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import sys from google.cloud import vision_v1 from google.cloud.vision_v1 import enums import io import json from google.cloud import storage import os def sample_batch_annotate_files(storage_uri): # os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = r"C:\Users\user\Desktop\doc_ai\rmi-insights-3e257c9c456c....
[ "google.cloud.vision_v1.ImageAnnotatorClient", "google.cloud.storage.Client" ]
[((421, 453), 'google.cloud.vision_v1.ImageAnnotatorClient', 'vision_v1.ImageAnnotatorClient', ([], {}), '()\n', (451, 453), False, 'from google.cloud import vision_v1\n'), ((1631, 1647), 'google.cloud.storage.Client', 'storage.Client', ([], {}), '()\n', (1645, 1647), False, 'from google.cloud import storage\n')]
# Based on ULN2003 driver lib: https://github.com/zhcong/ULN2003-for-ESP32 from utime import sleep_ms from machine import Pin from LogicalPins import physical_pin STEPPER_INST = None class StepperULN2003: FULL_ROTATION = int(4075.7728395061727 / 8) # http://www.jangeox.be/2013/10/stepper-motor-28byj-48_25.html ...
[ "utime.sleep_ms", "LogicalPins.physical_pin" ]
[((3304, 3327), 'LogicalPins.physical_pin', 'physical_pin', (['"""stppr_1"""'], {}), "('stppr_1')\n", (3316, 3327), False, 'from LogicalPins import physical_pin\n'), ((3340, 3363), 'LogicalPins.physical_pin', 'physical_pin', (['"""stppr_2"""'], {}), "('stppr_2')\n", (3352, 3363), False, 'from LogicalPins import physica...
""" coding:utf-8 file: setting_window.py @author: jiangwei @contact: <EMAIL> @time: 2020/6/27 23:07 @desc: """ import sys from ui.setting_window import Ui_Form from PyQt5.QtWidgets import QWidget, QApplication from util.common_util import SYS_STYLE class SettingWindow(Ui_Form, QWidget): def __init__(self): ...
[ "PyQt5.QtWidgets.QApplication" ]
[((863, 885), 'PyQt5.QtWidgets.QApplication', 'QApplication', (['sys.argv'], {}), '(sys.argv)\n', (875, 885), False, 'from PyQt5.QtWidgets import QWidget, QApplication\n')]
import os from testtools import TestCase from testtools.matchers import Contains from . import makeprefs from mock import Mock, patch from StringIO import StringIO from twisted.internet import defer class CommandTest(TestCase): def setUp(self): super(CommandTest, self).setUp() self.prefs = makepr...
[ "os.path.join", "mock.patch.object", "testtools.matchers.Contains", "twisted.internet.defer.succeed", "mock.patch", "mock.Mock", "lacli.main.LaCommand" ]
[((663, 704), 'mock.patch', 'patch', (['"""sys.stdin"""'], {'new_callable': 'StringIO'}), "('sys.stdin', new_callable=StringIO)\n", (668, 704), False, 'from mock import Mock, patch\n'), ((945, 987), 'mock.patch', 'patch', (['"""sys.stdout"""'], {'new_callable': 'StringIO'}), "('sys.stdout', new_callable=StringIO)\n", (...
import pytest from hyper_prompt.theme import BasicTheme @pytest.mark.parametrize( "test, result", [ ("RESET", BasicTheme.RESET), ("TEST_FG", BasicTheme.FG), ("TEST_BG", BasicTheme.BG) ] ) def test_get_key(test, result): assert BasicTheme({}).get(test) == result
[ "pytest.mark.parametrize", "hyper_prompt.theme.BasicTheme" ]
[((59, 190), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""test, result"""', "[('RESET', BasicTheme.RESET), ('TEST_FG', BasicTheme.FG), ('TEST_BG',\n BasicTheme.BG)]"], {}), "('test, result', [('RESET', BasicTheme.RESET), (\n 'TEST_FG', BasicTheme.FG), ('TEST_BG', BasicTheme.BG)])\n", (82, 190), Fal...
#setup cython code from setuptools import setup, find_packages from Cython.Build import cythonize import numpy import os import codecs def read(rel_path): here = os.path.abspath(os.path.dirname(__file__)) with codecs.open(os.path.join(here, rel_path), 'r') as fp: return fp.read() def get_version(rel_pa...
[ "os.path.join", "os.path.dirname", "setuptools.find_packages", "numpy.get_include", "Cython.Build.cythonize" ]
[((182, 207), 'os.path.dirname', 'os.path.dirname', (['__file__'], {}), '(__file__)\n', (197, 207), False, 'import os\n'), ((812, 827), 'setuptools.find_packages', 'find_packages', ([], {}), '()\n', (825, 827), False, 'from setuptools import setup, find_packages\n'), ((842, 946), 'Cython.Build.cythonize', 'cythonize', ...
import torch import torch.nn as nn class NCSNSampler(nn.Module): def __init__(self, score, sigmas, alphas, n_steps_each: int): super().__init__() self.score = score self.sigmas = sigmas self.alphas = alphas self.n_steps_each = n_steps_each def forward(self, x_T: torch....
[ "torch.randn_like", "torch.ones_like" ]
[((405, 428), 'torch.ones_like', 'torch.ones_like', (['x_T[0]'], {}), '(x_T[0])\n', (420, 428), False, 'import torch\n'), ((576, 597), 'torch.randn_like', 'torch.randn_like', (['x_T'], {}), '(x_T)\n', (592, 597), False, 'import torch\n')]
import pandas as pd import numpy as np import matplotlib.pyplot as plt from datetime import datetime def calculate_profit_from_columns(row): profit = 0 if row['Buy']: profit = row['Difference'] elif row['Sell']: profit = row['Difference'] * -1 return profit def convert_date(row): r...
[ "numpy.array", "matplotlib.pyplot.subplots", "datetime.datetime.strptime" ]
[((326, 381), 'datetime.datetime.strptime', 'datetime.strptime', (["row['Datetime']", '"""%Y-%m-%d %H:%M:%S"""'], {}), "(row['Datetime'], '%Y-%m-%d %H:%M:%S')\n", (343, 381), False, 'from datetime import datetime\n'), ((1665, 1687), 'numpy.array', 'np.array', (['wealth_array'], {}), '(wealth_array)\n', (1673, 1687), Tr...
# -*- coding: utf-8 -*- """ Created on Mon Sep 5 16:07:58 2016 @author: Administrator """ import unittest from app import create_app,db from app.models import User,Role from flask import url_for import re class FlaskClientTestCase(unittest.TestCase): def setUp(self): self.app = create_app...
[ "flask.url_for", "app.models.Role.insert_roles", "app.create_app", "app.db.create_all", "app.models.User.query.filter_by", "re.search", "app.db.drop_all", "app.db.session.remove" ]
[((310, 331), 'app.create_app', 'create_app', (['"""testing"""'], {}), "('testing')\n", (320, 331), False, 'from app import create_app, db\n'), ((425, 440), 'app.db.create_all', 'db.create_all', ([], {}), '()\n', (438, 440), False, 'from app import create_app, db\n'), ((450, 469), 'app.models.Role.insert_roles', 'Role....
import cv2 import imagezmq import simplejpeg # Instantiate and provide the first publisher address image_hub = imagezmq.ImageHub(open_port="tcp://192.168.12.29:5555", REQ_REP=False) # image_hub.connect('tcp://192.168.86.38:5555') # second publisher address while True: # show received images # sender_name, ima...
[ "cv2.imshow", "simplejpeg.decode_jpeg", "cv2.waitKey", "imagezmq.ImageHub" ]
[((112, 182), 'imagezmq.ImageHub', 'imagezmq.ImageHub', ([], {'open_port': '"""tcp://192.168.12.29:5555"""', 'REQ_REP': '(False)'}), "(open_port='tcp://192.168.12.29:5555', REQ_REP=False)\n", (129, 182), False, 'import imagezmq\n'), ((411, 463), 'simplejpeg.decode_jpeg', 'simplejpeg.decode_jpeg', (['jpg_buffer'], {'col...
from __future__ import division import gzip import matplotlib.pyplot as plt import numpy as np import random import math def Randomize_Weights(weight_vector: np.ndarray): rand_weights = weight_vector for j in range(0,len(weight_vector)): rand_weights[j][::1] = float(random.randint(-100, 100) / 100)...
[ "numpy.reshape", "matplotlib.pyplot.scatter", "matplotlib.pyplot.imshow", "math.log", "numpy.dtype", "matplotlib.pyplot.show", "numpy.inner", "numpy.zeros", "gzip.GzipFile", "math.exp", "numpy.argmax", "random.randint" ]
[((500, 512), 'numpy.zeros', 'np.zeros', (['(10)'], {}), '(10)\n', (508, 512), True, 'import numpy as np\n'), ((998, 1020), 'numpy.zeros', 'np.zeros', (['(10000, 784)'], {}), '((10000, 784))\n', (1006, 1020), True, 'import numpy as np\n'), ((2000, 2010), 'matplotlib.pyplot.show', 'plt.show', ([], {}), '()\n', (2008, 20...
# External Import from django.contrib import admin # Internal Import from .models import Post admin.site.register(Post)
[ "django.contrib.admin.site.register" ]
[((96, 121), 'django.contrib.admin.site.register', 'admin.site.register', (['Post'], {}), '(Post)\n', (115, 121), False, 'from django.contrib import admin\n')]
import json twinkle_twinkle = ['c4','c4','g4','g4','a4','a4','g4',\ 'f4','f4','e4','e4','d4','d4','c4',\ 'g5','g5','f4','f4','e4','e4','d4',\ 'g5','g5','f4','f4','e4','e4','d4',\ 'c4','c4','g4','g4','a4','a4','g4',\ 'f4','f4','e4','e4','d4...
[ "json.dump" ]
[((3553, 3575), 'json.dump', 'json.dump', (['notes', 'file'], {}), '(notes, file)\n', (3562, 3575), False, 'import json\n')]
# Generated by Django 2.1.1 on 2018-11-01 00:26 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('GestiRED', '0020_phase_observation'), ] operations = [ migrations.RemoveField( model_name='phase', name='observation...
[ "django.db.models.CharField", "django.db.migrations.RemoveField" ]
[((235, 297), 'django.db.migrations.RemoveField', 'migrations.RemoveField', ([], {'model_name': '"""phase"""', 'name': '"""observation"""'}), "(model_name='phase', name='observation')\n", (257, 297), False, 'from django.db import migrations, models\n'), ((456, 488), 'django.db.models.CharField', 'models.CharField', ([]...
from PyQt5.QtWidgets import QMainWindow, QStatusBar from PyQt5.QtCore import QObject, QEvent from PyQt5 import QtCore class MainWindow(QMainWindow): def __init__(self): QMainWindow.__init__(self) mousePressed = QtCore.pyqtSignal(str) def eventFilter(self, obj: 'QObject', event: 'QEven...
[ "PyQt5.QtCore.pyqtSignal", "PyQt5.QtWidgets.QMainWindow.__init__" ]
[((239, 261), 'PyQt5.QtCore.pyqtSignal', 'QtCore.pyqtSignal', (['str'], {}), '(str)\n', (256, 261), False, 'from PyQt5 import QtCore\n'), ((190, 216), 'PyQt5.QtWidgets.QMainWindow.__init__', 'QMainWindow.__init__', (['self'], {}), '(self)\n', (210, 216), False, 'from PyQt5.QtWidgets import QMainWindow, QStatusBar\n')]
# Generated by Django 2.0.9 on 2018-12-05 11:07 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('users', '0006_auto_20181202_1125'), ('student', '0005_auto_20181203_1208'), ('bge', '000...
[ "django.db.models.NullBooleanField", "django.db.models.ForeignKey", "django.db.models.IntegerField", "django.db.models.ImageField", "django.db.models.FileField", "django.db.models.DateTimeField", "django.db.models.DateField", "django.db.models.AutoField", "django.db.models.TextField", "django.db.m...
[((8718, 8822), 'django.db.models.OneToOneField', 'models.OneToOneField', ([], {'null': '(True)', 'on_delete': 'django.db.models.deletion.CASCADE', 'to': '"""branch.HostFamily"""'}), "(null=True, on_delete=django.db.models.deletion.CASCADE,\n to='branch.HostFamily')\n", (8738, 8822), False, 'from django.db import mi...
#!/usr/bin/env python3 # # submit_one_Door43_test.py # Written: Jan 2019 # Last modified: 2019-12-09 RJH # # Python imports import os import sys import json import logging import subprocess # ====================================================================== # User settings USE_LOCALCOMPOSE_URL = Tr...
[ "os.path.join", "subprocess.Popen", "json.loads", "os.path.isfile", "webbrowser.open", "logging.critical", "sys.exit" ]
[((993, 1043), 'os.path.join', 'os.path.join', (['TEST_FOLDER', "(TEST_FILENAME + '.json')"], {}), "(TEST_FOLDER, TEST_FILENAME + '.json')\n", (1005, 1043), False, 'import os\n'), ((1090, 1114), 'os.path.isfile', 'os.path.isfile', (['filepath'], {}), '(filepath)\n', (1104, 1114), False, 'import os\n'), ((6905, 6915), '...
'''entre no programa com a altura e largura de uma parede em mtr calcule a area e a quantidade de tinta necessária para pintá-la considerando que cada litro de tinta pinta 2m²''' from math import ceil cores = {'limpa': '\033[m', 'azul': '\033[1;34m'} print('{:-^40}'.format('CALCULO DE ÁREA')) largura = float(input('D...
[ "math.ceil" ]
[((722, 733), 'math.ceil', 'ceil', (['tinta'], {}), '(tinta)\n', (726, 733), False, 'from math import ceil\n')]
import numpy as np import sympy as sp import pandas as pd import sys #give input equation expr = sp.sympify("x_1**2 + x_2*x_3") #get number of columns from X dataframe and y dataframe num_of_columns = 3+1 #dataframe features len(X.columns) +1 num_of_y_columns = 2 #dataframe features len(Y.columns) +1 #create equation v...
[ "pandas.DataFrame", "sympy.sympify", "sympy.symarray", "sympy.lambdify" ]
[((97, 127), 'sympy.sympify', 'sp.sympify', (['"""x_1**2 + x_2*x_3"""'], {}), "('x_1**2 + x_2*x_3')\n", (107, 127), True, 'import sympy as sp\n'), ((390, 422), 'sympy.symarray', 'sp.symarray', (['"""x"""', 'num_of_columns'], {}), "('x', num_of_columns)\n", (401, 422), True, 'import sympy as sp\n'), ((456, 490), 'sympy....
""" Read sample documents from mongo db and write sample metadata files to iRODS. """ import argparse from itertools import islice import json import os import pprint import re import sys import time import pymongo import imicrobe.util.irods as irods def write_sample_metadata_files(target_root, file_limit): """...
[ "imicrobe.util.irods.irods_collection_exists", "pprint.pformat", "imicrobe.util.irods.irods_session_manager", "re.compile", "argparse.ArgumentParser", "json.dumps", "imicrobe.util.irods.irods_data_object_exists", "pymongo.MongoClient", "time.time", "os.path.split" ]
[((955, 1010), 're.compile', 're.compile', (['"""\\\\.(fa|fna|fasta|fastq)(\\\\.tar)?(\\\\.gz)?$"""'], {}), "('\\\\.(fa|fna|fasta|fastq)(\\\\.tar)?(\\\\.gz)?$')\n", (965, 1010), False, 'import re\n'), ((1017, 1028), 'time.time', 'time.time', ([], {}), '()\n', (1026, 1028), False, 'import time\n'), ((2947, 2958), 'time....
import json import pathlib import random import jsonpickle class BankAccount: def __init__(self, ssn, balance=0): self._ssn = ssn self._balance = balance @property def ssn(self): return self._ssn @property def balance(self): return self._balance @st...
[ "jsonpickle.decode", "json.load", "pathlib.Path", "random.randint" ]
[((1156, 1184), 'random.randint', 'random.randint', (['(10000)', '(99999)'], {}), '(10000, 99999)\n', (1170, 1184), False, 'import random\n'), ((2109, 2139), 'random.randint', 'random.randint', (['(100000)', '(200000)'], {}), '(100000, 200000)\n', (2123, 2139), False, 'import random\n'), ((543, 563), 'json.load', 'json...
#!/usr/bin/env python3 import sys import argparse import bz2 import pickle import numpy import textwrap import tabulate import copy import math import operator import collections import profileLib import statistics from xopen import xopen def error(baseline, value, totalBaseline, totalValue, weight, fullTotalBaselin...
[ "tabulate.tabulate", "copy.deepcopy", "bz2.BZ2File.open", "numpy.append", "argparse.ArgumentParser", "statistics.mean", "numpy.sum", "numpy.where", "textwrap.fill", "numpy.concatenate", "numpy.empty", "numpy.insert", "numpy.array", "sys.exit", "xopen.xopen", "operator.itemgetter" ]
[((4375, 4969), 'numpy.array', 'numpy.array', (["[['relative_error', 'Relative Error', relativeError], ['error', 'Error',\n error], ['absolute_error', 'Absolute Error', absoluteError], [\n 'weighted_error', 'Weighted Error', weightedError], [\n 'absolute_weighted_error', 'Absolute Weighted Error',\n absolut...
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib.auth.models import AbstractBaseUser from django.db import models # Create your models here. class Account(AbstractBaseUser): email = models.EmailField(unique=True) username = models.CharField(max_length=40, unique=True) ...
[ "django.db.models.DateTimeField", "django.db.models.CharField", "django.db.models.BooleanField", "django.db.models.EmailField" ]
[((228, 258), 'django.db.models.EmailField', 'models.EmailField', ([], {'unique': '(True)'}), '(unique=True)\n', (245, 258), False, 'from django.db import models\n'), ((274, 318), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(40)', 'unique': '(True)'}), '(max_length=40, unique=True)\n', (290, ...
# -*- coding: utf-8 -*- """ > :warning: This file is only for use by the Simmate team. Users should instead access data via the load_remote_archive method. This file is for pulling AFLOW data into the Simmate database. AFLOW's supported REST API can be accessed via "AFLUX API". This is a separate python package, w...
[ "pymatgen.io.ase.AseAtomsAdaptor.get_structure", "aflow.control.Query", "tqdm.tqdm" ]
[((3358, 3368), 'tqdm.tqdm', 'tqdm', (['data'], {}), '(data)\n', (3362, 3368), False, 'from tqdm import tqdm\n'), ((3548, 3592), 'pymatgen.io.ase.AseAtomsAdaptor.get_structure', 'AseAtomsAdaptor.get_structure', (['structure_ase'], {}), '(structure_ase)\n', (3577, 3592), False, 'from pymatgen.io.ase import AseAtomsAdapt...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = "<NAME>" __email__ = "<EMAIL>" import datetime import numpy as np import pandas as pd class DataType(object): INT = 1 STRING = 2 DECIMAL = 3 TIMESTAMP = 4 DATE = 5 ARRAY = 6 _converted_types = { DataType.INT: int, DataType...
[ "numpy.dtype" ]
[((384, 397), 'numpy.dtype', 'np.dtype', (['"""O"""'], {}), "('O')\n", (392, 397), True, 'import numpy as np\n')]
#!/usr/bin/env python import sys # import all necessary stuff import osg import osgDB import osgGA import osgViewer # create a root node node = osg.Group() # needed for python filepath = osgDB.getLibraryFilePathList() for item in sys.path: filepath.append(item) osgDB.setLibraryFilePathList(filepath) loadedmodel = ...
[ "osgDB.getLibraryFilePathList", "osgDB.setLibraryFilePathList", "osgViewer.ThreadingHandler", "osgViewer.Viewer", "osgViewer.StatsHandler", "osgViewer.HelpHandler", "osg.Group", "osgDB.readNodeFile", "osgViewer.WindowSizeHandler" ]
[((147, 158), 'osg.Group', 'osg.Group', ([], {}), '()\n', (156, 158), False, 'import osg\n'), ((191, 221), 'osgDB.getLibraryFilePathList', 'osgDB.getLibraryFilePathList', ([], {}), '()\n', (219, 221), False, 'import osgDB\n'), ((266, 304), 'osgDB.setLibraryFilePathList', 'osgDB.setLibraryFilePathList', (['filepath'], {...
import json import csv labels = ["E10","E11","E12","E13","E14","E15","E16","E17","E18","E19","E20","E21","E22","E23","E24","E25","E26","E27","E28","E29","E30","E31","E32","E33","E34","E35","E36","E37","E38","E39","E40","E41","E42","E43","E44","E45","E46","E47","E48","E49","E50","E51","E52","E53","E54","E55","E56","E57...
[ "csv.writer", "json.load" ]
[((612, 625), 'csv.writer', 'csv.writer', (['f'], {}), '(f)\n', (622, 625), False, 'import csv\n'), ((1193, 1206), 'csv.writer', 'csv.writer', (['f'], {}), '(f)\n', (1203, 1206), False, 'import csv\n'), ((1850, 1863), 'csv.writer', 'csv.writer', (['f'], {}), '(f)\n', (1860, 1863), False, 'import csv\n'), ((513, 525), '...
# Generated by Django 3.2.7 on 2021-10-08 08:21 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('firearm', '0001_initial'), ] operations = [ migrations.AddField( model_name='firearm', name='opType', fi...
[ "django.db.models.CharField", "django.db.models.TextField" ]
[((324, 352), 'django.db.models.TextField', 'models.TextField', ([], {'default': '""""""'}), "(default='')\n", (340, 352), False, 'from django.db import migrations, models\n'), ((481, 512), 'django.db.models.CharField', 'models.CharField', ([], {'max_length': '(30)'}), '(max_length=30)\n', (497, 512), False, 'from djan...
""" This file is part of LiberaForms. # SPDX-FileCopyrightText: 2021 LiberaForms.org # SPDX-License-Identifier: AGPL-3.0-or-later """ import os, shutil def ensure_uploads_dir_tree(app): uploads_dir = app.config['UPLOADS_DIR'] media_dir = os.path.join(uploads_dir, app.config['MEDIA_DIR']) attachment_dir ...
[ "os.path.join", "os.path.isdir", "os.makedirs" ]
[((250, 300), 'os.path.join', 'os.path.join', (['uploads_dir', "app.config['MEDIA_DIR']"], {}), "(uploads_dir, app.config['MEDIA_DIR'])\n", (262, 300), False, 'import os, shutil\n'), ((322, 377), 'os.path.join', 'os.path.join', (['uploads_dir', "app.config['ATTACHMENT_DIR']"], {}), "(uploads_dir, app.config['ATTACHMENT...
import datetime import pytz from sqlalchemy import DateTime from sqlalchemy.types import TypeDecorator def tzware_datetime(): """ Return a timezone aware datetime. :return: Datetime """ return datetime.datetime.now(pytz.utc) class AwareDateTime(TypeDecorator): """ A DateTime type which...
[ "datetime.datetime.now", "sqlalchemy.DateTime" ]
[((217, 248), 'datetime.datetime.now', 'datetime.datetime.now', (['pytz.utc'], {}), '(pytz.utc)\n', (238, 248), False, 'import datetime\n'), ((471, 494), 'sqlalchemy.DateTime', 'DateTime', ([], {'timezone': '(True)'}), '(timezone=True)\n', (479, 494), False, 'from sqlalchemy import DateTime\n')]
from multiprocessing import Pool import pandas as pd import os from model_based_analysis_tools import * base_dir = '../../' in_dirs = { 'data':'new-processed-model-processed-1en01', 'synthetic-data':'new-synthetic-model-processed-1en01', 'score-matched-data':'new-synthetic-score-matched-model-processed-1...
[ "os.listdir", "os.makedirs" ]
[((559, 579), 'os.makedirs', 'os.makedirs', (['out_dir'], {}), '(out_dir)\n', (570, 579), False, 'import os\n'), ((718, 747), 'os.listdir', 'os.listdir', (['(base_dir + in_dir)'], {}), '(base_dir + in_dir)\n', (728, 747), False, 'import os\n')]
import sys import numpy as np import scipy as sp import pandas as pd import networkx as nx import gensim.parsing.preprocessing as gpp import sklearn.metrics.pairwise as smp from .persistent_homology import PersistentHomology __all__ = ['Model'] class Model(PersistentHomology): """ Attributes ---------- ...
[ "numpy.random.choice", "numpy.append", "numpy.argwhere", "sys.stdout.flush", "numpy.delete", "numpy.random.binomial", "numpy.zeros", "numpy.array", "pandas.DataFrame", "numpy.argsort", "scipy.sparse.hstack" ]
[((1666, 1680), 'pandas.DataFrame', 'pd.DataFrame', ([], {}), '()\n', (1678, 1680), True, 'import pandas as pd\n'), ((7272, 7310), 'numpy.random.binomial', 'np.random.binomial', (['point[0]', 'point[1]'], {}), '(point[0], point[1])\n', (7290, 7310), True, 'import numpy as np\n'), ((7329, 7382), 'numpy.random.choice', '...
import numpy as np from scipy.special import expit class NeuralNet: def __init__(self, input_qty, hidden_dts, output_qty): """ input_qty : Quantidade de entradas que a rede vai receber. hidden_dts : Uma tuple contedo os detalhes das camadas escondidas. Primeiro valo...
[ "numpy.reshape", "numpy.asarray", "numpy.random.uniform", "numpy.maximum", "scipy.special.expit", "numpy.dot" ]
[((661, 679), 'numpy.asarray', 'np.asarray', (['inputs'], {}), '(inputs)\n', (671, 679), True, 'import numpy as np\n'), ((1579, 1608), 'numpy.reshape', 'np.reshape', (['weights', 'newshape'], {}), '(weights, newshape)\n', (1589, 1608), True, 'import numpy as np\n'), ((2075, 2106), 'numpy.random.uniform', 'np.random.uni...
import gzip from collections import OrderedDict from typing import Dict, Tuple import numpy as np import tensorflow as tf from tensorflow.python.lib.io import file_io def random_normal_initializer(_, dim): return np.random.normal(0, 0.01, dim) def zero_initializer(_, dim): return np.zeros(dim) def read_v...
[ "tensorflow.python.lib.io.file_io.FileIO", "numpy.std", "numpy.random.normal", "collections.OrderedDict", "numpy.zeros", "gzip.open" ]
[((220, 250), 'numpy.random.normal', 'np.random.normal', (['(0)', '(0.01)', 'dim'], {}), '(0, 0.01, dim)\n', (236, 250), True, 'import numpy as np\n'), ((294, 307), 'numpy.zeros', 'np.zeros', (['dim'], {}), '(dim)\n', (302, 307), True, 'import numpy as np\n'), ((665, 678), 'collections.OrderedDict', 'OrderedDict', ([],...
# MIT License # # Copyright (c) 2021 <NAME> and <NAME> and <NAME> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy...
[ "torch.rand", "torch.nn.functional.softmax", "openspeech.modules.wrapper.Linear", "torch.nn.Conv1d", "torch.sigmoid" ]
[((2769, 2842), 'torch.nn.Conv1d', 'nn.Conv1d', ([], {'in_channels': '(1)', 'out_channels': 'attn_dim', 'kernel_size': '(3)', 'padding': '(1)'}), '(in_channels=1, out_channels=attn_dim, kernel_size=3, padding=1)\n', (2778, 2842), True, 'import torch.nn as nn\n'), ((2869, 2902), 'openspeech.modules.wrapper.Linear', 'Lin...
TOKEN = "" # YOUR BOT TOKEN guildid = [] # YOUR GUILD ID import discord from discord.ext import commands # pip install -U git+https://github.com/Rapptz/discord.py.git (recommended) from discord_slash import SlashContext, SlashCommand from discord_slash.model import SlashCommandOptionType from discord_slash.ut...
[ "discord_slash.utils.manage_commands.create_choice", "discord.PermissionOverwrite", "discord.ext.commands.Bot", "discord_slash.utils.manage_commands.create_option", "discord_slash.SlashCommand" ]
[((460, 492), 'discord.ext.commands.Bot', 'commands.Bot', ([], {'command_prefix': '"""!"""'}), "(command_prefix='!')\n", (472, 492), False, 'from discord.ext import commands\n'), ((501, 538), 'discord_slash.SlashCommand', 'SlashCommand', (['bot'], {'sync_commands': '(True)'}), '(bot, sync_commands=True)\n', (513, 538),...
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