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"""Builds a DRAGNN graph for local training."""
from abc import ABCMeta
from abc import abstractmethod
import tensorflow as tf
from tensorflow.python.platform import tf_logging as logging
from dragnn.python import dragnn_ops
from dragnn.python import network_units
from syntaxnet.util import check
from syntaxnet.util... | {
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# builds a list of protein types in refseq organisms
# each output line is refseq_organism_ID gene_function1 gene_function2 ...
#
# also builds a list of gene IDs to protein descriptions
# each output line is gene_ID gene_description
#
# usage:
# *.py GMG.fasta organism2gene_table.txt gene2description_table.txt
#
# h... | {
"repo_name": "knights-lab/NINJA-SHOGUN",
"path": "shogun/scripts/old/scrape_organism2protein_map_from_GMG.py",
"copies": "2",
"size": "1906",
"license": "mit",
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'''Builds a model, organizes and loads data, and runs model training.'''
import argparse
from collections import defaultdict
import os
import glob
import random
import keras
import numpy as np
from keras.layers import Input, Average
from keras.layers.core import Dense, Flatten, Dropout
from keras.layers.merge import ... | {
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"path": "train.py",
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"license": "mit",
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"""Build sandboxes"""
from __future__ import print_function
import os.path
import re
import sys
from collections import OrderedDict
from glob import glob
try:
import simplejson as json
except ImportError:
import json
DEFAULT_ORDER = (
'type',
'ns',
'author',
'prefix',
'match',
'patte... | {
"repo_name": "marianocarrazana/anticontainer",
"path": "build/build_sandboxes.py",
"copies": "1",
"size": "2653",
"license": "mpl-2.0",
"hash": -7183662565266471000,
"line_mean": 25.2673267327,
"line_max": 73,
"alpha_frac": 0.5461741425,
"autogenerated": false,
"ratio": 3.726123595505618,
"con... |
"""Builds a pip package suitable for redistribution.
Adapted from tensorflow/tools/pip_package/build_pip_package.sh. This might have
to change if Bazel changes how it modifies paths.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
impor... | {
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"path": "syntaxnet/dragnn/tools/build_pip_package.py",
"copies": "2",
"size": "2371",
"license": "apache-2.0",
"hash": 5010136837265826000,
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"line_max": 80,
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"ratio": 3.5178041543026706,
... |
"""Builds a portfolio object containing asset allocation details."""
import time
import decimal
from stockretriever import get_current_info
DEC = decimal.Decimal
def init_portfolio(filename):
"""Returns a portfolio object containing positional, categorical, and
portfolio totals.
Usage:
call init... | {
"repo_name": "gurch101/portfolio-manager",
"path": "portfolio.py",
"copies": "1",
"size": "3332",
"license": "mit",
"hash": -6806379426760526000,
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... |
'''Builds arch
'''
import copy
import logging
import time
from . import data, exp, optimizer
from .parsing import parse_docstring, parse_inputs, parse_kwargs
from .handlers import (aliased, prefixed, NetworkHandler, LossHandler,
ResultsHandler)
from .utils import bad_values, update_dict_of_lis... | {
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"path": "cortex/_lib/models.py",
"copies": "1",
"size": "16743",
"license": "bsd-3-clause",
"hash": -3674438622647771600,
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"line_max": 80,
"alpha_frac": 0.5052260646,
"autogenerated": false,
"ratio": 4.297484599589322,
"config_test": fal... |
"""Builds a simple NNVM graph for testing."""
from os import path as osp
import nnvm
from nnvm import sym
from nnvm.compiler import graph_util
from nnvm.testing import init
import numpy as np
import tvm
CWD = osp.dirname(osp.abspath(osp.expanduser(__file__)))
def _get_model(dshape):
data = sym.Variable('data',... | {
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"path": "Fujitsu/benchmarks/resnet/implementations/mxnet/3rdparty/tvm/rust/tests/build_model.py",
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"size": "1762",
"license": "apache-2.0",
"hash": -866007126072056700,
"line_mean": 32.2452830189,
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"alpha_frac": 0.5976163451,
... |
"""Builds a spritemap image from a set of sprites."""
from array import array
from itertools import izip, chain, repeat
from .image import Image
class StitchedSpriteNodes(object):
"""An iterable that yields the image data rows of a tree of sprite
nodes. Suitable for writing to an image.
"""
def __in... | {
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"path": "spritecss/stitch.py",
"copies": "2",
"size": "3522",
"license": "mit",
"hash": 4191786147034988000,
"line_mean": 33.1941747573,
"line_max": 81,
"alpha_frac": 0.5905735378,
"autogenerated": false,
"ratio": 3.354285714285714,
"config_test": false,
... |
#
# Copyright (c) 2013 - 2018 Software AG, Darmstadt, Germany and/or its licensors
# Copyright (c) 2013 - 2019 Ben Spiller and Matthew Johnson
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Lice... | {
"repo_name": "xpybuild/xpybuild",
"path": "release-xpy.xpybuild.py",
"copies": "1",
"size": "2958",
"license": "apache-2.0",
"hash": -4769531556634403000,
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"alpha_frac": 0.7231237323,
"autogenerated": false,
"ratio": 3.372862029646522,
"config_test":... |
# build script for 'require.cython'
# - a cython extension for 'require', a Validation library
# ( script stolen from http://wiki.cython.org/PackageHierarchy )
import sys, os, stat, commands
from distutils.core import setup
from distutils.extension import Extension
#from setuptools import setup, Extension
include_di... | {
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"path": "setup.py",
"copies": "1",
"size": "1970",
"license": "unlicense",
"hash": -7895806552033004000,
"line_mean": 29.78125,
"line_max": 91,
"alpha_frac": 0.6558375635,
"autogenerated": false,
"ratio": 3.731060606060606,
"config_test": false,
"has_... |
# build-script
import pyjvm
import pyjvm.build
import pyjvm.build_java
import pyjvm.build_py
from pyjvm.build_java import JavacError
import shutil
import os
import sys
import yaml
import subprocess
from os.path import join
pyjvm.assert_build_script(__name__)
pyjvm.add_dir_to_path(__file__)
target_name = 'android-15... | {
"repo_name": "zielmicha/pyjvm",
"path": "android/src/build.py",
"copies": "1",
"size": "8948",
"license": "mit",
"hash": 7924830179405249000,
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"alpha_frac": 0.6099687081,
"autogenerated": false,
"ratio": 3.39453717754173,
"config_test": true,
"has_... |
# Build script of unrealcv, supports win, linux and mac.
# A single file library
# Weichao Qiu @ 2017
import subprocess, sys, os, argparse, platform, logging, glob, shutil, json
try: input = raw_input # to support python3
except NameError: pass
def get_platform_name():
''''
Python and UE4 use different names f... | {
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"path": "client/python/unrealcv/automation.py",
"copies": "1",
"size": "10484",
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"autogenerated": false,
"ratio": 3.8013052936910805,
"confi... |
# Build script of unrealcv, supports win, linux and mac.
# Weichao Qiu @ 2017
# Use python build.py to build the plugin
import argparse
from unrealcv.automation import UE4Automation
import os
def main():
# Parse arguments
parser = argparse.ArgumentParser()
parser.add_argument(
'descriptor_file',
... | {
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"path": "build.py",
"copies": "1",
"size": "1970",
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"line_mean": 27.9705882353,
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"alpha_frac": 0.6294416244,
"autogenerated": false,
"ratio": 3.832684824902724,
"config_test": false,
"has_no_keywor... |
"""Builds data packages with flash"""
__author__ = 'edelman@room77.com (Nicholas Edelman)'
__copyright__ = 'Copyright 2013 Room77, Inc.'
import re
from pylib.base.flags import Flags
from pylib.base.term_color import TermColor
from pylib.file.file_utils import FileUtils
from pylib.flash.make_rules import MakeRules
F... | {
"repo_name": "room77/py77",
"path": "pylib/flash/pkg_rules.py",
"copies": "1",
"size": "3191",
"license": "mit",
"hash": -130679831186046580,
"line_mean": 42.1216216216,
"line_max": 86,
"alpha_frac": 0.620808524,
"autogenerated": false,
"ratio": 3.6426940639269407,
"config_test": false,
"has... |
"""Builds elevation graph between one or more points.
Module searches route between two coordinate points, draws a
elevation graph and constructs a summary. Route and elevation are fetched
using Google Maps APIs. Graph is created from fetched elevation points and
drawn with Matplotlib.
Usage:
Find elevation from He... | {
"repo_name": "anttilip/telepybot",
"path": "telepybot/modules/elevation.py",
"copies": "1",
"size": "8954",
"license": "mit",
"hash": 8115131771954967000,
"line_mean": 31.56,
"line_max": 82,
"alpha_frac": 0.6219566674,
"autogenerated": false,
"ratio": 3.816709292412617,
"config_test": true,
... |
"""build setup for corda
"""
from setuptools import setup, find_packages
from codecs import open
from os import path
import versioneer
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
long_description = f.... | {
"repo_name": "resendislab/corda",
"path": "setup.py",
"copies": "2",
"size": "2575",
"license": "mit",
"hash": -6234275930503238000,
"line_mean": 33.7972972973,
"line_max": 79,
"alpha_frac": 0.652815534,
"autogenerated": false,
"ratio": 3.9493865030674846,
"config_test": false,
"has_no_keywo... |
# Builds homology models
import os, inspect
dirs = {}
dirs['script'] = os.path.dirname(os.path.abspath(\
inspect.getfile(inspect.currentframe())))
execfile(os.path.join(dirs['script'],'_external_paths.py'))
command_paths = findPaths(['qsub_command'])
# Parse arguments
import argparse
parser = argparse.ArgumentParse... | {
"repo_name": "CCBatIIT/AlGDock",
"path": "Pipeline/run_homology_model.py",
"copies": "1",
"size": "2460",
"license": "mit",
"hash": 8904852072360567000,
"line_mean": 32.2432432432,
"line_max": 68,
"alpha_frac": 0.6764227642,
"autogenerated": false,
"ratio": 3.241106719367589,
"config_test": fa... |
"""Builds objects representing a produced factorio item for templating."""
from __future__ import division
import math
from factorio import recipe
from factorio import production
from factorio import names
from appengine import icons
def get_wiki_url(username):
"""Constructs a URL refering to the factorio wik... | {
"repo_name": "brianquinlan/factorio-tools",
"path": "appengine/produced_item.py",
"copies": "1",
"size": "7445",
"license": "mit",
"hash": -2211776471871175400,
"line_mean": 30.1506276151,
"line_max": 80,
"alpha_frac": 0.6288784419,
"autogenerated": false,
"ratio": 4.264032073310424,
"config_t... |
# Builds one homology model
# Parse arguments
# import argparse
# parser = argparse.ArgumentParser()
# parser.add_argument('sequence_ali', default=None, help='Location of seq.ali')
# parser.add_argument('template_pdb', default=None, help='Template')
# parser.add_argument('--pylab', action='store_true')
# args = ... | {
"repo_name": "gkumar7/AlGDock",
"path": "Pipeline/homology_model.modeller.py",
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"size": "4054",
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"""Builds on top of nodes.py to track brackets."""
from dataclasses import dataclass, field
import sys
from typing import Dict, Iterable, List, Optional, Tuple, Union
if sys.version_info < (3, 8):
from typing_extensions import Final
else:
from typing import Final
from blib2to3.pytree import Leaf, Node
from b... | {
"repo_name": "psf/black",
"path": "src/black/brackets.py",
"copies": "1",
"size": "10760",
"license": "mit",
"hash": 1549267766199463200,
"line_mean": 31.2155688623,
"line_max": 87,
"alpha_frac": 0.6152416357,
"autogenerated": false,
"ratio": 3.938506588579795,
"config_test": false,
"has_no_... |
"""Builds packaged application.
Usage:
# For distribution.
python setup.py py2app
# For development (aliases).
python setup.py py2app -A
"""
from distutils import core
import py2app
import setuptools
import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'pygrow'))
from grow.common i... | {
"repo_name": "jeremydw/macgrow",
"path": "setup.py",
"copies": "1",
"size": "1429",
"license": "mit",
"hash": 1008890121736608000,
"line_mean": 19.1267605634,
"line_max": 74,
"alpha_frac": 0.6039188244,
"autogenerated": false,
"ratio": 3.292626728110599,
"config_test": false,
"has_no_keyword... |
"""Builds Swagger data model definitions using PAPI source docs."""
from __future__ import print_function
import argparse
import json
import modulefinder
import os
import re
import sys
def find_matching_obj_def(obj_defs, new_obj_def):
"""Find matching object definition."""
for obj_name in obj_defs:
e... | {
"repo_name": "Isilon/isilon_sdk",
"path": "components/papi_swagger_obj_defs_builder.py",
"copies": "1",
"size": "15948",
"license": "mit",
"hash": -1625208605476117000,
"line_mean": 37.062052506,
"line_max": 79,
"alpha_frac": 0.540381239,
"autogenerated": false,
"ratio": 3.919390513639715,
"co... |
"""build-stack-docs command-line application.
"""
__all__ = ("run_build_cli",)
import argparse
import logging
import os
import sys
from pkg_resources import DistributionNotFound, get_distribution
from ..stackdocs.build import build_stack_docs
try:
__version__ = get_distribution("documenteer").version
except Di... | {
"repo_name": "lsst-sqre/sphinxkit",
"path": "documenteer/bin/buildstackdocs.py",
"copies": "2",
"size": "1967",
"license": "mit",
"hash": 7213622407428009000,
"line_mean": 24.2179487179,
"line_max": 78,
"alpha_frac": 0.6120996441,
"autogenerated": false,
"ratio": 3.8796844181459567,
"config_te... |
"""Build standard, boring user interfaces in processing.py.
An Interface object can hold multiple Controls that represent standard
UI elements, like buttons, dropdown menus, etc.
To create an interface:
import spatialpixel.ui as ui
def setup():
global gui
gui = ui.Interface(this)
def dr... | {
"repo_name": "awmartin/spatialpixel",
"path": "ui/interface.py",
"copies": "2",
"size": "1721",
"license": "mit",
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"line_mean": 25.4769230769,
"line_max": 89,
"alpha_frac": 0.6321905869,
"autogenerated": false,
"ratio": 4.107398568019093,
"config_test": false,
"ha... |
"""Builds templates/agreements based on input data (in json format), submitting
to sla manager.
It is intended as backend service for a rest interface.
The json input must work together with the templates to form a valid template
or agreement for Xifi (be careful!)
This (very simple) service is coupled to t... | {
"repo_name": "Fiware/ops.Sla-dashboard",
"path": "slaclient/service/xifi/xifiservice.py",
"copies": "2",
"size": "2979",
"license": "apache-2.0",
"hash": 1880217281791343900,
"line_mean": 24.8378378378,
"line_max": 79,
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"autogenerated": false,
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"""Builds the Adience network.
Summary of available functions:
# Compute input images and labels for training. If you would like to run
# evaluations, use input() instead.
inputs, labels = distorted_inputs()
# Compute inference on the model inputs to make a prediction.
predictions = inference(inputs)
# Comput... | {
"repo_name": "NumesSanguis/MLTensor",
"path": "adience/adience.py",
"copies": "1",
"size": "18728",
"license": "apache-2.0",
"hash": 4289414121911946000,
"line_mean": 38.0981210856,
"line_max": 107,
"alpha_frac": 0.6212622811,
"autogenerated": false,
"ratio": 3.8111518111518112,
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"""Builds the application binaries."""
##==============================================================#
## SECTION: Imports #
##==============================================================#
import os
import os.path as op
import auxly.filesys as fs
import auxly.shell as ... | {
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"config_test": false,
"has_no_... |
"""Builds the C3D network.
Implements the inference pattern for model building.
model(): Builds the model as far as is required for running the network
forward to make predictions.
"""
import re
import numpy as np
import tensorflow as tf
def accuracy(logit, labels):
correct_pred = tf.equal(tf.argmax(logit, 1), ... | {
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"""Builds the CIFAR-10 network.
Summary of available functions:
# Compute input images and labels for training. If you would like to run
# evaluations, use input() instead.
inputs, labels = distorted_inputs()
# Compute inference on the model inputs to make a prediction.
predictions = inference(inputs)
# Compu... | {
"repo_name": "rickyHong/Tensorflow_modi",
"path": "tensorflow/models/image/cifar10/cifar10.py",
"copies": "5",
"size": "17758",
"license": "apache-2.0",
"hash": -5243008305147953000,
"line_mean": 35.9189189189,
"line_max": 80,
"alpha_frac": 0.6670796261,
"autogenerated": false,
"ratio": 3.573038... |
"""Builds the convolutional neural network model.
Matthew Alger
The Australian National University
2016
"""
import argparse
def main(n_filters, conv_size, pool_size, dropout,
patch_size, n_astro=7, out_path=None):
# Imports must be in the function, or whenever we import this module, Keras
# will du... | {
"repo_name": "chengsoonong/crowdastro",
"path": "crowdastro/compile_cnn.py",
"copies": "1",
"size": "3390",
"license": "mit",
"hash": 3277154968723846000,
"line_mean": 37.0898876404,
"line_max": 79,
"alpha_frac": 0.5725663717,
"autogenerated": false,
"ratio": 3.946449359720605,
"config_test": ... |
"""Builds the download page based on the released files.
This is just a little helper to execute after building all the release files. It will generate the contents of a wiki page that I can upload to wildbear to finish off a release.
"""
import hashlib
import sys
RELEASE_LISTING = [
'fct.h',
'fctx-doc-%(ver... | {
"repo_name": "imb/fctx",
"path": "wikify.py",
"copies": "1",
"size": "1699",
"license": "bsd-3-clause",
"hash": 3645844882083856000,
"line_mean": 26.4032258065,
"line_max": 177,
"alpha_frac": 0.5991759859,
"autogenerated": false,
"ratio": 3.1117216117216118,
"config_test": false,
"has_no_key... |
"""Builds the eye network.
Summary of available functions:
# Compute input images and labels for training. If you would like to run
# evaluations, use inputs() instead.
inputs, labels = distorted_inputs()
# Compute inference on the model inputs to make a prediction.
predictions = inference(inputs)
# Compute t... | {
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"path": "eye_model_predict.py",
"copies": "1",
"size": "14773",
"license": "mit",
"hash": -8834148983620873000,
"line_mean": 36.9768637532,
"line_max": 99,
"alpha_frac": 0.6082718473,
"autogenerated": false,
"ratio": 3.7230342741935485,
"config_te... |
'''Builds the lib and examples packages. Then, syncs to Dropbox
'''
import os
import subprocess
import shutil
from paths import PROJECT_DIR
SYNC_JARS = True
HOME_DIR = os.getenv("HOME")
OUTPUT_DIR = os.path.join(HOME_DIR, 'Dropbox/Public/')
LIB_JAR_PATH = os.path.join(HOME_DIR,
'.ivy2/l... | {
"repo_name": "dalab/dissolve-struct",
"path": "helpers/buildall.py",
"copies": "1",
"size": "1696",
"license": "apache-2.0",
"hash": 7457016097244273000,
"line_mean": 31.0188679245,
"line_max": 118,
"alpha_frac": 0.6574292453,
"autogenerated": false,
"ratio": 2.9964664310954063,
"config_test":... |
"""Builds the MNIST network.
Built to duplicate Hinton 2012 and Srivastava 2014 method of dropout feed forward
network with max norm regularisaton. A few learnings:
* dropout not applied to softmax layer (input and hidden layers only )
* max norm not applied to softmax layer - though it could be applied at a dif... | {
"repo_name": "mikowals/mnist",
"path": "mnist.py",
"copies": "1",
"size": "9825",
"license": "mit",
"hash": 7270090399144656000,
"line_mean": 40.4556962025,
"line_max": 174,
"alpha_frac": 0.6740966921,
"autogenerated": false,
"ratio": 3.3996539792387543,
"config_test": false,
"has_no_keyword... |
"""Builds the MNIST network.
Implements the inference/loss/training pattern for model building.
1. inference() - Builds the model as far as is required for running the network
forward to make predictions.
2. loss() - Adds to the inference model the layers required to generate loss.
3. training() - Adds to the loss mode... | {
"repo_name": "dnlcrl/TensorFlow-Playground",
"path": "1.tutorials/3.TensorFlow Mechanics 101/mnist.py",
"copies": "1",
"size": "5611",
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"hash": -4377784828179855400,
"line_mean": 41.5075757576,
"line_max": 79,
"alpha_frac": 0.6489039387,
"autogenerated": false,
"ratio": 3.956981... |
"""Builds the MNIST network.
Implements the inference/loss/training pattern for model building.
1. inference() - Builds the model as far as is required for running the network
forward to make predictions.
2. loss() - Adds to the inference model the layers required to generate loss.
3. training() - Adds to the loss mo... | {
"repo_name": "MemeticParadigm/TensorFlow",
"path": "tensorflow/g3doc/tutorials/mnist/mnist.py",
"copies": "2",
"size": "5438",
"license": "apache-2.0",
"hash": -6110393723923970000,
"line_mean": 34.7763157895,
"line_max": 79,
"alpha_frac": 0.6754321442,
"autogenerated": false,
"ratio": 3.7842727... |
"""Builds the MNIST network.
Simplify the MNIST model building work.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import tensorflow as tf
# The MNIST dataset has 10 classes, representing the digits 0 through 9.
NUM_CLASSES = 10
# The ... | {
"repo_name": "mengli/PcmAudioRecorder",
"path": "mnist/mnist_with_summary.py",
"copies": "2",
"size": "3224",
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"hash": -6829788456317698000,
"line_mean": 35.6363636364,
"line_max": 82,
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"ratio": 3.418875927889714,
"conf... |
#builds the model from existing data
import inspect,os
import markovify
from textstat.textstat import textstat
#Read files from directory
#Add their contents to a single string
#Make a model from this string
#generate first sentence from this model
class train():
dir=os.path.dirname(os.path.dirname(os.path.abspa... | {
"repo_name": "hailthedawn/HaikuGen",
"path": "haikubot/train.py",
"copies": "1",
"size": "1282",
"license": "mit",
"hash": 6718578018938595000,
"line_mean": 24.66,
"line_max": 146,
"alpha_frac": 0.616224649,
"autogenerated": false,
"ratio": 3.3385416666666665,
"config_test": false,
"has_no_k... |
"""Builds the network.
Summary of available functions:
# Compute input images and labels for training. If you would like to run
# evaluations, use inputs() instead.
inputs, labels = distorted_inputs()
# Compute inference on the model inputs to make a prediction.
predictions = inference(inputs)
# Compute the tota... | {
"repo_name": "sridhar912/Udacity_SDC_Challenge",
"path": "code/predict_steering.py",
"copies": "1",
"size": "22483",
"license": "mit",
"hash": 6951375620969463000,
"line_mean": 40.947761194,
"line_max": 106,
"alpha_frac": 0.5860427879,
"autogenerated": false,
"ratio": 3.494404724898974,
"confi... |
"""Builds the ocr network.
Summary of available functions:
# Compute input images and labels for training. If you would like to run
# evaluations, use inputs() instead.
inputs, labels = distorted_inputs()
# Compute inference on the model inputs to make a prediction.
predictions = inference(inputs)
# Compute t... | {
"repo_name": "Luonic/tf-cnn-lstm-ocr-captcha",
"path": "ocr.py",
"copies": "1",
"size": "22365",
"license": "mit",
"hash": -1114303585883825900,
"line_mean": 37.495697074,
"line_max": 103,
"alpha_frac": 0.6292421194,
"autogenerated": false,
"ratio": 3.6591950261780104,
"config_test": false,
... |
"""Builds the Python Package
"""
from __future__ import (
print_function, unicode_literals, division, absolute_import)
import os
import shutil
from subprocess import run, CalledProcessError
def copy_metadata():
"""
Copies metadata files from toolboxes folder to help folder
When geoprocessing toolbox... | {
"repo_name": "WSDOT-GIS/wsdot-route-gp",
"path": "build_package.py",
"copies": "1",
"size": "1819",
"license": "unlicense",
"hash": 324211018822026300,
"line_mean": 32.0727272727,
"line_max": 123,
"alpha_frac": 0.691588785,
"autogenerated": false,
"ratio": 3.829473684210526,
"config_test": fal... |
"""Builds the Unlimited Hand - sensor values network. (made from MNIST)
Implements the inference/loss/training pattern for model building.
1. inference() - Builds the model as far as is required for running the network
forward to make predictions.
2. loss() - Adds to the inference model the layers required to generat... | {
"repo_name": "eq-inc/eq-tensorflow-learn_uh_sensor_values",
"path": "uh_sensor_values.py",
"copies": "1",
"size": "4846",
"license": "apache-2.0",
"hash": 2338439048135673000,
"line_mean": 37.768,
"line_max": 107,
"alpha_frac": 0.6564176641,
"autogenerated": false,
"ratio": 3.9526916802610113,
... |
"""Builds the VGG16 network.
Implements the inference/loss/training pattern for model building.
1. inference() - Builds the model as far as is required for running the network
forward to make predictions.
2. loss() - Adds to the inference model the layers required to generate loss.
3. training() - Adds to the loss mo... | {
"repo_name": "HaydenFaulkner/phd",
"path": "tensorflow_code/model_defs/cnns/vgg16.py",
"copies": "1",
"size": "11503",
"license": "mit",
"hash": -2177490810821993700,
"line_mean": 40.3776978417,
"line_max": 117,
"alpha_frac": 0.6334869165,
"autogenerated": false,
"ratio": 3.3255276091355883,
"... |
""" Builds up a release package ready to be built or distributed by NPM. The distributable content
is taken from the development folder to make it easier to strip out unneeded package content. """
#!/usr/bin/python
# Imports
import os
import shutil
import fnmatch
import distutils.dir_util
import cli
#
# Finds all fi... | {
"repo_name": "leewinder/ng2-google-recaptcha",
"path": "automation/prepare_distribution_package.py",
"copies": "1",
"size": "2678",
"license": "mit",
"hash": -2391677465756806700,
"line_mean": 26.6082474227,
"line_max": 99,
"alpha_frac": 0.6631814787,
"autogenerated": false,
"ratio": 3.793201133... |
""" Build swig and f2py sources.
"""
from __future__ import division, absolute_import, print_function
import copy
import os
import re
import shlex
import sys
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.errors import DistutilsError, DistutilsSetupError
from d... | {
"repo_name": "DailyActie/Surrogate-Model",
"path": "01-codes/numpy-master/numpy/distutils/command/build_src.py",
"copies": "1",
"size": "31019",
"license": "mit",
"hash": -4454575390726785500,
"line_mean": 38.7679487179,
"line_max": 109,
"alpha_frac": 0.5049808182,
"autogenerated": false,
"ratio... |
""" Build swig and f2py sources.
"""
from __future__ import division, absolute_import, print_function
import os
import re
import sys
import shlex
import copy
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors import D... | {
"repo_name": "lancezlin/ml_template_py",
"path": "lib/python2.7/site-packages/numpy/distutils/command/build_src.py",
"copies": "24",
"size": "30917",
"license": "mit",
"hash": -6741487784436391000,
"line_mean": 38.8929032258,
"line_max": 122,
"alpha_frac": 0.5070349646,
"autogenerated": false,
"... |
""" Build swig and f2py sources.
"""
import os
import re
import sys
import shlex
import copy
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors import DistutilsError, DistutilsSetupError
# this import can't be done h... | {
"repo_name": "simongibbons/numpy",
"path": "numpy/distutils/command/build_src.py",
"copies": "8",
"size": "31180",
"license": "bsd-3-clause",
"hash": 6605238329278689000,
"line_mean": 39.3363518758,
"line_max": 122,
"alpha_frac": 0.5074727389,
"autogenerated": false,
"ratio": 4.067840834964123,
... |
""" Build swig, f2py, pyrex sources.
"""
from __future__ import division, absolute_import, print_function
import os
import re
import sys
import shlex
import copy
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors impo... | {
"repo_name": "WillieMaddox/numpy",
"path": "numpy/distutils/command/build_src.py",
"copies": "141",
"size": "32258",
"license": "bsd-3-clause",
"hash": 3010673648088964000,
"line_mean": 39.0223325062,
"line_max": 122,
"alpha_frac": 0.5061070122,
"autogenerated": false,
"ratio": 4.070410094637224... |
""" Build swig, f2py, pyrex sources.
"""
import os
import re
import sys
import shlex
import copy
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors import DistutilsError, DistutilsSetupError
def have_pyrex():
try... | {
"repo_name": "qsnake/numpy",
"path": "numpy/distutils/command/build_src.py",
"copies": "87",
"size": "32440",
"license": "bsd-3-clause",
"hash": -6927743717376959000,
"line_mean": 39.049382716,
"line_max": 122,
"alpha_frac": 0.5061960543,
"autogenerated": false,
"ratio": 4.075376884422111,
"co... |
""" Build swig, f2py, pyrex sources.
"""
import os
import re
import sys
import shlex
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors import DistutilsError, DistutilsSetupError
try:
import Pyrex.Compiler.Main
... | {
"repo_name": "houseind/robothon",
"path": "GlyphProofer/dist/GlyphProofer.app/Contents/Resources/lib/python2.6/numpy/distutils/command/build_src.py",
"copies": "1",
"size": "28704",
"license": "mit",
"hash": 6403029177121419000,
"line_mean": 39.0893854749,
"line_max": 122,
"alpha_frac": 0.5029960981... |
""" Build swig, f2py, pyrex sources.
"""
import os
import re
import sys
from distutils.command import build_ext
from distutils.dep_util import newer_group, newer
from distutils.util import get_platform
from distutils.errors import DistutilsError, DistutilsSetupError
try:
import Pyrex.Compiler.Main
have_pyrex... | {
"repo_name": "santisiri/popego",
"path": "envs/ALPHA-POPEGO/lib/python2.5/site-packages/numpy-1.0.4-py2.5-linux-x86_64.egg/numpy/distutils/command/build_src.py",
"copies": "1",
"size": "28765",
"license": "bsd-3-clause",
"hash": -2258175597111122000,
"line_mean": 39.1745810056,
"line_max": 122,
"alp... |
"""Build taggers and tag text"""
__author__ = 'Kyle P. Johnson <kyle@kyle-p-johnson.com>'
__license__ = 'MIT License. See LICENSE.'
import logging
import os
from pprint import pprint
import re
import site
class MakePOSTagger(object):
"""rework Perseus latin-analyses.txt into Python dictionary"""
def __init... | {
"repo_name": "cltk/latin_pos_lemmata_cltk",
"path": "pos_latin.py",
"copies": "1",
"size": "24334",
"license": "mit",
"hash": -1303732333404194000,
"line_mean": 55.1986143187,
"line_max": 87,
"alpha_frac": 0.3128955371,
"autogenerated": false,
"ratio": 5.246658042259595,
"config_test": false,
... |
# BuildTarget: images/blank.png
# BuildTarget: images/parameters.png
# BuildTarget: images/shaderBallColoredStripes.png
# BuildTarget: images/shaderBallStripes.png
import time
import imath
import Gaffer
import GafferOSL
import GafferUI
scriptWindow = GafferUI.ScriptWindow.acquire( script )
script["OSLCode"] = Gaf... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/TutorialUsingTheOSLCodeNode/screengrab.py",
"copies": "4",
"size": "2079",
"license": "bsd-3-clause",
"hash": -6429782668177917000,
"line_mean": 45.2,
"line_max": 169,
"alpha_frac": 0.7176527177,
"autogenerated": false,
"r... |
# BuildTarget: images/blank.png
import time
import imath
import Gaffer
import GafferOSL
import GafferUI
scriptWindow = GafferUI.ScriptWindow.acquire( script )
script["OSLCode"] = GafferOSL.OSLCode()
script.selection().add( script["OSLCode"] )
oslEditor = GafferUI.NodeEditor.acquire( script["OSLCode"], floating=Tr... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/TutorialUsingTheOSLCodeNode/screengrab.py",
"copies": "6",
"size": "1947",
"license": "bsd-3-clause",
"hash": -6904201482599586000,
"line_mean": 45.3571428571,
"line_max": 169,
"alpha_frac": 0.7092963534,
"autogenerated... |
# BuildTarget: images/conceptPerformanceBestPracticesContextsGraphEditor.png
# BuildTarget: images/conceptPerformanceBestPracticesContextsImprovedStats.png
# BuildTarget: images/conceptPerformanceBestPracticesContextsStats.png
# BuildTarget: images/conceptPerformanceBestPracticesContextsViewer.png
# BuildTarget: images... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/PerformanceBestPractices/screengrab.py",
"copies": "4",
"size": "5294",
"license": "bsd-3-clause",
"hash": 4165350455686202400,
"line_mean": 42.7603305785,
"line_max": 175,
"alpha_frac": 0.7661503589,
"autogenerated": false,... |
# BuildTarget: images/exampleAnamorphicCameraSetup.png
# BuildTarget: images/exampleSphericalCameraSetupArnoldTweaks.png
# BuildTarget: images/interfaceCameraVisualizer.png
# BuildTarget: images/renderDepthOfFieldBlur.png
# BuildTarget: images/taskCameraApertureFocalLengthPlugs.png
# BuildTarget: images/taskCameraCusto... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithScenes/Camera/screengrab.py",
"copies": "4",
"size": "15251",
"license": "bsd-3-clause",
"hash": 6826189736502910000,
"line_mean": 53.6630824373,
"line_max": 194,
"alpha_frac": 0.7362140188,
"autogenerated": false,
"ratio": 3.332095258... |
# BuildTarget: images/exampleMacbethChart.png
import os
import tempfile
import subprocess32 as subprocess
import imath
import IECore
import Gaffer
import GafferUI
# Create a random directory in `/tmp` for the dispatcher's `jobsDirectory`, so we don't clutter the user's `~gaffer` directory
__temporaryDirectory = temp... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialStartupConfig3/screengrab.py",
"copies": "3",
"size": "1528",
"license": "bsd-3-clause",
"hash": -5004691224341638000,
"line_mean": 34.5348837209,
"line_max": 140,
"alpha_frac": 0.7342931937,
"autogener... |
# BuildTarget: images/exampleMultiShotRenderSpreadsheet.png
# BuildTarget: images/examplePerLocationLightTweakSpreadsheet.png
# BuildTarget: images/examplePerLocationTransformSpreadsheet.png
# BuildTarget: images/interfaceSpreadsheetNode.png
# BuildTarget: images/interfaceSpreadsheetNodeAuxiliaryConnections.png
# Build... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/SpreadsheetNode/screengrab.py",
"copies": "4",
"size": "30022",
"license": "bsd-3-clause",
"hash": -655466601704415000,
"line_mean": 44.3504531722,
"line_max": 277,
"alpha_frac": 0.7578775565,
"autogenerated": false,
"rati... |
# BuildTarget: images/graphEditorAllNodes.png
# BuildTarget: images/graphEditorGroupConnections.png
# BuildTarget: images/graphEditorRearrangedNodes.png
# BuildTarget: images/graphEditorShaderAssignmentConnections.png
# BuildTarget: images/mainWindowFinalScene.png
# BuildTarget: images/mainWindowSphereNode.png
# BuildT... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialNodeGraphEditingInPython/screengrab.py",
"copies": "4",
"size": "6266",
"license": "bsd-3-clause",
"hash": -8978495803349897000,
"line_mean": 45.0735294118,
"line_max": 172,
"alpha_frac": 0.7701883179,
"auto... |
# BuildTarget: images/graphEditorGroupFirst.png images/graphEditorGroupSecond.png images/conceptPerformanceBestPracticesContextsViewer.png images/conceptPerformanceBestPracticesContextsGraphEditor.png images/conceptPerformanceBestPracticesContextsStats.png images/conceptPerformanceBestPracticesContextsImprovedStats.png... | {
"repo_name": "lucienfostier/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/PerformanceBestPractices/screengrab.py",
"copies": "2",
"size": "5311",
"license": "bsd-3-clause",
"hash": -6117138415407566000,
"line_mean": 44.0169491525,
"line_max": 320,
"alpha_frac": 0.7661457353,
"autogenerated"... |
# BuildTarget: images/hierarchyView.png
# BuildTarget: images/sceneInspector.png
# BuildTarget: images/sceneInspectorAttributesSection.png
# BuildTarget: images/sceneInspectorBoundSection.png
# BuildTarget: images/sceneInspectorObjectSection.png
# BuildTarget: images/sceneInspectorTransformSection.png
import IECore
im... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithScenes/AnatomyOfAScene/screengrab.py",
"copies": "4",
"size": "3630",
"license": "bsd-3-clause",
"hash": 4625653591915193000,
"line_mean": 42.734939759,
"line_max": 117,
"alpha_frac": 0.764738292,
"autogenerated": false,
"ratio": 3.483... |
# BuildTarget: images/illustrationStartupConfigDirectoryTree.png
# BuildTarget: images/tutorialSettingsWindowCustomContextVariable.png
# BuildTarget: images/tutorialSettingsWindowDefaultContextVariables.png
# BuildTarget: images/tutorialVariableSubstitutionExpression.png
# BuildTarget: images/tutorialVariableSubstituti... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialStartupConfig1/screengrab.py",
"copies": "4",
"size": "4670",
"license": "bsd-3-clause",
"hash": -5152656293151585000,
"line_mean": 43.9038461538,
"line_max": 140,
"alpha_frac": 0.7655246253,
"autogenerated"... |
# BuildTarget: images/interfaceCameraParameters.png
# BuildTarget: images/interfaceCameraSets.png
import IECore
import time
import imath
import Gaffer
import GafferUI
import GafferScene
import GafferSceneUI
import GafferOSL
import GafferAppleseed
# Interface: the object and set sections of a camera in the Scene Ins... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithScenes/AnatomyOfACamera/screengrab.py",
"copies": "4",
"size": "2326",
"license": "bsd-3-clause",
"hash": 912905782515140200,
"line_mean": 40.5357142857,
"line_max": 137,
"alpha_frac": 0.7489251935,
"autogenerated": false,
"ratio": 3.8... |
# BuildTarget: images/interfaceCameraParameters.png
import IECore
import time
import imath
import Gaffer
import GafferUI
import GafferScene
import GafferSceneUI
import GafferOSL
import GafferAppleseed
# Interface: the object and set sections of a camera in the Scene Inspector
script["Camera"] = GafferScene.Camera()... | {
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"path": "doc/source/WorkingWithScenes/AnatomyOfACamera/screengrab.py",
"copies": "4",
"size": "2280",
"license": "bsd-3-clause",
"hash": -4457397723045275000,
"line_mean": 40.4545454545,
"line_max": 137,
"alpha_frac": 0.7469298246,
"autogenerated": false,
"ra... |
# BuildTarget: images/interfaceCameraVisualizer.png
import os
import subprocess32 as subprocess
import tempfile
import time
import imath
import IECore
import Gaffer
import GafferScene
import GafferUI
import GafferSceneUI
scriptWindow = GafferUI.ScriptWindow.acquire( script )
viewer = scriptWindow.getLayout().editors... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithScenes/Camera/screengrab.py",
"copies": "3",
"size": "14762",
"license": "bsd-3-clause",
"hash": 6743312741693265000,
"line_mean": 53.2720588235,
"line_max": 194,
"alpha_frac": 0.7310662512,
"autogenerated": false,
"ratio": 3.3375... |
# BuildTarget: images/interfaceDefaultLightPlug.png
# BuildTarget: images/interfaceLightLinkSetupGraphEditor.png
# BuildTarget: images/interfaceLightSetGraphEditor.png
# BuildTarget: images/interfaceLightSetNodeEditor.png
# BuildTarget: images/interfaceLinkedLightsAttribute.png
# BuildTarget: images/interfaceLinkedLigh... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithScenes/LightLinking/screengrab.py",
"copies": "4",
"size": "6123",
"license": "bsd-3-clause",
"hash": 3266396225535910000,
"line_mean": 45.7404580153,
"line_max": 117,
"alpha_frac": 0.7759268333,
"autogenerated": false,
"ratio": 3.7244... |
# BuildTarget: images/interfaceDefaultLightPlug.png
# BuildTarget: images/interfaceLinkedLightsAttribute.png
# BuildTarget: images/interfaceLightLinkSetupGraphEditor.png
# BuildTarget: images/interfaceLinkedLightsPlug.png
# BuildTarget: images/taskLightLinkingSetExpressionLocation.png
# BuildTarget: images/interfaceLig... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithScenes/LightLinking/screengrab.py",
"copies": "4",
"size": "6066",
"license": "bsd-3-clause",
"hash": -8720241115458316000,
"line_mean": 45.6615384615,
"line_max": 117,
"alpha_frac": 0.774975272,
"autogenerated": false,
"ratio": 3... |
# BuildTarget: images/interfaceUIEditor.png
import os
import Gaffer
import GafferScene
import GafferUI
scriptWindow = GafferUI.ScriptWindow.acquire( script )
graphEditor = scriptWindow.getLayout().editors( GafferUI.GraphEditor )[0]
# Illustration of the basics of a Box
# script["fileName"].setValue( os.path.abspat... | {
"repo_name": "boberfly/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/BoxNode/screengrab.py",
"copies": "4",
"size": "5310",
"license": "bsd-3-clause",
"hash": -5940319457675287000,
"line_mean": 45.5789473684,
"line_max": 97,
"alpha_frac": 0.770433145,
"autogenerated": false,
"ratio": 3.39... |
# BuildTarget: images/mainDefaultLayout.png
# BuildTarget: images/mainSceneReaderNode.png
# BuildTarget: images/sceneReaderBound.png
# BuildTarget: images/viewerSceneReaderBounding.png
# BuildTarget: images/hierarchyViewExpandedTwoLevels.png
# BuildTarget: images/mainHeadAndLeftLegExpanded.png
# BuildTarget: images/vie... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/GettingStarted/TutorialAssemblingTheGafferBot/screengrab.py",
"copies": "4",
"size": "11759",
"license": "bsd-3-clause",
"hash": -145281597199879070,
"line_mean": 47.9958333333,
"line_max": 178,
"alpha_frac": 0.775065907,
"autogenerated": false,
... |
# BuildTarget: images/mainDefaultLayout.png
import os
import time
import imath
import IECore
import Gaffer
import GafferScene
import GafferUI
import GafferSceneUI
scriptWindow = GafferUI.ScriptWindow.acquire( script )
viewer = scriptWindow.getLayout().editors( GafferUI.Viewer )[0]
graphEditor = scriptWindow.getLa... | {
"repo_name": "boberfly/gaffer",
"path": "doc/source/GettingStarted/TutorialAssemblingTheGafferBot/screengrab.py",
"copies": "4",
"size": "10624",
"license": "bsd-3-clause",
"hash": -1710939308407735800,
"line_mean": 47.9585253456,
"line_max": 178,
"alpha_frac": 0.766189759,
"autogenerated": false,... |
# BuildTarget: images/pythonEditorHelloWorld.png
import os
import IECore
import imath
import time
import Gaffer
import GafferScene
import GafferUI
import GafferSceneUI
mainWindow = GafferUI.ScriptWindow.acquire( script )
pythonEditor = mainWindow.getLayout().editors( GafferUI.PythonEditor )[0]
graphEditor = mainWin... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialNodeGraphEditingInPython/screengrab.py",
"copies": "4",
"size": "5611",
"license": "bsd-3-clause",
"hash": 1104920265094168700,
"line_mean": 44.6178861789,
"line_max": 172,
"alpha_frac": 0.7595793976,
"... |
# BuildTarget: images/sceneInspector.png
import IECore
import time
import Gaffer
import GafferUI
import GafferScene
import GafferSceneUI
import GafferOSL
import GafferAppleseed
# Create and connect nodes
script["SceneReader"] = GafferScene.SceneReader()
script["ShaderAssignment"] = GafferScene.ShaderAssignment()
sc... | {
"repo_name": "appleseedhq/gaffer",
"path": "doc/source/WorkingWithScenes/AnatomyOfAScene/screengrab.py",
"copies": "4",
"size": "3368",
"license": "bsd-3-clause",
"hash": -1111725627480746900,
"line_mean": 42.1794871795,
"line_max": 117,
"alpha_frac": 0.7568289786,
"autogenerated": false,
"ratio... |
# BuildTarget: images/tutorialBookmarks.png
# BuildTarget: images/tutorialDefaultBookmark.png
# BuildTarget: images/tutorialDefaultImageNodeBookmark.png
# BuildTarget: images/tutorialDefaultImageNodePath.png
import os
import subprocess32 as subprocess
import tempfile
import time
import Gaffer
import GafferUI
import G... | {
"repo_name": "ImageEngine/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialStartupConfig2/screengrab.py",
"copies": "5",
"size": "4648",
"license": "bsd-3-clause",
"hash": -4368838754671804000,
"line_mean": 39.7719298246,
"line_max": 140,
"alpha_frac": 0.72267642,
"autogenerat... |
# BuildTarget: images/tutorialSettingsWindowDefaultContextVariables.png
# BuildTarget: images/tutorialSettingsWindowCustomContextVariable.png
# BuildTarget: images/tutorialVariableSubstitutionInStringPlug.png
# BuildTarget: images/tutorialVariableSubstitutionExpression.png
# BuildTarget: images/tutorialVariableSubstitu... | {
"repo_name": "lucienfostier/gaffer",
"path": "doc/source/WorkingWithThePythonScriptingAPI/TutorialStartupConfig1/screengrab.py",
"copies": "3",
"size": "4669",
"license": "bsd-3-clause",
"hash": 998621555613013400,
"line_mean": 43.0471698113,
"line_max": 140,
"alpha_frac": 0.7633326194,
"autogener... |
# BuildTarget: images/tutorialSettingUpASpreadsheetAppleseedOptionsNode.png
# BuildTarget: images/tutorialSettingUpASpreadsheetCleanColumn.png
# BuildTarget: images/tutorialSettingUpASpreadsheetDefaultCell.png
# BuildTarget: images/tutorialSettingUpASpreadsheetFullName.png
# BuildTarget: images/tutorialSettingUpASpread... | {
"repo_name": "hradec/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/TutorialSettingUpASpreadsheet/screengrab.py",
"copies": "4",
"size": "6922",
"license": "bsd-3-clause",
"hash": -1817683678453973000,
"line_mean": 41.9937888199,
"line_max": 130,
"alpha_frac": 0.7827217567,
"autogenerated": ... |
# BuildTarget: images/tutorialSettingUpASpreadsheetRow2Other.png images/tutorialSettingUpASpreadsheetRows2A2B.png images/tutorialSettingUpASpreadsheetOverscanValues.png images/tutorialSettingUpASpreadsheetFullName.png images/tutorialSettingUpASpreadsheetRow2.png images/tutorialSettingUpASpreadsheetCleanColumn.png image... | {
"repo_name": "lucienfostier/gaffer",
"path": "doc/source/WorkingWithTheNodeGraph/TutorialSettingUpASpreadsheet/screengrab.py",
"copies": "3",
"size": "6742",
"license": "bsd-3-clause",
"hash": 3867123581439572000,
"line_mean": 44.2483221477,
"line_max": 699,
"alpha_frac": 0.7840403441,
"autogenera... |
import El
import numpy as np
def buildTFUSE(k,N,fieldCode, ncells)
delta = np.divide(n,N, dtype=float)
N_sub = ncells[0]
n_sub = np.floor(delta * N_sub)
A_sub = El.DistSparseMatrix()
A_sub.Resize(n_sub,N_sub)
if fieldCode in ('R', 'Pos'):
El.Gaussian(A_sub , n_sub, N_sub) #should be ... | {
"repo_name": "monajemi/TensorPT",
"path": "Python/DEP/buildTFUSE.py",
"copies": "1",
"size": "1067",
"license": "bsd-3-clause",
"hash": -1057294037146373200,
"line_mean": 26.358974359,
"line_max": 98,
"alpha_frac": 0.633552015,
"autogenerated": false,
"ratio": 2.822751322751323,
"config_test":... |
'Build the bundled capnp distribution'
import subprocess
import os
import shutil
import struct
import sys
def build_libcapnp(bundle_dir, build_dir):
'''
Build capnproto
'''
bundle_dir = os.path.abspath(bundle_dir)
capnp_dir = os.path.join(bundle_dir, 'capnproto-c++')
build_dir = os.path.abspa... | {
"repo_name": "SymbiFlow/pycapnp",
"path": "buildutils/build.py",
"copies": "1",
"size": "2374",
"license": "bsd-2-clause",
"hash": -4587249826285556700,
"line_mean": 28.3086419753,
"line_max": 81,
"alpha_frac": 0.597725358,
"autogenerated": false,
"ratio": 3.657935285053929,
"config_test": fal... |
'Build the bundled capnp distribution'
import subprocess
import os
import shutil
import struct
import sys
def build_libcapnp(bundle_dir, build_dir): # noqa: C901
'''
Build capnproto
'''
bundle_dir = os.path.abspath(bundle_dir)
capnp_dir = os.path.join(bundle_dir, 'capnproto-c++')
build_dir =... | {
"repo_name": "jparyani/pycapnp",
"path": "buildutils/build.py",
"copies": "1",
"size": "2586",
"license": "bsd-2-clause",
"hash": -5532029897994063000,
"line_mean": 28.724137931,
"line_max": 81,
"alpha_frac": 0.5966744006,
"autogenerated": false,
"ratio": 3.6628895184135977,
"config_test": fal... |
"""Build the C client docs.
"""
from __future__ import with_statement
import os
import shutil
import socket
import subprocess
import time
import urllib2
def clean_dir(dir):
try:
shutil.rmtree(dir)
except:
pass
os.makedirs(dir)
def gen_api(dir):
clean_dir(dir)
clean_dir("docs/sourc... | {
"repo_name": "HeliumProject/mongo-c",
"path": "docs/buildscripts/docs.py",
"copies": "5",
"size": "1285",
"license": "apache-2.0",
"hash": -5538134482434875000,
"line_mean": 21.5438596491,
"line_max": 79,
"alpha_frac": 0.6194552529,
"autogenerated": false,
"ratio": 3.454301075268817,
"config_t... |
# Build the documentation for nanodbc library
# Configuration
nanodbc_name = 'nanodbc'
nanodbc_versions = ['master', '2.13.0']
# End of Configuration
import errno
import os
import sys
from subprocess import check_call, CalledProcessError, Popen, PIPE
def build_docs(**kwargs):
assert nanodbc_versions
version ... | {
"repo_name": "nanodbc/nanodbc",
"path": "doc/build.py",
"copies": "1",
"size": "2161",
"license": "mit",
"hash": 982275134241818600,
"line_mean": 33.3015873016,
"line_max": 76,
"alpha_frac": 0.5654789449,
"autogenerated": false,
"ratio": 3.43015873015873,
"config_test": false,
"has_no_keywor... |
"""Build the documentation
Copyright (c) 2015 Francesco Montesano
MIT Licence
"""
import colorama
import dodocs.config as dconf
import dodocs.logger as dlog
from dodocs.mkdoc import mkprofile as mkp
def build_cmd_arguments(subparser, formatter_class):
"""Create the ``build`` parser and fill it with the releva... | {
"repo_name": "montefra/dodocs",
"path": "dodocs/mkdoc/__init__.py",
"copies": "1",
"size": "1815",
"license": "mit",
"hash": -183293192613631400,
"line_mean": 26.5,
"line_max": 78,
"alpha_frac": 0.5785123967,
"autogenerated": false,
"ratio": 4.571788413098237,
"config_test": false,
"has_no_k... |
# build the exe by simply running this script
#import sys
#sys.argv.append("py2exe")
# standard setup file
from distutils.core import setup
import py2exe
# get all dependencies from dependencies folder
# and make sure all dlls and pyds are included
import sys
sys.path.append("pythongis/dependencies")
import os
def al... | {
"repo_name": "karimbahgat/PythonGis",
"path": "(sandbox,tobemerged)/setup,works.py",
"copies": "1",
"size": "1313",
"license": "mit",
"hash": 724995078176668800,
"line_mean": 31.0243902439,
"line_max": 72,
"alpha_frac": 0.5811119573,
"autogenerated": false,
"ratio": 4.015290519877676,
"config_... |
# Build the model, restore the variables and run the inference
# Need to use SavedModel builder and loader instead - future work
import os
import time
from multiprocessing import Process
import imageio
import numpy as np
import tensorflow as tf
from kafka import KafkaProducer
from scipy.misc import imread
from skimage... | {
"repo_name": "ani2404/ee6761cloud",
"path": "inf_main.py",
"copies": "1",
"size": "4827",
"license": "mit",
"hash": -7988056586810563000,
"line_mean": 36.4263565891,
"line_max": 172,
"alpha_frac": 0.6631448104,
"autogenerated": false,
"ratio": 3.623873873873874,
"config_test": false,
"has_no... |
""" build the nb classifier using the weka api
after training need to make predictions on an
incremental basis for the test data
USAGE : python naivebayes_casa.py path_to_training_arff path_to_test_arff """
# <imports>
import sys
import os
import weka.core.jvm as jvm
from weka.core.converters impo... | {
"repo_name": "aksheus/Detect-Depression",
"path": "naivebayes_csa.py",
"copies": "1",
"size": "1954",
"license": "mit",
"hash": 7962689176924905000,
"line_mean": 20.2391304348,
"line_max": 128,
"alpha_frac": 0.698567042,
"autogenerated": false,
"ratio": 3.166936790923825,
"config_test": true,
... |
""" Build the network architecture.
>>> arch = Architecture(
... rgb_shape=(3, 64, 64),
... lidar_shape=(6, 64, 64),
... fusion='early',
... obb_parametrization='vector_and_width',
... synthetic='no_pretrain',
... channel_dropout='cdrop',
.... | {
"repo_name": "jfemiani/srp-boxes",
"path": "srp/model/arch.py",
"copies": "1",
"size": "35262",
"license": "mit",
"hash": -94830538689034260,
"line_mean": 36.9569429494,
"line_max": 120,
"alpha_frac": 0.609664795,
"autogenerated": false,
"ratio": 3.7709335899903755,
"config_test": false,
"ha... |
"""Build the Pygments modules from the CSS."""
import os
import tools.pyg_css_convert as pcc
pth = os.path.dirname(os.path.abspath(__file__))
css = os.path.join(pth, 'stylesheets')
output = os.path.join(pth, 'pymdown_styles')
added = []
for f in os.listdir(output):
os.remove(os.path.join(output, f))
for f in os.... | {
"repo_name": "facelessuser/pymdown-styles",
"path": "build_modules.py",
"copies": "1",
"size": "1403",
"license": "mit",
"hash": 2937327654731811300,
"line_mean": 36.9189189189,
"line_max": 99,
"alpha_frac": 0.5759087669,
"autogenerated": false,
"ratio": 2.817269076305221,
"config_test": false... |
"""Build the qbsolv package."""
from setuptools import setup
from setuptools.extension import Extension
from setuptools.command.build_ext import build_ext
import os
cwd = os.path.abspath(os.path.dirname(__file__))
if not os.path.exists(os.path.join(cwd, 'PKG-INFO')):
try:
from Cython.Build import cythoniz... | {
"repo_name": "myriagon/qbsolv",
"path": "setup.py",
"copies": "1",
"size": "1915",
"license": "apache-2.0",
"hash": 2821918566325579300,
"line_mean": 26.3571428571,
"line_max": 80,
"alpha_frac": 0.5702349869,
"autogenerated": false,
"ratio": 3.377425044091711,
"config_test": false,
"has_no_k... |
# Build the Rust field and message types from the FIX spec.
import errno
import os
import re
from collections import namedtuple, Counter
import xml.etree.ElementTree as ET
from codegen_base import *
def format_name(name):
# Handle case where name begins with a numeric character
numbers = '0123456789'
if... | {
"repo_name": "billpmurphy/rustfix",
"path": "codegen/codegen.py",
"copies": "1",
"size": "13252",
"license": "bsd-2-clause",
"hash": 1693970052971519500,
"line_mean": 31.4009779951,
"line_max": 83,
"alpha_frac": 0.5402958044,
"autogenerated": false,
"ratio": 3.6306849315068495,
"config_test": ... |
""" Build the SASS - main.css and optionally the widgets """
import sass
import os
import shutil
from datetime import datetime
# SASS directory
SASS = os.path.join("cms", "sass")
# Output style
STYLE = "compressed"
# SASS and error file for the main CSS
MAIN_SETTINGS = (os.path.join(SASS, "main.scss"),
... | {
"repo_name": "DOAJ/doaj",
"path": "portality/cms/build_sass.py",
"copies": "1",
"size": "4028",
"license": "apache-2.0",
"hash": -9202428084632396000,
"line_mean": 33.1355932203,
"line_max": 146,
"alpha_frac": 0.566285998,
"autogenerated": false,
"ratio": 3.382031905961377,
"config_test": fals... |
"""Build the simplest model of bilayer graphene and compute its band structure"""
import pybinding as pb
import matplotlib.pyplot as plt
from math import sqrt, pi
pb.pltutils.use_style()
def bilayer_graphene():
"""Bilayer lattice in the AB-stacked form (Bernal-stacked)
This is the simplest model with just a... | {
"repo_name": "dean0x7d/pybinding",
"path": "docs/examples/lattice/bilayer_graphene.py",
"copies": "2",
"size": "1728",
"license": "bsd-2-clause",
"hash": 7181603806228669000,
"line_mean": 24.7910447761,
"line_max": 93,
"alpha_frac": 0.5289351852,
"autogenerated": false,
"ratio": 2.48275862068965... |
"""Build the Srctools package."""
from setuptools import setup, Extension, find_packages
import sys
import os
WIN = sys.platform.startswith('win')
SQUISH_CPP = [
'libsquish/alpha.cpp',
'libsquish/clusterfit.cpp',
'libsquish/colourblock.cpp',
'libsquish/colourfit.cpp',
'libsquish/colourset.cpp',
... | {
"repo_name": "TeamSpen210/srctools",
"path": "setup.py",
"copies": "1",
"size": "3043",
"license": "unlicense",
"hash": -3213793882237253600,
"line_mean": 27.7075471698,
"line_max": 79,
"alpha_frac": 0.5264541571,
"autogenerated": false,
"ratio": 3.7291666666666665,
"config_test": false,
"ha... |
"""Build the static files."""
import os
import sys
import time
import csscompressor
import watchdog.events
import watchdog.observers
maps = {
'index.min.css': (
'normalize.css',
'skeleton.css',
'common.css',
'index.css',
),
'analyse.min.css': (
'normalize.css',
... | {
"repo_name": "thisismyrobot/dnstwister",
"path": "build/build_fed.py",
"copies": "1",
"size": "1786",
"license": "unlicense",
"hash": 6212118969230743000,
"line_mean": 21.325,
"line_max": 72,
"alpha_frac": 0.539193729,
"autogenerated": false,
"ratio": 3.447876447876448,
"config_test": false,
... |
"""Build the thumbnails for the hexbin
"""
import itertools
from random import shuffle
import sys
import json
import io
import urllib
import yaml
from PIL import Image
import requests
def check_status(datum):
"""Check that both the url and image link are valid URLs and that the
image link isn't just a redi... | {
"repo_name": "wd15/chimad-phase-field",
"path": "_data/hexbin.py",
"copies": "1",
"size": "2868",
"license": "mit",
"hash": -4053042398622083000,
"line_mean": 28.5670103093,
"line_max": 86,
"alpha_frac": 0.6052998605,
"autogenerated": false,
"ratio": 3.2739726027397262,
"config_test": false,
... |
"""Build the thumbnails for the hexbin
"""
import json
import io
import urllib
import yaml
from PIL import Image
import progressbar
import numpy as np
import requests
def hexbin_yaml_to_json():
"""Generate JSON image data from the YAML.
"""
data = yaml.load(open('_data/hexbin.yaml', 'r'))
for item ... | {
"repo_name": "usnistgov/chimad-phase-field",
"path": "_data/hexbin.py",
"copies": "1",
"size": "3066",
"license": "mit",
"hash": -2217355434092464000,
"line_mean": 29.3564356436,
"line_max": 77,
"alpha_frac": 0.5769732551,
"autogenerated": false,
"ratio": 3.3217768147345614,
"config_test": fal... |
"""Build the tutorial data files from the IMDB *.list.gz files."""
import csv
import gzip
import os
import re
from datetime import datetime
split_on_tabs = re.compile(b'\t+').split
def main():
os.chdir(os.path.dirname(__file__))
if not os.path.isdir('../data'):
os.makedirs('../data')
# Load movi... | {
"repo_name": "randomthought/mastering_python_pandas",
"path": "build/BUILD.py",
"copies": "3",
"size": "6055",
"license": "mit",
"hash": -8994958366625696000,
"line_mean": 26.3981900452,
"line_max": 78,
"alpha_frac": 0.5156069364,
"autogenerated": false,
"ratio": 3.8371356147021545,
"config_te... |
"""Build the tutorial data files from the IMDB *.list.gz files."""
import csv
import gzip
import os
import re
from datetime import datetime
split_on_tabs = re.compile(b'\t+').split
def main():
os.chdir(os.path.dirname(os.path.abspath(__file__)))
if not os.path.isdir('../data'):
os.makedirs('../data'... | {
"repo_name": "abecede753/trax",
"path": "notebooks/pycon-pandas-tutorial-master/build/BUILD.py",
"copies": "1",
"size": "6174",
"license": "mit",
"hash": 5315510542815042000,
"line_mean": 26.3185840708,
"line_max": 78,
"alpha_frac": 0.5155490768,
"autogenerated": false,
"ratio": 3.84194150591163... |
"""Build the tutorial data files from the IMDB *.list.gz files."""
import csv
import gzip
import os
import re
import sys
from datetime import datetime
split_on_tabs = re.compile(b'\t+').split
BAD_GENRES = {b'Adult', b'Documentary', b'Short', b'Horror', b'Reality-TV',
b'Talk-Show', b'Game-Show', b'Reali... | {
"repo_name": "brandon-rhodes/pycon-pandas-tutorial",
"path": "build/BUILD.py",
"copies": "1",
"size": "6481",
"license": "mit",
"hash": 283241817587773730,
"line_mean": 26.8154506438,
"line_max": 78,
"alpha_frac": 0.5176670267,
"autogenerated": false,
"ratio": 3.772409778812573,
"config_test":... |
"""Build the yago to lkif mapping using lkif_to_yago mapping and the
yago hierarchy graph.
Usage:
get_yago_to_lkif.py <mapping_filename> <graph_filename> <output_file>
"""
import utils
from collections import defaultdict
from docopt import docopt
def get_oldest_ancestors(node, graph):
"""Returns the oldes... | {
"repo_name": "MIREL-UNC/mirel-scripts",
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