[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Implement Depth-First Execution with Mapping Currently each "level" of a mapped pipeline is executed before proceeding to the next level. This is undesirable especially for pipelines where it's important that each "branch" of the pipeline finish as quickly as possible. To implement DFE, we'll need to rearrange two things: - how mapped work gets submitted (it should start being submitted from the Flow Runner not the Task Runner) - in order to submit work to Dask and let Dask handle the DFE scheduling, we'll want to refactor how we walk the DAG and wait to determine the width of a pipeline before we submit it (because mapping is fully dynamic we can only ascertain this width at runtime) We'll need to be vigilant about: - performance - retries - result handling Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Using "pid: host" with override files no longer works in 1.9 I'm setting `pid: host` for one of the services in my docker-compose.yml file. This works as expected if I just use this file -- however, if I apply an override file, this option no longer works and the container will have its own PID namespace. This was working in 1.8, so this appears to be a regression. Adding `pid: host` to the override file does not appear to resolve the problem. There may be other settings that are also being overridden incorrectly as a result of this regression. The example below demonstrates this -- the PID printed by the container's entrypoint.sh script is a very low number because it is running in its own PID namespace. If I don't use the override file, the PID printed is a much higher number because it is in the host's namespace. I'll poke around in a few days if I get a chance to see what recent changes could have caused this. For the moment I've reverted to 1.8. ``` $ docker-compose -f docker-compose.yml -f docker-compose-prod.yml up --build Building netconfig ... Attaching to dockercomposeerror_netconfig_1 netconfig_1 | My PID = 6 ``` ``` $ docker-compose -f docker-compose.yml up --build Building netconfig ... Attaching to dockercomposeerror_netconfig_1 netconfig_1 | My PID = 22083 ``` Example files: **docker-compose.yml** ``` version: '2' services: netconfig: build: . privileged: true pid: host ``` **docker-compose-prod.yml** ``` version: '2' services: netconfig: ports: - "179:179/tcp" - "1194:1194/udp" ``` **Dockerfile** ``` FROM debian:stable ADD entrypoint.sh /test/entrypoint.sh CMD bash /test/entrypoint.sh ``` **entrypoint.sh** ``` #!/bin/bash echo "My PID = $$" ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Nbconvert, default_preprocessors to list of dotted name not list of obj in some places in nbconvert we have default that are list of object. they should be list of `DottedObject` (strings). Which is probably easier to configure, and does not lead to the following in config files ... ``` # List of preprocessors available by default, by name, namespace, instance, or # type. # c.TemplateExporter.default_preprocessors = [<function wrappedfunc at 0x106d86d70>, <class 'IPython.nbconvert.preprocessors.svg2pdf.SVG2PDFPreprocessor'>, <class 'IPython.nbconvert.preprocessors.extractoutput.ExtractOutputPreprocessor'>, <class 'IPython.nbconvert.preprocessors.csshtmlheader.CSSHTMLHeaderPreprocessor'>, <class 'IPython.nbconvert.preprocessors.revealhelp.RevealHelpPreprocessor'>, <class 'IPython.nbconvert.preprocessors.latex.LatexPreprocessor'>, <class 'IPython.nbconvert.preprocessors.highlightmagics.HighlightMagicsPreprocessor'>] ``` nothing prevent us from also supporting directly object/fucntions ... Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: basis_gates not being passed to JSON unroller Currently there the `basis_gates` argument of the `compile` function is ignored when compiling circuits to JSON. This fix simply passes the value of basis gates to the dag2json compiler so that the JSON can be compiled in a user specified set of basis_gates as intended. ## Expected Behavior When you run `QuantumProgram.compile('circuit', basis_gates='a,b,c,d')` the resulting qobj should compile using the basis gates `a,b,c,d`. ## Current Behavior When you run `QuantumProgram.compile('circuit', basis_gates='a,b,c,d')` the JSON unroller is always passed `basis_gates='u1,u2,u3,cx,id` instead. ## Possible Solution Will add pull request to fix this by adding basis_gates argument to the `dag2json` function in `_openquantumcompiler.py`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: SparsePauliOp causes bugs in e.g. commutators. <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: 0.18 - **Python version**: 3.8 - **Operating system**: MacOS ### What is the current behavior? The `SparsePauliOp` does not handle coefficients correctly or is used against its specification in opflow. With the help of @Cryoris we noticed the following: ``` >>> SparsePauliOp(Pauli('iZ')) == SparsePauliOp(Pauli('-iZ')) True >>> SparsePauliOp(Pauli('iZ')) == SparsePauliOp(Pauli('Z')) True ``` which is probably the root of the problem with, e.g., the commutator below. ### Steps to reproduce the problem ``` X Out[189]: PauliOp(Pauli('X'), coeff=1.0) Y Out[190]: PauliOp(Pauli('Y'), coeff=1.0) v = commutator(X,Y) v Out[192]: PauliSumOp(SparsePauliOp([[False, False]], coeffs=[0.+0.j]), coeff=1.0) v.equals(2j*Z) Out[193]: False ``` The same problem occurs by a direct calculation: ``` w = X@Y - Y@X w Out[205]: PauliSumOp(SparsePauliOp([[False, True], [False, True]], coeffs=[ 1.+0.j, -1.+0.j]), coeff=1.0) w.equals(2j*Z) Out[206]: False ``` ### What is the expected behavior? ``` >>> SparsePauliOp(Pauli('iZ')) == SparsePauliOp(Pauli('-iZ')) False >>> SparsePauliOp(Pauli('iZ')) == SparsePauliOp(Pauli('Z')) False ``` Or handling it differently in opflow. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: Mismatch between CLIP fast and non-fast tokenizers ### System Info - `transformers` version: 4.26.1 - Platform: Windows-10-10.0.22621-SP0 - Python version: 3.8.1 - Huggingface_hub version: 0.11.0 - PyTorch version (GPU?): 1.12.1+cu116 (True) - Tensorflow version (GPU?): not installed (NA) - Flax version (CPU?/GPU?/TPU?): not installed (NA) - Jax version: not installed - JaxLib version: not installed - Using GPU in script?: no - Using distributed or parallel set-up in script?: no ### Who can help? @ArthurZucker @younesbelkada @sgugger ### Information - [ ] The official example scripts - [X] My own modified scripts ### Tasks - [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction Here is a minimal working example to show the mismatch: ```python from transformers import AutoTokenizer tokenizer_fast = AutoTokenizer.from_pretrained('openai/clip-vit-base-patch16', use_fast=True) tokenizer = AutoTokenizer.from_pretrained('openai/clip-vit-base-patch16', use_fast=False) text = "You should've done this" print(tokenizer(text)) print(tokenizer_fast(text)) print(tokenizer(text) == tokenizer_fast(text)) # Outputs: # {'input_ids': [49406, 592, 1535, 262, 563, 1700, 589, 49407], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1]} # {'input_ids': [49406, 592, 1535, 1200, 1700, 589, 49407], 'attention_mask': [1, 1, 1, 1, 1, 1, 1]} # False ``` It appears to stem from the `'ve` token. ### Expected behavior The non-fast tokenization should match the fast tokenization (https://github.com/huggingface/tokenizers) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: Improperly-formatted docstring for numpy.lib.format.descr_to_dtype The docstring for `numpy.lib.format.descr_to_dtype` does not conform to the `numpydoc` standard. Currently the docstring is not included in the documentation generated by sphinx. ### Numpy/Python version information: 1.20.0.dev0+e7adb14 3.8.3 (default, May 17 2020, 18:15:42) [GCC 10.1.0] Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [BUG] Conan Tools does not export detected_os To help us debug your issue please explain: When I was updating cmake_installer, I just found that `detected_os` is not exported by conans.tools Conan Version 1.15.0 ```python from conans import tools if __name__ == "__main__": tools.detected_os() ``` **ERROR**: ``` Traceback (most recent call last): File "conanfile.py", line 4, in <module> tools.detected_os() AttributeError: module 'conans.tools' has no attribute 'detected_os' ``` - [X] I've read the [CONTRIBUTING guide](https://github.com/conan-io/conan/blob/develop/.github/CONTRIBUTING.md). - [X] I've specified the Conan version, operating system version and any tool that can be relevant. - [X] I've explained the steps to reproduce the error or the motivation/use case of the question/suggestion. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Working with multiple Windows containers: The semaphore timeout period has expired. Starting twelve containers with docker-compose 1.9.0-rc2 still shows a problem. Follow up of #4082 ``` PS C:\xxxxx> docker-compose up -d Creating xxxxx_consul_1 Creating xxxxx_db_1 Creating xxxxx_service1_1 Creating xxxxx_service2_1 Creating xxxxx_service3_1 Creating xxxxx_service4_1 Creating xxxxx_service5_1 Creating xxxxx_cli_1 ERROR: for service6 (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') ERROR: for service7 (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') ERROR: for service8 (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') ERROR: for service9 (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') ERROR: for service3 (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') Traceback (most recent call last): File "<string>", line 3, in <module> File "compose\cli\main.py", line 65, in main File "compose\cli\main.py", line 117, in perform_command File "compose\cli\main.py", line 849, in up File "compose\project.py", line 400, in up File "compose\parallel.py", line 64, in parallel_execute pywintypes.error: (121, 'WaitNamedPipe', 'The semaphore timeout period has expired.') docker-compose returned -1 PS C:\xxxxx> docker-compose --version docker-compose version 1.9.0-rc2, build d41f869 ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: Problem: conda-build doesn't clean up temporary files @gabm commented on [Thu Aug 17 2017](https://github.com/conda/conda-build/issues/2289) It seems conda-build doesn't clean up temporary files located under `/tmp/tmpxxxxxx` or `User/../AppData/Local/tmpxxxxxx` on windows. After the build these folders contain the decompressed packages that I suppose have been installed as dependencies during the build. Maybe its also a conda problem?! Anyway, on our Windows build machine we accumulated 25Gb within some weeks .... --- @gabm commented on [Thu Aug 17 2017](https://github.com/conda/conda-build/issues/2289#issuecomment-323134590) .. the same files are located again in `miniconda3/pkgs`... --- @msarahan commented on [Thu Aug 17 2017](https://github.com/conda/conda-build/issues/2289#issuecomment-323158750) Conda-build uses this functionality in conda for temporary folders: https://github.com/conda/conda/blob/dbe99de1d45206c5d6f2e19017a9e2466f81dc6d/conda/compat.py#L23-L67 When we get files from packages, we do so with the package_has_file function: https://github.com/conda/conda-build/blob/master/conda_build/utils.py#L714-L730 package_has_file does not ever extract the whole package. This seems like a conda issue. Sorry, I don't currently have time to investigate this more. I can move this issue to the conda repo if you'd like. --- @gabm commented on [Thu Aug 17 2017](https://github.com/conda/conda-build/issues/2289#issuecomment-323170508) ok, then please move it there... If I find time, I'll have a further look. I realised some strange folders `/tmp/tmpxxxxxxx` some weeks ago, so could be easy to reproduce... Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: /parallel/apps/launcher.py error IPython 1.1.0 starting at line 956: def write_job_file(self, n): job = IPEngineSetJob(parent=self) ``` for i in range(n): t = IPEngineTask(parent=self) ``` get keyword errors because IPEngineSetJob and PEngineTask do not have 'parent' in winhpcjob.py: Also, winhpcjob.py uses regEx and tries to pass unicode when run under python 3. This results in error Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: conda search should do partial name searches (regression) The behavior of `conda search` used to be that `conda search X` would show all packages whose name contained the string `X`. There was a `-f` flag to search for full names. Now it seems you have to explicitly add `*` to either side of the string to do a partial name search. I get that search now accepts a general package spec, but adding stars is annoying and unintuitive to beginner users. The most common desired behavior is to search for substrings. This is how the search functionality for every other package manager that I've used works (`pip search`, `apt-cache search`, `yum search`, `brew search`, `fink list`, `cabal list`, I'm sure you could find and try others) I would suggest making search do a partial match search by default, as long as the search string doesn't include characters that would indicate it's a more general package spec. It can also use the `-f` flag, which was apparently kept but hidden from the help, to override this behavior. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: New field `network_mode` for v2 format Currently we support `host`, `bridge` and `none` as special cases in the list of networks, and we don't support `net: container:...` or `net: service:...`. The new `network_mode` field would be a single scalar string value which supports any of the above, and we would remove this support from the `networks` field. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: ModelCheckpoint Filepath Doesn't Use Logger Save Dir # 🐛 Bug Not sure if this is intended, but the model checkpoint isn't using the same directory as the logger, even if the logger exists. I would have expected this line [here](https://github.com/PyTorchLightning/pytorch-lightning/blob/588ad8377167c0b7d29cf4f362dbf42015f7568d/pytorch_lightning/trainer/callback_config.py#L28) to be `self.logger.save_dir` instead of `self.default_save_path`. Thank you, -Collin Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: using `DaskExecutor` is noisy `dask.distributed` is very verbose with its logging, which is a good thing; however, for newer users (especially those unfamiliar with dask distributed), this can be scary. We could potentially silence all logs that are not "CRITICAL" level by default, with a kwarg that allows this to be toggled during development. Another set of logs come from dangling connections / streams and tend to look like: ```python-traceback tornado.iostream.StreamClosedError: Stream is closed ... distributed.comm.core.CommClosedError: in <closed TCP>: ConnectionResetError: [Errno 54] Connection reset by peer ... ``` [these are innocuous](https://github.com/dask/distributed/issues/2220#issuecomment-417075131) but annoying; it would be a good research task to dig into this and see if we can find the source, for our own peace of mind that we clean up our processes appropriately. **cc:** @joshmeek Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: 'ExtractJob.destination_uri_file_counts' docstring copy pasta In #5241, @yiga2 reported: > BTW, there is also an issue with the documentation - see discrepancy @ > https://google-cloud-python.readthedocs.io/en/latest/bigquery/reference.html#google.cloud.bigquery.job.ExtractJob.destination_uri_file_counts and elaborated later: > For the doc, it seems `Returns: number of DML rows affected by the job, or None if job is not yet complete.` is from another property. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the explosion/spaCy codebase. Here's the problem: Lemmatizer exceptions: `lemma_strings` get sorted anyway Lemmatization exceptions have been working inconsistently, even when they are added directly in `corpora/en/wordnet/dict/verb.exc` The minimal test case of `coping` at https://github.com/explosion/spaCy/issues/389 reveals that, at https://github.com/explosion/spaCy/blob/master/spacy/lemmatizer.py#L94, the lemmatizer's list of potential forms (where the thing in lemmatizer.exceptions is item [0]) is cast to a `set` (and so loses ordering); then in https://github.com/explosion/spaCy/blob/master/spacy/morphology.pyx#L149, that `set` gets sorted. So lemmatizer exceptions only work if they also come first alphabetically! I've implemented the fix for this, but I need this issue in order to submit the PR! One question, though, for @honnibal: this can be fixed either as I did it locally -- return the whole list, with exceptions and then anything that comes back from the lemmatizer's `rules` -- or skip the rules altogether if we used an exception. I think it's more useful downstream if we keep all lemma candidates, even if we're not using them in the default pipeline. But it also seems only destructive to do `sorted(set())` on them! Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: No Mass Delete Option for Task Instances Similar to What DAGRuns Have in UI ### Apache Airflow version 2.1.3 (latest released) ### Operating System macOS Big Sur 11.3.1 ### Versions of Apache Airflow Providers n/a ### Deployment Astronomer ### Deployment details default Astronomer deployment with some test DAGs ### What happened In the UI for DAGRuns there are checkboxes that allow multiple DAGRuns to be selected. ![image](https://user-images.githubusercontent.com/89415310/133841290-94cda771-9bb3-4677-8530-8c2861525719.png) Within the Actions menu on this same view, there is a Delete option which allows multiple DAGRuns to be deleted at the same time. ![image](https://user-images.githubusercontent.com/89415310/133841362-3c7fc81d-a823-4f41-8b1d-64be425810ce.png) Task instance view on the UI does not offer the same option, even though Task Instances can be individually deleted with the trash can button. ![image](https://user-images.githubusercontent.com/89415310/133841442-3fee0930-a6bb-4035-b172-1d10b85f3bf6.png) ### What you expected to happen I expect that the Task Instances can also be bulk deleted, in the same way that DAGRuns can be. ### How to reproduce Open up Task Instance and DAGRun views from the Browse tab and compare the options in the Actions dropdown menus. ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: [ENH] Compare environments I find I am often in a situation where I want to know if my current Conda environment matches the environment specification of an `environment.yml` file or a `requirements.txt` file or some other specification of Conda packages. Why? Because as much as I love Conda environments, sometimes I'd like to know: *"Can I just run this in my current environment without changing anything? Because if so, then I know others can also run this thing in this same environment that I know they have access to, rather than having to complicate my life and theirs with instructions on how to augment their current environment appropriately."* So off the top of my head this would mean the ability to do something like: ``` conda compare environment.yml # report on delta between current environment and environment.yml conda compare foo bar # where foo and bar are two named environments ``` But as it stands I end up writing some complicated `conda list -e | grep` statements by hand, after doing `cat environment.yml`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: When COMPOSE_HTTP_TIMEOUT is reached the exit code should be non-zero We often run into timeout issues when using `docker-compose` in [circleci](https://circleci.com/) to run unit tests, for example: ``` $docker-compose run yiic create_unit_test_db ERROR: An HTTP request took too long to complete. Retry with --verbose to obtain debug information. If you encounter this issue regularly because of slow network conditions, consider setting COMPOSE_HTTP_TIMEOUT to a higher value (current value: 60). ``` The problem is that the exit code that `docker-compose` returns is zero, meaning the build continues, whereas it should be stopped. --- compose v1.5.0. It was installed with `sudo pip install --upgrade docker-compose` as part of the `circle.yml` file. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: save_pretrained crashes when torch_dtype is passed If you have the following code ``` p = pipeline(... torch_dtype=torch.bfloat16) p.save_pretrained() ``` you get a crash because `torch.bfloat16` is not json serializable in the `tokenizer.save_pretrained()` method. This PR fixes this. @Narsil @ArthurZucker Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Drop Python 3.5 support Dask (and Dask Distributed) are core dependencies of Prefect and [have dropped Python 3.5](https://github.com/dask/dask/issues/5478) support. This means that all Prefect users are effectively stuck on old versions of dask with Prefect. Given that, and given the occasional frustration of supporting Python 3.5 (typing, dict ordering, etc.) I'd like to open up a discussion for whether we should continue supporting 3.5 or not. To be clear, if users are not using dask executors or hooks, then they might not care. If you are a user who requires 3.5 support please chime in here so we can assess this decision! Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: logger does not reload ``` import logging; import sys logging.basicConfig(stream=sys.stdout, level=logging.DEBUG) transpile(circuit, coupling_map=coupling_map, optimization_level=0) ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: conda config --set show_channel_urls yes doesn't work anymore This is happening since the latest conda update: ``` bat λ conda config --set show_channel_urls yes Error: Key: show_channel_urls; yes is not a YAML boolean. ``` It happens with both conda 4.1.1 (local windows py 3.5) and 4.1.0 (appveyor, https://ci.appveyor.com/project/mdboom/matplotlib/build/1.0.1774) and it worked with 4.0.8 (https://ci.appveyor.com/project/mdboom/matplotlib/build/1.0.1765/job/bkldg98f8p087xmf) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Clean up methods which return self See https://github.com/GoogleCloudPlatform/gcloud-python/pull/770/files#r27422508 `return self` is a JavaScript-y method chaining construct. In Python ``` python foo = Foo() foo2 = foo.update() ``` indicates that `foo2` is indeed a `Foo` object, but that `foo.update()` has applied the changes without mutating `foo`. Using `return self` breaks that expectation. For example on `list` ``` python >>> a = [3, -4, 1, 0] >>> b = a.sort() >>> b is None True >>> a [-4, 0, 1, 3] ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: The extract_objects() method warns unconditionally Starting from 0.36.0, this code: solver_objects = libemeus.extract_objects(solver_sources) where `solver_sources` is an array with a subset of sources used by a library, generates a warning when running Meson: ```` Single object files can not be extracted in Unity builds. You can only extract all the object files at once. ```` This happens regardless of whether I pass `--unity` or not, and even if I wrap the `extract_objects()` call under a: if not meson.is_unity() ... endif This does not happen with Meson < 0.36.0, and being able to extract a subset of objects is useful when writing tests for a specific internal API. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: [Metrics] Bleu ## 🚀 Feature Implement BLEU Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: Dependency for generators I was having a look at the port of protobuf-c to meson and one issue they build an executable that is passed as a command line param to the generator in this format: ``` gen_protobuf_c = generator(protoc, output : ['@BASENAME@.pb-c.c', '@BASENAME@.pb-c.h'], arguments : ['--proto_path=@CURRENT_SOURCE_DIR@', '--plugin=protoc-gen-c=@0@'.format(protoc_gen_c.full_path()), '--cpp_out=@BUILD_DIR@', @INPUT@']) ``` When I try to use the generator it does not find the protoc_gen_c yet, I think we need a way to tell the generator that the executable has to be ready before calling it. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Adapt the`Result` API to the new backend result format after the introduction of Qobj. <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? The format of the results is going to need some changes due to the introduction of `Qobj` in 0.6. The `Result` class needs to be updated to be able to cope with the changes - actually, it will need to understand both the new format and the old format during the transition. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: np.broadcast_to regression in the latest JAX version The new version 0.1.47 introduces a regression where `np.broadcast_to(1, (3, 2))` throws the error `AttributeError: 'int' object has no attribute 'ndim'`. cc @mattjj @neerajprad Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: reduce test warnings ## What does this PR do? Try to ignore all these warnings... ``` tests/models/test_cpu.py::test_early_stopping_cpu_model | 318s -- | -- 1700 | /drone/src/pytorch_lightning/utilities/distributed.py:23: RuntimeWarning: 2.5854711532592773 is supposed to be a torch.Tensor. Saving checkpoint may not work correctly. HINT: check the value of val_loss in your validation loop | 318s 1701 | warnings.warn(*args, **kwargs) ``` but it would be better to fix them instead ## PR review Anyone in the community is free to review the PR once the tests have passed. If we didn't discuss your PR in Github issues there's a high chance it will not be merged. ## Did you have fun? Make sure you had fun coding 🙃 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: CLI "Login successful" should print green `prefect auth login` should print a green `"Login successful"` confirmation. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: String literals cannot contain literal '\n' At the moment, `\\` is replaced by `\` before handling of `\n`. This means string literals cannot be made with the sequence `\n` in them. For instance, ~~~Meson message('c:\\fun\\name') ~~~ results in a string where there is a newline between 'fun' and 'ame'. Perhaps something along the lines of: ~~~diff diff --git a/mesonbuild/mparser.py b/mesonbuild/mparser.py index 8400a1ac..5a91a3b9 100644 --- a/mesonbuild/mparser.py +++ b/mesonbuild/mparser.py @@ -111,6 +111,7 @@ class Lexer: par_count = 0 bracket_count = 0 col = 0 + newline_rx = re.compile(r'(?<!\\)(\\\\)*\\n') while loc < len(self.code): matched = False value = None @@ -139,10 +140,9 @@ class Lexer: elif tid == 'dblquote': raise ParseException('Double quotes are not supported. Use single quotes.', self.getline(line_start), lineno, col) elif tid == 'string': - value = match_text[1:-1]\ - .replace(r"\'", "'")\ - .replace(r" \\ ".strip(), r" \ ".strip())\ - .replace("\\n", "\n") + value = match_text[1:-1].replace(r"\'", "'") + value = newline_rx.sub(r'\1\n', value) + value = value.replace(r" \\ ".strip(), r" \ ".strip()) elif tid == 'multiline_string': tid = 'string' value = match_text[3:-3] ~~~ Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: Minor documentation error in np.take_along_axis There is a minor mistake in the documentation of [`np.take_along_axis`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.take_along_axis.html). In the "Notes" section there is a snippet functionally equivalent to the function that begins with: ```python Ni, M, Nk = a.shape[:axis], a.shape[axis], a.shape[axis+1:] J = indices.shape[axis] # Need not equal M out = np.empty(Nk + (J,) + Nk) ``` As I understand it, the definition of `out` should be: ````python out = np.empty(Ni + (J,) + Nk) ```` With the initial `Nk` replaced by `Ni`. ### Reproducing code example NA ### Error message NA ### Numpy/Python version information: 1.16.1 Minor documentation error in np.take_along_axis There is a minor mistake in the documentation of [`np.take_along_axis`](https://docs.scipy.org/doc/numpy/reference/generated/numpy.take_along_axis.html). In the "Notes" section there is a snippet functionally equivalent to the function that begins with: ```python Ni, M, Nk = a.shape[:axis], a.shape[axis], a.shape[axis+1:] J = indices.shape[axis] # Need not equal M out = np.empty(Nk + (J,) + Nk) ``` As I understand it, the definition of `out` should be: ````python out = np.empty(Ni + (J,) + Nk) ```` With the initial `Nk` replaced by `Ni`. ### Reproducing code example NA ### Error message NA ### Numpy/Python version information: 1.16.1 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: hdf5.py fails with exception if the project is not set up for C **Describe the bug** what it says in the title. If you have, e.g. a c++ project, trying to call ```dependency('hdf5', language: 'cpp', method: 'config-tool')``` will cause an exception ``` <...> File "/usr/lib/python3.11/site-packages/mesonbuild/dependencies/hdf5.py", line 119, in __init__ compiler = environment.coredata.compilers[for_machine][language] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^ KeyError: 'c' ``` hdf5.py always tries to configure ```c``` language, which is a problem whan it's not set in the project **To Reproduce** ``` project('test', 'cpp') dependency('hdf5', language: 'cpp', method: 'config-tool') ``` **Expected behavior** no exception. If C is always needed for HDF5 - make a special error for this case. **system parameters** meson 1.0.1 ninja 1.11.1 fedora 38 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Inverse U gate parameter ordering issue To whom it may concern, It came to my attention that the inverse of U gate doesn't have the right order of parameters as the math notation and understanding. Though it is working as expected in the simulation, the user needs to swap the orders, which is mathematically incorrect. Please look at the order of parameters and mathematical order. https://qiskit.org/documentation/_modules/qiskit/circuit/library/standard_gates/u.html#UGate.inverse math:`U(\theta,\phi,\lambda)^{\dagger} =U3(-\theta,-\phi,-\lambda)`) """ return UGate(-self.params[0], **-**self.params[2], -self.params[1]****) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Mismatch of transaction IDs in 'g.datastore.connection.Connecction.rollback_transaction()' The method first checks that a transaction exists for the connection, and that it has a truthy ID[1], but then does not use that ID when setting up the API request: instead, it uses a passed-in ID[2]. This is not the same behavior as in 'g.datastore.connection.Connecction.commit()', where the ID is used from the connection's transaction (if present)[3]. Is there a usecase for using a connection to rollback any transaction ID other than the one bound to the connection? [1] https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/connection.py#L176 [2] https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/connection.py#L180 [3] https://github.com/GoogleCloudPlatform/gcloud-python/blob/master/gcloud/datastore/connection.py#L300 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Support `--log-driver` Docker 1.6 adds support for the `--log-driver` option. It'd be great to be able to set this in the `docker-compose.yml` file. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Add tree search swap mapper ### What is the expected behavior? Add a new tree search based swap mapper as a possible pass in the transpiler. The algorithm was submitted to the 2018 Qiskit Developer Challange and is described at https://medium.com/qiskit/improving-a-quantum-compiler-48410d7a7084 . Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: convert integer for `static_argnums` to tuple automatically I've made the same mistake a few times on `static_argnums` on `jit` function, by not using a tuple e.g., `jit(f, static_argnums=1)` would it be possible / reasonable to add a simple `if` statement to convert it to tuple? where the correct way is `jit(f, static_argnums=(1,) )` also note `(1)` is not a tuple, but `(1,)` is Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: unused variables should be removed if not needed <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? Follow-up to #2396: some variables are unused. If there's really no reason for them to be there, remove them entirely. - [ ] qiskit/qasm/node/binaryop.py - [ ] qiskit/qasm/node/binaryoperator.py - [ ] qiskit/qasm/node/external.py - [ ] qiskit/qasm/node/format.py - [ ] qiskit/qasm/node/id.py - [ ] qiskit/qasm/node/indexedid.py - [ ] qiskit/qasm/node/intnode.py - [ ] qiskit/qasm/node/prefix.py - [ ] qiskit/qasm/node/real.py - [ ] qiskit/qasm/node/unaryoperator.py - [ ] qiskit/qasm/qasmlexer.py - [ ] qiskit/qasm/qasmparser.py - [ ] qiskit/quantum_info/operators/channel/transformations.py - [ ] qiskit/test/mock.py - [ ] qiskit/tools/jupyter/backend_monitor.py - [ ] qiskit/tools/jupyter/backend_overview.py - [ ] qiskit/visualization/latex.py - [ ] qiskit/visualization/matplotlib.py - [ ] test/python/test_util.py Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: typing should not be a dependency for python>=3.5 https://github.com/ipython/ipython/commit/3ff1be2ea8ef180a6f17a6a03a3f8452303b9abe added `typing` as an `install_requires`. This package is builtin for python>=3.5, so it should be protected by an environment marker (just like `pathlib2`) in setup.py. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [bug] `cmake.test()` cannot execute ### Environment Details (include every applicable attribute) * Operating System+version: Ubuntu 22.04 on WSL * Compiler+version: CMake 3.23.1 * Conan version: 1.49.0 * Python version: 3.10.4 ### Steps to reproduce (Include if Applicable) Put `cmake.test()` and run `conan build .` with `Ninja Multi-Config` as a generator. ### Logs (Executed commands with output) (Include/Attach if Applicable) ``` conanfile.py (mp-units/0.8.0): CMake command: cmake --build "/home/mpusz/repos/units/build-gcc-11" --config Release '--' '-j12' [308/308] Linking CXX executable test/unit_test/runtime/Release/unit_tests_runtime conanfile.py (mp-units/0.8.0): CMake command: cmake --build "/home/mpusz/repos/units/build-gcc-11" --config Release '--target' 'RUN_TESTS' '--' '-j12' ninja: error: unknown target 'RUN_TESTS' ERROR: conanfile.py (mp-units/0.8.0): Error in build() method, line 172 cmake.test() ConanException: Error 1 while executing cmake --build "/home/mpusz/repos/units/build-gcc-11" --config Release '--target' 'RUN_TESTS' '--' '-j12' ``` CMake target `RUN_TESTS` is not available. `test` target works correctly but Conan does not use it for some reason. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: DAGs imported from networkx cannot be drawn <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Informations - **Qiskit version**: 0.19.2 - **Python version**: 3.8.12 - **Operating system**: Windows 10 ### What is the current behavior? I can successfully create `DAGCircuit` objects by importing them from networkx graphs. Those objects seem to behave correctly, but whenever I try to draw them using the `dag_drawer` function, I get an error. I verified that the error only occurs for DAGCircuit objects imported from networkx graphs - in fact, I can draw a dag correctly, but if I convert it to networkx and back (`new_dag = from_networkx(dag.to_networkx())`), then new_dag can no longer be drawn. ### Steps to reproduce the problem ``` import qiskit from qiskit.circuit.random import random_circuit from qiskit.converters import circuit_to_dag, dag_to_circuit from qiskit.tools.visualization import dag_drawer from qiskit.dagcircuit import DAGCircuit in_circ = random_circuit(1,1) in_dag = circuit_to_dag(in_circ) # dag_drawer(in_dag) # if uncommented, draws the DAG correctly graph = in_dag.to_networkx() out_dag = DAGCircuit.from_networkx(graph) dag_drawer(out_dag) # throws an error ``` outputs ``` KeyError Traceback (most recent call last) ---> [12]() dag_drawer(out_dag) --> [224]() dot_str = dag._multi_graph.to_dot(node_attr_func, edge_attr_func, graph_attrs) --> [206]() n["label"] = bit_labels[node.wire] KeyError: Qubit(QuantumRegister(1, 'q'), 0) ``` ### What is the expected behavior? That DAG objects created from networkx graphs have the same properties as those created from quantum circuits. ### Suggested solutions Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the dagster-io/dagster codebase. Here's the problem: Ability to yield a RunRequest from a run status sensor User says: "While working with sensors, we came to the conclusion that you cannot yield a RunRequest from a run_status_sensor . This forces us to have a generic sensor which queries runs and assets with RunsFilter and EventRecordsFilter , then yield a run request for a downstream graph. This works well enough, but it would be much simpler to have run_status_sensor able to yield run requests as it would have the job run and the assets it produced in the sensor context, which means we don’t need to go against the storage API". Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Rename DirectionMapper <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? I would like to rename the DirectionMapper to GateDirection or SwapDirection or DirectionSelection or just CXDirection. I think it is important to separate it from mapper pass. This allows us to define the mapper problem as working for any two qubit gate and it just connects with swaps. This way it is clear that this is not an alternative mapper pass Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: Clean up activate.py using proper OO inheritence See * https://github.com/conda/conda/pull/6585#issuecomment-354178822 * https://github.com/conda/conda/pull/6585#issuecomment-354303897 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: config appears to not pick up conda_build/matrix_base_dir in 4.6.0b1 In my .condarc: ``` conda_build: matrix_base_dir: ~/code/automated-build/c3i_configurations/anaconda_public ``` This is for c3i. Somehow this isn't getting loaded properly: ``` c3i one-off py36_win python-3.6-feedstock -p "win*" Traceback (most recent call last): File "/Users/msarahan/miniconda3/bin/c3i", line 11, in <module> load_entry_point('conda-concourse-ci', 'console_scripts', 'c3i')() File "/Users/msarahan/code/conda-concourse-ci/conda_concourse_ci/cli.py", line 240, in main execute.submit_one_off(pass_throughs=pass_throughs, **args.__dict__) File "/Users/msarahan/code/conda-concourse-ci/conda_concourse_ci/execute.py", line 802, in submit_one_off config_root_dir = os.path.expanduser(config_root_dir) File "/Users/msarahan/miniconda3/lib/python3.6/posixpath.py", line 235, in expanduser path = os.fspath(path) TypeError: expected str, bytes or os.PathLike object, not NoneType ``` The code that loads this setting is at https://github.com/conda/conda-concourse-ci/blob/master/conda_concourse_ci/cli.py#L43 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: os.rename throws exception when renaming directories on lower overlayfs layers OS: CentOS Linux release 7.2.1511 (Core) docker version: 1.12.6 docker storage driver: overlayfs Docker Image has existing conda environment baked into layer ``` During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/exceptions.py", line 640, in conda_exception_handler return_value = func(*args, **kwargs) File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/cli/main.py", line 140, in _main exit_code = args.func(args, p) File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/cli/main_install.py", line 80, in execute install(args, parser, 'install') File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/cli/install.py", line 326, in install execute_actions(actions, index, verbose=not context.quiet) File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/plan.py", line 830, in execute_actions execute_instructions(plan, index, verbose) File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/instructions.py", line 247, in execute_instructions cmd(state, arg) File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/instructions.py", line 108, in UNLINKLINKTRANSACTION_CMD txn.execute() File "/opt/continuum/anaconda/lib/python3.6/site-packages/conda/core/link.py", line 297, in execute rollback_excs, conda.CondaMultiError: [Errno 22] Invalid argument: '/opt/continuum/anaconda/envs/anaconda44_py35/lib/python3.5/version.txt' -> '/opt/continuum/anaconda/envs/anaconda44_py35/lib/python3.5/version.txt.c~' ``` cc @msarahan @kalefranz @mmarchetti @dsludwig Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Add pulse channels to `FakeBackendV2` ### What is the expected enhancement? https://github.com/Qiskit/qiskit-terra/pull/7643 implemented mocked IBM Quantum Systems backends using the new BackendV2 interface. The BackendV2 class contains [pulse channels](https://github.com/Qiskit/qiskit-terra/blob/main/qiskit/providers/backend.py#L484-L549) (`drive_channel`, `measure_channel`, `acquire_channel`, `control_channel`) that were not implemented by #7643. It's unclear to me whether these channels are useful for fake backends. If they are useful, we should add them. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: Batching rule for `dyanmic_slice` not defined If you use indexing , e.g. `x[0]` in a function you `vmap`, it fails. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: wandLogger().name is None in DDP mode If you remove [line 54](https://github.com/PyTorchLightning/pytorch-lightning/blob/8ca8336ce52ee7379f4d399520636143eb31018b/pytorch_lightning/trainer/callback_config.py#L54), everything works. When you're not in ddp mode, this is not an issue. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the dagster-io/dagster codebase. Here's the problem: rename op_version to code_version Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: PubSub: correctly decrement the byte counter in drop() I'm looking at this 2 files: - https://github.com/GoogleCloudPlatform/google-cloud-python/blob/5c010e3790c9067e6d7bf8ba37724ee5121eadb7/pubsub/google/cloud/pubsub_v1/subscriber/policy/base.py#L215 - https://github.com/GoogleCloudPlatform/google-cloud-python/blob/5c010e3790c9067e6d7bf8ba37724ee5121eadb7/pubsub/tests/unit/pubsub_v1/subscriber/test_policy_base.py Should the code in `base.py` line 215 be `max` instead of `min`? ``` self._bytes = min([self._bytes, 0]) ``` Current code: 1. current state `self._bytes = 50` 2. then we call `self._bytes -= 20` 3. now `self._bytes == 30` 4. but then we do `self._bytes = min([30, 0])` -> `self._bytes = 0` Should be: 1. current state `self._bytes = 50` 2. then we call `self._bytes -= 20` 3. now `self._bytes == 30` 4. but then we do `self._bytes = max([30, 0])` -> `self._bytes = 30` even if we drop it below 0, we should use `max`: 1. `self._bytes = 10` 2. `self._bytes -= 20` 3. `self._bytes == -10` 4. `min([-10, 0]) == -10` should be `max([-10, 0]) == 0` Or is there something I miss? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: print name for IPython Notebooks has become uninformative In versions prior to 0.13, the web page containing a print view would have the notebook name as the title. This meant that when printing the notebook to a PDF printer, the resulting PDF file would have the name of the notebook as the file name. In version 0.13, the print view has the name "Notebook" regardless of the name of the worksheet. This is very inconvenient, and I don't see any reason for the change. Could you please change back to using the worksheet name for the title of the print view? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: `post_execute` and `post_run_cell` hooks not always triggered Due to various early returns in the code below, `post_execute` and `post_run_cell` hooks are not triggered in some cases. Since the pre hooks are always called, this is either a bug or the [docs](http://ipython.readthedocs.io/en/stable/config/callbacks.html#post-run-cell) should mention that post hooks are not guaranteed to be triggered. https://github.com/ipython/ipython/blob/ca86b79bfd5cdd633ea6cb9c18bb2c1c493402a1/IPython/core/interactiveshell.py#L2694-L2739 /cc @craigcitro Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Multiple %%%% in tab-completion after pdb ``` [carlos@carlos ~]$ ipython Python 3.4.3 (default, Feb 26 2015, 23:01:07) Type "copyright", "credits" or "license" for more information. IPython 3.0.0 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. In [1]: %pdb Automatic pdb calling has been turned ON In [2]: 1/0 --------------------------------------------------------------------------- ZeroDivisionError Traceback (most recent call last) <ipython-input-2-05c9758a9c21> in <module>() ----> 1 1/0 ZeroDivisionError: division by zero > <ipython-input-2-05c9758a9c21>(1)<module>() ----> 1 1/0 ipdb> q In [3]: %<Tab><Tab><Tab><Tab>... ``` Each succesive tab press adds a new %. Multiple %%%% in tab-completion after pdb ``` [carlos@carlos ~]$ ipython Python 3.4.3 (default, Feb 26 2015, 23:01:07) Type "copyright", "credits" or "license" for more information. IPython 3.0.0 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object', use 'object??' for extra details. In [1]: %pdb Automatic pdb calling has been turned ON In [2]: 1/0 --------------------------------------------------------------------------- ZeroDivisionError Traceback (most recent call last) <ipython-input-2-05c9758a9c21> in <module>() ----> 1 1/0 ZeroDivisionError: division by zero > <ipython-input-2-05c9758a9c21>(1)<module>() ----> 1 1/0 ipdb> q In [3]: %<Tab><Tab><Tab><Tab>... ``` Each succesive tab press adds a new %. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Move collaboration features to a separate package ### Problem Once the implementation of RTC through IDrive is done. We can extract every specific RTC UI elements to a separate extension. So RTC is a opt-in through extension installation. And we are able to keep iterating faster on the UI elements. The elements that need to be in core for RTC are: - Document model stored in RTC compatible object (= Yjs document) - Getting user identity and permission (Jupyter Server Identity & Authorization API) Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the celery/celery codebase. Here's the problem: Restarting celery issues and better supervisord config file I use supervisord config file based on the example in celery repository and have some issues when celeryd restart is occured: sometimes task processing silently stops after restarting celery without any error messages in logs. Processes remains visible in process list. Finally I figured out that sometimes when processes are restarted celery spawns additional process that is not managed by supervisord and this leads to these bugs. So I started to watch `ps` output carefully after each restart and kill extra processes manually via kill <id>. After killing these processes tasks begin to be executed properly. This is sort of hack that solve a problem for a week or so. And today I think the real reason is found. The default supervisord value for 'stopwaitsecs' option is 10s. This means that after 10s celery process will be killed with KILL signal instead of TERM. It seems that celery don't like being killed and try to spawn additional process in that case. So I think it'll be good to add something like 'stopwaitsecs=600' to all supervisord example config files (from faq: "You should never stop celeryd with the KILL signal (-9), unless you’ve tried TERM a few times and waited a few minutes to let it get a chance to shut down.") and investigate celeryd behaviour on KILL signal: it is mentioned in docs that tasks will be lost (and it is tolerably in many cases) but the issue with spawned process is a bit weird. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: [DO NOT MERGE] Logging: failed to blacken after synth This PR was generated using Autosynth. :rainbow: Here's the log from Synthtool: ``` synthtool > Executing /tmpfs/src/git/autosynth/working_repo/logging/synth.py. synthtool > Ensuring dependencies. synthtool > Pulling artman image. latest: Pulling from googleapis/artman Digest: sha256:8b45fae963557c3299921037ecbb86f0689f41b1b4aea73408ebc50562cb2857 Status: Image is up to date for googleapis/artman:latest synthtool > Cloning googleapis. synthtool > Running generator for google/logging/artman_logging.yaml. synthtool > Generated code into /home/kbuilder/.cache/synthtool/googleapis/artman-genfiles/python/logging-v2. synthtool > Replaced '(^.*$\\n)*' in google/cloud/logging_v2/proto/logging_pb2.py. synthtool > Replaced '(^.*$\\n)*' in google/cloud/logging_v2/proto/logging_metrics_pb2.py. synthtool > Replaced '(^.*$\\n)*' in google/cloud/logging_v2/proto/log_entry_pb2.py. synthtool > Replaced '(^.*$\\n)*' in google/cloud/logging_v2/proto/logging_config_pb2.py. .coveragerc .flake8 MANIFEST.in noxfile.py.j2 setup.cfg Running session blacken Session blacken skipped: Python interpreter 3.7 not found. synthtool > Cleaned up 2 temporary directories. synthtool > Wrote metadata to synth.metadata. ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Remove legacy `VariationalForm` <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? When the `algorithms` module from Qiskit Aqua got migrated to Terra, the `VariationalForm` was included (possibly by accident). Before the next release, this class will no longer be needed because all variational forms will have been refactored into `BlueprintCircuit`s (see also https://github.com/Qiskit/qiskit-nature/pull/66 for an example). Thus, it would be good to remove the `VariationalForm` class. Furthermore, the `preferred_init_points` argument, which is checked for in [`VariationalAlgorithm`](https://github.com/Qiskit/qiskit-terra/blob/master/qiskit/algorithms/variational_algorithm.py#L204) and set to a dummy value in [`NLocal`](https://github.com/Qiskit/qiskit-terra/blob/master/qiskit/circuit/library/n_local/n_local.py#L509) will no longer be needed. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conda/conda codebase. Here's the problem: prioritize channels within multi-channels Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: Batchsize and learning rate scheduler I was wondering if I need to adjust the batch size when using TPUs. I had a memory error when trying to run a (image 256x256x3) batch of size 128, which works perfectly fine on GPUs. Furthermore, do I need to adjust my custom learning rate scheduler which on GPUs run every batch (not just epoch): ``` def configure_optimizers(self): optimizer = get_optimizer(self) one_cycle_scheduler = OneCycleScheduler(optimizer, EPOCHS * steps_per_epoch // GRAD_ACCUMULATE) scheduler = {'scheduler': one_cycle_scheduler, "interval": "step"} return [optimizer], [scheduler] ``` pl version: 0.8.5 system: kaggle Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Add support for build-time extra_hosts I'm having an issue with extra_hosts on compose. ```bash $> docker -v Docker version 17.06.0-ce, build 02c1d87 ``` ```bash $> docker-compose -v docker-compose version 1.16.1, build 6d1ac219 ``` The `--add-host` option works correctly with `docker build` but the `extra_hosts` of `docker-compose` doesn't. I'm using a 3.3 version ok Compose file, here is a sample ```Dockerfile version: '3.3' services: my_service: build: context: ./some_folder args: ARG1: $ARG1 ARG2: $ARG2 extra_hosts: - "my.local.network.url:XXX.XXX.XXX.XXX" environment: SOME_VAR: $SOME_VAR volumes: - ./folder1:/folder1 ``` My volumes are not interfering with /etc/hosts or anything like that. Can anyone tell me if I'm doing anything wrong ? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: AutoConfig.from_pretrained("model", return_unused_kwargs=True) returns `"_from_auto": True` field against specification ### System Info ```shell - `transformers` version: 4.17.0 - Platform: Linux-5.13.0-40-generic-x86_64-with-glibc2.34 - Python version: 3.9.7 - PyTorch version (GPU?): 1.11.0+cu102 (False) - Tensorflow version (GPU?): not installed (NA) - Flax version (CPU?/GPU?/TPU?): not installed (NA) - Jax version: not installed - JaxLib version: not installed ``` ### Who can help? @sgugger Small bug in which for some cases `{"_from_auto": True}` is returned [against specification](https://github.com/huggingface/transformers/blob/31ec2cb2badfbdd4c1ac9c6c9b8a74e974984206/src/transformers/models/auto/configuration_auto.py#L646). Seems to originate [here](https://github.com/huggingface/transformers/blob/31ec2cb2badfbdd4c1ac9c6c9b8a74e974984206/src/transformers/models/auto/configuration_auto.py#L671) and/or [here](https://github.com/huggingface/transformers/blob/31ec2cb2badfbdd4c1ac9c6c9b8a74e974984206/src/transformers/configuration_utils.py#L659) ### Information - [ ] The official example scripts - [X] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [X] My own task or dataset (give details below) ### Reproduction Replicable with ```py >>> from transformers import AutoConfig >>> config, kwargs = AutoConfig.from_pretrained("bert-base-uncased", return_unused_kwargs=True) >>> kwargs {'_from_auto': True} ``` ### Expected behavior There should be no `"_from_auto": True` field in returned dict. ```py >>> from transformers import AutoConfig >>> config, kwargs = AutoConfig.from_pretrained("bert-base-uncased", return_unused_kwargs=True) >>> kwargs {} ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: In examples, complete steps not correct when load from checkpoint ### System Info https://github.com/huggingface/transformers/blob/8f093fb799246f7dd9104ff44728da0c53a9f67a/examples/pytorch/language-modeling/run_clm_no_trainer.py#L575 Should be: ```python completed_steps = resume_step // args.gradient_accumulation_steps ``` ### Who can help? @sgugger ### Information - [X] The official example scripts - [ ] My own modified scripts ### Tasks - [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction 1. Enable grad acc. 1. Save the checkpoint. 1. Load from it. ### Expected behavior The `completed_steps` should be divided by grad acc steps. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Menu item schema extraction in documentation is off See "Item must follow this definition:" in https://jupyterlab.readthedocs.io/en/stable/extension/extension_points.html#context-menu being shifted off by several lines. It is trivial to updated, but opening the issue to get any suggestions on how to handle it better. This also affects the toolbar item definitions: https://jupyterlab.readthedocs.io/en/latest/extension/extension_points.html#toolbar-registry (after "Add the toolbar item must follow this definition:") Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: CmdDef always returns positive FC phase. <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: - **Python version**: - **Operating system**: ### What is the current behavior? When we `.get` u1, u2 or u3 from `CmdDef`, all FrameChange phases become positive value. ### Steps to reproduce the problem ``` cmd_def = pulse.CmdDef.from_defaults(defaults.cmd_def, defaults.pulse_library) cmd_def.get('u1', 0, P0=-pi) ``` this returns a schedule consisting of FrameChange of +pi (because P0 is negated in cmd_def). ``` cmd_def = pulse.CmdDef.from_defaults(defaults.cmd_def, defaults.pulse_library) cmd_def.get('u1', 0, P0=pi) ``` this returns a schedule consisting of FrameChange of +pi, but this should be -pi. ### What is the expected behavior? ### Suggested solutions Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: In the PTK terminal, control-o should indent the newly created line Suppose I have: ``` In [5]: def f(): ...: [CURSOR]a = 1 ``` If I press control-O to open up a new line, I get: ``` In [5]: def f(): ...: [CURSOR] ...: a = 1 ``` I would prefer to get: ``` In [5]: def f(): ...: [CURSOR] ...: a = 1 ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: UserWarning: __floordiv__ is deprecated Dear All, I am trying to Fine-tune XLSR for Speech Recognition "facebook/wav2vec2-base" model for Urdu Language. However when I run the trainer, I am getting the following warning: ``` /home/e-team/anaconda3/lib/python3.9/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:704: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor'). return (input_length - kernel_size) // stride + 1 ``` Also Consequently my WER is 1.00 which means training is not being done correctly. Can anyone guide ? What changes to make and where? Torch Version: 1.10.1+cu102 Python Version: 3.9.7 CUDA Version: 11.2 Tensorflow Version: 2.7.0 ![image](https://user-images.githubusercontent.com/42676982/148747322-aee21356-a4ee-4b11-a81d-8176ccf214ae.png) Best regards, Yasir Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: Missing 8.3 version of gcc Hi, [conan 1.15.0] is this possible to add the 8.3 version of gcc into the default settings.yml generated ? Regards, Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: PubSub JSON Double base64 Encode We recently upgraded from 0.18.1 to 0.21.0 and we do *not* use gRPC/GAX/Protobuf fun times, but we use the JSONPublisherApi. Maybe we are using the topic.Batch().Commit() method wrong, but we have been using it in our retry strategy to just simply call Commit() again. With the change in #2577 it seems that Commit() will double encode *if* you just call Commit() again on a network failure. Is this the intended design? Are we supposed to keep another copy of the message batch or create another message batch? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Add support for variable width operations to Target ### What should we add? Right now the target class doesn't have proper support for modelling instructions that have variable width. If you have a gate that can use more than a single number of qubits and the backend supports all variants of that instruction (or at least more than one). We don't have a way to express that. The target currently requires a 1:1 mapping of operation name to a `Operation` instance and that instance is used for type checking and parameter checking at different points in the transpiler. However this requirement won't work for variable width instructions because a single instance of the instructions can only have a single number of qubits. To be able to accurately model these instructions being supported on a target backend we need to come up with an interface to model this in the target, which might mean introducing a `TargetV2`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: [AIP-31] Create XComArg model **Description** XComArg is a class that references an XCom entry from an operator. Can be used to explicitly set XCom dependencies and explictly pass results between operators. _Class attributes:_ - `operator: BaseOperator`: Origin operator instance. - `key: str`: Stores key for XCom value. Defaults to `airflow.models.xcom. XCOM_RETURN_KEY` _Class methods_ - `get(context: dict)-> Any`: Resolves XCom value given `operator` and `key`. - `__getitem__(key, str) -> XComArg`: Easy method to create new XComArg using the same operator but a different key. - `add_downstream_dependent(operator: BaseOperator)->None`: Add an operator as a downstream dependency of `operator`. [Optional] Makes this task simpler. Proposed implementation: https://github.com/casassg/corrent/blob/master/corrent/xcom_arg.py **Use case / motivation** - Explicit way to pass around results between operators. - This object is a reference to an XCom value that has not been created and will need to be resolved in the future. - It can generate new XComArgs that point to the same operator but has a different key by using the key accessor. E.g: output['train']. - To do so, it includes as class attributes both the originating operator instance and a key (both needed to pull the XCom). - Has a property op that allows access to the origin operator. **Stretch goal** - Store type class for the XCom and lie to MyPy when trying to check class signature. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: Mask2Former ImageProcessor produces different results on Mac vs Windows. ### System Info >>> transformers.__version__ '4.27.0.dev0' >>> Python 3.10.6 Windows vs Mac ### Who can help? @amyeroberts ### Information - [ ] The official example scripts - [ ] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [X] My own task or dataset (give details below) ### Reproduction ``` import torch from transformers import AutoImageProcessor, Mask2FormerForUniversalSegmentation processor = AutoImageProcessor.from_pretrained("facebook/mask2former-swin-large-cityscapes-instance", reduce_labels=False, ignore_index=255, do_resize=True, size=dict(width=500, height=500), do_normalize=True, image_mean=[0.485, 0.456, 0.406], image_std=[0.229, 0.224, 0.225]) device = torch.device("cpu") image = Image.open(filename1) image = image.convert('RGB') image = np.array(image) image = image.astype(np.float32) image = image.transpose(2,0,1) print(image.dtype, image.shape, image.mean((1, 2))) # float32 (3, 1000, 1000) [156.41327 149.47672 137.97989] ret = processor([image], return_tensors="pt") pixel_values = ret["pixel_values"].to(device) print(pixel_values.dtype, pixel_values.shape, pixel_values[0].mean((1, 2)), pixel_values[0].std((1, 2))) ``` Windows ``` float32 (3, 1000, 1000) [156.41327 149.47672 137.97989] mean = [-0.4228946 -0.17078026 0.25235963] std = [0.81622934 0.699496 0.71027416] ``` Mac ``` float32 (3, 1000, 1000) [156.41327 149.47672 137.97989] mean = [-1.229962 -1.1720737 -0.6407509] std = [1.5912648 1.5453817 1.7506045] ``` ### Expected behavior Same result on Windows and Mac Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Remove legacy simulators This i think should be done in two parts. I will remove the python code and fix the test that applies. @atilag can you do the removing of the source code and the updating of the install instructions. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Build Recommend Dialog always pops up ### From Gitter: ### > I'm on the latest released jupyterlab and have also installed the ipywidgets and jupyterlab-hub extensions. When I start jupyterlab I get a Build Recommended dialog suggesting I run jupyter lab build from the command line. When I do so nothing much seems to happen and I still get the dialog when I relaunch jupyterlab. ``` C:\>jupyter lab build > npm install > npm run build C:\> ``` > @dhirschfeld, that sounds like a bug, what does jupyter labextension list give? and also npm -v Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Use new URL format for Q network registration <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues to confirm this idea does not exist. --> ### What is the expected enhancement? The registration for the Q network needs to use the new URL format. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose up prints out "stty: standard input: Inappropriate ioctl for device" I have created a docker image using ubuntu trusty as the base. The image is configured to run a Ruby application locally using the Ruby web server Thin. Whenever I run docker-compose up I get the message in the subject constantly printing out along with stdout from the Ruby process. This does not happen when I run a container from the save image using 'docker run' Anyone got any ideas to fix this? Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: DotDict doesn't accept non-string keys Trying to set a non-string key results in `TypeError: hasattr(): attribute name must be string` because of [this line](https://github.com/PrefectHQ/prefect/blob/dcf0cdb2b27fc1434ad433afe9beb0720eb192db/src/prefect/utilities/collections.py#L62). Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: circuit.extend produces empty circuit.qubits <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: master@9e78907d2 - **Python version**: 3.7.7 - **Operating system**: macOS ### What is the current behavior? The `QuantumCircuit.extend` operation extends an existing circuit with another circuit. If the second circuit contains registers that are not in the first one, the register is added to the first. This operation can therefore add quantum registers. Before #4766 this was not a problem because the `QuantumCircuit.qubits` attribute was generated from the registers, but now that the qubits are cached, calling extend causes a mismatch between the registers and qubits, because the qubits attribute is not properly updated. ### Steps to reproduce the problem ```python from qiskit import QuantumCircuit empty = QuantumCircuit() other = QuantumCircuit(1) other.x(0) empty.extend(other) print(empty) print(empty.qubits) ``` Before #4766 (1db0340eb): ``` ┌───┐ q_0: ┤ X ├ └───┘ [Qubit(QuantumRegister(1, 'q'), 0)] ``` After: ``` ┌───┐ q_0: ┤ X ├ └───┘ [] ``` ### Suggested solutions Update `self.qubits` upon calling `self.extend`. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose cannot handle unicode file paths on Windows I've just hit this error: ``` Traceback (most recent call last): File "<string>", line 3, in <module> File "compose\cli\main.py", line 61, in main File "compose\cli\main.py", line 113, in perform_command File "compose\cli\main.py", line 219, in build File "compose\project.py", line 300, in build File "compose\service.py", line 727, in build File "site-packages\docker\api\build.py", line 54, in build File "site-packages\docker\utils\utils.py", line 103, in tar File "tarfile.py", line 2006, in add File "tarfile.py", line 1878, in gettarinfo WindowsError: [Error 123] The filename, directory name, or volume label syntax is incorrect: 'C:\\[redacted]\\?.jpg' ``` The actual file name is `∆.jpg` (don't ask why). This looks like the same issue in http://stackoverflow.com/questions/11545185/handling-utf-filenames-in-python Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: AutotoolsBuildEnvironment adjusting gnueabi in triplet for x86 To help us debug your issue please explain: - [x] I've read the [CONTRIBUTING guide](https://raw.githubusercontent.com/conan-io/conan/develop/.github/CONTRIBUTING.md). - [x] I've specified the Conan version, operating system version and any tool that can be relevant. - [x] I've explained the steps to reproduce the error or the motivation/use case of the question/suggestion. https://twitter.com/DEGoodmanWilson/status/968797501447917568 Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [QoL] Allow `conan remove -t *` In the CI with the cache, it's needed to reinstall system requirements when the machine has been changed. Currently, it's only supported with a full reference. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Compose 1.20.0 crashes while building image from Dockerfile I have a setup with Compose 1.20.0 installed inside a virtualenv. When building an image using a local Dockerfile, it crashes. I can confirm the same behavior in 3 different Linux environments - Fedora 27 x86_64 (dev machine) - Debian Jessie x86_64 (different dev machine) - Ubuntu 14.04 (Travis CI) ``` Building cassandra ERROR: Error processing tar file(exit status 1): open /venv/include/python2.7/Python-ast.h: no such file or directory ``` It seems to me for some reason an absolute path is being used, and my virtualenv obviously does not reside inside my system root. Compose 1.19.0 does not seem to show the same problem. The Dockerfile and Compose config follow. ```dockerfile FROM cassandra:3.11.1 RUN sed -e 's/authorizer: AllowAllAuthorizer/authorizer: CassandraAuthorizer/' -e 's/authenticator: AllowAllAuthenticator/authenticator: PasswordAuthenticator/' -i /etc/cassandra/cassandra.yaml ``` ```yaml version: '2.3' services: cassandra: build: context: . dockerfile: Dockerfile-cassandra environment: MAX_HEAP_SIZE: 250M HEAP_NEWSIZE: 50M ports: - "9042:9042" - "7199:7199" ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the huggingface/transformers codebase. Here's the problem: 2 RAG test failures The two failures here look related to recent tokenizer changes: https://github.com/huggingface/transformers/runs/1236753957?check_suite_focus=true ``` =========================== short test summary info ============================ FAILED tests/test_modeling_rag.py::RagModelIntegrationTests::test_rag_sequence_generate_batch FAILED tests/test_modeling_rag.py::RagModelIntegrationTests::test_rag_token_generate_batch ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: Implement checkpointing for data Currently tasks have a dummy "checkpoint" attribute which needs to be handled Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the apache/airflow codebase. Here's the problem: Provider dependencies do not work well with alphas. The dependencies in Alphas are currently >= 2.0.0 and should be >=2.0.0a0 in order to work with Alphas in cases which are not PEP 440-compliant. According to https://www.python.org/dev/peps/pep-0440/, >= 2.0.0 should also work with alpha/beta releases (a1/a2) but in some cases it does not (https://apache-airflow.slack.com/archives/C0146STM600/p1602774750041800) Changing to ">=2.0.0a0" should help. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the google/jax codebase. Here's the problem: MAML Gradients + Convnets don't work The attached python code snippet implements a MAML gradient update on 1) an MLP and 2) a CNN. When MODEL_TYPE = 'mlp', everything works. When MODEL_TYPE = 'conv', I get the following error: RuntimeError: Invalid argument: Expected LHS feature dimension (value 1) to be a multiple of feature_group_count (value 1), and LHS feature dimension / feature_group_count = RHS feature dimension (value 40); got <conv>(f32[1,1,40,40], f32[10,1,1,40]) Dimension numbers: {kernel_input_feature_dimension: 3 kernel_spatial_dimensions: 1 kernel_spatial_dimensions: 2 input_batch_dimension: 3 output_batch_dimension: 2 output_feature_dimension: 3 input_spatial_dimensions: 1 input_spatial_dimensions: 2 output_spatial_dimensions: 0 [maml-cnn.txt](https://github.com/google/jax/files/2867892/maml-cnn.txt) output_spatial_dimensions: 1 }.: @ 0x7ff2befc9214 xla::XlaBuilder::ReportErrorOrReturn() @ 0x7ff2befd6eaa xla::ConvGeneralDilated() @ 0x7ff2b82e4cb8 xla::swig::LocalComputationBuilder::ConvGeneralDilated() @ 0x7ff029565901 _wrap_LocalComputationBuilder_ConvGeneralDilated() @ 0x4bc454 PyEval_EvalFrameEx Note that for both model architectures, the maml objective loss can be computed. It's only in the case of attempting to take a gradient of the CNN-based loss, things break. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Lightning-AI/lightning codebase. Here's the problem: Pretty test result with pprint ## 🚀 Feature ### Motivation Test results are shown at the end of test loops since v0.7.0. The content of the indication is `prog_bar_metrics`, which is basically inputted as a `dict`. By default, this part uses built-in `print` function: ![image](https://user-images.githubusercontent.com/14917234/76911857-44df9100-68f5-11ea-8719-744acfc05855.jpeg) This way cannot display the pretty results so I suggest using `pprint`: ![image](https://user-images.githubusercontent.com/14917234/76911882-5c1e7e80-68f5-11ea-81c5-54226c3262e8.jpeg) ### Pitch - Substitute `print` at the end of the test loop with `pprint` . ### Alternatives Modify [here ](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/trainer/evaluation_loop.py#L375)like: ```python if test_mode: if self.proc_rank == 0: from pprint import pprint print('-' * 100) print('TEST RESULTS') pprint(prog_bar_metrics) print('-' * 100) ``` Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Optim level 2 and 3 modifiy circuits that match topology   ### Information - **Qiskit Terra version**: master - **Python version**: - **Operating system**: ### What is the current behavior? The following circuit fits Vigo-like topologies exactly:  But optimization level 3 gives:  Where as the default gives the expected original circuit (save for H -> U2):  ### Steps to reproduce the problem ```python qc = QuantumCircuit(5) qc.h(3) qc.cx([3, 3, 1, 1], [1, 4, 2, 0]) qc.measure_all() new_qc = transpile(qc, backend, optimization_level=3) new_qc.draw(output='mpl') ``` ### What is the expected behavior? ### Suggested solutions Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the mesonbuild/meson codebase. Here's the problem: meson_options.txt don't allow splitting long strings nicely Currently `meson_options.txt` don't provide a way to split long strings in multiple lines. If I try to use the `+` operator, the syntax is rejected. My use case is the `description` value. Descriptions can be long to be useful, but I don't like writing anything beyond the 80-column barrier and would rather break this long line. Can you help me debug this systematically and explain your reasoning?


[System] You are an expert software debugging assistant. Help debug issues by analyzing problems systematically and providing clear, step-by-step reasoning.

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: transpile() always returns a circuit not in a list whether or not the input is a circuit in a list <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: - **Python version**: - **Operating system**: ### What is the current behavior? When you run transpile function with a circuit list of only one circuit, then the output is the circuit, not the circuit in a list. ### Steps to reproduce the problem from qiskit import * new_qc = transpile([qc], backend) #for some circuit qc and backend new_qc ### What is the expected behavior? Right now, new_qc would produce a circuit not in a list, but I think it would be helpful if it would result as a list. ### Suggested solutions One suggested solution is to make a new variable in the transpile function called list_boolean, or something else, which would keep track of whether the input is a list or not, and in the conditional where the input list is length 1, one can check the value of list_boolean and if it is true, it returns the transpiled circuit in a list, and if false, it just returns the circuit. Can you help me debug this systematically and explain your reasoning?