[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: mesa x86_64 -> x86 compilation broken with meson 0.48 Commit 16fa65730469dacbdb9374858c090fe59c1aa70c adds code that checks that if a compiled file is used as a generator that it is either native to the build_machine or there is an exe wrapper. There are some cases where the build machine can run host machine binaries without an emulation layer, such as when building x86 code on an x86_64 machine of the same OS. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose complains about invalid TLS configuration I am running Docker 1.11.2, and so far, everything is fine. The Docker engine is exposed via TCP, TLS is enabled. The certificate is a self-signed one, but so far it has always been working. E.g., if you run ``` $ docker ps ``` everything is fine and the running processes are shown. Now I tried to use docker-compose to start an application. This failed with the following error message: > TLS configuration is invalid - make sure your DOCKER_TLS_VERIFY and DOCKER_CERT_PATH are set correctly The same error happens if you provide the parameters `--tlscert` and `--tlskey` manually. The certificate contains the host name, so it should not be related to #3365. I have read multiple times that setting `CURL_CA_BUNDLE` to an empty value should help, but it didn't. I have experienced this behavior with docker-compose 1.7.0 and 1.8.0. Any ideas? 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 incorrectly detects loop in CMake custom target **Describe the bug** If a CMake subproject contains a custom target in which the basename of the output file is the same as the basename of the input file, importing it into meson will incorrectly generate the following error: ``` meson.build:3:0: ERROR: Cycle in CMake inputs/dependencies detected. ``` Building the same project in CMake works as expected. **To Reproduce** * Clone the example repository at https://github.com/conte91/meson_cmake_cycle_issue * Run `meson build` **Expected behavior** The `test.txt` target is correctly detected to be an output file, depending on the input file at `subprojects/test_cmake/test.txt`. **system parameters** * Native build * Arch Linux * Python 3.8.1 * `meson --version` 0.53.0 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 googleapis/google-cloud-python codebase. Here's the problem: Release new storage client I need a new version of the storage client containing the IAM bits so I can write some samples. :) 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 virtualenv on Windows should generate shell script as well as .bat and .ps1 Hi, It's a fairly common usecase in Windows for people to develop software using bash shells such as git-bash, MSYS2, cygwin, etc. Right now, conan only generates environment scripts for CMD and powershell, although these terminals often are not the preferred choice. This means that users have to open a windows command prompt just to execute the programs they've built. It would be far more ideal to just generate the bash script which already gets generated in unix. I don't see this change really breaking anyone's workflow either, it would only make it easier to write software on windows using conan. Many 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 ipython/ipython codebase. Here's the problem: Widget TextView Placeholder Mainly also a question to @jdfreder , Is there a way to have placeholder in text widget, especially when default value is empty string, it would be nice. I'm not familiar with widget infrastructure to find how to do it. Any advice appreciated ! Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Remove opflow dependency in `EvolvedOperatorAnsatz` ### What should we add? The `EvolvedOperatorAnsatz` class still depends on opflow expectations, and is not compatible with the new primitive-based workflow. This WIP PR #7275 already proposes an alternative to replace `EvolvedOperatorAnsatz` with `EvolutionGates`, so it might be a good starting point to realize this task. 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: formalize gate operands as Qubit objects <!-- ⚠ 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 gates operate on qubits as a `(QuantumRegister, int)` tuple. To improve code clarity this could be formalized into it's own type. A simple solution would be just something like, ```from collections import namedtuple Qubit = namedtuple('Qubit', ['register', 'index']) # then you could do qr = QuantumRegister(5) q1 = Qubit(qr, 1) qc = QuantumCircuit(qr) qc.x(q1) if q1.register == qr and q1.index != 0: qc.h(q1) def my_gate(self, q): assert isinstance(q, Qubit) ``` Something more complex could do type checking. 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: segment_sum primitives / advanced indexing in jax.ops.index_add Would it be useful to others (aside from me) to have better support of sorted and unsorted segment_sums? https://www.tensorflow.org/api_docs/python/tf/math/unsorted_segment_sum https://www.tensorflow.org/api_docs/python/tf/math/segment_sum In numpy one way to do unsorted segment sums is to sort then call np.add.reduceat, but this doesn't seem to be in jax or autograd: ``` >>> import jax.numpy as np np.add >>> np.add <function _one_to_one_binop.<locals>.<lambda> at 0x1430cdbf8> >>> np.add.reduceat Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: 'function' object has no attribute 'reduceat' ``` 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: Installing any package fails (on one of my machines) (master) Master (`4.0.7.dev430+2b8b214`) again. I get: ``` Traceback (most recent call last): File "/home/ilan/minonda/bin/conda", line 6, in <module> sys.exit(main()) File "/home/ilan/conda/conda/cli/main.py", line 120, in main args_func(args, p) File "/home/ilan/conda/conda/cli/main.py", line 127, in args_func args.func(args, p) File "/home/ilan/conda/conda/cli/main_install.py", line 62, in execute install.install(args, parser, 'install') File "/home/ilan/conda/conda/cli/install.py", line 394, in install plan.execute_actions(actions, index, verbose=not args.quiet) File "/home/ilan/conda/conda/plan.py", line 555, in execute_actions inst.execute_instructions(plan, index, verbose) File "/home/ilan/conda/conda/instructions.py", line 133, in execute_instructions cmd(state, arg) File "/home/ilan/conda/conda/instructions.py", line 80, in UNLINK_CMD install.unlink(state['prefix'], arg) File "/home/ilan/conda/conda/install.py", line 1075, in unlink mk_menus(prefix, meta['files'], remove=True) TypeError: 'NoneType' object has no attribute '__getitem__' ``` This only happens on one of my machines. CC @kalefranz @mcg1969 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.load() fails to read empty archive created by np.savez() Try this: np.savez('nothing.npz') # OK np.load('nothing.npz') # error Loading fails: OSError: Failed to interpret file 'nothing.npz' as a pickle It should succeed (and give you an object with no arrays inside). Likewise for `savez_compressed()` (which also currently fails). I'm using NumPy 1.13.1. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Re-generate library using tasks/synth.py This PR was created by autosynth. 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: Make GraphViz optional Following up on #101 -- I think GraphViz should be optional. Should we have a "viz" `extras` package in `setup.py` that includes bokeh and graphviz? 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: support a commutative DAG. Opinions? In #1503, @godott raises, as I see it, a valid point. Many passes, as gate cancelation, could make a good use of commutative set. The question now is how to support it. Ideas? Opinions? Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the conda/conda codebase. Here's the problem: Conda 4.4.x does not prevent removal of conda dependencies from base environment? Some user tried to remove `pycosat` from within Navigator using conda 4.4.8 as reported on [this issue](https://github.com/ContinuumIO/anaconda-issues/issues/8563) It seems conda 4.4.x is allowing user to remove conda dependencies like `pycosat` which effectively leaves them in a broken state. I checked with 4.4.9 and 4.4.10 and it seems to be that this is still possible. I have tested on Mac, @jjhelmus tested on Linux. Need to check on windows 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 other service account types Not just JWT certificate. 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 jupyterlab/jupyterlab codebase. Here's the problem: Move YDocWebSocketHandler to Jupyter Server core ### Problem I think that the [YDocWebSocketHandler](https://github.com/jupyterlab/jupyterlab/blob/055099fa565f3589d8db38588678614fdb286023/jupyterlab/handlers/ydoc_handler.py) is not specific to JupyterLab and deserves to live in [jupyter-server](https://github.com/jupyter-server/jupyter_server) core. It is a generic websocket server that can talk to any websocket provider for the supported Y documents. JupyterLab is just one of them, but I can imagine e.g. a Python web client that would also have a websocket provider, such as [ypy-websocket](https://github.com/y-crdt/ypy-websocket/blob/39252430d79141ec7900cda8c291996da6aaf340/ypy_websocket/websocket_provider.py), to implement a Jupyter client in the terminal. In that case we wouldn't need to run JupyterLab in the back-end but only Jupyter Server. ### Proposed Solution Move [ydoc_handler.py](https://github.com/jupyterlab/jupyterlab/blob/055099fa565f3589d8db38588678614fdb286023/jupyterlab/handlers/ydoc_handler.py) to [jupyter-server](https://github.com/jupyter-server/jupyter_server). ### Additional context This is also needed if we want to implement a [new kernels REST API](https://github.com/jupyter-server/jupyter_server/issues/900) in jupyter-server. 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: Capturing shell command output after indentation causes SyntaxError in IPython console. To reproduce, type this in console: ```python def test(): for i in range(1): print(i) res =! ls ``` But if something is put above the line, everything will seem to be fine. ```python def test(): for i in range(1): print(i) 'just a separate line' res =! ls ``` Find this in IPython 7.1.0.dev 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: D: strip unsupported -D (and -f) flags for ldc2 Building [tilix](https://github.com/gnunn1/tilix) on FreeBSD, where the x11 pkgconf file contains a define flag: ``` % cat /usr/local/libdata/pkgconfig/x11.pc […] Cflags: -I${includedir} -D_THREAD_SAFE ``` ``` [1/63] ldc2 -I=tilix@exe -I=. -I=.. -I=../source/ -I=data -I/usr/local/include/d/gtkd-3/ -I/usr/local/include -enable-color -wi -release -enable-inlining -Hkeep-all-bodies -O3 -D_THREAD_SAFE -vcolumns -d-version=StdLoggerDisableTrace -of='tilix@exe/source_secretc_secret.d.o' -c ../source/secretc/secret.d FAILED: tilix@exe/source_secretc_secret.d.o ldc2 -I=tilix@exe -I=. -I=.. -I=../source/ -I=data -I/usr/local/include/d/gtkd-3/ -I/usr/local/include -enable-color -wi -release -enable-inlining -Hkeep-all-bodies -O3 -D_THREAD_SAFE -vcolumns -d-version=StdLoggerDisableTrace -of='tilix@exe/source_secretc_secret.d.o' -c ../source/secretc/secret.d ldc2: Unknown command line argument '-D_THREAD_SAFE'. Try: 'ldc2 -help' ldc2: Did you mean '-pre-RA-sched'? ``` I guess such flags should be just removed… Also, FreeBSD Ports sets up `LDFLAGS` for C/C++, and meson ends up passing unsupported flags to ldc2 here as well: ``` ldc2: Unknown command line argument '-fstack-protector-strong'. Try: 'ldc2 -help' ldc2: Did you mean '-stack-symbol-ordering'? ``` Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: circuit.draw(output = 'latex') truncates circuit unexpectedly <!-- ⚠ 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**: 0.7.0 - **Python version**: 3.6.5 - **Operating system**: Windows 10 ### What is the current behavior? test.draw(output = 'latex') ![image](https://user-images.githubusercontent.com/38588126/51922343-d7059c80-23b6-11e9-9125-ebc7ad7c573b.png) ### Steps to reproduce the problem ``` numq = 6 q = QuantumRegister(numq, name='qn') c = ClassicalRegister(numq, name='cn') test = QuantumCircuit(q,c) for i in range(numq): test.h(q[i]) test.barrier(q[i]) for i in range(numq-1): test.h(q[i+1]) test.cx(q[i],q[i+1]) test.h(q[i+1]) test.barrier(q[i+1]) ``` ### What is the expected behavior? test.draw(output = 'mpl') ![image](https://user-images.githubusercontent.com/38588126/51922373-ea186c80-23b6-11e9-9b67-54d63e358ef2.png) ### Suggested solutions possibly a issue with latex or windows, might not be terra related Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the docker/compose codebase. Here's the problem: docker-compose pull doesn't work with mixure of official and local images I use my own image build process in my development environment. This process create images localy so I can test them. I also use mose official images (databases) in my `docker-compose.yml`. With this combination `docker-compose pull` command fail when its tries to pull my local only images and if I'm not lucky no database images are pulled. I would like to from time to time pull new images from repository and so far I have to list them all. Is it possible to pass some flag to `pull` that it tries to pull all images and only report those that failed (instead of stop pulling others)? 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: Revert change to `User-Agent` header From #2223. See https://github.com/GoogleCloudPlatform/gcloud-common/issues/179 for rationale, such as it is and what there is of it. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the jupyterlab/jupyterlab codebase. Here's the problem: Update to MathJax 3 MathJax 3 was released a few days ago. Perhaps we should upgrade to it in 2.0. PR for our external plugin is at https://github.com/jupyterlab/jupyter-renderers/pull/213 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: Recursive declare_dependency() Hi Jussi, This is somewhat related to #304 - should this work? I ran into this the other day. I have a library that depends on another library and there is a `declare_dependency` for both of them. ``` opencl_inc = include_directories('/usr/local/opencl12', '/opt/AMDAPP/include') opencl_dep = declare_dependency( include_directories: opencl_inc, dependencies: find_library('OpenCL', dirs:'/usr/lib64'), ) another_dep = declare_dependency( include_directories: another_inc, dependencies: opencl_dep ) foo = executable('foo', src, dependencies:[another_dep], ) ``` This is the error: ``` Dependencies must be external deps ``` 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: Since 1.4, `docker-compose up container` logs all containers, not just those passed as argument `docker-compose up lb wsgi` now also logs other containers, not just those explicitly passed in argument ("lb" and "wsgi" in this example). So instead of having just the logs I'm interested in like before, I'm now flooded with logs of verbose containers like varnish. Since 1.4, `docker-compose up container` logs all containers, not just those passed as argument `docker-compose up lb wsgi` now also logs other containers, not just those explicitly passed in argument ("lb" and "wsgi" in this example). So instead of having just the logs I'm interested in like before, I'm now flooded with logs of verbose containers like varnish. 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: Adding regularizers to Stax Some utilities for regularizing the cost functions would be useful in Stax. I have not seen this mentioned in #137. Is this planned? Also, I was wondering about the best way to implement this in pure JAX. For example considering L2 regularization, with the flattening utility from #190 I could write: ``` w_flat, _ = ravel_pytree(w) reg = np.sum(w_flat ** 2.0) ``` Looking a little bit on the code of tree_util I can also write: ``` reg= tree_reduce(lambda x, y: np.sum(x) + np.sum(y), tree_map(lambda wi: np.sum(wi**2.0), w)) ``` Is there a simpler solution I am missing? More in general it would be useful to document tree utilities in the main doc. 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: Add gcc 10.1 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: Python 3.8 and `python3-config --libs` Quoting https://bugzilla.redhat.com/show_bug.cgi?id=1718290: > The build no longer links to libpython, resulting in undefined references to Python API. Code that embeds Python (rather than building an extension module) needs to pass `--embed` to any `python3-config --libs` invocation to build with Python 3.8. More information: https://docs.python.org/3.8/whatsnew/3.8.html#debug-build-uses-the-same-abi-as-release-build In libratbag, we are using swig to generate a Python library that we link with a dependencies of `dependency('python3')`. I wasn't able to find out how the pkg-config was invoced, so I can not really submit a patch. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the conda/conda codebase. Here's the problem: `conda.install.update_prefix` is modifying cached pkgs in Windows Since files are hardlinks, it looks like conda's prefix replacement mechanism is breaking its own files. File contents inside package: ``` python x = r'/opt/anaconda1anaconda2anaconda3\Scripts', ``` File contents after installing in 'env1': ``` python x = r'C:\Miniconda\envs\env1\Scripts', ``` File contents after installing in 'NOTENV1': ``` python x = r'C:\Miniconda\envs\env1\Scripts', ``` Note that the second install fails, because the first one modified the cached files in `C:\Miniconda\pkgs`. Reading @asmeurer comments in #679, I agree that the correct behavior in this case would be to delete the file being modified and re-create it to avoid this 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: Refactor progress bars After the transition to the _tqdm_ library, it would be nice to make consistent the way in that the progress bars are created and used in different places in Conan. 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: Accurate Control Channels <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: - **Python version**: - **Operating system**: This only applies for OpenPulse enabled backends, for users trying to get data from the backend to build Pulse Schedules. ### What is the current behavior? `backend.configuration().control(qubit: int)` returns a trivial mapping to a `ControlChannel` with index specified by the given int `qubit`. This is not correct. It should be possible to determine the correct channel by inspecting the backend hamiltonian, if it is provided. ### What is the expected behavior? Right now the easiest (and hacky) way to get the correct channel is by reverse engineering the control channel index by inspecting the `cmd_def` of `backend.defaults()`. ### Suggested solutions I think the Pulse simulator does some hamiltonian parsing to figure out the same information that would be required to implement this feature. That is probably a good starting place. It should be implemented in `qiskit.providers.models.PulseBackendConfiguration.control`. 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() kwarg vs_module_defs should trigger rebuild When the visual studio module definitions file is edited, the library that uses it should get re-linked. 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: Layout source folder when using ``source()`` to ``git clone`` a third-party fails - Layout defines source folder as ``src`` - Conan exports at least ``conanfile.py`` and ``conanmanifests.txt`` into the ``export`` folder in the cache - The ``export`` folder in the cache is automatically copied to ``source/src`` in the cache. - If the package tries to do a ``git clone <url> src`` to put the sources inside the ``src`` folder as the layout specified, it fails with "folder already exists". Should we? - Do not copy the ``export`` into the ``source/src`` folder, only the ``exports_sources``? - Document some git gymnastics to do it, like cloning in a different 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: PrimitiveOp does not handle binding to complex values. <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: 0.18 - **Python version**: 3.8 - **Operating system**: MacOS ### What is the current behavior? Error when binding a complex coefficient to an operator's parameter. ``` return self.assign_parameters(param_dict) File "/qiskit-terra/qiskit/opflow/primitive_ops/primitive_op.py", line 249, in assign_parameters param_value = float(self.coeff.bind(binds)) File "/qiskit-terra/qiskit/circuit/parameterexpression.py", line 431, in __float__ return float(self._symbol_expr) File "symengine_wrapper.pyx", line 1133, in symengine.lib.symengine_wrapper.Basic.__float__ File "symengine_wrapper.pyx", line 958, in symengine.lib.symengine_wrapper.Basic.n File "symengine_wrapper.pyx", line 4194, in symengine.lib.symengine_wrapper.evalf RuntimeError: Not Implemented ``` ### Steps to reproduce the problem ``` from qiskit.opflow import X from qiskit.circuit import Parameter th = Parameter('th') (th * X).bind_parameters({th: 1j}) ``` ### What is the expected behavior? No error, handling a potentially complex value. ### Suggested solutions In File "/qiskit-terra/qiskit/opflow/primitive_ops/primitive_op.py", line 431, changing `param_value = float(self.coeff.bind(binds))` to `param_value = complex(self.coeff.bind(binds))`. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the google/jax codebase. Here's the problem: np.array named columns and different column types not working Classical numpy arrays allow to specify column names/identifiers and assign different types to columns. From the documentation: > Data-type consisting of more than one element: > > ``` >>>> x = np.array([(1,2),(3,4)],dtype=[('a','<i4'),('b','<i4')]) >>>> x['a'] >array([1, 3]) > ``` The same documentation is given for jax's `np.array` but trying the above example yields a ``` TypeError: unhashable type: 'list' ``` for the `dtype` argument (raised in function `_check_user_dtype_supported`, line 5096, `jax/lax/lax.py`). Is there a chance that this kind of array specifications could be supported? If not, could at least the documentation be clarified? Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the PrefectHQ/prefect codebase. Here's the problem: CLI `run cloud --logs` needs exit Currently the watch on logs does no exit and should finish on completion of flow run 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: asn1 error in reading credentials on windows Hi, I reckon line 39 in glcoud.credentials should open the private key with read binary on windows: private_key=open(private_key_path, 'rb').read(), cheers, David 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: Make redis use of sorted sets for group results opt-out Following up on #6245 - can we make the use of sorted set opt-out for 5.0 as discussed? In particular, this would simply be a change to the default value of the config value, and associated changes to tests and doco merged in #6245. 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: IAM: Improve Policy docs It would help the Policy docs if there were an example of how to set bindings. The dunder methods don't have docstrings and so, without looking at the source, it's not very obvious how to assign roles and members to a policy. ``` policy = iam.Policy() policy[role] = [iam.Policy.user(user_email)] ``` This will help people reading the docs for methods that take an `iam.Policy` who follow the link to the class definition and then can't figure out how to build the policy they want--for instance, for a new storage bucket. (I was helping a friend today who also found this confusing.) I'm happy to contribute an example here but not sure how you all would like that done. Edit: [Link to current Policy docs](https://googleapis.github.io/google-cloud-python/latest/core/iam.html#google.cloud.iam.Policy) 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: Fargate agent warning is too aggressive ## Description This warning can be relaxed because it does not suit all use cases ## Expected Behavior Elevate warning only under certain conditions ## Reproduction Run the fargate agent without ARNs 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: Add --json flag on conda-env that works! The json flag seems to be there, but it is not working. With a file that looks like ```yaml # environment.yaml name: test_env_1 channels: - defaults dependencies: - python - pytest-cov ``` ``` (root) $ conda-env create --json Using Anaconda API: http s://api.anaconda.org (root) $ ``` So two problems here: 1.) No json output on the create process 2.) `Using Anaconda API: https://api.anaconda.org` 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: Ignore calls to flow.register when parsing a flow using file based storage ## Current behavior <!-- Please describe how the feature works today --> If a flow script contains a reference to the `.register` method, it'll fail with this error: ``` Failed to load and execute Flow's environment: RuntimeError('Attempting to call `flow.register` during execution of flow file will lead to unexpected results.') ``` ## Proposed behavior <!-- Please describe your proposed change to the current behavior --> Flow runner ignores calls to the `.register` method. ## Example <!-- Please give an example of how the enhancement would be useful --> Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the docker/compose codebase. Here's the problem: Add ability to resolve image digests without pulling entire images PR #4333 added `--resolve-image-digests` to `docker-compose config`, which resolves image tags to their digest to form stable references. However, this relies on the images being available on the Docker host. It would be useful if Docker Compose could fetch image digests without having to pull the image if the image doesn't exist locally. In CI jobs using Docker-in-Docker, pulling images just for tag digests can be a significant waste of time and network resources. Digests can be obtained using `HEAD` requests against `/v2/<name>/manifests/<reference>` in the [v2 API](https://docs.docker.com/registry/spec/api/#manifest). https://stackoverflow.com/questions/35186693/what-is-the-docker-registry-v2-api-endpoint-to-get-the-digest-for-an-image#35420411 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: Console animations printed to the log files as new lines I have a system that execs the `compose`command and that logs the output (stderr/stdout output streams redirected) to a log file. Apparently the `docker up -d` is showing some image pull animations (obviously contains ANSI escape sequences to clear lines or delete chars) and when those get logged to the log file, I just see bunch of empty lines. Not a big deal, mostly a cosmetics issue but wanted to bring up if it's easy to fix. Output: ``` Creating compose307929553_blog_1... Pulling image ghost:latest... latest: Pulling from ghost ghost:latest: The image you are pulling has been verified. Important: image verification is a tech preview feature and should not be relied on to provide security. Digest: sha256:b415d8cdf5aa809b95def3e122251b80fe6f99c557bd37ba9d7af2523089511a Status: Downloaded newer image for ghost:latest Creating compose307929553_cache_1... Pulling image memcached:latest... latest: Pulling from memcached memcached:latest: The image you are pulling has been verified. Important: image verification is a tech preview feature and should not be relied on to provide security. Digest: sha256:61a047af4f93bf3750658197594e5145beadf02f1236b411034b9ce6cfa61140 Status: Downloaded newer image for memcached:latest ``` 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: 0.50.0: c_link_args is ignored in compiler sanity checks of cross-builds with exe_wrapper See https://github.com/mesonbuild/meson/pull/5085 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: **gather_all_tensors_if_available** share the same underlying storage for all GPUs <!-- ### Common bugs: 1. Tensorboard not showing in Jupyter-notebook see [issue 79](https://github.com/PyTorchLightning/pytorch-lightning/issues/79). 2. PyTorch 1.1.0 vs 1.2.0 support [see FAQ](https://github.com/PyTorchLightning/pytorch-lightning#faq) --> ## 🐛 Bug <!-- A clear and concise description of what the bug is. --> Hi, one of new features in #2528 `gather_all_tensors_if_available` has a `list` copy bug, and this would lead that tensors in all GPUs are the wrongly same as one GPU, since they share the same storage: https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/metrics/converters.py#L304 ``` gathered_result = world_size * [torch.zeros_like(result)] ``` change into: ``` gathered_result = [torch.zeros_like(result) for _ in range(world_size)] ``` 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: Non-standard scaling factor for the covariance matrix in `numpy.polyfit` As discussed on the [mailing list](http://numpy-discussion.10968.n7.nabble.com/Inconsistent-results-for-the-covariance-matrix-between-scipy-optimize-curve-fit-and-numpy-polyfit-td45582.html) recently, and (as @josef-pkt pointed out to me) also already [in a discussion in 2013](https://mail.scipy.org/pipermail/numpy-discussion/2013-February/065664.html), `numpy.polyfit` uses a non-standard factor in the estimated scale of the covariance matrix. Namely, rather than using the standard `chisq/(M-N)`, it scales it with `chisq/(M-N-2)` where `M` is the number of data points and `N` is the number of parameters. Neither my colleague @wummo and I, while researching this, nor @josef-pkt as stated in the subsequent E-Mail conversation has found any reference for this in the literature. There is a comment in the corresponding code here explaining the choice: https://github.com/numpy/numpy/blob/79ec65de3064cbdc687820ab09f20b989028509d/numpy/lib/polynomial.py#L593-L604 But there is no reference given there. As this is non-standard and is inconsistent with other fitting programs (such as e.g. `scipy.optimize.curve_fit`), we feel that this should be changed to avoid surprises when using this library. As a side note, one could use the occasion to add an additional parameter which enables the return of an unscaled covariance matrix (@josef-pkt suggested the name `absolute_weights`, analogous to `curve_fit`'s `absolute_sigma`). This was already suggested in both mailing list discussions. It would be useful in occasions, where the weights are given by `1/sigma` with sigma being the (known) standard errors of (gaussian distributed) data points, in which case the unscaled matrix is already a correct estimate for the covariance matrix. 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: Adding environments to repository.yml and then supporting in dagit Per discussion at lunch, add the ability to register environments in repository.yml and then surface them nicely in dagit. 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: ediff1d handles data type errors badly If the `to_end` or `to_begin` argument is an invalid type for the array, you don't get an error message, you just get bad results. For example, if you try to put `np.nan` into an int array: ```Python a = np.array([1, 2, 3]) np.ediff1d(a, np.nan) ``` You get `array([ 1, 1, -9223372036854775808])` 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: Add base_url to labextension handler cf https://github.com/jupyterlab/jupyterlab/blob/bcf78198f1220257a92ff95523afc86f7af9e816/jupyterlab/labapp.py#L197-L204 From gitter debugging session with @epifanio. The app was trying to load extensions from `/hub/labextension/`, while the correct url should have been `/user/epinux/labextension`. 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: BSD detect_cmake: _INCLUDED_FILE "NOTFOUND" Hi. On at least OpenBSD and FreeBSD, the cmake module fails to determine the compilerpath. This is because it looks at the _INCLUDED_FILE value: ``` $ cmake --system-information -G Ninja | grep _INCLUDED_FILE ``` On BSD, the output is: ``` _INCLUDED_FILE "NOTFOUND" ``` On Linux, the output is: ``` _INCLUDED_FILE "/usr/share/cmake-3.12/Modules/Platform/Linux-GNU-CXX.cmake" ``` I wonder is we could maybe use something like _INCLUDED_SYSTEM_INFO_FILE which has the following output (according to the OS): ``` /usr/local/share/cmake/Modules/Platform/OpenBSD.cmake /usr/share/cmake-3.12/Modules/Platform/Linux.cmake" ``` 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: typo IBERT in `__repr__` should be `quant_mode: {self.quant_mode}` in here https://github.com/huggingface/transformers/blob/71e602725b90f63f404109bae9f72cbdf755477b/src/transformers/models/ibert/quant_modules.py#L150-L155 typo IBERT in `__repr__` should be `quant_mode: {self.quant_mode}` in here https://github.com/huggingface/transformers/blob/71e602725b90f63f404109bae9f72cbdf755477b/src/transformers/models/ibert/quant_modules.py#L150-L155 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: CMake for dependencies can't use modules CMake for finding dependencies could easily be further extended with off-the-shelf `Find<foo>.cmake` scripts. The only thing that needs to happen for that is that the invocation of `cmake` needs to point `-DCMAKE_MODULE_PATH=<dir>` at the directory containing these scripts. A good place for this might be here: https://github.com/mesonbuild/meson/blob/90c9b868b20b11bb089fc5e0c634d5ed76fea0cb/mesonbuild/dependencies/base.py#L1422 As a simple suggestion, just redefine all `CMAKE_*` environment variables as CMake variables: ```python for key in env.keys(): if key.startswith('CMAKE_'): args.append('-D%s=%s' % (key, env[key])) ``` That should do the trick (some testing required). As an added benefit, you can influence CMake further with other `CMAKE_*` variables in the environment. 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 bucket labels See: https://cloud.google.com/storage/docs/json_api/v1/buckets#labels 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: Datastore: broken paging next_page_token I want to use `datastore` paging to fetch the query results. Specifically, I upload 11 entities to `datastore` and then want to fetch them (`limit=10`) using following code: ```python query = <google.cloud.datastore.Client>.query(kind='test_kind') query_iter = query.fetch(limit=limit, start_cursor=cursor) page = next(query_iter.pages) next_cursor = query_iter.next_page_token entities = list(page) logging.info('Cursor: %s, Next cursor: %s, Loaded entities: %d.', cursor, next_cursor, len(entities)) ``` (where initially `cursor = None` and then is set to `next_cursor` value) Unfortunately, I am getting not `None` value for the `next_cursor` even there are not any more results to fetch: ``` # First call, everything as expected Cursor: None, Next cursor: foo, Loaded entities: 10. # Second call, expected next_page_token = None Cursor: foo, Next cursor: bar, Loaded entities: 1. # Third call, again expected next_page_token = None Cursor: bar, Next cursor: bar, Loaded entities: 0. ``` It seems that `next_page_token` is always not `None` and moreover, if there is not any result to fetch, `next_cursor == cursor`. Setup: ``` Python 2.7.12 google-cloud-datastore==1.3.0 ``` Is this expected? If yes, how can I recognise that there are not more results to fetch? I've checked the code briefly and it might be related to https://github.com/GoogleCloudPlatform/google-cloud-python/blob/master/datastore/google/cloud/datastore/query.py#L457. It seems like `response_pb.batch.end_cursor == b''` does not hold and thus `next_page_token` is not set to `None`, but not sure why this is the case. 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 functions equivalent to create_rows and create_rows_json that create a table for you using a load job 1. BigQuery API 2. Linux, Ubuntu 16.04.3 LTS running Google Cloud Datalab 1.0.1 3. Python 2.7.12 4. Google cloud v 0.31.0 5. // 6. Create a dataframe or dict list and try to send to an existing table. The first request will raise no errors but nothing will be appended to the table. Running the same command again and rows are added. This will not add rows: ``` from google.cloud import bigquery as bq import time client = bq.Client(project='project-name') dataset = bq.DatasetReference('project-name', 'dataset-name') tableref = bq.table.TableReference(dataset, 'users') schema = [bq.SchemaField('email', 'STRING'), bq.SchemaField('id', 'STRING'), bq.SchemaField('added', 'TIMESTAMP')] table = bq.Table(tableref, schema=schema) create = client.create_table(table) public_members = [{'email': 'testemail@email.com', 'id': '1234', 'added': '2017-12-01 13:13:13 UTC'}] client.create_rows_json(table, public_members) ``` This will add exactly one row: ``` from google.cloud import bigquery as bq import time client = bq.Client(project='project-name') dataset = bq.DatasetReference('project-name', 'dataset-name') tableref = bq.table.TableReference(dataset, 'users') schema = [bq.SchemaField('email', 'STRING'), bq.SchemaField('id', 'STRING'), bq.SchemaField('added', 'TIMESTAMP')] table = bq.Table(tableref, schema=schema) create = client.create_table(table) public_members = [{'email': 'testemail@email.com', 'id': '1234', 'added': '2017-12-01 13:13:13 UTC'}] client.create_rows_json(table, public_members) time.sleep(15) client.create_rows_json(table, public_members) ``` 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: Make python-constraint requirement optional ### What is the expected enhancement? After #7213 we're no longer using the CSP layout pass in preset passmanagers, while I think keeping the pass in terra makes sense since we're not using it by default with `transpile()` anymore I think we can remove `python-constraint` from the requirements list and make it an optional dependency and only require it if people are explicitly using the csplayout pass. This is technically a breaking change but I think one with minimal impact as most users are not going to be explicitly using the pass. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the ipython/ipython codebase. Here's the problem: Copying from Qt console appends newline in clipboard IPython 2.1.0 on Windows As title says, for example if I copy single word in clipboard I have the word plus '\r\n'. 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: Name change for S_dg and T_dg not reflected in drawers <!-- ⚠ If you do not respect this template, your issue will be closed --> <!-- ⚠ Make sure to browse the opened and closed issues --> ### Information - **Qiskit Terra version**: master - **Python version**: 3.8 - **Operating system**: Ubuntu 18.04 ### What is the current behavior? Previously the s-dagger and t-dagger gates were named sdg and tdg. This was changed to S_dg and T_dg, which means the drawers no longer display the dagger icon. ### Steps to reproduce the problem ``` qc = QuantumCircuit(1) qc.sdg(0) qc.draw('mpl') ``` ### What is the expected behavior? Both gates should display the dagger icon after S or T. ### Suggested solutions This can be fixed in qcstyle.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 docker/compose codebase. Here's the problem: Wrong suggestion message Version ``` docker-compose -v docker-compose version 1.8.0, build f3628c7 docker -v Docker version 1.12.1, build 23cf638 ``` docker-compose.yml ``` version: '2' services: nginx: image: 'nginx:1.10-alpine' ``` command ``` $ docker-compose bundle ERROR: Some images are missing digests. The following images need to be pulled: nginx:1.10-alpine Use `docker-compose pull nginx:1.10-alpine` to pull them. ``` Clearly, the message should've been `docker pull nginx:1.10-alpine`, without 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: Internal static library leaks to the ldflags when using gnome.gtkdoc() Similar to #3934: additional uninstalled static libraries end up on the linker flags for shared libraries, causing build failures when running `gtkdoc-scangobj`: ``` ERROR: 'gtkdoc-scangobj' failed with status 1 /usr/bin/ld: cannot find -lgeoclue-public-api collect2: error: ld returned 1 exit status 2018-07-24 18:53:45,120:scangobj.py:execute_command:1196:WARNING:Linking scanner failed: 1, command: ccache cc libgeoclue-scan.o -L/home/ebassi/gnome/source/geoclue/_build/libgeoclue -L/home/ebassi/gnome/install/lib -Wl,-rpath,/home/ebassi/gnome/install/lib -Wl,-rpath,/home/ebassi/gnome/source/geoclue/_build/libgeoclue -lgeoclue-2 -lgeoclue-public-api -lglib-2.0 -lgio-2.0 -lgobject-2.0 -o libgeoclue-scan ``` `geoclue-public-api` is a static library defined as an internal dependency of `geoclue-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 huggingface/transformers codebase. Here's the problem: AttributeError: 'Trainer' object has no attribute 'is_world_master' ## Environment info - `transformers` version: 4.0.0 - Platform: Linux-4.15.0-96-generic-x86_64-with-debian-buster-sid - Python version: 3.7.8 - PyTorch version (GPU?): 1.7.0 (True) - Tensorflow version (GPU?): not installed (NA) - Using GPU in script?: Yes - Using distributed or parallel set-up in script?: No - Ray version: 1.0.1.post1 ### Who can help @sgugger — Would you be able to offer any insight? ## Information Model I am using (Bert, XLNet ...): BertForSequenceClassification The problem arises when using: * [ ] the official example scripts: * [ x] my own modified scripts: The tasks I am working on is: * [ ] an official GLUE/SQUaD task: * [ x] my own task or dataset: ## To reproduce The error occurs when I try to run a hyperparameter search for my finetuning step using Ray Tune. I am able to successfully finetune the BertForSequenceClassification model normally — the error only arises when running hyperparameter search. ``` config = BertConfig.from_pretrained(pretrained_model_path, num_labels=num_labels, finetuning_task ='text-classification') def model_init(): return BertForSequenceClassification.from_pretrained(pretrained_model_path, config=config) trainer = Trainer( model=model, args=training_args, train_dataset=train_dataset, eval_dataset=eval_dataset, model_init=model_init ) trainer.hyperparameter_search( direction="minimize", backend="ray", n_trials=20, keep_checkpoints_num=1, resources_per_trial = {'gpu':1, 'cpu':1} ) ``` ## Expected behavior I am trying to run Ray Tune from Huggingface as per these instructions: https://huggingface.co/blog/ray-tune If anyone has any insight as to what could be causing this error, it would be greatly appreciated, 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 huggingface/transformers codebase. Here's the problem: Swap `eval_delay signs` ### Who can help @sgugger ## Information The signs for the `eval_delay` comparisons need to be switched. This is pretty NB @sgugger as there are a lot of breakages involved here. Greater than sign must be changed to less than sign [here](https://github.com/huggingface/transformers/blob/main/src/transformers/trainer_callback.py#L422) and [here](https://github.com/huggingface/transformers/blob/main/src/transformers/trainer_callback.py#L446). I'll put in a PR if need be. 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: Unable to find locally built image I have a locally built image (built with `docker build -t project/heroku-base ./project-heroku-base`) that version 1.3 of docker-compose is not finding during the build process for another image. I can build with `docker build app ./app`, and with version 1.2 of docker-compose I can build with `docker-compose build app`. ``` $ docker-compose build app Building app... Step 0 : FROM project/heroku-base:latest Pulling repository project/heroku-base Service 'app' failed to build: Error: image project/heroku-base:latest not found ``` ``` $ docker images REPOSITORY TAG IMAGE ID CREATED VIRTUAL SIZE project/heroku-base latest ebe895ea759a 10 minutes ago 1.325 GB mysql latest d63d4723d715 2 days ago 283.5 MB debian jessie bf84c1d84a8f 2 days ago 125.2 MB heroku/cedar 14 89fc314a0a6e 4 weeks ago 1.242 GB busybox latest 8c2e06607696 8 weeks ago 2.433 MB ``` ``` $ docker-compose -v docker-compose version: 1.3.0 CPython version: 2.7.9 OpenSSL version: OpenSSL 1.0.1e 11 Feb 2013 $ docker version Client version: 1.7.0 Client API version: 1.19 Go version (client): go1.4.2 Git commit (client): 0baf609 OS/Arch (client): linux/amd64 Server version: 1.7.0 Server API version: 1.19 Go version (server): go1.4.2 Git commit (server): 0baf609 OS/Arch (server): linux/amd64 ``` 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: more control over job_monitor output <!-- ⚠ 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? Allow the user to control the new line characters that are emitted by job_monitor output. I found myself needing to change this to allow me to use qiskit-terra's tools on my non jupyter notebook environment. I'm already working on a PR for this, which will appear linked here very soon. more control over job_monitor output <!-- ⚠ 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? Allow the user to control the new line characters that are emitted by job_monitor output. I found myself needing to change this to allow me to use qiskit-terra's tools on my non jupyter notebook environment. I'm already working on a PR for this, which will appear linked here very soon. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the Qiskit/qiskit codebase. Here's the problem: Add support for exporting `Expr` values to OpenQASM 3 ### What should we add? This tracks the work labelled "PR 3" in [the initial classical-expression design document](https://github.com/Qiskit/RFCs/blob/master/0010-simple-classical-representations.md). Fully depends on #10223. Work can begin following only that, but to be properly useful, this also depends on #10224. Brief overview: - add support for exporting `Expr` values in the OpenQASM 3 exporter. 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: Different behavior in DistilBERT when using "inputs_embeds" ### System Info - `transformers` version: 4.24.0 - Platform: Linux-3.10.0-1160.80.1.0.1.el7.x86_64-x86_64-with-glibc2.27 - Python version: 3.10.8 - Huggingface_hub version: 0.11.1 - PyTorch version (GPU?): 1.12.1 (True) @ArthurZucker @younesbelkada ### Reproduction Do a forward pass with distilBERT passing "inputs_embs" instead of "input_ids", where "inputs_embs" contains the output of the forward over the word embedding matrix, i.e. just picking the token embeddings. When doing this, one would expect the same behaviour as other popular models like BERT or ROBERTA, but distilBERT skips "positional embeddings addition + layerNorm + droput" as it skips the self.embedding() call. I would expect that passing inputs_embs instead of input_ids has a coherent behaviour across diferent architectures, but it is not the case, at least for distilBERT. I am not sure if other models have this issue. ### Expected behavior Properly build the input embedding by adding positional embeddings + layerNorm + droput (as happens in modeling_bert or modeling_roberta). This does not happen as the call to self.embedding() is skipped. 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: [feature] Verbose option for apply_conandata_patches() ### What is your suggestion? I'd like to have this... ```diff -def apply_conandata_patches(conanfile): +def apply_conandata_patches(conanfile, verbose=False): ``` ...which does this when `verbose=True`... ```diff ======== Installing packages ======== zlib/1.2.13: Calling source() in /home/username/.conan2/p/zlibef641b716caf2/s +zlib/1.2.13: Applying: patches/0001-Fix-cmake.patch +zlib/1.2.13: Applying: patches/0002-gzguts-xcode12-compile-fix.patch -------- Installing package zlib/1.2.13 (1 of 1) -------- zlib/1.2.13: Building from source ``` ...so that information on which patches were applied is recorded in the build log. I have this implemented and ready to go. ### Have you read the CONTRIBUTING guide? - [X] I've read the CONTRIBUTING guide 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: Celery executor should support custom database backend models Currently, the celery executor imports the `Task` model for the Celery database backend directly: https://github.com/apache/airflow/blob/2dd4e96045d4a7f45cc8c06df3d25c4f1479392c/airflow/executors/celery_executor.py#L38 However, Celery, being highly customisable, uses `self.task_cls` in the backend implementation; this defaults to either `Task` or `TaskExtended` depending on the Celery configuration, see [`celery.backends.database:66`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L66): > ```python > task_cls = Task > ``` and [`celery.backends.database:76,77`](https://github.com/celery/celery/blob/406f04a082949ac42ec7a4af94fed896c515aaa4/celery/backends/database/__init__.py#L76-L77): > ```python > if self.extended_result: > self.task_cls = TaskExtended > ``` Airflow should support this flexibility, and instead of importing a fixed class just use `backend.task_cls`, so in `_get_many_from_db_backend` just use: ```python Task = app.backend.task_cls with session_cleanup(session): tasks = session.query(Task).filter(Task.task_id.in_(task_ids)).all() ``` I suppose there is one downside to this: `TaskExtended` fetches a few more columns per task, but given that the result of `task.to_dict()` is passed to `backend.meta_from_decoded()`, which could also have been customised to make use of information contained in a custom model, that's neither here nor there. It would be the price anyone using the `result_extended` option would need to pay elsewhere 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 googleapis/google-cloud-python codebase. Here's the problem: DISCUSSION: Implement Key.__eq__ and Entity.__eq__ Currently comparison must be done in an ad-hoc way: ``` python assert dict(arya_entity.items()) == {'name': 'Arya', 'family': 'Stark'}) ``` FWIW `__eq__` is not something that should really be needed outside of the `Key`, and even then not so much. **NOTE**: This was a small part of #336 DISCUSSION: Implement Key.__eq__ and Entity.__eq__ Currently comparison must be done in an ad-hoc way: ``` python assert dict(arya_entity.items()) == {'name': 'Arya', 'family': 'Stark'}) ``` FWIW `__eq__` is not something that should really be needed outside of the `Key`, and even then not so much. **NOTE**: This was a small part of #336 DISCUSSION: Implement Key.__eq__ and Entity.__eq__ Currently comparison must be done in an ad-hoc way: ``` python assert dict(arya_entity.items()) == {'name': 'Arya', 'family': 'Stark'}) ``` FWIW `__eq__` is not something that should really be needed outside of the `Key`, and even then not so much. **NOTE**: This was a small part of #336 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: datastore: default to empty dataset When working with datasets, the Datastore backend will normalize any empty datasets to the dataset of the calling application. This should be preferred to prepending "s~" to dataset ids as that is not always a valid operation. 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: [Suggestion] has_function should accept 'required' keyword has_header_symbol accepts the required keyword so it can error when a symbol is missing. has_function is more robust since it checks that it's able to link, but doesn't accept the required keyword. Since they're similar in purpose and usage, I see no reason has_function shouldn't offer the required keyword for convenience as well. Checked against Meson 0.55 on Debian Bullseye GNU/Linux. ``` project('f', 'c') cc = meson.get_compiler('c') cc.has_function('puts', required : 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 conda/conda codebase. Here's the problem: Add expansion of environment variables in `channels` config key As per https://github.com/conda/conda/issues/1156#issuecomment-299913430, can we get expansion of environment variables in the `channels` config key? This would be useful for me, as I can then add the following lines to my `.condarc` file: ``` channels: - https://${USERNAME}:${PASSWORD}@my.private.conda.channel ``` 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: [feature] Improve custom CMakeToolchain blocks extension From https://github.com/conan-io/docs/pull/2312, lets avoid the ``import CMakeToolchainBlock`` altogether, using Python dynamism. 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: MongoDB integration should run the `top` command on the admin database. When configuring the agent check for a database != `admin` to gather stats on the collections, the `top` additional metric no longer works: ``` dd.collector[29969]: WARNING (mongo.py:997): Failed to record `top` metrics top may only be run against the admin database. ``` That's because the `top` command can only be run against the admin database: https://docs.mongodb.com/manual/reference/command/top/#dbcmd.top The issue comes from this line: https://github.com/DataDog/integrations-core/blob/master/mongo/datadog_checks/mongo/mongo.py#L962 That should probably be changed to be: ``` dbtop = admindb.command('top') ``` as the `admindb` variable points to the admin database to be able to run commands that only run against the admin database as stated https://github.com/DataDog/integrations-core/blob/master/mongo/datadog_checks/mongo/mongo.py#L734 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: Incorrect listing of `order` parameter in tobytes The docstring for `tobytes` ([link to source](https://github.com/numpy/numpy/blob/e66453568b685dee47d6e6e634b3a47edffcaeed/numpy/core/_add_newdocs.py#L3935-L3969)) lists the options for the order parameter as 'C', 'F', and None but does not include 'A' or 'K' (as in e.g. the copy docstring). 'Any' is also mentioned as a (seemingly) valid input for the `order` argument in the first part of the docstring. ### Numpy/Python version information: 1.19.0.dev0+35d5c2f 3.8.2 (default, Apr 8 2020, 14:31:25) [GCC 9.3.0] 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 apache/airflow codebase. Here's the problem: ExternalTaskSensor logs a poke message that lists the current execution_date, it should show the execution_date it is poking for. The log for ExternalTaskSensor shows a poke for "dag.task on context[executino_date]" which is the execution_date of the running task. But it would be more helpful to know what execution date it is actually looking for. 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: Remove the "Beta" release label? I think we are being somewhat ineffective in communicating to users that JupyterLab is ready for use. I propose that we drop the "Beta" label on releases, but still keep the pre-1.0 version number. We've had discussions and disagreements about whether we want to release 1.0 or not, and I think this strikes a nice balance of communicating what we want to the different audiences we are addressing. As a huge generalization, users seem to pay attention to the words, while developers seem to pay attention to the more precise and semantically meaningful version numbers. If we want to communicate to users that JLab is ready for use, I think we should drop the "Beta" label. If we want to communicate to developers that we are still stabilizing the extension api, and breaking changes are coming every 4-6 weeks with a new 0.x release, we should keep the pre-1.0 version numbers. I think we want to do both, so I propose we call the next release just JupyterLab 0.33. I think we have done a lot of polishing since February, so I think it was still valuable to have a "beta" release period up to this point. What do you think? Are there some important polish issues to address before dropping the beta label? 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 gitpython-developers/GitPython codebase. Here's the problem: Nose unsupported, doesnt work with Python 3.10 3 months until 3.10 is released (Oct 2021), so i've just tried run the test suite on 3.10.0beta4. Didn't get very far, as Nose does not work on 3.10. The issue was reported during 3.9alpha release, so not going to be fixed or released: https://github.com/nose-devs/nose/issues/1099. Finally time to move to pytest? Then can use all the plugins! Seems is as easy to move to pytest as Nose2. If anyone wants to help with that..... ('ve never used Nose before). https://github.com/pytest-dev/nose2pytest might help? Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the googleapis/google-cloud-python codebase. Here's the problem: Incorrect padding error Hi, This is in regards to the pubsub module. When I send a test message with data "testing 1 2 3" from the web console to a simple python application it fails to decode the message and throws a ``` binascii.Error: Incorrect padding ``` Error from ``` File "/python3.5/site-packages/google/cloud/pubsub/message.py", line 88, in from_api_repr data = base64.b64decode(api_repr.get('data', b'')) File "/lib/python3.5/base64.py", line 88, in b64decode ``` I get the same error if I send the same message using the Go libraries. I do not get the error if I send the message using python however. All I'm doing is receiving and printing out the messages. 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: USERPROFILE in conanbuildinfo.props Visual Studio files PR https://github.com/conan-io/conan/pull/2936 was reverted due to failing things. cc/ @pawelkami 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: Fix conda init "--no-user" argument being ignored Currently it is being ignored, because option `no_user` in [https://github.com/conda/conda/blob/master/conda/cli/main_init.py#L46](main_init.py) is marked `False` when `--no-user` option is present. I picked `action="store_true"` instead of `dest="user"` because of existance of the reference to `args.no_user` in the code, probably it is left on intent. 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: Optimizer initialization with DDP ## ❓ Questions and Help #### What is your question? I would have expected optimizers to always be initialized after parameters have been moved to their destination device. However, some ddp backends such as [ddp_backend](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/accelerators/ddp_backend.py#L174), [ddp_spawn_backend](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/accelerators/ddp_spawn_backend.py#L115), [ddp2_backend](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/accelerators/ddp2_backend.py#L111) initialize the optimizer with the CPU parameters before moving the model to the GPU while others such as [gpu_backend](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pytorch_lightning/accelerators/gpu_backend.py#L39) pass the GPU parameters. I'm currently trying to understand two things: (1) Where does the linking from the CPU to GPU parameters happen? (2) Is it actually necessary to initialize the optimizer before moving to the specific device or could it be done afterwards? (Most tutorials initialize the optimizer *after* placing the parameters on the corresponding device, e.g. [this one](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html#basic-use-case)) The reason I'm asking is that I did some parameter/gradient bending to be views into other tensors. This does not work with the current implementation as the optimizer keeps the reference to the CPU parameters with these tweaks but works fine when adapting the pytorch_lightning code by moving the optimizer creation after the model has been moved to the correct device. Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the conan-io/conan codebase. Here's the problem: [bug] Linter "Unable to import" warning when importing a shared Python Conan package in the build() step - [x] I've read the [CONTRIBUTING guide](https://raw.githubusercontent.com/conan-io/conan/develop/.github/CONTRIBUTING.md). - [x] I've specified the Conan version, operating system version and any tool that can be relevant. - [x] I've explained the steps to reproduce the error or the motivation/use case of the question/suggestion. --- I followed the instructions on http://docs.conan.io/en/latest/howtos/python_code_reuse.html. When I get to the "Requiring a python conan package" step, the linter gives me a warning about importing the shared package: $ git clone https://github.com/smokris/conan-test-library $ cd conan-test-library $ conan export . me/testing $ cd .. $ git clone https://github.com/smokris/conan-test-consumer $ cd conan-test-consumer $ conan create . me/testing HelloPyReuse/1.0@me/testing: Exporting package recipe Linter warnings WARN: Linter. Line 9: Unable to import 'hello' … HelloPyReuse/1.0@me/testing: Calling build() Hello World from Python! … (The imported package works fine; the problem is just that the linter is emitting a warning. I'd prefer that the linter not show this false-positive warning, to improve the linter's signal-to-noise ratio.) I'm able to reproduce this using: - Conan 1.1.1 on my local macOS 10.13.3 system - Conan 1.1.1 on Travis CI's Mac OS 10.10.5 image - Conan 1.1.1 on Travis CI's Ubuntu 14.04.5 image - Conan 1.2.0 on CentOS 7.4 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: Remove `--live-stream` option ### What is the idea? Remove the `--live-stream` option as it isn't useful and it's confusing users (eg. https://github.com/conda/conda/issues/10558). ### Why is this needed `--live-stream` is used (only!) by `subprocess_call` (and is only passed in `conda.cli.main_run`): https://github.com/conda/conda/blob/35cd47952fe694b49375a72bdbaf7834570fdc2d/conda/cli/main_run.py#L30-L37 and has the effect that stdout/stderr are printed as well as captured in the parent process: https://github.com/conda/conda/blob/20622423ace946475ba1680b74ea99c52ed2230e/conda/gateways/subprocess.py#L87-L94 The captured stdout/stderr is attached to the `response` object returned by that function: https://github.com/conda/conda/blob/20622423ace946475ba1680b74ea99c52ed2230e/conda/gateways/subprocess.py#L124 But it is ignored subsequently: https://github.com/conda/conda/blob/35cd47952fe694b49375a72bdbaf7834570fdc2d/conda/cli/main_run.py#L49-L53 Thus it looks like the only effect `--live-stream` does have is that it makes `conda xyz` output appear live on the terminal, the same effect as `--no-capture-output`. ### What should happen? Deprecate `--live-stream` and temporarily make it an alias to `--no-capture-output`, then in the future remove the `--live-stream` option ### Additional Context _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 mesonbuild/meson codebase. Here's the problem: No docs on handling sysroot for pkg-config in cross-builds? Hi, 1. First, my impression is that the recommended way to make pkg-config work when cross-compiling is to set PKG_CONFIG_PATH and PKG_CONFIG_SYSROOT_DIR. Is this accurate? 2. Second, assuming that #1 is at least partially accurate, can we say something about this in the help for doing cross-compilation? I ask because I spent about 5 hours figuring this approach out while doing a cross-compile from linux to windows using gtk2 libs from `repo.msys2.org`. There's nothing about sysroots in here: http://mesonbuild.com/Cross-compilation.html It also looks like setting the sys_root property is (maybe) deprecated and (maybe) doesn't do anything? Maybe this should also be mentioned in the docs. if @nirbheek or @jpakkane can give my an overview I can make a PR with some attempted docs. 3. Third, it looks like there is no way to set the PKG_CONFIG_PATH and PKG_CONFIG_SYSROOT variables in the cross file. is this intentional? My apologies if I'm just overlooking some documentation. Meson is pretty nice overall to use for cross-building. -BenRI 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: Error in Rz gate There is a bug in this line and the line above it (rz gate): https://github.com/QISKit/qiskit-sdk-py/blob/4f15c99c1dc4b91abd5d54ccc6b94c8e38ac4997/qiskit/extensions/standard/rz.py#L61 It is replicated in rx and ry as well. 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: dir(numpy) returns duplicate "testing" <!-- Please describe the issue in detail here, and fill in the fields below --> ### Reproducing code example: <!-- A short code example that reproduces the problem/missing feature. It should be self-contained, i.e., possible to run as-is via 'python myproblem.py' --> ```python import numpy as np >>> np.__version__ '1.18.1' >>> len(dir(np)) 620 >>> np.testing <module 'numpy.testing' from 'C:\\Python\\Python38\\lib\\site-packages\\numpy\\testing\\__init__.py'> >>> len(dir(np)) 621 >>> [i for i in dir(np) if i == "testing"] ['testing', 'testing'] ``` ### Error: "testing" appears twice in dir(np) ### Numpy/Python version information: <!-- Output from 'import sys, numpy; print(numpy.__version__, sys.version)' --> Python 3.8.0 (tags/v3.8.0:fa919fd, Oct 14 2019, 19:37:50) [MSC v.1916 64 bit (AMD64)] on win32 >>> np.__version__ '1.18.1' 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: Pre-processing re-runs for each process ### System Info - `transformers` version: 4.22.0.dev0 - Platform: Linux-4.15.0-180-generic-x86_64-with-glibc2.27 - Python version: 3.10.4 - Huggingface_hub version: 0.8.1 - PyTorch version (GPU?): 1.12.1+cu102 (True) - Tensorflow version (GPU?): not installed (NA) - Flax version (CPU?/GPU?/TPU?): not installed (NA) - Jax version: not installed - JaxLib version: not installed - Using GPU in script?: yes - Using distributed or parallel set-up in script?: yes ### Who can help? @muellerzr @sgugger @patil-suraj ### Information - [X] The official example scripts - [ ] My own modified scripts ### Tasks - [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction In `examples/summarization_no_trainer.py`, we use the following code to pre-process the data: ``` with accelerator.main_process_first(): processed_datasets = raw_datasets.map( preprocess_function, batched=True, num_proc=args.preprocessing_num_workers, remove_columns=column_names, load_from_cache_file=not args.overwrite_cache, desc="Running tokenizer on dataset", ) ``` In a multi-GPU (process) setup, the main process pre-processes the data first and saves it in the cache. Ideally, the other processes should just pick it up from there. But that's not happening. Every process is re-pre-processing the data. This is a problem when the data is large. I have tried to check if something changes during the run with `Hasher.hash(preprocess_func)`. But the hash remains the same. ### Expected behavior Processes other than the main process should read the processed data from cache.the 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: custom_jvp does not work when first jvp rule is None Here is a repro code ```python from jax import grad, custom_jvp @custom_jvp def f(x, y): return x ** 2 * y f.defjvps(None, lambda x_dot, primal_out, x, y: 2 * x * y * x_dot) print(grad(f, 1)(2., 3.)) ``` Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the numpy/numpy codebase. Here's the problem: np.array_repr fails on np.matrix objects Cause of #5875: ```python >>> np.array_repr(np.eye(2).view(np.matrix)) Traceback (most recent call last): File "<pyshell#52>", line 1, in <module> np.array_repr(np.matrix(np.eye(2))) File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\numeric.py", line 1807, in array_repr ', ', "array(") File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 447, in array2string separator, prefix, formatter=formatter) File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 325, in _array2string _summaryEdgeItems, summary_insert)[:-1] File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 519, in _formatArray summary_insert) File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 496, in _formatArray word = format_function(a[-1]) File "C:\Program Files\Python 3.5\lib\site-packages\numpy\core\arrayprint.py", line 598, in __call__ if isnan(x): ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() ``` Spot the `x[i].shape == x.shape[1:]` fallacy... 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: Normalize module docstring patterns From https://github.com/GoogleCloudPlatform/gcloud-python/pull/1164/files#r40942738. ``` $ git grep "API wrapper" gcloud/bigquery/__init__.py:"""Google Cloud BigQuery API wrapper. gcloud/dns/__init__.py:"""Google Cloud DNS API wrapper. gcloud/pubsub/__init__.py:"""Google Cloud Pubsub API wrapper. gcloud/resource_manager/__init__.py:"""Google Cloud Resource Manager API wrapper gcloud/search/__init__.py:"""Google Cloud Search API wrapper.""" $ git grep "interacting with API" gcloud/bigquery/client.py:"""gcloud bigquery client for interacting with API.""" gcloud/client.py:"""gcloud client base class for interacting with API.""" gcloud/dns/client.py:"""gcloud dns client for interacting with API.""" gcloud/pubsub/client.py:"""gcloud pubsub client for interacting with API.""" gcloud/search/client.py:"""gcloud dns client for interacting with API.""" gcloud/storage/client.py:"""gcloud storage client for interacting with API.""" ``` Can you help me debug this systematically and explain your reasoning?


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

[User] I'm having an issue with the conda/conda codebase. Here's the problem: conda install --offline still performs online operations Even `conda` seems to notice that it shouldn't be doing an online operation when the `--offline` flag has been specified: ```bash $ conda install --offline statsmodels Fetching package metadata ........... Solving package specifications: . Package plan for installation in environment C:\Users\d53542\AppData\Local\Continuum\Anaconda2: The following packages will be UPDATED: statsmodels: 0.6.1-np111py27_1 --> 0.8.0-np111py27_0 Proceed ([y]/n)? y CondaError: RuntimeError(u'EnforceUnusedAdapter called with url https://repo.continuum.io/pkgs/free/win-64/statsmodels-0.8.0-np111py27_0.tar.bz2\nThis command is using a remote connection in offline m ode.\n',) CondaError: RuntimeError(u'EnforceUnusedAdapter called with url https://repo.continuum.io/pkgs/free/win-64/statsmodels-0.8.0-np111py27_0.tar.bz2\nThis command is using a remote connection in offline m ode.\n',) CondaError: RuntimeError(u'EnforceUnusedAdapter called with url https://repo.continuum.io/pkgs/free/win-64/statsmodels-0.8.0-np111py27_0.tar.bz2\nThis command is using a remote connection in offline m ode.\n',) C:\Users\d53542\Documents\GIT\health_score>conda -V conda 4.3.17 ``` I'm at PyCon and am seeing this on the computer of someone I'm talking to (an Anaconda user) 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: TPU Training Issues and Feature Requests TPU training is really cool. A couple issues that came up in training. * There is no longer a call to `optimizer_step` this is needed for setting learning rates that change over each step. Not sure how to fix this except by maybe having another "post_optimizer" call, which might be a better place for this style of stepping. * According to this tutorial https://github.com/pytorch/xla/blob/master/TROUBLESHOOTING.md `clip_grad_norm_` is very slow in XLA. The give a suggestion for a replacement function call. It would be nice if lightning just called this instead. * Nice to have: Point to that speed tutorial in the docs so people don't get stuck. * When using DDP, we have been using proc_rank to decide when to print debug statements. Might be nice to have a value that works with DDP and TPU to abstract away from using this term. 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: Windows: NameError: global name 'ExecOperation' is not defined If I try to run a `docker-compose exec` command it always gives me this error: ``` D:\Path\> docker-compose exec some-container some-command Traceback (most recent call last): File "<string>", line 3, in <module> File "compose\cli\main.py", line 57, in main File "compose\cli\main.py", line 108, in perform_command File "compose\cli\main.py", line 347, in exec_command NameError: global name 'ExecOperation' is not defined docker-compose returned -1 ``` Is there a known bug on this message? My guess is that this has something to do with this message `Interactive mode is not yet supported on Windows.` when you use `docker-compose run` but I'm not sure.. Thanks for any help in advance! Some more system information: ``` D:\> docker version Client: Version: 1.11.0 API version: 1.23 Go version: go1.5.4 Git commit: 4dc5990 Built: Wed Apr 13 18:13:28 2016 OS/Arch: windows/amd64 Server: Version: 1.11.0 API version: 1.23 Go version: go1.5.4 Git commit: 4dc5990 Built: Wed Apr 13 19:36:04 2016 OS/Arch: linux/amd64 D:\> docker-compose version docker-compose version 1.7.0, build 0d7bf73 docker-py version: 1.8.0 CPython version: 2.7.11 OpenSSL version: OpenSSL 1.0.2d 9 Jul 2015 ``` 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: BLD: Regression: improper double quotes appear in rpath (linux) ### Steps to reproduce the problem: I've observed a regression on RH7 when installing numpy (currently v1.16.0) with ```bash pip install numpy --force-reinstall --ignore-installed --no-binary :all: ``` Until now I had no problem with python 3.6.5 (and previous) and with earlier versions of numpy (v1.14.3), now I observe the following issue (python 3.7.2, and even python 3.6.5) with numpy 1.16.0. I fill `~/site.cfg` with information where to find lapack and blas libraries ```ini [lapack] lapack_libs = lapack language = gfortran library_dirs = /some/path/rh7/lapack/3.6.1/lib runtime_library_dirs = /some/path/rh7/lapack/3.6.1/lib [blas] blas_libs = blas,cblas language = gfortran library_dirs = /some/path/rh7/lapack/3.6.1/lib runtime_library_dirs = /some/path/rh7/lapack/3.6.1/lib ``` ### Observed problem: When I run `ldd` on the produced `numpy/linalg/lapack_lite.cpython-*m-x86_64-linux-gnu.so`, `liblapack.so`, `libblas.so` and `libblas.so` aren't found. When I ask `readelf -d numpy/linalg/lapack_lite.cpython-*m-x86_64-linux-gnu.so | grep rpath`, I see ``` 0x000000000000000f (RPATH) Library rpath: ["/some/path/rh7/lapack/3.6.1/lib"] ``` instead of ``` 0x000000000000000f (RPATH) Library rpath: [/some/path/rh7/lapack/3.6.1/lib] ``` that I had with previous versions of numpy. Removing the double-quotes with `chrpath` fixes the issue. ### Numpy/Python version information: Numpy 1.16.0 (according to `pip -v`) Python 1.6.5 and 1.7.2 No trouble with Numpy 1.14.3 (and earlier versions) and Python 1.6.5 (and earlier versions) Can you help me debug this systematically and explain your reasoning?