Thu Jul 16, 2015
I’ve been excited to try out Lollipop for a long time, especially after delving deep into Google’s new design language, dubbed Material Design, and even using it in my own user interface design projects. But that is precisely the problem with Android, unless you’re using a Nexus, you have to wait a long, long time before getting the latest. All told, it takes roughly one year for most Android users to catch up. So, when “Android M” was announced, I knew my time was near. Except, it wasn’t.
In case you haven’t been following along (shocking, I know), I’m currently using Cyanogenmod to extend the life of my One S, which HTC wantonly threw into the obsolescence pile after barely a year of support. Wading into the murky pool of aftermarket ROMs is daunting in and of itself, but now I’ve fully come to realize how inconsistent and whimsical placing your trust into a ragtag bunch of humble volunteers truly is.
And total respect to all the community developers who code these ROMs in their spare time, cause without you guys… well, let’s just say that the adoption rate for the latest Android software would probably be a lot lower.
However, it seems that ever since the company split off its for-profit arm, Cyanogen OS, resources have followed the $$$ instead. I get it - this is how capitalism works. It doesn’t make the situation any less frustrating though. Let me explain.
Cyanogenmod promised a stable snapshot version of Lollipop within two weeks of the announcement. Several months later, the snapshot was conspicuously lacking. Then, there was a blog post declaring, with great fanfare, that the snapshot had arrived and builds were rolling out. Except, it turned out only a scant few devices were getting snapshots. Many, including the One S, were still on nightlies.
Now, Lollipop nightlies have been available for a long time, but many of us were waiting for a more stable snapshot, as we were accustomed to getting every month on KitKat. I eventually capitulated and moved onto the nightlies. Which have been great, by the way, my worries about stability were unfounded - I should have just flashed the nightlies a year ago.
The fundamental problem here is communication, plain and simple. Given that Cyanogenmod is a community effort, I’m willing to adapt to changing development cycles and go wherever the wind is blowing. But even polite queries from users about the status of the snapshots were pointedly ignored. Instead we got developer profiles and T-shirt competitions. Why not just be honest and open about where things are at? Instead of trying to draw in a wider user base that may not fall into the uber-geek category, Cyanogenmod comes off as very exclusionary.
 It’s a shame, because Cyanogenmod could be something more than a homebrew club. It could be a genuine grassroots movement - especially for the developing world that cannot afford to upgrade their phone every year.
I didn’t mean this to turn into a rant, but there you go. I harbour no ill feeling toward Cyanogenmod, and frankly, I’ll be moving on anyway once I upgrade my phone this year.
In the meantime, Lollipop is better than I hoped it would be. The interface is noticeably faster and Material Design looks great, even on my AMOLED display, which tends to favour dark colours over white. Overheating issues seem to have dissipated somewhat (but it is a hot summer, so hard to tell). But what I’m most impressed with is the increase in battery life. I suspect this improvement is due to a new runtime environment, which changed from Dalvik to to ART in Lollipop.
Like I said, I should have been enjoying Lollipop months ago, but here we are. I’ll have a few more months to use it yet, and then I’ll be moving onto a flagship. There have been a few launched this year, but there are many more to come.
Stay frosty, my friends.


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| Packages that use Sprite | |
|---|---|
| com.tabuto.j2dgf | |
| com.tabuto.j2dgf.collision | |
| com.tabuto.jsimlife |
| Uses of Sprite in com.tabuto.j2dgf |
|---|
| Classes in com.tabuto.j2dgf with type parameters of type Sprite | |
|---|---|
class |
Group<E extends Sprite>
Group is a variable size contiguous indexable array of Sprite . |
| Fields in com.tabuto.j2dgf with type parameters of type Sprite | |
|---|---|
java.util.Vector<Sprite> |
SpriteGroup.group
Deprecated. The Sprite vector group |
| Methods in com.tabuto.j2dgf that return Sprite | |
|---|---|
Sprite |
SpriteGroup.getSprite(int index)
Deprecated. Return a Sprite by the index |
Sprite |
SpriteGroup.getSpriteByHash(int hash)
Deprecated. Find a sprite with a specific ID |
private E[] |
Group.newElementArray(int size)
|
| Methods in com.tabuto.j2dgf with parameters of type Sprite | |
|---|---|
void |
SpriteGroup.AddSprite(Sprite s)
Deprecated. This method add an element in the group Vector |
private int |
SpriteGroup.FindSprite(Sprite p)
Deprecated. Find the Sprite p in the group Vector and returns the element's vector index |
boolean |
Sprite.isCollide(Sprite other)
Return true if this Sprite collides with other one. |
boolean |
Sprite.isCollide(Sprite other,
double DIST)
Return true if this Sprite collides with other or if
the distance beetween sprite is minus than DIST |
void |
Sprite.moveTo(Sprite s)
Set sprite's direction in order to reach the Sprite s |
void |
SpriteGroup.RemoveSprite(Sprite p)
Deprecated. Remove a Sprite from the Group Vector |
| Uses of Sprite in com.tabuto.j2dgf.collision |
|---|
| Fields in com.tabuto.j2dgf.collision with type parameters of type Sprite | |
|---|---|
protected Group<? extends Sprite> |
CollisionDetector.group1
SpriteGroups we want to check |
protected Group<? extends Sprite> |
CollisionDetector.group2
SpriteGroups we want to check |
| Methods in com.tabuto.j2dgf.collision with parameters of type Sprite | |
|---|---|
void |
CollisionBoundDetector.Bounce(Sprite s)
NOT YET IMPLEMENTED |
void |
CollisionBoundDetector.CollisionAction(Sprite s)
Calls the right method to change Sprite direction or position with CollisionBoundDetector.Reflection(Sprite) or CollisionBoundDetector.Through(Sprite) methods |
protected void |
CollisionBoundDetector.Reflection(Sprite s)
Change the Sprite angle to simulate an elastic collision with the boundary |
protected void |
CollisionBoundDetector.Through(Sprite s)
Change the Sprite position to simulate a pass through the boundary |
| Constructor parameters in com.tabuto.j2dgf.collision with type arguments of type Sprite | |
|---|---|
CollisionBoundDetector(Group<? extends Sprite> sp1,
java.awt.Dimension d)
CONSTRUCTOR CollisionBoundDetector constructor |
|
CollisionDetector(Group<? extends Sprite> pg1)
CONSTRUCTOR CollisionDetector(SpriteGroup pg1) The Constructor of CollisionDetector for collision between the same group elements. |
|
CollisionDetector(Group<? extends Sprite> pg1,
Group<? extends Sprite> pg2)
CONSTRUCTOR The Constructor of CollisionDetector for collision between elements of two groups. |
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CollisionDetector(Group<? extends Sprite> pg1,
Group<? extends Sprite> pg2)
CONSTRUCTOR The Constructor of CollisionDetector for collision between elements of two groups. |
|
TimeCollisionDetector(Group<? extends Sprite> pg1,
int time)
|
| Uses of Sprite in com.tabuto.jsimlife |
|---|
| Subclasses of Sprite in com.tabuto.jsimlife | |
|---|---|
class |
Seed
Class that represents some food. |
class |
Zatropod
|
class |
Zatropod.Limb
|
class |
Zetatron
Class Zetatron extends ZLife in order to add a neural network (using Brain class) to change its state. |
class |
Zlife
Class Zlife represent an elementary life's form able to reproduce itself
using a Dna to transmit its Genetic Code! |
class |
Zretador
Class Zretador represent an evolution of ZLife able to eat other Zlifes. |
| Fields in com.tabuto.jsimlife with type parameters of type Sprite | |
|---|---|
(package private) java.util.Vector<Sprite> |
Zatropod.spriteVector
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Kia Seltos AWD showcased at LA Auto show
by Akbar MerchantKia Seltos X-Line Urban and Seltos X-line Trail attack concepts also make debut.
Kia has taken the wraps off the North American-spec Seltos SUV at the ongoing Los Angeles Auto Show 2019. The model went on sale in markets like India and a few other ASEAN regions earlier this year. The new Kia SUV slots between the Kia Soul on the lower end and the Kia Sportage on the higher end of the Korean brand's North American line-up.
The left-hand-drive Kia Seltos looks more or less identical to the one sold in our market but comes with a different set of engines. Powering the Seltos for North America is a 2.0-litre petrol good for 146hp as well as a 1.6-litre turbo-petrol engine that churns out 176hp. The Seltos 2.0 comes with a CVT gearbox while the 1.6 version gets a 7-speed dual-clutch transmission. Higher variants also come with standard AWD. Kia will sell the Seltos SUV in North America in five variants. It also gets Kia’s UVO Connect system, a 10.25-inch screen, wireless charging and multiple USB ports.
The Seltos for the North American market comes with Kia’s Drive Wise safety package, which is already available in other Kia models like the full-size Telluride SUV and the Stinger sport sedan. This package includes features like blind spot monitoring, blind spot collision avoidance, driver attention warning, lane keep assist, automatic emergency braking, lane departure warning, highway follow assist, rear occupant alert, safe exit assist and adaptive cruise control.
Apart from the production-spec Seltos, the company also showcased the Seltos X-line Trail Attack concept and the Seltos X-line Urban concept at the Los Angeles Auto Show. Both concepts are powered by Kia’s 1.6-litre turbo-petrol engine.
The Seltos X-line Trail Attack concept (pictured) sits on a custom suspension setup that gives it a 2-inch lift and around 235mm of ground clearance. The concept is based on Seltos AWD and is also shod with a center differential lock. Additionally, it gets 17-inch custom alloy wheels, a winch at the back, a custom roof rack, and additional Hella auxiliary lights on the front bumper and on the roof.
The Seltos X-Line Urban concept gets 17-inch wheels with gold finish, a similar 2-inch lift with AWD, lesser number of auxiliary lights, a hood scoop and a roof rack. It however gets the same interior as the production spec SUV.
Closer to home, the Seltos made its debut earlier this year and is available in eighteen variants and multiple engine-gearbox options. The company has now begun work on the Carnival MPV as well as an all-new compact SUV for India. Both upcoming Kia models will hit the showrooms next year.
Also see:
Los Angeles Auto Show 2019 image gallery
Maruti, Hyundai, Kia top sales charts in October 2019
India-bound Kia compact SUV takes shape
Kia Seltos
Rs 10.87 lakh * on road price (New Delhi)


--- layout: default title: Calendar of Events permalink: /calendar/ scripts: - //www.google.com/jsapi - DOMAIN/static/js/calendar.min.js description: The Chattizen calendar includes information about upcoming public meetings in Hamilton County. ---


Relic data
Relic:Foundry
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This website uses storage objects (HTML5 web storage), that are similar in function to cookies, to store user settings and data that is essential to the applications' functions. Personal data is not stored.


{% extends "layout.html" %} {% block content %}
Enter the name of a Wikipedia page (e.g 'Data science', 'Ice cream', 'France') to get a visualisation of the most common words in the article.
NOTE: Some shorter words may fail to match correctly. In this case, try using an additional word to specify (e.g. 'cake food', 'cat animal')
Processing: {{ title }}...
Please wait - this may take a few seconds.
{% endif %} {% endblock content %}


Quellcode für qiskit.backends.local.localprovider
# -*- coding: utf-8 -*-
# Copyright 2018, IBM.
#
# This source code is licensed under the Apache License, Version 2.0 found in
# the LICENSE.txt file in the root directory of this source tree.
# pylint: disable=invalid-name, bad-continuation
"""Provider for local backends."""
import logging
from qiskit._qiskiterror import QISKitError
from qiskit.backends import BaseProvider
from .qasm_simulator_cpp import CliffordSimulatorCpp, QasmSimulatorCpp
from .qasm_simulator_py import QasmSimulatorPy
from .statevector_simulator_cpp import StatevectorSimulatorCpp
from .statevector_simulator_py import StatevectorSimulatorPy
from .unitary_simulator_py import UnitarySimulatorPy
logger = logging.getLogger(__name__)
SDK_STANDARD_BACKENDS = [
QasmSimulatorCpp,
QasmSimulatorPy,
StatevectorSimulatorCpp,
StatevectorSimulatorPy,
UnitarySimulatorPy,
CliffordSimulatorCpp,
]
[Doku]class LocalProvider(BaseProvider):
"""Provider for local backends."""
def __init__(self, *args, **kwargs):
super().__init__(args, kwargs)
# Populate the list of local backends.
self.backends = self._verify_local_backends()
[Doku] def get_backend(self, name):
return self.backends[name]
[Doku] def available_backends(self):
"""Get a list of available backends from the Local provider.
Returns:
list[BaseBackend]: a list of backend instances available
from the Local provider.
"""
# pylint: disable=arguments-differ
return list(self.backends.values())
[Doku] def grouped_backend_names(self):
return {
'local_qasm_simulator': ['local_qasm_simulator_cpp',
'local_qasm_simulator_py',
'local_clifford_simulator_cpp'],
'local_statevector_simulator': ['local_statevector_simulator_cpp',
'local_statevector_simulator_py'],
'local_unitary_simulator': ['local_unitary_simulator_cpp',
'local_unitary_simulator_py']
# TODO: restore after clifford simulator release
# 'local_clifford_simulator': ['local_clifford_simulator_cpp']
}
[Doku] def deprecated_backend_names(self):
return {
'local_qiskit_simulator': 'local_qasm_simulator_cpp',
'wood_simulator': 'local_qasm_simulator_cpp',
}
[Doku] def aliased_backend_names(self):
return {
}
@classmethod
def _verify_local_backends(cls):
"""
Return the local backends in `SDK_STANDARD_BACKENDS` that are
effectively available (as some of them might depend on the presence
of an optional dependency or on the existence of a binary).
Returns:
dict[str:BaseBackend]: a dict of the local backends instances for
the backends that could be instantiated, keyed by backend name.
"""
ret = {}
for backend_cls in SDK_STANDARD_BACKENDS:
try:
backend_instance = cls._get_backend_instance(backend_cls)
backend_name = backend_instance.configuration['name']
ret[backend_name] = backend_instance
except QISKitError as e:
# Ignore backends that could not be initialized.
logger.info('local backend %s is not available: %s',
backend_cls, str(e))
return ret
@classmethod
def _get_backend_instance(cls, backend_cls):
"""
Return an instance of a backend from its class.
Args:
backend_cls (class): Backend class.
Returns:
BaseBackend: a backend instance.
Raises:
QISKitError: if the backend could not be instantiated or does not
provide a valid configuration containing a name.
"""
# Verify that the backend can be instantiated.
try:
backend_instance = backend_cls()
except Exception as err:
raise QISKitError('Backend %s could not be instantiated: %s' %
(cls, err))
# Verify that the instance has a minimal valid configuration.
try:
_ = backend_instance.configuration['name']
except (LookupError, TypeError):
raise QISKitError('Backend %s has an invalid configuration')
return backend_instance


Dashboard
{% for sensor in temp_sensors %}
{% endfor %}
{% for sensor in humidity_sensors %}
{% endfor %}
{{ sensor['name'] }}
unknown version
---
---
{{ sensor['name'] }}
unknown version
---
---


Strictly fans distracted by Tess Daly's strap as she is compared to EastEnders character
'I have been pretending that Tess' strap doesn't bother me but it does it really does'
by Rose Hill, https://www.mirror.co.uk/authors/rose-hill/Tess Daly looked utterly stunning tonight - but Strictly viewers were a little distracted by an element of her outfit.
Wearing a silver wrap dress, she hosted the show tonight alongside co-star Claudia Winkleman.
But fans kept getting drawn to one of the straps of her dress, which had slid down her shoulder.
Viewers flocked to Twitter in frustration. and compared her to EastEnders Karen Taylor, who notoriously has one strap hanging off a shoulder.
One tweeted: "Can't cope with the strap situation #StrictlyComeDancing2019 #strictlyblackpool #strictly."
While another commented: "tess daly giving karen taylor a run for her money #Strictly."
A third remarked: "I have been pretending that Tess's strap doesn't bother me but it does it really does #scd #strictly."
"Tess. Please do us all a favour, I know this isn’t a first world problem but.. PLEASE PUT YOUR FECKIN’ STRAP UP!! #Strictly #StrictlyComeDancing #StrictlyComeDancing2019 #SCD," another wrote.
Tonight, the remaining seven couples took to the floor to perform at the famous Blackpool Tower Ballroom.
This year's celebs packed up their fake tan, glitter and dancing shoes to head to the home of ballroom.
The grand final is now in sight, so the celebs will know what's at stake as they do their best to impress all of the judges.
Tonight's dances included a Beyonce-themed Paso to a Salsa to Uptown Funk.
Fans will have to wait until tomorrow to discover the remaining celebs' fate, as well as watch a huge Westlife performance.
Unfortunately, BBC presenter Mike Bushell missed out on Blackpool as he became the latest celeb to leave last weekend.
His partner Katya Jones told him after they were voted out: "Honestly I’m so proud of him and I think after even this dance which I think was your best dance you can leave with your head held up honestly; and in my eyes you’re the winner. The only thing he has lost is weight.
"He came in every single day giving his heart, soul, everything, 200% no matter what after every single dance off and thank you so much. I’m so sorry I couldn’t take to Blackpool."
*Strictly results air tomorrow at 7.15pm on BBC One


--- title: shapeFactor sidebar: function_reference_sidebar permalink: grain2d.shapeFactor.html folder: function_reference toc: false ---
calculates the shapefactor of the grain-polygon, without Holes
define as
\[ F = \frac{P}{EP} \],
where \(P\) is the perimeter and \(EP\) is the equivalent perimeter.
| p | grain2d |
| F | shapefactor |
polygon.aspectRatio polygon.equivalentPerimeter polygon.perimeter


Programmer's Notepad 2.3
Download
v2.3 (2.4MB)
Download Portable
>>What's New?
<< Programmer's Notepad Home Page


{% comment %} Yeah, great, Django doesn't provide any blocks. Guess we'll just copy paste everything shall we? This exists because using a table/tbody and jquery-ui sortables are grim in various ways. {% endcomment %} {% load i18n admin_static %} {% if result_hidden_fields %}


Recipe courtesy of Alton Brown.
In a large bowl place the scooped avocado pulp and lime juice, toss to coat. Drain, and reserve the lime juice, after all of the avocados have been coated. Using a potato masher add the salt, cumin, and cayenne and mash. Then, fold in the onions, jalapeno, tomatoes, cilantro, and garlic. Add 1 tablespoon of the reserved lime juice. Let sit at room temperature for 1 hour and then serve.


Frequently Asked Questions¶
Author: Mark Saroufim
At a high level, the PyTorch 2.0 stack consists of a graph capture from Python code using dynamo and a backend compiler. In this example the backend compiler consists of backward graph tracing using AOTAutograd and graph lowering using TorchInductor. There are of course many more compilers available here but for this document we will focus on inductor as a motivating example.
Torchdynamo supports training, using AotAutograd to capture backwards:
the
.forward()
graph andoptimizer.step()
is captured by torchdynamo’s python evalframe frontendfor each segment of
.forward()
that torchdynamo captures, it uses AotAutograd to generate a backward graph segmenteach pair of forward, backward graph are (optionally) min-cut partitioned to save the minimal state between forward/backward
the forward, backward pairs are wrapped in autograd.function modules 5. usercode calling
.backward()
still triggers eager’s autograd engine, which runs each ‘compiled backward’ graph as if it were one op, also running any non-compiled eager ops’ .backward() functions
Do you support Distributed code?¶
DDP has been tested and works, support for other distributed training libraries is under discussion.
The main reason why Distributed code is challenging with dynamo is because AOTAutograd unrolls both the forward and backward pass and provides 2 graphs for backends to optimize. This is a problem for distributed code because we’d like to ideally overlap communication operations with computations. Eager pytorch accomplishes this in different ways for DDP/FSDP- using autograd hooks, module hooks, and modifications/mutations of module states. In a naive application of dynamo, hooks that should run directly after an operation during backwards may be delayed until after the entire compiled region of backwards ops, due to how AOTAutograd compiled functions interact with dispatcher hooks.
The basic strategy for optimizing DDP with Dynamo is outlined in distributed.py where the main idea will be to graph break on DDP bucket boundaries.
When each node in DDP needs to synchronize its weights with the other nodes it organizes its gradients and parameters into buckets which reduces communication times and allows a node to broadcast a fraction of its gradients to other waiting nodes.
Graph breaks in distributed code mean you can expect dynamo and its backends to optimize the compute overhead of a distributed program but not its communication overhead. Graph-breaks may interfere with compilation speedups, if the reduced graph-size robs the compiler of fusion opportunities. However, there are diminishing returns with increasing graph size since most of the current compute optimizations are local fusions. So in practice this approach may be sufficient.
Do I still need to export whole graphs?¶
For the vast majority of models you probably don’t and you can use
torch._dynamo()
optimize as is but there are a few situations where
full graphs are necessary and you can can ensure a full graph by simply
running torch.dynamo(..., nopython=True)
* Large scale training
runs, think $250K+ that require pipeline parallelism and other advanced
sharding strategies * Inference optimizers like
TensorRT or
AITemplate that rely
on fusing much more aggressively than training optimizers * Mobile training or
inference.
Future work will include tracing communication operations into graphs, coordinating these operations with compute optimizations, and optimizing the communication operations.
Why is my code crashing?¶
If your code ran just fine without dynamo and started to crash with it enabled then the most important first step is figuring out which part of the stack your failure occurred in so try running things in the below order and only try the next step if the previous step succeeded.
torch.compile(..., backend="eager")
which only runs torchdynamo forward graph capture and then runs the captured graph with PyTorch. If this fails then there’s an issue with TorchDynamo.torch.compile(..., backend="aot_eager")
which runs torchdynamo to capture a forward graph, and then AOTAutograd to trace the backward graph without any additional backend compiler steps. PyTorch eager will then be used to run the forward and backward graphs. If this fails then there’s an issue with AOTAutograd.torch.compile(..., backend="inductor")
which runs torchdynamo to capture a forward graph, and then AOTAutograd to trace the backward graph with the TorchInductor compiler. If this fails then there’s an issue with TorchInductor
TorchDynamo Errors¶
If the error that is generated occurs with the "eager"
backend, then
torchdynamo is the most likely source of the error.
To debug these issues we recommend setting
torch._dynamo.config.verbose=True
to get a full stack trace to both
the error in torchdynamo and the user code. In addition to this flag,
you can also set the log_level
of torchdynamo through
torch._dynamo.config.log_level
. The available levels are the
following: - logging.DEBUG
: Print every instruction that is
encountered in addition to all below log levels - logging.INFO
:
Print each function that is compiled (original and modified bytecode)
and the graph that is captured in addition to all below log levels -
logging.WARNING
(default): Print graph breaks in addition to all
below log levels - logging.ERROR
: Print errors only
If a model is sufficiently large, the logs can become overwhelming. If an error occurs deep within a model’s python code, it can be useful to execute only the frame in which the error occurs to enable easier debugging. There are 2 tools available to enable this:
env TORCHDYNAMO_DEBUG_FUNCTION=<desired_function_name>
will only run TorchDynamo on functions with that name.env torch._dynamo.config.replay_record_enabled = True
) which dumps an execution record when an error is encountered. This record can then be replayed to run only the frame where an error occurred.
TorchInductor Errors¶
With TorchInductor as the chosen backend, AOTAutograd is used to generate the backward graph from the forward graph captured by torchdynamo. It’s important to note that errors can occur during this tracing and also while TorchInductor lowers the forward and backward graphs to GPU code or C++.
A model can often consist of hundreds or thousands of FX nodes, so narrowing the exact nodes where this problem occurred can be very difficult which is why we highly recommend you use our minifier to create tiny reproducible examples of failures you’re seeing. We can minify errors that occur either at the AOTAutograd layer or Inductor layer which you should try in the following order.
env TORCHDYNAMO_REPRO_AFTER="aot" python your_model.py
env TORCHDYNAMO_REPRO_AFTER="dynamo" python your_model.py
Minifying your error is the quickest path to getting it fixed.
The minifier will actually create a repro.py
for you at the location
set by env TORCHDYNAMO_REPRO_DIR
so make you have right access to
that directory. You can then run python repro.py
and confirm that
you are getting the same error.
Note
For other compilers such as nvfuser, the process is similar but
instead you would leverage env TORCHDYNAMO_REPRO_AFTER="dynamo" python your_model.py
.
Why is compilation slow?¶
Dynamo Compilation¶
TorchDynamo has a builtin stats function for collecting and displaying
the time spent in each compilation phase. These stats can be accessed by
calling torch._dynamo.utils.compile_times()
after executing
torch._dynamo
. By default, this returns a string representation of
the compile times spent in each TorchDynamo function by name.
Inductor Compilation¶
TorchInductor has a builtin stats and trace function for displaying time
spent in each compilation phase, output code, output graph visualization
and IR dump. env TORCH_COMPILE_DEBUG=1 python repro.py
. This is a
debugging tool designed to make it easier to debug/understand the
internals of TorchInductor with an output that will look something like
this
Each file in that debug trace can be enabled/disabled via
torch._inductor.config.trace.*
. The profile and the diagram are both
disabled by default since they are expensive to generate. See the
example debug directory
output
for more examples.
Excessive Recompilation¶
When TorchDynamo compiles a function (or part of one), it makes certain
assumptions about locals and globals in order to allow compiler
optimizations, and expresses these assumptions as guards that check
particular values at runtime. If any of these guards fail, Dynamo will
recompile that function (or part) up to
torch._dynamo.config.cache_size_limit
times. If your program is
hitting the cache limit, you will first need to determine which guard is
failing and what part of your program is triggering it.
The recompilation profiler automates the process of setting TorchDynamo’s cache limit to 1 and running your program under an observation-only ‘compiler’ that records the causes of any guard failures. You should be sure to run your program for at least as long (as many iterations) as you were running when you ran into trouble, and the profiler will accumulate statistics over this duration.
from torch._dynamo.utils import CompileProfiler
prof = CompileProfiler()
def my_model():
...
profiler_model = torch.compile(my_model, backend=prof)
profiler_model()
print(prof.report())
Many of the reasons for graph breaks and excessive recompilation will be fixed with upcoming support for tracing dynamic tensor shapes, more careful choices for guards and better tuned heuristics.
Why are you recompiling in production?¶
In some cases, you may not want unexpected compiles after a program has warmed up. For example, if you are serving production traffic in a latency critical application. For this, TorchDynamo provides an alternate mode where prior compiled graphs are used, but no new ones are generated:
frozen_toy_example = dynamo.run(toy_example)
frozen_toy_example(torch.randn(10), torch.randn(10))
How are you speeding up my code?¶
There are 3 major ways to accelerate PyTorch code:
Kernel fusion via vertical fusions which fuse sequential operations to avoid excessive read/writes. For example, fuse 2 subsequent cosines means you can can do 1 read 1 write instead 2 reads 2 writes 2. Horizontal fusion: the simplest example being batching where a single matrix is multiplied with a batch of examples but the more general scenario is a grouped GEMM where a group of matrix multiplications are scheduled together
Out of order execution: A general optimization for compilers, by looking ahead at the exact data dependencies within a graph we can decide on the most opportune time to execute a node and which buffers can be reused
Automatic work placement: Similar of the out of order execution point, but by matching nodes of a graph to resources like physical hardware or memory we can design an appropriate schedule
The above are general principles for accelerating PyTorch code but different backends will each make different tradeoffs on what to optimize. For example Inductor first takes care of fusing whatever it can and only then generates Triton kernels. It can also
Triton in addition offers speedups because of automatic memory coalescing, memory management and scheduling within each Streaming Multiprocessor and has been designed to handle tiled computations.
However, regardless of the backend you use it’s best to use a benchmark and see approach so try out the PyTorch profiler, visually inspect the generated kernels and try to see what’s going on for yourself.
Why am I not seeing speedups?¶
Graph Breaks¶
The main reason you won’t see the speedups you’d like to by using dynamo is excessive graph breaks. So what’s a graph break?
Given a program like:
def some_fun(x):
...
torch.compile(some_fun)(x)
...
Torchdynamo will attempt to compile all of the torch/tensor operations
within some_fun()
into a single FX graph, but it may fail to capture
everything into one graph.
Some graph break reasons are insurmountable to TorchDynamo like calling into a C extension other than torch is invisible to torchdynamo, and could do arbitrary things without TorchDynamo being able to introduce necessary guards to ensure that the compiled program would be safe to reuse.
To maximize performance, it’s important to have as few graph breaks as possible.
Identifying the cause of a graph break¶
To identify all graph breaks in a program and the associated reasons for
the breaks, torch._dynamo.explain
can be used. This tool runs
TorchDynamo on the supplied function and aggregates the graph breaks
that are encountered. Here is an example usage:
import torch
import torch._dynamo as dynamo
def toy_example(a, b):
x = a / (torch.abs(a) + 1)
print("woo")
if b.sum() < 0:
b = b * -1
return x * b
explanation, out_guards, graphs, ops_per_graph = dynamo.explain(toy_example, torch.randn(10), torch.randn(10))
print(explanation)
"""
Dynamo produced 3 graphs, with 2 graph break and 6 ops.
Break reasons:
1. call_function BuiltinVariable(print) [ConstantVariable(str)] {}
File "t2.py", line 16, in toy_example
print("woo")
2. generic_jump
File "t2.py", line 17, in toy_example
if b.sum() < 0:
"""
To throw an error on the first graph break encountered you can use
disable python fallback by using nopython=True
, this should be
familiar if you’ve worked with export based compilers.
def toy_example(a, b):
...
torch.compile(toy_example, fullgraph=True, backend=<compiler>)
Why didn’t my code recompile when I changed it?¶
If you went ahead and enabled dynamic shapes via
env TORCHDYNAMO_DYNAMIC_SHAPES=1 python model.py
then your code
won’t recompile on shape changes. We’ve added support for dynamic shapes
which avoids recompilations in the case when shapes vary by less than a
factor of 2. This is especially useful in scenarios like varying image
sizes in CV or variable sequence length in NLP. In inference scenarios
it’s often not possible to know what a batch size will be beforehand
because you take what you can get from different client apps.
In general, TorchDynamo tries very hard not to recompile things unnecessarily so if for example torchdynamo finds 3 graphs and your change only modified one graph then only that graph will recompile. So another tip to avoid potentially slow compilation times is to warmup a model by compiling it once after which subsequent compilations will be much faster. Cold start compile times is still a metric we track visibly.
Why am I getting incorrect results?¶
Accuracy issues can also be minified if you set the environment variable
TORCHDYNAMO_REPRO_LEVEL=4
, it operates with a similar git bisect
model and a full repro might be something like
TORCHDYNAMO_REPRO_AFTER="aot" TORCHDYNAMO_REPRO_LEVEL=4
the reason
we need this is downstream compilers will codegen code whether it’s
Triton code or the C++ backend, the numerics from those downstream
compilers can be different in subtle ways yet have dramatic impact on
your training stability. So the accuracy debugger is very useful for us
to detect bugs in our codegen or with a backend compiler.
If you’d like to ensure that random number generation is the same across both torch
and triton then you can enable torch._inductor.config.fallback_random = True
Why am I getting OOMs?¶
Dynamo is still an alpha product so there’s a few sources of OOMs and if
you’re seeing an OOM try disabling the following configurations in this
order and then open an issue on GitHub so we can solve the root problem
1. If you’re using dynamic shapes try disabling them, we’ve disabled
them by default: env TORCHDYNAMO_DYNAMIC_SHAPES=0 python model.py
2.
CUDA graphs with Triton are enabled by default in inductor but removing
them may alleviate some OOM issues: torch._inductor.config.triton.cudagraphs = False
.


JGProgressHUDFadeZoomAnimation Class Reference
| Inherits from | JGProgressHUDAnimation : NSObject |
|---|---|
| Declared in | JGProgressHUDFadeZoomAnimation.h JGProgressHUDFadeZoomAnimation.m |
Overview
An animation that fades in the HUD and expands the HUD from scale @c (0, 0) to a customizable scale, and finally to scale @c (1, 1), creating a bouncing effect.
Other Methods
– show
The @c progressHUD is hidden from screen with @c alpha = 1 and @c hidden = @c YES. Ideally, you should prepare the HUD for presentation, then set @c hidden to @c NO on the @c progressHUD and then perform the animation. @post Call @c animationFinished.
- (void)show
Discussion
The @c progressHUD is hidden from screen with @c alpha = 1 and @c hidden = @c YES. Ideally, you should prepare the HUD for presentation, then set @c hidden to @c NO on the @c progressHUD and then perform the animation. @post Call @c animationFinished.
Declared In
JGProgressHUDAnimation.h
– hide
The @c progressHUD wis visible on screen with @c alpha = 1 and @c hidden = @c NO. You should only perform the animation in this method, the @c progressHUD itself will take care of hiding itself and removing itself from superview. @post Call @c animationFinished.
- (void)hide
Discussion
The @c progressHUD wis visible on screen with @c alpha = 1 and @c hidden = @c NO. You should only perform the animation in this method, the @c progressHUD itself will take care of hiding itself and removing itself from superview. @post Call @c animationFinished.
Declared In
JGProgressHUDAnimation.h
Other Methods
shrinkAnimationDuaration
Duration of the animation from or to the shrinked state.
@property (nonatomic, assign) NSTimeInterval shrinkAnimationDuaration
Discussion
Duration of the animation from or to the shrinked state.
@b Default: 0.2.
Declared In
JGProgressHUDFadeZoomAnimation.h
expandAnimationDuaration
Duration of the animation from or to the expanded state.
@property (nonatomic, assign) NSTimeInterval expandAnimationDuaration
Discussion
Duration of the animation from or to the expanded state.
@b Default: 0.1.
Declared In
JGProgressHUDFadeZoomAnimation.h
expandScale
The scale to apply to the HUD when expanding.
@property (nonatomic, assign) CGSize expandScale
Discussion
The scale to apply to the HUD when expanding.
@b Default: (1.1, 1.1).
Declared In
JGProgressHUDFadeZoomAnimation.h


Create Election
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View Voters
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Returns the current member in the input dimension.
The current member is evaluated in the context of query execution mechanics. Used in conjunction with iterative functions such as Filter, at every stage of iteration the member being operated upon is the current member.
Syntax
dimension.CurrentMember
CurrentMember ( dimension )
| Parameter | Description |
|---|---|
dimension |
A dimension specification. |
Notes
This function returns the child of an implied shared member instead of the member itself. To avoid this behavior when using CurrentMember in MDX formulas and calculated members, tag the parent with the "Never Share" property.
An implied share occurs when a parent has only one child, or only one child that consolidates. For more information, see "Understanding Shared Members" in the Oracle Essbase Database Administrator's Guide.
Example
The following query selects the quarters during which sales growth is 3% or more compared to the previous month.
SELECT Filter ( [Year].Children, -- outer loop Max ( Except ( [Year].CurrentMember.Children, -- current in outer loop { [Year].[Jan] } ), ( [Year].CurrentMember -- current in Max loop / [Year].CurrentMember.PrevMember) ) >= 1.03 ) ON axis(0) FROM Sample.Basic WHERE ([Measures].[Sales])
Returns the grid:
| Qtr2 | Qtr4 |
| 101679 | 98141 |


From:Hayslett Rod To:Geaccone Tracy ; Sommers Jeffrey E. Sent:2017-01-11T04:37:43.0000000Z Subject:FW: MESSAGE FROM MARK LINDSEY - 4TH Q 2001
Please take a look and get back to me by the first thing next week. Please copy Tracy on your response to this.... Let's be honest so that Stan and Rick can get the right feel about the issues remaining relative to the years earnings.
-----Original Message-----
From: Schwarzbach, Stephen
Sent: Wednesday, September 12, 2001 5:10 PM
To: Colwell, Wes; Stubblefield, Wade; Price, Brent A.; Sommers, Jeffrey E.; Hayslett, Rod; Dyson, Fernley; Castleman, Kent; Roper, Kerry
Cc: Lindsey, Mark E.
Subject: MESSAGE FROM MARK LINDSEY - 4TH Q 2001
As discussed in Rick Causey's staff meeting yesterday, please begin to review 4th quarter earnings for your business unit(s) and compile a list of any major hurdles, challenges, etc. (i.e. bonus accrual, "clean-up" items).
Furthermore, please assess any additional items that would be candidates for clean up, given the opportunity to expedite their resolution.
Meetings will be set up within the next week to discuss these items with you.
Thank you,
Mark Lindsey
***********
EDRM Enron Email Data Set has been produced in EML, PST and NSF format by ZL Technologies, Inc. This Data Set is licensed under a Creative Commons Attribution 3.0 United States License <http://creativecommons.org/licenses/by/3.0/us/> . To provide attribution, please cite to "ZL Technologies, Inc. (http://www.zlti.com)."
***********
California


Person Re-identification: Past, Present and Future[PDF][Baseline Code] Liang Zheng, Yi Yang, Alexander Hauptmann
ArXiv:1610.02984, 2016.
Dual-Path Convolutional Image-Text Embedding[PDF][Code] Zhedong Zheng, Liang Zheng, Michael Garrett, Yi Yang, Yi-Dong Shen
ArXiv:1711.05535, 2017.
Random Erasing Data Augmentation[PDF][Code] Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang
ArXiv:1708.04896, 2017.
Improving Person Re-identification by Attribute and Identity Learning[PDF][Attributes] Yutian Lin, Liang Zheng, Zhedong Zheng, Yu Wu, Yi Yang
ArXiv:1703.07220, 2017.
Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification[PDF][Code] Qingji Guan, Yaping Huang, Zhun Zhong, Zhedong Zheng, Liang Zheng, Yi Yang
ArXiv:1801.09927, 2018.
2018
Few-shot Object Detection with Model Communication[PDF][Code] Xuanyi Dong, Liang Zheng, Fan Ma, Yi Yang, Deyu Meng
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
SIFT Meets CNN: A Decade Survey of Instance Retrieval.[PDF][Bibtex] Liang Zheng, Yi Yang, Qi Tian
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 40(5): 1224-1244, 2018.
Generalizing A Person Retrieval Model Hetero- and Homogeneously[PDF][Code] Zhun Zhong, Liang Zheng, Shaozi Li, Yi Yang
ECCV, 2018.
Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)[PDF][Code] Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, Shengjin Wang
ECCV, 2018.
Macro-Micro Adversarial Network for Human Parsing[PDF][Code] Yawei Luo, Zhedong Zheng, Liang Zheng, Tao Guan, Junqing Yu, Yi Yang
ECCV, 2018.
Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization[PDF][Code coming soon]
Guoliang Kang, Liang Zheng, Yan Yan, Zikun Liu, Yi Yang
ECCV, 2018.
Unsupervised Person Re-identification: Clustering and Fine-tuning[PDF][Code] Hehe Fan, Liang Zheng, Chenggang Yan, Yi Yang
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2018.
Camera Style Adaptation for Person Re-identification[PDF][Code] Zhun Zhong, Liang Zheng, Zhedong Zheng, Shaozi Li, Yi Yang
CVPR, 2018.
Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification[PDF][Code] Weijian Deng, Liang Zheng, Guoliang Kang, Yi Yang, Qixiang Ye, and Jianbin Jiao
CVPR, 2018.
Twitter100k: A Real-world Dataset for Weakly Supervised Cross-Media Retrieval[PDF][Code] Yuting Hu, Liang Zheng, Yi Yang, Yongfeng Huang
IEEE Transactions on Multimedia (TMM), 20(4): 927-938, 2018.
2017
Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro.[PDF][Code][DukeMTMC-reID dataset] Zhedong Zheng, Liang Zheng, Yi Yang
ICCV, 2017.
SVDNet for Pedestrian Retrieval. [PDF][Code] Yifan Sun, Liang Zheng, Weijian Deng, Shengjin Wang
ICCV, 2017.
Dynamic Label Graph Matching for Unsupervised Video Re-Identification. [PDF][Code] Mang Ye, Andy J Ma, Liang Zheng, Jiawei Li, Pong C Yuen
ICCV, 2017.
Person Re-identification in the Wild[PDF][Dataset] Liang Zheng*, Hengheng Zhang*, Shaoyan Sun*, Manmohan Chandraker, Yi Yang, and Qi Tian (* equal contribution)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
Re-ranking Person Re-identification with k-reciprocal Encoding[PDF][Code] Zhun Zhong, Liang Zheng, Donglin Cao and Shaozi Li
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
A Discriminatively Learned CNN Embedding for Person Re-identification[PDF][Code] Zhedong Zheng, Liang Zheng, Yi Yang
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 14(1), 13, 2017
Part-based deep hashing for large-scale person re-identification[PDF][Code] Fuqing Zhu, Xiangwei Kong, Liang Zheng, Haiyan Fu, Qi Tian
IEEE Transactions on Image Processing 26 (10), 4806-4817, 2017
2016
MARS: A Video Benchmark for Large-Scale Person Re-identification[PDF][Dataset] Liang Zheng*, Zhi Bie*, Yifan Sun*, Jingdong Wang, Shengjin Wang, Chi Su, and Qi Tian (* equal contribution)
European Conference of Computer Vision (ECCV), 2016.
Accurate Image Search with Multi-Scale Contextual Evidences[PDF] Liang Zheng, Shengjin Wang, Jingdong Wang, and Qi Tian
International Journal of Computer Vision (IJCV), 120(1), 1-13, 2016.
Interactive: Inter-layer activeness propagation Lingxi Xie*, Liang Zheng*, Jingdong Wang, Alan Yuille, Qi Tian (* equal contribution)
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
2015
Scalable Person Re-identification: A Benchmark[PDF][Dataset] Liang Zheng*, Liyue Sheng*, Lu Tian*, Shengjin Wang, Jingdong Wang, and Qi Tian (* equal contribution)
IEEE International Conference on Computer Vision (ICCV), 2015.
Query-Adaptive Late Fusion for Image Search and Person Re-identification[PDF][Extended Abstract][Code] Liang Zheng, Shengjin Wang, Lu Tian, Fei He, Ziqiong Liu, and Qi Tian
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
Fast Image Retrieval: Query Pruning and Early Termination.[PDF] Liang Zheng, Shengjin Wang, Ziqiong Liu, and Qi Tian
IEEE Transactions on Multimedia (TMM), 17(5): 648-659, 2015.
2014
Packing and Padding: Coupled Multi-Index for Accurate Image Retrieval[PDF][Code][Baseline Project] Liang Zheng, Shengjin Wang, Ziqiong Liu, and Qi Tian
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1947-1954, 2014.
In case you cannot download the codes on OneDrive, we provide another link here [Code].
Bayes Merging of Multiple Vocabularies for Scalable Image Retrieval[PDF][Suppl.][Code][Baseline Project] Liang Zheng, Shengjin Wang, Wengang Zhou, and Qi Tian
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1963-1970, 2014.
In case you cannot download the codes on OneDrive, we provide another link here [Code].
Tensor Index for Large Scale Image Retrieval[PDF] Liang Zheng, Shengjin Wang, Peizhen Guo, Hanyue Liang, and Qi Tian
Multimedia Systems, 21(6): 569-579, 2015.
Coupled Binary Embedding for Large-scale Image Retrieval[PDF] Liang Zheng, Shengjin Wang, and Qi Tian
IEEE Transactions on Image Processing (TIP), 23(8): 3368-3380, 2014.
Lp-norm IDF for Scalable Image Retrieval[PDF] Liang Zheng, Shengjin Wang, and Qi Tian
Accepted in IEEE Transactions on Image Processing (TIP), 2014.
It is an extended version of our CVPR'13 paper.
2013
Lp-norm IDF for Large Scale Image Search[PDF] Liang Zheng, Shengjin Wang, Ziqiong Liu, and Qi Tian
IEEE Conference
on Computer Vision and Pattern Recognition (CVPR), pp. 1626-1633, 2013.
Visual Phraselet: Refining Spatial Constraints for Large Scale Image Search[PDF] Liang Zheng, Shengjin Wang
IEEE Signal
Processing Letters, 20(4): 391-394, 2013.


Table of Contents:
Custom Install Instructions
Step 1
Step 2
Step 3
Step 4
Step 5
Step 6
Optional Custom Install Instructions
Step 1
Custom Install Instructions:
A custom install should be used when integrating the Cut Scene Cam into a pre-existing project. The instructions in this section are mandatory
for a custom install, optional instructions are below. These instructions are for a new project created using the "Full" template in
T3D 3.10.0.
After you have fully finished the installation process, open up a new mission within that project and press "alt s" to open the Cut Scene Cam Editor.
Read the text and tooltips within the editor and you should have your camera up and running in no time.
If you need further assistance, check the Usage Instructions.
Step 1:
Backup all files that are going to be changed. They are:
source/gui/game/guiFadeinBitmapCtrl.h
source/gui/game/guiFadeinBitmapCtrl.cpp
source/T3D/pathCamera.h
source/T3D/pathCamera.cpp
scripts/server/scriptExec.cs
Step 2:
In the source folder, write over the stock files with the files that came with the CSC:
source/gui/game/guiFadeinBitmapCtrl.h
source/gui/game/guiFadeinBitmapCtrl.cpp
source/T3D/pathCamera.h
source/T3D/pathCamera.cpp
Step 3:
Step 4:
File- scripts/server/scriptExec.cs
After the line:
// Load turret support scripts
exec("./turret.cs");
Add:
exec("./CSC_userValues.cs");
Step 5:
In the folder: scripts/server/
Add the following files:
CSC_pathCamera.cs
CSC_pathManagement.cs
CSC_userValues.cs
Step 6:
Add the following editor files to the correct locations:
tools/worldEditor/gui/CSC_Editor.gui
tools/worldEditor/scripts/CSC_Editor.cs
tools/worldEditor/scripts/CSC_PathEditor.cs
Optional Custom Install Instructions:
These instructions are an optional part of a custom install. This will add the Cut Scene Cam Editor to the bottom of your "Edit" menu within the mission editor. If you're having problems
while doing a custom installation, try skipping this part. This step is not included in the quick install files.
Step 1:
File- tools/worldEditor/scripts/menus.ed.cs
Function- EditorGui::buildMenus()
After the line:
item[16] = "PostEffect Manager" TAB "" TAB "Canvas.pushDialog(PostFXManager);";
Add:
item[17] = "-";
item[18] = "Cut Scene Cam Editor" TAB "Alt S" TAB "toggleCSCEditor(1);";


Georgia needs access to your microphone before she can start listening to commands. Hit "Allow microphone access" to get started.


"People say nothing is impossible, But I do nothing everyday"
Tre was born in the thriving community of Los Angeles, California. As a child he played baseball and basketball but was never tall enough to take his talents to the next level. So like any other height challenged individual he got really into computer and console video games. For a minute electronics were his life and programming peaked his interest. As years progressed and relationships haulted progress, he is now back at it in full effect and hungry to learn.


| AttachmentDownloadServlet |
class AttachmentDownloadServlet : HttpServlet
Allows the node administrator to either download full attachment zips, or individual files within those zips. |
| Config |
class Config : ContextResolver<ObjectMapper>
Primary purpose is to install Kotlin extensions for Jackson ObjectMapper so data classes work and to organise serializers / deserializers for java.time.* classes as necessary. |
| DataUploadServlet |
class DataUploadServlet : HttpServlet
Accepts binary streams, finds the right AcceptsFileUpload implementor and hands the stream off to it. |
| ResponseFilter |
class ResponseFilter : ContainerResponseFilter
This adds headers needed for cross site scripting on API clients. |


×
PLAYER UNKNOWN BATTLE GROUND (PUBG)
RULES
- A team of maximum four members can participate.
- Only mobile users are permitted.
- Emulators are strictly prohibited.
- If any sort of malpractices is detected from any player, the entire team will be disqualified from the contest.
- Possible technical issues with PUBG, its servers and/or network may cause games to be rescheduled or canceled at the sole discretion of the organizers.
- Match will be restarted in the event if that more than four (4) or more players from different teams are kicked from the server before the start of the match, or two (2) or more players from the same team are kicked from the server.


Represents an in-memory audio buffer.
More...
#include <audio_buffer.hpp>
|
| | audio_buffer () |
| | Creates an empty audio_buffer. More...
|
| |
| | audio_buffer (const span< const uint8_t > &data, audio_buffer_format format, int smp_rate) |
| | Creates an audio_buffer object with the given parameters. More...
|
| |
| | audio_buffer (std::vector< uint8_t > &&data, audio_buffer_format format, int smp_rate) |
| | Creates an audio_buffer object with the given parameters, moving the data. More...
|
| |
| | audio_buffer (audio_stream_in &audio_stream) |
| | Creates an audio_buffer object with the data from the given stream. More...
|
| |
| | audio_buffer (audio_stream_in &&audio_stream) |
| | Creates an audio_buffer object with the data from the given stream. More...
|
| |
| const al::buffer_handle & | get_handle () const noexcept |
| | Gets the OpenAL buffer handle. More...
|
| |
| audio_buffer_format | get_format () const |
| | Gets the audio format of the buffer. More...
|
| |
| uint | get_channel_count () const |
| | Gets the number of channels of the buffer, based on its audio format. More...
|
| |
| uint | get_bytes_per_sample () const |
| | Gets the number of bytes per sample of the buffer, based on its audio format. More...
|
| |
| int | get_sample_rate () const |
| | Gets the number of samples per second. More...
|
| |
| uint | get_byte_count () const |
| | Gets the number of bytes in the buffer. More...
|
| |
| uint | get_sample_count () const |
| | Gets the number of samples in the buffer for a single channel. More...
|
| |
| void | set_data (const span< const uint8_t > &data, audio_buffer_format format, int smlRate) |
| | Sets the buffer data with the provided values. More...
|
| |
| void | set_data (std::vector< uint8_t > &&data, audio_buffer_format format, int smlRate) |
| | Sets the buffer data with the provided values, moving the data. More...
|
| |
| void | set_data (audio_stream_in &audio_stream) |
| | Sets the buffer data by reading the provided audio_stream_in) More...
|
| |
| void | set_data (audio_stream_in &&audio_stream) |
| | Sets the buffer data by reading the provided audio_stream_in) More...
|
| |
|
| non_copyable () noexcept |
| | default constructor
|
| |
|
virtual | ~non_copyable () |
| | Destructor.
|
| |
|
| non_copyable (const non_copyable &)=delete |
| | Deleted copy constructor.
|
| |
|
| non_copyable (non_copyable &&)=default |
| | Defaulted move constructor.
|
| |
|
non_copyable & | operator= (const non_copyable &)=delete |
| | Deleted copy assignment operator.
|
| |
|
non_copyable & | operator= (non_copyable &&)=default |
| | Defaulted move assignment operator.
|
| |
Represents an in-memory audio buffer.
It is not possible to play a sound with an audio_buffer object alone. It is necessary to create an audio_source object and assign a reference to an audio_buffer to it. Many audio_source objects can share the same audio_buffer objects, allowing to save resources.
An audio_buffer object loads the whole audio data into memory. For large audio data this might be expensive. In that case, it is suggested to use audio streams and a streaming_audio_source.
◆ audio_buffer() [1/5]
| hou::audio_buffer::audio_buffer |
( |
| ) |
|
Creates an empty audio_buffer.
The buffer is created with one single sample set to 0, mono16 format, and a frequency of 1 sample per second.
◆ audio_buffer() [2/5]
Creates an audio_buffer object with the given parameters.
- Parameters
-
| data | the data. |
| format | the audio format. |
| smp_rate | the sample rate. |
◆ audio_buffer() [3/5]
| hou::audio_buffer::audio_buffer |
( |
std::vector< uint8_t > && |
data, |
|
|
audio_buffer_format |
format, |
|
|
int |
smp_rate |
|
) |
| |
Creates an audio_buffer object with the given parameters, moving the data.
- Parameters
-
| data | the data. |
| format | the audio format. |
| smp_rate | the sample rate. |
◆ audio_buffer() [4/5]
Creates an audio_buffer object with the data from the given stream.
- Note
- this function will set the cursor position in audio_stream to the end of the stream.
- Parameters
-
◆ audio_buffer() [5/5]
Creates an audio_buffer object with the data from the given stream.
- Parameters
-
◆ get_byte_count()
| uint hou::audio_buffer::get_byte_count |
( |
| ) |
const |
Gets the number of bytes in the buffer.
- Returns
- the number of bytes in the channel.
◆ get_bytes_per_sample()
| uint hou::audio_buffer::get_bytes_per_sample |
( |
| ) |
const |
Gets the number of bytes per sample of the buffer, based on its audio format.
The number returned is the number of bytes per sample for a single channel.
- Returns
- 1 for 8-bit audio formats, 2 for 16-bit audio formats.
◆ get_channel_count()
| uint hou::audio_buffer::get_channel_count |
( |
| ) |
const |
Gets the number of channels of the buffer, based on its audio format.
- Returns
- 1 if the audio format is mono, 2 if the audio format is stereo.
◆ get_format()
Gets the audio format of the buffer.
- Returns
- the audio format of the buffer.
◆ get_handle()
| const al::buffer_handle& hou::audio_buffer::get_handle |
( |
| ) |
const |
|
noexcept |
Gets the OpenAL buffer handle.
- Returns
- the OpenAL buffer handle.
◆ get_sample_count()
| uint hou::audio_buffer::get_sample_count |
( |
| ) |
const |
Gets the number of samples in the buffer for a single channel.
- Returns
- the number of samples in the buffer for a single channel.
◆ get_sample_rate()
| int hou::audio_buffer::get_sample_rate |
( |
| ) |
const |
Gets the number of samples per second.
- Returns
- the sample rate in samples per second.
◆ set_data() [1/4]
Sets the buffer data with the provided values.
- Parameters
-
| data | the data. |
| format | the audio format. |
| smlRate | the sample rate. |
◆ set_data() [2/4]
| void hou::audio_buffer::set_data |
( |
std::vector< uint8_t > && |
data, |
|
|
audio_buffer_format |
format, |
|
|
int |
smlRate |
|
) |
| |
Sets the buffer data with the provided values, moving the data.
- Parameters
-
| data | the data. |
| format | the audio format. |
| smlRate | the sample rate. |
◆ set_data() [3/4]
Sets the buffer data by reading the provided audio_stream_in)
- Note
- this function will set the cursor position in audio_stream to the end of the stream.
- Parameters
-
◆ set_data() [4/4]
The documentation for this class was generated from the following file:


Why Is Training Set Error Zero In SVM and Random Forest?
QUESTIONS
Q: Why if a model like SVM or Random Forest is trained and evaluated for training error, you will get zero error? (And on the other hand, when a model like a Gaussian Naive Bayes classifier is used instead, the training error is non-zero in general.)
**A: SVM and decision-tree based variants are instance based classifiers, and thus can fit with the data perfectly. a Guassian Naives Bayes classifier is not.**
More explanation
For the case of SVM, an SVM model is actually a representation of the examples in space where a margin is picked to separate the examples with a gap as wide as possible. For Random Forest (a decision tree based classifier) model, the classifying rules are all derived exactly from the examples and thus has the capability to classify perfectly to the examples given.


Shapefiles - Metadata
Credits: Created with ArcGIS Online and the ESRI Javascript API. User Interface by JQuery, JQueryUI, JQuery Selectbox Plugin. Charts created by D3.js. Colorschemes courtesy of Colorbrewer. Print Services created with Phantom.js.


Chris Heathwood
18/10/2018
It's open source
Other open source stuff runs on it
It's lightweight
It runs on almost anything
It's free
sftp server for DXC
Apache Nifi
Neo4j
Couchbase
Mongo
Rabbit
Everything?
Multi User, Multitasking Operating System
Dumb terminals
Built around the "Unix philosophy"
Linus Torvalds
Runs on x86 (originally 386)
Ported a lot of programs from unix
All the same
One of the main things behind docker
All the same core
Focus on different areas
Different levels of support
Focused on size
Born out of linux distro for low powered hardware
Used a lot for docker
Most popular
Based on debian
Supported by canonical
A lot of businesses use this
Based down stream from redhat
Fairly easy to move to redhat at a later date
Different distros have different package managers
CentOS uses yum
yum update -y
yum instal -y xxx
Gnome
KDE
A shell is a program that takes commands and gives them to the operating system to be executed.
bash
tcsh/csh
ksh
zsh
fish
Has it's own scripting language for shell scripts
.bashrc
pwd
ls -al
mv
cp
cat
grep
sed
awk
more/less
tail -f
names.txtbob
fred
dave
cat names.txt | tail -n 1 | sed 's/.*/\u&/'
.mds file/build/source/target/artifacts/hadoop-3.1.1.tar.gz:
MD5 = 0B 6A B0 6B 59 AE 75 F4 33 DE 38 77 83 F1 90 11
/build/source/target/artifacts/hadoop-3.1.1.tar.gz:
SHA256 = F837FE26 0587F716 29AAD1F4 FB671927 4E948111 DC96FFC5 A8E26F27 DEAC5602
curl $MIRROR/$HADOOP_BINARY_URL.mds | grep "^SHA256" | sed 's/ //g' | sed 's/SHA256=//'
Available everywhere
Has two modes view and edit
In view mode "gg" takes you to the start of a file
In view mode "GG" takes you to the end of a file
"/search" takes you to the search (this is a regex)
keep using "/" to keep searching
You can go in to edit mode in different ways
"i" insert here, "A" insert at the end of a line
"u" undoes a change
":q!"


Methods
Class Public methods
find_by_beacon_number(phone_number)
Link
Source: show
# File app/models/data_center.rb, line 10 def self.find_by_beacon_number(phone_number) settings = Setting.where(key: 'beacon_number', value: phone_number) if settings.size == 1 return settings.first.data_center else raise StandardError.new("Data Center: not able to determine data center by beacon number. Number of data centers = #{settings.size}.") end return nil end
Instance Public methods


PTC-Sim
Home
{% block content %} {% endblock %}
©2018 - Dustin Fast -
http://github.com/dustinfast/PTC-Sim


Hello!
This is a test email sent from AS3Mailer.
For more information check out https://github.com/Matan/AS3Mailer.
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Does Flash? | AS3 Blog In my opinion, YES, Flash Does. What do you think?


{% extends parent_template|default:"patients/base_enrollments.html" %} {% block title %} {{ block.super }} | Enrollment {% endblock %} {% block page_heading %} Enrollment Details {% endblock %} {% block page_subheading %} {% endblock %} {% block page_breadcrumb %}
{% if enrollment.comment %} {{ enrollment.comment }} {% else %} There currently isn't any comment about this enrollment {% endif %}
{% if enrollment.program.description %} {{ enrollment.program.description }} {% else %} This program currently does not have a description. {% endif %}


Use this command to search the file. This brings up a modeless dialog box that you can leave on the screen and use whenever necessary. It is sometimes quicker and simpler to use the Find Tool on the Edit Bar.
The bytes to search for can either be entered in hex or as a string (ASCII, Unicode or EBCDIC). For more information see the Basic Find page of the Find dialog.
Shortcuts
Keys: Ctrl+F
Toolbar:


OpenSCAD
OpenSCAD is a software for creating solid 3D CAD models. It is free software and available for Linux/UNIX, Windows and Mac OS X. Unlike most free software for creating 3D models (such as Blender) it does not focus on the artistic aspects of 3D modelling but instead on the CAD aspects. Thus it might be the application you are looking for when you are planning to create 3D models of machine parts but pretty sure is not what you are looking for when you are more interested in creating computer-animated movies.
OpenSCAD is not an interactive modeller. Instead it is something like a 3D-compiler that reads in a script file that describes the object and renders the 3D model from this script file. This gives you (the designer) full control over the modelling process and enables you to easily change any step in the modelling process or make designs that are defined by configurable parameters.
OpenSCADpm
OpenSCADpm is a package manager for OpenSCAD, akin to Node Package Manager (NPM) or Ruby Gems, and hence allows developers to more easily share and install modules. In sum, OpenSCADpm manages packages and their associated dependencies.
The package manager currently constitutes a command line tool and a website. The command line tool is utilized for the installation and managing of modules by allowing users to use terminal commands. The website serves as a way for packages to be browsed and explained with a high level description.


404 Page Not Found
The DCMS web page or document you are looking for has not been found.
We have recently redesigned and restructured our website, and the information you are looking for may have been moved or deleted.
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- If you are looking for a specific piece of information, you may find it easier to use the search engine or our Site Map.
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MIGHTY APHRODITE A film review by Christopher Null Copyright 1995 Christopher Null
I guess it's true that you can't win 'em all. One of my favorite writers and directors, Woody Allen, just released his 25th film as director. Unfortunately, his recent streak of wildly funny films (including HUSBANDS AND WIVES and BULLETS OVER BROADWAY), his hit a speed bump with the unfulfilling MIGHTY APRODITE.
 Allen's character, Lenny, is a sports writer this time. He's married to Amanda (Helena Bonham Carter), with whom he rather suddenly adopts a child. When marriage with Amanda starts to fizzle and their new son Max begins to shine, Lenny begins to wonder if Max's real mother might just be the girl for him. Come to find out, mom is really prostitute/porn actress Linda (Mira Sorvino), and Allen's paranoia and angst really begin to shine.
As you can imagine, this scenario makes for some perfect comic opportunities. Unfortunately, the time needed to set this up is extreme, as is the time needed to resolve everything at the end. The result is a few good bits of comedy right in the middle of the movie, when Lenny is first getting to know Linda. The rest of it, about Amanda's wandering eye and Lenny's attempt to set Linda up with a boxer (Michael Rapaport), is simply limp.
The worst of all is Allen's decision to use an inexplicable "chorus," in the style of an old Greek tragedy, in lieu of his own narration. So between scenes of downtown Manhattan, we switch to an ancient stone stage, where 20 guys in period costume wax poetic about Lenny's dilemma. It's cute, but it never really works. Allen is usually skilled at pulling off this kind of out-of-place addition (as in ALICE, THE PURPLE ROSE OF CAIRO, and others), but this time it's just too much and too silly.
Mira Sorvino's Linda is the one to watch, pulling off the "ditzy blonde" more memorably than anyone else has in recent years. Allen's acting is good, but he seems a bit tired, and most of the additional supporting cast is solid.  It's almost painful to listen to her.
The real disappointment here is that MIGHTY APRHODITE lacks the rich subtlety of Allen's previous work. You can watch ANNIE HALL a hundred times and catch something new with each viewing.  Like the chorus directly states at the end: "Isn't life ironic?" Well, yeah. But there are much better ways to tell us about it.
RATING: ***
\-------------------------------\ |* Unquestionably awful | |** Sub-par on many levels | |*** Average, hits and misses | |**** Good, memorable film | |***** Perfection | \-------------------------------\
-Christopher Null /<EMAIL_ADDRESS>-Movie Emporium (archives) / http://www.notes.tpoint.net/emporium/ -Contributing Editor, FEEDBACK / http://www.eden.com/~feedback -E-mail requests to join the movie review mailing list
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
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Please direct comments/criticisms of the review to relevant newsgroups.
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Related links: index of all rec.arts.movies.reviews reviews


Donate your Time, Talents, Services or Goods:
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From time to time everyone is in need of a particular service or good. Why not search the DoingGood network first for what you are looking to pay for? Hiring a DoingGood member or purchasing an item through the DoingGood platform allows the money you spend to directly benefit a worthy cause.
Benefit your Community, Organization or Cause
The best part about volunteering your time, talents, services and goods through The best part about volunteering your time, talents, services and goods through DoingGood is that YOU get to choose the beneficiary of your good deeds! Search our list of organizations and causes to choose where you want your donated funds go. You can also search current opportunities available that benefit your cause.
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switch
statements/expressions
with too low a ratio of switch labels to executable statements. Such switch
statements
may be confusing, and should probably be refactored.
Example of the reported code:
switch (i) { // one case and 5 executable statements -> 20% density case 1: System.out.println("1"); System.out.println("2"); System.out.println("3"); System.out.println("4"); System.out.println("5"); break; }
Use the field below to specify allowed ration of the switch labels to executable statements.


In Stock
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Delivery by, Wed Apr 24
7% off 1 offers Available
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@header@
| Specific Server Installation Details |
|
Pebble has been tested on a variety of web/application servers and some of these require additional/alternative installation steps. If you have successfully deployed Pebble on other servers, please send us an e-mail and we'll update this page.
Tomcat 4.1.x and 5.0.xPlease see the getting started instructions that are written with Tomcat in mind.
JBoss 3.x/Tomcat 4.1.xHere's a summary of the steps required to get Pebble working, based on a default installation and assuming that you are deploying the web application to a web context called/blog .
<application-policy name="blog"> <authentication> <login-module code="org.jboss.security.auth.spi.UsersRolesLoginModule" flag="required" /> </authentication> </application-policy> users.properties file underneath the WEB-INF/classes directory to specify the users for this webapp.# users.properties file has user=password pairs simon=password roles.properties file underneath the WEB-INF/classes directory to map users to roles for this webapp.# roles.properties has user=role,role2,roleN pairs simon=blog-owner,blog-contributor WEB-INF directory to specify the security domain.
<jboss-web> <security-domain>java:/jaas/blog</security-domain> </jboss-web>
Resin 2.1.xHere's a summary of the steps required to get Pebble working on a default installation of Resin 2.1.x, assuming that you plan to install it to a web context of/blog .
Resin 3.0.xHere's a summary of the steps required to get Pebble working on a default installation of Resin 3.0.x, assuming that you plan to install it to a web context of/blog . Essentially, deploying a webapp on Resin 3.0.x is the same as deploying to Resin 2.1.x although it uses a slightly different syntax.
Jetty 4.2.xHere's a summary of the steps required to get Pebble working on a default installation of Jetty 4.2.x.
Jetty 5.0.xFollow the steps for Jettey 4.2.x and then, before starting, remove the following files from/WEB-INF/lib .
BEA WebLogic 8.1The normal installation instructions should be followed, with the exception that all security role names shouldn't contain the hyphen character. The easiest way to do this is open theweb.xml file and search/replace blog-owner for blog_owner and blog-contributor for blog_contributor . These new role names should then be used when setting up users in the security realm.
Orion 1.x and 2.xUnfortunately, at the time of writing, deployment to Orion is not supported due to a number of bugs in their implementation of the Servlet specification. |


Intro to Digital Product Design • Co-Teacher
The question at hand: How might we address the lack of practical design education at Cornell?
The problem we were facing at Cornell was, being a resesarch institute, the university focused more on academia over industry application.
As such, a few of us created a course on digital product design that focused on solving a real life problem in the form of a case study. The course was 10 weeks long and university credited. The lectures focused on product-thinking, design process, and learning relevant design tools.
By the end, many students ended up pursuing design as a career at companies such as Facebook, Grubhub, Jet.com, IBM Maelstrom, and Amazon.


--- layout: default date: 22/06/2019 ---
Covers races from 1st May — 19th June.
Last updated: {{ page.date | date: "%A, %B %e" }}
{% include standings.html riders=site.data.2019.series_3.timetrial teams=site.data.2019.series_3.timetrialteam %} {% include datetime.html %}


The Chico State chapter of the Association for computing Machinery
The ACM club focuses on algorithms, interview prep, and competitive programming!
Learn how to contribute to the site by checking out the site readme or our site's github page!


Psalms 107:10
Such as sit in darkness and in the shadow of death, being bound in affliction and iron;


This provides you with mocked status responses your projects.
Create a Mocked Response
below.
Add request header eg. x-ag-expected-status: 200
in your project.
Point the project requests to the API Garage Mocking Server http://localhost:{{mockingPort}}/path/to/endpoint
Start Mocking Server {Project Name} > Start Mocking Server
.


Industry leaders since 2006. The best companies use our system to find the best and brightest professionals.


Zone 1: Cook and Lake Counties
Crisis Intervention
Talkline Help Lines, Inc.
P.O. Box 1321
Elk Grove Village, IL 60007
Talk Line (for adults):<PHONE_NUMBER>
Teen Line: (708) 228-TEEN (8336)
Kids Line: (708) 228-KIDS (5437)
Fax:<PHONE_NUMBER>
Community Information and Referral Service
560 West Lake Street
Chicago, IL 60661
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
A professional information and referral service supported by the United Way/Crusade of Mercy. Trained and experienced social work consultants link people who need help with qualified service providers.
Lutheran Child and Family Services of Illinois
7620 Madison Street
River Forest, IL 60305
Phone:<PHONE_NUMBER> or<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
United Way Community Referral Service
560 West Lake Street
Chicago, IL 60661-1499
Phone:<PHONE_NUMBER>
Toll-Free:<PHONE_NUMBER> (Chicago metro area)
Fax:<PHONE_NUMBER>
Connection Telephone Crisis Intervention and Referral Service
P.O. Box 906
Libertyville, IL 60048
Hotline:<PHONE_NUMBER>
Office:<PHONE_NUMBER>
Lake County Urban League
122 Madison Avenue
Waukegan, IL 60085
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Zone 2: McHenry, Kane, DuPage, and Will Counties
Crisis Intervention
Community Crisis Center
P.O. Box 1390
Elgin, IL 60121
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
American Red Cross
Arlington Heights Center
544 West Northwest Highway
Arlington Heights, IL 60004
Service Center Phone:<PHONE_NUMBER>
Suburban Region Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
DuPage County Department of Human Resources
Division of Human Services
421 County Farm Road North
Wheaton, IL 60187
Senior Services Phone:<PHONE_NUMBER>
Toll-Free:<PHONE_NUMBER>
TDD:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Senior Services Center of Will County
310 North Joliet Street
Joliet, IL 60432
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Kane County Information
1035 East State Street
Geneva, IL 60134
Phone:<PHONE_NUMBER>
American Red Cross, Rock River Chapter
727 North Church Street
Rockford, IL 61103
Phone:<PHONE_NUMBER>
United Way Services, Inc.
612 North Main Street, #200
Rockford, IL 61101-6929
Phone:<PHONE_NUMBER>
Information and Assistance
1905 East Main
Urbana, IL 61801
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Infoline
P.O. Box 1976
Rockford, IL 61110
Phone:<PHONE_NUMBER>
Toll-Free:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Springfield Urban League
100 North 11th Street
P.O. Box 3865
Springfield, IL 62708
Phone:<PHONE_NUMBER>
United Way of McLean County
201 East Grove, #100
Bloomington, IL 61701
Phone:<PHONE_NUMBER>
Path Crisis Center
201 East Grove
Bloomington, IL 61701
Phone:<PHONE_NUMBER>
First Call for Help
405 South State Street
Champaign, IL 61820
Phone:<PHONE_NUMBER>
TDD:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
United Way Help Line
300 Civic Center Plaza, #260
Quincy, IL 62301
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Your Link to Help
509 West High Street
Peoria, IL 61606
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Toll-Free in Illinois:<PHONE_NUMBER>
Serving Tri-county area of central Illinois (Peoria, Tazewell, Woodford Counties).
Call for Help
9400 Lebanon Road
Edgemont, IL 62203
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Information and Referral
9400 Lebanon Road
Edgemont, IL 62203
Phone:<PHONE_NUMBER>
24-Hour Hotline:<PHONE_NUMBER>
Information and Assistance
P.O. Box 631
Effingham, IL 62401
Phone:<PHONE_NUMBER>
Elder Abuse:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Catholic Social Services of Belleville
617 South Belt West
Belleville, IL 62220-2482
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Fax:<PHONE_NUMBER>
Serves social needs of 28 southern counties.
Champaign County Urban League
17 Taylor Street
Champaign, IL 61820
Phone:<PHONE_NUMBER>
Chicago Urban League
4510 South Michigan Avenue
Chicago, IL 60653
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Illinois Committee on Black Concerns
411 East Broadway
East St. Louis, IL 62201
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Lake County Urban League
122 Madison Street
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Madison County Urban League
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Phone:<PHONE_NUMBER>
Springfield County Urban League
100 North 11th Street
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Springfield, IL 62708
Phone:<PHONE_NUMBER>
Domestic Abuse, Assault, Victim Services
Illinois Coalition Against Domestic Violence
730 East Vine Street, #109
Springfield, IL 62703
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Provides emergency shelter, food, medical care and counseling to victims of domestic violence.
Illinois Coalition Against Sexual Assault
123 South Seventh Street, #500
Springfield, IL 62701
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Provides services for victims of sexual assault.
Northwest Action Against Rape
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Provides counseling and crisis services.

Stopping Woman Abuse Now
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Olney, IL 62450
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Provides legal and social services to victims of domestic violence in southeastern Illinois.
University of Chicago Gay and Lesbian Alliance
1212 East 59th Street, Room 207
Chicago, IL 60637
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Promotes individual rights; provides support services.
AIDS Foundation of Chicago
1332 North Halstead
Chicago, IL 60622
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Serves persons with AIDS.
AIDS Pastoral Care Network
4753 North Broadway, #800
Chicago, IL 60640
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Interfaith support and crisis counseling.
Midwest AIDS Foundation
2202 North Cleveland Street
Chicago, IL 60614
Phone:<PHONE_NUMBER>
Provides assistance and support to persons affected by AIDS.
Chinese Mutual Aid Association
1100 West Argyle Street
Chicago, IL 60640
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Provides employment services, counseling and community organizing to Chinese immigrants and refugees.
Southeast Asian Center
1134 West Ainslie
Chicago, IL 60640
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Fosters self-sufficiency for Southeast Asian immigrants and refugees.
Vietnamese Association of Illinois
5252 North Broadway Street
Chicago, IL 60640
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Provides employment and immigration services, youth and elderly services and assistance to refugee businesses.
Centro Hispano Sembrador
921 West State Street
Rockford, IL 61102
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Provides social services for Hispanic community.
Mujeres Latinas En Accion
1823 West 17th Street
Chicago, IL 60608
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Operates domestic violence program, youth advocacy program and parental support groups.
Hispanic AIDS Network
1874 North Milwaukee Avenue
Chicago, IL 60647
Phone:<PHONE_NUMBER>
Hispanic Social Service Agency, Lutheran Family and Child Services
3859 West 26th Street
Chicago, IL 60623
Phone:<PHONE_NUMBER>
Latino Counseling Service
3225 North Sheffield
Chicago, IL 60657
Phone:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Oasis Women's Center
111 Market Street
Alton, IL 62002
Phone:<PHONE_NUMBER>
Toll-Free:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Kindred Spirit
224 Ridge Avenue
Evanston, IL 60201
Phone:<PHONE_NUMBER>
YWCA of Metropolitan Chicago South
Suburban Center
4343 West Lincoln Highway, #210
Matteson, IL 60443
Phone:<PHONE_NUMBER>
24-Hour Hotline:<PHONE_NUMBER>
Fax:<PHONE_NUMBER>
Provides transitions counseling.
Illinois Women's Agenda
Six North Michigan Avenue, Suite 1313
Chicago, IL 60602
Phone:<PHONE_NUMBER>
Protects women's rights in Illinois; women's rights advocacy.
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draw title string
Draw title at top of graph. Backslash within string denotes new line.
title
string


This page displays a single snapshot taken from the system's default video camera. If a camera isn't available, a generic image is displayed.
Use the following buttons on the camera page to:
Update the picture from the system's camera.
Go to the system's web page.
Get help.
By default, the camera is disabled. To enable the camera for your
system, log in as root and edit the file /var/www/cgi-bin/sgi-camera/snap/.
Change the value of the variable camera to ENABLED,
as in:
camera = "ENABLED"
To disable the camera, change the value to:
camera = "DISABLED"
You can include the camera picture from this system in another Web page
by adding the line:
<IMG SRC="http://systemname/cgi-bin/sgi-camera/snap">
where systemname is the name of the system on which the camera resides.
See the Access Control page to learn how to restrict access to the directory /var/www/cgi-bin/sgi-camera.


Produce a Great Tech Talk by Asking Yourself (and Answering!) These Questions
Members of the Gilt engineering team give lots of technical presentations at meetups, conferences, our in-house gatherings, and online. How do we make sure that our content is “tech” enough to interest experienced engineers? And how do we confidently tell the most compelling stories possible? With these concerns in mind, I’ve created this list of questions to ask while planning and preparing a tech talk. All of you engineers out there in Greater Internetlandia might find it useful as you work on your own presentations:
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Which technology/technologies will you discuss in this talk?
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Which technology or aspect of technology will be the primary focus: a language, a framework, a problem, a methodology, or a combination of technologies working together? (Or “other”? If “other” is your answer, please define)
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How would you title and summarize your topic so that, if you saw it advertised on a random events listing page, you would regard it as a “must-attend” talk? (If it’s not a “must-attend” yet, keep working!)
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Will this topic be of obvious interest to engineers? What type of engineers? Please be as precise as possible in describing type (for example, “experienced generalist engineers who lean front-end,” “front-end mobile UX engineers,” “back-end engineers who work on big data initiatives involving X, Y and Z technologies,” etc.”)
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Have you done online research to make sure that no one in the area has given a substantially similar talk in the last 3-6 months? (If someone has already given a similar talk, one option is to take an opposing view; another is to highlight subtopics that the past presenter(s) didn’t discuss)
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From a technical POV, what is the most novel/exciting aspect of the content you’re providing? And from an implementation POV, what makes your approach remarkable? (In related: What about this topic personally excites and inspires you?)
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Does your presentation offer a solution to a commonly held technical problem? What about your proposed solution is novel/different from what you’ve seen discussed in other, similar talks/blog posts/tech lit? (Put another way: Does your presentation offer a way to work better/more efficiently/more creatively?)
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The format that would make this talk most compelling would be (choose one): “how-to,” “explainer,” “argument/opinion,” “case study/narrative,“ "comparison,” "demonstration”
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Will your talk include a live demo? And what will your samples of code demonstrate or reveal?
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What notable outside sources–widely discussed technical articles, others’ presentations that have gone viral, quotes by well-known technologists–can your cite in order to place your talk in the broader context of what’s currently “hot” in the engineering community?
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What are the resources you need to start and complete your talk: research help? guidance with structure? help creating visuals?
- Who else on your team would you like to bring in to provide objective, constructive criticism, brainstorming help, and feedback? (Pick 1-2 members of your team + 1-2 engineers whose work isn’t directly related to your talk’s content)
Feel free to share your feedback by emailing lapple at gilt dot com. And if you have tips of your own, send them my way–you’ll receive a byline here + a link to your Twitter feed, website or other choice online property that you own.


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gsw_gibbs
Gibbs energy and its derivatives
Contents
USAGE:
gibbs = gsw_gibbs(ns,nt,np,SA,t,p)
DESCRIPTION:
Calculates specific Gibbs energy and its derivatives up to order 2 for seawater. The Gibbs function for seawater is that of TEOS-10 (IOC et al., 2010), being the sum of IAPWS-08 for the saline part and IAPWS-09 for the pure water part. These International Association for the Properties of Water and Steam (IAPWS) releases are the officially blessed IAPWS descriptions of Feistel (2008) and the pure water part of Feistel (2003). Absolute Salinity, SA, in all of the GSW routines is expressed on the Reference-Composition Salinity Scale of 2008 (RCSS-08) of Millero et al. (2008).
Click for a more detailed description of Gibbs energy. |
INPUT:
ns = order of SA derivative [ integers 0, 1 or 2 ] nt = order of t derivative [ integers 0, 1 or 2 ] np = order of p derivative [ integers 0, 1 or 2 ] SA = Absolute Salinity [ g/kg ] t = in-situ temperature (ITS-90) [ deg C ] p = sea pressure [ dbar ] (ie. absolute pressure - 10.1325 dbar)
SA, t and p need to have the same dimensions.
OUTPUT:
gibbs = Specific Gibbs energy or its derivatives.
The Gibbs energy (when ns = nt = np = 0) has units of: [ J/kg ] The Absolute Salinity derivatives are output in units of: [ (J/kg) (g/kg)^(-ns) ] The temperature derivatives are output in units of: [ (J/kg) (K)^(-nt) ] The pressure derivatives are output in units of: [ (J/kg) (Pa)^(-np) ] The mixed derivatives are output in units of: [ (J/kg) (g/kg)^(-ns) (K)^(-nt) (Pa)^(-np) ]
Note. The derivatives are taken with respect to pressure in Pa, not withstanding that the pressure input into this routine is in dbar.
AUTHOR:
David Jackett [<EMAIL_ADDRESS>] MODIFIED: Trevor McDougall and Paul Barker
VERSION NUMBER:
3.03 (30th April, 2013)
REFERENCES:
Feistel, R., 2003: A new extended Gibbs thermodynamic potential of seawater, Progr. Oceanogr., 58, 43-114.
Feistel, R., 2008: A Gibbs function for seawater thermodynamics for -6 to 80°C and salinity up to 120 g kg–1, Deep-Sea Res. I, 55, 1639-1671.
IAPWS, 2008: Release on the IAPWS Formulation 2008 for the Thermodynamic Properties of Seawater. The International Association for the Properties of Water and Steam. Berlin, Germany, September 2008, available from http://www.iapws.org. This Release is referred to as IAPWS-08.
IAPWS, 2009: Supplementary Release on a Computationally Efficient Thermodynamic Formulation for Liquid Water for Oceanographic Use. The International Association for the Properties of Water and Steam. Doorwerth, The Netherlands, September 2009, available from http://www.iapws.org. This Release is referred to as IAPWS-09.
IOC, SCOR and IAPSO, 2010: The international thermodynamic equation of seawater - 2010: Calculation and use of thermodynamic properties. Intergovernmental Oceanographic Commission, Manuals and Guides No. 56, UNESCO (English), 196 pp. Available from http://www.TEOS-10.org See section 2.6 and appendices A.6, G and H of this TEOS-10 Manual.
Millero, F. J., R. Feistel, D. G. Wright, and T. J. McDougall, 2008: The composition of Standard Seawater and the definition of the Reference-Composition Salinity Scale, Deep-Sea Res. I, 55, 50-72.
The software is available from http://www.TEOS-10.org


Rough categorization for well-known web applications. This section is designed for full applications as opposed to tools/frameworks that are powering them on the backend (see Attacks > Software > Web Technologies).


Demo - Kleer Hat
Video - Kleer Hat (Video created by dex)
This was a funny thing that happened to BoltR when we were cooping Sierra de Chiapas on Tourist. A Kleer jumped on his head and stayed there for a moment, the situation was conveniently named "Kleer Hat" :) Pretty awesome.
To switch view in the demo, press num plus or num minus. You can also switch to multiview with num 1-4.
Demo - No-Damage run on Serious by DavizZz
DavizZz made a No-Damage run on Serious through the long corridor in the level The Grand Cathedral. He did get hit a bit at the end because of the explosion of one of the Cannonballs, but we'll forgive him for that ;) It's a nice run.
A while back I made a video for him but I don't have that video anymore. I'll probably create another video sometime in the future.
Also, I should note that he got all weapons right away and maxed his health, armor, and ammo (Or at least enough of it ;)). And DavizZz intentionally used no Serious Bombs to make it more interesting.
The run length is 0:32:44.


Pahang prohibits water recreational, hiking activities during monsoon season
KUANTAN, Nov 20 — The Pahang government has from today prohibited water recreational and hiking activities in the state throughout the northeast monsoon season for safety reasons.
State Secretary Datuk Seri Dr Sallehuddin Ishak said the prohibition would be until Jan 20 next year or at a later date.
Among the activities prohibited are hiking, camping, swimming and fishing in waterfalls, lakes as well beaches.
“The rainy season can cause a sudden surge of water at waterfalls, an increase in water levels at lakes as well as the high tide and big wave phenomenon,” he said in a statement here today.
Sallehuddin said local authorities and relevant state government agencies would also increase monitoring particularly during the school holiday season, as well as put warning signs at high-risk areas. — Bernama