[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: VideoMAE missing CLS tokens in embedding ### System Info I'm not sure if I've missed something in the code, but I can't seem to find where the CLS tokens are added? I have input data of shape (64,45,2,32,32) with tubelet size = 5, patch_size = 4. This results in a sequence length of 576. From my understanding that is the total number of tubelets. I see that after the data is passed through the embedding layer the final embedding shape is (64,576,768) where 768 is the hidden size. However, should the dimensions not be (64,577,768) since we should be adding a CLS token to the sequence? Would be great to get hear back soon because I'm not sure if I'm wrong or if there is something wrong with the code. Thanks! @NielsRogge ### Reproduction pixel_values = torch.randn(1,45, 2, 32, 32) config = VideoMAEConfig() config.num_frames = 45 config.image_size = 32 config.patch_size = 4 config.tubelet_size = 5 config.num_channels = 2 num_patches_per_frame = (model.config.image_size // model.config.patch_size) ** 2 seq_length = (model.config.num_frames // model.config.tubelet_size) * num_patches_per_frame print(seq_length.shape) videomae = VideoMAEModel(config) output = videomae(pixel_values, output_hidden_states=True) sequence_output = output[0] print(sequence_output.shape) ### Expected behavior seq_length = 576 sequence_output = (1,577,768) The embedding sequence length should be total number of tubelets + 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 apache/airflow codebase. Here's the problem: Mark Success on a mapped task, reruns other failing mapped tasks ### Apache Airflow version 2.3.0b1 (pre-release) ### What happened Have a DAG with mapped tasks. Mark at least two mapped tasks as failed. Mark one of the failures as success. See the other task(s) switch to `no_status` and rerun. ![Apr-22-2022 10-21-41](https://user-images.githubusercontent.com/4600967/164734320-bafe267d-6ef0-46fb-b13f-6d85f9ef86ba.gif) ### What you think should happen instead Marking a single mapped task as a success probably shouldn't affect other failed mapped tasks. ### How to reproduce _No response_ ### Operating System OSX ### Versions of Apache Airflow Providers _No response_ ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] 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: post-link scripts are unable to call entrypoints Using the latest combination of conda and conda-build packages fail to execute anything under bin/ (this folder doesn't exist in this phase). See https://github.com/conda-forge/jupyterlab_code_formatter-feedstock/pull/2 with build log https://dev.azure.com/conda-forge/feedstock-builds/_build/results?buildId=49083&view=logs&jobId=1bf226d3-0e2f-52d8-fa93-7d9e633347b3 for example failure. Going through the changelog of both, the only possible PR affecting this could be https://github.com/conda/conda/pull/8833/files `conda-info`: ``` active environment : base active env location : /Users/uwe/miniconda3 shell level : 1 user config file : /Users/uwe/.condarc populated config files : /Users/uwe/.condarc conda version : 4.7.6 conda-build version : 3.18.7 python version : 3.7.3.final.0 virtual packages : base environment : /Users/uwe/miniconda3 (writable) channel URLs : https://conda.anaconda.org/conda-forge/osx-64 https://conda.anaconda.org/conda-forge/noarch https://repo.anaconda.com/pkgs/main/osx-64 https://repo.anaconda.com/pkgs/main/noarch https://repo.anaconda.com/pkgs/r/osx-64 https://repo.anaconda.com/pkgs/r/noarch package cache : /Users/uwe/miniconda3/pkgs /Users/uwe/.conda/pkgs envs directories : /Users/uwe/miniconda3/envs /Users/uwe/.conda/envs platform : osx-64 user-agent : conda/4.7.6 requests/2.22.0 CPython/3.7.3 Darwin/18.6.0 OSX/10.14.5 UID:GID : 501:20 netrc file : None offline mode : False ``` 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: Easy api for custom primitives and vjps JAX supports custom primitives and vjps, just like Autograd did. Improvements: 1) add this to documentation 2) add a minimal example of this in the examples section 3) add a wrapper function if appropriate? 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 DataDog/integrations-core codebase. Here's the problem: Elasticsearch cluster/index health values Hello, I have noticed that in the [Elasticsearch](https://github.com/DataDog/integrations-core/tree/e3368b3ebaa87d37e01be3b1f58e26fa00e8337f/elastic) integration, index health values are reported as: https://github.com/DataDog/integrations-core/blob/e3368b3ebaa87d37e01be3b1f58e26fa00e8337f/elastic/datadog_checks/elastic/elastic.py#L156 whereas cluster health values are reported as: https://github.com/DataDog/integrations-core/blob/e3368b3ebaa87d37e01be3b1f58e26fa00e8337f/elastic/datadog_checks/elastic/metrics.py#L476 Considering that the index level status is controlled by the worst shard status and the cluster status is controlled by the worst index status, shouldn't the reported values be aligned between the two? 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: Expose a client method for listing jobs See: https://cloud.google.com/bigquery/docs/reference/v2/jobs/list 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: jax_debug_nans does not work with complex numbers Running with flag --jax_debug_nans: With this this, I get no error (but I do get nans): ``` @jax.jit def fn(x): return (x * 0.) / jnp.zeros_like(x) print(fn(1j * jnp.ones([2, 3]))) ``` but with this, I get an error (as expected): ``` @jax.jit def fn(x): return (x * 0.) / jnp.zeros_like(x) print(fn(jnp.ones([2, 3]))) ``` Could we add support for nan detection on complex numbers? 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: Elevate `ENDRUN` to `signals` API We've seen multiple situations now (e.g., https://github.com/PrefectHQ/prefect/issues/1184) where users want to aggressively end a run, avoiding the standard checks. Our `ENDRUN` signal satisfies the correct behavior, but isn't exposed publicly. We should move this signal into our public `signals` API for better visibility to users, and document it accordingly. 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: BigQuery: Add support for use_avro_logical_types for extract jobs use_avro_logical_types is supported for load jobs: https://github.com/googleapis/google-cloud-python/blob/89eaedb4a40bd1268df134cc40a4063d6cf8b823/bigquery/google/cloud/bigquery/job.py#L1318 We should add the same mapping for extract jobs. BigQuery already supports it in the API backend. 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: Tokenizers as an optional dependency # 🚀 Feature request <!-- A clear and concise description of the feature proposal. Please provide a link to the paper and code in case they exist. --> Would it be possible to make `tokenizers` an optional dependency? I see this was already attempted here by @thomwolf: https://github.com/huggingface/transformers/pull/2342. ## Motivation <!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too. --> For various reasons we are unable to support Rust in our environment. Given that `tokenizers` is a hard dependency, this means we cannot use `transformers` at all. We would be fine with using the non-fast versions of tokenizers as a workaround. 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: DISCUSSION: Is there a way for a Transaction to indicate success/failure from __exit__ From #336. Currently, there is no way to determine if this occurs. It's unclear what a way forward would look like but in `ndb` transactions have [retries](https://cloud.google.com/appengine/docs/python/ndb/transactions) and can [create](https://cloud.google.com/appengine/docs/python/ndb/functions) `Future` objects which know about the success or failure. 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: KeyError with '--update-deps' ``` error: KeyError(True,) command: /home/jgrnt/miniconda/bin/conda install --update-deps python= numpy nose scipy matplotlib pandas pytest h5py mkl mkl-service user_agent: conda/4.4.7 requests/2.18.4 CPython/3.6.3 Linux/4.14.4-gentoo gentoo/2.4.1 glibc/2.25 _messageid: -9223372036837525416 _messagetime: 1515513689937 / 2018-01-09 10:01:29 Traceback (most recent call last): File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/exceptions.py", line 743, in __call__ return func(*args, **kwargs) File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/cli/main.py", line 78, in _main exit_code = do_call(args, p) File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/cli/conda_argparse.py", line 76, in do_call exit_code = getattr(module, func_name)(args, parser) File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/cli/main_install.py", line 11, in execute install(args, parser, 'install') File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/cli/install.py", line 236, in install force_reinstall=context.force, File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/core/solve.py", line 504, in solve_for_transaction force_remove, force_reinstall) File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/core/solve.py", line 437, in solve_for_diff final_precs = self.solve_final_state(deps_modifier, prune, ignore_pinned, force_remove) File "/home/jgrnt/miniconda/lib/python3.6/site-packages/conda/core/solve.py", line 385, in solve_final_state for spec in grouped_specs[True]) KeyError: True ``` 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: install_sources installs python sources into wrong directory on windows Standard MSVC python: ``` Python 3.6.6 (v3.6.6:4cf1f54eb7, Jun 27 2018, 03:37:03) [MSC v.1900 64 bit (AMD64)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> from distutils import sysconfig >>> sysconfig.get_python_lib() 'C:\\Python36\\Lib\\site-packages' ``` modules/python.py - INSTALL_PATHS_COMMAND - sets posix_prefix (on windows) ``` print (json.dumps(sysconfig.get_paths(scheme='posix_prefix', vars={'base': '', 'platbase': '', 'installed_base': ''}))) {"stdlib": "\\lib\\python3.6", "platstdlib": "\\lib\\python3.6", "purelib": "\\lib\\python3.6\\site-packages", "platlib": "\\lib\\python3.6\\site-packages", "include": "\\include\\python3.6", "platinclude": "C:\\Python36\\include\\python3.6", "scripts": "\\bin", "data": "."} ``` syconfig does the right thing when not forced into posix_prefix ``` print (json.dumps(sysconfig.get_paths( vars={'base': '', 'platbase': '', 'installed_base': ''}))) >>> print (json.dumps(sysconfig.get_paths( vars={'base': '', 'platbase': '', 'installed_base': ''}))) {"stdlib": "\\Lib", "platstdlib": "\\Lib", "purelib": "\\Lib\\site-packages", "platlib": "\\Lib\\site-packages", "include": "\\Include", "platinclude": "\\Include", "scripts": "\\Scripts", "data": "."} ``` 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: Composing circuit with a switch statement causes a bug in the QASM3 exporter ### Environment - **Qiskit Terra version**: 0.25.0 - **Python version**: 3.9 - **Operating system**: OSX ### What is happening? When composing a circuit with another circuit containing a switch statement and then exporting to OpenQASM 3. I receive an error ``` KeyError: "'ClassicalRegister(3, 'random')' is not defined in the current context" ``` This may be related to #9746. ### How can we reproduce the issue? Run ```python from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister qr = QuantumRegister(3) cr_random = ClassicalRegister(3, "random") cr_result = ClassicalRegister(3, "result") qc = QuantumCircuit(qr, cr_random, cr_result) # build a random state qc.h(qr) # measure the state qc.measure(qr, cr_random) with qc.switch(cr_random) as case: with case(1): qc.x(qr[0]) with case(2): qc.x(qr[1]) with case(3): qc.x(qr[0]) qc.x(qr[1]) with case(4): qc.x(qr[2]) with case(5): qc.x(qr[0]) qc.x(qr[2]) with case(6): qc.x(qr[1]) qc.x(qr[2]) with case(7): qc.x(qr) with case(case.DEFAULT): pass qc.measure(qr, cr_result) composed = QuantumCircuit(3, 6) composed.compose(qc, inplace=True) from qiskit import qasm3 print(qc_qasm3 := qasm3.dumps(composed, disable_constants=True, experimental=qasm3.ExperimentalFeatures.SWITCH_CASE_V1)) ``` ### What should happen? QASM3 should be exported. ### Any suggestions? _No response_ 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: BigQuery: Add maximum_bytes_billed option to magics **Background** BigQuery queries can get expensive, but the `maximum_bytes_billed` query option adds a cap to the price billed and rejects queries that could be too expensive. Provide a default value for `maximum_bytes_billed` when constructing a client by specifying a `default_query_job_config`, but this is not possible when using the `%%bigquery` magics. **Feature Request** Add a `--maximum_bytes_billed` option to `%%bigquery`. Possible values: * `UNSPECIFIED` - Use the default value . Set `job_config.maximum_bytes_billed = google.cloud.bigquery.magics.context.maximum_bytes_billed`. * `--maximum_bytes_billed=None` - No maximum value. Set `job_config.maximum_bytes_billed = None`. This allows all queries to run, overriding any value from the global context. * `--maximum_bytes_billed=123456789` - Set maximum to value specified. Set `job_config.maximum_bytes_billed = int(value)`. * `--maximum_bytes_billed=NotAnInteger` - Raise `ValueError`. 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: wav2vec processor batching logic is too restrictive ### System Info transformers version at the time of writing is `4.26.1` ### Who can help? _No response_ ### Information - [ ] The official example scripts - [ ] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction ```python # !pip install transformers torch # in jupyter notebook from transformers import Wav2Vec2Processor import torch import numpy as np batch = 4 # create Wav2Vec2Processor processor = Wav2Vec2Processor.from_pretrained("facebook/hubert-large-ls960-ft") # generate random input tensor input_tensor = torch.tensor(np.random.randn(batch, 10, 10)) # pass input tensor through processor output = processor(input_tensor, return_tensors="pt") print(output["input_values"].shape) # 1 x 4 x 10 x 10 ``` ### Expected behavior It seems reasonable that an input could be of shape `batch x d_1 x d_2 ...` and I'd expect the output to have the same shape. However, [here](https://github.com/huggingface/transformers/blob/main/src/transformers/models/wav2vec2/feature_extraction_wav2vec2.py#L184) the code has an extra check for type list or tuple that results in it misinterpreting the input as a single example. Side note: I'm unsure what to infer from the type checking logic because it doesn't match the type hints i.e. `tuple` isn't supposed to be possible here anyways, according to the `__call__` type hint. I did check some other examples of `is_batched` appearing in the `src/transformers/models` directory and they look similar but unexpected. 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: Secrets not export via docker-compose config 3.2 Example: ```yml version: '3.2' services: rabbitmq: image: 'Asd' secrets: - source: api-config-v1 target: config.toml secrets: api-config-v1: file: ~/nx_configs/config.toml ``` `docker-compose config` will export: ```yml networks: {} services: rabbitmq: image: Asd secrets: - source: api-config-v1 target: config.toml version: '3.2' volumes: {} ``` It works fine with version 3.1 I may found the problem: https://github.com/docker/compose/blob/master/compose/config/serialize.py#L10 https://github.com/docker/compose/blob/master/compose/config/serialize.py#L12 I think it should be: ``` from compose.const import COMPOSEFILE_V2_2 as V2_2 from compose.const import COMPOSEFILE_V3_2 as V3_2 ``` https://github.com/docker/compose/blob/master/compose/config/serialize.py#L53 because variable `V3_2` contains `3.1` and the version in the config is `3.2` 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: Test for whether inside virtualenv does not work if directory is symlinked The following test for whether IPython is running inside a virtualenv does not work if the python executable and the VIRTUAL_ENV variable are at the same place but one is at a symlinked path to the other: https://github.com/ipython/ipython/blob/5bf4949fbd30de6211226e4b27e8680c4b199fc9/IPython/core/interactiveshell.py#L719 Discovered when using invewrapper, but problem appears more generic: https://github.com/berdario/invewrapper/issues/8 ``` tcorbettclark@cmed1:~$ python -c "import IPython; print(IPython.sys_info())" {'codename': 'An Afternoon Hack', 'commit_hash': '7c2ea3a', 'commit_source': 'installation', 'default_encoding': 'UTF-8', 'ipython_path': '/home/tcorbettclark/.virtualenvs/ice/local/lib/python2.7/site-packages/IPython', 'ipython_version': '1.1.0', 'os_name': 'posix', 'platform': 'Linux-3.5.0-42-generic-x86_64-with-Ubuntu-12.10-quantal', 'sys_executable': '/home/tcorbettclark/.virtualenvs/ice/bin/python', 'sys_platform': 'linux2', 'sys_version': '2.7.3 (default, Sep 26 2013, 16:35:25) \n[GCC 4.7.2]'} tcorbettclark@cmed1:~$ ``` 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: Define static IP address for container It would be useful to be able to define a static IP address for a container within the `docker-compose.yml`. I see that `docker run --ip xxx.xxx.xxx.xxx` is now available in [docker 1.10.0-rc2](https://github.com/docker/docker/releases/tag/v1.10.0-rc2). More details in the merged pull request: https://github.com/docker/docker/pull/19001 Example: ``` docker network create --driver=bridge --subnet=192.168.0.0/24 --gateway=192.168.0.1 mynet docker run --ip=192.168.0.10 --net=mynet -ti some_image ``` Define static IP address for container It would be useful to be able to define a static IP address for a container within the `docker-compose.yml`. I see that `docker run --ip xxx.xxx.xxx.xxx` is now available in [docker 1.10.0-rc2](https://github.com/docker/docker/releases/tag/v1.10.0-rc2). More details in the merged pull request: https://github.com/docker/docker/pull/19001 Example: ``` docker network create --driver=bridge --subnet=192.168.0.0/24 --gateway=192.168.0.1 mynet docker run --ip=192.168.0.10 --net=mynet -ti some_image ``` 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: encoding.py missing OGG_OPUS and SPEEX_WITH_HEADER_BYTE encodings The new encodings OGG_OPUS and SPEEX_WITH_HEADER_BYTE are missing. [https://github.com/GoogleCloudPlatform/google-cloud-python/blob/master/speech/google/cloud/speech/encoding.py][1] [1]: https://github.com/GoogleCloudPlatform/google-cloud-python/blob/46e417e838001f4d1eb13f5e3fc2a54d390dd5db/speech/google/cloud/speech/encoding.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 Lightning-AI/lightning codebase. Here's the problem: fix segmentation demo @akshaykvnit @Borda ``` ERROR collecting pl_examples/full_examples/semantic_segmentation/semseg.py No module named 'torchvision.models.segmentation' oops, looks like this test fails. Need to fix asap ``` 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: jax.numpy.sum behaving funny for non-existent axis When invoking the `sum` operation on a non-existent axis I don't get an error (as would be the expected result), but sums over one of the existing axes. As far as I can tell, for any array `x` with `n` axes, calls to `sum` with axis `j > n` behave as if the provided axis was `j % n`. E.g., if the array `x` has 3 axes, calls to `sum` with `j` being any multiple of three all sum over the first axis (j=0,3,6,9,... all give the same result). This is especially noteworthy for the one-dimensional array (only one axis), where calls to `sum` with any value for `axis` always sums over the whole array. It would be preferable if either an error was raised, or summing over a non-existing axis would be a no-op. Might be related to #278 example code ``` import jax.numpy as np x = np.array([ [ [ 1, 2 ], [ 3, 4 ] ], [ [ 5, 6 ], [ 7, 8] ], [ [ 9, 10 ], [ 11, 12 ] ] ]) assert(np.all(np.sum(x, axis=3) == np.sum(x, axis=0))) assert(np.all(np.sum(x, axis=4) == np.sum(x, axis=1))) assert(np.all(np.sum(x, axis=5) == np.sum(x, axis=2))) assert(np.all(np.sum(x, axis=6) == np.sum(x, axis=0))) # and so on.. ``` 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: name 'IProgress' is not defined name 'IProgress' is not defined when running from Jupyter notebook. 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: html.py conflict with html module find that html.py is conflict with python `html` module. that is why when execute `IPython.__main__.py`, this error appears: ``` python __main__.py /Users/suoyi/Documents/GitHub/ipython/IPython/html.py:12: ShimWarning: The `IPython.html` package has been deprecated since IPython 4.0. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`. warn("The `IPython.html` package has been deprecated since IPython 4.0. " Traceback (most recent call last): File "/Users/suoyi/Documents/GitHub/ipython/IPython/__main__.py", line 12, in <module> from IPython import start_ipython File "/Users/suoyi/miniconda3/envs/ipython/lib/python3.9/site-packages/IPython/__init__.py", line 56, in <module> from .terminal.embed import embed File "/Users/suoyi/miniconda3/envs/ipython/lib/python3.9/site-packages/IPython/terminal/embed.py", line 15, in <module> from IPython.core.interactiveshell import DummyMod, InteractiveShell File "/Users/suoyi/miniconda3/envs/ipython/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 60, in <module> from IPython.display import display File "/Users/suoyi/miniconda3/envs/ipython/lib/python3.9/site-packages/IPython/display.py", line 16, in <module> from IPython.lib.display import * File "/Users/suoyi/miniconda3/envs/ipython/lib/python3.9/site-packages/IPython/lib/display.py", line 5, in <module> from html import escape as html_escape ImportError: cannot import name 'escape' from 'html' (/Users/suoyi/Documents/GitHub/ipython/IPython/html.py) ``` when remove html.py, this error disappear. can you fix this by renaming this 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 ipython/ipython codebase. Here's the problem: HTML vs Iframe I was again the witness of people miss-using HTML to display IFrames, and having issues. Could we detect in HTML the usage of `<iframe>....</iframe>` and warn user that there is an iframe object ? 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: Celerybeat runs periodic tasks every 5 seconds regardless of interval I recently upgraded to celery 3 and have been experiencing some strange behavior with celerybeat, which was acting normally before the upgrade. My environment: python 2.7.3 django 1.4.1 virtualenv django-celery 3.0.6 celery 3.0.6 Regardless of what interval I define for my periodic tasks - which I adjust through the django admin - celerybeat fires off the periodic tasks every 5 seconds. This occurs regardless of the interval. Interestingly, however, when the periodic task is set disabled, celerybeat stops sending tasks, so it must be responsive to the scheduler at some level. 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: Unify basis_gates parameter handling (using a list) <!-- ⚠ 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 have the feeling there is already an issue for this topic but can't seem to find it - apologies if it ends up being a duplicated issue). After #1323, the `basis_gates` for a backend is defined in its configuration as a list: ``` 'basis_gates': ['u1', 'u2', 'u3', 'cx', 'id', 'snapshot'] ``` Traditionally, we have been passing a comma-separated string around for the internal functions (throughout the transpiler layers), which is a tad ackward and cumbersome (specially since the final "consumers" of the basis gates end up splitting the string into a list, such as the `DAGBackend`). Actually one of the changes in #1323 was actually to "stringify" back the basis gates [at the right point in the transpilation process](https://github.com/Qiskit/qiskit-terra/blob/master/qiskit/transpiler/_transpiler.py#L62), mostly for avoiding modifying the function signatures. It might be a good time to avoid that going back and forth entirely, making it always a list throughout the whole transpilation process. ### Proposed solution Remove the default value for `basis_gates` in the functions involved in the transpilation process, updating the docstrings and ensuring that it is handled properly at the main entry point. A potential drawback is that we might need to change the format of the argument in the public `compile()` method, deprecating or similar (although might not be a concern if we mostly keep the change internal). 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: 0.49.0 fails to find Qt5 using qmake My CI fails on both macOS and Windows: https://travis-ci.org/z3ntu/razer_test/jobs/468630035 https://ci.appveyor.com/project/z3ntu/razer-test/builds/21043013/job/5upak41rvyneo2qu `meson.build:20:0: ERROR: Dependency "qt5" not found, tried pkgconfig, qmake-qt5 and qmake` On those platforms, meson used the `qmake` detection with earlier versions 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 - Error message on subscription.close() Python version: 2.7.14 API Client version: 0.33.0 While closing a subscription, the following message is printed to stderr but no exception is thrown: ``` ERROR:root:Exception serializing message! Traceback (most recent call last): File "/miniconda/lib/python2.7/site-packages/grpc/_common.py", line 87, in _transform return transformer(message) TypeError: descriptor 'SerializeToString' requires a 'google.protobuf.pyext._message.CMessage' object but received a 'UUID' ``` Recreated by creating a topic+subscription and running the following script: ``` import google.cloud.pubsub sub_client = google.cloud.pubsub.SubscriberClient() sub_name = sub_client.subscription_path('[PROJECT]', '[SUBSCRIPTION]') sub = sub_client.subscribe(sub_name) sub.open(lambda x: x.ack()) sub.close() ``` 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: Add new example which rewrites Docker Example using functional API By request, so that users can compare the differences. 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: Qasm3 Exporter needs to export arrays of qubtis for concatenation in alias of OpenQASM3. <!-- ⚠ 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? Currently Qasm3 Exporter generates `qubit[2] _q; let q = _q[0] || _q[1];` to generate an array of `qubit`s in OpenQASM 3. https://github.com/Qiskit/qiskit-terra/blob/main/test/python/circuit/test_circuit_qasm3.py#L34-L35 However, I think that the spec allows concatenating of only two arrays. https://qiskit.github.io/openqasm/language/types.html#register-concatenation-and-slicing In the above case, the type of ` _q[0]` and `_q[1]` is `qubit` and not `qubit[1]`. One of quick fixes may be generating `let q = _q[0:0] || _q[1:1];` instead of `let q = _q[0] || _q[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: shared_library vs_modules_defs parameter dies when passed anything but string I'm not sure whether the bug here is that passing a list (particularly an empty one) is not acceptable, or whether generating a giant stacktrace instead of a nice error message is the bug. But either a more helpful error message or accepting the empty list would be good. meson psuedo code: ```meson if cc.get_id() == 'msvc' def = 'foo.def' else def = [] endif libfoo = shared_library( 'libfoo', 'foo.c', vs_modules_def: def, ) ``` 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: Create a single point for tracking package version Currently version is tracked in both `setup.py` and the `__init__.py`. I would recommend moving to a single location for both to avoid possible headaches in the future. Possible solutions from Python docs: [https://packaging.python.org/guides/single-sourcing-package-version/](https://packaging.python.org/guides/single-sourcing-package-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 jupyterlab/jupyterlab codebase. Here's the problem: Edit/cmd mode keyboard toggles not working Esc/Enter should move back and forth between cmd/edit mode, currently not working. 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 %magic help, remove duplicate aliases Certain magics are actually just aliases of another, like %hist and %history. In %magic, we show the full help for both, which can be confusing. We should instead indicate which one is an alias and refer the reader to the original for details. 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: Modifications to PCH don't trigger rebuild of the target with GCC Modifying the header file only rebuilds the PCH, but doesn't rebuild the target. If a header that is included by the PCH is modified, then only the sources that also `#include` it will be rebuilt, which leads to inconsistencies and surprising bugs. I've only tested this with GCC 8.2.1 and Clang 7.0.1 so far, C only. With clang it works fine: updating the pch rebuilds the whole project. I'm not sure if this might be a GCC bug (omitting command-line includes from the depfile?), but even if it is, I think it's worth working around in Meson anyway. 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: follow up from #948 add a remove_all_accounts() command <!-- ⚠ 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? removed many accounts are annoying we need a remove_all command 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: DOC: argmin, argmax, argort, etc. should link to `np.take_along_axis` in their documentation In #6075, I wondered whether it might be possible to > to have some simple way to use the output of `np.arg[min|max|sort]` as a proper index (to avoid hackery as in https://github.com/astropy/astropy/blob/master/astropy/time/core.py#L896 -- if there is a simpler way already, let me know!) and @jaimefrio suggested that it might be simpler to have > a `make_me_an_indexing_tuple=False` new keyword argument for the `argxxx` functions? That indeed seems better, so I'm raising this as a separate issue. The code linked to above could be used as a template on how to generate the index tuple. 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: Recommended Adafactor settings for T5 cause error ## Environment info - `transformers` version: 3.3.1 - Platform: Darwin-19.6.0-x86_64-i386-64bit - Python version: 3.7.7 - PyTorch version (GPU?): 1.6.0 (False) - Tensorflow version (GPU?): 2.2.0 (False) - Using GPU in script?: No - Using distributed or parallel set-up in script?: No ### Who can help @sshleifer (from activity on Adafactor PRs) ## Information Model I am using (Bert, XLNet ...): T5 The problem arises when using: * [ ] the official example scripts: (give details below) * [X] my own modified scripts: (give details below) The tasks I am working on is: * [ ] an official GLUE/SQUaD task: (give the name) * [X] my own task or dataset: (give details below) ## To reproduce The Adafactor docs recommend the following for T5 : `Adafactor(model.parameters(), lr=1e-3, relative_step=False, warmup_init=True)` However, the init code then has: ``` if lr is not None and relative_step: raise ValueError("Cannot combine manual lr and relative_step options") if warmup_init and not relative_step: raise ValueError("warmup_init requires relative_step=True") ``` which makes this setting impossible (as well as just changing to `relative_step=True`). So something seems to be missing either in the recommendations or in the implementation. Thanks! 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: Can't pickle UFuncTypeError numpy 1.18.4-py38h8854b6b_0 (conda-forge) Linux x64 ```python import pickle import numpy try: numpy.ones(1) * "foo" except Exception as e: pickle.dumps(e) ``` Output: ``` Traceback (most recent call last): File "ufunctypeerror.py", line 6, in <module> numpy.ones(1) * "foo" numpy.core._exceptions.UFuncTypeError: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U32'), dtype('<U32')) -> dtype('<U32') During handling of the above exception, another exception occurred: Traceback (most recent call last): File "ufunctypeerror.py", line 8, in <module> pickle.dumps(e) _pickle.PicklingError: Can't pickle <class 'numpy.core._exceptions.UFuncTypeError'>: it's not the same object as numpy.core._exceptions.UFuncTypeError ``` 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: Escaping espaces for defines in cmake generator Comes from: https://github.com/conan-io/cmake-conan/issues/82 ```python def package_info(self): self.cpp_info.defines= ['MY_DEF=My string', 'MY_DEF2=My other string'] ``` Fails because of the spaces. Escaping in cmake works. cc/ @atvise 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 configure -Doption=unknown-value fails with a traceback Compare: ```console $ meson configure build -Dman=asdf Traceback (most recent call last): File "/usr/bin/meson", line 37, in <module> sys.exit(main()) File "/usr/bin/meson", line 34, in main return mesonmain.run(sys.argv[1:], launcher) File "/usr/lib/python3.6/site-packages/mesonbuild/mesonmain.py", line 302, in run return mconf.run(remaining_args) File "/usr/lib/python3.6/site-packages/mesonbuild/mconf.py", line 279, in run c.set_options(options.sets) File "/usr/lib/python3.6/site-packages/mesonbuild/mconf.py", line 130, in set_options tgt.set_value(v) File "/usr/lib/python3.6/site-packages/mesonbuild/coredata.py", line 131, in set_value raise MesonException('Value "%s" for combo option "%s" is not one of the choices. Possible choices are: %s.' % (newvalue, self.name, optionsstring)) mesonbuild.mesonlib.MesonException: Value "asdf" for combo option "man" is not one of the choices. Possible choices are: "auto", "true", "false". $ meson build-tmp -Dman=asdf The Meson build system Version: 0.43.0 Source dir: /home/zbyszek/src/systemd Build dir: /home/zbyszek/src/systemd/build-tmp Build type: native build Meson encountered an error in file meson_options.txt, line 96, column 0: Value "asdf" for combo option "man" is not one of the choices. Possible choices are: "auto", "true", "false". A full log can be found at /home/zbyszek/src/systemd/build-tmp/meson-logs/meson-log.txt ``` This is with meson-0.43.0-1.fc27.noarch. 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: Storage: Blob.compose doesn't use default content_type [`Blob.compose`](https://github.com/GoogleCloudPlatform/google-cloud-python/blob/51ba7e148fc76e07018dc60192219fb28ff628b0/storage/google/cloud/storage/blob.py#L1363-L1381) does not use the [`self._get_content_type` method](https://github.com/GoogleCloudPlatform/google-cloud-python/blob/51ba7e148fc76e07018dc60192219fb28ff628b0/storage/google/cloud/storage/blob.py#L605-L633), which means Blob.compose raises an error if the `content_type` is not explicitly specified. This is [documented behavior](https://github.com/GoogleCloudPlatform/google-cloud-python/blob/51ba7e148fc76e07018dc60192219fb28ff628b0/storage/google/cloud/storage/blob.py#L1377-L1381), but is it intended behavior? Should compose use `self._get_content_type` to use the default type, or perhaps infer the type from the blobs being composed? 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: Make Meson recover from bad download **Describe the bug** When meson encounters an error while downloading a dependency, it might get into inconsistent state with following error: ``` meson.build:147:0: ERROR: Subproject exists but has no meson.build file ``` **To Reproduce** ```meson # meson.build project('test', 'c') executable('main', 'main.c', dependencies: [ subproject('libuv').get_variable('libuv_dep') ] ) ``` ```c // main.c int main(int argc, char **argv) { return 0; } ``` ```ini # subprojects/libuv.wrap [wrap-file] directory = libuv-v1.42.0 source_url = https://dist.libuv.org/dist/v1.42.0/libuv-v1.42.0.tar.gz source_filename = libuv-v1.42.0.tar.gz source_hash = 43129625155a8aed796ebe90b8d4c990a73985ec717de2b2d5d3a23cfe4deb72 patch_filename = libuv_1.42.0-1_patch.zip patch_url = https://bad-wrapdb.mesonbuild.com/v2/libuv_1.42.0-1/get_patch patch_hash = 891698d781bc68379b799e47bc7e100698f03985b6db5d1ddc4eaa9be42a8f35 [provide] libuv = libuv_dep ``` `bad-wrapdb` above will simulate a network error (in practice error might be caused by network timeout, temporary DNS resolution issue, etc.). Now do usual `meson setup build` and you'll get an obvious error. If you replace `bad-wrapdb` with `wrapdb` to simulate the end of intermittent network issues you'll get: ``` meson.build:3:0: ERROR: Subproject exists but has no meson.build file ``` **Expected behavior** Meson shoudn't keep subprojects in inconsistent state when such issues happen and thus should be able to recover without requiring user to go and manually remove directories under `subprojects`. Retries would also be nice to have I think, like 3 attempts with exponential backoff. **system parameters** * Plain native build * Ubuntu 21.04 * Python 3.9.5 * Meson 0.60.2 * Ninja 1.10.2.git.kitware.jobserver-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: Huggingface create_optimizer method not working ## Environment info - `transformers` version: 3.0.2 - Platform: Windows-10-10.0.18362-SP0 - Python version: 3.6.6 - PyTorch version (GPU?): 1.5.0+cpu (False) - Tensorflow version (GPU?): 2.2.0 (False) - Using GPU in script?: No - Using distributed or parallel set-up in script?: No ### Who can help @sgugger @jplu ## Information Model I am using (Bert, XLNet ...): Roberta The problem arises when using: * [ ] my own modified scripts: (give details below) The tasks I am working on is: * [ ] my own task or dataset: (give details below) ## To reproduce Steps to reproduce the behavior: 1. Run this code: ``` import tensorflow as tf from transformers import RobertaConfig, TFRobertaForMaskedLM, create_optimizer config = RobertaConfig() optimizer,lr = create_optimizer(1e-4,1000000,10000,0.1,1e-6,0.01) training_loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True) model = TFRobertaForMaskedLM(config) model.compile(optimizer=optimizer, loss=training_loss) input = tf.random.uniform(shape=[1,25], maxval=100, dtype=tf.int32) hist = model.fit(input, input, epochs=1, steps_per_epoch=1,verbose=0) ``` 2. I am getting an error: > TypeError: apply_gradients() got an unexpected keyword argument 'experimental_aggregate_gradients' ## Expected behavior optimizer should be created 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: @CURRENT_SOURCE_DIR@ expands to ../ instead of .. Using meson 0.42.0. My goals were similar to those in https://github.com/mesonbuild/meson/issues/1622 but my sources are setup as follows: ``` ├── meson.build ├── proto │ ├── myproto.capnp ├── src └── test ├── meson.build ├── proto │ └── testproto.capnp ├── tests-main.cpp ``` and as such, I'd like to create a single `generator` in the top level meson.build: ``` capnproto_gen = generator(capnp, output : ['@PLAINNAME@.c++', '@PLAINNAME@.h'], arguments : ['compile', '--src-prefix=@CURRENT_SOURCE_DIR@/proto', '-oc++:@BUILD_DIR@', '@INPUT@'] ) ``` However, in the top level build file `@CURRENT_SOURCE_DIR@` expands to `../` (as verified w `ninja -v`) instead of `..`, which creates paths like `--src-prefix=..//proto` which the generator does not accept. It actually ends up working in the subdir, as it expands to `../test` which happens to work OK. I tried `arguments : ['compile', '--src-prefix=@0@/proto'.format(meson.current_source_dir()), '-oc++:@BUILD_DIR@', '@INPUT@']` but that doesn't work since the call to `format()` only happens when the top level build file is processed, not at expansion time. 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: Support 'capacityProviderStrategy' option for ECSOperator **Description** [AWS launches Fargate Spot](https://aws.amazon.com/about-aws/whats-new/2019/12/aws-launches-fargate-spot-save-up-to-70-for-fault-tolerant-applications/) on December, 2019. It can be configured in [run_task on boto3 with 'capacityProviderStrategy' option](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/ecs.html#ECS.Client.run_task). It would be nice if we could set this option for ECSOperator. **Use case / motivation** Tasks with Fargate Spot are cheaper than tasks without Fargate Spot. **Related Issues** None found. 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: Should be able to initialize from an integer <!-- ⚠ 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? Should be able to do: ```` qc.initialize(int) ```` and have it add x gates where the bit values are one. 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: Ability to create internal networks missing I cannot find a way to specify in the docker-compose file (even v2) that a network must be internal (as if it was created with `docker network create --internal ...`). 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: [ldap] section in configuration is not applicable anymore in 2.0 **Apache Airflow version**: 2.0.0b* / master **What happened**: `[ldap]` section in `airflow.cfg` is not applicable anymore in 2.0 and `master`, because the LDAP authentication (for webserver and API) is handled by FAB, and the configuration for this is handled by `webserver_config.py` file. ![airflow_–_default_airflow_cfg](https://user-images.githubusercontent.com/11539188/99289209-ef210700-283c-11eb-948e-16811ba09293.png) **What you expected to happen**: The `[ldap]` section should be removed from `airflow/config_templates/default_airflow.cfg` and `airflow/config_templates/config.yml` (and some other applicable files). Otherwise leaving this section there will be a big confusion for users. 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: CLI: Add --detach option for up, run and exec commands This contribution allows the usage of --detach option when running: docker-compose run --detach docker-compose exec --detach docker-compose up --detach The behavior is the same as the -d option. I think it would be one item from #363 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: Conan replaces backslashes with forward slashes in env_info variable in activate.bat Conan replaces all backslashes with forward slashes in activate.bat (and activate.ps1 and activate.sh). This means that to use a variable to pass the path to an executable, we have to manually convert the forward slashes back to backslashes. I am using Conan 1.8.4 on Windows on Python 3.6. I have created a conanfile.py which contains the following: ```python from conans import ConanFile import os.path class TestPkgConan(ConanFile): name = "TestPkg" version = "0.0.1" description = "A test package" settings = "os", "arch" def package_info(self): self.env_info.testpkg_root = self.package_folder self.env_info.testpkg_normalized = os.path.normpath(self.package_folder) self.env_info.testpkg_test = 'AC\\DC' ``` and I get the following activate.bat from the virtualenv generator ```cmd @echo off SET PROMPT=(conanenv) %PROMPT% SET testpkg_root=C:/.conan/data/TestPkg/0.0.1/adam/testing/package/ca33edce272a279b24f87dc0d4cf5bbdcffbc187 SET testpkg_normalized=C:/.conan/data/TestPkg/0.0.1/adam/testing/package/ca33edce272a279b24f87dc0d4cf5bbdcffbc187 SET testpkg_test=AC/DC ``` I would expect the environment variable to be set verbatim to the value I chose. And the job of doing path separator conversion to be the packagers, however given that conan seems to do path separator conversion I would at least expect it to output windows native paths for files which are supposed to be consumed by Windows native tools, i.e. activate.bat and activate.ps1. 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: Define package-revision exploration/search in Api V2 How to inspect the different revisions of a package recipe from a server? ``conan search`` only retrieves latest. Same for package binaries too. 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: Remove pre-3.8 codepath. Once https://github.com/ipython/ipython/pull/13315 is merged the master branch will not support 3.7 anymore, this gives opportunities to remove all the pre-3.8 codepath. If you like to contribute, find 1 block of code that is execute only before python 3.8 (look for sys.version_info in the code base), and simplify it. It may be more than just deleting code, as you might be then able to cleanup imports, or simplify more logics. 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: Bump NPY_API_VERSION for 1.14 I attempted this in my own PR but failed. The version needs to be increased to use WRITEBACKIFCOPY. 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: Autoreload Enum Error I'm getting a weird error when trying to use autoreload and Enums. I have an Enum class defined in a file as: ```python class MyEnum(Enum): A = 'A' B = 'B' ``` Using `%autoreload 2`, if I try to add `C = 'C'` to `MyEnum`, or remove an existing definition, I get the following error: ``` [autoreload of updates_type failed: Traceback (most recent call last): File "/home/amarder/anaconda3/lib/python3.5/site-packages/IPython/extensions/autoreload.py", line 247, in check superreload(m, reload, self.old_objects) RecursionError: maximum recursion depth exceeded ] ``` Sometimes it is a different error: ``` [autoreload of updates_type failed: Traceback (most recent call last): File "/home/amarder/anaconda3/lib/python3.5/site-packages/IPython/extensions/autoreload.py", line 247, in check superreload(m, reload, self.old_objects) AttributeError: __abstractmethods__ ] ``` I'm running the code on Debian Linux, using Anaconda with python 3.5. 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: SimMIM output num_channels should not be hardcoded ### Feature request In all 3 simmim models, reconstructed images channel is hardcoded as 3. This should be configurable as num_channels ``` deit/modeling_deit.py swin/modeling_swin.py vit/modeling_vit.py nn.Conv2d(in_channels=config.hidden_size, out_channels=config.encoder_stride**2 * 3, kernel_size=1) ``` @NielsRogge ### Motivation I'm training a grayscale model, but the reconstructed image has different dimension as the input image. ### Your contribution None 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: Regression: np.ma.masked_values(..., shrink=True) no longer works The [documentation for `np.ma.masked_values()`](https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.ma.masked_values.html) explains the role of the `shrink` option (which defaults to True) as follows: > Whether to collapse a mask full of False to nomask. In Numpy <= 1.13.3, this works correctly: ``` $ python -c 'import numpy as np; print(repr(np.ma.masked_values(np.arange(10.0), -1)))' masked_array(data = [ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9.], mask = False, fill_value = -1.0) ``` In Numpy >= 1.14.0 and on master, it is broken: ``` $ python -c 'import numpy as np; print(repr(np.ma.masked_values(np.arange(10.0), -1)))' masked_array(data=[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0], mask=[False, False, False, False, False, False, False, False, False, False], fill_value=-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 numpy/numpy codebase. Here's the problem: `np.random.permutation` & `np.random.shuffle` are slow. `np.random.permutation(x)` is the same as `x[np.random.permutation(x.shape[0])]` semantically if `x` is an array. Why the latter is so much faster than the former? ```python x = np.random.rand(50000, 2) %timeit x.take(np.random.permutation(x.shape[0]), axis=0) # 1.02 ms %timeit x[np.random.permutation(x.shape[0])] # 1.75 ms %timeit np.random.permutation(x) # 34.1 ms %timeit np.random.shuffle(x) # 34.2 ms ``` 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: Multiple v1 config files breaks logging I don't think this is specific to AWS, but this is where I was able to repro. Of the following scenarios, only "Two v1 config files" fails to generate the AWS logs output. It does, however, run the command and produce no error messages. The fact that it works with the "v2" config files means that it is probably either user error on my part or a Docker Compose bug. ``` gherkin Feature: Docker Compose awslogs driver Background: Given Docker v1.10.1 And Docker Compose v1.6.0 And the Docker daemon is configured correctly for the `awslogs` driver And config file "a-v1.yml" like so: """ a: image: alpine log_driver: awslogs log_opt: awslogs-region: us-west-2 awslogs-group: docker command: date """ And config file "b-v1.yml" like so: """ b: image: alpine command: date """ And config file "a-v2.yml" like so: """ version: '2' services: a: image: alpine logging: driver: awslogs options: awslogs-region: us-west-2 awslogs-group: docker command: date """ And config file "b-v2.yml" like so: """ version: '2' services: b: image: alpine command: date """ Scenario: Single v1 config file When I run `docker-compose -f a-v1.yml run --rm a` Then I see the output in the AWS logs Scenario: Two v1 config files When I run `docker-compose -f a-v1.yml -f b-v1.yml run --rm a` Then I see the output in the AWS logs Scenario: Single v2 config file When I run `docker-compose -f a-v2.yml run --rm a` Then I see the output in the AWS logs Scenario: Two v2 config files When I run `docker-compose -f a-v2.yml -f b-v2.yml run --rm a` Then I see the output in the AWS logs ``` 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: Need documentation for understanding the difference between `7B` and `7Bf` Unclear what the tradeoffs are between using eg `7B` and `7Bf` as an argument for `model_size` in the `convert_llama_weights_to_hf.py` script: https://github.com/huggingface/transformers/blob/f9cc333805c47665c6afee8b5867931e54abe0c6/src/transformers/models/llama/convert_llama_weights_to_hf.py#L65 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: Automate docs for `values.yaml` via pre-commit config and break them into logical groups Automate docs for values.yaml via pre-commit config and break them into logical groups like https://github.com/bitnami/charts/tree/master/bitnami/airflow 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: Whitespace in error messages I started creating an environment then cancelled it. The error messages for the later commands have some extra vertical whitespace. Also, the "CondaValueError" part and "Value Error" parts seem like they shouldn't be included in the terminal output. ``` $conda create -n dot2tex python=2.7 CondaValueError: Value error: prefix already exists: /Users/aaronmeurer/anaconda/envs/dot2tex $conda remove -n dot2tex --all Remove all packages in environment /Users/aaronmeurer/anaconda/envs/dot2tex: $conda create -n dot2tex python=2.7 ... ``` Whitespace in error messages I started creating an environment then cancelled it. The error messages for the later commands have some extra vertical whitespace. Also, the "CondaValueError" part and "Value Error" parts seem like they shouldn't be included in the terminal output. ``` $conda create -n dot2tex python=2.7 CondaValueError: Value error: prefix already exists: /Users/aaronmeurer/anaconda/envs/dot2tex $conda remove -n dot2tex --all Remove all packages in environment /Users/aaronmeurer/anaconda/envs/dot2tex: $conda create -n dot2tex python=2.7 ... ``` 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: hotdoc module generates broken "Edit on github" links - Browse to https://mesonbuild.com/Hotdoc-module.html - Click "Edit on github" - Be redirected to https://github.com/mesonbuild/meson//edit/master/docs/builddir/markdown/Hotdoc-module.md - notice "builddir/" in the url /cc @thiblahute 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: [revisions] Error on search recipe revisions in remote When revisions are NOT enabled in the Conan Client and a remote search or recipe revisions is done, Conan errors with: ``` $ conan search wiringpi/2.46@conan/stable --revisions -r conan-virtual ERROR: The remote doesn't support revisions. [Remote: conan-virtual] ``` H owever, the remote DOES support revisions and the fault is in the client not having them activated and thus not being able to talk via V2 with the remote. There should be raise early in the code saying that revisions are not enabled, then, if the user enables revisions and finally the remote DOES NOT support revisions, the message ``ERROR: The remote doesn't support revisions. [Remote: conan-virtual]`` would be valid ---------------------------------------- There could be also the option of disabling the ``--revisions`` flag even for local search when revisions are not enabled 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: TrainingArguments._n_gpus serialization I'm not sure, but I think that `TrainingArguments._n_gpu` attribute is not supposed to be serialized in `TrainingArguments.to_dict()` . Or even basically all the attributes that are defined as `dataclass.field(init=False...)` should be filtered out while doing `to_dict()`. What do you think? @sgugger 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: ppermute is returning 0s Tested with TPUs. ```python @partial(jax.pmap, axis_name="shard") def f(a): return jax.lax.ppermute( a, "shard", zip(range(8), [1, 0, 2, 3, 4, 5, 6, 7])) a = np.ones((8, 2, 2)) print(f(a)) ``` Prints out ``` [[[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 0.]] [[0. 0.] [0. 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 huggingface/transformers codebase. Here's the problem: BioGPT Token Classification ### Feature request It would be nice to have this available. ### Motivation working on biomedical token classification datasets and I would like to try BioGPT with them. ### Your contribution I could send a PR if you want. I guess it shouldn't be too hard. 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: Add support for lifecycle management in gcloud.storage.bucket Consider allowing storage.bucket.Bucket.delete_key to silently fail if user requests it From TODO: ``` python # TODO: Should we accept a 'silent' param here to not raise an exception? ``` See [`storage.bucket.Bucket.delete_key`](https://github.com/GoogleCloudPlatform/gcloud-python/blob/1f2aaf3606802f4f02eeb30e22e1082ef7f4594e/gcloud/storage/bucket.py#L158) for relevant code and #146 for some context. `git blame` output ``` b7f1b774 (JJ Geewax 2014-01-29 18:02:29 -0500 158) # TODO: Should we accept a 'silent' param here to not raise an exception? ``` Big query TIMESTAMP field off by factor of 1000 Using master branch. In BigQuery TIMESTAMP fields are off by a factor of 1000 when using fetch_data. See my in-line comment - https://github.com/GoogleCloudPlatform/gcloud-python/commit/41e64395661a31af8352fb2358e5c95ff5437830#diff-c56e349a3e511bfabb4e8dfcfe686bc8R739 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: Core: change the default timeout of JSONConnection.api_request() to non-None As discussed offline - a `None` default timeout can cause requests to hang indefinitely, which is especially problematic in libraries that do not provide any reasonable means of overriding that timeout. In order to avoid bugs resulting from that, the current default needs to be changed. 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: Include partition_expr in DuckDB documentation From https://github.com/pybokeh/dagster-partitioning-av: > Furthermore, I was using duckdb IO manager, but I soon learned dagster's documentation for duckdb integration isn't as complete as their Snowflake documenation. It was not until I looked at their Snowflake's [documenation](https://docs.dagster.io/integrations/snowflake/reference#storing-partitioned-assets) did I learn that I need to add the metadata= parameter to add the partition_expr key and it's value. 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: Test that dataset not updated when task skipped the AIP specifies that when a task is skipped, that we don’t mark the dataset as “updated”. we should simply add a test that verifies that this is what happens (and make changes if necessary) @blag, i tried to make this an issue so i could assign to you but can't. anyway, can reference in PR with `closes` 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: "name" is not a valid service config field Example: ``` yaml web: image: "alpine:edge" name: "different name" ``` This config would be valid, but shouldn't be. I think `name` is included because we modify the config to move the name in as a field, but I think we should validate it separately as part of the "top level" validation instead. The example config should raise an error about an unsupported key. 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: Reconsider an optimization for triggers when there are no upstream states Right now, triggers are skipped if there are no upstream states. This was originally done because it seemed like a simple optimization -- if there are no upstream states, there's no need to compare them to a trigger function. However, `manual_only` should fire regardless, so we should remove this optimization. The one catch is to make sure that all triggers properly handle the (very likely) scenario of receiving an empty set of upstream states. 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: Consider PackageFolders that abstract layout for cache, workspaces Now, the layout of a conan package is cache is directly obtained from ``ClientCache``, which is hardcoded into many processes and algorithms. It might be useful to create an abstract ``PackageFolders`` or similar, that abstract that. It will have a concrete ``CachePackageFolders`` which will be an indirection over the ``ClientCache``, but it could be replaced by a ``WorkspacePackageFolders``, for workspaces. It could also enable improvements in the local workflow, and allow other cache layouts, and other operations (e.g. ``conan download`` directly to user folder) 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: Barrier when reversebits circuit drawer <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Informations - **Qiskit Terra version**: - **Python version**: - **Operating system**: ### What is the current behavior? I saw two problems when using barriers in the latex drawer. 1. When using `'reversebits': True` in the style, the barriers get messed up. The following should have barriers on quantum registers q and v: ![image](https://user-images.githubusercontent.com/8622381/46925091-21296480-cff8-11e8-943f-d35e4d9feb56.png) 2. The style `'plotbarrier': False` is introduced by the mpl drawer, but the latex drawer ignores it. It would be nice if this style affected both drawers. ### Steps to reproduce the problem ``` from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit from qiskit.tools.visualization import circuit_drawer q = QuantumRegister(3, 'q') v = QuantumRegister(2, 'v') c = ClassicalRegister(4, 'c') d = ClassicalRegister(3, 'd') circ = QuantumCircuit(q, v, c, d) circ.x(q[0]) circ.x(q[2]) circ.x(v[1]) circ.barrier(q) circ.barrier(v) circ.measure(q[0], c[1]) circ.measure(q[2], d[2]) circ.measure(v[1], c[0]) circuit_drawer(circ, output='latex', scale=0.5, style={'reversebits': True, 'plotbarrier': False}) ``` ### What is the expected behavior? Barrier on registers `q` and `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 numpy/numpy codebase. Here's the problem: Source link in doc of `printoptions` goes to contextlib The source link in [the documentation of the new `printoptions` context manager](https://docs.scipy.org/doc/numpy/reference/generated/numpy.printoptions.html?highlight=printoption) has the wrong link target: it goes to the invalid ``` http://github.com/anaconda3/lib/python3.6/contextlib.py#L281-L311 ``` Seems like an issue with the link auto-generation machinery, maybe even with other decorated functions? 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: Ability to configure project without a language The use case would be something like a Gnome application written purely in a scripting language such as Python. As such it never needs a C compiler to build any libraries but it is still far more useful than setuptools because you have easy access to building GResource files, configuring desktop files, handling translations, and it isn't setuptools which is awful. 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: Separate out a new builder package <!-- Welcome! Thanks for thinking of a way to improve JupyterLab. If this solves a problem for you, then it probably solves that problem for lots of people! So the whole community will benefit from this request. Before creating a new feature request please search the issues for relevant feature requests. --> ### Problem We are starting to add a lot of dependencies to `buildutils` that aren't needed for simple utilities like `update:dependency`. <!-- Provide a clear and concise description of what problem this feature will solve. For example: * I'm always frustrated when [...] because [...] * I would like it if [...] happened when I [...] because [...] --> ### Proposed Solution Create a new top-level `builder` package (`@jupyterlab/builder`) that has the `webpack` config and the `build-extension` script. <!-- Provide a clear and concise description of a way to accomplish what you want. For example: * Add an option so that when [...] [...] will happen --> ### Additional context Also need to move the `source-map-loader` and `html-loader` out of this package and back into `dev_mode`. <!-- Add any other context or screenshots about the feature request here. You can also include links to examples of other programs that have something similar to your request. For example: * Another project [...] solved this by [...] --> 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: `slogdet` sign is incorrect In the following, numpy disagrees with JAX ```python mat = np.array([[[-0.01]], [[-0.01]]]) print(np.linalg.slogdet(mat)) print(jnp.linalg.slogdet(jnp.array(mat))) ``` => ``` (array([-1., -1.]), array([-4.60517019, -4.60517019])) (DeviceArray([1., 1.]), DeviceArray([-4.60517019, -4.60517019])) ``` 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: Recent shape checking changes result in new XLA errors It turns out that PR #2017 breaks the following code: ``` array = np.ones(5) print(array[:10]) ``` should print `[1. 1. 1. 1. 1.]` but instead throws an error ``` Traceback (most recent call last): File "/Users/necula/Source/jax/jax/interpreters/xla.py", line 230, in primitive_computation return c.Build() File "/Users/necula/Source/jax/jax/lib/xla_bridge.py", line 281, in Build *args, **kwargs) File "/Users/necula/Source/jax/build/jaxlib/xla_client.py", line 734, in Build return Computation(self._builder.Build(), backend=backend) RuntimeError: Invalid argument: Slice size at index 0 in gather op is out of range, must be within [0, 6), got 10.: ``` In some sense this error is reasonable, but it is not what JAX used to do before. Before JAX used to sanitize indices, and produce the following JAXPR for the `gather`: ``` { lambda b ; a. let c = gather[ dimension_numbers=GatherDimensionNumbers(offset_dims=(0,), collapsed_slice_dims=(), start_index_map=(0,)) operand_shape=(5,) slice_sizes=(5,) ] a b in c } ``` After this change, the JAXPR is: ``` { lambda b ; a. let c = gather[ dimension_numbers=GatherDimensionNumbers(offset_dims=(0,), collapsed_slice_dims=(), start_index_map=(0,)) operand_shape=(5,) slice_sizes=(10,) ] a b in c } ``` 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: integrate content/images on broadcasting in docs https://scipy.github.io/old-wiki/pages/EricsBroadcastingDoc explains broadcasting well (including useful diagrams) and is linked to from https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html. It is the only link to https://scipy.github.io/old-wiki left. This content should be integrated in the user guide. There's also useful code to draw such diagrams at https://jakevdp.github.io/PythonDataScienceHandbook/02.05-computation-on-arrays-broadcasting.html 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: Drop support for `fig.yml` and FIG_PROJECT_NAME It's been a year and 5 releases, I think 1.6 will be a good time to drop support, since we're introducing a bunch of new conditionals for v1/v2 config. 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 kubeflow/pipelines codebase. Here's the problem: Cloudpickle fails to deserialize a function Deserializing a python function during runtime fails in case the function has a default parameter, which uses an argo variable. Here is a simple example: ``` def _test_func( path: str, local_path: str, remote_artifact_name: str, minio_bucket: str = 'mlpipeline', minio_key: str = 'runs/{{workflow.uid}}/{{pod.name}}', minio_ext: str = '.tgz', ): remote_path = f'minio://{minio_bucket}/{minio_key}/{remote_artifact_name}{minio_ext}' print(remote_path) ``` This can be executed fine when compiled with 0.1.19 (latest version in PyPI), but fails with the latest master (which uses cloudpickle). The error message is one of the following: - in case only `{{workflow.uid}}` is used: ``` Traceback (most recent call last): File "<string>", line 9, in <module> AttributeError: 'dict' object has no attribute 'append' ``` - in case `{{pod.name}}` is used: ``` Traceback (most recent call last): File "<string>", line 9, in <module> _pickle.UnpicklingError: invalid load key, '5'. ``` Using a default value without brackets resolves the 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 conan-io/conan codebase. Here's the problem: Packages should include licensing information Some projects cannot operate with specific licenses and having that information would be significantly helpful. An added bonus would be to add restrictions on what licenses can be used/not used for a project. This feature would need to support libraries that have multiple licensing agreements (i.e. Qt with LGPL2 and LGPL3). 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: BigQuery: harden 'ArrayQueryParameter.from_api_repr' against missing 'parameterValue'. Closes #7309. 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: Suggest %pip or %conda when user types !pip or !conda To guide users towards doing things right, could we suggest they use the magics instead of the shell invocations? Possibly with a short explanation why. Was also mentioned in <https://github.com/ipython/ipython/pull/11524#issuecomment-444875270>. Suggest %pip or %conda when user types !pip or !conda To guide users towards doing things right, could we suggest they use the magics instead of the shell invocations? Possibly with a short explanation why. Was also mentioned in <https://github.com/ipython/ipython/pull/11524#issuecomment-444875270>. 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: "visual_studio" generator support for multi-config variables (N configs -> 1 package) I'm introducing ```conan``` in products of my company. But, I found one limitation and I want improvement of it. http://docs.conan.io/en/latest/creating_packages/package_approaches.html#n-configs-1-package > The automatic conversion of multi-config variables to generators is currently only implemented in the cmake and txt generators. If you want to have support for them in another build system, please open a GitHub issue for it. I found that sentence in above documentation. And I want to have support for them in **Visual Studio**, So I open this issue. Thank you. 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: BUG: mgrid result sensitive to data type Using `np.mgrid' depends on slice dtype ### Reproducing code example: ```python import numpy as np a = np.mgrid[[slice(np.float32(0.1), np.float32(0.3), np.float32(0.1)) for _ in range(1)]] # returns array([[0, 0, 0]]) b = np.mgrid[[slice(np.float64(0.1), np.float64(0.3), np.float64(0.1)) for _ in range(1)]] # returns array([[0.1, 0.2]]) np.testing.assert_allclose(a, b) ``` ### Numpy/Python version information: <!-- Output from 'import sys, numpy; print(numpy.__version__, sys.version)' --> 1.18.4 3.6.7 (default, Mar 27 2020, 15:56:09) [GCC 6.5.0 20181026] 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: Rewrite Finite Difference/Parameter Shift/Linear Comb. of Unitaries gradients with primitives. 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: What is the purpose of the empty "prefect.flows" module? What is the purpose of the empty "prefect.flows" module? It is also imported here https://github.com/PrefectHQ/prefect/blob/6f1015957019a86bb86a0504555c354cd8f4af6e/src/prefect/__init__.py#L14 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: celery beat: OSError: [WinError 87] Suddenly I started getting this error when I run celery beat ``` celery beat -A proj ``` Funny thing is that celery worker still runs but beat doesn't. I'm running version 4.1 (latest version) btw. ``` celery beat v4.1.0 (latentcall) is starting. OSError: [WinError 87] The parameter is incorrect ... SystemError: <class 'OSError'> returned a result with an error set ``` 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: (Spurious?) RuntimeError: No specified compiler can handle file impl/json/jsmn.c With 0.44.0, I get this error: ``` RuntimeError: No specified compiler can handle file impl/json/jsmn.c ``` This in a project which is mostly C++, but it uses this one `.c` file, defined as: ``` jsmn = declare_dependency( sources: ['impl/json/jsmn.c'], compile_args: [ '-DJSMN_STRICT=1', '-DJSMN_PARENT_LINKS=1' ]) ``` The project statement at the top was: ``` project('name','cpp',default_options : ['cpp_std=c++11','b_pch=false']) ``` Previous versions of Meson didn't report any errors, but I figured I'd have to add `'c'` to the list. I tried: ``` project('name',['cpp','c'],default_options : ['cpp_std=c++11','b_pch=false']) ``` which gave me the error message I quoted at the top of this report. 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: Pub/Sub API lists the wrong (slightly incompatible) type for Message.attributes When a subscriber receives a message, the API says it has an 'attributes' member that is a dict: https://github.com/GoogleCloudPlatform/google-cloud-python/blob/11e310ab9f63f06252ff2b9ada201fd8c11ce06c/pubsub/google/cloud/pubsub_v1/subscriber/message.py#L36 However, it is not, in fact, a dict; it is a protobuf map. The behaviour is quite different, which the Python protobuf API documentation explains at some length: https://developers.google.com/protocol-buffers/docs/reference/python-generated#map-fields This is not a small difference... the semantic gap is substantial, because using the `.attributes` type in place of a dict breaks code like this: ``` message_rev = None if some_condition: try: message_rev = int(message.attributes['revision']) except KeyError: message_rev = DEFAULT ``` In this case, instead of assigning the value `DEFAULT`, this code simply raises a new exception that doesn't happen with dicts (it's a ValueError, because the try-block will execute `int('')`). This is an incompatible, breaking change. Again, this is a subtle, but important, API difference. At a minimum, it seems like the PubSub API docs should point to the Protobuf docs, instead of simply listing the incorrect type. 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: upload --no-overwrite option doesn't work if the package doesn't exists remotely While the new `--no-overwrite` option to upload is great in theory it doesn't work as expected when the package is not available in the remote: ``` conan search -r test zlib/1.2.8-5@plex/stable ERROR: Recipe not found: plex/zlib/1.2.8-5/stable. [Remote: test] conan upload --no all zlib/1.2.8-5@plex/stable -r test Uploading zlib/1.2.8-5@plex/stable ERROR: Local recipe is different from the remote recipe. Forbbiden overwrite. [Remote: test] conan upload zlib/1.2.8-5@plex/stable -r test Uploading zlib/1.2.8-5@plex/stable Uploading conanmanifest.txt [==================================================] 58B/58B Uploading conanfile.py [==================================================] 3.2KB/3.2KB Uploaded conan recipe 'zlib/1.2.8-5@plex/stable' to 'test': https://artifactory.plex.bz/artifactory/api/conan/conan-test conan upload zlib/1.2.8-5@plex/stable -r test -no all Uploading zlib/1.2.8-5@plex/stable Recipe is up to date, upload skipped ``` I'll argue that `upload --no-overwrite all` should work with a package that is not available in the remote. Our remote is a artifactory server running 5.10.3 and I am running conan 1.2.3 locally. 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: Update default behaviour of `rm` As per the warning message: ``` console $ docker-compose rm WARNING: Not including one-off containers created by `docker-compose run`. To include them, use `docker-compose rm --all`. This will be the default behavior in the next version of Compose. ``` 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: [regression] String formatting has regressed since 0.60. ERROR: Format placeholder @9@ out of range. **Describe the bug** There is a regression of as yet unknown cause in Meson's string formatting, as discovered by @alex3kov and diagnosed by myself at libsixel/libsixel#50. This regression causes previously building package to no longer build. **To Reproduce** https://github.com/libsixel/libsixel/blob/v1.10.3/meson.build **Expected behavior** Good build **system parameters** * Is this a [cross build](https://mesonbuild.com/Cross-compilation.html) or just a plain native build (for the same computer)? Plain build. * what operating system (e.g. MacOS Catalina, Windows 10, CentOS 8.0, Ubuntu 18.04, etc.) Arch Linux * what Python version are you using e.g. 3.8.0 Python 3.9.7 * what `meson --version` Versions above 0.59.2 I confirm are affected. * what `ninja --version` if it's a Ninja build We do not get to Ninja step, Meson is the cause. Can you help me debug this systematically and explain your reasoning?