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
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Tutorial 8 - Using A Custom Model Fit
=====================================
SAILS provides implementations of several algorithms for fitting autoregressive
models but it is straightforward to create a custom class which implements a
new model fit or uses one from another package.
This tutorial will outline how to cre... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial8.rst | 0.971307 | 0.957715 | tutorial8.rst | pypi |
Tutorial 5 - MVAR Connectivity Estimation
=========================================
In this tutorial, we will explore a range of connectivity estimators in a
simulated network.
We start by importing sails and defining some meta-parameters as we did in
previous tutorials.
.. code-block:: python
import numpy as n... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial5.rst | 0.964043 | 0.917893 | tutorial5.rst | pypi |
Tutorial 1 - A pink noise system
================================
In this tutorial we will demonstrate how to set up a simple univariate
AR model which models a pink noise process. We will use the model
to demonstrate how to extract the transfer function using both a Fourier
and Modal estimator.
We start by importin... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial1.rst | 0.966268 | 0.959383 | tutorial1.rst | pypi |
Tutorial 11 - Morlet Wavelet Decomposition
=======================================================
In this tutorial, we will look at describing time-frequency dynamics in a
signal using a Morlet Wavelet decomposition.
For this tutorial, we will use the same MEG example data which we have used in previous
tutorials.
... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial11.rst | 0.948131 | 0.963196 | tutorial11.rst | pypi |
Tutorial 3 - Fitting real univariate data
=========================================
In the previous two tutorials we set up our system using the polynomial
representation. In most cases, we will want to learn the parameters
of our model from real data. In this section, we cover how this is
done.
We will be using so... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial3.rst | 0.9556 | 0.888372 | tutorial3.rst | pypi |
Tutorial 10 - Dynamic connectivity during a task
================================================
Here, we will look at using MVAR modelling to describe changes in connectivity
within a functional network as participants perform a simple button press task.
This is similar to the sliding window modelling in tutorial 6
... | /sails-1.4.0.tar.gz/sails-1.4.0/doc/source/tutorials/tutorial10.rst | 0.914991 | 0.950041 | tutorial10.rst | pypi |
from saimll import SAIML
# There are include macros that will do cool affects like make the passed text rainbow
SAIML.print("[^rainbow]Rainbow Text")
# There is also an included macro for displaying hyperlinks
SAIML.print("[~https://tired-fox.github.io/SAIMLDecor/teddecor.html]Documentation")
# There is currently also... | /saimll-0.4.0.tar.gz/saimll-0.4.0/examples/basics.py | 0.66769 | 0.32532 | basics.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
stdev (float) representing ... | /saj_distributions-0.1.tar.gz/saj_distributions-0.1/saj_distributions/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
from colorama import Fore
class TableVetayenaKanchha(Exception):
"""
Database ma nai table navayesi aaune error !
"""
def __init__(self, table_name,db_name) -> None:
super().__init__(Fore.RED + f"Timle deko table '{table_name}' {db_name} vanne database ma nai vetayena ! Spelling bigryo ki her... | /sajilo_orm-0.0.6-py3-none-any.whl/sajilo_orm/exceptions.py | 0.586523 | 0.155142 | exceptions.py | pypi |
import jax
import jax.numpy as jnp
from flax import linen as nn
from typing import Callable, Optional
from .utils import ExpNormalSmearing
from .functional import get_x_minus_xt, get_x_minus_xt_norm, get_h_cat_ht
from functools import partial
def double_sigmoid(x):
return 2.0 * jax.nn.sigmoid(x)
class ContinuousF... | /sake-gnn-0.0.2.post1.tar.gz/sake-gnn-0.0.2.post1/sake/layers.py | 0.872538 | 0.289657 | layers.py | pypi |
import jax
import jax.numpy as jnp
import numpy as onp
from flax import linen as nn
import math
def coloring(x, mean, std):
return std * x + mean
def cosine_cutoff(x, lower=0.0, upper=5.0):
cutoffs = 0.5 * (
jnp.cos(
math.pi
* (
2
* (x - lower)
... | /sake-gnn-0.0.2.post1.tar.gz/sake-gnn-0.0.2.post1/sake/utils.py | 0.841272 | 0.414129 | utils.py | pypi |
import jax
import jax.numpy as jnp
from flax import linen as nn
from typing import Callable, Union, List
from .layers import (
DenseSAKELayer,
EquivariantGraphConvolutionalLayer,
EquivariantGraphConvolutionalLayerWithSmearing,
)
class DenseSAKEModel(nn.Module):
hidden_features: int
out_features: in... | /sake-gnn-0.0.2.post1.tar.gz/sake-gnn-0.0.2.post1/sake/models.py | 0.891729 | 0.291882 | models.py | pypi |
import io
import os
from shutil import copyfile
from sakee import addoninfo
from sakee.colors import Colors
from sakee.stub import KodiStub
class File(object): # NOSONAR
def __init__(self, path, flags='r'):
""" File class.
:param str path: The file or directory to open
:param str fl... | /sakee-0.1.4.tar.gz/sakee-0.1.4/xbmcvfs.py | 0.682891 | 0.283168 | xbmcvfs.py | pypi |
from sakura.daemon.processing.operator import Operator
from sakura.daemon.processing.source import ComputedSource
from numpy.lib import recfunctions
from time import time
import numpy as np
class PlotOperator(Operator):
NAME = "Plot"
SHORT_DESC = "Displays a plot from a list of 2D points"
TAGS = [ "visual... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/operators/plot/operator.py | 0.645455 | 0.190762 | operator.py | pypi |
from sakura.daemon.processing.operator import Operator
from sakura.daemon.processing.source import ComputedSource
from numpy.lib import recfunctions
from time import time
import numpy as np
class gps2d(Operator):
NAME = "GPS_2D"
SHORT_DESC = "Displays trajectories on a 2D map."
TAGS = [ "visualisation"]
... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/operators/gps2d/operator.py | 0.555676 | 0.188231 | operator.py | pypi |
import numpy as np
import math, copy, random
def distance_2D(a, b):
return math.sqrt( (b[0]-a[0])**2 +
(b[1]-a[1])**2 )
def m_mult(a, b):
i, j = 0, 0
M = [1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1]
while i < 4:
while j < 4:
M[i*4 + j] = a[i*4]*b[j]... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/operators/SpaceTimeCube/stc/libs/geomaths.py | 0.404155 | 0.535888 | geomaths.py | pypi |
import math, time
import numpy as np
from . import geomaths as gm
def intersection(p1,p2,v1,v2):
beta = (p1[1] + (p2[0]-p1[0])*v1[1]/v1[0] - p2[1])/(v2[1] - v2[0]*v1[1]/v1[0])
return [x+beta*y for x,y in zip(p1,v1)]
def cross(v1,v2):
return [v1[1]*v2[2]-v1[2]*v2[1],
v1[2]*v2[0]-v1[0]*v2[2],
... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/operators/SpaceTimeCube/stc/libs/projector.py | 0.487551 | 0.414958 | projector.py | pypi |
import numpy as np
from .. import shader as sh
from .. import geomaths as gm
try:
from OpenGL.GL import *
from OpenGL.GL import shaders
except:
print ('''ERROR in cube.py: PyOpenGL not installed properly. ** ''')
def wire_cube(mins, maxs):
size = np.fabs(maxs - mins)
... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/operators/SpaceTimeCube/stc/libs/display_objs/cube.py | 0.499268 | 0.349644 | cube.py | pypi |
from pony.orm import Required, Optional, Set, Json, \
composite_key as UNIQUE, PrimaryKey
from sakura.hub.mixins.dataflow import DataflowMixin
from sakura.hub.mixins.project import ProjectMixin
from sakura.hub.mixins.page import ProjectPageMixin
from sakura.hub.mixins.daemon import DaemonMixin
from... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/sakura/hub/db/schema.py | 0.674158 | 0.291756 | schema.py | pypi |
import re
GEOJSON_BBOX = '''{
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "%(srid)s"
}
},
"coordinates": [[
[%(min_longitude)s, %(min_latitude)s],
[%(min_longitude)s, %(max_latitude)s],
[%(max_longitude)s, %(max_latitud... | /sakura-py-0.9.6.tar.gz/sakura-py-0.9.6/sakura/daemon/processing/geo.py | 0.403449 | 0.412648 | geo.py | pypi |
import requests
import json
import base64
import random
from urllib.parse import unquote
from Sakurajima.models import (
Anime,
RecommendationEntry,
Relation,
AniWatchEpisode,
Episode,
ChronicleEntry,
UserAnimeListEntry,
UserMedia,
UserOverview,
AniwatchStats,
Notification,
... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/api.py | 0.711832 | 0.209409 | api.py | pypi |
import datetime
import requests
import json
from m3u8 import M3U8
from Crypto.Cipher import AES
from Sakurajima.models.relation import Relation
from Sakurajima.models.recommendation import RecommendationEntry
from Sakurajima.models.chronicle import ChronicleEntry
from Sakurajima.models.media import Media
from Sakurajim... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/base_models.py | 0.546496 | 0.205974 | base_models.py | pypi |
class AniwatchStats(object):
def __init__(self, data_dict):
self.total_streams = data_dict["hoster"][0]["count"]
"""The total number of streams on aniwatch.me"""
self.total_1080p_streams = data_dict["hoster"][0]["rows"][0]["count"]
"""The total number of 1080p streams on aniwatch.me"... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/stats.py | 0.624866 | 0.316633 | stats.py | pypi |
import json
from Sakurajima.models import base_models as bm
class RecommendationEntry(object):
def __init__(self, data_dict, network):
self.__network = network
self.title = data_dict.get("title", None)
"""The title of the recommeneded anime."""
self.episodes_max = data_dict.get("ep... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/recommendation.py | 0.621426 | 0.364976 | recommendation.py | pypi |
import requests
import json
import datetime
class Notification(object):
def __init__(self, data_dict, network):
self.__network = network
self.data_dict = data_dict
self.id = data_dict.get("id", None)
"""The ID of the notification."""
self.type = data_dict.get("type", None)
... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/notification.py | 0.584983 | 0.284675 | notification.py | pypi |
import requests
import json
from Sakurajima.models import base_models as bm
from Sakurajima.models.chronicle import ChronicleEntry
import datetime
class UserAnimeListEntry(object):
"""A UserAnimeListEntry represents a single show on a user's aniwatch.me
anime list.
"""
def __init__(self, data_dict, n... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/user_models.py | 0.801431 | 0.390883 | user_models.py | pypi |
import requests
import json
import datetime
class Media(object):
"""Contains media entries for categories like openings, endings and OSTs"""
def __init__(self, data_dict, network, anime_id):
self.__network = network
self.anime_id = anime_id
"""The ID of the anime to which the media bel... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/models/media.py | 0.71602 | 0.356755 | media.py | pypi |
from Sakurajima.models import base_models as bm
class EpisodeList(object):
"""An :class:`EpisodeList` is very similar to a normal list. You can do everything
with a :class:`EpisodeList` that you can with a normal list. The only difference is that
an EpisodeList has some convinience methods that make sele... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/utils/episode_list.py | 0.852107 | 0.375792 | episode_list.py | pypi |
import os
from Crypto.Cipher import AES
from Crypto.Util.Padding import pad, unpad
from Sakurajima.utils.merger import ChunkMerger, FFmpegMerger, ChunkRemover
from threading import Thread, Lock
from progress.bar import IncrementalBar
from Sakurajima.utils.progress_tracker import ProgressTracker
from Sakurajima.utils.de... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/utils/downloader.py | 0.695855 | 0.268654 | downloader.py | pypi |
import shutil
import subprocess
import os
class ChunkMerger(object):
"""Merges the downloaded chunks by concatinating them into a single file.
"""
def __init__(self, file_name, total_chunks):
"""
:param file_name: The file name prefix of the chunks.
:type file_name: str
:p... | /sakurajima-0.3.1.tar.gz/sakurajima-0.3.1/Sakurajima/utils/merger.py | 0.540924 | 0.271429 | merger.py | pypi |
# %% auto 0
__all__ = ['WithChildrenMixin', 'Data', 'MappedData', 'map_data', 'render', 'FrontMatter', 'parse_arg', 'parse_attrs']
# %% ../nbs/00_core.ipynb 4
from typing import Any
from copy import deepcopy
from textwrap import indent
from collections import ChainMap
from typing import Callable, Optional
from jinja2... | /sal_code_generator-0.0.29-py3-none-any.whl/sal/core.py | 0.812756 | 0.444505 | core.py | pypi |
import time
from .Color import Color
from .Typer import Typer
import random
class ProgressBar:
def __init__(self, iteration: int, total: int, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r", ending = '\n') -> None:
"""
Call in a loop to create terminal... | /sal_dutils-0.1.2-py3-none-any.whl/dutils/ProgressBar.py | 0.644113 | 0.194923 | ProgressBar.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
stdev (float) representing ... | /salRad_distributions-0.1.tar.gz/salRad_distributions-0.1/salRad_distributions/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
import argparse
from pprint import pformat
__author__ = "salammzere3"
__copyright__ = "Copyright (c) 2023, salammzere3"
EMOTICONS = [":)", ":D", ":P", ":S", ":(", "=)", "=/", ":/", ":{", ";)"]
EMOJIS = [
"\U0001f600",
"\U0001f603",
"\U0001f604",
"\U0001f601",
"\U0001f605",
"\U0001f923",
"... | /salamemojify-1.0.0-py3-none-any.whl/salamemojify-1.0.0.data/scripts/salamemojify.py | 0.452294 | 0.226987 | salamemojify.py | pypi |
import functools
from heapq import nsmallest
from operator import itemgetter
from collections import defaultdict
try:
from collections import Counter
except ImportError:
class Counter(dict):
'Mapping where default values are zero'
def __missing__(self, key):
return 0
def twolvl... | /salang_saara-0.4.2-py3-none-any.whl/CodernityDB/lfu_cache_with_lock.py | 0.466846 | 0.15084 | lfu_cache_with_lock.py | pypi |
import re
import tokenize
import token
import uuid
class IndexCreatorException(Exception):
def __init__(self, ex, line=None):
self.ex = ex
self.line = line
def __str__(self):
if self.line:
return repr(self.ex + "(in line: %d)" % self.line)
return repr(self.ex)
... | /salang_saara-0.4.2-py3-none-any.whl/CodernityDB/indexcreator.py | 0.414899 | 0.166981 | indexcreator.py | pypi |
from salary_stone.salary_extractor import Salary_Extractor
def recommend(skill_vec, data, model: Salary_Extractor, extracted_scol:str):
"""
The purpose of this method is to provide the recommended skills and predicted percentage increase in salary
that could be expected if that skill were to be included.
... | /salary_stone-0.4.0.tar.gz/salary_stone-0.4.0/salary_stone/skill_recommender.py | 0.532182 | 0.751648 | skill_recommender.py | pypi |
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('saleboxdjango', '0021_auto_20210814_1825'),
]
operations = [
migrations.AddField(
model_name='attribute',
name='created',
field=models.DateTimeField(bla... | /salebox-django-0.0.243.tar.gz/salebox-django-0.0.243/saleboxdjango/migrations/0022_auto_20210814_1828.py | 0.729616 | 0.190159 | 0022_auto_20210814_1828.py | pypi |
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('saleboxdjango', '0013_analytic'),
]
operations = [
migrations.AddField(
model_name='analytic',
name='language',
field=models.CharField(blank=True, max_l... | /salebox-django-0.0.243.tar.gz/salebox-django-0.0.243/saleboxdjango/migrations/0014_auto_20191216_1334.py | 0.703753 | 0.159905 | 0014_auto_20191216_1334.py | pypi |
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_... | /salebox-django-0.0.243.tar.gz/salebox-django-0.0.243/saleboxdjango/migrations/0001_initial.py | 0.513181 | 0.170681 | 0001_initial.py | pypi |
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('saleboxdjango', '0019_auto_20210807_0644'),
]
operations = [
migrations.CreateModel(
name='ContentP... | /salebox-django-0.0.243.tar.gz/salebox-django-0.0.243/saleboxdjango/migrations/0020_contentpage_contentpageitem_keyvaluestore_synclog_syncqueue.py | 0.534127 | 0.193338 | 0020_contentpage_contentpageitem_keyvaluestore_synclog_syncqueue.py | pypi |
from django.conf import settings
from django.utils.translation import get_language
from python2c2p.redirectapi import twoctwop_redirectapi
from saleboxdjango.lib.basket import SaleboxBasket
from saleboxdjango.views.checkout.gateway import SaleboxCheckoutGatewayView
class SaleboxProviders2C2PGatewayView(SaleboxCheck... | /salebox-django-0.0.243.tar.gz/salebox-django-0.0.243/saleboxdjango/providers/twoctwop/gateway.py | 0.401336 | 0.184786 | gateway.py | pypi |
import json
from datetime import datetime
import requests
from bs4 import BeautifulSoup
def parse_report(url):
"""
Parse the report's HTML into a Report object.
Parameters
-------------
url: :class:`str`
The report URL
Raises
-------------
ValueError
Parsing failed (I... | /salem_parser-v1.0.3.tar.gz/salem_parser-v1.0.3/salem_parser/main.py | 0.700997 | 0.172189 | main.py | pypi |
.. _gis:
Map transformations
===================
Most of the georeferencing machinery for gridded datasets is
handled by the :py:class:`~salem.Grid` class: its capacity to handle
gridded datasets in a painless manner was one of the primary
motivations to develop Salem.
Grids
-----
A point on earth can be defined un... | /salem-0.3.9.tar.gz/salem-0.3.9/docs/gis.rst | 0.959988 | 0.841696 | gis.rst | pypi |
from .utils import graphql_request, graphql_multipart_request, override_dict, handle_errors, get_payload
class ETLDataLoader:
"""abstraction around several graphQL query to load data into Saleor.
Notes
-----
This class requires a valid `auth_token` to be provided during
initialization. An `app` m... | /saleor-gql-loader-0.0.5.tar.gz/saleor-gql-loader-0.0.5/saleor_gql_loader/data_loader.py | 0.904598 | 0.618291 | data_loader.py | pypi |
import requests
import json
from pathlib import Path
from requests_toolbelt import MultipartEncoder
from django.core.serializers.json import DjangoJSONEncoder
GQL_DEFAULT_ENDPOINT = "http://localhost:8000/graphql/"
def graphql_request(query, variables={}, headers={},
endpoint=GQL_DEFAULT_ENDPOINT... | /saleor-gql-loader-0.0.5.tar.gz/saleor-gql-loader-0.0.5/saleor_gql_loader/utils.py | 0.806472 | 0.302314 | utils.py | pypi |
<div align="center">
<h1>Saleor Commerce</h1>
</div>
<div align="center">
<strong>Customer-centric e-commerce on a modern stack</strong>
</div>
<div... | /saleor-2.10.1.tar.gz/saleor-2.10.1/README.md | 0.749912 | 0.771198 | README.md | pypi |
import pandas as pd
# --------------------------------------------------------------------------
# Data pipeline
class SalesPipeline:
"""Backend pipeline for data in sales_analysis/data_pipeline/data
Parameters
----------
data : dict of pd.DataFrame
dict should contain sales data from
... | /sales_analysis-0.4-py3-none-any.whl/sales_analysis/data_pipeline/_pipeline.py | 0.859531 | 0.356979 | _pipeline.py | pypi |
from itertools import chain
from sklearn import base
import pandas as pd
import numpy as np
import os
import glob
import datetime
class ToWeeklySalesDataset(base.BaseEstimator, base.TransformerMixin):
def __init__(self, DATETYPE_COLUMNS_LIST, DTYPE_DICT, COLS_TO_KEEP, INPUT_FILE_PREFIX, DEBUT_DATE):
self.D... | /sales_forecast_package-0.0.3.tar.gz/sales_forecast_package-0.0.3/sales_forecast_package/ToWeeklySalesDataset.py | 0.407098 | 0.183191 | ToWeeklySalesDataset.py | pypi |
import mysql.connector as sql
import datetime
#Crear connexión
cnx = sql.connect(user='root',
password='example',
host='db',
database='booking')
# Creamos la clase BaseManager
class BaseManager:
connection = None
@classmethod
# Establece una... | /sales_module-0.0.1.tar.gz/sales_module-0.0.1/sales.py | 0.434941 | 0.210848 | sales.py | pypi |
from hyperopt import STATUS_OK, Trials, fmin, hp, tpe
from xgboost import XGBRegressor
from functools import partial
from sklearn.metrics import mean_squared_error
from sklearn.ensemble import RandomForestRegressor
DEFAULT_XGBR_SPACE = {
'n_estimators': hp.quniform('n_estimators', 10, 1000, 1),
'max_depth': hp... | /sales_pred_filiankova-1.3.9.tar.gz/sales_pred_filiankova-1.3.9/sales_pred_filiankova/models/tuning.py | 0.738952 | 0.375878 | tuning.py | pypi |
import numpy as np
import pandas as pd
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
import category_encoders as ce
class FeatureScaler(BaseEstimator, TransformerMixin):
def __init__(self):
self._feat_scaler... | /sales_pred_filiankova-1.3.9.tar.gz/sales_pred_filiankova-1.3.9/sales_pred_filiankova/features/preprocessing.py | 0.759136 | 0.292623 | preprocessing.py | pypi |
import time
from enum import Enum
from typing import List
from . import base as bulk_base
from .. import base
from ... import config, exceptions
from ...models import bulk as models
class OPERATION(Enum):
DELETE = 'delete'
INSERT = 'insert'
QUERY = 'query'
QUERY_ALL = 'queryall'
UPSERT = 'upsert'... | /salesforce-api-0.1.45.tar.gz/salesforce-api-0.1.45/salesforce_api/services/bulk/v1.py | 0.757077 | 0.153803 | v1.py | pypi |
# Salesforce Bulkipy
A Python library for the Salesforce Bulk API (that actually works)
## Changes over [salesforce-bulk](https://github.com/heroku/salesforce-bulk)
The [salesforce-bulk](https://github.com/heroku/salesforce-bulk) library was used to export 18k records to [Wingify](https://github.com/wingify)'s Sales... | /salesforce-bulkipy-1.0.tar.gz/salesforce-bulkipy-1.0/README.md | 0.417984 | 0.921534 | README.md | pypi |
import base64
import dateutil.parser
import pyarrow
from .constants import API_VERSION_V2
from .constants import QUERY_RESPONSE_KEY_DONE
from .constants import QUERY_RESPONSE_KEY_NEXT_BATCH_ID
from .constants import QUERY_RESPONSE_KEY_ARROW_STREAM
from .constants import QUERY_RESPONSE_KEY_METADATA
from .constants im... | /salesforce-cdp-connector-1.0.7.tar.gz/salesforce-cdp-connector-1.0.7/salesforcecdpconnector/pandas_utils.py | 0.659405 | 0.209025 | pandas_utils.py | pypi |
import dateutil.parser
from .constants import QUERY_RESPONSE_KEY_DATA
from .constants import QUERY_RESPONSE_KEY_METADATA
from .constants import QUERY_RESPONSE_KEY_DONE
from .constants import QUERY_RESPONSE_KEY_NEXT_BATCH_ID
from .constants import DATA_TYPE_TIMESTAMP
from .constants import QUERY_RESPONSE_KEY_PLACE_IN_O... | /salesforce-cdp-connector-1.0.7.tar.gz/salesforce-cdp-connector-1.0.7/salesforcecdpconnector/query_result_parser.py | 0.690872 | 0.203312 | query_result_parser.py | pypi |
from datetime import date, time, datetime
from .exceptions import NotSupportedError, Error
from .query_result_parser import QueryResultParser
from .query_submitter import QuerySubmitter
class SalesforceCDPCursor:
"""
This class represents the cursor
"""
_TRANSLATION_TABLE = str.maketrans({"\\": r"\\... | /salesforce-cdp-connector-1.0.7.tar.gz/salesforce-cdp-connector-1.0.7/salesforcecdpconnector/cursor.py | 0.871461 | 0.210279 | cursor.py | pypi |
<p align="center">
<br>
<img src="assets/logo.png" width="500"/>
<br>
<p>
<div align="center">
<a href="https://opensource.org/license/apache-2-0/">
<img alt="license" src="https://img.shields.io/badge/License-Apache%202.0-green.svg"/>
</a>
<a href="https://www.python.org/downloads/release/py... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/README.md | 0.753194 | 0.927626 | README.md | pypi |
import sys
from pathlib import Path
sys.path.append(str(Path(".").absolute().parent))
from transformers import AutoTokenizer
from codetf.models.base_model import BaseModel
from transformers import AutoModelForSeq2SeqLM, AutoConfig
from codetf.common.registry import registry
from accelerate import Accelerator
import tor... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/models/seq2seq_models/__init__.py | 0.483161 | 0.178097 | __init__.py | pypi |
import sys
from pathlib import Path
sys.path.append(str(Path(".").absolute().parent))
from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig
from codetf.models.base_model import BaseModel
from codetf.common.registry import registry
from collections import defaultdict
from tqdm import tqdm
import torch... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/models/causal_lm_models/__init__.py | 0.454472 | 0.168857 | __init__.py | pypi |
import sys
from pathlib import Path
sys.path.append(str(Path(".").absolute().parent))
from transformers import RobertaTokenizer, RobertaModel, RobertaConfig
from codetf.models.base_model import BaseModel
from codetf.common.registry import registry
from accelerate import Accelerator
from collections import defaultdict
f... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/models/bert_models/__init__.py | 0.442877 | 0.152473 | __init__.py | pypi |
from codetf.data_utility.base_dataset import BaseDataset
from datasets import load_dataset
class CodeXGLUEDataset(BaseDataset):
def __init__(self, tokenizer, max_length=512):
super().__init__(tokenizer, max_length)
self.load_funcs = {
'text-to-code': self.load_codexglue_text_... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/data_utility/codexglue_dataset.py | 0.803714 | 0.342599 | codexglue_dataset.py | pypi |
import sys
from pathlib import Path
sys.path.append(str(Path(".").absolute().parent))
from codetf.models import load_model_pipeline
from codetf.data_utility.util import EOF_STRINGS, EndOfFunctionCriteria, remove_last_block
from torch.utils.data.dataloader import DataLoader
from transformers import StoppingCriteriaList
... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/performance/model_evaluator.py | 0.596198 | 0.230065 | model_evaluator.py | pypi |
import sacrebleu
from rouge_score import rouge_scorer
from nltk.translate.meteor_score import meteor_score
from sklearn.metrics import f1_score, precision_score, recall_score
from transformers import EvalPrediction
class EvaluationMetric:
def __init__(self, metric, tokenizer):
self.metric = metric
... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/performance/evaluation_metric.py | 0.826081 | 0.420778 | evaluation_metric.py | pypi |
import json
import os
from urllib.parse import urlparse
from iopath.common.file_io import g_pathmgr
from codetf.common.registry import registry
def now():
from datetime import datetime
return datetime.now().strftime("%Y%m%d%H%M")[:-1]
def is_url(url_or_filename):
parsed = urlparse(url_or_filename)
... | /salesforce-codetf-1.0.2.2.tar.gz/salesforce-codetf-1.0.2.2/codetf/common/utils.py | 0.595845 | 0.215041 | utils.py | pypi |
from dataclasses import dataclass
from .data_api import DataAPI
__all__ = ["User", "Org", "Context"]
@dataclass(frozen=True, kw_only=True, slots=True)
class User:
"""
Information about the Salesforce user that invoked the function.
When deployed to a compute environment, the function runs as the Salesf... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/context.py | 0.883085 | 0.609088 | context.py | pypi |
from dataclasses import dataclass
from datetime import datetime
from typing import Generic, TypeVar
__all__ = ["InvocationEvent"]
T = TypeVar("T")
@dataclass(frozen=True, kw_only=True, slots=True)
class InvocationEvent(Generic[T]):
"""
The metadata and data payload of the event that caused the function to b... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/invocation_event.py | 0.933264 | 0.817829 | invocation_event.py | pypi |
from ._requests import (
CreateRecordRestApiRequest,
DeleteRecordRestApiRequest,
RestApiRequest,
UpdateRecordRestApiRequest,
)
from .record import Record
from .reference_id import ReferenceId
__all__ = ["UnitOfWork"]
class UnitOfWork:
"""
Represents a `UnitOfWork`.
A `UnitOfWork` encapsu... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/data_api/unit_of_work.py | 0.886782 | 0.870817 | unit_of_work.py | pypi |
from typing import Any, TypeVar
import aiohttp
import orjson
from aiohttp.payload import BytesPayload
from ..__version__ import __version__
from ._requests import (
CompositeGraphRestApiRequest,
CreateRecordRestApiRequest,
DeleteRecordRestApiRequest,
QueryNextRecordsRestApiRequest,
QueryRecordsRes... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/data_api/__init__.py | 0.84994 | 0.549459 | __init__.py | pypi |
from dataclasses import dataclass
# The order in `__all__` is the in which pdoc3 will display the classes in the docs.
__all__ = [
"DataApiError",
"SalesforceRestApiError",
"InnerSalesforceRestApiError",
"MissingFieldError",
"ClientError",
"UnexpectedRestApiResponsePayload",
]
class DataApiEr... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/data_api/exceptions.py | 0.926287 | 0.281603 | exceptions.py | pypi |
import logging
import structlog
def configure_logging() -> None:
"""
Configure structlog to output logs in logfmt format, using options recommended for best performance.
https://www.brandur.org/logfmt
https://www.structlog.org/en/stable/performance.html
"""
structlog.configure(
proce... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/_internal/logging.py | 0.761095 | 0.598312 | logging.py | pypi |
import importlib.util
import inspect
import sys
import traceback
import typing
from pathlib import Path
from typing import Any, Awaitable, Callable
from ..context import Context
from ..invocation_event import InvocationEvent
FUNCTION_MODULE_NAME = "main"
FUNCTION_NAME = "function"
Function = Callable[[InvocationEven... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/_internal/function_loader.py | 0.549641 | 0.318671 | function_loader.py | pypi |
import re
import sys
from dataclasses import dataclass
from pathlib import Path
from typing import Any
if sys.version_info < (3, 11):
# `tomllib` was only added to the stdlib in Python 3.11, so for older Python
# versions we use the third party `tomli` package, which has an identical API.
import tomli as t... | /salesforce_functions-0.6.0-py3-none-any.whl/salesforce_functions/_internal/config.py | 0.5564 | 0.155495 | config.py | pypi |
<p align="center">
<br>
<img src="docs/_static/logo_final.png" width="400"/>
<br>
<p>
<div align="center">
<a href="https://github.com/salesforce/LAVIS/releases"><img alt="Latest Release" src="https://img.shields.io/github/release/salesforce/LAVIS.svg" /></a>
<a href="https://opensource.salesforce.com/... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/README.md | 0.574275 | 0.830044 | README.md | pypi |
from collections import OrderedDict
from itertools import repeat
import collections.abc
import math
import torch
import torch.nn.functional as F
from torch import nn
from fairscale.nn.checkpoint.checkpoint_activations import checkpoint_wrapper
from lavis.models.eva_vit import convert_weights_to_fp16
from lavis.commo... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/clip_vit.py | 0.962961 | 0.379982 | clip_vit.py | pypi |
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.models.vision_transformer import _cfg, PatchEmbed
from timm.models.registry import register_model
from timm.models.layers import trunc_normal_, DropPath
from timm.models.helpers import named_apply, ad... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/vit.py | 0.947381 | 0.277357 | vit.py | pypi |
import math
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as checkpoint
from timm.models.layers import drop_path, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from lavis.common.dist_utils import download_cache... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/eva_vit.py | 0.917136 | 0.337749 | eva_vit.py | pypi |
import logging
import torch
from omegaconf import OmegaConf
from lavis.common.registry import registry
from lavis.models.base_model import BaseModel
from lavis.models.albef_models.albef_classification import AlbefClassification
from lavis.models.albef_models.albef_feature_extractor import AlbefFeatureExtractor
from l... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/__init__.py | 0.656218 | 0.152663 | __init__.py | pypi |
from copy import deepcopy
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.albef_models import compute_sim_matrix
from lavis.models.base_model import (
MomentumDistilationMixin,
SharedQueueMixin,
all_gather_with_grad,
concat_all_gather,
)
from la... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip_models/blip_retrieval.py | 0.878458 | 0.290257 | blip_retrieval.py | pypi |
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.blip_models.blip import BlipBase
from torch import nn
from lavis.models.med import XBertEncoder
from lavis.models.vit import VisionTransformerEncoder
@registry.register_model("blip_image_text_matching")
class Bl... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip_models/blip_image_text_matching.py | 0.766031 | 0.290768 | blip_image_text_matching.py | pypi |
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.base_model import tile
from lavis.models.blip_models.blip import BlipBase
from lavis.models.blip_models.blip_outputs import (
BlipOutput,
BlipIntermediateOutput,
)
from lavis.models.med import XBertEncoder,... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip_models/blip_vqa.py | 0.90943 | 0.644952 | blip_vqa.py | pypi |
from dataclasses import dataclass
from typing import Optional
import torch
from transformers.modeling_outputs import (
ModelOutput,
BaseModelOutputWithPoolingAndCrossAttentions,
CausalLMOutputWithCrossAttentions,
)
@dataclass
class BlipSimilarity(ModelOutput):
sim_i2t: torch.FloatTensor = None
si... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip_models/blip_outputs.py | 0.958333 | 0.733977 | blip_outputs.py | pypi |
from copy import deepcopy
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.base_model import MomentumDistilationMixin, SharedQueueMixin
from lavis.models.blip_models import tie_encoder_decoder_weights
from lavis.models.blip_models.blip import BlipBase
from lavis... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip_models/blip_pretrain.py | 0.900996 | 0.232093 | blip_pretrain.py | pypi |
import torch
import torch.nn as nn
from lavis.common.registry import registry
from lavis.models.base_model import BaseModel
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import GPT2LMHeadModel
from transformers.modeling_outputs import CausalLMOutputWithCrossAttentions
@registry.register_model("gpt_... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/gpt_models/gpt_dialogue.py | 0.819785 | 0.213746 | gpt_dialogue.py | pypi |
import logging
import torch
from torch.cuda.amp import autocast as autocast
import torch.nn as nn
from lavis.common.registry import registry
from lavis.models.blip2_models.blip2 import Blip2Base, disabled_train
from lavis.models.blip2_models.modeling_opt import OPTForCausalLM, OPTConfig
from transformers import AutoT... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip2_models/blip2_opt.py | 0.873647 | 0.331823 | blip2_opt.py | pypi |
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.blip2_models.blip2_qformer import Blip2Qformer
@registry.register_model("blip2_image_text_matching")
class Blip2ITM(Blip2Qformer):
"""
BLIP Image-Text Matching (ITM) model.
Supported model types:
... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip2_models/blip2_image_text_matching.py | 0.813905 | 0.381248 | blip2_image_text_matching.py | pypi |
import logging
import torch
import torch.nn as nn
from torch.cuda.amp import autocast as autocast
from transformers import T5TokenizerFast
from lavis.common.registry import registry
from lavis.models.blip2_models.blip2 import Blip2Base, disabled_train
from lavis.models.blip2_models.modeling_t5 import T5Config, T5ForC... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/blip2_models/blip2_t5.py | 0.87448 | 0.314761 | blip2_t5.py | pypi |
from copy import deepcopy
import numpy as np
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.common.utils import get_abs_path
from lavis.models.albef_models import AlbefBase
from lavis.models.albef_models.albef_outputs import (
AlbefIntermediateOutput,
AlbefOu... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/albef_pretrain.py | 0.853974 | 0.262471 | albef_pretrain.py | pypi |
from copy import deepcopy
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.models.albef_models import AlbefBase, compute_sim_matrix
from lavis.models.albef_models.albef_outputs import (
AlbefIntermediateOutput,
AlbefOutput,
AlbefSimilarity,
)
from lavis.mod... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/albef_retrieval.py | 0.868227 | 0.271653 | albef_retrieval.py | pypi |
import warnings
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.common.utils import get_abs_path
from lavis.models.albef_models import AlbefBase
from lavis.models.albef_models.albef_outputs import AlbefOutputFeatures
from lavis.models.med import BertForMaskedLM
from l... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/albef_feature_extractor.py | 0.836053 | 0.477493 | albef_feature_extractor.py | pypi |
from dataclasses import dataclass
from typing import Optional
import torch
from transformers.modeling_outputs import (
BaseModelOutputWithPoolingAndCrossAttentions,
CausalLMOutputWithCrossAttentions,
ModelOutput,
)
@dataclass
class AlbefSimilarity(ModelOutput):
sim_i2t: torch.FloatTensor = None
s... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/albef_outputs.py | 0.957893 | 0.636014 | albef_outputs.py | pypi |
import datetime
import logging
import os
import time
import lavis.common.dist_utils as dist_utils
import torch
import torch.distributed as dist
import torch.nn.functional as F
from lavis.common.dist_utils import download_cached_file
from lavis.common.logger import MetricLogger
from lavis.common.utils import is_url
fro... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/__init__.py | 0.572006 | 0.218211 | __init__.py | pypi |
import logging
import os
from copy import deepcopy
import torch
import torch.nn.functional as F
from lavis.common.registry import registry
from lavis.common.utils import get_abs_path, is_url
from lavis.models.albef_models import AlbefBase
from lavis.models.albef_models.albef_outputs import AlbefIntermediateOutput, Alb... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/albef_models/albef_vqa.py | 0.817246 | 0.249467 | albef_vqa.py | pypi |
import logging
import os
import torch
import torch.nn.functional as F
from lavis.common.dist_utils import download_cached_file
from lavis.common.utils import is_url
from lavis.models.base_model import BaseModel
from transformers import BertTokenizer
class AlproBase(BaseModel):
@classmethod
def init_tokenizer... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/alpro_models/__init__.py | 0.661158 | 0.241277 | __init__.py | pypi |
import logging
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils
import torch.utils.checkpoint
from einops import rearrange
from fairscale.nn.checkpoint.checkpoint_activations import checkpoint_wrapper
from .helpers import load_pretrained, load_pretra... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/timesformer/vit.py | 0.925052 | 0.264026 | vit.py | pypi |
import hashlib
import os
import urllib
import warnings
from tqdm import tqdm
_RN50 = dict(
openai="https://openaipublic.azureedge.net/clip/models/afeb0e10f9e5a86da6080e35cf09123aca3b358a0c3e3b6c78a7b63bc04b6762/RN50.pt",
yfcc15m="https://github.com/mlfoundations/open_clip/releases/download/v0.2-weights/rn50-q... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/clip_models/pretrained.py | 0.514888 | 0.243867 | pretrained.py | pypi |
Copied from https://github.com/openai/CLIP. Originally MIT License, Copyright (c) 2021 OpenAI.
"""
import gzip
import html
import os
from functools import lru_cache
from typing import Union, List
import ftfy
import regex as re
import torch
@lru_cache()
def default_bpe():
return os.path.join(
os.path.dirn... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/clip_models/tokenizer.py | 0.801159 | 0.342022 | tokenizer.py | pypi |
import logging
import torch
import torch.distributed.nn
from torch import distributed as dist, nn as nn
from torch.nn import functional as F
try:
import horovod.torch as hvd
except ImportError:
hvd = None
def gather_features(
image_features,
text_features,
local_loss=False,
gather_with_grad=F... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/clip_models/loss.py | 0.782496 | 0.346514 | loss.py | pypi |
import torch
import torch.nn as nn
from lavis.common.registry import registry
from lavis.models.base_model import BaseModel
from lavis.common.utils import get_abs_path
from transformers import T5Config, T5Tokenizer, T5ForConditionalGeneration
@registry.register_model("pnp_unifiedqav2_fid")
class PNPUnifiedQAv2FiD(T5F... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/pnp_vqa_models/pnp_unifiedqav2_fid.py | 0.893309 | 0.230422 | pnp_unifiedqav2_fid.py | pypi |
import torch
import torch.nn as nn
from itertools import chain
from lavis.common.registry import registry
from lavis.models.base_model import BaseModel
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import T5ForConditionalGeneration
from lavis.models.pnp_vqa_models import prepare_qa_input
from lavis.m... | /salesforce-lavis-1.0.2.tar.gz/salesforce-lavis-1.0.2/lavis/models/pnp_vqa_models/pnp_vqa.py | 0.859457 | 0.404507 | pnp_vqa.py | pypi |
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