Torchaudio installed through PIP not detecting ffmpeg from conda-forge channel #3872
Comments
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Same for non-conda, under Windows environment. I'm trying to launch this tutorial: https://github.com/pytorch/audio/blob/main/examples/tutorials/audio_data_augmentation_tutorial.py Tried 7-6-5 versions, PATH variable is correct. |
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I also see this. E.g., running from torio.utils.ffmpeg_utils import get_audio_encoders
get_audio_encoders()
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
Cell In[13], line 1
----> 1 get_audio_encoders()
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/utils/ffmpeg_utils.py:135, in get_audio_encoders()
119 def get_audio_encoders() -> Dict[str, str]:
120 """Get the available audio encoders.
121
122 Returns:
(...)
133 ... alac: ALAC (Apple Lossless Audio Codec)
134 """
--> 135 return ffmpeg_ext.get_audio_encoders()
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/_extension/utils.py:25, in _LazyImporter.__getattr__(self, item)
24 def __getattr__(self, item):
---> 25 self._import_once()
26 return getattr(self.module, item)
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/_extension/utils.py:39, in _LazyImporter._import_once(self)
37 def _import_once(self):
38 if self.module is None:
---> 39 self.module = self.import_func()
40 # Note:
41 # By attaching the module attributes to self,
42 # module attributes are directly accessible.
43 # This allows to avoid calling __getattr__ for every attribute access.
44 self.__dict__.update(self.module.__dict__)
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/_extension/utils.py:143, in _init_ffmpeg()
141 def _init_ffmpeg():
142 ffmpeg_vers = _get_ffmpeg_versions()
--> 143 ext = _find_ffmpeg_extension(ffmpeg_vers)
144 ext.init()
145 if ext.get_log_level() > 8:
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/_extension/utils.py:122, in _find_ffmpeg_extension(ffmpeg_vers)
120 _LG.debug("Failed to load FFmpeg%s extension.", ffmpeg_ver, exc_info=True)
121 continue
--> 122 raise ImportError(
123 f"Failed to intialize FFmpeg extension. Tried versions: {ffmpeg_vers}. "
124 "Enable DEBUG logging to see more details about the error."
125 )
ImportError: Failed to intialize FFmpeg extension. Tried versions: ['6', '5', '4', '']. Enable DEBUG logging to see more details about the error.I get the same errors are others reported. But delving further, to find the source of this, if I do: from torio._extension.utils import _load_lib
version = 6
lib = f"libtorio_ffmpeg{version}"
_load_lib(lib)
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
Cell In[21], line 1
----> 1 _load_lib(lib)
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torio/_extension/utils.py:94, in _load_lib(lib)
92 if not path.exists():
93 return False
---> 94 torch.ops.load_library(path)
95 return True
File ~/miniconda3/envs/tadl/lib/python3.10/site-packages/torch/_ops.py:1357, in _Ops.load_library(self, path)
1352 path = _utils_internal.resolve_library_path(path)
1353 with dl_open_guard():
1354 # Import the shared library into the process, thus running its
1355 # static (global) initialization code in order to register custom
1356 # operators with the JIT.
-> 1357 ctypes.CDLL(path)
1358 self.loaded_libraries.add(path)
File ~/miniconda3/envs/tadl/lib/python3.10/ctypes/__init__.py:374, in CDLL.__init__(self, name, mode, handle, use_errno, use_last_error, winmode)
371 self._FuncPtr = _FuncPtr
373 if handle is None:
--> 374 self._handle = _dlopen(self._name, mode)
375 else:
376 self._handle = handle
OSError: /home/matthew/miniconda3/envs/tadl/bin/../lib/libstdc++.so.6: version `GLIBCXX_3.4.32' not found (required by /lib/x86_64-linux-gnu/libavfilter.so.9)It seems to be a C++ library version/linkage issue, with the library in my conda environment. I partially solved this error by using the answer from here, i.e., installing: although I this leads to a different GCC library error: I solved this one by linking my system $ ln -sf /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 ${CONDA_PREFIX}/libNow running: from torio.utils.ffmpeg_utils import get_audio_encoders
get_audio_encoders()works! I don't know how to do the same under Windows/for non-conda environment setups. |
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🐛 Describe the bug
torchaudionot detectingffmpeginstalled from theconda-forgechannel.Environment:
To reproduce, set up the following environment:
Code to reproduce:
Versions
PyTorch version: 2.2.1+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.2 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31
Python version: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:36:39) [GCC 10.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-130-generic-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration:
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000
GPU 2: NVIDIA RTX A6000
GPU 3: NVIDIA RTX A6000
GPU 4: NVIDIA RTX A6000
GPU 5: NVIDIA RTX A6000
GPU 6: NVIDIA RTX A6000
GPU 7: NVIDIA RTX A6000
Nvidia driver version: 535.183.01
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 43 bits physical, 48 bits virtual
CPU(s): 256
On-line CPU(s) list: 0-255
Thread(s) per core: 2
Core(s) per socket: 64
Socket(s): 2
NUMA node(s): 2
Vendor ID: AuthenticAMD
CPU family: 23
Model: 49
Model name: AMD EPYC 7662 64-Core Processor
Stepping: 0
Frequency boost: enabled
CPU MHz: 3295.616
CPU max MHz: 2154.2959
CPU min MHz: 1500.0000
BogoMIPS: 4000.00
Virtualization: AMD-V
L1d cache: 4 MiB
L1i cache: 4 MiB
L2 cache: 64 MiB
L3 cache: 512 MiB
NUMA node0 CPU(s): 0-63,128-191
NUMA node1 CPU(s): 64-127,192-255
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow: Mitigation; safe RET
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
Versions of relevant libraries:
[pip3] torch==2.2.1+cpu
[pip3] torchaudio==2.2.1+cpu
[conda] libopenvino-pytorch-frontend 2024.4.0 h5888daf_2 conda-forge
[conda] torch 2.2.1+cpu pypi_0 pypi
[conda] torchaudio 2.2.1+cpu pypi_0 pypi
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