sharjeelyunus/github-issues-dataset huggingface dataset:
Repository: pytorch
Issue: I hope Caffe2's python interface add DataLoader Module Similar to pytorch's DataSet and DataLoader
Labels: caffe2

I  abstract the trainable cnn model to three parts:DataInput、 convolution blocks、 output/loss。
Train are mostly use python interface for fast implementation， now caffe2 already have many Various operators like conv、bn、losses, and some data read operators;
I find that no matter it is detection, classification, tracking tasks, ---convolution blocks and output/loss are relatively fixed（mostly use Common Structure like resnet50), but The input part of the network is various, especially in the multi-task problems.That is to say, if we want to implement an idea, the most part we should change is the trian input part(which is only used in train mode, inference's input is just an image)，Deploy in with cpp interface does not require  input part， so the trian input part is Unworthy to implement it in cpp by end users.

So I hope Caffe2's python interface could  add DataLoader Module Similar to pytorch's DataSet and DataLoader, so that we could speed up very mush to Realize our ideas with caffe2 support。

Thank you!
Repository: flutter
Issue: [image_picker] New feature to store picked image/video in a custom path.
Labels: c: new feature,p: image_picker,package,c: proposal,team-ecosystem,P2,triaged-ecosystem

this is image path "/storage/emulated/0/Android/data/com.example.xxxxx/files/Pictures/cd7fa05d-2f01-47ec-b733-d535c2ed50972289172933902660221.jpg".

```
    var image = await ImagePicker.pickImage(source: ImageSource.camera);
    print(image);  //    storage/emulated/0/Android/data/com.example.xxxxx/files/Pictures/cd7fa05d-2f01-47ec-b733-d535c2ed50972289172933902660221.jpg`
```

I want to save the photo in sdCard. but i don't how to resolve it.
Repository: vscode
Issue: Clear all problems in the 'Problems' pane with a button
Labels: feature-request,error-list,languages-diagnostics

Please add a button in the `Problems` pane that allows the developer to clear all items in there.

**Following discussions from #15524, #29169, #66343 and #50448.**

Currently we see problems from different sources (linters, tasks, etc) and they sometimes stay there after the problem or the source file is gone, e.g. problems in an unsaved buffer, in files that were renamed, or files removed when we switch Git branches.

More often than not I have a bunch of problems and the only way to clear that pane is to restart the entire editor.
Repository: flutter
Issue: Navigation with a drawer does not have closing animation
Labels: c: new feature,framework,f: material design,a: quality,has reproducible steps,P2,found in release: 3.3,found in release: 3.7,team-design,triaged-design

Hey,
I'm currently developing a flutter app. Because of its flexibility I use a navigation drawer. I came across multiple tutorials about navigation with a drawer in flutter, but no one was really satisfying. The first approach is to use one Scaffold with multiple layouts inside, like described [here](https://medium.com/@kashifmin/flutter-setting-up-a-navigation-drawer-with-multiple-fragments-widgets-1914fda3c8a8). But like one of the comments says it isn't a clean solution especially in a big app. Another approach is described [here](https://proandroiddev.com/flutter-creating-drawers-e31414f7d71a). It uses multiple Scaffolds and pushes them with `Navigator.of(context).push(...)`. Because of this method you have an animation between pages and are able to use the back button on android. So my question is, if there is a proper solution to use a navigation drawer. Maybe I'm just missing something and there's an example.

Thanks in advance!
Repository: pytorch
Issue: why check ArgumentInfo is_pod? suffer bugs
Labels: module: docs,low priority,triaged

we writing a Mixed C++/CUDA extension(https://pytorch.org/tutorials/advanced/cpp_extension.html)
success compile and running test in pytorch=0.4.1 and python= 3.6
however suffer bug in pytorch=1.0 and python= 3.6 
`anaconda3/envs/python3.6_pytorch1.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct`

in order to success compile ，We have to uncomment/disable line 59-60 in torch/lib/include/torch/csrc/jit/argument_spec.h 
`static_assert(std::is_pod<ArgumentInfo>::value,
  "ArgumentInfo is to be a POD struct");`

SO We wonder is check pod necessary ？ What is the significance of doing this?

THX
Repository: go
Issue: proposal: net/http: add MethodSearch constant for HTTP SEARCH method
Labels: Proposal,Proposal-Hold

### What version of Go are you using (`go version`)?

<pre>
$ go version
go version go1.11.4 darwin/amd64
</pre>

### What operating system and processor architecture are you using (`go env`)?
MacOS/amd64
<details><summary><code>go env</code> Output</summary><br><pre>
$ go env
GOARCH="amd64"
GOBIN=""
GOCACHE="/Users/arthur/Library/Caches/go-build"
GOEXE=""
GOFLAGS=""
GOHOSTARCH="amd64"
GOHOSTOS="darwin"
GOOS="darwin"
GOPATH="/Users/arthur/go"
GOPROXY=""
GORACE=""
GOROOT="/usr/local/Cellar/go/1.11.4/libexec"
GOTMPDIR=""
GOTOOLDIR="/usr/local/Cellar/go/1.11.4/libexec/pkg/tool/darwin_amd64"
GCCGO="gccgo"
CC="clang"
CXX="clang++"
CGO_ENABLED="1"
GOMOD=""
CGO_CFLAGS="-g -O2"
CGO_CPPFLAGS=""
CGO_CXXFLAGS="-g -O2"
CGO_FFLAGS="-g -O2"
CGO_LDFLAGS="-g -O2"
PKG_CONFIG="pkg-config"
GOGCCFLAGS="-fPIC -m64 -pthread -fno-caret-diagnostics -Qunused-arguments -fmessage-length=0 -fdebug-prefix-map=/var/folders/0m/qqy9wr_n4l5_2zhm0fhnp9jw0000gp/T/go-build084923408=/tmp/go-build -gno-record-gcc-switches -fno-common"
</pre></details>

### What did you do?
Added a MethodSearch = "SEARCH" to http/net/method.go, to let developers conveniently use public API, in this particular case constant for http requests in web-apps.

References to RFCs and examples:
https://tools.ietf.org/id/draft-snell-search-method-00.html#search
https://tools.ietf.org/id/draft-snell-search-method-00.html#rfc.section.4.2
Repository: pytorch
Issue: [JIT] Support C++ front end module and JIT interop
Labels: oncall: jit

Creating an issue to track this feature request.

## 🚀 Feature
Allow a C++ front end module to be interop in JIT. (since right now C++ front end module can already be interoped in Python)

## Motivation

TorchScript is ultimately very limited. If I have a module that has complex logic. It would be important to be able to write the whole module in C++ and then be called in Python

## Pitch

This allows Pytorch to be a truly production ready framework

## Alternatives

Currently, we can use C++ custom ops for certain things, but for more complex use cases (for example, if the module has to keep track of complex state - e.g. tracking in robotics). C++ custom ops is un-suitable
Repository: pytorch
Issue: support for multiple torch.cuda.max_memory_allocated() counters
Labels: todo,feature,module: cuda,triaged

## 🚀 Feature

Having multiple resettable torch.cuda.max_memory_allocated() counters

## Motivation

With the help of torch.cuda's `reset_max_memory_allocated` and `max_memory_allocated` one can now measure peak memory usage. Which is very helpful.

Now, there is a need for identical functionality, but supported in multiple and concurrent scopes, where scopes can overlap or be nested, and as such one global counter is not enough.

Scenario 1: an application relying on the normal functioning (pre-reset implementation) max_memory_allocated or max_memory_cached could now malfunction if some other application resets either or both (action a a distance).

Scenario 2: two profilers measuring different scopes. Say one measuring at a function level, another at a wider or narrower scope. Since there is only one counter they will be resetting each other’s measurements. python’s tracemalloc has the same issue, since it doesn’t create an object instance for the counter.

The 2nd scenario is not hypothetical, it’s actually a need I have right now as I have different profilers measuring different scopes. There are in different applications so they can’t really communicate with each other to keep each other in sync with reset calls. e.g. I have one profiler running on the train loop epoch-level, another on the jupyter cell-level, yet another on larger parts of the notebook. And unfortunately, my current peak measuring thread approach is clearly failing to catch all peaks, so it’d be extremely helpful to be able to switch to use max_memory_allocated yet different instances of it in different scopes.

## Pitch

So I need to be able to do something like:
```
max_obj1 = MaxMemoryAllocated()
# run some code 1
for epoch in epochs:
    max_obj2 = MaxMemoryAllocated()
    # run epoch code
    peak_epoch = max_obj2.peak()
# run some code ...
peak = max_obj1.peak()
```
Of course, those would be unrelated applications, this code sample is just demonstrating how their execution will overlap and why the current implementation is insufficient.

## Alternatives

Currently, I spawn a thread per counter that measures peak memory usage via nvml (reading directly nvidia stats). Which doesn't give correct measurements, since it's easy for a thread to miss a peak.

## Additional context

Discussion thread: https://discuss.pytorch.org/t/measuring-peak-memory-usage-tracemalloc-for-pytorch/34067/19

Thank you.
Repository: pytorch
Issue: Complete dtype support for torch.norm
Labels: module: docs,triaged

## 🚀 Feature
<!-- A clear and concise description of the feature proposal -->

After https://github.com/pytorch/pytorch/pull/15414, torhch.norm supports dtype, but not with 'fro' or 'nuc' arguments.  This is confusing and not documented.

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too -->

## Pitch

<!-- A clear and concise description of what you want to happen. -->

## Alternatives

<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->

## Additional context

<!-- Add any other context or screenshots about the feature request here. -->
Repository: opencv
Issue: Throw an exception on namedWindow() if monitor isn't connected or it is ran over SSH
Labels: priority: low,category: highgui-gui

<!--
If you have a question rather than reporting a bug please go to http://answers.opencv.org where you get much faster responses.
If you need further assistance please read [How To Contribute](https://github.com/opencv/opencv/wiki/How_to_contribute).

Please:

* Read the documentation to test with the latest developer build.
* Check if other person has already created the same issue to avoid duplicates. You can comment on it if there already is an issue.
* Try to be as detailed as possible in your report.
* Report only one problem per created issue.


This is a template helping you to create an issue which can be processed as quickly as possible. This is the bug reporting section for the OpenCV library.
-->

##### System information (version)
<!-- Example
- OpenCV => 3.1
- Operating System / Platform => Windows 64 Bit
- Compiler => Visual Studio 2015
-->

- OpenCV => 4.0
- Operating System / Platform => Windows 7 x64, Linux x64
- Compiler => any

##### Detailed description

<!-- your description -->

Feature request: throwing an exception instead of crashing the program with message `QXcbConnection: Could not connect to display`, if the function `cv::namedWindow()` or `cv::imshow()` is called on computer without monitor or if it is run over SSH.

##### Steps to reproduce

<!-- to add code example fence it with triple backticks and optional file extension
    ```.cpp
    // C++ code example
    ```
 or attach as .txt or .zip file
-->

For example, I want to write `cv::mat` to the `output.jpg` file instead of crash the program  if a monitor isn't connected or if I run it over SSH:

```cpp
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace cv;
using namespace std;

int main( int argc, char** argv )
{
    if( argc != 2) return -1;
    Mat image = imread(argv[1], CV_LOAD_IMAGE_COLOR); 
    if(! image.data )  return -1;
    try {
        namedWindow( "Display window", WINDOW_AUTOSIZE ); // throw an exception instead of crash
        imshow( "Display window", image );
        waitKey(0);
    } catch(...) {
       imwrite( "output.jpg", image );
    }
    return 0;
}
```
Repository: godot
Issue: Add ability to unload resource from ResourceInteractiveLoader
Labels: enhancement,topic:core,documentation

**Godot version:** 3.1 beta

**OS/device including version:** Windows 10

**Issue description:**
I have an application that loads sometimes from the same file and saves to the same file, in one area of the application it uses a ResourceInteractiveLoader and in another area it just uses ResourceLoader.  I was struggling to save to the file when it was loaded with ResourceInteractiveLoader, and was pointed in the right direction to that file being locked on Windows 10.  

The hackish work around I discovered was to just load a dummy file with ResourceInteractiveLoader, which unlocked the file.

My suggestion is, is adding an Unload flag to get_resource( ), or a method to ResourceInteractiveLoader, that is unload_resource()
Repository: go
Issue: x/website/internal/dl: store the list of validUsers in a more dynamic way
Labels: NeedsInvestigation

The list of validUsers is hardcoded at https://github.com/golang/tools/blob/master/godoc/dl/dl.go#L317. This means that every time someone is doing a release for a first time, we need to make a CL to add them to this list (so that they can run the release command) and redeploy golang.org.

We may want to store this list in a more dynamic way.
Repository: TypeScript
Issue: Add type definitions for Files And Directories API
Labels: Suggestion,In Discussion,Help Wanted,Domain: lib.d.ts

## Search Terms

<!-- List of keywords you searched for before creating this issue. Write them down here so that others can find this suggestion more easily -->
`"Files And Directories API"`
`FileSystemFileEntry`

## Suggestion

Add types for the Files And Directories API:  https://wicg.github.io/entries-api/

Specifically:
* `FileSystemEntry`
* `FileSystemDirectoryEntry`
* `FileSystemDirectoryReader`
* `FileSystemFileEntry`
* `FileSystem`

## Use Cases

Handling drag/drop of multiple files and/or folders, and gleaning extra information about the dropped files (which is what the API provides).

## Checklist

My suggestion meets these guidelines:

* [x] This wouldn't be a breaking change in existing TypeScript/JavaScript code
* [x] This wouldn't change the runtime behavior of existing JavaScript code
* [x] This could be implemented without emitting different JS based on the types of the expressions
* [x] This isn't a runtime feature (e.g. library functionality, non-ECMAScript syntax with JavaScript output, etc.)
* [x] This feature would agree with the rest of [TypeScript's Design Goals](https://github.com/Microsoft/TypeScript/wiki/TypeScript-Design-Goals).
Repository: scrcpy
Issue: USB devices freeze occasionally when scrcp is running
Labels: usb

Hi.

I discovered scrcpy just today, and it's really great and almost flawless so far!
The only thing I found to be annoying is that, when scrcpy is up¹, my USB devices(?) seem to die every now and then. Most noticibly, I had to unplug and re-plug my mouse and keyboard for over 10 times today as they just froze (usually at the same time) and kept spamming inputs.

**Where it occured:** Two unrelated Windows 10 (1809) computers.

For this to happen it doesn't even matter whether I'm operating inside the scrcpy window or not. scrcpy just has to be running in the background.

If there's anything I can send in for further investigation (like debug logs or some sort of USB crash dumps?), let me know.


¹it happened today for the first time and on two different computers, so it's gotta be scrcpy
Repository: rust
Issue: Confusing compiler error when iterating over Option<IntoIterator>
Labels: C-enhancement,A-diagnostics,P-low,T-compiler,D-papercut

I recently wrote a type that implemented IntoIterator with a tuple as the Item type. I then tried to test this by using this iterator in a for loop. I got the following error:

```
     for (i, j) in foo
         ^^^^^^ expected struct `MyIter`, found tuple
```

This left me confused, because I had assumed that foo's type was MyIter. Why was the iterator returning itself, instead of the item type I had specified? I began to suspect my implementation of IntoIterator before I realized that foo was actually `Option<MyIter>`. As it turns out, Option also implements IntoIterator (#27996), so the compiler thought I was trying to iterate over the Option instead of the enclosed type!

It'd be nice if there were a note associated with the compiler error in cases where the iterator is type `Option<T : IntoIterator>`. Something like this, maybe?

```
"Note: `iter` is `Option<MyIter>`. Did you forget to unwrap?"
```

Simple reproduction of the compiler error:

https://play.rust-lang.org/?version=nightly&mode=debug&edition=2018&gist=4432a78517e24ea649a31c7246b34edd
Repository: pytorch
Issue: Confusing documentation with distributions.Categorical about logits
Labels: module: distributions,module: docs,triaged

## 📚 Documentation

<!-- A clear and concise description of what content in https://pytorch.org/docs is an issue. If this has to do with the general https://pytorch.org website, please file an issue at https://github.com/pytorch/pytorch.github.io/issues/new/choose instead. If this has to do with https://pytorch.org/tutorials, please file an issue at https://github.com/pytorch/tutorials/issues/new -->
![screenshot_2019-01-24 probability distributions - torch distributions pytorch master documentation](https://user-images.githubusercontent.com/5520155/51647989-eadf7780-1f4c-11e9-8a6a-a3310705513e.png)

The [documentation for Categorical distributions](https://pytorch.org/docs/stable/distributions.html) states that it can take logits, which it calls "event log **probabilities**". I think this should either be log odds. This is minor but the terminology with logits is confusing enough already.
Repository: pytorch
Issue: Unexpected behavior of jit.trace when PYTORCH_JIT=0
Labels: oncall: jit,low priority

One of the biggest uses of tracing is to save a snapshot of a computation graph. However, when `PYTORCH_JIT=0` (debug mode on), the input function/module of `jit.trace` is simply returned, causing undesired behavior when users expect a snapshot is saved. E.g., the following code snippets behave differently when the flag is set/unset: 
1. Save a training graph & a eval graph:
   ```py
   net.train()
   saved_train = torch.jit.trace(net, ...)
   net.eval()
   saved_eval = torch.jit.trace(net, ...)
   # and proceed to use saved_train and saved_eval 
   # assuming they are fixed graphs corresponding to the two modes
   ```
2. Save a graph with a set of substituted weights:
   ```py
   original_ws = [conv.w for conv in net.convs]
   # substitute with new weights
   for new_w, conv in zip(new_ws, net.convs):
     conv.w = new_w
   graph_with_new_weights = jit.trace(net, ...)
   for original_w, conv in zip(original_ws, net.convs):
     conv.w = original_w
   ```
3. Crazy things like `read_next_network_from_disk_and_run()`.

The "ideal" solution would be to save a copy of all things the traced function can possibly access, but this approach is obviously not practical (we would need to save the entire internet if the function runs file downloaded from a random url). After a discussion with @apaszke , we think it makes sense to implement the following best-effort mechanism for `jit.trace` when `PYTORCH_JIT=0` (JIT is disabled):

1. A `jit.trace(fn, ...)` call will issue a warning. 
2. It will return something that contains both the traced (unoptimized) graph and the original `fn`.
3. When that thing is called, it calls the original `fn` with the given new inputs, trace the call, and raise if the graph and/or leaf nodes that aren’t inputs is different from those of the saved graph.

It's worth noting that even with this mechanism, there is still difference wrt when `fn` is run (see table below), but that's really unavoidable. We should make it really clear in the docs and the warning message.

|  |`PYTORCH_JIT=1` (default) | Current `PYTORCH_JIT=0` | Proposed `PYTORCH_JIT=0`  |
| :-: |:----------: |:-------------:| :-----:|
| `traced = jit.trace(fn,...)` |   `fn(...)` is called  | - |  `fn(...)` is called |
| `traced(...)` | -  |   `fn(...)` is called   |   `fn(...)` is called |
Repository: pytorch
Issue: caffe2::CudnnConvOp::RunOnDevice() fails on Squeezenet
Labels: caffe2

## 🐛 Bug

`caffe2::CudnnConvOp::RunOnDevice()` fails on Squeezenet

## To Reproduce

Steps to reproduce the behavior:

1. Unzip and copy [test_trt.zip](https://github.com/pytorch/pytorch/files/2790075/test_trt.zip) to `caffe2/python/trt/`

2. Run `test_trt.TensorRTTransformTest.test_squeezenet_core test:

```
Error
Traceback (most recent call last):
  File "/home/snikolaev/anaconda3/lib/python3.6/unittest/case.py", line 59, in testPartExecutor
    yield
  File "/home/snikolaev/anaconda3/lib/python3.6/unittest/case.py", line 605, in run
    testMethod()
  File "/home/snikolaev/pytorch2/caffe2/python/trt/test_trt.py", line 668, in test_squeezenet_core
    workspace.RunNet(pred_net.name)
  File "/home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/workspace.py", line 236, in RunNet
    StringifyNetName(name), num_iter, allow_fail,
  File "/home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/workspace.py", line 197, in CallWithExceptionIntercept
    return func(*args, **kwargs)
RuntimeError: [enforce fail at conv_op_cudnn.cc:522] X.dim() >= 3 && X.dim() <= 5. 
Error from operator: 
input: "data" input: "conv1_w" input: "conv1_b" output: "conv1" type: "Conv" arg { name: "stride" i: 2 } arg { name: "pad" i: 0 } arg { name: "kernel" i: 3 } device_option { device_type: 1 device_id: 0 } engine: "CUDNN"frame #0: <unknown function> + 0x3e075 (0x7f3ee48fc075 in /home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #1: std::function<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > ()>::operator()() const + 0x4c (0x7f3ee48fc504 in /home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #2: c10::ThrowEnforceNotMet(char const*, int, char const*, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, void const*) + 0x57 (0x7f3ee48fbbf4 in /home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #3: bool caffe2::CudnnConvOp::DoRunWithType<float, float, float, float>() + 0xf9 (0x7f3ee8b43d25 in /home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/../../torch/lib/libcaffe2_gpu.so)
frame #4: caffe2::CudnnConvOp::RunOnDevice() + 0x4e (0x7f3ee8b3c6c2 in /home/snikolaev/anaconda3/lib/python3.6/site-packages/caffe2/python/../../torch/lib/libcaffe2_gpu.so)
```