Space Duplication does not work. Build Error

#6
by sas404 - opened

Hello, I am trying to duplicate the SadTalker HuggingFace Space running on A10G but I get a bunch of build errors and it fails.

Can someone help?

any error here?

Same issue tried with the A10G and A10G Large duplicate none with success - Also getting build errors

Here is the end of the log - I will attach the text as well if possible

        error: Command "gcc -pthread -Wno-unused-result -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -DNPY_INTERNAL_BUILD=1 -DHAVE_NPY_CONFIG_H=1 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE=1 -D_LARGEFILE64_SOURCE=1 -Ibuild/src.linux-x86_64-3.1/numpy/core/src/umath -Ibuild/src.linux-x86_64-3.1/numpy/core/src/npymath -Ibuild/src.linux-x86_64-3.1/numpy/core/src/common -Inumpy/core/include -Ibuild/src.linux-x86_64-3.1/numpy/core/include/numpy -Inumpy/core/src/common -Inumpy/core/src -Inumpy/core -Inumpy/core/src/npymath -Inumpy/core/src/multiarray -Inumpy/core/src/umath -Inumpy/core/src/npysort -I/home/user/.pyenv/versions/3.10.11/include/python3.10 -Ibuild/src.linux-x86_64-3.1/numpy/core/src/common -Ibuild/src.linux-x86_64-3.1/numpy/core/src/npymath -Ibuild/src.linux-x86_64-3.1/numpy/core/src/common -Ibuild/src.linux-x86_64-3.1/numpy/core/src/npymath -c build/src.linux-x86_64-3.1/numpy/core/src/multiarray/scalartypes.c -o build/temp.linux-x86_64-cpython-310/build/src.linux-x86_64-3.1/numpy/core/src/multiarray/scalartypes.o -MMD -MF build/temp.linux-x86_64-cpython-310/build/src.linux-x86_64-3.1/numpy/core/src/multiarray/scalartypes.o.d" failed with exit status 1
        [end of output]
  
    note: This error originates from a subprocess, and is likely not a problem with pip.
  error: legacy-install-failure
  
  ร— Encountered error while trying to install package.
  โ•ฐโ”€> numpy
  
  note: This is an issue with the package mentioned above, not pip.
  hint: See above for output from the failure.
  
  [notice] A new release of pip available: 22.3.1 -> 23.1.2
  [notice] To update, run: pip install --upgrade pip
  [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
error: subprocess-exited-with-error

ร— pip subprocess to install build dependencies did not run successfully.
โ”‚ exit code: 1
โ•ฐโ”€> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.

[notice] A new release of pip available: 22.3.1 -> 23.1.2
[notice] To update, run: pip install --upgrade pip

--> ERROR: process "/bin/sh -c pip install --no-cache-dir -r requirements.txt" did not complete successfully: exit code: 1

Here is a link to a txt error log I extracted from here: http://u.pc.cd/8XN

you can try to replace the scipy==1.5.1 in requirements.txt with scipy==1.10.1 and the compiler it again. For me, T4 might be working fine for our model.

Doesn't work

you can try to replace the scipy==1.5.1 in requirements.txt with scipy==1.10.1 and the compiler it again. For me, T4 might be working fine for our model.

Having the same issue trying to duplicate the space. Not working on when running via the GitHub.

you can try to replace the scipy==1.5.1 in requirements.txt with scipy==1.10.1 and the compiler it again. For me, T4 might be working fine for our model.

But since we try to duplicate the space Huggingface does not allow us to do this - it just executes an onsite duplication

you can edit the file

you can edit the file

Not really - There is simply a button - Duplicate Space and then a build fail

Duplicate Space... It will fail most likely but to make the changes follow along with video.
It still fails for me but at a different part.

Anyone have ideas?

Fixed. There have some 3rd packages showing different behaviors.

Temporally remove the TTS package.

Yup - I could duplicate the space now

Yup - I could duplicate the space now

However I have reverted back to my local CPU driven SadTalker creation, because the HuggingFace duplicated space keeps returning errors towards the end of processing and the time I am using to reprocess and the effort is nearly the same as just setting the script to run it locally on CPU

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