UpdateFun | Android APP update library./android app自动检测更新库 | Android library
kandi X-RAY | UpdateFun Summary
kandi X-RAY | UpdateFun Summary
Android APP update library./android app自动检测更新库
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Top functions reviewed by kandi - BETA
- Run the download
- Gets the external cache directory
- Get cache directory
- Runs the data
- Extract data from the result
- Check apk
- Returns the package name of an APK
- Initializes the activity s state
- Initializes the UpdateFunGO
- Initializes the tv view
- Run the update
- Initializes the DownloadKey
- Starts the apk installation
- Get the current application version name
- Get the icon for the application
UpdateFun Key Features
UpdateFun Examples and Code Snippets
Community Discussions
Trending Discussions on UpdateFun
QUESTION
I'm writing a parser and a type checker in Haskell starting from BNFC. The main function of the type checker is implemented as follows:
...ANSWER
Answered 2017-Sep-27 at 20:16As mostly covered in @mb14's comments, the usual method involves doing two things:
- First, instead of returning either a type-checked tree or an error, be prepared to always return a type-checked tree together with a log of zero or more errors. This is easily accomplished with a
Writer
monad. - Second, whenever an error is detected, log the error, try to recover by assuming some valid type for the node being type-checked, and continue the type check.
In this simple scheme, the type checking always returns a typed tree. If the log of error messages is empty, the type check has succeeded, and the typed tree is valid. Otherwise, the type check has failed with the given set of errors, and the typed tree can be discarded. In a more complex scheme, you could differentiate between warnings and errors in your log, and consider the type checking to have succeeded if it contains zero or more warnings, but no errors.
I've included a complete example of the technique below for a very simplified grammar. It only returns the top-level type instead of the typed tree, but this is just to keep the code simple -- returning a type-checked tree is not difficult. The hard part in adapting it to your grammar will be determining how to forge ahead (i.e., what valid type to supply) when an error occurs, and it will be highly dependent on the details of your program. Some general techniques are illustrated below:
- If a node always returns a particular type (e.g.,
Len
below), always assume that type for the node, even if the node doesn't type-check. - If a node combines compatible types to determine its result type (e.g,
Plus
below, or a BNF alternation), then when a type incompatibility is detected, take the type of the node to be determined by the type of its first argument.
Anyway, here is the complete example:
QUESTION
I am new to reactjs.
What is the proper way to pass the parent value to child setState
, I am having error says below, and I am unable to change input value, the value looks correct but unable to be changed.
..."is changing an uncontrolled input of type text to be controlled. Input elements should not switch from uncontrolled to controlled (or vice versa). Decide between using a controlled or uncontrolled input element for the lifetime of the component"
ANSWER
Answered 2017-Aug-01 at 12:53You need to use defaultValue
instead of value
. Also you must add onChange
handler to your input. To handle input changes.
Child example
QUESTION
I implement classic image classification problem with tensorflow, I have 9 classes, first I use softmax_cross_entropy_with_logits
as classifier and train network, after some steps it gives to about 99% train accuracy,
Then test the same problem with sparse_softmax_cross_entropy_with_logits
this time it doesn't converge at all,(train accuracy is around 0.10 and 0.20)
Only for your information, for softmax_cross_entropy_with_logits
, I use [batch_size, num_classes] with dtype float32 for labels, and for sparse_softmax_cross_entropy_with_logits
I use [batch_size] with dtype int32 for labels.
Does anybody have any idea?
Update:
...ANSWER
Answered 2017-Apr-15 at 17:14I found the problem, thanks to @mrry for helpful comment, actually I mistake about calculation of accuracy, in fact, "sparse_softmax" and "softmax" has the same loss(or cost) for input logits,
for computation accuracy, I change
correct_pred = tf.equal(tf.argmax(self.score_,1), tf.argmax(y,1))
to
correct_pred = tf.equal(tf.argmax(self.score_,1), y ))
since in "sparse_softmax" the ground truth labels are not in one-hot vector format, but real int32 or int64 numbers.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install UpdateFun
You can use UpdateFun like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the UpdateFun component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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