code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
## RankGen - Improving Text Generation with Large Ranking Models
[](#python)
[](https://arxiv.org/abs/2205.09726)
[]... | /rankgen-0.1.1.tar.gz/rankgen-0.1.1/README.md | 0.678327 | 0.939637 | README.md | pypi |
import torch
from ranking_metrics_torch.common import _check_inputs
from ranking_metrics_torch.common import _create_output_placeholder
from ranking_metrics_torch.common import _extract_topk
from ranking_metrics_torch.common import _mask_with_nans
def dcg_at(
ks: torch.Tensor, scores: torch.Tensor, labels: torch... | /ranking_metrics_torch-0.3.0-py3-none-any.whl/ranking_metrics_torch/cumulative_gain.py | 0.94062 | 0.522507 | cumulative_gain.py | pypi |
import torch
from ranking_metrics_torch.common import _check_inputs
from ranking_metrics_torch.common import _extract_topk
from ranking_metrics_torch.common import _create_output_placeholder
from ranking_metrics_torch.common import _mask_with_nans
def precision_at(
ks: torch.Tensor, scores: torch.Tensor, labels:... | /ranking_metrics_torch-0.3.0-py3-none-any.whl/ranking_metrics_torch/precision_recall.py | 0.947793 | 0.524456 | precision_recall.py | pypi |
from collections import Iterable
import numpy as np
DISCOUNTS = np.log2(np.arange(1000) + 2)
def dcg_score(y_true, y_score, k=10, gains="exponential"):
if not isinstance(y_true, np.ndarray):
y_true = np.array(y_true)
y_score = np.array(y_score)
order = np.argsort(y_score)[::-1]
y_true = ... | /ranking_metrics-0.1.1-py3-none-any.whl/rankingmetrics/ndcgs.py | 0.806548 | 0.540621 | ndcgs.py | pypi |
from collections import Iterable
import numpy as np
def err_with_sorted(y_true_sorted, max_score):
err_ = 0.
prob_pre_step = 1.
ERRS = []
for idx, rel in enumerate(y_true_sorted):
idx += 1
utility = (np.power(2, rel) - 1) / np.power(2, max_score)
err_ += prob_pre_step * utilit... | /ranking_metrics-0.1.1-py3-none-any.whl/rankingmetrics/errs.py | 0.533884 | 0.302868 | errs.py | pypi |
import os
from typing import List, Tuple, Dict, Iterator
import yaml
from unidecode import unidecode
import shutil
import pandas as pd
# Loads some names from config.yaml
user_config_path = os.path.join("data_rtt", "config")
if not os.path.exists(user_config_path):
shutil.copytree(os.path.dirname(__file__) + "/... | /ranking_table_tennis-2021.3.30-py3-none-any.whl/ranking_table_tennis/models.py | 0.708515 | 0.212927 | models.py | pypi |
import pandas as pd
import numpy as np
class Rankings:
def __init__(self, rating_df, ranking, ties, rating_names, reviewer_col_name="Reviewer Name", prop_col_name="Proposal Name", overall_col_name="Overall Score"):
self.scores = rating_df
self.ranking = ranking
self.ties = ties
self... | /rankings_UI-1.8.tar.gz/rankings_UI-1.8/rankingTool/Ranking.py | 0.400867 | 0.206474 | Ranking.py | pypi |
# Rankit
[](https://travis-ci.org/wattlebird/ranking) [](https://badge.fury.io/py/rankit)
## What is Rankit?
_Rankit_ is a project facilitating ranking process through pairwise comparision.... | /rankit-0.3.1.tar.gz/rankit-0.3.1/README.md | 0.511473 | 0.906322 | README.md | pypi |
import numpy as np
import scipy.linalg as la
from collections import namedtuple
from .AbstractSampler import AbstractSampler
class RollingWindowSampler(AbstractSampler):
def __init__(self, sample_size: int, out_of_sample_size: int):
super().__init__()
self.__sample_size = sample_size
sel... | /ranmath-0.1.tar.gz/ranmath-0.1/Ranmath/MatrixSamplers/RollingWindowSampler.py | 0.640636 | 0.614365 | RollingWindowSampler.py | pypi |
from .AbstractEstimator import AbstractEstimator
import numpy as np
import scipy.linalg as la
from ..Norms import frobenius_norm_squared
class LinearShrinkageEstimator(AbstractEstimator):
def __init__(self):
super().__init__()
def get_lse_alpha_oracle(self, sample_estimator_eigenvalues, sample_estim... | /ranmath-0.1.tar.gz/ranmath-0.1/Ranmath/CorrelationEstimators/LinearShrinkageEstimator.py | 0.830181 | 0.417479 | LinearShrinkageEstimator.py | pypi |
from .AbstractEstimator import AbstractEstimator
from ..Resolvents import SimulatedEigenvaluesResolvent as resolvent
import numpy as np
from sympy import coth
class QuarticRIEstimator(AbstractEstimator):
def __init__(self):
super().__init__()
def __quartic_equation(self, q, g, l, h, r):
R0 ... | /ranmath-0.1.tar.gz/ranmath-0.1/Ranmath/CorrelationEstimators/QuarticRIEstimator.py | 0.776284 | 0.659104 | QuarticRIEstimator.py | pypi |
from typing import Union
from datetime import datetime
from logging import getLogger
from typing import IO, List
from xml.etree.ElementTree import ElementTree
import defusedxml.ElementTree as ET
from .elements import *
logger = getLogger()
TIME_FORMAT = r"%M:%S.%f"
def parse(file: Union[IO, str]) -> RanorexReport... | /ranorex_report_parser-0.1.9-py3-none-any.whl/ranorex_report_parser/parser.py | 0.523664 | 0.382891 | parser.py | pypi |
from typing import List, Union
from datetime import datetime, timedelta
from hashlib import sha256
from enum import Enum
class ReportStatus(Enum):
Success = 1
Failed = 2
Ignored = 3
class ReportElement(object):
def __init__(self, start_time: datetime, duration: int):
self.start_time = start_t... | /ranorex_report_parser-0.1.9-py3-none-any.whl/ranorex_report_parser/elements/base.py | 0.889072 | 0.261728 | base.py | pypi |
from datetime import datetime
from hashlib import sha256
from typing import List, Tuple
from .base import ReportElementWithStatus, ReportStatus, ReportElement
from .item import ItemElement
from .test_suite import TestSuiteElement
from .test_case import TestCaseElement
from .test_module import TestModuleElement
class ... | /ranorex_report_parser-0.1.9-py3-none-any.whl/ranorex_report_parser/elements/report.py | 0.770378 | 0.18508 | report.py | pypi |
<div align="center">
<img src="https://repository-images.githubusercontent.com/268892956/750228ec-f3f2-465d-9c17-420c688ba2bc">
</div>
<p align="center">
<!-- Python -->
<a href="https://www.python.org" alt="Python"><img src="https://badges.aleen42.com/src/python.svg"></a>
<!-- Version -->
<a href="https://p... | /ranx-0.3.16.tar.gz/ranx-0.3.16/README.md | 0.766381 | 0.924824 | README.md | pypi |
import math
import matplotlib.pyplot as plt
from .Generaldistribution import Distribution
class Gaussian(Distribution):
""" Gaussian distribution class for calculating and
visualizing a Gaussian distribution.
Attributes:
mean (float) representing the mean value of the distribution
stdev (float) representing ... | /ranyou_distributions-0.1.tar.gz/ranyou_distributions-0.1/ranyou_distributions/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
C = int(0x1000000000)
#--------------------------------------------------------------------
def norm(n):
return n & int(0xFFFFFFFF)
#====================================================================
class U32:
v = int(0)
#--------------------------------------------------------------------
def __... | /raok-0.5.4.post1-py3-none-any.whl/py3mschap/U32.py | 0.459076 | 0.206414 | U32.py | pypi |
import hashlib
import random
from . import mschap
SHSpad1 = \
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00" + \
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00" + \
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00" + \
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00"
SHSpad2 = \
b"\xf2\xf2\xf2\xf2\xf2\xf2\xf2\xf2\... | /raok-0.5.4.post1-py3-none-any.whl/py3mschap/mppe.py | 0.41182 | 0.610947 | mppe.py | pypi |
from . import des_c
from . import utils
#---------------------------------------------------------------------
class DES:
des_c_obj = None
#-----------------------------------------------------------------
def __init__(self, key_str):
""
k = str_to_key56(key_str)
k = key56_to_ke... | /raok-0.5.4.post1-py3-none-any.whl/py3mschap/des.py | 0.405449 | 0.155623 | des.py | pypi |
import hashlib
from . import des
from . import md4
from . import utils
def challenge_hash(peer_challenge, authenticator_challenge, username: str):
"""ChallengeHash"""
sha_hash = hashlib.sha1()
sha_hash.update(peer_challenge)
sha_hash.update(authenticator_challenge)
sha_hash.update(bytes(username... | /raok-0.5.4.post1-py3-none-any.whl/py3mschap/mschap.py | 0.423339 | 0.259374 | mschap.py | pypi |
from json import dumps as json_dumps
from requests_toolbelt import MultipartEncoder
from rapconector.utils import parse_or_raise
class Document:
'''Representação de um documento no Conector.'''
def __init__(self, client, json):
# API client, for future requests.
self._client = client
... | /rap-conector-client-0.21.0.1.tar.gz/rap-conector-client-0.21.0.1/rapconector/document.py | 0.655446 | 0.197657 | document.py | pypi |
import re
try:
from json.decoder import JSONDecodeError
except ImportError:
# For python2.7
JSONDecodeError = ValueError
from .errors import AuthenticationError, NotFoundError, ServerError
def get_err_msg(res):
'''
Utility function to paper over different ways an error message may be
returne... | /rap-conector-client-0.21.0.1.tar.gz/rap-conector-client-0.21.0.1/rapconector/utils.py | 0.661486 | 0.159872 | utils.py | pypi |
import random
import re
import sys
from copy import deepcopy
from tqdm import tqdm
from rapbuilder import config
from rapbuilder import constant
import math
from rapbuilder.rbs_predictor import RBSPredictor
def monte_carlo_rbs(pre_seq: str, post_seq: str, TIR_target: float = 0, rbs_init: str = None, dG_target: flo... | /rapBuilder-0.1.4.tar.gz/rapBuilder-0.1.4/rapbuilder/utils.py | 0.405213 | 0.275264 | utils.py | pypi |
import math
import matplotlib.pyplot as plt
from .Generaldistribution import Distribution
class Gaussian(Distribution):
""" Gaussian distribution class for calculating and
visualizing a Gaussian distribution.
Attributes:
mean (float) representing the mean value of the distribution
... | /raphpy_distributions-1.0.tar.gz/raphpy_distributions-1.0/raphpy_distributions/Gaussiandistribution.py | 0.899387 | 0.89616 | Gaussiandistribution.py | pypi |
import struct
class SpecialLengths(object):
END_OF_DATA_SECTION = -1
PYTHON_EXCEPTION_THROWN = -2
TIMING_DATA = -3
END_OF_STREAM = -4
NULL = -5
START_ARROW_STREAM = -6
class Serializer(object):
def dump_stream(self, iterator, stream):
"""
Serialize an iterator of objects to... | /raphtory_client-0.1.4-py3-none-any.whl/raphtoryclient/serializers.py | 0.73029 | 0.206974 | serializers.py | pypi |
from enum import Enum
from .config import Config
class PlaybackType(int, Enum):
PLAY_CASE = 0
PLAY_SUITE = 1,
PLAY_ALL_SUITES = 2
class SnapshotStatus(int, Enum):
NO_SNAPSHOT = 0
SNAPSHOT_ON_ERRORS = 1,
ALWAYS_SNAPSHOT = 2
class Status(int, Enum):
NO_SENDING = 0
SENDING_ON_ERRORS =... | /rapi_api-1.0.0-py3-none-any.whl/rapi_api/configBuilder.py | 0.856498 | 0.178992 | configBuilder.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import compas
import compas.geometry as cg
from compas_ghpython.artists import MeshArtist
try:
import Rhino
import Rhino.Geometry as rg
except ImportError:
compas.raise_if_ironpython()
def cgpoin... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/rhino/compas_to_rhino.py | 0.920057 | 0.70117 | compas_to_rhino.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import compas
import compas.geometry as cg
from compas_rhino.geometry import RhinoMesh
try:
import Rhino
import Rhino.Geometry as rg
except ImportError:
compas.raise_if_ironpython()
def rgpoint_t... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/rhino/rhino_to_compas.py | 0.917252 | 0.714192 | rhino_to_compas.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import json
from collections import OrderedDict
from compas.utilities import DataDecoder
try:
from pathlib import Path
except ImportError:
pass
def csv_reports(args):
"""Convert fabr... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/fab_data/tools.py | 0.659734 | 0.18208 | tools.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import logging
import compas_rrc
import confuse
log = logging.getLogger(__name__)
class ZoneDataTemplate(confuse.Template):
""":class:`confuse.Template` for ABB zonedata."""
# Describes the valid z... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/fab_data/fab_conf.py | 0.781997 | 0.220426 | fab_conf.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import compas_rrc
from compas.geometry import Frame
from compas_fab.robots import Configuration
from compas_fab.robots import JointTrajectory
from compas_fab.robots import to_degrees
try:
from collections.... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/robots/trajectories.py | 0.921574 | 0.317096 | trajectories.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from compas_fab.backends import RosClient
from compas_rrc import AbbClient
from compas_rrc import Motion
from compas_rrc import MoveToFrame
from compas_rrc import Noop
from compas_rrc import PrintText
from comp... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/robots/abb_standalone_move_to_frame.py | 0.890604 | 0.185836 | abb_standalone_move_to_frame.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from rapid_clay_formations_fab import fab_data
try:
import typing
except ImportError:
pass
else:
if typing.TYPE_CHECKING:
from typing import List
from compas.geometry import Frame
... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/robots/pick_station.py | 0.928737 | 0.224353 | pick_station.py | pypi |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
from compas.geometry import Frame
class RapidToolData(object):
"""Create Rapid ToolData.
Parameters
----------
tcp_coord : :class:`list` of class:`float`
Coordinate of to... | /rapid_clay_formations_fab-0.7.1.tar.gz/rapid_clay_formations_fab-0.7.1/src/rapid_clay_formations_fab/robots/abb_rapid_tooldata.py | 0.914599 | 0.49939 | abb_rapid_tooldata.py | pypi |
__author__ = 'marcos.medeiros'
from django.db import models
from django.db.models.fields.related import ForeignObjectRel
import datetime
import decimal
import inspect
import locale
from django.template import loader, Context
_filter_templates = 'rapid/filters/'
_filter_url_parameter = 'filter'
class FilterOperator... | /rapid-django-0.0.1a1.tar.gz/rapid-django-0.0.1a1/src/rapid/filters.py | 0.651687 | 0.191158 | filters.py | pypi |
__author__ = 'marcos.medeiros'
from django.forms import widgets
from django.template import loader, Context
from rapid.wrappers import ModelData, InstanceData
class RapidReadOnly(widgets.Widget):
def __init__(self, *args, **kwargs):
super(RapidReadOnly, self).__init__(*args, **kwargs)
def render(se... | /rapid-django-0.0.1a1.tar.gz/rapid-django-0.0.1a1/src/rapid/widgets.py | 0.574992 | 0.193014 | widgets.py | pypi |
__author__ = 'marcos.medeiros'
class Permission:
"""
A permission for an registry entry.
"""
def __init__(self, model, instances):
self.model = model
self.instances = instances
def all_instances(model):
"""
Shortuct function for granting permission over all instances of a mod... | /rapid-django-0.0.1a1.tar.gz/rapid-django-0.0.1a1/src/rapid/permissions.py | 0.760651 | 0.385086 | permissions.py | pypi |
import logging
from sqlalchemy import and_, exists
from rapid.ci.data.models import Commit
from rapid.lib.constants import ModuleConstants, StatusConstants, status_type_severity_mapping
from rapid.lib.framework.injectable import Injectable
from rapid.lib import get_db_session
from rapid.release.data.models import Ste... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/release/data/release_dal.py | 0.513912 | 0.219861 | release_dal.py | pypi |
import datetime
from sqlalchemy.orm import relationship, backref
from sqlalchemy import Column, String, ForeignKey, Integer, DateTime, Boolean, Text, Enum
from rapid.lib import get_declarative_base
from rapid.master.data.database.models.base.base_model import BaseModel
from rapid.lib.constants import VcsReleaseStepT... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/release/data/models.py | 0.465145 | 0.152979 | models.py | pypi |
import uuid
from ..lib.configuration import Configuration
# pylint: disable=too-many-instance-attributes,too-few-public-methods
class MasterConfiguration(Configuration):
def __init__(self, file_name=None):
self.port = None
self.queue_time = None
self.db_connect_string = None
self.... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/master/master_configuration.py | 0.50708 | 0.162148 | master_configuration.py | pypi |
from xml.dom.minidom import parseString
from rapid.lib.constants import Constants
from .abstract_parser import AbstractParser
class XUnitParser(AbstractParser):
@staticmethod
def get_type():
return "XUnit"
def _parse_lines(self, lines): # pylint: disable=too-many-locals,too-many-branches,too-ma... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/client/parsers/xunit_parser.py | 0.420362 | 0.201754 | xunit_parser.py | pypi |
from rapid.lib.constants import Constants
parsers = {}
def register(clz):
parsers[clz.get_type()] = clz
return clz
def load_parsers():
from .xunit_parser import XUnitParser
from .tap_parser import TapParser
for parser in [XUnitParser, TapParser]:
register(parser)
def parse_file(lines... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/client/parsers/__init__.py | 0.464416 | 0.221161 | __init__.py | pypi |
import datetime
from sqlalchemy.orm import relationship
from sqlalchemy.sql.schema import UniqueConstraint
from sqlalchemy import Column, String, ForeignKey, Integer, DateTime, Boolean, Text
from rapid.lib import get_declarative_base
from rapid.master.data.database.models.base.active_model import ActiveModel
from rapi... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/qa/data/models.py | 0.491944 | 0.198355 | models.py | pypi |
from sqlalchemy import and_
from sqlalchemy.orm import joinedload
from sqlalchemy.sql.functions import func
from rapid.lib.results_serializer import ResultsSerializer
from rapid.qa.data.models import QaProduct
from rapid.lib.utils import ORMUtil
from rapid.lib.constants import Constants, StatusConstants
from rapid.lib... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/qa/data/dals/qa_dal.py | 0.413951 | 0.300329 | qa_dal.py | pypi |
from rapid.lib.framework.injectable import Injectable
from rapid.workflow.action_dal import ActionDal
from rapid.workflow.data.dal.pipeline_dal import PipelineDal
from rapid.workflow.data.dal.report_dal import ReportDal
class ActionService(Injectable):
__injectables__ = {'pipeline_dal': PipelineDal, 'action_dal':... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/workflow/action_service.py | 0.756807 | 0.181155 | action_service.py | pypi |
import datetime
from sqlalchemy.orm import relationship
from sqlalchemy import Column, String, ForeignKey, Integer, Boolean, Text
from rapid.lib import get_declarative_base
from rapid.lib.constants import StatusConstants
from rapid.lib.converters import ObjectConverter
from rapid.master.data.database.models.base.base... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/workflow/data/models.py | 0.499268 | 0.160299 | models.py | pypi |
from abc import ABCMeta, abstractmethod
class QaModule(object):
__metaclass__ = ABCMeta
@abstractmethod
def save_results(self, action_instance, session, post_data):
yield
@abstractmethod
def reset_results(self, action_instance_id, session):
"""
Reset Stacktrace and QaTest... | /rapid-framework-23.816.141625.tar.gz/rapid-framework-23.816.141625/rapid/lib/modules.py | 0.866951 | 0.177526 | modules.py | pypi |
import traceback
from io import BytesIO
from pathlib import Path
from typing import List, Union
import cv2
import numpy as np
from onnxruntime import GraphOptimizationLevel, InferenceSession, SessionOptions
from PIL import Image, UnidentifiedImageError
root_dir = Path(__file__).resolve().parent
InputType = Union[str,... | /rapid_latex_ocr-0.0.3-py3-none-any.whl/rapid_latex_ocr/utils_load.py | 0.645567 | 0.200127 | utils_load.py | pypi |
import argparse
import re
import time
import traceback
from pathlib import Path
from typing import Tuple, Union
import numpy as np
import yaml
from PIL import Image
from .models import EncoderDecoder
from .utils import PreProcess, TokenizerCls
from .utils_load import InputType, LoadImage, LoadImageError, OrtInferSess... | /rapid_latex_ocr-0.0.3-py3-none-any.whl/rapid_latex_ocr/main.py | 0.688992 | 0.150965 | main.py | pypi |
from pathlib import Path
from typing import Tuple, Union
import numpy as np
from .utils_load import OrtInferSession
class EncoderDecoder:
def __init__(
self,
encoder_path: Union[Path, str],
decoder_path: Union[Path, str],
bos_token: int,
eos_token: int,
max_seq_le... | /rapid_latex_ocr-0.0.3-py3-none-any.whl/rapid_latex_ocr/models.py | 0.879987 | 0.392395 | models.py | pypi |
import copy
import warnings
from io import BytesIO
from pathlib import Path
from typing import Union
import cv2
import numpy as np
import yaml
from onnxruntime import (GraphOptimizationLevel, InferenceSession,
SessionOptions, get_available_providers, get_device)
from PIL import Image, Unidenti... | /rapid_layout-3.6-py3-none-any.whl/rapid_layout/utils.py | 0.71889 | 0.178848 | utils.py | pypi |
from typing import Union
import gpytorch
import gpytorch.constraints
import torch
# @TODO: This function is nowhere called.
# If we keep it, we should add type hints and possibly a unit test.
# @AGRE / @ELD: Delete?
# CLAROS, 2022-11-01
def optim_step(model, loss_function, optimizer):
"""
... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/gp_models/utils.py | 0.702122 | 0.658129 | utils.py | pypi |
from typing import Any, Dict, List, Union
import numpy as np
from nptyping import Float, NDArray, Shape
from rapid_models.gp_diagnostics.cv import (check_folds_indices,
check_lower_triangular,
check_numeric_array, loo_cholesky,
... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/gp_diagnostics/metrics.py | 0.929648 | 0.610715 | metrics.py | pypi |
import itertools
from typing import Any, List, Tuple, Union
import numpy as np
from nptyping import Float, Int, NDArray, Shape
import rapid_models.gp_diagnostics.utils.checks as checks
from rapid_models.gp_diagnostics.utils.linalg import (chol_inv, mulinv_solve,
t... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/gp_diagnostics/cv.py | 0.877818 | 0.697377 | cv.py | pypi |
import itertools
from typing import Any, List, Tuple, Union, overload
import numpy as np
import torch
from nptyping import Float, NDArray, Shape
from scipy.stats import norm
def snorm_qq(
x: NDArray[Shape['N'], Float] # noqa: F821
) -> Tuple[NDArray[Shape['N'], Float], # noqa: F821
NDArray[Shape['N'... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/gp_diagnostics/utils/stats.py | 0.93992 | 0.537709 | stats.py | pypi |
import contextlib
from typing import Union
import numpy as np
import scipy.linalg.lapack as lapack
from nptyping import Float, NDArray, Shape
def triang_solve(
A: NDArray[Shape['N, N'], Float], # noqa: F821
B: Union[NDArray[Shape['N'], Float], # noqa: F821
NDArray[Shape['N, M'], Float]], # no... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/gp_diagnostics/utils/linalg.py | 0.883776 | 0.652767 | linalg.py | pypi |
import pyDOE2 # ELD TODO: Is it ok to import all from pyDOE to use this doe as a wrapper?
import numpy as np
from scipy.spatial import Delaunay
from sklearn.cluster import KMeans
from scipy.spatial import distance_matrix
def fullfact_with_bounds(LBs, UBs, N_xi):
"""
Return a ND array of corresponding (x_0,... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/doe/utils.py | 0.740174 | 0.662612 | utils.py | pypi |
def scale_x_to_box(x, bounds):
"""
Input x = points in [0, 1]^n
output scaled to lie in the box given by bounds
"""
x_tmp = x.copy()
for i in range(x.shape[1]):
x_tmp[:,
i] = x_tmp[:, i] * (bounds[i][1] - bounds[i][0]) + bounds[i][0]
return x_tmp
def scale_x_to_box... | /rapid_models-0.1.7.tar.gz/rapid_models-0.1.7/src/rapid_models/preprocessing/scalers.py | 0.895614 | 0.747144 | scalers.py | pypi |
import importlib
import warnings
from io import BytesIO
from pathlib import Path
from typing import Union
import cv2
import numpy as np
from onnxruntime import (GraphOptimizationLevel, InferenceSession,
SessionOptions, get_available_providers, get_device)
from PIL import Image, UnidentifiedIma... | /rapid_orientation-3.6-py3-none-any.whl/rapid_orientation/utils.py | 0.705379 | 0.18363 | utils.py | pypi |
import functools
import logging
import pickle
import warnings
from pathlib import Path
from typing import Any, Dict, Iterable, List, NamedTuple, Set, Tuple, Union
import numpy as np
import yaml
from onnxruntime import (
GraphOptimizationLevel,
InferenceSession,
SessionOptions,
get_available_providers,
... | /rapid_paraformer-2.0.4-py3-none-any.whl/rapid_paraformer/utils.py | 0.792384 | 0.198316 | utils.py | pypi |
from pathlib import Path
from typing import List, Tuple, Union
import librosa
import numpy as np
from .utils import (
CharTokenizer,
Hypothesis,
ONNXRuntimeError,
OrtInferSession,
TokenIDConverter,
WavFrontend,
get_logger,
read_yaml,
)
logging = get_logger()
class RapidParaformer:
... | /rapid_paraformer-2.0.4-py3-none-any.whl/rapid_paraformer/rapid_paraformer.py | 0.772101 | 0.27244 | rapid_paraformer.py | pypi |
# KaldiFeat
KaldiFeat is a light-weight Python library for computing Kaldi-style acoustic features based on NumPy. It might be helpful if you want to:
- Test a pre-trained model on new data without writing shell commands and creating a bunch of files.
- Run a pre-trained model in a new environment without installing ... | /rapid_paraformer-2.0.4-py3-none-any.whl/rapid_paraformer/kaldifeat/README.md | 0.600774 | 0.879406 | README.md | pypi |
import numpy as np
from .feature import sliding_window
# ---------- compute-vad ----------
def compute_vad(log_energy, energy_mean_scale=0.5, energy_threshold=0.5, frames_context=0, proportion_threshold=0.6):
""" Apply voice activity detection
:param log_energy: Log mel energy.
:param energy_mean_scale... | /rapid_paraformer-2.0.4-py3-none-any.whl/rapid_paraformer/kaldifeat/ivector.py | 0.844249 | 0.59705 | ivector.py | pypi |
import numpy as np
from scipy.fftpack import dct
# ---------- feature-window ----------
def sliding_window(x, window_size, window_shift):
shape = x.shape[:-1] + (x.shape[-1] - window_size + 1, window_size)
strides = x.strides + (x.strides[-1],)
return np.lib.stride_tricks.as_strided(x, shape=shape, strid... | /rapid_paraformer-2.0.4-py3-none-any.whl/rapid_paraformer/kaldifeat/feature.py | 0.577614 | 0.447823 | feature.py | pypi |
import math
from math import pi
import numpy as np
import lal
_a2m2 = math.sqrt(5.0 / (64.0 * math.pi))
_a2m1 = math.sqrt(5.0 / (16.0 * math.pi))
_a20 = math.sqrt(15.0 /(32.0 * math.pi))
_a21 = math.sqrt(5.0 / (16.0 * math.pi))
_a22 = math.sqrt(5.0 / (64.0 * math.pi))
def _compute_sph_l_eq_2(theta, phi, selected_m... | /rapid_pe-0.0.3.tar.gz/rapid_pe-0.0.3/rapid_pe/sph_harmonics.py | 0.475605 | 0.471771 | sph_harmonics.py | pypi |
# rapid-response-xblock
A django app plugin for edx-platform
## Setup
### 1) Add rapid response as a dependency
In production, the current practice as of 01/2021 is to add this dependency via Salt.
For local development, you can use one of the following options to add this as a dependency in the `edx-platform` repo... | /rapid_response_xblock-0.8.0.tar.gz/rapid_response_xblock-0.8.0/README.md | 0.708818 | 0.776242 | README.md | pypi |
from builtins import str
from common.models import UserProfile, Student, Class
from django.contrib.auth.models import User
from django.db import models
def theme_choices():
from game.theme import get_all_themes
return [(theme.name, theme.name) for theme in get_all_themes()]
def character_choices():
fr... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/models.py | 0.800107 | 0.190423 | models.py | pypi |
from django.db import migrations
def update(apps, schema_editor):
mappings = [
(u"1", 1),
(u"2", 1),
(u"3", 1),
(u"4", 1),
(u"5", 1),
(u"6", 1),
(u"7", 1),
(u"8", 1),
(u"9", 1),
(u"10", 1),
(u"11", 1),
(u"12", 1),
... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/migrations/0041_level_episode_refs.py | 0.475605 | 0.639539 | 0041_level_episode_refs.py | pypi |
from django.db import migrations
from game.level_management import set_decor_inner, set_blocks_inner
import json
def new_level(apps, schema_editor):
Level = apps.get_model("game", "Level")
Character = apps.get_model("game", "Character")
Theme = apps.get_model("game", "Theme")
LevelDecor = apps.get_mod... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/migrations/0033_recursion_level.py | 0.401336 | 0.226623 | 0033_recursion_level.py | pypi |
from django.db import migrations
from game.level_management import set_decor_inner, set_blocks_inner
import json
def new_level(apps, schema_editor):
Level = apps.get_model("game", "Level")
Character = apps.get_model("game", "Character")
Theme = apps.get_model("game", "Theme")
LevelDecor = apps.get_mod... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/migrations/0032_cannot_turn_left_level.py | 0.423935 | 0.174463 | 0032_cannot_turn_left_level.py | pypi |
from __future__ import absolute_import
from __future__ import division
from common.models import Student, Class
from django.shortcuts import render
from portal.templatetags import app_tags
import game.messages as messages
import game.permissions as permissions
from game.forms import LevelModerationForm
from game.mode... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/views/level_moderation.py | 0.683631 | 0.226527 | level_moderation.py | pypi |
'use strict';
var ocargo = ocargo || {};
ocargo.Node = function (coordinate) {
this.coordinate = coordinate;
this.connectedNodes = [];
this.trafficLights = [];
this.cows = [];
this.parent = null;
};
ocargo.Node.prototype.addConnectedNode = function(node) {
this.connectedNodes.push(node);
};
oca... | /rapid-router-5.11.3.tar.gz/rapid-router-5.11.3/game/static/game/js/node.js | 0.619471 | 0.618233 | node.js | pypi |
from datetime import datetime
from typing import Dict, Optional
import json
import time
import requests
import pandas as pd
from pandas import DataFrame
from rapid.auth import RapidAuth
from rapid.items.schema import Schema
from rapid.items.query import Query
from rapid.utils.constants import TIMEOUT_PERIOD
from rapi... | /rapid-sdk-0.0.8.tar.gz/rapid-sdk-0.0.8/rapid/rapid.py | 0.91497 | 0.349227 | rapid.py | pypi |
from typing import Union, List
from pandas import DataFrame
from rapid.exceptions import (
ColumnNotDifferentException,
DataFrameUploadValidationException,
)
from rapid.items.schema import Schema, SchemaMetadata, Column
from rapid import Rapid
def upload_and_create_dataframe(
rapid: Rapid, metadata: Schem... | /rapid-sdk-0.0.8.tar.gz/rapid-sdk-0.0.8/rapid/patterns/data.py | 0.872836 | 0.691035 | data.py | pypi |
from enum import Enum
from typing import Dict, List, Optional, Union
from pydantic.main import BaseModel
class SensitivityLevel(Enum):
PUBLIC = "PUBLIC"
PRIVATE = "PRIVATE"
PROTECTED = "PROTECTED"
class UpdateBehaviour(Enum):
APPEND = "APPEND"
OVERWRITE = "OVERWRITE"
class Owner(BaseModel):
... | /rapid-sdk-0.0.8.tar.gz/rapid-sdk-0.0.8/rapid/items/schema.py | 0.881398 | 0.388995 | schema.py | pypi |
from contextlib import closing
from .ui.text.progressbar import ProgressBar
import rapid
import gzip, os
import logging
log = logging.getLogger('root')
def init(data_dir, _ui):
""" Create rapid module."""
global spring_dir, pool_dir, rapid, ui
ui = _ui
log.info('Using data directory: %s', data_dir)
rapid.se... | /rapid-spring-0.6.0.tar.gz/rapid-spring-0.6.0/rapid/main.py | 0.554712 | 0.179279 | main.py | pypi |
import os, re, sys
import logging
from optparse import OptionParser
from rapid.main import *
from .interaction import TextUserInteraction
from rapid.unitsync.api import get_writable_data_directory
USAGE = """Usage: %prog [options...] <verb> [arguments...]
Where the different verbs and their arguments are:
* `upg... | /rapid-spring-0.6.0.tar.gz/rapid-spring-0.6.0/rapid/ui/text/main.py | 0.473414 | 0.247067 | main.py | pypi |
import os, ctypes
from ctypes import c_bool, POINTER, c_ushort, c_char, c_char_p, c_int, c_uint, c_float, Structure, create_string_buffer, cast, pointer
class StartPos(Structure):
_fields_ = [('x', c_int), ('y', c_int)]
def __str__(self):
return '(%i, %i)' % (self.x, self.y)
class MapInfo(Structure):
def __init_... | /rapid-spring-0.6.0.tar.gz/rapid-spring-0.6.0/rapid/unitsync/unitsync.py | 0.425009 | 0.207054 | unitsync.py | pypi |
from io import BytesIO
from pathlib import Path
from typing import Union
import cv2
import numpy as np
from PIL import Image, UnidentifiedImageError
InputType = Union[str, np.ndarray, bytes, Path]
class LoadImage():
def __init__(self, ):
pass
def __call__(self, img: InputType) -> np.ndarray:
... | /rapid_table-3.6-py3-none-any.whl/rapid_table/utils.py | 0.789356 | 0.334753 | utils.py | pypi |
import argparse
import copy
import time
from pathlib import Path
from typing import Union
import cv2
import numpy as np
from rapidocr_onnxruntime import RapidOCR
from .table_matcher import TableMatch
from .table_structure import TableStructurer
from .utils import LoadImage, vis_table
root_dir = Path(__file__).resolv... | /rapid_table-3.6-py3-none-any.whl/rapid_table/rapid_table.py | 0.721449 | 0.183722 | rapid_table.py | pypi |
import numpy as np
from .utils import compute_iou, deal_bb, distance
class TableMatch():
def __init__(self, filter_ocr_result=True, use_master=False):
self.filter_ocr_result = filter_ocr_result
self.use_master = use_master
def __call__(self, structure_res, dt_boxes, rec_res):
pred_st... | /rapid_table-3.6-py3-none-any.whl/rapid_table/table_matcher/matcher.py | 0.40592 | 0.332988 | matcher.py | pypi |
import re
def deal_isolate_span(thead_part):
"""
Deal with isolate span cases in this function.
It causes by wrong prediction in structure recognition model.
eg. predict <td rowspan="2"></td> to <td></td> rowspan="2"></b></td>.
:param thead_part:
:return:
"""
# 1. find out isolate span... | /rapid_table-3.6-py3-none-any.whl/rapid_table/table_matcher/utils.py | 0.594551 | 0.675771 | utils.py | pypi |
import subprocess
from pathlib import Path
from typing import Optional
cur_dir = Path(__file__).resolve().parent
class VideoSubFinder:
def __init__(
self,
vsf_exe_path: Optional[str] = None,
clear_dirs: bool = True,
run_search: bool = True,
create_cleared_text_images: bool... | /rapid_videocr-2.2.7-py3-none-any.whl/rapid_videocr/video_sub_finder.py | 0.775095 | 0.28189 | video_sub_finder.py | pypi |
import argparse
from pathlib import Path
from typing import Optional
try:
from .logger import logger
from .rapid_videocr import RapidVideOCR
from .utils import float_range
from .video_sub_finder import VideoSubFinder
except:
from logger import logger
from utils import float_range
from video... | /rapid_videocr-2.2.7-py3-none-any.whl/rapid_videocr/main.py | 0.746231 | 0.166134 | main.py | pypi |
import argparse
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Union
import cv2
import numpy as np
from rapidocr_onnxruntime import RapidOCR
from tqdm import tqdm
try:
from .logger import logger
from .utils import CropByProject, compute_poly_iou, is_inclusive_each_other, mkdir
except... | /rapid_videocr-2.2.7-py3-none-any.whl/rapid_videocr/rapid_videocr.py | 0.779616 | 0.166066 | rapid_videocr.py | pypi |
import argparse
from enum import Enum
from pathlib import Path
from typing import List, Union
import cv2
import numpy as np
import shapely
from shapely.geometry import MultiPoint, Polygon
logger_initialized = {}
class RecMode(Enum):
SINGLE = "single"
CONCAT = "concat"
class CropByProject:
"""投影法裁剪"""
... | /rapid_videocr-2.2.7-py3-none-any.whl/rapid_videocr/utils.py | 0.754553 | 0.459925 | utils.py | pypi |
# rapidash: a transformer between database and Parquet file
## Introduction:
rapidash is a python tool library based on Python pyarrow which supports multithread and asynchronous calls. It can help users transform data between database and Parquet files.
## Features:
- Multithread: support batch reading/writeing an... | /rapidash-0.0.6.tar.gz/rapidash-0.0.6/README.md | 0.575588 | 0.864539 | README.md | pypi |
import ckeditor.fields
import datetime
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import filer.fields.image
import imagekit.models.fields
import mptt.fields
class Migration(migrations.Migration):
initial = True
dependencies = [
migrati... | /rapidbounce-cms-0.3.0.tar.gz/rapidbounce-cms-0.3.0/rapidbounce_cms/migrations/0001_initial.py | 0.476823 | 0.189671 | 0001_initial.py | pypi |
<h1 align="center">
<img src="https://raw.githubusercontent.com/maxbachmann/RapidFuzz/main/docs/img/RapidFuzz.svg?sanitize=true" alt="RapidFuzz" width="400">
</h1>
<h4 align="center">Rapid fuzzy string matching in Python and C++ using the Levenshtein Distance</h4>
<p align="center">
<a href="https://github.com/maxba... | /rapidfuzz-2.4.2.tar.gz/rapidfuzz-2.4.2/README.md | 0.756088 | 0.933764 | README.md | pypi |
<img src='logo.png' width='100%'></img>
<h1 align='center'>RapidKode: get it right the first time</h1>
#### RapidKode is a Python package that provides fast, flexible, and expressive data structures,alogorithms designed to make working with both competitive programming and coding easy and intuitive. It aims to be th... | /rapidkode-1.0.6.tar.gz/rapidkode-1.0.6/README.md | 0.401923 | 0.937697 | README.md | pypi |
import abc
from collections import namedtuple
from tokenizers import BertWordPieceTokenizer
CharLevelEncoding = namedtuple("CharLevelEncoding", ["tokens", "ids", "type_ids", "attention_mask", "offsets"])
class CharLevelTokenizer(abc.ABC):
"""Abstract char-level tokenizer"""
@abc.abstractmethod
def enco... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/charlevel_tokenizer.py | 0.810104 | 0.245062 | charlevel_tokenizer.py | pypi |
import abc
import logging
import multiprocessing
import random
from collections import namedtuple
from typing import List
from tokenizers import BertWordPieceTokenizer
from rapidnlp_datasets import readers
ExampleForMaskedLanguageModel = namedtuple(
"ExampleForMaskedLanguageModel", ["input_ids", "token_type_ids"... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/masked_lm.py | 0.855399 | 0.325755 | masked_lm.py | pypi |
import json
import logging
import os
import tensorflow as tf
try:
AUTOTUNE = tf.data.AUTOTUNE
except Exception as e:
AUTOTUNE = tf.data.experimental.AUTOTUNE
def read_tfrecord_files(input_files, num_parallel_calls=None, **kwargs):
num_parallel_calls = num_parallel_calls or AUTOTUNE
if isinstance(inp... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/utils_tf.py | 0.452778 | 0.300021 | utils_tf.py | pypi |
import abc
import logging
import multiprocessing
from collections import namedtuple
from typing import List
from tokenizers import BertWordPieceTokenizer
from rapidnlp_datasets import readers
ExampleForSequenceClassification = namedtuple(
"ExampleForSequenceClassification", ["input_ids", "token_type_ids", "atten... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/sequence_classification.py | 0.846483 | 0.311898 | sequence_classification.py | pypi |
import abc
import logging
import multiprocessing
from copy import deepcopy
from typing import List
from tokenizers import BertWordPieceTokenizer
from rapidnlp_datasets import readers
class ExampleForSimCSE:
"""Example for SimCSE model"""
def __init__(self, **kwargs) -> None:
self.tokens = kwargs.ge... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/simcse.py | 0.851737 | 0.295116 | simcse.py | pypi |
import abc
import multiprocessing
from collections import namedtuple
from typing import List, Union
from black import logging
from tokenizers import BertWordPieceTokenizer
from rapidnlp_datasets import readers
from .charlevel_tokenizer import BertCharLevelTokenizer
ExampleForTokenClassification = namedtuple(
"E... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/token_classification.py | 0.808786 | 0.33372 | token_classification.py | pypi |
import logging
import tensorflow as tf
from . import utils
from .dataset import TFDataset
class TFDatasetForSequenceClassifiation(TFDataset):
"""Datapipe for sequence classification"""
def __init__(
self,
examples=None,
input_ids="input_ids",
token_type_ids="token_type_ids",... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/tf/sequence_classification_dataset.py | 0.872863 | 0.36201 | sequence_classification_dataset.py | pypi |
import logging
from typing import List
import tensorflow as tf
from . import utils
from .dataset import TFDataset
class TFDatasetForSimCSE(TFDataset):
"""Dataset for SimCSE in tensorflow"""
def __init__(self, examples, with_positive_sequence=False, with_negative_sequence=False, **kwargs) -> None:
s... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/tf/simcse_dataset.py | 0.899392 | 0.488527 | simcse_dataset.py | pypi |
import abc
import tensorflow as tf
class TFDataset(abc.ABC):
"""Abstract dataset"""
def __init__(self, examples=None, **kwargs) -> None:
super().__init__()
self.examples = examples or []
def __call__(
self,
dataset: tf.data.Dataset,
batch_size=32,
pad_id=... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/tf/dataset.py | 0.829561 | 0.171998 | dataset.py | pypi |
import json
import logging
import os
import tensorflow as tf
try:
AUTOTUNE = tf.data.AUTOTUNE
except Exception as e:
AUTOTUNE = tf.data.experimental.AUTOTUNE
def read_tfrecord_files(input_files, num_parallel_calls=None, **kwargs):
num_parallel_calls = num_parallel_calls or AUTOTUNE
if isinstance(inp... | /rapidnlp_datasets-0.2.0-py3-none-any.whl/rapidnlp_datasets/tf/utils.py | 0.452778 | 0.300021 | utils.py | pypi |
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