Bug#1067375: amp: FTBFS: FileNotFoundError: [Errno 2] No such file or directory: 'meson'
Lucas Nussbaum
lucas at debian.org
Wed Mar 20 20:40:50 GMT 2024
Source: amp
Version: 0.6.1-1
Severity: serious
Justification: FTBFS
Tags: trixie sid ftbfs
User: lucas at debian.org
Usertags: ftbfs-20240319 ftbfs-trixie
Hi,
During a rebuild of all packages in sid, your package failed to build
on amd64.
Relevant part (hopefully):
> make[2]: Entering directory '/<<PKGBUILDDIR>>/amp/descriptor'
> gfortran -c cutoffs.f90
> cp cutoffs.mod ..
> make[2]: Leaving directory '/<<PKGBUILDDIR>>/amp/descriptor'
> f2py3.12 -c -m fmodules model.f90 descriptor/cutoffs.f90 descriptor/gaussian.f90 descriptor/zernike.f90 model/neuralnetwork.f90
> rmbadname1: Replacing "index" with "index_bn".
> Cannot use distutils backend with Python>=3.12, using meson backend instead.
> Using meson backend
> Will pass --lower to f2py
> See https://numpy.org/doc/stable/f2py/buildtools/meson.html
> Reading fortran codes...
> Reading file 'model.f90' (format:free)
> ::image_forces <re.Match object; span=(0, 14), match='::image_forces'>
> ::integer_one_d_array <re.Match object; span=(0, 21), match='::integer_one_d_array'>
> ::embedded_real_one_one_d_array <re.Match object; span=(0, 31), match='::embedded_real_one_one_d_array'>
> ::embedded_real_one_two_d_array <re.Match object; span=(0, 31), match='::embedded_real_one_two_d_array'>
> ::embedded_integer_one_one_d_array <re.Match object; span=(0, 34), match='::embedded_integer_one_one_d_array'>
> ::embedded_one_one_two_d_array <re.Match object; span=(0, 30), match='::embedded_one_one_two_d_array'>
> Reading file 'descriptor/cutoffs.f90' (format:free)
> Reading file 'descriptor/gaussian.f90' (format:free)
> Reading file 'descriptor/zernike.f90' (format:free)
> Reading file 'model/neuralnetwork.f90' (format:free)
> ::real_two_d_array <re.Match object; span=(0, 18), match='::real_two_d_array'>
> ::element_parameters <re.Match object; span=(0, 20), match='::element_parameters'>
> ::real_one_d_array <re.Match object; span=(0, 18), match='::real_one_d_array'>
> Post-processing...
> Block: fmodules
> Block: check_version
> Block: fingerprint_props
> Block: model_props
> Block: images_props
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_energy
> vars2fortran: No typespec for argument "image_no".
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_forces
> vars2fortran: No typespec for argument "image_no".
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_denergy_dparameters
> vars2fortran: No typespec for argument "image_no".
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_numerical_denergy_dparameters
> vars2fortran: No typespec for argument "image_no".
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_dforces_dparameters
> vars2fortran: No typespec for argument "image_no".
> {}
> In: :fmodules:model.f90:calculate_loss:calculate_numerical_dforces_dparameters
> vars2fortran: No typespec for argument "image_no".
> Block: calculate_loss
> In: :fmodules:model.f90:calculate_loss
> get_useparameters: no module neuralnetwork info used by calculate_loss
> Block: image_forces
> In: :fmodules:model.f90:calculate_loss:image_forces
> get_useparameters: no module neuralnetwork info used by image_forces
> Block: integer_one_d_array
> In: :fmodules:model.f90:calculate_loss:integer_one_d_array
> get_useparameters: no module neuralnetwork info used by integer_one_d_array
> Block: embedded_real_one_one_d_array
> In: :fmodules:model.f90:calculate_loss:embedded_real_one_one_d_array
> get_useparameters: no module neuralnetwork info used by embedded_real_one_one_d_array
> Block: embedded_real_one_two_d_array
> In: :fmodules:model.f90:calculate_loss:embedded_real_one_two_d_array
> get_useparameters: no module neuralnetwork info used by embedded_real_one_two_d_array
> Block: embedded_integer_one_one_d_array
> In: :fmodules:model.f90:calculate_loss:embedded_integer_one_one_d_array
> get_useparameters: no module neuralnetwork info used by embedded_integer_one_one_d_array
> Block: embedded_one_one_two_d_array
> In: :fmodules:model.f90:calculate_loss:embedded_one_one_two_d_array
> get_useparameters: no module neuralnetwork info used by embedded_one_one_two_d_array
> Block: deallocate_variables
> In: :fmodules:model.f90:deallocate_variables
> get_useparameters: no module neuralnetwork info used by deallocate_variables
> Block: cutoffs
> Block: cutoff_fxn
> Block: cutoff_fxn_prime
> Block: calculate_g2
> Block: calculate_g4
> Block: calculate_g2_prime
> Block: calculate_g4_prime
> Block: calculate_zernike_prime
> Block: calculate_z
> Block: calculate_z_prime
> Block: calculate_q
> Block: binomial
> Block: neuralnetwork
> Block: real_two_d_array
> Block: element_parameters
> Block: real_one_d_array
> Block: calculate_image_energy
> Block: calculate_atomic_energy
> Block: calculate_force_
> Block: calculate_force
> Block: calculate_denergy_dparameters_
> Block: calculate_datomicenergy_dparameters
> Block: calculate_dforce_dparameters_
> Block: calculate_dforce_dparameters
> Applying post-processing hooks...
> character_backward_compatibility_hook
> Post-processing (stage 2)...
> Block: fmodules
> Block: unknown_interface
> Block: check_version
> Block: fingerprint_props
> Block: model_props
> Block: images_props
> Block: calculate_loss
> Block: image_forces
> Block: integer_one_d_array
> Block: embedded_real_one_one_d_array
> Block: embedded_real_one_two_d_array
> Block: embedded_integer_one_one_d_array
> Block: embedded_one_one_two_d_array
> Block: deallocate_variables
> Block: cutoffs
> Block: cutoff_fxn
> Block: cutoff_fxn_prime
> Block: calculate_g2
> Block: calculate_g4
> Block: calculate_g2_prime
> Block: calculate_g4_prime
> Block: calculate_zernike_prime
> Block: calculate_z
> Block: calculate_z_prime
> Block: calculate_q
> Block: binomial
> Block: neuralnetwork
> Block: real_two_d_array
> Block: element_parameters
> Block: real_one_d_array
> Block: calculate_image_energy
> Block: calculate_atomic_energy
> Block: calculate_force_
> Block: calculate_force
> Block: calculate_denergy_dparameters_
> Block: calculate_datomicenergy_dparameters
> Block: calculate_dforce_dparameters_
> Block: calculate_dforce_dparameters
> Building modules...
> Building module "fmodules"...
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "check_version"...
> warning = check_version(version)
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_loss"...
> loss,dloss_dparameters,energyloss,forceloss,energy_maxresid,force_maxresid = calculate_loss(parameters,lossprime,[num_parameters])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "deallocate_variables"...
> deallocate_variables()
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_g2"...
> ridge = calculate_g2(neighbornumbers,neighborpositions,g_number,g_eta,rc,cutofffn,ri,[p_gamma])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_g4"...
> ridge = calculate_g4(neighbornumbers,neighborpositions,g_numbers,g_gamma,g_zeta,g_eta,rc,cutofffn,ri,[p_gamma])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_g2_prime"...
> ridge = calculate_g2_prime(neighborindices,neighbornumbers,neighborpositions,g_number,g_eta,rc,cutofffn,i,ri,m,l,[p_gamma])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_g4_prime"...
> ridge = calculate_g4_prime(neighborindices,neighbornumbers,neighborpositions,g_numbers,g_gamma,g_zeta,g_eta,rc,cutofffn,i,ri,m,l,[p_gamma])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_zernike_prime"...
> norm_prime = calculate_zernike_prime(n,l,n_indices,numbers,rs,g_numbers,cutoff,indexx,home,p,q,factorial,cutofffn,[n_length,fac_length,p_gamma])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_z"...
> output = calculate_z(n,l,m,x,y,z,factorial,[length])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_z_prime"...
> output = calculate_z_prime(n,l,m,x,y,z,p,factorial,[length])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "calculate_q"...
> output = calculate_q(nu,k,l,factorial,[length])
> Generating possibly empty wrappers"
> Maybe empty "fmodules-f2pywrappers.f"
> Constructing wrapper function "binomial"...
> output = binomial(n,k,factorial,[length])
> Constructing F90 module support for "fingerprint_props"...
> Variables: num_fingerprints_of_elements raveled_fingerprints raveled_fingerprintprimes
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> Constructing F90 module support for "model_props"...
> Variables: mode_signal train_forces energy_coefficient force_coefficient overfit numericprime d
> Constructing F90 module support for "images_props"...
> Variables: num_images num_elements elements_numbers num_images_atoms atomic_numbers num_neighbors raveled_neighborlists actual_energies actual_forces num_atoms atomic_positions
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> Constructing F90 module support for "cutoffs"...
> Skipping cutoffs since it is in 'use'...
> Constructing F90 module support for "neuralnetwork"...
> Variables: min_fingerprints max_fingerprints no_layers_of_elements no_nodes_of_elements activation_signal
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> getarrdims:warning: assumed shape array, using 0 instead of ':'
> f90mod_rules.buildhooks: skipping type real_two_d_array
> f90mod_rules.buildhooks: skipping type element_parameters
> f90mod_rules.buildhooks: skipping type real_one_d_array
> Creating wrapper for Fortran function "calculate_image_energy"("calculate_image_energy")...
> Constructing wrapper function "neuralnetwork.calculate_image_energy"...
> calculate_image_energy = calculate_image_energy(inputs,parameters,[num_inputs,num_parameters])
> Creating wrapper for Fortran function "calculate_atomic_energy"("calculate_atomic_energy")...
> Constructing wrapper function "neuralnetwork.calculate_atomic_energy"...
> calculate_atomic_energy = calculate_atomic_energy(symbol,fingerprint,elements_numbers,parameters,[len_of_fingerprint,num_elements,num_parameters])
> Creating wrapper for Fortran function "calculate_force_"("calculate_force_")...
> Constructing wrapper function "neuralnetwork.calculate_force_"...
> calculate_force_ = calculate_force_(inputs,inputs_,parameters,[num_inputs,num_parameters])
> Creating wrapper for Fortran function "calculate_force"("calculate_force")...
> Constructing wrapper function "neuralnetwork.calculate_force"...
> calculate_force = calculate_force(symbol,fingerprint,fingerprintprime,elements_numbers,parameters,[len_of_fingerprint,num_elements,num_parameters])
> Creating wrapper for Fortran function "calculate_denergy_dparameters_"("calculate_denergy_dparameters_")...
> Constructing wrapper function "neuralnetwork.calculate_denergy_dparameters_"...
> calculate_denergy_dparameters_ = calculate_denergy_dparameters_(inputs,parameters,[num_inputs,num_parameters])
> Creating wrapper for Fortran function "calculate_datomicenergy_dparameters"("calculate_datomicenergy_dparameters")...
> Constructing wrapper function "neuralnetwork.calculate_datomicenergy_dparameters"...
> calculate_datomicenergy_dparameters = calculate_datomicenergy_dparameters(symbol,fingerprint,elements_numbers,parameters,[len_of_fingerprint,num_elements,num_parameters])
> Creating wrapper for Fortran function "calculate_dforce_dparameters_"("calculate_dforce_dparameters_")...
> Constructing wrapper function "neuralnetwork.calculate_dforce_dparameters_"...
> calculate_dforce_dparameters_ = calculate_dforce_dparameters_(inputs,inputs_,parameters,[num_inputs,num_parameters])
> Creating wrapper for Fortran function "calculate_dforce_dparameters"("calculate_dforce_dparameters")...
> Constructing wrapper function "neuralnetwork.calculate_dforce_dparameters"...
> calculate_dforce_dparameters = calculate_dforce_dparameters(symbol,fingerprint,fingerprintprime,elements_numbers,parameters,[len_of_fingerprint,num_elements,num_parameters])
> Wrote C/API module "fmodules" to file "./fmodulesmodule.c"
> Fortran 90 wrappers are saved to "./fmodules-f2pywrappers2.f90"
> Traceback (most recent call last):
> File "/usr/bin/f2py", line 8, in <module>
> sys.exit(main())
> ^^^^^^
> File "/usr/lib/python3/dist-packages/numpy/f2py/f2py2e.py", line 766, in main
> run_compile()
> File "/usr/lib/python3/dist-packages/numpy/f2py/f2py2e.py", line 738, in run_compile
> builder.compile()
> File "/usr/lib/python3/dist-packages/numpy/f2py/_backends/_meson.py", line 178, in compile
> self.run_meson(self.build_dir)
> File "/usr/lib/python3/dist-packages/numpy/f2py/_backends/_meson.py", line 171, in run_meson
> self._run_subprocess_command(setup_command, build_dir)
> File "/usr/lib/python3/dist-packages/numpy/f2py/_backends/_meson.py", line 167, in _run_subprocess_command
> subprocess.run(command, cwd=cwd, check=True)
> File "/usr/lib/python3.12/subprocess.py", line 548, in run
> with Popen(*popenargs, **kwargs) as process:
> ^^^^^^^^^^^^^^^^^^^^^^^^^^^
> File "/usr/lib/python3.12/subprocess.py", line 1026, in __init__
> self._execute_child(args, executable, preexec_fn, close_fds,
> File "/usr/lib/python3.12/subprocess.py", line 1953, in _execute_child
> raise child_exception_type(errno_num, err_msg, err_filename)
> FileNotFoundError: [Errno 2] No such file or directory: 'meson'
> make[1]: *** [Makefile:5: python3.12] Error 1
The full build log is available from:
http://qa-logs.debian.net/2024/03/19/amp_0.6.1-1_unstable.log
All bugs filed during this archive rebuild are listed at:
https://bugs.debian.org/cgi-bin/pkgreport.cgi?tag=ftbfs-20240319;users=lucas@debian.org
or:
https://udd.debian.org/bugs/?release=na&merged=ign&fnewerval=7&flastmodval=7&fusertag=only&fusertagtag=ftbfs-20240319&fusertaguser=lucas@debian.org&allbugs=1&cseverity=1&ctags=1&caffected=1#results
A list of current common problems and possible solutions is available at
http://wiki.debian.org/qa.debian.org/FTBFS . You're welcome to contribute!
If you reassign this bug to another package, please mark it as 'affects'-ing
this package. See https://www.debian.org/Bugs/server-control#affects
If you fail to reproduce this, please provide a build log and diff it with mine
so that we can identify if something relevant changed in the meantime.
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