorqux_peterg04_rocksdan_yfchen')
url = 'http://datamechanics.io/data/eileenli_yidingou/Restaurant.json'
re... | getRestaurants | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_10k_train_007883 | 4,123 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | stack_v2_sparse_classes_30k_train_004039 | Implement the Python class `getRestaurants` described below.
Class description:
Implement the getRestaurants class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | Implement the Python class `getRestaurants` described below.
Class description:
Implement the getRestaurants class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | 97e72731ffadbeae57d7a332decd58706e7c08de | <|skeleton|>
class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class getRestaurants:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('bohorqux_peterg04_rocksdan_yfchen', ... | the_stack_v2_python_sparse | bohorqux_peterg04_rocksdan_yfchen/getRestaurants.py | ROODAY/course-2017-fal-proj | train | 3 | |
3f3512127d680bb5f79a9685decf337d7c91c727 | [
"conn, cursor = get_db_cursor()\nbuild = 'toy_build'\ndatabase = 'scratch/toy.db'\nrun_info = talon.init_run_info(database, build)\ntalon.get_counters(database)\nedge_dict = init_refs.make_edge_dict(cursor)\nlocation_dict = init_refs.make_location_dict(build, cursor)\ntranscript_dict = init_refs.make_transcript_dic... | <|body_start_0|>
conn, cursor = get_db_cursor()
build = 'toy_build'
database = 'scratch/toy.db'
run_info = talon.init_run_info(database, build)
talon.get_counters(database)
edge_dict = init_refs.make_edge_dict(cursor)
location_dict = init_refs.make_location_dict(b... | TestIdentifyISM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestIdentifyISM:
def test_ISM_suffix(self):
"""Example where the transcript is an ISM with suffix"""
<|body_0|>
def test_ISM_prefix(self):
"""Example where the transcript is a prefix ISM with a novel start"""
<|body_1|>
def test_no_match(self):
"... | stack_v2_sparse_classes_10k_train_007884 | 4,995 | permissive | [
{
"docstring": "Example where the transcript is an ISM with suffix",
"name": "test_ISM_suffix",
"signature": "def test_ISM_suffix(self)"
},
{
"docstring": "Example where the transcript is a prefix ISM with a novel start",
"name": "test_ISM_prefix",
"signature": "def test_ISM_prefix(self)... | 3 | stack_v2_sparse_classes_30k_train_003391 | Implement the Python class `TestIdentifyISM` described below.
Class description:
Implement the TestIdentifyISM class.
Method signatures and docstrings:
- def test_ISM_suffix(self): Example where the transcript is an ISM with suffix
- def test_ISM_prefix(self): Example where the transcript is a prefix ISM with a novel... | Implement the Python class `TestIdentifyISM` described below.
Class description:
Implement the TestIdentifyISM class.
Method signatures and docstrings:
- def test_ISM_suffix(self): Example where the transcript is an ISM with suffix
- def test_ISM_prefix(self): Example where the transcript is a prefix ISM with a novel... | 8014faed5f982e5e106ec05239e47d65878e76c3 | <|skeleton|>
class TestIdentifyISM:
def test_ISM_suffix(self):
"""Example where the transcript is an ISM with suffix"""
<|body_0|>
def test_ISM_prefix(self):
"""Example where the transcript is a prefix ISM with a novel start"""
<|body_1|>
def test_no_match(self):
"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestIdentifyISM:
def test_ISM_suffix(self):
"""Example where the transcript is an ISM with suffix"""
conn, cursor = get_db_cursor()
build = 'toy_build'
database = 'scratch/toy.db'
run_info = talon.init_run_info(database, build)
talon.get_counters(database)
... | the_stack_v2_python_sparse | testing_suite/test_ISM_identification.py | kopardev/TALON | train | 0 | |
49919c2323266cadcc59c59e708a976a5f266ba7 | [
"flags.AddParentFlagsToParser(parser)\nparser.add_argument('--location', metavar='LOCATION', required=True, help='Location')\nparser.add_argument('--insight-type', metavar='INSIGHT_TYPE', required=False, help='Insight type to list insights for. Supported insight-types can be found here: https://cloud.google.com/rec... | <|body_start_0|>
flags.AddParentFlagsToParser(parser)
parser.add_argument('--location', metavar='LOCATION', required=True, help='Location')
parser.add_argument('--insight-type', metavar='INSIGHT_TYPE', required=False, help='Insight type to list insights for. Supported insight-types can be found ... | List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: project, billing_account, folder a... | List | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class List:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: pr... | stack_v2_sparse_classes_10k_train_007885 | 6,196 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "Run 'gcloud recommender insight... | 2 | stack_v2_sparse_classes_30k_train_007246 | Implement the Python class `List` described below.
Class description:
List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the followi... | Implement the Python class `List` described below.
Class description:
List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the followi... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class List:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: pr... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class List:
"""List insights for a cloud entity. This command lists all insights for a given cloud entity, location and insight type. Supported insight-types can be found here: https://cloud.google.com/recommender/docs/insights/insight-types. Currently the following cloud_entity_types are supported: project, billin... | the_stack_v2_python_sparse | lib/surface/recommender/insights/list.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
fad45349477c4720b55af5af71e50dfc643c06bd | [
"if not matrix or not matrix[0]:\n return False\nxs, xe, ys, ye = (0, len(matrix), 0, len(matrix[0]))\nwhile True:\n row_s, col_s = (map(lambda line: line[ys], matrix), matrix[xs])\n row_s_index = bisect.bisect_left(row_s, target, xs, xe)\n if row_s_index != xe and row_s[row_s_index] == target:\n ... | <|body_start_0|>
if not matrix or not matrix[0]:
return False
xs, xe, ys, ye = (0, len(matrix), 0, len(matrix[0]))
while True:
row_s, col_s = (map(lambda line: line[ys], matrix), matrix[xs])
row_s_index = bisect.bisect_left(row_s, target, xs, xe)
i... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix2(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k_train_007886 | 2,041 | permissive | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix",
"signature": "def searchMatrix(self, matrix, target)"
},
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix2",
"signature": "def search... | 2 | stack_v2_sparse_classes_30k_train_001362 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix2(self, matrix, target): :type matrix: List[List[int]] :typ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix2(self, matrix, target): :type matrix: List[List[int]] :typ... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix2(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def searchMatrix(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if not matrix or not matrix[0]:
return False
xs, xe, ys, ye = (0, len(matrix), 0, len(matrix[0]))
while True:
row_s, col_s = (map(lambda ... | the_stack_v2_python_sparse | 201-300/231-240/240-search2DArray2/search2DArray2.py | xuychen/Leetcode | train | 0 | |
30d16061e5d35c0b7cf7061e9787f9bf524500e9 | [
"self.current_shoot_params = {'video_file': '', 'audio_file': '', 'merged_file': ''}\nself.current_shot_params = {'file': ''}\nself.current_video_file = ''\nself.current_audio_file = ''\nself.current_merged_file = ''\nself.shoot_formats = {'video': shoot_formats[0], 'audio': shoot_formats[1], 'merged': shoot_format... | <|body_start_0|>
self.current_shoot_params = {'video_file': '', 'audio_file': '', 'merged_file': ''}
self.current_shot_params = {'file': ''}
self.current_video_file = ''
self.current_audio_file = ''
self.current_merged_file = ''
self.shoot_formats = {'video': shoot_format... | Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_system.recordation.RecordManager.merge_audio_and_video` for merging separate au... | Recorder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Recorder:
"""Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_system.recordation.RecordManager.merge_audi... | stack_v2_sparse_classes_10k_train_007887 | 18,130 | permissive | [
{
"docstring": "Initialization method of :class:`t_system.recordation.Recorder` class. Args: shot_format (str): Format of the shot. (jpg, png etc.) shoot_formats (list): Formats of the records for video, audio and merged. camera: Camera object from PiCamera. hearer: Hearer object.",
"name": "__init__",
... | 6 | stack_v2_sparse_classes_30k_train_003437 | Implement the Python class `Recorder` described below.
Class description:
Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_syst... | Implement the Python class `Recorder` described below.
Class description:
Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_syst... | 4cf34572b8f8eac54d6c339f37aa72b6a13d8934 | <|skeleton|>
class Recorder:
"""Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_system.recordation.RecordManager.merge_audi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Recorder:
"""Class to define a recording ability of tracking system. This class provides necessary initiations and functions named :func:`t_system.recordation.RecordManager.start` for creating a Record object and start recording by this object. :func:`t_system.recordation.RecordManager.merge_audio_and_video` ... | the_stack_v2_python_sparse | t_system/recordation.py | LookAtMe-Genius-Cameraman/T_System | train | 9 |
0f3c4d09b7dcc6b293fa1e0701c12a1a6c5fc585 | [
"super().__init__()\nself.d_model = d_model\nself.xscale = math.sqrt(self.d_model)\nself.dropout = nn.Dropout(p=dropout_rate)\nself.pe = None\nself.dtype = dtype\nself.extend_pe(paddle.expand(paddle.zeros([1]), (1, max_len)))",
"if self.pe is not None:\n if paddle.shape(self.pe)[1] >= paddle.shape(x)[1] * 2 - ... | <|body_start_0|>
super().__init__()
self.d_model = d_model
self.xscale = math.sqrt(self.d_model)
self.dropout = nn.Dropout(p=dropout_rate)
self.pe = None
self.dtype = dtype
self.extend_pe(paddle.expand(paddle.zeros([1]), (1, max_len)))
<|end_body_0|>
<|body_start... | Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum input length. | RelPositionalEncoding | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelPositionalEncoding:
"""Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int):... | stack_v2_sparse_classes_10k_train_007888 | 9,302 | permissive | [
{
"docstring": "Construct an PositionalEncoding object.",
"name": "__init__",
"signature": "def __init__(self, d_model, dropout_rate, max_len=5000, dtype='float32')"
},
{
"docstring": "Reset the positional encodings.",
"name": "extend_pe",
"signature": "def extend_pe(self, x)"
},
{
... | 3 | null | Implement the Python class `RelPositionalEncoding` described below.
Class description:
Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rat... | Implement the Python class `RelPositionalEncoding` described below.
Class description:
Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rat... | 17854a04d43c231eff66bfed9d6aa55e94a29e79 | <|skeleton|>
class RelPositionalEncoding:
"""Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int):... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RelPositionalEncoding:
"""Relative positional encoding module (new implementation). Details can be found in https://github.com/espnet/espnet/pull/2816. See : Appendix B in https://arxiv.org/abs/1901.02860 Args: d_model (int): Embedding dimension. dropout_rate (float): Dropout rate. max_len (int): Maximum inpu... | the_stack_v2_python_sparse | paddlespeech/t2s/modules/transformer/embedding.py | anniyanvr/DeepSpeech-1 | train | 0 |
bd3a352089c1a6a8c5b80fabaf252dc2b30bf8be | [
"if self.request.user.is_superuser:\n return self.queryset\nreturn self.queryset.filter(user=self.request.user)",
"instance = self.get_object()\nif instance.contest.publish_date < timezone.now():\n raise exceptions.PermissionDenied('You cannot delete already published submission sets.')\ninstance.submission... | <|body_start_0|>
if self.request.user.is_superuser:
return self.queryset
return self.queryset.filter(user=self.request.user)
<|end_body_0|>
<|body_start_1|>
instance = self.get_object()
if instance.contest.publish_date < timezone.now():
raise exceptions.Permissio... | SubmissionSetViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
<|body_0|>
def destroy(self, request, *args, **kwargs):
"""Destroy the instance... | stack_v2_sparse_classes_10k_train_007889 | 5,658 | permissive | [
{
"docstring": "Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Destroy the instance and all related submissions.",
"name... | 2 | stack_v2_sparse_classes_30k_train_003589 | Implement the Python class `SubmissionSetViewSet` described below.
Class description:
Implement the SubmissionSetViewSet class.
Method signatures and docstrings:
- def get_queryset(self): Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submis... | Implement the Python class `SubmissionSetViewSet` described below.
Class description:
Implement the SubmissionSetViewSet class.
Method signatures and docstrings:
- def get_queryset(self): Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submis... | d9876e37d8057009c10ef0c4d23a2b04d322f4eb | <|skeleton|>
class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
<|body_0|>
def destroy(self, request, *args, **kwargs):
"""Destroy the instance... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SubmissionSetViewSet:
def get_queryset(self):
"""Return queryset for submissions that can be shown to user. Return: * all submissions for already finished contests * user's submissions"""
if self.request.user.is_superuser:
return self.queryset
return self.queryset.filter(us... | the_stack_v2_python_sparse | src/rolca/core/api/views.py | dblenkus/rolca | train | 0 | |
8af40f54ae1e25fee10666d8b576f84e25c4620e | [
"d = {'}': '{', ']': '[', ')': '('}\nstack = []\nfor i in s:\n if d.get(i) is not None:\n if len(stack) == 0 or stack.pop() != d[i]:\n return False\n else:\n stack.append(i)\nif len(stack) == 0:\n return True\nelse:\n return False",
"d = {'}': '{', ']': '[', ')': '('}\nl = lis... | <|body_start_0|>
d = {'}': '{', ']': '[', ')': '('}
stack = []
for i in s:
if d.get(i) is not None:
if len(stack) == 0 or stack.pop() != d[i]:
return False
else:
stack.append(i)
if len(stack) == 0:
re... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def other(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d = {'}': '{', ']': '[', ')': '('}
stack = []
for i in s:
... | stack_v2_sparse_classes_10k_train_007890 | 956 | no_license | [
{
"docstring": ":type s: str :rtype: bool",
"name": "isValid",
"signature": "def isValid(self, s)"
},
{
"docstring": ":type s: str :rtype: bool",
"name": "other",
"signature": "def other(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003161 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def other(self, s): :type s: str :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValid(self, s): :type s: str :rtype: bool
- def other(self, s): :type s: str :rtype: bool
<|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :... | e178f91ebffff06977e8c231de12786a72b3b13d | <|skeleton|>
class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
<|body_0|>
def other(self, s):
""":type s: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isValid(self, s):
""":type s: str :rtype: bool"""
d = {'}': '{', ']': '[', ')': '('}
stack = []
for i in s:
if d.get(i) is not None:
if len(stack) == 0 or stack.pop() != d[i]:
return False
else:
... | the_stack_v2_python_sparse | iamsochun/Leetcode20.py | moonlight035/algorithm | train | 0 | |
3d3ad799f7567edc33596bba82f96f319225ce12 | [
"if head == None or head.next == None:\n return False\nslow = head\nfast = head.next\nwhile slow != fast:\n if fast == None or fast.next == None:\n return False\n else:\n slow = slow.next\n fast = fast.next.next\nreturn True",
"table = {}\nwhile head != None:\n if head in table.ke... | <|body_start_0|>
if head == None or head.next == None:
return False
slow = head
fast = head.next
while slow != fast:
if fast == None or fast.next == None:
return False
else:
slow = slow.next
fast = fast.n... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycleHash(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if head == None or head.next == None:
... | stack_v2_sparse_classes_10k_train_007891 | 1,205 | permissive | [
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycle",
"signature": "def hasCycle(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: bool",
"name": "hasCycleHash",
"signature": "def hasCycleHash(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000394 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle(self, head): :type head: ListNode :rtype: bool
- def hasCycleHash(self, head): :type head: ListNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hasCycle(self, head): :type head: ListNode :rtype: bool
- def hasCycleHash(self, head): :type head: ListNode :rtype: bool
<|skeleton|>
class Solution:
def hasCycle(self... | 0e4af391274e33a9bb9f999a9032b74d06fc878e | <|skeleton|>
class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
<|body_0|>
def hasCycleHash(self, head):
""":type head: ListNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def hasCycle(self, head):
""":type head: ListNode :rtype: bool"""
if head == None or head.next == None:
return False
slow = head
fast = head.next
while slow != fast:
if fast == None or fast.next == None:
return False
... | the_stack_v2_python_sparse | leetcode/link-list/cycle.py | Gaurav-Pande/DataStructures | train | 6 | |
cdd7d53e7076a12223cfe9a047fa457d007ff587 | [
"self.Id = id\nif transitions == None:\n self.Transitions = []\nself.IsStart = False\nself.IsEnd = False",
"for l in range(len(self.Transitions)):\n conditions = self.Transitions[l].Conditions\n transitionActions = TransitionActions([], [])\n transitionActions.Actions = [action for action in self.Tran... | <|body_start_0|>
self.Id = id
if transitions == None:
self.Transitions = []
self.IsStart = False
self.IsEnd = False
<|end_body_0|>
<|body_start_1|>
for l in range(len(self.Transitions)):
conditions = self.Transitions[l].Conditions
transitionAc... | # PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA | State | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class State:
"""# PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA"""
def __init__(self, id=None, transitions=None):
"""Constructor"""
<|body_0|>
def NextStateWithActions(self, word, charIndex=None, charIndexForward=True):
"""[charIndexForward] is used ... | stack_v2_sparse_classes_10k_train_007892 | 3,795 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, id=None, transitions=None)"
},
{
"docstring": "[charIndexForward] is used to specify the look ahead direction is it forward or backward.",
"name": "NextStateWithActions",
"signature": "def NextStateWithAct... | 2 | stack_v2_sparse_classes_30k_train_000010 | Implement the Python class `State` described below.
Class description:
# PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA
Method signatures and docstrings:
- def __init__(self, id=None, transitions=None): Constructor
- def NextStateWithActions(self, word, charIndex=None, charIndexForward=True): [charI... | Implement the Python class `State` described below.
Class description:
# PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA
Method signatures and docstrings:
- def __init__(self, id=None, transitions=None): Constructor
- def NextStateWithActions(self, word, charIndex=None, charIndexForward=True): [charI... | e02cf223442d50c4b11d926c79133496c79a4405 | <|skeleton|>
class State:
"""# PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA"""
def __init__(self, id=None, transitions=None):
"""Constructor"""
<|body_0|>
def NextStateWithActions(self, word, charIndex=None, charIndexForward=True):
"""[charIndexForward] is used ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class State:
"""# PyUML: Do not remove this line! # XMI_ID:_qzIH5I35Ed-gg8GOK1TmhA"""
def __init__(self, id=None, transitions=None):
"""Constructor"""
self.Id = id
if transitions == None:
self.Transitions = []
self.IsStart = False
self.IsEnd = False
def ... | the_stack_v2_python_sparse | SourceCode/Controllers/Transducers/State.py | Qutuf/Qutuf | train | 112 |
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_10k_train_007893 | 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_005901 | 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_10k | 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 | |
d4ba1cd917884ee1503fe147fe6bb3ed9493e61f | [
"def serialize_core(root):\n str = ''\n if not root:\n str += '$'\n str += ' '\n return\n str += str(root.val)\n str += ' '\n return str + serialize_core(root.left) + serialize_core(root.right)\nif not root:\n return '$ '\nreturn serialize_core(root)",
"if not data:\n ret... | <|body_start_0|>
def serialize_core(root):
str = ''
if not root:
str += '$'
str += ' '
return
str += str(root.val)
str += ' '
return str + serialize_core(root.left) + serialize_core(root.right)
if... | Codec2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec2:
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_10k_train_007894 | 2,353 | 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_000885 | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | Implement the Python class `Codec2` described below.
Class description:
Implement the Codec2 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 :rtyp... | ce29ea836bd20841d69972180273e4d4ec11514d | <|skeleton|>
class Codec2:
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_10k | data/stack_v2_sparse_classes_30k | class Codec2:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def serialize_core(root):
str = ''
if not root:
str += '$'
str += ' '
return
str += str(root.val)
... | the_stack_v2_python_sparse | 37.py | NeilWangziyu/JZOffer | train | 1 | |
0cd2651fcda284073141c63060442ef1dafacbc5 | [
"gerrit_setting = self.config.get('gerrit', None)\nif gerrit_setting is not None:\n return gerrit_setting\nrepo = utils.get_git_repo(self.pod.root)\nif repo is None:\n return False\nfor remote in repo.remotes:\n url = remote.config_reader.get('url')\n result = urllib.parse.urlparse(url)\n if result.n... | <|body_start_0|>
gerrit_setting = self.config.get('gerrit', None)
if gerrit_setting is not None:
return gerrit_setting
repo = utils.get_git_repo(self.pod.root)
if repo is None:
return False
for remote in repo.remotes:
url = remote.config_reader... | Gerrit installer. | GerritInstaller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GerritInstaller:
"""Gerrit installer."""
def should_run(self):
"""Should the installer run?"""
<|body_0|>
def install(self):
"""Install dependencies."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
gerrit_setting = self.config.get('gerrit', None... | stack_v2_sparse_classes_10k_train_007895 | 1,751 | permissive | [
{
"docstring": "Should the installer run?",
"name": "should_run",
"signature": "def should_run(self)"
},
{
"docstring": "Install dependencies.",
"name": "install",
"signature": "def install(self)"
}
] | 2 | null | Implement the Python class `GerritInstaller` described below.
Class description:
Gerrit installer.
Method signatures and docstrings:
- def should_run(self): Should the installer run?
- def install(self): Install dependencies. | Implement the Python class `GerritInstaller` described below.
Class description:
Gerrit installer.
Method signatures and docstrings:
- def should_run(self): Should the installer run?
- def install(self): Install dependencies.
<|skeleton|>
class GerritInstaller:
"""Gerrit installer."""
def should_run(self):
... | 17471c436621ebfd978b51225fa4de05367a53e1 | <|skeleton|>
class GerritInstaller:
"""Gerrit installer."""
def should_run(self):
"""Should the installer run?"""
<|body_0|>
def install(self):
"""Install dependencies."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class GerritInstaller:
"""Gerrit installer."""
def should_run(self):
"""Should the installer run?"""
gerrit_setting = self.config.get('gerrit', None)
if gerrit_setting is not None:
return gerrit_setting
repo = utils.get_git_repo(self.pod.root)
if repo is None... | the_stack_v2_python_sparse | grow/sdk/installers/gerrit_installer.py | grow/grow | train | 352 |
d448ae38e9c60446f77edf25aae476cb7fbe29bd | [
"vim_connection = pecan.request.vim.open_connection()\nvim_connection.send(rpc_request.serialize())\nmsg = vim_connection.receive()\nif msg is None:\n DLOG.error('No response received for %s.' % rpc_request)\n return httplib.INTERNAL_SERVER_ERROR\nresponse = rpc.RPCMessage.deserialize(msg)\nif rpc.RPC_MSG_RES... | <|body_start_0|>
vim_connection = pecan.request.vim.open_connection()
vim_connection.send(rpc_request.serialize())
msg = vim_connection.receive()
if msg is None:
DLOG.error('No response received for %s.' % rpc_request)
return httplib.INTERNAL_SERVER_ERROR
... | Virtualised Resources - Computes Migrate API | ComputeMigrateAPI | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComputeMigrateAPI:
"""Virtualised Resources - Computes Migrate API"""
def _do_migrate(rpc_request):
"""Return an image details"""
<|body_0|>
def post(self, compute_id, request_data):
"""Perform a migrate against a virtual compute resource"""
<|body_1|>
<... | stack_v2_sparse_classes_10k_train_007896 | 23,213 | permissive | [
{
"docstring": "Return an image details",
"name": "_do_migrate",
"signature": "def _do_migrate(rpc_request)"
},
{
"docstring": "Perform a migrate against a virtual compute resource",
"name": "post",
"signature": "def post(self, compute_id, request_data)"
}
] | 2 | null | Implement the Python class `ComputeMigrateAPI` described below.
Class description:
Virtualised Resources - Computes Migrate API
Method signatures and docstrings:
- def _do_migrate(rpc_request): Return an image details
- def post(self, compute_id, request_data): Perform a migrate against a virtual compute resource | Implement the Python class `ComputeMigrateAPI` described below.
Class description:
Virtualised Resources - Computes Migrate API
Method signatures and docstrings:
- def _do_migrate(rpc_request): Return an image details
- def post(self, compute_id, request_data): Perform a migrate against a virtual compute resource
<|... | 6dba3df3e3c4e5f4ae20ae0c4a48ae72e6d6e274 | <|skeleton|>
class ComputeMigrateAPI:
"""Virtualised Resources - Computes Migrate API"""
def _do_migrate(rpc_request):
"""Return an image details"""
<|body_0|>
def post(self, compute_id, request_data):
"""Perform a migrate against a virtual compute resource"""
<|body_1|>
<... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ComputeMigrateAPI:
"""Virtualised Resources - Computes Migrate API"""
def _do_migrate(rpc_request):
"""Return an image details"""
vim_connection = pecan.request.vim.open_connection()
vim_connection.send(rpc_request.serialize())
msg = vim_connection.receive()
if msg... | the_stack_v2_python_sparse | nfv/nfv-vim/nfv_vim/api/controllers/v1/virtualised_resources/_computes_api.py | starlingx/nfv | train | 3 |
8702a664fee7703c48db3aef5d829cd76fe8286f | [
"settings.addListsToRepository('skeinforge_tools.craft_plugins.lash.html', '', self)\nself.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Lash', self, '')\nself.openWikiManualHelpPage = settings.HelpPage().getOpenFromAbsolute('http://www.bits... | <|body_start_0|>
settings.addListsToRepository('skeinforge_tools.craft_plugins.lash.html', '', self)
self.fileNameInput = settings.FileNameInput().getFromFileName(interpret.getGNUTranslatorGcodeFileTypeTuples(), 'Open File for Lash', self, '')
self.openWikiManualHelpPage = settings.HelpPage().ge... | A class to handle the lash settings. | LashRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LashRepository:
"""A class to handle the lash settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Lash button has been clicked."""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_10k_train_007897 | 6,957 | no_license | [
{
"docstring": "Set the default settings, execute title & settings fileName.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Lash button has been clicked.",
"name": "execute",
"signature": "def execute(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002871 | Implement the Python class `LashRepository` described below.
Class description:
A class to handle the lash settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Lash button has been clicked. | Implement the Python class `LashRepository` described below.
Class description:
A class to handle the lash settings.
Method signatures and docstrings:
- def __init__(self): Set the default settings, execute title & settings fileName.
- def execute(self): Lash button has been clicked.
<|skeleton|>
class LashRepositor... | fd69d8e856780c826386dc973ceabcc03623f3e8 | <|skeleton|>
class LashRepository:
"""A class to handle the lash settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
<|body_0|>
def execute(self):
"""Lash button has been clicked."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LashRepository:
"""A class to handle the lash settings."""
def __init__(self):
"""Set the default settings, execute title & settings fileName."""
settings.addListsToRepository('skeinforge_tools.craft_plugins.lash.html', '', self)
self.fileNameInput = settings.FileNameInput().getFr... | the_stack_v2_python_sparse | skeinforge_tools/craft_plugins/lash.py | bmander/skeinforge | train | 34 |
3e11ea23b73cd44233ce95d18c02ed90782b7faf | [
"self._name = name or 'swaption'\nwith tf.name_scope(self._name):\n self._dtype = dtype\n self._expiry_date = dates.convert_to_date_tensor(expiry_date)\n self._swap = swap",
"model = model or rc.InterestRateModelType.LOGNORMAL_RATE\nname = name or self._name + '_price'\nwith tf.name_scope(name):\n swa... | <|body_start_0|>
self._name = name or 'swaption'
with tf.name_scope(self._name):
self._dtype = dtype
self._expiry_date = dates.convert_to_date_tensor(expiry_date)
self._swap = swap
<|end_body_0|>
<|body_start_1|>
model = model or rc.InterestRateModelType.LOGN... | Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive floating rate is called a payer swaption while the swaption that grants the ... | Swaption | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Swaption:
"""Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive floating rate is called a payer swaption... | stack_v2_sparse_classes_10k_train_007898 | 8,660 | permissive | [
{
"docstring": "Initialize a batch of European swaptions. Args: swap: An instance of `InterestRateSwap` specifying the interest rate swaps underlying the swaptions. The batch size of the swaptions being created would be the same as the batch size of the `swap`. expiry_date: An optional rank 1 `DateTensor` speci... | 3 | stack_v2_sparse_classes_30k_train_000555 | Implement the Python class `Swaption` described below.
Class description:
Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive f... | Implement the Python class `Swaption` described below.
Class description:
Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive f... | 0d3a2193c0f2d320b65e602cf01d7a617da484df | <|skeleton|>
class Swaption:
"""Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive floating rate is called a payer swaption... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Swaption:
"""Represents a batch of European Swaptions. A European Swaption is a contract that gives the holder an option to enter a swap contract at a future date at a prespecified fixed rate. A swaption that grants the holder to pay fixed rate and receive floating rate is called a payer swaption while the sw... | the_stack_v2_python_sparse | tf_quant_finance/experimental/instruments/swaption.py | google/tf-quant-finance | train | 4,165 |
1cac1555a7173861e64dcd0166c179adbda9b727 | [
"if compute is None:\n compute = impl.get_runtime().default_ip\nreturn tf_impl.type_factory.custom_int(bits, signed, compute)",
"frac_type = Quant.int(bits=frac, signed=signed, compute=ti.i32)\nif signed:\n scale = range / 2 ** (frac - 1)\nelse:\n scale = range / 2 ** frac\nif compute is None:\n compu... | <|body_start_0|>
if compute is None:
compute = impl.get_runtime().default_ip
return tf_impl.type_factory.custom_int(bits, signed, compute)
<|end_body_0|>
<|body_start_1|>
frac_type = Quant.int(bits=frac, signed=signed, compute=ti.i32)
if signed:
scale = range / 2... | Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf. | Quant | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Quant:
"""Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf."""
def int(bits, signed=False, compute=None):
"""Generates a quantized type for integers. Args: bits (int): Number of bits. signed (bool): Signe... | stack_v2_sparse_classes_10k_train_007899 | 2,606 | permissive | [
{
"docstring": "Generates a quantized type for integers. Args: bits (int): Number of bits. signed (bool): Signed or unsigned. compute (DataType): Type for computation. Returns: DataType: The specified type.",
"name": "int",
"signature": "def int(bits, signed=False, compute=None)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_005678 | Implement the Python class `Quant` described below.
Class description:
Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf.
Method signatures and docstrings:
- def int(bits, signed=False, compute=None): Generates a quantized type for integer... | Implement the Python class `Quant` described below.
Class description:
Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf.
Method signatures and docstrings:
- def int(bits, signed=False, compute=None): Generates a quantized type for integer... | c9b8166d7b019734438232d9b247eb3555e0d6f0 | <|skeleton|>
class Quant:
"""Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf."""
def int(bits, signed=False, compute=None):
"""Generates a quantized type for integers. Args: bits (int): Number of bits. signed (bool): Signe... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Quant:
"""Generator of quantized types. For more details, read https://yuanming.taichi.graphics/publication/2021-quantaichi/quantaichi.pdf."""
def int(bits, signed=False, compute=None):
"""Generates a quantized type for integers. Args: bits (int): Number of bits. signed (bool): Signed or unsigned... | the_stack_v2_python_sparse | python/taichi/lang/quant_impl.py | ljcc0930/taichi | train | 2 |
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