- getClassesForFile(String, String) - Method in class org.pitest.coverage.CoverageData
-
- getClassesForFile(String, String) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getClassInfo(Collection<ClassName>) - Method in class org.pitest.coverage.CoverageData
-
- getClassInfo(Collection<ClassName>) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getCountFailedTests() - Method in class org.pitest.coverage.CoverageData
-
- getCoverage() - Method in class org.pitest.coverage.CoverageSummary
-
- getCoverage() - Method in class org.pitest.mutationtest.ListenerArguments
-
- getCoverageIdForClass(ClassName) - Method in class org.pitest.coverage.CoverageData
-
- getCoverageIdForClass(ClassName) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getCoverageReporter(CoverageData, Writer, Writer)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
- getCoverageReporter(CoverageData, Writer, Writer, ReportFormatter)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
CoverageReporter FactoryMethod
- getCoverageReporter(CoverageData, Writer, Writer)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getCoverageReporter(CoverageData, Writer, Writer, ReportFormatter)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getDetails() - Method in class org.pitest.mutationtest.MutationResult
-
- getEngine() - Method in class org.pitest.mutationtest.ListenerArguments
-
- getFailingTestDescriptions() - Method in class org.pitest.coverage.CoverageData
-
- getFileName() - Method in class org.pitest.mutationtest.ClassMutationResults
-
- getFileWriter()
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
Delegates to FileWriter.getInstance()
- getFileWriter()
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getFormattedLocation(BlockCoverage)
- Method in interface org.pitest.mutationtest.report.detailed.csv.ReportFormatter
-
Method name and class formatting (specialized for BlockCoverage, delegates to generic
method).
- getFormattedLocation(MutationResult)
- Method in interface org.pitest.mutationtest.report.detailed.csv.ReportFormatter
-
Method name and class formatting (specialized for MutationResult, delegates to generic
method).
- getFormattedLocation(BlockCoverage)
- Method in class org.pitest.mutationtest.report.detailed.csv.ReportFormatterImpl
-
- getFormattedLocation(MutationResult)
- Method in class org.pitest.mutationtest.report.detailed.csv.ReportFormatterImpl
-
- getInstance()
- Static method in class org.pitest.mutationtest.report.detailed.csv.ReportFormatterImpl
-
- getInstance()
- Static method in class org.pitest.mutationtest.report.detailed.csv.utils.FileWriterImpl
-
- getKillingTest() - Method in class org.pitest.mutationtest.MutationResult
-
- getKillingTestDescription() - Method in class org.pitest.mutationtest.MutationResult
-
- getKillingTests() - Method in class org.pitest.mutationtest.MutationResult
-
- getListener(Properties, ListenerArguments) - Method in interface org.pitest.mutationtest.MutationResultListenerFactory
-
- getListener(ListenerArguments, String, String, String)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
Alternative DetailedCSVReportListener Factory Method
- getListener(FileWriter, CoverageReporter, MutationReporter)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
Alternative DetailedCSVReportListener Factory Method
- getListener(Properties, ListenerArguments)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
Main DetailedCSVReportListener Factory Method
- getListener(ListenerArguments, String, String, String)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getListener(FileWriter, CoverageReporter, MutationReporter)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getLocator() - Method in class org.pitest.mutationtest.ListenerArguments
-
- getMutatedClass() - Method in class org.pitest.mutationtest.ClassMutationResults
-
- getMutationReporter(Writer)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
MutationReporter Factory Method
- getMutationReporter(ReportFormatter, Writer)
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
MutationReporter Factory Method
- getMutationReporter(Writer)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getMutationReporter(ReportFormatter, Writer)
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getMutations() - Method in class org.pitest.mutationtest.ClassMutationResults
-
- getMutations() - Method in class org.pitest.mutationtest.MutationMetaData
-
- getNumberOfCoveredLines(Collection<ClassName>) - Method in class org.pitest.coverage.CoverageData
-
- getNumberOfCoveredLines(Collection<ClassName>) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getNumberOfCoveredLines() - Method in class org.pitest.coverage.CoverageSummary
-
- getNumberOfLines() - Method in class org.pitest.coverage.CoverageSummary
-
- getNumberOfTestsRun() - Method in class org.pitest.mutationtest.MutationResult
-
- getOutputStrategy() - Method in class org.pitest.mutationtest.ListenerArguments
-
- getPackageName() - Method in class org.pitest.mutationtest.ClassMutationResults
-
- getReportFormatter()
- Method in interface org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactory
-
Delegates to ReportFormatter.getInstance()
- getReportFormatter()
- Method in class org.pitest.mutationtest.report.detailed.csv.DetailedCSVReportFactoryImpl
-
- getStartTime() - Method in class org.pitest.mutationtest.ListenerArguments
-
- getStatus() - Method in class org.pitest.mutationtest.MutationResult
-
- getStatusDescription() - Method in class org.pitest.mutationtest.MutationResult
-
- getStatusTestPair() - Method in class org.pitest.mutationtest.MutationResult
-
- getSucceedingTests() - Method in class org.pitest.mutationtest.MutationResult
-
- getTestsForClass(ClassName) - Method in class org.pitest.coverage.CoverageData
-
- getTestsForClass(ClassName) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getTestsForClassLine(ClassLine) - Method in class org.pitest.coverage.CoverageData
-
- getTestsForClassLine(ClassLine) - Method in interface org.pitest.coverage.CoverageDatabase
-
- getTestsForInstructionLocation(InstructionLocation) - Method in class org.pitest.coverage.CoverageData
-
- getTestsForInstructionLocation(InstructionLocation) - Method in interface org.pitest.coverage.CoverageDatabase
-


The emerging evidence available to us is suggesting that there may be some significant risks posed by social media use to young people’s mental health and emotional wellbeing. However, research is thus far limited and due to social media being a relatively new introduction to the lives of young people, far more long-term research will be necessary before we are able to fully understand its effects. We would like to see academic institutions, independent researchers and social media companies fund and undertake much more research into the subject, especially in developing countries like Romania, where mental health problems are usually frowned upon and dismissed by the general population.


FizzBuzz example
Input:
Starting value:
Ending value:
Fizz value:
Buzz value:
Make DIVS
Clear DIVS
Reset
Output:
Id number divides evenly with "Fizz" and "Buzz" value:
Id number divides evenly with "Fizz" value ONLY:
Id number divides evenly with "Buzz" value ONLY:
Does not divide with "Fizz" or "Buzz" value:


| Employees | Department | {{header}} |
|---|---|---|
|
|
{{employee.DepartmentCode}} | {{leave}} |
| Employees | {{header}} |
|---|---|
| {{leave}} |
| Employees | {{header}} |
|---|---|
| {{leave}} |
| Employees | {{header}} |
|---|---|
| {{leave}} |
| Employees | {{header}} |
|---|---|
| {{leave}} |


--- layout: default title: About description: Basic info and about Josh Davis including links and contact info. ---
My name is Josh Davis.
I'm a software engineer currently trying to build something new. I used to work at AWS and graduated from Iowa State University with a degree in Computer Science.
I like simple things that work well. I'm passionate in all that I do. I think learning is the ultimate pursuit of humankind. I never save anything for the swim back.
When I'm not trying to change the world through code, I can often be found reading and collecting books, running, and coding.
Feel free to contact me through Twitter, or privately through email. I really enjoy talking with people.
If you'd like to contact me securely, feel free to verify my identity on Keybase.io. and encrypt your communications using my public key.


Hi all,
Just built my first board, the emonTx.
I have it connected up with USB power and USB data connection via the FDTI plug.
Arduino software seems to be running properly on my PC (Old Dell running Ubuntu 10.4)
Tools>Serial Port sees the board as /dev/ttyUSB0 when the board is connected and doesn't see anything when it's not.
When I try to upload the blinkwithoutdelay sketch I receive the following error:
avrdude: stk500_recv(): programmer is not responding.
I've read the troubleshooting guide at Arduino home but can't find anything there to help.
Where should I next look?
Thanks,
Richard
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
Have you selected 'Uno' under tools>board?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
I have.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
After more reading of the Arduino support boards, should the green led be lit when power is applied to the board?
The blue led on the FTDI plug lights up when it's plugged in but the green led on the emonTx board does not?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
No the green LED should not Light. Try checking that the emonTx is getting power, instructions towards the end of the build guide: http://ichilton.github.com/openenergymonitor/emontx/build_guide.html. This is a new build guide that is still in the making.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
I've checked the voltage between the 3V and GND sockets in the line of sockets between the FTDI connecter and the chrystal.
The voltage is measured at 3.87V.
Is that out of range?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
This is a bit high, I think it's because you're powering the emonTx from both the FTDI and mini-usb. Best to only power it either or. Try powering it with only the FTDI and measure the voltage again. Although I don't think this is the problem, it should still work.
Have you got a normal Arduino? Can you program this via your computer?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
If I just use the FTDI connector with the connector board the same way up as the emonTx board, the voltage measured between the 3.3V hold and the GND hole is .438V. If I put the connector board the other way up, it gets 3.3V.
Either way the software does the same thing and gives the same error.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
Here's a picture of the correct orientation of the FTDI connector, the ground pin label on the FTDI and the emontx will be aligned.
What operating system are you using?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
As for another Arduino board I have the emonBase and the emonGLCD to build.
Any recommendations as to which I should try first?
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
That's the way that I have it. That gives me 3.3V
When you ask for the O/S, I assume you mean my PC?
It's running Ubuntu 10.4.
I used the guide at http://www.pluggy.me.uk/arduino-ubuntu/ to set it up.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
The guide you followed is using an old version of Arduino IDE. You need Arduino 1.0. Download from here: http://arduino.cc/en/Main/Software.
Try following the guides to setting up with Ubuntu on the Arduino website: http://www.arduino.cc/playground/Learning/Linux.
I'm using Ubuntu 11.10, no setup was needed at all. I just downloaded Arduino 1.0, marked the filed 'arduino' as executable then double clicked to run it.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
Similar problems here.
Everything plugged together properly. Voltages seem just fine. Blue LED on the FTDI card.
I know the drivers work (I'm on a Mac) because my Jeelink works fine, and that has an internal USB to FTDI interface.
I'm not the neatest solderer in the world but I've checked all of the connections with a magnifying glass, as well as zooming in with a camera, and they look fine.
But I'm getting:
Using Port : /dev/tty.SLAB_USBtoUART
Using Programmer : arduino
Overriding Baud Rate : 115200
avrdude: Send: 0 [30] [20]
avrdude: Send: 0 [30] [20]
avrdude: Send: 0 [30] [20]
avrdude: ser_recv(): programmer is not responding
avrdude: stk500_recv(): programmer is not responding
Anyone have any ideas where to look?
P.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
Just re-checked VCC - it's a nice 3.3V when the board is powered via the USB connection, but it's 3.98V when powered via the FTDI card.
Does this mean I've messed up somewhere?
5V is 5V in both cases.
P.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
SOLVED - It wasn't my soldering, it was whoever soldered the FTDI board! There was a solder splash shorting out a couple of the pins on the reverse side of the FTDI connector.
Hopefully this will help anyone else that comes across a similar problem.
P.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
Incidentally, I think that photo of the FTDI attached (above) would be a useful addition to the build guide. I know that GND has to be aligned on both, but it's not easy to see which pin in GND on a fully populated eMonTX. That photo would have saved me 15 minutes of searching!
P.
Re: RESOLVED: emonTx - uploading the blinkwithoutdelay sketch; Fallen at the first hurdle
It is quite hard to see which is the GND end - I looked at the underside of the pcb to see where the ground plane connects, then put a spot of paint on the end of the header.
For what it's worth, I've made up a short ribbon cable to put between the FTDI and the target board. That way, it will be much harder to damage the connectors and/or the pcb if subjected to mishandling.


WWW Access Statistics for 1997
December 1997
November 1997
October 1997
September 1997
August 1997
July 1997
June 1997
May 1997
April 1997
March 1997
February 1997
January 1997
Close navigation window


female body females energy prey pup Fig distance foraging length fur abundance aggregation fishing mass seal Antarctic Guinet resource time seals conditions trip data marine rate success place pups {border-style central level breeding changes intermediate period px;} #ffffff;} mortality Dist levels mean number optimal probability results sea survival Mar island model resources Female PC. average behavior environmental parameters Click Kerguelen LINK Sciences Table additional effect file. initial location memorization spent Abund Energy Foraging Polar current events final food patches Aggreg Biology LMG animals ashore change climate fish growth km, map rearing simulation Ecol However, Lea Ser. Simulation distribution duration oceanographic relation travelled using (see Dataset Life Prog cell circles) defined environment function gained highly hour importance increase max recorded suckle Arctocephalus B). Boyd Cherel Effect M-A Subantarctic colony corresponding days feed likely possible px; ratio relationship simulations size used value values {font-family (b) Beauplet Ecol. MarCPFS Marine SD) Southern Text). University areas considered critical death diving drag female-pup font-size foragers high increased individual poor predators provided random ranging real section set shift species trips type walk (SP) (mean Animal Biol. Distance Ecology Mem ]). ability area available calculated conditions, content correlated decision decreased distance, distances double; energetic expenditure favorable field forage forager higher larger length. obtained ocean pairs plateau population positive reach return richest showed shown simulated successful successfully variables (Aggreg (Arctocephalus (TXT) (a) (c) D). Dubroca E/SP Finally, Fishing Indeed, Initial Islands Length Maximal Mean Optimal Pup Rep Time Zool. accessibility behaviour best border-color border-width cells compared consistent covered depends direct effects end force gain gazella hour, increasing intake linear longer low memory models needed new populations predator pup. pups, pups. rates respectively. seal, seals: similar solid; southward spatial speed step strategies strong studies suckling sufficient systems visited weights {font-style {font-weight (Dist) (PDF) (ZIP) (d) (level A). Arnould Bailleul Behavior Behavior: C). Econtent Females Fig). France Goldsworthy Mass Maternal NbrFishing NbrTrip Ocean Press, Sci. able animal balance below). bold condition consequences consider corresponds courier; direction divided e., em; environment. factors features feeding fixed frontal gazella) given highest impact information involved lactation large lead length, lowest mainly mammals maternal maximal modify night open outcomes particular performances period, period. periods pp. prenatal prey. productive pt;} quadratic quality quickly reference replication represents reproductive response resulting satellite sea, seal) searching study temperature theory time. trajectories travel unpublished use validation


An example is introduced by McCullough in paper "Noninterference and the Composability of Security Properties".
In that example, the buffer BC is used to guarantee that if A's message is read by S first, then S will not read another message until A output 0 to buffer BD. It is applicable to process B.


Get the App
Login
SignUp
Discover the best food & drinks in
Thrissur, Kerala
Thrissur, Kerala
Trivandrum, Kerala
Palakkad, Kerala
Kochi, Kerala
Pathanamthitta, Kerala
Calicut, Kerala
Kasaragod, Kerala
Kollam, Kerala
Wayanadu, Kerala
Kannur, Kerala
Kottayam, Kerala
Alappuzha, Kerala
Ernakulam,Kerala
Idukki, Kerala
Malappuram, Kerala
Kozhikode, Kerala
|
Popular localities in and around
Thrissur, Kerala
Thrissur, Kerala (15 Places)
Get the Zomato App
We'll send you a link, open it on your phone to download the App
Email
Phone
Share
Download app from
Explore other options for you here
Popular cuisines near me
American food near me
BBQ food near me
Bar food near me
Burger food near me
Cafe food near me
Chinese food near me
Coffee and Tea food near me
Dessert food near me
German food near me
Greek food near me
Ice-Cream food near me
Italian food near me
Japanese food near me
Mexican food near me
Pizza food near me
Sandwich food near me
Sea food near me
Steak food near me
Sushi food near me
Tea food near me
Popular restaurant types near me
Bakeries near me
Bars around me
Cafes near me
Casual Dining near me
Dessert shops near me
Chinese food near me
Fast casual near me
Fast food near me
Pizzerias near me
Quick Bytes near me
Sandwich shops near me
Taquerias near me


I have done morning glory seeds(MGS) three times before, the first time finding they were real with 150 seeds (feeling only stoned), the second time find they were powerful with 250 seeds (having CEVs) and the third time finding nothing with no approximate dose but no effects either.
I told my friend about them and he said he wanted to try them. I hadn't taken them in a while so I went to a store and bought 15 1.5 gram packs of MGS. I told him a good fun dose that isn't too dangerous is about 250 seeds or 5 packs, so he took those. I took 10 packs or 500 seeds because I wanted to be trippin' balls.
We started taking the seeds at 7:00 P.M. so we could be inconspicuous. It took about 45 minutes to get them all down. We had no way to grind them up and just chewed them. In fifteen minutes we were both laughing hysterically. He got on the computer and started talking on the phone as I laid on the bed and watched spiraling clowns in CEV. I was going on and on about how much I hated clowns but was fun to watch them anyway.
We went to the bathroom and saw how dilated our pupils were. I started getting OEVs and my face was going in and out of proportion.
I sat on the sink and laughed hysterically at the wavy walls. My friend sat in the tub and I fell down in the corner laughing at him. We migrated back to my room and sat on the bed. He asked me if there was any way to stop the trip. I said no. Then he ran in the bathroom and puked 6 times as soon as I got there.
 I started calming him down and I refused to go get my mom and said it would be alright. He said he felt much better and that he was really happy after the seeds were out of his body. We went back to my room and talked about our happiness and Nirvana. I was peaking at that moment and saw the walls melting and waving. This was about at 11. He fell asleep and I was still tripping but wanted to sleep.
I went downstairs with a sleeping bag and fell asleep at about 12.
I am glad nobody got hurt. It went well after the rough experience.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Hosted Checkout - Return to Merchant - PHP/JavaScript/NVP
Payment Details
Order Amount
Order Currency
Customer Email Receipt Address


Provides two functions: Group_function() and Parallel_Tree(). Group_function() applies a given function (e.g.,mean()) to input variable(s) by group across levels. Has additional data management options. Parallel_Tree() uses 'ggplot2' to create a parallel coordinate plots (technically a facsimile of parallel coordinate plots in a Cartesian coordinate system). Used in combination these functions can create parallel tree plots, a variant of parallel coordinate plots, which are useful for visualizing multilevel data.
| Version: | 0.1.2 |
| Depends: | ggplot2 |
| Imports: | stats |
| Published: | 2016-11-22 |
| Author: | Patrick O'Keefe |
| Maintainer: | Patrick O'Keefe <patrick.okeefe at vanderbilt.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | ParallelTree results |
| Reference manual: | ParallelTree.pdf |
| Package source: | ParallelTree_0.1.2.tar.gz |
| Windows binaries: | r-devel: ParallelTree_0.1.2.zip, r-release: ParallelTree_0.1.2.zip, r-oldrel: ParallelTree_0.1.2.zip |
| OS X binaries: | r-release: ParallelTree_0.1.2.tgz, r-oldrel: ParallelTree_0.1.2.tgz |
| Old sources: | ParallelTree archive |
Please use the canonical form https://CRAN.R-project.org/package=ParallelTree to link to this page.


Optimizer¶
-
class
chainer.
Optimizer
[source]¶ Base class of all numerical optimizers.
This class provides basic features for all optimization methods. It optimizes parameters of a target link. The target link is registered via the
setup()
method, and then theupdate()
method updates its parameters based on a given loss function.Each optimizer implementation must be defined as a child class of Optimizer. It must override
update()
method. An optimizer can use internal states each of which is tied to one of the parameters. State is a dictionary of serializable values (typically arrays of size same as the corresponding parameters). In order to use state dictionaries, the optimizer must overrideinit_state()
method (or its CPU/GPU versions,init_state_cpu()
andinit_state_gpu()
).If the optimizer is based on single gradient computation (like most first-order methods), then it should inherit
GradientMethod
, which adds some features dedicated for the first order methods.Optimizer instance also supports hook functions. Hook function is registered by the
add_hook()
method. Each hook function is called in registration order in advance of the actual parameter update.Variables: - target – Target link object. It is set by the
setup()
method. - t – Number of update steps. It must be incremented by the
update()
method. - epoch – Current epoch. It is incremented by the
new_epoch()
method.
-
accumulate_grads
(grads)[source]¶ Accumulates gradients from other source.
This method just adds given gradient arrays to gradients that this optimizer holds. It is typically used in data-parallel optimization, where gradients for different shards are computed in parallel and aggregated by this method. This method correctly treats multiple GPU devices.
Parameters: grads (Iterable) – Iterable of gradient arrays to be accumulated. Deprecated since version v1.5: Use the
chainer.Link.addgrads()
method of the target link instead.
-
add_hook
(hook, name=None)[source]¶ Registers a hook function.
Hook function is typically called right after the gradient computation, though the timing depends on the optimization method.
Parameters:
-
clip_grads
(maxnorm)[source]¶ Clips the norm of whole gradients up to the threshold.
Parameters: maxnorm (float) – Threshold of gradient L2 norm. Deprecated since version v1.5: Use the
GradientClipping
hook function instead.
-
compute_grads_norm
()[source]¶ Computes the norm of whole gradients.
Returns: L2 norm of whole gradients, i.e. square root of sum of square of all gradient elements. Return type: float Warning
This method returns a CPU-computed value, which means that this method synchronizes between CPU and GPU if at least one of the gradients reside on the GPU.
Deprecated since version v1.5.
-
init_state
(param, state)[source]¶ Initializes the optimizer state corresponding to the parameter.
This method should add needed items to the
state
dictionary. Each optimizer implementation that uses its own states should override this method or CPU/GPU dedicated versions (init_state_cpu()
andinit_state_gpu()
).Parameters: See also
-
init_state_cpu
(param, state)[source]¶ Initializes the optimizer state on CPU.
This method is called from
init_state()
by default.Parameters: - param (Variable) – Parameter variable. Its data array is
of type
numpy.ndarray
. - state (dict) – State dictionary.
See also
- param (Variable) – Parameter variable. Its data array is
of type
-
init_state_gpu
(param, state)[source]¶ Initializes the optimizer state on GPU.
This method is called from
init_state()
by default.Parameters: See also
-
new_epoch
()[source]¶ Starts a new epoch.
This method increments the
epoch
count. Note that if the optimizer depends on the epoch count, then user should call this method appropriately at the beginning of each epoch.
-
prepare
()[source]¶ Prepares for an update.
This method initializes missing optimizer states (e.g. for newly added parameters after the set up), and copies arrays in each state dictionary to CPU or GPU according to the corresponding parameter array.
-
remove_hook
(name)[source]¶ Removes a hook function.
Parameters: name (str) – Registered name of the hook function to remove.
-
serialize
(serializer)[source]¶ Serializes or deserializes the optimizer.
It only saves or loads the following things:
- Optimizer states
- Global states (
t
andepoch
)
It does not saves nor loads the parameters of the target link. They should be separately saved or loaded.
Parameters: serializer (AbstractSerializer) – Serializer or deserializer object.
-
setup
(link)[source]¶ Sets a target link and initializes the optimizer states.
Given link is set to the
target
attribute. It also prepares the optimizer state dictionaries corresponding to all parameters in the link hierarchy. The existing states are discarded.Parameters: link (Link) – Target link object.
-
update
(lossfun=None, *args, **kwds)[source]¶ Updates the parameters and optimizer states.
This method updates the parameters of the target link and corresponding optimizer states. The behavior of this method is different for the cases either
lossfun
is given or not.If
lossfun
is given, then this method initializes the gradients by zeros, calls it with given extra arguments, and calls thebackward()
method of its output to compute the gradients. The implementation might calllossfun
more than once.If
lossfun
is not given, then this method assumes that the gradients of all parameters are already computed. An implementation that requires multiple gradient computations might raise an error on this case.In both cases, this method invokes the update procedure for all parameters.
Parameters: - lossfun (function) – Loss function. It accepts arbitrary arguments
and returns one
Variable
object that represents the loss (or objective) value. This argument can be omitted for single gradient-based methods. In this case, this method assumes gradient arrays computed. - kwds (args,) – Arguments for the loss function.
- lossfun (function) – Loss function. It accepts arbitrary arguments
and returns one
-
weight_decay
(decay)[source]¶ Applies weight decay to the parameter/gradient pairs.
Parameters: decay (float) – Coefficient of weight decay Deprecated since version v1.5: Use the
WeightDecay
hook function instead.
-
zero_grads
()[source]¶ Fills all gradient arrays by zeros.
Deprecated since version v1.5: Use the
chainer.Link.zerograds()
method for the target link instead.
- target – Target link object. It is set by the
-
class
chainer.
GradientMethod
[source]¶ Base class of all single gradient-based optimizers.
This is an extension of the
Optimizer
class. Typical gradient methods that just require the gradient at the current parameter vector on an update can be implemented as its child class.An implementation of a gradient method must override the following methods:
init_state()
or bothinit_state_cpu()
andinit_state_gpu()
update_one()
or bothupdate_one_cpu()
andupdate_one_gpu()
-
update
(lossfun=None, *args, **kwds)[source]¶ Updates parameters based on a loss function or computed gradients.
This method runs in two ways.
- If
lossfun
is given, then use it as a loss function to compute gradients. - Otherwise, this method assumes that the gradients are already computed.
In both cases, the computed gradients are used to update parameters. The actual update routines are defined by the
update_one()
method (or its CPU/GPU versions,update_one_cpu()
andupdate_one_gpu()
).- If
-
update_one
(param, state)[source]¶ Updates a parameter based on the corresponding gradient and state.
This method calls appropriate one from
update_param_cpu()
orupdate_param_gpu()
.Parameters:
Hook functions¶
-
class
chainer.optimizer.
WeightDecay
(rate)[source]¶ Optimizer hook function for weight decay regularization.
This hook function adds a scaled parameter to the corresponding gradient. It can be used as a regularization.
Parameters: rate (float) – Coefficient for the weight decay. Variables: rate (float) – Coefficient for the weight decay.
-
class
chainer.optimizer.
Lasso
(rate)[source]¶ Optimizer hook function for Lasso regularization.
This hook function adds a scaled parameter to the sign of each weight. It can be used as a regularization.
Parameters: rate (float) – Coefficient for the weight decay. Variables: rate (float) – Coefficient for the weight decay.
-
class
chainer.optimizer.
GradientClipping
(threshold)[source]¶ Optimizer hook function for gradient clipping.
This hook function scales all gradient arrays to fit to the defined L2 norm threshold.
Parameters: threshold (float) – L2 norm threshold. Variables: threshold (float) – L2 norm threshold of gradient norm.


/Users/kaipila/Documents/php/repos/webscale/webscale/lib
/
Driver
(Dashboard)
Class Coverage Distribution
Class Complexity
Top Project Risks
AbstractDriver
(575)
FileSystem
(36)
Factory
(33)
Memcached
(16)
Couchbase
(15)
Least Tested Methods
AbstractDriver::getErrorMode
(0%)
AbstractDriver::critical
(0%)
AbstractDriver::setErrorMode
(0%)
AbstractDriver::setLogger
(0%)
AbstractDriver::setMultiple
(44%)
AbstractDriver::set
(50%)
AbstractDriver::delete
(50%)
AbstractDriver::clearNamespace
(50%)
AbstractDriver::log
(50%)
AbstractDriver::deleteMultiple
(50%)


This documentation relates to Opera's now deprecated .oex Extension API framework for Opera versions <= 12.15 and also provided by our OEX2NEX shim library.
For the latest Opera Extensions API documentation for Opera versions > 12.15 please consult the latest Opera Extensions API documentation online.
Publishing your first Opera extension is a multi-step process that begins when you submit your extension for review. Extension developers are encouraged to publish and host their Opera extensions in the Opera extensions catalog. You should take a look at the Opera extensions publishing guidelines to get the most out of hosting your Opera extensions with us.
In case you decide to also distribute Opera extensions through your own site, you will need to set the MIME type of your server. This is important because as Opera extensions carry the possibly unknown .oex
file type, web servers might end up "guessing" the MIME type as being text/plain or application/octet-stream. According to the HTTP specifications, Opera will then have to process the document based on the reported MIME type instead of the correct MIME type.
For Apache web servers, you will add a .htaccess
file in the same folder as the .oex
file. It will affect the current directory and its sub-directories. You can append to an existing .htaccess
file or create one with the content below.
# OEX
AddType application/x-opera-extension .oex
For Microsoft IIS server, see see Microsoft's documentation on editing MIME types.
Once you work on an extension and release it, that's not usually the end of the story. Over time you will want to add updates, bug fixes, and more features to your extensions. It is also important that once you do release a new version of your extension, users need to be updated to the new version without any hassle. Understanding the auto-update process is important in this regard.
The auto-update process has two steps from a network perspective. First, when the browser triggers the extensions update, it checks if there is an update string stored in config.xml
. The update string looks like this:
<update-description href="http://test.opera.com/api/w3c-wd1/update/opera-configurator-1.0-1/"/>
The receiving server will respond with:
<update-info xmlns="http://www.w3.org/ns/widgets" src="http://test.opera.com/media/extensions/23/235873f76d9245be97481c262e05b8d1.oex" version="1.1">
</update-info>
As implied, src
is where the updated extension is located. It will be downloaded and installed by the browser. In the case where there is no update available, the server will not send anything back.
An extension is identified by an id
stored in config.xml
, for example id="extensions:opera-configurator"
. There is also version
where nothing will be updated if it is already up-to-date. An extension might be updated in the range of 1 to 30 days. You can change the auto-update check interval by going to opera:config#AutoUpdate|UpdateCheckInterval
- the default value is 3 days or 259200 seconds.
The whole update mechanism for Opera extensions can be turned off together with the browser auto-update under opera:config#UserPrefs|LevelOfUpdateAutomation
. If the update server is different than the default Opera URL, an untrusted repository warning will be displayed as shown below:
NOTE: It is essential that the ID attribute is included in the <widget>
element. Without this attribute the update process will not work. Some users have reported crashes when auto-update is performed without an ID attribute.
Full specification of Widget Updates (Note: Update Description, which can be sent via server response in the form of update info, is not supported in Opera 11.)


CASS
Framework Manager
Profile Manager
Resource Alignment
View
Transcript
Timeline
Action
Create
Assertion
Busy...
Invite
Login
Logout
X
Me
Assertions for
Selected Contact
across
All Frameworks
Selected Competency
Competency
<Restricted> ago
,
<Restricted>
claimed
<Restricted>
possessed
Competency
at
Level
with
<Restricted> pieces of evidence
,
and
.
<Restricted> pieces of evidence
Delete
Framework 1
🔒
Loading...
Loading...
Framework 1
Loading...
X
Me
Loading...
No Description.
No Title.
No Description.
Login
An account will automatically be created if none exists.
Login
I,
believe
holds
at a(n)
level with
50
percent confidence.
My evidence is:
My judgment was made at:
And I declare to expire:
with confidence decaying based on a:
Linear Decay
Logarithmic Decay
Exponential Decay
function.
Make Assertion
Visibility
Private
Public
Name of Object
Owners:
X
Me
Viewers:
Evidence
Loading...


Automated testing systems with authentication is tricky. You need to make fake users and let them login to your system or fake the token itself. This is even harder if you are using OAuth systems.
For DotDev I have a set of UI tests that cover many common actions that users perform on the site. It’s important to have several user accounts to test all of the different scenarios. In addition account creation and login is an important aspect which I want to prove against every deployment.
As I do not provide any local login to the site I had to create dummy social accounts. This doesn’t seem too bad but all of the social providers I used have measures in place to prevent bot logins. This made my tests unstable and frustrating to manage.
The alternatives aren’t great
At this point I had two options to try and resolve the issues with UI Test logins.
To build a new way of logging in users for my tests which bypassed OAuth.
This would have been a bit of work, but more to the point it would have been work which had no relevance outside of testing. It also would obscure several critical login systems which I specifically want to test.
Find a provider which did not do all of the bot prevention stuff
This seemed like a better option however It was very hard to find a provider fitting this description. It’s not the kind of thing that a provider would list about themselves and it would have been trial and error to find one. To spite this I tried a few, all of which I eventually discovered had some annoying countermeasure.
Enter NoAuth
I felt the second option was still the right answer to this problem. So I decided to do a mini project to write my own OAuth provider specifically for testing.
NoAuth is an OAuth provider for testing which offers no security guarantees at all. You can log in with any claims you like without the hassles of passwords or security checks.
During your login loop instead of being prompted for a username/password you can enter in a list of claims you want to make. Alternately you can populate a random user from RandomUser.me (which is super awesome by the way). This allows for quick and easy creation of test users with some realistic data, and the ability to test some more complex login paths by using different claims.
NoAuth is open source and avaliable to use for testing your own sites.
In addition to the actual OAuth site, I have build owin bindings to easially integrate noauth into a .net application and some Selenium helpers to make using noauth in your tests easy. I would love some pull requests for integrations with other languages.
I hope it goes without saying, but do not use noauth in production or you’re gunna have a bad time.