[WIP] Add pytorch dependencies

[hmaarrfk]

Results:

• libonnx libonxx + 1.15.0 migration onnx-feedstock#105

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I do have some suggestions for making it better though...

For recipes/pthreadpool:

• Jinja2 variable references are suggested to take a {{<one space><variable name><one space>}} form. See lines [22].

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[conda-forge-linter]

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Here's what I've got...

For recipes/opcodes:

• noarch: python recipes are required to have a lower bound on the python version. Typically this means putting python >=3.6 in both host and run but you should check upstream for the package's Python compatibility.

For recipes/pthreadpool:

• Jinja2 variable references are suggested to take a {{<one space><variable name><one space>}} form. See lines [22].

[ngam]

xref: conda-forge/pytorch-cpu-feedstock#108

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Here's what I've got...

For recipes/opcodes:

• noarch: python recipes are required to have a lower bound on the python version. Typically this means putting python >=3.6 in both host and run but you should check upstream for the package's Python compatibility.

For recipes/peachpy:

• noarch: python recipes are required to have a lower bound on the python version. Typically this means putting python >=3.6 in both host and run but you should check upstream for the package's Python compatibility.

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• Jinja2 variable references are suggested to take a {{<one space><variable name><one space>}} form. See lines [22].

[conda-forge-linter]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipes/clog, recipes/cpuinfo, recipes/fp16, recipes/fxdiv, recipes/opcodes, recipes/peachpy, recipes/psimd, recipes/pthreadpool, recipes/qnnpack, recipes/xnnpack) and found some lint.

Here's what I've got...

For recipes/opcodes:

• noarch: python recipes are required to have a lower bound on the python version. Typically this means putting python >=3.6 in both host and run but you should check upstream for the package's Python compatibility.

For recipes/peachpy:

• noarch: python recipes are required to have a lower bound on the python version. Typically this means putting python >=3.6 in both host and run but you should check upstream for the package's Python compatibility.

[conda-forge-linter]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipes/clog, recipes/cpuinfo, recipes/fp16, recipes/fxdiv, recipes/opcodes, recipes/peachpy, recipes/psimd, recipes/pthreadpool, recipes/qnnpack, recipes/xnnpack) and found it was in an excellent condition.

[conda-forge-linter]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipes/clog, recipes/cpuinfo, recipes/fp16, recipes/fxdiv, recipes/nnpack, recipes/opcodes, recipes/peachpy, recipes/psimd, recipes/pthreadpool, recipes/qnnpack, recipes/xnnpack) and found it was in an excellent condition.

[conda-forge-linter]

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I just wanted to let you know that I linted all conda-recipes in your PR (recipes/clog, recipes/cpuinfo, recipes/fp16, recipes/fxdiv, recipes/gloo, recipes/nnpack, recipes/opcodes, recipes/peachpy, recipes/psimd, recipes/pthreadpool, recipes/qnnpack, recipes/xnnpack) and found it was in an excellent condition.

[h-vetinari]

Awesome work!

Let me know if something specific needs reviewing. :)

[hmaarrfk]

One thing I would want to do is make the patches for the CMake changes upstreamable. I've learned that some dependencies are header only.

Those are stated as STATIC libraries, while we should only be looking for the INTERFACE. This seems like something that upstream might accept.

Finally, I think using FindPackage is likely good for shared system libraries, but I haven't had a chance to test this hypothesis.

Ultimately, this is mostly an academic exercise at this stage, since I don't know how to maintain this.
We would likely have to build these libraries statically, but they don't really move the needle in terms of compilation time for pytorch.

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Here's what I've got...

For recipes/torch_tb_profiler:

• The recipe must have a build/number section.

For recipes/torch_tb_profiler:

• Whenever possible python packages should use pip. See https://conda-forge.org/docs/maintainer/adding_pkgs.html#use-pip
• License is not an SPDX identifier (or a custom LicenseRef) nor an SPDX license expression.

Documentation on acceptable licenses can be found here.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipes/asmjit, recipes/c10, recipes/clog, recipes/cpuinfo, recipes/dynolog, recipes/fbgemm, recipes/fp16, recipes/fxdiv, recipes/gloo, recipes/kineto, recipes/libnop, recipes/libonnx, recipes/libtorch, recipes/nnpack, recipes/onnx-tensorrt, recipes/opcodes, recipes/peachpy, recipes/pfs, recipes/psimd, recipes/pthreadpool, recipes/pytorch_qnnpack, recipes/qnnpack, recipes/tensorpipe, recipes/torch_tb_profiler, recipes/xnnpack) and found some lint.

Here's what I've got...

For recipes/torch_tb_profiler:

• The recipe must have a build/number section.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I wanted to let you know that I linted all conda-recipes in your PR (recipes/asmjit, recipes/c10, recipes/clog, recipes/cpuinfo, recipes/dynolog, recipes/fbgemm, recipes/fp16, recipes/fxdiv, recipes/gloo, recipes/kineto, recipes/libnop, recipes/libtorch, recipes/nnpack, recipes/onnx, recipes/onnx-tensorrt, recipes/opcodes, recipes/peachpy, recipes/pfs, recipes/psimd, recipes/pthreadpool, recipes/pytorch_qnnpack, recipes/qnnpack, recipes/tensorpipe, recipes/torch_tb_profiler, recipes/xnnpack) and found some lint.

Here's what I've got...

For recipes/torch_tb_profiler:

• The recipe must have a build/number section.

[conda-forge-webservices]

Hi! This is the friendly automated conda-forge-linting service.

I just wanted to let you know that I linted all conda-recipes in your PR (recipes/asmjit, recipes/c10, recipes/clog, recipes/cpuinfo, recipes/dynolog, recipes/fbgemm, recipes/fp16, recipes/fxdiv, recipes/gloo, recipes/kineto, recipes/libnop, recipes/libtorch, recipes/nnpack, recipes/onnx, recipes/onnx-tensorrt, recipes/opcodes, recipes/peachpy, recipes/pfs, recipes/psimd, recipes/pthreadpool, recipes/pytorch_qnnpack, recipes/qnnpack, recipes/tensorpipe, recipes/torch_tb_profiler, recipes/xnnpack) and found it was in an excellent condition.

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[stale]

Hi friend!

We really, really, really appreciate that you have taken the time to make a PR on conda-forge/staged-recipes! conda-forge only exists because people like you donate their time to build and maintain conda recipes for use by the community.

In an effort to maintain this repository and increase the signal-to-noise for open PRs, the maintainers of staged-recipes close excessively old PRs after six months. This PR will remain open for another month, and then will be closed.

If you'd like to keep it open, please comment/push and we will be happy to oblige! Note that very old PRs will likely need to be rebased on main so that they can be rebuilt with the most recent CI scripts. If you have any trouble, or we missed reviewing this PR in the first place (sorry!), feel free to ping the team using a special command in a comment on the PR to get the attention of the staged-recipes team.

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