matlok - Python Src Code Datasets (base)
Collection
Python code from leading AI research and tools repositories • 2 items • Updated • 1
Datasets:
name stringlengths 1 152 | class_name stringlengths 1 51 | class_bases stringlengths 0 159 ⌀ | is_member bool 2
classes | args stringlengths 0 804 | class_docstr stringlengths 4 8.19k ⌀ | class_docstr_tok stringlengths 2 11.6k ⌀ | docstr stringlengths 0 11.4k ⌀ | docstr_tok stringlengths 2 13.4k ⌀ | returns stringlengths 0 260 ⌀ | code stringlengths 21 52.4k ⌀ | code_tok stringlengths 33 92.8k ⌀ | lstart int64 1 1.75k | lend int64 5 1.75k | raises stringclasses 16
values | filename stringlengths 5 66 | file_path stringlengths 12 161 | imports stringlengths 0 1.77k | total_objects int64 15 15 | num_classes float64 1 7 ⌀ | num_imports int64 0 14 | num_functions int64 0 15 | num_all_bases float64 0 9 ⌀ | num_methods float64 1 14 ⌀ | num_bases float64 1 7 ⌀ | label_desc stringlengths 69 1.05k | label_desc_len int64 69 1.05k | label_id stringclasses 15
values | __index_level_0__ int64 468 2.35M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
_fit_sklearn_model_with_active_run | global | null | false | pandas_df | null | null | null | null | mlflow | def _fit_sklearn_model_with_active_run(pandas_df):
run_id = mlflow.active_run().info.run_id
_fit_sklearn(pandas_df)
return mlflow.get_run(run_id)
| ["def","_fit_sklearn_model_with_active_run","(","pandas_df",")",":","run_id","=","mlflow.active_run","(",")",".info.run_id","_fit_sklearn","(","pandas_df",")","return","mlflow.get_run","(","run_id",")"] | 32 | 35 | null | test_spark_datasource_autologging_crossframework.py | mlflow/tests/spark/autologging/datasource/test_spark_datasource_autologging_crossframework.py | import time
import numpy
import pytest
from sklearn.linear_model import LinearRegression
import mlflow
import mlflow.spark
from tests.spark.autologging.utils import _assert_spark_data_logged | 15 | null | 7 | 8 | null | null | null | Use image node_id 3 for calling a global function with example usage: _fit_sklearn_model_with_active_run(pandas_df) and returns: mlflow | 135 | node_id 3 | 1,357,874 |
test_super | TestGaussianNoise | unittest | true | self | A unittest class for testing the GaussianNoise postprocessor. | ["A","unittest","class","for","testing","the","GaussianNoise","postprocessor","."] | null | null | null | def test_super(self):
gan = GaussianNoise(scale=0.1)
self.assertTrue(gan.is_fitted)
self.assertFalse(gan._apply_fit)
self.assertTrue(gan._apply_predict)
gan.fit(preds=np.array([0.1, 0.2, 0.3]))
| ["def","test_super","(","self",")",":","gan","=","GaussianNoise","(","scale=0.1",")","self.assertTrue","(","gan.is_fitted",")","self.assertFalse","(","gan._apply_fit",")","self.assertTrue","(","gan._apply_predict",")","gan.fit","(","preds=np.array","(","[","0.1",",","0.2",",","0.3","]",")",")"] | 104 | 109 | null | test_gaussian_noise.py | adversarial-robustness-toolbox/tests/defences/test_gaussian_noise.py | import logging
import unittest
import numpy
from art.defences.postprocessor import GaussianNoise
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 7 for calling the TestGaussianNoise obj's underlying member method code with example usage: obj.test_super() without return types | 147 | node_id 7 | 235,295 |
setUpClass | TestHighConfidence | unittest | true | cls | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | null | null | null | def setUpClass(cls):
(x_train, y_train), (x_test, y_test), _, _ = load_dataset("mnist")
cls.mnist = (x_train, y_train), (x_test, y_test)
| ["def","setUpClass","(","cls",")",":","(","x_train",",","y_train",")",",","(","x_test",",","y_test",")",",","_",",","_","=","load_dataset","(","``","mnist","''",")","cls.mnist","=","(","x_train",",","y_train",")",",","(","x_test",",","y_test",")"] | 37 | 39 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 1 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.setUpClass(cls) without return types | 151 | node_id 1 | 235,296 |
test_ThompsonSamplerInfeasible | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def test_ThompsonSamplerInfeasible(self) -> None:
generator = ThompsonSampler(min_weight=0.9)
generator.fit(
# pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
# bool, float, int, str]]]]` but got `List[List[List[int]]]`.
Xs=self.Xs,
# pyre-fixme[6]: For 2nd par... | ["def","test_ThompsonSamplerInfeasible","(","self",")","-",">","None",":","generator","=","ThompsonSampler","(","min_weight=0.9",")","generator.fit","(","#","pyre-fixme","[","6","]",":","For","1st","param","expected","`","List","[","List","[","List","[","Union","[","None",",","#","bool",",","float",",","int",",","str",... | 174 | 198 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 6 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSamplerInfeasible() without return types | 169 | node_id 6 | 9,540 |
_maybe_clause | global | null | false | clause | null | null | null | null | unknown | def _maybe_clause(clause: Optional[str]) -> Sequence[str]:
return [clause] if clause is not None else []
| ["def","_maybe_clause","(","clause",":","Optional","[","str","]",")","-",">","Sequence","[","str","]",":","return","[","clause","]","if","clause","is","not","None","else","[","]"] | 40 | 41 | null | store_ext.py | tfx/tfx/orchestration/portable/mlmd/store_ext.py | import collections
import itertools
from typing import Callable, Mapping, Optional, Sequence, Union
from tfx.dsl.compiler import compiler_utils
from tfx.dsl.compiler import constants
from tfx.orchestration.experimental.core import constants
from tfx.orchestration.portable.mlmd import event_lib
from tfx.orchestration.po... | 15 | null | 9 | 6 | null | null | null | Use image node_id 2 for calling a global function with example usage: _maybe_clause(clause) and returns: unknown | 112 | node_id 2 | 2,198,856 |
__init__ | EventSievesConfiguration | SievesConfiguration | true | self | null | null | null | null | EventSievesConfiguration | def __init__(self):
super(EventSievesConfiguration, self).__init__()
self.run_evaluation = True
self.sieves_order = [
(RelationType.SAME_HEAD_LEMMA, 1.0),
(RelationType.EXACT_STRING, 1.0),
(RelationType.WIKIPEDIA_DISAMBIGUATION, 0.1),
(RelationType.WORD_EMBEDDING_MATCH, 0.7... | ["def","__init__","(","self",")",":","super","(","EventSievesConfiguration",",","self",")",".__init__","(",")","self.run_evaluation","=","True","self.sieves_order","=","[","(","RelationType.SAME_HEAD_LEMMA",",","1.0",")",",","(","RelationType.EXACT_STRING",",","1.0",")",",","(","RelationType.WIKIPEDIA_DISAMBIGUATION","... | 59 | 78 | null | sieves_config.py | nlp-architect/nlp_architect/models/cross_doc_coref/sieves_config.py | from typing import List, Tuple
from nlp_architect.data.cdc_resources.relations.relation_types_enums import RelationType | 15 | 3 | 2 | 0 | 3 | 1 | 1 | Use image node_id 1 to create a new EventSievesConfiguration object from inherited base classes: SievesConfiguration with example: obj = EventSievesConfiguration() | 163 | node_id 1 | 1,443,098 |
simple_segmentation_example | global | null | false | null | null | null | null | null | def simple_segmentation_example():
"Perfect results!"
parameters = legion_parameters()
parameters.eps = 0.02
parameters.alpha = 0.005
parameters.betta = 0.1
parameters.gamma = 7.0
parameters.teta = 0.9
parameters.lamda = 0.1
parameters.teta_x = -0.5
parameters.teta_p = 7.0
pa... | ["def","simple_segmentation_example","(",")",":","``","Perfect","results","!","''","parameters","=","legion_parameters","(",")","parameters.eps","=","0.02","parameters.alpha","=","0.005","parameters.betta","=","0.1","parameters.gamma","=","7.0","parameters.teta","=","0.9","parameters.lamda","=","0.1","parameters.teta_x... | 94 | 126 | null | legion_examples.py | pyclustering/pyclustering/nnet/examples/legion_examples.py | from pyclustering.utils import draw_dynamics
from pyclustering.nnet.legion import legion_network, legion_parameters
from pyclustering.nnet import * | 15 | null | 3 | 12 | null | null | null | Use image node_id 12 for calling a global function with example usage: simple_segmentation_example() without return types | 121 | node_id 12 | 1,634,375 | |
forward | ConstantGate | torch.nn | true | self,inp | null | null | null | null | idx, score | def forward(self, inp):
idx = torch.zeros(
(inp.shape[0], self.top_k),
dtype=torch.int64,
device=inp.device,
)
score = (
torch.ones((inp.shape[0], 1, self.top_k), device=inp.device)
/ 2
)
return idx, score
| ["def","forward","(","self",",","inp",")",":","idx","=","torch.zeros","(","(","inp.shape","[","0","]",",","self.top_k",")",",","dtype=torch.int64",",","device=inp.device",",",")","score","=","(","torch.ones","(","(","inp.shape","[","0","]",",","1",",","self.top_k",")",",","device=inp.device",")","\/","2",")","return","... | 16 | 20 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | 1 | 7 | 4 | 1 | 2 | 1 | Use image node_id 2 for calling the ConstantGate obj's underlying member method code with example usage: obj.forward(inp) and returns: idx, score | 146 | node_id 2 | 2,201,994 |
__init__ | ConstantGate | torch.nn | true | self,d_model,num_expert,world_size,top_k | null | null | null | null | ConstantGate | def __init__(self, d_model, num_expert, world_size, top_k=1):
super().__init__()
self.top_k = top_k
| ["def","__init__","(","self",",","d_model",",","num_expert",",","world_size",",","top_k=1",")",":","super","(",")",".__init__","(",")","self.top_k","=","top_k"] | 12 | 14 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | 1 | 7 | 4 | 1 | 2 | 1 | Use image node_id 1 to create a new ConstantGate object from inherited base classes: torch.nn with example: obj = ConstantGate(d_model, num_expert, world_size, top_k) | 166 | node_id 1 | 2,201,993 |
test_GetLastPoint | RandomModelTest | TestCase | true | self | null | null | null | null | null | def test_GetLastPoint(self) -> None:
generated_points = np.array([[1, 2, 3], [4, 5, 6]])
RandomModelWithPoints = RandomModel(
generated_points=generated_points
)
result = RandomModelWithPoints._get_last_point()
expected = torch.tensor([[4], [5], [6]])
comparison = result == expected
... | ["def","test_GetLastPoint","(","self",")","-",">","None",":","generated_points","=","np.array","(","[","[","1",",","2",",","3","]",",","[","4",",","5",",","6","]","]",")","RandomModelWithPoints","=","RandomModel","(","generated_points=generated_points",")","result","=","RandomModelWithPoints._get_last_point","(",")","e... | 74 | 81 | null | test_random.py | Ax/ax/models/tests/test_random.py | import numpy
import torch
from ax.models.random.base import RandomModel
from ax.utils.common.testutils import TestCase
from ax.utils.common.typeutils import not_none | 15 | 1 | 5 | 0 | 1 | 8 | 1 | Use image node_id 8 for calling the RandomModelTest obj's underlying member method code with example usage: obj.test_GetLastPoint() without return types | 152 | node_id 8 | 9,517 |
get_config | global | null | false | null | null | null | null | config, args | def get_config():
parser = argparse.ArgumentParser(
"Global Config Argument Parser", allow_abbrev=False
)
parser.add_argument(
"--config_yaml",
required=True,
type=str,
help="the configuration file for this experiment.",
)
parser.add_argument(
"--resum... | ["def","get_config","(",")",":","parser","=","argparse.ArgumentParser","(","``","Global","Config","Argument","Parser","''",",","allow_abbrev=False",")","parser.add_argument","(","``","--","config_yaml","''",",","required=True",",","type=str",",","help=","''","the","configuration","file","for","this","experiment",".","`... | 123 | 138 | null | config.py | OpenPrompt/openprompt/config.py | import argparse
from yacs.config import CfgNode
import sys
from openprompt.utils.utils import check_config_conflicts
from .default_config import get_default_config
from openprompt.utils.logging import logger
import os | 15 | null | 7 | 8 | null | null | null | Use image node_id 8 for calling a global function with example usage: get_config() and returns: config, args | 109 | node_id 8 | 152,524 | |
save_config_to_yaml | global | null | false | config | null | null | null | null | null | def save_config_to_yaml(config):
from contextlib import redirect_stdout
saved_yaml_path = os.path.join(config.logging.path, "config.yaml")
with open(saved_yaml_path, "w") as f:
with redirect_stdout(f):
print(config.dump())
logger.info("Config saved as {}".format(saved_yaml_path))
| ["def","save_config_to_yaml","(","config",")",":","from","contextlib","import","redirect_stdout","saved_yaml_path","=","os.path.join","(","config.logging.path",",","``","config.yaml","''",")","with","open","(","saved_yaml_path",",","``","w","''",")","as","f",":","with","redirect_stdout","(","f",")",":","print","(","con... | 116 | 121 | null | config.py | OpenPrompt/openprompt/config.py | import argparse
from yacs.config import CfgNode
import sys
from openprompt.utils.utils import check_config_conflicts
from .default_config import get_default_config
from openprompt.utils.logging import logger
import os | 15 | null | 7 | 8 | null | null | null | Use image node_id 7 for calling a global function with example usage: save_config_to_yaml(config) without return types | 118 | node_id 7 | 152,523 |
update_cfg_with_argparser | global | null | false | cfg,args,prefix | null | null | null | null | null | def update_cfg_with_argparser(cfg, args, prefix=None):
r"""To support update cfg with command line"""
for key in cfg:
value = cfg[key]
full_key_name = (
prefix + "." + key if prefix is not None else key
)
if isinstance(value, CfgNode):
update_cfg_with_argp... | ["def","update_cfg_with_argparser","(","cfg",",","args",",","prefix=None",")",":","r","''","''","''","To","support","update","cfg","with","command","line","''","''","''","for","key","in","cfg",":","value","=","cfg","[","key","]","full_key_name","=","(","prefix","+","``",".","''","+","key","if","prefix","is","not","None... | 99 | 113 | null | config.py | OpenPrompt/openprompt/config.py | import argparse
from yacs.config import CfgNode
import sys
from openprompt.utils.utils import check_config_conflicts
from .default_config import get_default_config
from openprompt.utils.logging import logger
import os | 15 | null | 7 | 8 | null | null | null | Use image node_id 6 for calling a global function with example usage: update_cfg_with_argparser(cfg, args, prefix) without return types | 135 | node_id 6 | 152,522 |
test_ConvertBounds | RandomModelTest | TestCase | true | self | null | null | null | null | null | def test_ConvertBounds(self) -> None:
bounds = [(1.0, 2.0), (3.0, 4.0), (5.0, 6.0)]
bounds_result = self.random_model._convert_bounds(bounds)
bounds_expected = torch.tensor(
[[1, 3, 5], [2, 4, 6]], dtype=torch.double
)
bounds_comparison = bounds_result == bounds_expected
# pyre-fixme[16]... | ["def","test_ConvertBounds","(","self",")","-",">","None",":","bounds","=","[","(","1.0",",","2.0",")",",","(","3.0",",","4.0",")",",","(","5.0",",","6.0",")","]","bounds_result","=","self.random_model._convert_bounds","(","bounds",")","bounds_expected","=","torch.tensor","(","[","[","1",",","3",",","5","]",",","[","2"... | 63 | 72 | null | test_random.py | Ax/ax/models/tests/test_random.py | import numpy
import torch
from ax.models.random.base import RandomModel
from ax.utils.common.testutils import TestCase
from ax.utils.common.typeutils import not_none | 15 | 1 | 5 | 0 | 1 | 8 | 1 | Use image node_id 7 for calling the RandomModelTest obj's underlying member method code with example usage: obj.test_ConvertBounds() without return types | 153 | node_id 7 | 9,516 |
test_ConvertInequalityConstraints | RandomModelTest | TestCase | true | self | null | null | null | null | null | def test_ConvertInequalityConstraints(self) -> None:
A = np.array([[1, 2], [3, 4]])
b = np.array([[5], [6]])
A_result, b_result = not_none(
self.random_model._convert_inequality_constraints((A, b))
)
A_expected = torch.tensor([[1, 2], [3, 4]], dtype=torch.double)
b_expected = torch.tenso... | ["def","test_ConvertInequalityConstraints","(","self",")","-",">","None",":","A","=","np.array","(","[","[","1",",","2","]",",","[","3",",","4","]","]",")","b","=","np.array","(","[","[","5","]",",","[","6","]","]",")","A_result",",","b_result","=","not_none","(","self.random_model._convert_inequality_constraints","(",... | 49 | 61 | null | test_random.py | Ax/ax/models/tests/test_random.py | import numpy
import torch
from ax.models.random.base import RandomModel
from ax.utils.common.testutils import TestCase
from ax.utils.common.typeutils import not_none | 15 | 1 | 5 | 0 | 1 | 8 | 1 | Use image node_id 6 for calling the RandomModelTest obj's underlying member method code with example usage: obj.test_ConvertInequalityConstraints() without return types | 168 | node_id 6 | 9,515 |
test_ConvertEqualityConstraints | RandomModelTest | TestCase | true | self | null | null | null | null | null | def test_ConvertEqualityConstraints(self) -> None:
fixed_features = {3: 0.7, 1: 0.5}
d = 4
C, c = not_none(
self.random_model._convert_equality_constraints(
d, fixed_features
)
)
c_expected = torch.tensor([[0.5], [0.7]], dtype=torch.double)
C_expected = torch.tensor(
... | ["def","test_ConvertEqualityConstraints","(","self",")","-",">","None",":","fixed_features","=","{","3",":","0.7",",","1",":","0.5","}","d","=","4","C",",","c","=","not_none","(","self.random_model._convert_equality_constraints","(","d",",","fixed_features",")",")","c_expected","=","torch.tensor","(","[","[","0.5","]",... | 35 | 47 | null | test_random.py | Ax/ax/models/tests/test_random.py | import numpy
import torch
from ax.models.random.base import RandomModel
from ax.utils.common.testutils import TestCase
from ax.utils.common.typeutils import not_none | 15 | 1 | 5 | 0 | 1 | 8 | 1 | Use image node_id 5 for calling the RandomModelTest obj's underlying member method code with example usage: obj.test_ConvertEqualityConstraints() without return types | 166 | node_id 5 | 9,514 |
add_cfg_to_argparser | global | null | false | cfg,parser,prefix | null | null | null | null | null | def add_cfg_to_argparser(cfg, parser, prefix=None):
r"""To support argument parser style in addition to yaml style"""
for key in cfg:
value = cfg[key]
full_key_name = (
prefix + "." + key if prefix is not None else key
)
if isinstance(value, CfgNode):
add_... | ["def","add_cfg_to_argparser","(","cfg",",","parser",",","prefix=None",")",":","r","''","''","''","To","support","argument","parser","style","in","addition","to","yaml","style","''","''","''","for","key","in","cfg",":","value","=","cfg","[","key","]","full_key_name","=","(","prefix","+","``",".","''","+","key","if","pr... | 78 | 96 | null | config.py | OpenPrompt/openprompt/config.py | import argparse
from yacs.config import CfgNode
import sys
from openprompt.utils.utils import check_config_conflicts
from .default_config import get_default_config
from openprompt.utils.logging import logger
import os | 15 | null | 7 | 8 | null | null | null | Use image node_id 5 for calling a global function with example usage: add_cfg_to_argparser(cfg, parser, prefix) without return types | 132 | node_id 5 | 152,521 |
_get_node_live_artifacts | global | null | false | store | null | null | null | null | store | def _get_node_live_artifacts(
store: mlmd.MetadataStore,
*,
pipeline_id: str,
node_id: str,
pipeline_run_id: Optional[str] = None,
) -> Sequence[mlmd.proto.Artifact]:
"""Gets all LIVE node artifacts.
Args:
store: A MetadataStore object.
pipeline_id: The pipeline ID.
node_i... | ["def","_get_node_live_artifacts","(","store",":","mlmd.MetadataStore",",","*",",","pipeline_id",":","str",",","node_id",":","str",",","pipeline_run_id",":","Optional","[","str","]","=","None",",",")","-",">","Sequence","[","mlmd.proto.Artifact","]",":","``","''","''","Gets","all","LIVE","node","artifacts",".","Args","... | 44 | 87 | null | store_ext.py | tfx/tfx/orchestration/portable/mlmd/store_ext.py | import collections
import itertools
from typing import Callable, Mapping, Optional, Sequence, Union
from tfx.dsl.compiler import compiler_utils
from tfx.dsl.compiler import constants
from tfx.orchestration.experimental.core import constants
from tfx.orchestration.portable.mlmd import event_lib
from tfx.orchestration.po... | 15 | null | 9 | 6 | null | null | null | Use image node_id 3 for calling a global function with example usage: _get_node_live_artifacts(store) and returns: store | 120 | node_id 3 | 2,198,857 |
get_node_executions | global | null | false | store | null | null | null | null | store | def get_node_executions(
store: mlmd.MetadataStore,
*,
pipeline_id: str,
node_id: str,
pipeline_run_id: Optional[str] = None,
order_by: mlmd.OrderByField = mlmd.OrderByField.ID,
is_asc: bool = True,
execution_states: Optional[
Sequence["mlmd.proto.Execution.State"]
] = None,
... | ["def","get_node_executions","(","store",":","mlmd.MetadataStore",",","*",",","pipeline_id",":","str",",","node_id",":","str",",","pipeline_run_id",":","Optional","[","str","]","=","None",",","order_by",":","mlmd.OrderByField","=","mlmd.OrderByField.ID",",","is_asc",":","bool","=","True",",","execution_states",":","Opt... | 90 | 154 | null | store_ext.py | tfx/tfx/orchestration/portable/mlmd/store_ext.py | import collections
import itertools
from typing import Callable, Mapping, Optional, Sequence, Union
from tfx.dsl.compiler import compiler_utils
from tfx.dsl.compiler import constants
from tfx.orchestration.experimental.core import constants
from tfx.orchestration.portable.mlmd import event_lib
from tfx.orchestration.po... | 15 | null | 9 | 6 | null | null | null | Use image node_id 4 for calling a global function with example usage: get_node_executions(store) and returns: store | 115 | node_id 4 | 2,198,858 |
__init__ | Distribution | object | true | self,generator | Sampling distribution for mystic optimizers
| ["Sampling","distribution","for","mystic","optimizers"] | generate a sampling distribution with interface dist(size=None)
input::
- generator: a 'distribution' method from scipy.stats or numpy.random
- rng: a mystic.random_state object [default: random_state('numpy.random')]
- args: positional arguments for the distribtution object
- kwds: keyword arguments f... | ["generate","a","sampling","distribution","with","interface","dist","(","size=None",")","input",":",":","-","generator",":","a","'distribution","'","method","from","scipy.stats","or","numpy.random","-","rng",":","a","mystic.random_state","object","[","default",":","random_state","(","'numpy.random","'",")","]","-","arg... | Distribution | def __init__(self, generator=None, *args, **kwds):
"""
generate a sampling distribution with interface dist(size=None)
input::
- generator: a 'distribution' method from scipy.stats or numpy.random
- rng: a mystic.random_state object [default: random_state('numpy.random')]
- args: po... | ["def","__init__","(","self",",","generator=None",",","*","args",",","*","*","kwds",")",":","``","''","''","generate","a","sampling","distribution","with","interface","dist","(","size=None",")","input",":",":","-","generator",":","a","'distribution","'","method","from","scipy.stats","or","numpy.random","-","rng",":","a... | 55 | 144 | null | __init__.py | mystic/mystic/math/__init__.py | from .poly import polyeval, poly1d
from .grid import gridpts, samplepts, fillpts
from .approx import almostEqual, tolerance
from .approx import approx_equal
from .None import discrete
from .None import distance | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 1 to create a new Distribution object from inherited base classes: object with example: obj = Distribution(generator) | 135 | node_id 1 | 1,406,721 |
__call__ | Distribution | object | true | self,size | Sampling distribution for mystic optimizers
| ["Sampling","distribution","for","mystic","optimizers"] | generate a sample of given size (tuple) from the distribution | ["generate","a","sample","of","given","size","(","tuple",")","from","the","distribution"] | unknown | def __call__(self, size=None):
"""generate a sample of given size (tuple) from the distribution"""
return self.norm * self.rvs(size)
| ["def","__call__","(","self",",","size=None",")",":","``","''","''","generate","a","sample","of","given","size","(","tuple",")","from","the","distribution","''","''","''","return","self.norm","*","self.rvs","(","size",")"] | 145 | 147 | null | __init__.py | mystic/mystic/math/__init__.py | from .poly import polyeval, poly1d
from .grid import gridpts, samplepts, fillpts
from .approx import almostEqual, tolerance
from .approx import approx_equal
from .None import discrete
from .None import distance | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 2 for calling the Distribution obj's underlying member method code with example usage: obj.__call__(size) and returns: unknown | 144 | node_id 2 | 1,406,722 |
__repr__ | Distribution | object | true | self | Sampling distribution for mystic optimizers
| ["Sampling","distribution","for","mystic","optimizers"] | null | null | self | def __repr__(self):
return self.repr(self.__class__.__name__, self.norm)
| ["def","__repr__","(","self",")",":","return","self.repr","(","self.__class__.__name__",",","self.norm",")"] | 148 | 149 | null | __init__.py | mystic/mystic/math/__init__.py | from .poly import polyeval, poly1d
from .grid import gridpts, samplepts, fillpts
from .approx import almostEqual, tolerance
from .approx import approx_equal
from .None import discrete
from .None import distance | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 3 for calling the Distribution obj's underlying member method code with example usage: obj.__repr__() and returns: self | 137 | node_id 3 | 1,406,723 |
__add__ | Distribution | object | true | self,dist | Sampling distribution for mystic optimizers
| ["Sampling","distribution","for","mystic","optimizers"] | null | null | new | def __add__(self, dist):
if not isinstance(dist, Distribution):
msg = "unsupported operand type(s) for +: '{0}' and '{1}'".format(
self.__class__.__name__, type(dist)
)
raise TypeError(msg)
# add data from multiple distributions
new = Distribution()
first = "{0}".form... | ["def","__add__","(","self",",","dist",")",":","if","not","isinstance","(","dist",",","Distribution",")",":","msg","=","``","unsupported","operand","type","(","s",")","for","+",":","'","{","0","}","'","and","'","{","1","}","'","''",".format","(","self.__class__.__name__",",","type","(","dist",")",")","raise","TypeError... | 150 | 164 | null | __init__.py | mystic/mystic/math/__init__.py | from .poly import polyeval, poly1d
from .grid import gridpts, samplepts, fillpts
from .approx import almostEqual, tolerance
from .approx import approx_equal
from .None import discrete
from .None import distance | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 4 for calling the Distribution obj's underlying member method code with example usage: obj.__add__(dist) and returns: new | 139 | node_id 4 | 1,406,724 |
convert_cfg_to_dict | global | null | false | cfg_node,key_list | null | null | null | null | cfg_node,cfg_dict | def convert_cfg_to_dict(cfg_node, key_list=[]):
"""Convert a config node to dictionary"""
if not isinstance(cfg_node, CfgNode):
if type(cfg_node) not in _VALID_TYPES:
print(
"Key {} with value {} is not a valid type; valid types: {}".format(
".".join(key_l... | ["def","convert_cfg_to_dict","(","cfg_node",",","key_list=","[","]",")",":","``","''","''","Convert","a","config","node","to","dictionary","''","''","''","if","not","isinstance","(","cfg_node",",","CfgNode",")",":","if","type","(","cfg_node",")","not","in","_VALID_TYPES",":","print","(","``","Key","{","}","with","value... | 65 | 76 | null | config.py | OpenPrompt/openprompt/config.py | import argparse
from yacs.config import CfgNode
import sys
from openprompt.utils.utils import check_config_conflicts
from .default_config import get_default_config
from openprompt.utils.logging import logger
import os | 15 | null | 7 | 8 | null | null | null | Use image node_id 4 for calling a global function with example usage: convert_cfg_to_dict(cfg_node, key_list) and returns: cfg_node, cfg_dict | 141 | node_id 4 | 152,520 |
get_live_output_artifacts_of_node_by_output_key | global | null | false | store | null | null | null | null | output_artifacts_by_output_key,dict,dict | def get_live_output_artifacts_of_node_by_output_key(
store: mlmd.MetadataStore,
*,
pipeline_id: str,
node_id: str,
pipeline_run_id: Optional[str] = None,
execution_states: Optional[
Sequence["mlmd.proto.Execution.State"]
] = None,
) -> Mapping[str, Sequence[Sequence[mlmd.proto.Artifa... | ["def","get_live_output_artifacts_of_node_by_output_key","(","store",":","mlmd.MetadataStore",",","*",",","pipeline_id",":","str",",","node_id",":","str",",","pipeline_run_id",":","Optional","[","str","]","=","None",",","execution_states",":","Optional","[","Sequence","[","``","mlmd.proto.Execution.State","''","]","]",... | 157 | 273 | null | store_ext.py | tfx/tfx/orchestration/portable/mlmd/store_ext.py | import collections
import itertools
from typing import Callable, Mapping, Optional, Sequence, Union
from tfx.dsl.compiler import compiler_utils
from tfx.dsl.compiler import constants
from tfx.orchestration.experimental.core import constants
from tfx.orchestration.portable.mlmd import event_lib
from tfx.orchestration.po... | 15 | null | 9 | 6 | null | null | null | Use image node_id 5 for calling a global function with example usage: get_live_output_artifacts_of_node_by_output_key(store) and returns: output_artifacts_by_output_key, dict, dict | 180 | node_id 5 | 2,198,859 |
test_zero_fwd | global | null | false | num_expert,batch_size,d_hidden,world_size | null | null | null | null | null | def test_zero_fwd(
num_expert=2, batch_size=4, d_hidden=8, world_size=1
):
_run_distributed(
"_test_zero_fwd",
1,
{
"num_expert": num_expert,
"batch_size": batch_size,
"d_hidden": d_hidden,
},
script=__file__,
)
| ["def","test_zero_fwd","(","num_expert=2",",","batch_size=4",",","d_hidden=8",",","world_size=1",")",":","_run_distributed","(","``","_test_zero_fwd","''",",","1",",","{","``","num_expert","''",":","num_expert",",","``","batch_size","''",":","batch_size",",","``","d_hidden","''",":","d_hidden",",","}",",","script=__fil... | 23 | 32 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | null | 7 | 4 | null | null | null | Use image node_id 1 for calling a global function with example usage: test_zero_fwd(num_expert, batch_size, d_hidden, world_size) without return types | 150 | node_id 1 | 2,201,995 |
_test_zero_fwd | global | null | false | num_expert,batch_size,d_hidden,world_size | null | null | null | null | null | def _test_zero_fwd(
num_expert=2, batch_size=4, d_hidden=8, world_size=1
):
inp = torch.rand(batch_size, d_hidden).cuda()
gate = torch.zeros(batch_size, dtype=torch.int64).cuda()
x = _fmoe_general_global_forward(
inp, gate, lambda x, y: x, num_expert, world_size
)
| ["def","_test_zero_fwd","(","num_expert=2",",","batch_size=4",",","d_hidden=8",",","world_size=1",")",":","inp","=","torch.rand","(","batch_size",",","d_hidden",")",".cuda","(",")","gate","=","torch.zeros","(","batch_size",",","dtype=torch.int64",")",".cuda","(",")","x","=","_fmoe_general_global_forward","(","inp",",",... | 34 | 38 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | null | 7 | 4 | null | null | null | Use image node_id 2 for calling a global function with example usage: _test_zero_fwd(num_expert, batch_size, d_hidden, world_size) without return types | 151 | node_id 2 | 2,201,996 |
test_zero_transformer | global | null | false | num_expert,batch_size,d_hidden,world_size | null | null | null | null | null | def test_zero_transformer(
num_expert=2, batch_size=4, d_hidden=8, world_size=1
):
_run_distributed(
"_test_zero_transformer",
1,
{
"num_expert": num_expert,
"batch_size": batch_size,
"d_hidden": d_hidden,
},
script=__file__,
)
| ["def","test_zero_transformer","(","num_expert=2",",","batch_size=4",",","d_hidden=8",",","world_size=1",")",":","_run_distributed","(","``","_test_zero_transformer","''",",","1",",","{","``","num_expert","''",":","num_expert",",","``","batch_size","''",":","batch_size",",","``","d_hidden","''",":","d_hidden",",","}","... | 41 | 50 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | null | 7 | 4 | null | null | null | Use image node_id 3 for calling a global function with example usage: test_zero_transformer(num_expert, batch_size, d_hidden, world_size) without return types | 158 | node_id 3 | 2,201,997 |
_test_zero_transformer | global | null | false | num_expert,batch_size,d_hidden,world_size | null | null | null | null | null | def _test_zero_transformer(
num_expert=2, batch_size=4, d_hidden=8, world_size=1
):
inp = torch.rand(batch_size, d_hidden).cuda()
mask = torch.zeros(inp.shape[0], dtype=torch.long)
mask[1] = 1
mask_dict = {1: torch.zeros(d_hidden).cuda()}
model = FMoETransformerMLP(
num_expert,
d... | ["def","_test_zero_transformer","(","num_expert=2",",","batch_size=4",",","d_hidden=8",",","world_size=1",")",":","inp","=","torch.rand","(","batch_size",",","d_hidden",")",".cuda","(",")","mask","=","torch.zeros","(","inp.shape","[","0","]",",","dtype=torch.long",")","mask","[","1","]","=","1","mask_dict","=","{","1",... | 52 | 61 | null | test_zero.py | thu-pacman-faster-moe/tests/test_zero.py | import os
import sys
import json
import torch
from fmoe.layers import _fmoe_general_global_forward
from fmoe import FMoETransformerMLP
from test_ddp import _run_distributed | 15 | null | 7 | 4 | null | null | null | Use image node_id 4 for calling a global function with example usage: _test_zero_transformer(num_expert, batch_size, d_hidden, world_size) without return types | 159 | node_id 4 | 2,201,998 |
setUp | TestHighConfidence | unittest | true | self | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | null | null | null | def setUp(self):
master_seed(seed=1234)
| ["def","setUp","(","self",")",":","master_seed","(","seed=1234",")"] | 41 | 42 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 2 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.setUp() without return types | 143 | node_id 2 | 235,297 |
test_difference | TestIntervalIndex | null | true | self,closed,sort | null | null | null | null | null | def test_difference(self, closed, sort):
index = IntervalIndex.from_arrays(
[1, 0, 3, 2], [1, 2, 3, 4], closed=closed
)
result = index.difference(index[:1], sort=sort)
expected = index[1:]
if sort is None:
expected = expected.sort_values()
tm.assert_index_equal(result, expected)
... | ["def","test_difference","(","self",",","closed",",","sort",")",":","index","=","IntervalIndex.from_arrays","(","[","1",",","0",",","3",",","2","]",",","[","1",",","2",",","3",",","4","]",",","closed=closed",")","result","=","index.difference","(","index","[",":1","]",",","sort=sort",")","expected","=","index","[","1",... | 131 | 149 | null | test_setops.py | pandas/pandas/tests/indexes/interval/test_setops.py | import numpy
import pytest
from pandas import Index, IntervalIndex, Timestamp, interval_range
import pandas._testing | 15 | 1 | 4 | 2 | 0 | 8 | null | Use image node_id 6 for calling the TestIntervalIndex obj's underlying member method code with example usage: obj.test_difference(closed, sort) without return types | 164 | node_id 6 | 1,514,638 |
test_ThompsonSamplerUniformWeights | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def test_ThompsonSamplerUniformWeights(self) -> None:
generator = ThompsonSampler(min_weight=0.0, uniform_weights=True)
generator.fit(
# pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
# bool, float, int, str]]]]` but got `List[List[List[int]]]`.
Xs=self.Xs,
# ... | ["def","test_ThompsonSamplerUniformWeights","(","self",")","-",">","None",":","generator","=","ThompsonSampler","(","min_weight=0.0",",","uniform_weights=True",")","generator.fit","(","#","pyre-fixme","[","6","]",":","For","1st","param","expected","`","List","[","List","[","List","[","Union","[","None",",","#","bool","... | 146 | 172 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 5 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSamplerUniformWeights() without return types | 173 | node_id 5 | 9,539 |
test_ThompsonSamplerMinWeight | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def test_ThompsonSamplerMinWeight(self) -> None:
generator = ThompsonSampler(min_weight=0.01)
generator.fit(
# pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
# bool, float, int, str]]]]` but got `List[List[List[int]]]`.
Xs=self.Xs,
# pyre-fixme[6]: For 2nd par... | ["def","test_ThompsonSamplerMinWeight","(","self",")","-",">","None",":","generator","=","ThompsonSampler","(","min_weight=0.01",")","generator.fit","(","#","pyre-fixme","[","6","]",":","For","1st","param","expected","`","List","[","List","[","List","[","Union","[","None",",","#","bool",",","float",",","int",",","str",... | 116 | 144 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 4 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSamplerMinWeight() without return types | 168 | node_id 4 | 9,538 |
test_ThompsonSamplerValidation | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def test_ThompsonSamplerValidation(self) -> None:
generator = ThompsonSampler(min_weight=0.01)
# all Xs are not the same
with self.assertRaises(ValueError):
generator.fit(
Xs=[
[[1, 1], [2, 2], [3, 3], [4, 4]],
[[1, 1], [2, 2], [4, 4]],
],
... | ["def","test_ThompsonSamplerValidation","(","self",")","-",">","None",":","generator","=","ThompsonSampler","(","min_weight=0.01",")","#","all","Xs","are","not","the","same","with","self.assertRaises","(","ValueError",")",":","generator.fit","(","Xs=","[","[","[","1",",","1","]",",","[","2",",","2","]",",","[","3",",",... | 60 | 114 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 3 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSamplerValidation() without return types | 169 | node_id 3 | 9,537 |
test_ThompsonSampler | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def test_ThompsonSampler(self) -> None:
generator = ThompsonSampler(min_weight=0.0)
generator.fit(
# pyre-fixme[6]: For 1st param expected `List[List[List[Union[None,
# bool, float, int, str]]]]` but got `List[List[List[int]]]`.
Xs=self.Xs,
# pyre-fixme[6]: For 2nd param expecte... | ["def","test_ThompsonSampler","(","self",")","-",">","None",":","generator","=","ThompsonSampler","(","min_weight=0.0",")","generator.fit","(","#","pyre-fixme","[","6","]",":","For","1st","param","expected","`","List","[","List","[","List","[","Union","[","None",",","#","bool",",","float",",","int",",","str","]","]","]... | 29 | 58 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 2 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.test_ThompsonSampler() without return types | 159 | node_id 2 | 9,536 |
setUp | ThompsonSamplerTest | TestCase | true | self | null | null | null | null | null | def setUp(self) -> None:
self.Xs = [
[[1, 1], [2, 2], [3, 3], [4, 4]]
] # 4 arms, each of dimensionality 2
self.Ys = [[1, 2, 3, 4]]
self.Yvars = [[1, 1, 1, 1]]
self.parameter_values = [[1, 2, 3, 4], [1, 2, 3, 4]]
self.outcome_names = ["x", "y"] # not used for regular TS
self.multi... | ["def","setUp","(","self",")","-",">","None",":","self.Xs","=","[","[","[","1",",","1","]",",","[","2",",","2","]",",","[","3",",","3","]",",","[","4",",","4","]","]","]","#","4","arms",",","each","of","dimensionality","2","self.Ys","=","[","[","1",",","2",",","3",",","4","]","]","self.Yvars","=","[","[","1",",","1",",... | 15 | 27 | null | test_thompson.py | Ax/ax/models/tests/test_thompson.py | import numpy
from ax.exceptions.model import ModelError
from ax.models.discrete.thompson import ThompsonSampler
from ax.utils.common.testutils import TestCase | 15 | 1 | 4 | 0 | 1 | 9 | 1 | Use image node_id 1 for calling the ThompsonSamplerTest obj's underlying member method code with example usage: obj.setUp() without return types | 144 | node_id 1 | 9,535 |
test_decimals_0_1 | TestHighConfidence | unittest | true | self | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | Test with cutoff of 0.1. | ["Test","with","cutoff","of","0.1","."] | null | def test_decimals_0_1(self):
"""
Test with cutoff of 0.1.
"""
(_, _), (x_test, _) = self.mnist
classifier = get_image_classifier_kr_tf()
preds = classifier.predict(x_test[0:1])
postprocessor = HighConfidence(cutoff=0.1)
post_preds = postprocessor(preds=preds)
classifier_prediction_e... | ["def","test_decimals_0_1","(","self",")",":","``","''","''","Test","with","cutoff","of","0.1.","``","''","''","(","_",",","_",")",",","(","x_test",",","_",")","=","self.mnist","classifier","=","get_image_classifier_kr_tf","(",")","preds","=","classifier.predict","(","x_test","[","0:1","]",")","postprocessor","=","High... | 44 | 76 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 3 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.test_decimals_0_1() without return types | 155 | node_id 3 | 235,298 |
test_decimals_0_2 | TestHighConfidence | unittest | true | self | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | Test with cutoff of 0.2. | ["Test","with","cutoff","of","0.2","."] | null | def test_decimals_0_2(self):
"""
Test with cutoff of 0.2.
"""
(_, _), (x_test, _) = self.mnist
classifier = get_image_classifier_kr_tf()
preds = classifier.predict(x_test[0:1])
postprocessor = HighConfidence(cutoff=0.2)
post_preds = postprocessor(preds=preds)
classifier_prediction_e... | ["def","test_decimals_0_2","(","self",")",":","``","''","''","Test","with","cutoff","of","0.2.","``","''","''","(","_",",","_",")",",","(","x_test",",","_",")","=","self.mnist","classifier","=","get_image_classifier_kr_tf","(",")","preds","=","classifier.predict","(","x_test","[","0:1","]",")","postprocessor","=","High... | 78 | 110 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 4 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.test_decimals_0_2() without return types | 155 | node_id 4 | 235,299 |
test_binary_decimals_0_5 | TestHighConfidence | unittest | true | self | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | Test with cutoff of 0.5 for binary classifier. | ["Test","with","cutoff","of","0.5","for","binary","classifier","."] | null | def test_binary_decimals_0_5(self):
"""
Test with cutoff of 0.5 for binary classifier.
"""
(_, _), (x_test, _) = self.mnist
classifier = get_image_classifier_kr_tf_binary()
preds = classifier.predict(x_test[0:1])
postprocessor = HighConfidence(cutoff=0.5)
post_preds = postprocessor(preds... | ["def","test_binary_decimals_0_5","(","self",")",":","``","''","''","Test","with","cutoff","of","0.5","for","binary","classifier.","``","''","''","(","_",",","_",")",",","(","x_test",",","_",")","=","self.mnist","classifier","=","get_image_classifier_kr_tf_binary","(",")","preds","=","classifier.predict","(","x_test","... | 112 | 126 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 5 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.test_binary_decimals_0_5() without return types | 162 | node_id 5 | 235,300 |
test_RandomModelGenSamples | RandomModelTest | TestCase | true | self | null | null | null | null | null | def test_RandomModelGenSamples(self) -> None:
with self.assertRaises(NotImplementedError):
self.random_model._gen_samples(n=1, tunable_d=1)
| ["def","test_RandomModelGenSamples","(","self",")","-",">","None",":","with","self.assertRaises","(","NotImplementedError",")",":","self.random_model._gen_samples","(","n=1",",","tunable_d=1",")"] | 25 | 27 | null | test_random.py | Ax/ax/models/tests/test_random.py | import numpy
import torch
from ax.models.random.base import RandomModel
from ax.utils.common.testutils import TestCase
from ax.utils.common.typeutils import not_none | 15 | 1 | 5 | 0 | 1 | 8 | 1 | Use image node_id 3 for calling the RandomModelTest obj's underlying member method code with example usage: obj.test_RandomModelGenSamples() without return types | 161 | node_id 3 | 9,512 |
test_binary_decimals_0_6 | TestHighConfidence | unittest | true | self | A unittest class for testing the HighConfidence postprocessor. | ["A","unittest","class","for","testing","the","HighConfidence","postprocessor","."] | Test with cutoff of 0.6 for binary classifier. | ["Test","with","cutoff","of","0.6","for","binary","classifier","."] | null | def test_binary_decimals_0_6(self):
"""
Test with cutoff of 0.6 for binary classifier.
"""
(_, _), (x_test, _) = self.mnist
classifier = get_image_classifier_kr_tf_binary()
preds = classifier.predict(x_test[0:1])
postprocessor = HighConfidence(cutoff=0.6)
post_preds = postprocessor(preds... | ["def","test_binary_decimals_0_6","(","self",")",":","``","''","''","Test","with","cutoff","of","0.6","for","binary","classifier.","``","''","''","(","_",",","_",")",",","(","x_test",",","_",")","=","self.mnist","classifier","=","get_image_classifier_kr_tf_binary","(",")","preds","=","classifier.predict","(","x_test","... | 128 | 142 | null | test_high_confidence.py | adversarial-robustness-toolbox/tests/defences/test_high_confidence.py | import logging
import unittest
import numpy
from art.defences.postprocessor import HighConfidence
from art.utils import load_dataset
from tests.utils import master_seed, get_image_classifier_kr_tf, get_image_classifier_kr_tf_binary | 15 | 1 | 6 | 0 | 1 | 7 | 1 | Use image node_id 6 for calling the TestHighConfidence obj's underlying member method code with example usage: obj.test_binary_decimals_0_6() without return types | 162 | node_id 6 | 235,301 |
convert | Converter | ImageConverter | true | self,_from,_to | null | null | Converts the image from SVG to PDF using chrome. | ["Converts","the","image","from","SVG","to","PDF","using","chrome","."] | True | def convert(self, _from: str, _to: str) -> bool:
"""Converts the image from SVG to PDF using chrome."""
with open(_from, "r") as f:
svg = f.read()
HTML = (
"<html><head><style>body {margin: 0; }</style><script>function init() {const element = document.querySelector('svg');const positionInfo... | ["def","convert","(","self",",","_from",":","str",",","_to",":","str",")","-",">","bool",":","``","''","''","Converts","the","image","from","SVG","to","PDF","using","chrome",".","''","''","''","with","open","(","_from",",","``","r","''",")","as","f",":","svg","=","f.read","(",")","HTML","=","(","``","<","html",">","<",... | 71 | 89 | null | convert-svg-to-pdf.py | sympy/doc/ext/convert-svg-to-pdf.py | from __future__ import annotations
from sphinx.transforms.post_transforms.images import ImageConverter
from sphinx.util import logging
import os
import platform
from typing import Any
from sphinx.application import Sphinx | 15 | 1 | 7 | 1 | 1 | 5 | 1 | Use image node_id 5 for calling the Converter obj's underlying member method code with example usage: obj.convert(_from, _to) and returns: True | 143 | node_id 5 | 2,029,278 |
_setup | RunnerTrafficMetricsMiddleware | null | true | self,metrics_client | null | null | null | null | null | def _setup(
self,
metrics_client: "PrometheusClient" = Provide[
BentoMLContainer.metrics_client
],
):
self.metrics_client = metrics_client
self.metrics_request_duration = metrics_client.Histogram(
namespace=self.namespace,
name="request_duration_seconds",
documentati... | ["def","_setup","(","self",",","metrics_client",":","``","PrometheusClient","''","=","Provide","[","BentoMLContainer.metrics_client","]",",",")",":","self.metrics_client","=","metrics_client","self.metrics_request_duration","=","metrics_client.Histogram","(","namespace=self.namespace",",","name=","''","request_duration... | 150 | 187 | null | instruments.py | BentoML/src/bentoml/_internal/server/http/instruments.py | from __future__ import annotations
import contextvars
import logging
from timeit import default_timer
from typing import TYPE_CHECKING
from simple_di import Provide
from simple_di import inject
from ...configuration.containers import BentoMLContainer
from ...context import component_context | 15 | 2 | 9 | 0 | 0 | 2 | null | Use image node_id 2 for calling the RunnerTrafficMetricsMiddleware obj's underlying member method code with example usage: obj._setup(metrics_client) without return types | 170 | node_id 2 | 14,515 |
command_runner | Converter | ImageConverter | true | self,chrome,_to,temp_name | null | null | null | null | os,int | def command_runner(
self, chrome: str | None, _to: str, temp_name: str
) -> int:
if not chrome:
return 1
command = f"{chrome} --headless --disable-gpu --disable-software-rasterizer --print-to-pdf={_to} {temp_name}"
logger.error(command)
return os.system(command)
| ["def","command_runner","(","self",",","chrome",":","str","|","None",",","_to",":","str",",","temp_name",":","str",")","-",">","int",":","if","not","chrome",":","return","1","command","=","f","''","{","chrome","}","--","headless","--","disable-gpu","--","disable-software-rasterizer","--","print-to-pdf=","{","_to","}","... | 64 | 69 | null | convert-svg-to-pdf.py | sympy/doc/ext/convert-svg-to-pdf.py | from __future__ import annotations
from sphinx.transforms.post_transforms.images import ImageConverter
from sphinx.util import logging
import os
import platform
from typing import Any
from sphinx.application import Sphinx | 15 | 1 | 7 | 1 | 1 | 5 | 1 | Use image node_id 4 for calling the Converter obj's underlying member method code with example usage: obj.command_runner(chrome, _to, temp_name) and returns: os, int | 165 | node_id 4 | 2,029,277 |
chromium_command | Converter | ImageConverter | true | self | null | null | null | null | None,None,str,str,str+path+str,path,str | def chromium_command(self) -> str | None:
if platform.win32_ver()[0]:
if os.system("where chromium") == 0:
return "chromium"
path = os.path.join(
os.environ["PROGRAMW6432"],
"Chromium\\Application\\chrome.exe",
)
if os.path.exists(path):
... | ["def","chromium_command","(","self",")","-",">","str","|","None",":","if","platform.win32_ver","(",")","[","0","]",":","if","os.system","(","``","where","chromium","''",")","==","0",":","return","``","chromium","''","path","=","os.path.join","(","os.environ","[","``","PROGRAMW6432","''","]",",","``","Chromium\\\\Appli... | 44 | 61 | null | convert-svg-to-pdf.py | sympy/doc/ext/convert-svg-to-pdf.py | from __future__ import annotations
from sphinx.transforms.post_transforms.images import ImageConverter
from sphinx.util import logging
import os
import platform
from typing import Any
from sphinx.application import Sphinx | 15 | 1 | 7 | 1 | 1 | 5 | 1 | Use image node_id 3 for calling the Converter obj's underlying member method code with example usage: obj.chromium_command() and returns: None, None, str, str, str, path, str, path, str | 185 | node_id 3 | 2,029,276 |
_test_texture_as_input | TestShapeShifter | TestBase | true | self,sign_gradients,use_spectral,soft_clip | null | null | null | null | background, image_frame, y_,current_image | def _test_texture_as_input(
self, sign_gradients, use_spectral, soft_clip
):
# We must start a new graph
tf.reset_default_graph()
# Only import if object detection module is available
from art.estimators.object_detection.tensorflow_faster_rcnn import (
TensorFlowFasterRCNN,
)
from a... | ["def","_test_texture_as_input","(","self",",","sign_gradients",",","use_spectral",",","soft_clip",")",":","#","We","must","start","a","new","graph","tf.reset_default_graph","(",")","#","Only","import","if","object","detection","module","is","available","from","art.estimators.object_detection.tensorflow_faster_rcnn","i... | 139 | 235 | null | test_shapeshifter.py | adversarial-robustness-toolbox/tests/attacks/test_shapeshifter.py | from __future__ import absolute_import, division, print_function, unicode_literals
import logging
import unittest
import importlib
import tensorflow
import numpy
from tests.utils import TestBase, master_seed | 15 | 1 | 7 | 0 | 1 | 6 | 1 | Use image node_id 5 for calling the TestShapeShifter obj's underlying member method code with example usage: obj._test_texture_as_input(sign_gradients, use_spectral, soft_clip) and returns: background, image_frame, y_, current_image | 234 | node_id 5 | 234,965 |
test_check_params | TestShapeShifter | TestBase | true | self | null | null | null | null | null | def test_check_params(self):
from art.estimators.object_detection import TensorFlowFasterRCNN
from art.attacks.evasion import ShapeShifter
images = tf.Variable(
initial_value=np.zeros([1, 28, 28, 1]), dtype=tf.float32
)
obj_dec = TensorFlowFasterRCNN(images=images)
with self.assertRais... | ["def","test_check_params","(","self",")",":","from","art.estimators.object_detection","import","TensorFlowFasterRCNN","from","art.attacks.evasion","import","ShapeShifter","images","=","tf.Variable","(","initial_value=np.zeros","(","[","1",",","28",",","28",",","1","]",")",",","dtype=tf.float32",")","obj_dec","=","Tens... | 237 | 380 | null | test_shapeshifter.py | adversarial-robustness-toolbox/tests/attacks/test_shapeshifter.py | from __future__ import absolute_import, division, print_function, unicode_literals
import logging
import unittest
import importlib
import tensorflow
import numpy
from tests.utils import TestBase, master_seed | 15 | 1 | 7 | 0 | 1 | 6 | 1 | Use image node_id 6 for calling the TestShapeShifter obj's underlying member method code with example usage: obj.test_check_params() without return types | 153 | node_id 6 | 234,966 |
End of preview. Expand in Data Studio
Python Copilot Large Coding Dataset
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details
Each row contains python code, either a class method or a global function, imported modules, base classes (if any), exceptions (ordered based off the code), returns (ordered based off the code), arguments (ordered based off the code), and more.
- Rows: 2350782
- Size: 3.1 GB
- Data type: text
- Format: Extracted code using python AST
Schema
{
"args": "string",
"class_bases": "string",
"class_docstr": "string",
"class_docstr_tok": "string",
"class_name": "string",
"code": "string",
"code_tok": "string",
"docstr": "string",
"docstr_tok": "string",
"file_path": "string",
"filename": "string",
"imports": "string",
"is_member": "bool",
"label_desc": "string",
"label_desc_len": "int64",
"label_id": "string",
"lend": "int64",
"lstart": "int64",
"name": "string",
"num_all_bases": "float64",
"num_bases": "float64",
"num_classes": "float64",
"num_functions": "int64",
"num_imports": "int64",
"num_methods": "float64",
"raises": "string",
"returns": "string",
"total_objects": "int64"
}
How to use the dataset
from datasets import load_dataset
ds = load_dataset("matlok/python-copilot-training-from-many-repos-large", data_dir="files")
- Downloads last month
- 43
Size of downloaded dataset files:
26.7 MB
Size of the auto-converted Parquet files:
26.7 MB
Number of rows:
32,000