It's useless on mac #129
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ok thanks |
请问是在mac里安装python3然后运行吗？谢谢 |
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I deploy it on my mac(Apple M1,8GB,Ventura 13.5),when i use it,it always run a while,then
`VALL-E EOS [413 -> 727]
libc++abi: terminating due to uncaught exception of type c10::Error: Unsupported type byte size: ComplexFloat
Exception raised from getGatherScatterScalarType at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/View.mm:758 (most recent call first):
frame #0: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::__1::basic_string<char, std::__1::char_traits, std::__1::allocator> const&) + 92 (0x16a4f92b8 in libc10.dylib)
frame #1: at::native::mps::getGatherScatterScalarType(at::Tensor const&) + 304 (0x28e923150 in libtorch_cpu.dylib)
frame #2: invocation function for block in at::native::mps::gatherViewTensor(at::Tensor const&, at::Tensor&) + 128 (0x28e924ca0 in libtorch_cpu.dylib)
frame #3: dispatch_client_callout + 20 (0x19acb4400 in libdispatch.dylib)
frame #4: dispatch_lane_barrier_sync_invoke_and_complete + 56 (0x19acc397c in libdispatch.dylib)
frame #5: at::native::mps::gatherViewTensor(at::Tensor const&, at::Tensor&) + 888 (0x28e923838 in libtorch_cpu.dylib)
frame #6: at::native::mps::mps_copy(at::Tensor&, at::Tensor const&, bool) + 3096 (0x28e87ab58 in libtorch_cpu.dylib)
frame #7: at::native::copy_impl(at::Tensor&, at::Tensor const&, bool) + 1944 (0x28a5f7604 in libtorch_cpu.dylib)
frame #8: at::native::copy(at::Tensor&, at::Tensor const&, bool) + 100 (0x28a5f6dac in libtorch_cpu.dylib)
frame #9: at::ops::copy::call(at::Tensor&, at::Tensor const&, bool) + 288 (0x28b32d718 in libtorch_cpu.dylib)
frame #10: at::native::clone(at::Tensor const&, c10::optionalc10::MemoryFormat) + 444 (0x28a981f84 in libtorch_cpu.dylib)
frame #11: at::_ops::clone::call(at::Tensor const&, c10::optionalc10::MemoryFormat) + 276 (0x28b03b0c4 in libtorch_cpu.dylib)
frame #12: at::_ops::contiguous::call(at::Tensor const&, c10::MemoryFormat) + 272 (0x28b45fa60 in libtorch_cpu.dylib)
frame #13: at::TensorBase::__dispatch_contiguous(c10::MemoryFormat) const + 40 (0x28a447130 in libtorch_cpu.dylib)
frame #14: at::native::mps::binaryOpTensor(at::Tensor const&, at::Tensor const&, c10::Scalar const&, at::Tensor const&, std::__1::basic_string<char, std::__1::char_traits, std::__1::allocator>, MPSGraphTensor* (at::native::mps::BinaryOpCachedGraph*, MPSGraphTensor*, MPSGraphTensor*) block_pointer) + 968 (0x28e863330 in libtorch_cpu.dylib)
frame #15: at::native::structured_mul_out_mps::impl(at::Tensor const&, at::Tensor const&, at::Tensor const&) + 128 (0x28e8673f0 in libtorch_cpu.dylib)
frame #16: at::(anonymous namespace)::wrapper_MPS_mul_Tensor(at::Tensor const&, at::Tensor const&) + 140 (0x28c003ea8 in libtorch_cpu.dylib)
frame #17: at::_ops::mul_Tensor::call(at::Tensor const&, at::Tensor const&) + 284 (0x28ae41898 in libtorch_cpu.dylib)
frame #18: torch::autograd::THPVariable_mul(_object*, _object*, _object*) + 396 (0x1781f82dc in libtorch_python.dylib)
frame #19: object* torch::autograd::TypeError_to_NotImplemented<&torch::autograd::THPVariable_mul(_object*, _object*, _object*)>(_object*, _object*, _object*) + 12 (0x178154330 in libtorch_python.dylib)
frame #20: method_vectorcall_VARARGS_KEYWORDS + 144 (0x104b77f88 in Python)
frame #21: vectorcall_maybe + 104 (0x104bd5824 in Python)
frame #22: slot_nb_multiply + 148 (0x104bd2588 in Python)
frame #23: binary_op1 + 228 (0x104b5021c in Python)
frame #24: PyNumber_Multiply + 36 (0x104b5082c in Python)
frame #25: _PyEval_EvalFrameDefault + 51104 (0x104c467d0 in Python)
frame #26: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #27: method_vectorcall + 164 (0x104b6e0c0 in Python)
frame #28: _PyEval_EvalFrameDefault + 48300 (0x104c45cdc in Python)
frame #29: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #30: _PyObject_FastCallDictTstate + 96 (0x104b6afe8 in Python)
frame #31: slot_tp_call + 180 (0x104bd076c in Python)
frame #32: _PyObject_MakeTpCall + 128 (0x104b6ad3c in Python)
frame #33: _PyEval_EvalFrameDefault + 40584 (0x104c43eb8 in Python)
frame #34: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #35: _PyVectorcall_Call + 152 (0x104b6b82c in Python)
frame #36: _PyEval_EvalFrameDefault + 48300 (0x104c45cdc in Python)
frame #37: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #38: _PyEval_EvalFrameDefault + 48300 (0x104c45cdc in Python)
frame #39: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #40: _PyEval_EvalFrameDefault + 48300 (0x104c45cdc in Python)
frame #41: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #42: _PyObject_VectorcallTstate.4608 + 88 (0x104c62a28 in Python)
frame #43: context_run + 92 (0x104c628e4 in Python)
frame #44: cfunction_vectorcall_FASTCALL_KEYWORDS + 76 (0x104bb3a00 in Python)
frame #45: _PyEval_EvalFrameDefault + 48300 (0x104c45cdc in Python)
frame #46: _PyEval_Vector + 116 (0x104c48564 in Python)
frame #47: method_vectorcall + 380 (0x104b6e198 in Python)
frame #48: thread_run + 168 (0x104cfaad4 in Python)
frame #49: pythread_wrapper + 48 (0x104c9c1cc in Python)
frame #50: _pthread_start + 148 (0x19ae63fa8 in libsystem_pthread.dylib)
frame #51: thread_start + 8 (0x19ae5eda0 in libsystem_pthread.dylib)
[1] 36424 abort python3 -X utf8 launch-ui.py`
IT EVEN USE ME 20GB RAM!!!!(zipped,i dont know what's that mean)
Optimize it,please.
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